Most link building advice assumes one website. One domain authority score. One backlink profile to grow. Plenty of excellent guides on this blog do the same. That works fine for a SaaS company or an online store. Now hand it to a plumber who covers six towns. Or a cleaning company working across three counties. Or an HVAC business with a service radius instead of a storefront.

The job here is different in kind. These businesses have to earn trust in five, ten, or twenty local markets at once. Apply a single-score playbook and the budget leaks out fast. Effort that would compound on one domain gets spread thin instead, across markets that each need their own signals. So they need a framework shaped like the real problem. Not a generic guide with a few local examples bolted on.

This guide lays out that framework. It starts from the geographic relevance shift documented in Whitespark’s annual ranking factors research. It then adds AI generated answers, which have become a second audience for the same signals. Everything below assumes “local” means a multi-city footprint or a service radius. Not a single address.

Why Standard Link Building Advice Under-Serves Local Businesses

Generic link building guidance optimizes for domain authority. Get links from high-DA sites. Prioritize dofollow. Chase editorial placements on recognizable publications. That is all correct advice for ranking one website in national or global search.

Local and multi-location businesses are judged on different signals. They are targeting the Local Pack. That is the three-listing map result sitting above organic results for any “near me” or city-qualified search. The Local Pack algorithm weighs signals that standard link building advice barely mentions.

The clearest evidence comes from Whitespark’s Local Search Ranking Factors survey. It is the most comprehensive ongoing study of local ranking signals. Whitespark compiles it every year from dozens of practicing local SEO specialists. The 2026 edition confirms a trend several years in the making. For Local Pack and Maps rankings, the geographic and topical relevance of a link now outweighs raw link volume or domain authority. One link from your city’s newspaper can beat dozens of generic placements. So can a link from your regional trade association, or a well known local blog. It does not matter that those generic placements sit on higher-DA sites.

That gives multi-location and service-area businesses their first principle. For local ranking, a mediocre-DA link with geographic and topical relevance beats a high-DA link with no connection to your market. Standard advice, tuned purely for DA, steers you toward the wrong targets. It helps to understand what a backlink actually is and how search engines evaluate it first. The geographic weighting sits on top of those fundamentals. It does not replace them.

Citations Are Splitting Into Two Jobs

Read anything about local SEO from the past two years and you will run into the claim that citations are dead. A Yellow Pages holdover Google stopped weighing years ago. There is some truth in that. But something bigger is happening to citations in 2026.

For traditional Local Pack ranking, the claim holds up. The direct ranking weight of citations has declined for years. Most modern ranking factor studies now put them well behind on-page signals, review signals, and geographically relevant backlinks. If citations were only a ranking play, dropping them would be defensible.

But 2026 gave citations a second job. AI answer engines now handle “who should I hire” questions directly. Google’s AI Overviews, ChatGPT and Perplexity all work this way. They answer in place, so the searcher never reaches a results page. These systems pull from structured, verifiable business data. Consistent name, address, phone, category and service information, repeated across trustworthy sources. That is the definition of a citation.

This is already reshaping the discipline. The structured data theme runs through every AI driven SEO shift, not just the local one. See how AI is changing SEO strategy across the board for that wider picture. On citations specifically, Google’s own Business Profile documentation is explicit. Complete, accurate, consistently structured business information feeds directly into how Google surfaces and describes a business. That is exactly the raw material an AI system uses to build a shortlist.

In practice, a business can hold a perfectly good backlink profile and still never appear in an AI answer. Its NAP data is thin or inconsistent across the sources those systems read. So a 2026 link strategy needs a citation layer. The old ranking argument for citations has weakened. The AI visibility argument replaced it, and that one keeps getting stronger.

The Multi-Location Complication: One Profile Per Territory

Here the framework splits from single-domain link building. A SaaS company builds one backlink profile for one domain. A business covering five service towns is building local relevance in five separate micro markets at once. One generic strategy, applied evenly across all five, loses to a strategy that treats each location as its own campaign.

This shows up constantly. Take a remodeling company with a strong reputation in one town. Deep community roots, a chamber membership, a sponsorship of the local youth sports league. Forty minutes away, in a second town it also serves, it has almost no footprint. One backlink strategy across both treats that strength as if it travels. It does not. Local relevance does not cross city lines the way domain authority crosses pages.

The fix is a per-territory link map. For each city the business genuinely wants to win, find two or three geographically relevant link opportunities in that specific town. This is slower than a blanket campaign. It is also the only approach that concentrates enough relevance in one place to move that town’s Local Pack. Blanket campaigns spread effort across a whole service area and end up owning none of it.

Where Multi-Location Businesses Should Actually Be Looking

Precision matters here. A generic “here is where to find links” list is exactly the trap this framework avoids. Every source below earns its place for a reason tied to the multi-location, citation-first problem.

Local press and community journalism matters more than most sources. Publication level geographic relevance is the strongest signal in the Whitespark data above. A link from a market’s own newspaper is about as geographically relevant as a link gets. It also reinforces the NAP consistency AI systems weigh. These placements come from being newsworthy locally. Sponsor an event. Join a community initiative. Be the local expert a reporter quotes.

Chambers of commerce and local business associations work for the same dual reason. The link sits on a page with strong topical and geographic relevance. Chamber directories are also structured, verifiable, third party listings, so they function as citations. That is what makes them matter for AI. The relationship then produces more: co-sponsored events, joint press mentions, cross promotion with other members. Each one adds another consistent NAP touchpoint.

Sponsorships of local teams, events and causes produce a sponsor page link with very tight geographic relevance. Businesses overlook this channel when they think of link building as a purely digital, outreach driven activity. For a local business it is a natural extension of community work it already does, or could start easily.

Trade and industry associations with a regional chapter combine both kinds of relevance in one placement. Topical from the trade, geographic from the chapter’s territory. These directories are structured and verifiable by nature. So they work as a link and a citation at once, the double duty this framework prioritizes.

Supplier, manufacturer and partner pages are a source most campaigns never think to ask for. For a multi-location business, each relationship across different service areas can produce its own geographically tagged listing. That is another per territory citation.

Each of these sources carries lower raw domain authority than a national publication. By the relevance principle above, each is still worth more for the Local Pack. Each is also more useful to an AI system building a shortlist. Want to check how much of your current profile already fits this pattern? Linkody’s guide to distinguishing strong backlinks from weak ones is a useful first filter.

Building the Citation Layer Correctly

A multi-location citation strategy has one non negotiable foundation. Absolute NAP consistency, across every location and every platform. It sounds simple. In real audits it is the most common failure point. A business with three service areas ends up with subtly different address formatting. Or an old phone number lingering on one directory. Or a name that reads slightly differently across platforms. None of it is intentional. All of it undermines the trust signal citations exist to build. Inconsistent NAP data is worse than none at all. It confuses the systems trying to verify the business is real, whether that is Google’s local algorithm or an AI engine.

So resist the temptation to build one “master” citation and let each location drift. Every location specific citation has to trace back to identical core data. That covers each directory listing, each Google Business Profile, each mention. One technique helps a lot here. The Google UULE parameter shows how your business appears in search as if you were standing in each service area. It makes an inconsistency in a satellite territory easy to catch, before it quietly costs you rankings there.

Aim for a solid base rather than volume. Start with consistent citations across the major general directories. Then add industry specific and locally relevant directories for each service area. Quality and consistency beat quantity by a wide margin. The same principle runs through white-hat link building tactics more broadly, where sustainable, relevant placements outlast volume driven ones.

Putting the Framework Together

Here is a practical sequence for a multi-location or service-area business.

Start with the NAP audit. Before chasing a single new link, verify consistency across every current citation and profile. New link building effort compounds an existing consistency problem faster than it compounds a solid foundation.

Map each service territory separately. List every city or area the business wants to rank in. Then find two or three geographically relevant link opportunities in each one.

Prioritize relevance over raw authority. Weigh geographic and topical relevance to the specific service area at least as heavily as domain authority. A locally relevant DA-25 link is often the better investment than a generic DA-60 link.

Treat the citation layer as infrastructure. It is a continuous operation. Business information changes. Directories drift. Each change has to propagate everywhere. So build re-verification into your recurring SEO calendar, alongside every other SEO KPI you track.

Track results by territory, not just in aggregate. Overall visibility can look healthy in blended reporting while individual territories quietly underperform.

Five Mistakes That Undermine Multi-Location Link Building

Even businesses that understand the framework trip on the same handful of execution mistakes.

Treating the metro area as the territory. Homeowners search “roofer in Ashburn”, not “roofer in the DMV”. A strategy built at the metro level spreads its relevance signals too thin to move any single town’s Local Pack.

Letting the newest location get the least attention. When a business expands, existing locations already hold citations and links. The new territory starts from zero. Over-weight new territory outreach for the first several months to correct that.

Chasing DA on directories that do not match the business category. A mid-DA directory built for the trade or the region carries more local relevance weight. It beats a generic top-100 business directory, even when the raw authority score favors the generic one.

Building citations once and never revisiting them. A citation audit is a recurring task. Revisit it any time core business information changes. Run a baseline check at least twice a year regardless.

Ignoring the review layer while building the link layer. A location with strong citations and a thin, aging review profile sends a mixed trust signal. The strongest multi-location strategies build the citation layer and the review system in parallel, not one after the other.

The Bigger Shift This Reflects

The businesses that handle this best will run link building and citation building as one local relevance strategy. That strategy serves two audiences. First, the traditional ranking algorithm, which still rewards geographically relevant backlinks. Second, the AI answer engines, which increasingly decide who gets recommended before a searcher sees a results page.

For a single location business, link building and citation building really can be separate disciplines with separate playbooks. For a multi-location or service-area business, they have merged. The businesses treating them that way build real, durable local visibility. One territory at a time.

None of this means abandoning what already works. Editorial outreach, digital PR and linkable assets still have a place. What changes is the priority order and the unit of analysis. A single domain business asks one question. Does this link help my site? A multi-location business asks three. Which territory does this help? Is that a territory I am actually trying to win? Does this placement double as a citation, or is it only a link? Asked consistently, those questions are most of the framework. The tactics are learnable. The discipline is what separates the businesses that quietly dominate their service areas. The rest are still wondering why a generic campaign never moved their map rankings.

About the Author

Steve Fleurant is the founder of Leads Akolytos. The Reston, VA agency does SEO exclusively for home service and construction businesses across the DC, Maryland and Virginia region.

The post Local Link Building for Multi-Location and Service-Area Businesses: A Citation-First Framework appeared first on Linkody's Blog.

Every SEO gets asked this question eventually. The client sees a line item for branded search in the Google Ads invoice, works out that people typing the company name were going to find the site anyway, and asks why anyone is paying for that.

It is a fair question. I have given the opinion answer plenty of times myself, usually some version of “competitors will take the click if you stop”, which sounds right and proves nothing.

I have spent 20 years in ecommerce marketing and audited more than 1,300 online stores, working both sides of this argument, and I can count on one hand the accounts where somebody had actually measured it. The rest had a position, usually inherited from whoever set the account up, and a slide in the monthly deck defending it. So here is the test rather than the opinion. What the research says, how to set the measurement up, how to run the pause without wrecking it, and how to read what comes back.

This Is Not the Cannibalisation You Already Know

The word is overloaded, so let us separate the two problems before we go further.

The version SEOs deal with weekly is keyword cannibalization, where two of your own pages chase the same query and split the signals between them. That is an internal, organic-only problem, and the fix is editorial. Consolidate, redirect, pick a winner.

Brand search cannibalisation is a different animal. Nothing on your site is competing with anything else. Your paid result is competing with your free one, on a query where you already own the intent, using money. The two pages of the argument sit in different departments and often in different companies, which is exactly why nobody resolves it.

There is a reason it stays unresolved. Brand terms have low cost per click, high click-through rate and a wonderful return on ad spend, so brand campaigns make the whole account look good. Nobody rushes to switch off the campaign that props up the average.

What the Research Actually Shows

Two pieces of evidence are worth knowing, because you will need them in the room when someone claims this is settled.

Google published a meta-analysis of 390 of its own search ads pause studies, looking at what happens to organic clicks when the ads stop. The headline that gets quoted, that around 89 percent of ad clicks are incremental, is not the number that matters here. The number that matters is the breakdown by organic rank. When the advertiser already held the top organic result, only 50 percent of the ad clicks were incremental. At ranks two to four it was 82 percent, and below rank four, 96 percent.

Read that again with brand queries in mind. On your own brand name you are almost always the top organic result. Google’s own research puts you in the bucket where half the ad clicks are clicks you had already earned.

The second piece is more brutal. Economists at eBay ran a large-scale field experiment, switching off paid search on some engines while keeping others as a control, and published it in Econometrica. For brand keywords they found substitution was close to complete, with natural search catching almost all of the forgone traffic and attributed sales. Their broader finding, that non-experimental estimates of paid search returns are wildly optimistic because clicks and purchase intent are correlated, is the part I would tattoo on every reporting dashboard.

Now the caveats, because I want you to use this honestly. Both studies are a decade old, on click and sales data rather than profit, and the SERP has changed enormously since, mostly in ways that push organic results further down the page. Neither tells you what happens in your account. They tell you the prior you should start from, which is that on brand terms a large share of what you pay for is a toll on traffic you already own, and that the only way to know your share is to run the experiment yourself.

Instrument the Question Before You Touch Anything

Skipping this stage is why most brand-pause tests produce an argument rather than an answer. Give it a fortnight before you pause a thing.

Define the brand query set, precisely. Open Search Console, go to the Performance report, and build a regex filter that catches the brand name, the common misspellings, the domain typed as a query, and the spaced and unspaced variants. Something in the shape of (brandname|brand name|brandnam|brandname\.com). Save it. Every number in this test depends on both platforms counting the same queries, and eyeballing “queries containing our name” will not do it.

Split brand into two buckets. Pure navigational queries, where somebody types the brand and nothing else, behave completely differently to brand plus modifier queries like “brand reviews”, “brand discount code”, “brand vs competitor” or “brand size guide”. You may own position one for the first bucket and sit fifth behind an affiliate roundup for the second. Those two buckets can honestly deserve opposite decisions, and averaging them together is how teams end up with a result that feels wrong to everyone.

Then go looking for every campaign that touches brand traffic, because this is where audits go sideways. Brand queries leak into Performance Max, Demand Gen, dynamic search ads and broad match non-brand campaigns, so pausing “the brand campaign” often pauses a fraction of the brand spend. Brand exclusions on Performance Max and Demand Gen are the control that actually holds. Add them, then verify with the search terms report a few days later rather than trusting the setting.

Seasonality is the next trap. Pull 13 months of brand query data so you can see the annual shape, then at minimum a stable 4 weeks immediately before the test, and mark every event that moves brand search on a calendar. Email sends, a TV or podcast spot, an influencer post, a product launch and a sale all spike branded queries. Run the pause across a promotion and you have not measured anything, you have just watched a busy fortnight.

Last, write down the numbers you will compare, in advance. Paid brand clicks and cost. Organic brand clicks and impressions. Organic CTR on the pure-brand query set. Branded revenue and orders. Total brand clicks, paid and organic added together, which is the number the whole test turns on. Deciding the metrics afterwards is how a null result quietly becomes a win.

Two extra checks before you go. Run Auction insights on the brand campaign to see who else is bidding on your name, because a competitor sitting above you changes the whole calculation. And note your mobile SERP, since a brand query with shopping ads, sitelinks and an AI answer above the fold is a different page to the one you see on desktop.

Running a Brand-Pause Test That Holds Up

There are two designs worth using, and the one you pick depends on how much traffic you have.

The cleaner design is a geographic holdout. Split your market into two comparable sets of regions, keep brand ads running in one and switch them off in the other, and compare the change between groups over the same weeks. Because both groups experience the same promotions, seasonality and algorithm updates, you get a genuine control. It needs enough brand volume in each region to see past the noise, which rules it out for smaller advertisers.

The fallback is a time-based on-off design. Two weeks off, two weeks on, repeated at least twice. Alternating cycles matter more than length here, because a single before-and-after comparison cannot separate the pause from whatever else happened that month. If you only ever run one two-week pause, be honest in the report that you measured a period, not an effect.

Whichever design you use, freeze everything else. No budget shifted into non-brand campaigns, no new landing pages on brand destinations, no changes to sitelinks or promotions, no rebrand, no big email push, no PR launch. If the marketing calendar cannot give you four undisturbed weeks, take the four weeks you can get and note the contamination rather than pretending it away.

Set a stopping rule before you start. Mine is simple. If a competitor’s impression share on brand queries rises materially mid-test, or organic brand clicks fall while total clicks fall with them, the test ends early and the ads go back on. You are running this to find out. If you catch yourself hoping for a particular result, that is worth noticing.

If organic brand clicks do slide mid-test, rule out the ordinary causes before you blame the pause. The usual method to investigate ranking drops using Google Search Console applies here unchanged, and a site-wide ranking problem that happened to land in your test window will otherwise be recorded as an advertising finding for the next two years.

Reading the Result

Here is the arithmetic, which is less complicated than the debate around it.

Take the paid brand clicks you gave up. Take the organic brand clicks you gained over the same window against baseline. The recovery rate is the second divided by the first. Whatever is left over is your incremental click count, the traffic that genuinely disappeared when the ads went dark.

Then price it. Divide the spend you saved by the incremental clicks lost, and you have what those clicks were really costing you, which is always dramatically higher than your reported brand cost per click. A brand campaign at 40 cents a click with a 70 percent recovery rate is not a 40 cent click. It is a dollar thirty-three for the clicks that were actually additional, and you should compare that against your non-brand cost per click before deciding it is cheap.

Now do the same on revenue, because clicks are not the deliverable. Compare branded revenue and order count, paid and organic combined, against baseline. This is where a lot of tests fall apart, since attribution moves traffic between channels when you pause ads, and last non-direct models will shuffle credit around without any real behaviour changing. Look at total branded revenue rather than channel-level revenue, and treat direct traffic as part of the brand bucket, because a chunk of it is brand search that lost its referrer.

A worked example with made-up round numbers, purely to show the shape of the calculation. Baseline month, 10,000 paid brand clicks at 40 cents, so $4,000 spend, plus 30,000 organic brand clicks. Pause month, zero paid clicks and 36,000 organic brand clicks. You recovered 6,000 of the 10,000, a 60 percent recovery rate, and lost 4,000 clicks that were genuinely incremental. That $4,000 was buying 4,000 additional clicks at a dollar each, not 10,000 clicks at 40 cents. Whether a dollar is a good price depends entirely on what those clicks are worth, which is why the revenue comparison matters more than the click comparison.

One statistical warning. Brand click volumes wander week to week on their own, and small accounts wander a lot. If your swing is inside about 10 percent and you have only run one cycle, you have measured noise. Run more cycles or accept that the honest answer is “we cannot tell at this volume”, which is still more useful than an invented one.

The Cases Where Paying for Your Own Brand Is Correct

I am not arguing for switching brand campaigns off. I am arguing for knowing. Several situations genuinely justify the toll, and a good test surfaces them rather than burying them.

Competitors bidding on your name is the obvious one. If Auction insights shows a rival appearing on half your brand impressions, your paid result is not buying a click you already had, it is denying a click to someone else. That value is real and it never shows up in a recovery-rate calculation, so judge it separately.

Weak organic ownership of the brand plus modifier bucket is the second, and it is far more common than people expect. Affiliate roundups, review aggregators, marketplace listings and resellers routinely outrank the brand itself on “brand reviews” and “brand discount code”. If you are not position one there, Google’s own rank breakdown says most of those ad clicks are incremental, and the ads are doing exactly what ads are supposed to do.

Paying is the short-term answer in that situation. The durable one is taking the query back, which usually means building the page that answers it and giving it the internal links and structured data to compete, across a catalogue rather than one URL at a time. That is bulk work, better suited to tooling than to anyone with a spreadsheet, and it is the sort of project that quietly retires an ad spend line twelve months later.

Then there is control of the message. A sale, a shipping cut-off, a recall, a rebrand, a stock shortage. The ad is the only element of that SERP you can change this afternoon, and during a period when the message matters more than the click economics, that alone can justify the spend.

Finally, watch the pure navigational bucket in accounts running heavy paid social or offline media. Those channels drive brand searches, and cutting brand ads during a big awareness push can hand the last click to a comparison site at the worst moment.

Reporting It Without Starting a War

The internal politics here are worse than the mathematics. The person running the ads account has a monthly efficiency target, and your test threatens the campaign with the best numbers in the deck. Approach it as a shared experiment, not an audit finding, or you will get compliance instead of cooperation and the test will quietly not happen.

Two things make it land. Give the paid team the incremental cost per click figure rather than a verdict, because it is a media-buying metric they can act on and it lets them make the call themselves. And commit in advance to reporting the result either way, including the outcome where the ads turn out to be pulling their weight and you were wrong.

In the report itself, keep the experiment log visible over time rather than burying the result in one month’s commentary. If you already maintain SEO reports for clients with a fixed structure, add a standing experiments section, since this is the kind of finding that gets forgotten and re-litigated every time a new marketing manager arrives. The same applies to the SEO KPIs and dashboards you already track. Total brand clicks, paid and organic combined, deserves a permanent tile, because it is the number that catches this problem and almost nobody plots it.

One more habit worth building. Recheck the answer annually, or after any rebrand, SERP layout shift or new competitor. This is a measurement with a shelf life, not a permanent policy.

Five Ways These Tests Get Botched

Most failed brand-pause tests fail the same handful of ways.

1. Pausing the brand campaign while Performance Max, Demand Gen or a broad match campaign keeps serving on brand queries. You measure a partial pause and conclude the ads did nothing.
2. Running the test across a promotion, a launch or a big email send, then attributing the branded traffic spike to the experiment.
3. Comparing paid clicks against organic sessions from two different tools with two different definitions of a brand query. Same definition, both platforms, or the numbers do not mean anything.
4. Measuring channel revenue rather than total branded revenue, so attribution reshuffling looks like a real change in customer behaviour.
5. Calling a single two-week window a result. Brand search moves on its own. One cycle tells you what happened, not what your ads do.

If you are already working through reasons your SEO is not working or the common SEO mistakes that quietly drain performance, add this one to the list. Not because paying for brand terms is always wrong. Because almost nobody knows which case they are in, and finding out costs a fortnight of discipline. Next time the question comes up in a meeting, it would be good to answer it with a figure out of your own account.

About the Author

Josh Uebergang is one of the most experienced SEOs in ecommerce. Over 20 years he has audited more than 1,300 online stores, recovered brands from traffic collapses most agencies walk away from, and built the SEO software thousands of merchants now run on their catalogues. He founded Digital Darts, the Shopify SEO agency the platform’s fastest-growing brands call when organic revenue has to move.

The post Brand Search Cannibalisation, How to Tell When Google Ads Is Stealing Your Organic Clicks appeared first on Linkody's Blog.

Most link building statistics posts say the same thing. They quote the same studies. They recycle numbers from 2019 and label them 2026.

We did something different. We went into Linkody’s own database.

Linkody monitors backlinks for a living. So we pulled the numbers from more than 865,000 real backlinks that our users actively track. Then we checked every finding against the best outside research we could verify.

This is what the data actually shows about backlinks in 2026. How they look. How they age. How many quietly die. And whether they still matter at all.

How we got these numbers. Linkody monitors millions of backlinks. For this study we used only the links where the data is clean and current. We left out competitor links (tracked for research, not owned), trial accounts, and churned users whose link status is frozen and out of date.

What remains is a sample of more than 865,000 backlinks across a broad range of websites and industries, each one checked continuously. Everything is aggregated and anonymized. Pulled June 2026. Outside data comes from more than 30 sources, each dated and linked.

Key Takeaways

• Only 56% of monitored backlinks are still live and correct.
• Half the links that die are gone within a year. Average lifespan is about 20 months.
• 77% of links are dofollow. Barely 1.6% use rel=sponsored or rel=ugc.
• 56% of anchors are keyword or phrase anchors. Just 18% are branded.
• Links from weak domains vanish fast. Two in three are already gone.
• Backlinks still sit inside Google’s ranking systems. But for AI search, brand mentions now matter more.

Do Backlinks Still Matter in 2026?

Ask Google and you get a mixed answer.

In 2023, Gary Illyes said backlinks are not a top three ranking factor (Search Engine Land, 2023). In 2024 he went further. We need very few links to rank a page, he told a conference (Search Engine Journal, Apr 2024). John Mueller has said their importance keeps fading.

So links are dead? Not so fast.

Two events tell a different story.

First, the 2024 Google API documentation leak. It exposed thousands of internal attributes. Several deal with links: source quality tiers, anchor spam signals, even a site authority feature Google had long denied (iPullRank, May 2024). We cannot see how much weight each one carries. The analysts who found them said the same. But the fields are real.

Second, the US antitrust trial. Under oath, Google staff described PageRank as a live signal that still feeds page quality. Anchors and clicks sit in the core too. This is sworn testimony, not a leak. It is the strongest confirmation we have.

Here is the honest read. Google plays down link volume in public. Its own systems still run on links. Both things are true at once.

What changed is the bar. Volume is out. Quality, relevance, and a clean link profile are in. That is the thread running through every number below.

The old correlation studies still get quoted. Backlinko found the top result has 3.8 times more backlinks than the rest. That data is from 2020, so treat it as a long standing baseline, not fresh proof.

The Anatomy of a Backlink

Before we ask whether links last or rank, look at what they actually are.

Most backlinks still pass authority. In our sample, 77% are dofollow. The other 23% are nofollow. So the classic dofollow link is far from dead.

The surprise is what is missing. Google launched rel=sponsored and rel=ugc back in 2019. They were meant to label paid links and links inside user content. Years later, almost nobody uses them. Just 1.4% of our links carry rel=ugc. Only 0.25% use rel=sponsored.

Read that again. After more than six years, fewer than 2 in 100 links use the tags Google asked for.

Type tells a similar story. The web still runs on text. 96% of backlinks are plain text links. Only about 4% are images.

The takeaway is simple. The backlink has barely changed shape. A text anchor with a dofollow tag is still the default unit of link building.

Anchor Text in the Wild

Anchor text is where link building gets risky. Use the right words and you help readers. Lean too hard on your keywords and you wave a flag at Google.

So what do real anchors look like? We sorted our sample into types.

• Keyword or phrase anchors: 56%
• Branded anchors: 18%
• Naked URLs: 15%
• Empty or image links: 10%
• Generic text like “click here”: 1%

One number stands out. 56% of anchors are keyword or phrase anchors. That is high.

A natural profile usually leans the other way. Practitioner guides put branded anchors around 40% to 60% and keep exact match anchors low, often under 10% (FATJOE, 2026). Our sample flips that. Branded sits at just 18%.

Why the gap? Because these are monitored links. People watch the links they worked to get. Built links carry more keywords than links earned by chance.

We will be honest about one limit. Our keyword bucket mixes exact match and partial match. We cannot split them cleanly. So read 56% as keyword leaning, not 56% exact match.

Still, the signal is clear. The links SEOs track are more keyword heavy than a natural profile. That is the kind of pattern Google has demoted since the Penguin update in 2012 (GSQI).

Only 56% of Backlinks Are Still Live

Now the finding that should change how you work. Most backlinks do not stay healthy.

In our sample, only 56% of monitored backlinks are still live and correct. The rest have a problem.

• Live and correct: 56%
• Removed, page still up: 17%
• Page returns an error: 14%
• Crawl error: 13%
• Anchor or rel changed: under 1%

Two failures dominate. Either the page dies, or the link gets pulled while the page lives on. Together that is almost a third of all links, broken or gone.

We are being careful here. The crawl errors, about 13%, are murky. Some are dead links. Some are just our crawler getting blocked or timing out. So we count only removed links and dead pages as confirmed losses. That floor is 31%.

The honest headline: roughly 1 in 3 backlinks you built is no longer the link you think it is. And you would never know without checking.

How Long Backlinks Last

If links break, the next question is when. So we tracked the moment each link first went bad. We know the date a link was added and the date it failed. The gap is its lifespan.

The pattern is harsh. Links die young.

Of the links that died:

• 21% were gone within 3 months
• 34% within 6 months
• 52% within a year

Half of all dying links do not survive twelve months. The average lifespan to death is about 20 months.

Flip it to survival and the story holds. Group links by how long we have watched them:

• After 3 months, 89% are still live
• After a year, around 63%
• After 2 to 5 years, 46%
• After 5 years or more, just 31%

A backlink is not a monument. It has a shelf life.

This lines up with the largest outside study. Ahrefs looked at more than 2 million sites and found about half of all links are lost within seven years, with the heaviest losses early (Ahrefs, 2024). Our curve sits right inside theirs. The difference is we can show it month by month.

One caveat. Our clock starts when a link enters Linkody, not when it was first published. And we count only confirmed deaths. So real decay runs a little higher, not lower.

Why the Average Describes Almost Nobody

Added August 2026.

Every number above treats links as one big pile. We went back and grouped them by account instead. The picture changed.

Take every account that added at least 30 links in 2025. That is 139 accounts and 234,138 links. Pool them together and 14.3% of those links have since been removed.

Now look at the accounts one at a time. The median account lost 1.8%.

The average is nearly eight times the typical experience. Here is how the 139 accounts actually split:

• 73% of accounts lost less than 10% of their links
• 10% of accounts lost more than 70%
• 17% sat anywhere in between

Loss clusters at the two ends. Most people barely lose anything. A small group loses almost everything. The steady middling decay that an average implies is the rarest outcome of the three.

We tested it four ways before believing it.

The split holds whether we count accounts with 10 links or 100. It holds in every year from 2021 to 2025, with 80% to 86% of accounts at the extremes each time. It holds for accounts that show up in only one year, so it is not a handful of heavy users repeating.

And the big losses are not one website going down. We checked the linking domains. One account lost 1,695 links spread across 1,695 separate domains. Across the whole losing group, the single worst domain accounted for between 0.1% and 12% of what they lost. These are broad losses, not one publisher clearing house.

So what separates the two groups?

The obvious answer is that they bought from different places. One person’s supplier keeps its sites up for years. Another’s sells placements that get cleared out in months. That would produce exactly this split.

We cannot prove it, and it is worth being straight about why. We record where a link is, not who sold it. There is no supplier field in our data, so we cannot line one vendor up against another.

What it means in practice: budget from your own live rate, not from an industry average, and track that rate per supplier if you buy links. If you are in the safe group, replacement planning built on a 14% figure will have you buying links you do not need. If you are in the losing group, you already have a bigger problem than a budget line.

Authority and Survival: Quality Pays

Not all links rot at the same rate. Authority is the difference.

We grouped links by the domain authority of the site they sit on (Moz DA). Then we checked how many were still live.

• Sites under DA 10: only 33% of links still live
• DA 30 to 49: about 70% still live

Links on weak domains vanish. Two out of three are already gone. Links on mid authority sites last more than twice as well.

It makes sense. Low authority domains are often thin, cheap, or short lived. They get abandoned. The page disappears, and your link with it.

Dofollow rates follow the same logic, with a twist. The share of dofollow links climbs as authority rises, from 63% on weak sites to nearly 90% in the mid range. Then it dips at the very top. The DA 70 and above group is back near 72% dofollow.

Why? The biggest sites are news outlets, universities, and government pages. They link out carefully, and they nofollow more often. So the most valuable links are also the hardest to win as dofollow.

The lesson runs through the whole study. A link from a strong, relevant site is worth chasing. It ranks better, and it lasts. A link from a weak site may be gone before it ever helped.

The Risk Side: Bad Links Now Fail Quietly

Link building has a dark side. Paid links, link networks, spammy anchors. The old fear was a penalty. A manual action in Search Console, a visible drop, a painful cleanup.

That fear is outdated. The risk today is quieter.

Since 2022, Google’s SpamBrain system does not just catch bought links. It neutralizes them. The links simply stop passing value (Google, Dec 2022). No warning. No message. The link still sits on the page, doing nothing.

Google kept tightening this through 2024 and 2025. More sites lost rankings with no manual action shown at all (iMark, 2025).

So the math on paid links has changed. You can still pay. You just cannot count on the link to work. And nobody tells you when it stops.

This is where monitoring earns its keep. If a link turns nofollow, drops off the page, or lands on a dead site, you want to know. Otherwise you are paying for ghosts.

What about disavow, the old cleanup tool? Our data says most people have moved on. Only about 9% of active sites in our sample have a single disavow rule. And when people do disavow, they swing hard. 80% of disavow rules target a whole domain, not one URL. It is a blunt instrument, used rarely.

One more pattern. About 1 in 10 of the links we monitor has a cost attached. Plenty of SEOs still pay for links, and they track the spend.

Links in the AI Search Era

Search is not just ten blue links anymore. People ask ChatGPT, Perplexity, and Google’s AI Overviews. So a fair question: do backlinks even matter for AI answers?

The data says yes, but less than you think. And something else matters more.

Ahrefs studied 75,000 brands and what drives visibility in AI Overviews. Backlinks showed only a weak tie, a correlation of 0.22. Brand mentions across the web showed a much stronger one, 0.66 (Ahrefs, May 2025). In plain terms, being talked about beats being linked to.

Other work points the same way. SALT.agency tested several AI engines and found backlinks correlate only moderately with AI visibility, around 0.39 to 0.42 (SALT.agency, Dec 2025). Useful, but not the whole game.

The ground is shifting fast too. In mid 2025, about 76% of AI Overview citations came from pages in the top ten results. By 2026 that had fallen to 38% (Ahrefs). AI engines are reaching past the first page for sources.

A caveat we owe you. These are correlations, not proof of cause. And the two AI Overview studies used different methods, so treat the drop as a direction, not an exact figure.

Here is the read. Links still help AI engines find and trust you. But mentions, citations, and a known brand now carry more weight. To track where your brand shows up in AI answers, we wrote a full guide to AI citation tracking.

How People Actually Build Links in 2026

So where do links come from now? The outside surveys are clear, and they disagree in an interesting way.

Digital PR is the tactic pros rate most effective. In a 2026 survey of 518 professionals, 48.6% named it the top performer. Guest posting trailed at 16% (Editorial.link, Mar 2026).

But effective and popular are not the same. Guest posting is still the most used tactic by far. People do what they know, even when they rate something else higher.

On timing, link building is faster than its reputation. 57% of pros expect results within one to three months (Editorial.link, Mar 2026).

Pricing is where it gets sobering. A 2026 analysis of a large vendor database put guest posts around $300 to $460 each, and digital PR links at $1,250 to $1,500. Worse, only 1.37% of vendor sites met a basic quality bar of real authority and traffic (BuzzStream, Jun 2026).

Read that last number twice. Fewer than 2 in 100 sites selling links are worth buying from. Which brings us back to the theme of this whole study. Quality is rare, and quality is what lasts.

Link Building in 2026, by the Numbers

If you remember nothing else, remember these.

Frequently Asked Questions

Do backlinks still matter in 2026?

Yes. Google plays down their weight in public. But sworn antitrust testimony and the 2024 API leak both show links, anchors, and PageRank still sit inside the ranking systems. Volume matters less. Quality and relevance matter more.

How long does a backlink last?

Not as long as you would hope. In our data, half of the links that die are gone within a year. After five years, only about 31% are still live and correct.

What share of backlinks are dofollow?

About 77% in our sample. Roughly 23% are nofollow. The rel=sponsored and rel=ugc tags stay rare, on under 2% of links.

Are nofollow links worth anything?

Yes. They send traffic, build brand, and look natural in a profile. And for AI search, mentions may matter more than the link type at all.

How much do backlinks cost?

External 2026 data puts guest posts around $300 to $460, and digital PR links above $1,200. But quality is rare. Fewer than 2 in 100 vendor sites meet a basic quality bar.

Should I still disavow links?

Usually no. Google now neutralizes most bad links on its own. In our data, only about 9% of active sites disavow at all. Save it for clear cases of paid or spammy links you control.

What This Means for Your Links

Put it all together and a clear message appears.

Link building is no longer just building. It is keeping.

You can earn a great link today and lose it within a year. Almost half of monitored links are already broken, removed, or pointing at dead pages. The web does not hold still.

So the winning approach in 2026 looks like this. Chase fewer, stronger links. Favor relevant, high authority sites, because those links last and carry weight. Watch your anchors, so your profile does not drift into keyword heavy territory. And check your links often, because the ones you cannot see failing are the ones quietly costing you.

That last part is the whole reason this data exists. Linkody monitors backlinks so you find out the moment one breaks, drops, or turns nofollow. You built those links. It is worth knowing they are still there.

So here is the real question. When did you last check your backlinks?

The post Link Building Statistics 2026: What 865,000 Monitored Backlinks Reveal appeared first on Linkody's Blog.

Search used to be simple. Someone typed a query. Google showed ten blue links. You fought to reach the top of page one.

That world is fading fast. People now ask ChatGPT for product picks. They ask Perplexity to run their research. They read Google’s AI Overview and never scroll. The answer shows up before the click does.

This is not a hunch. Gartner expects traditional search volume to fall 25% by 2026 as people lean on AI chatbots and answer engines. The shift is already underway.

Here is the catch. You can rank well in organic search and still be missing from these AI answers. The reverse happens too. An AI engine might quote your article while you sit nowhere near the top of the results page.

So how do you know if any of this is working for you? You measure it.

This guide is about AI citation tracking. You will learn what a citation is, why it matters in 2026, how the engines pick their sources, and how to watch your own presence across ChatGPT, Perplexity, and Google AI Overviews. Let’s dig in.

What Is an AI Citation, Exactly?

An AI citation is any moment an AI answer points to you. It might name your brand. It might link to your page. It might repeat a fact you published without crediting you at all.

There are three common types, and each one counts.

• Linked citations. The engine names your page and links to it. This is the clearest win.
• Brand mentions. The answer names your company but does not link out. Still useful, because the reader now knows you exist.
• Uncredited pulls. The model leans on your data or phrasing with no mention. These are harder to spot, yet they still shape the answer.

Classic SEO trained us to chase the linked version. AI search forces you to care about all three. A mention with no link can still send a buyer your way.

Why AI Citation Tracking Matters Now

You might be thinking this is a problem for later. It is not. Here are three reasons to start today.

1. Clicks keep drying up

Zero click searches were already common. SparkToro’s 2024 study found that roughly 58.5% of United States Google searches end with no click at all. AI answers are speeding that up. Pew Research Center studied this in 2025. When an AI summary appeared, people clicked a traditional result just 8% of the time, against 15% when no summary showed. That is close to half the clicks, gone. We unpacked the wider shift in our guide to zero click searches. Citations are becoming the new visibility.

2. Visibility no longer equals ranking

The old rule was simple. Rank high, get seen. The new rule is different. Get cited, get seen. You can be quoted in an AI Overview without holding the top organic spot. You can also rank first and never appear in the answer. Rankings and citations are two separate scoreboards now.

3. Your competitors are already in the answers

Every day you do not measure, a rival might be the default source for questions in your niche. If you cannot see it, you cannot respond. Tracking turns a blind spot into a plan.

The takeaway is blunt. AI search is not a someday concern. It is shaping real buying decisions right now, inside answers you never see unless you go looking for them. Tracking is how you stop guessing and start steering. It is also how you catch a problem while it is still small.

How AI Engines Decide Who Gets Cited

Before you track citations, it helps to know what earns them. The engines are not guessing. They lean on a short list of signals.

• Relevance. Does your page answer the exact question? Vague content gets skipped.
• Authority. A strong backlink profile still signals trust. The same links that help you rank help you get cited.
• Brand popularity. Analysts like Kevin Indig argue popularity is one of the biggest citation factors. Brands that show up everywhere get pulled more often.
• Structure. Clear headings, direct answers, and clean formatting make your content easy to lift.
• Freshness. Current pages beat stale ones, especially on fast moving topics.
• Source quality. Pointing to credible references makes your own page look more trustworthy.

Notice the overlap with classic SEO. Many of these signals are the same ones that lift your outbound links score and your rankings. The same idea sits at the heart of generative engine optimization. AI search did not throw out the rulebook. It added new chapters.

How the Major AI Engines Handle Citations

Not every engine cites the same way. Knowing the quirks helps you read your tracking data.

ChatGPT

ChatGPT pulls from its training and, with browsing on, from live results. When it browses, it often lists linked sources beside the answer. Brands with real authority and clear pages tend to surface. Without browsing, you may get a mention with no link, so watch for both.

Perplexity

Perplexity is built around citations. Almost every answer shows numbered sources right in the text. That makes it the easiest engine to track. It is also a great place to test which of your pages earn a spot.

Google AI Overviews

AI Overviews sit on top of the familiar results page. They blend a generated summary with a few linked sources. Ranking well still helps your odds. It is not a guarantee, though. Plenty of strong pages never make the summary. Pew Research found that 58% of United States users ran at least one search with an AI summary in March 2025. These are common now, not a novelty.

Gemini and AI Mode

Gemini and the newer AI Mode push further toward full answers. AI Mode can replace the blue links entirely. That raises the stakes. If the answer is the whole page, a citation is the only way in.

How to Track Your AI Citations Step by Step

Now the practical part. You do not need an enterprise budget to start. You need a process. Here is one you can run this week.

Keep it lightweight at first. A simple spreadsheet does the job. One column for the prompt. One column for each engine. One column for who got cited. You are hunting for patterns, not perfection. The habit matters more than the tooling on day one.

1. Run a manual audit first

Open ChatGPT, Perplexity, and Google AI Overviews. Ask the questions your customers ask. Note who gets cited. Note whether you appear at all. This rough snapshot becomes your baseline.

2. Build a prompt list

Guessing once is not tracking. Write a fixed list of prompts and reuse it every time. Include branded prompts, like questions about your company. Include unbranded prompts, like the problems your product solves. The unbranded ones matter most, since that is where new buyers find you.

3. Map who else gets cited

For each prompt, log every source the engine names. Patterns appear fast. Maybe one competitor owns a topic. Maybe a forum keeps surfacing. This is your share of voice inside AI answers, and it shows you where to push.

4. Watch for AI referral traffic

Open your analytics. Look for visits coming from ChatGPT, Perplexity, and other AI tools. The numbers are often small today. The trend line is the point. Rising AI referrals mean your citations are turning into clicks.

5. Track which pages get pulled

When you do earn a citation, note the exact page. Over time you will see which formats win. Maybe your data studies get quoted while your opinion pieces get ignored. Double down on what the engines like.

6. Use a dedicated AI visibility tool

Manual checks do not scale. Once you outgrow the spreadsheet, a tool helps. A handful of dedicated AI visibility platforms now run prompts at scale and report where your brand is and is not getting cited across engines. They flag pages losing ground to rivals in AI answers, so you can act before the gap widens. Try a few and pick the one that fits your stack.

7. Connect it back to your backlinks

Authority feeds citations. Your backlink profile is one of the clearest authority signals an engine can read. Keep monitoring your links, prune the toxic ones, and chase quality placements. A backlink monitor like Linkody keeps that data in one place, which supports both your rankings and your odds of being cited.

Here is what that looks like in practice. Say you sell project management software. You ask, what is the best tool for small agencies. ChatGPT names three rivals and skips you. Perplexity lists you fourth with a link. AI Overviews ignores the topic entirely. Now you know where you stand. You also know which engine to fix first.

The Metrics That Actually Matter

Tracking produces noise. Focus on a few numbers that mean something.

• Presence rate. Out of your prompt list, how often do you appear at all?
• Share of voice. Of every cited source, what slice belongs to you versus your rivals?
• Sentiment and context. Are you named as the recommended option or buried as a footnote?
• Source overlap. Which domains the engines trust for your topics. Those are your outreach and link building targets.
• AI referral traffic. The real clicks your citations send back to you.

Review these monthly. A single snapshot can lie. A trend tells you the truth.

How Often Should You Check?

There is no single right cadence. A monthly cycle works for most teams. Run your full prompt list once a month, log the results, and compare against last time. In a fast moving niche, go every two weeks. The point is a steady rhythm, not a one time look. AI answers drift, so a habit beats a heroic audit you never repeat.

Mistakes to Avoid When You Track AI Visibility

• Checking once. AI answers shift between sessions and model updates. Sample on a schedule.
• Only tracking your brand name. The unbranded prompts are where growth hides.
• Ignoring the sources you keep losing to. Their content and backlinks are your roadmap.
• Treating AI search as separate from SEO. It is not. It runs on the same foundation.

How to Earn More Citations Once You Are Tracking

Tracking shows the gap. Closing it looks a lot like good SEO with sharper aim.

• Publish original data. Surveys, studies, and first hand numbers get cited because nobody else has them. Our guide to linkable assets is a good place to begin.
• Refresh aging pages. Stale content slips out of AI answers, so a regular content refresh keeps you in the running.
• Earn quality backlinks. Authority is currency in both rankings and citations.
• Link out to trusted sources. It signals care and gives the reader context.
• Write for extraction. Short answers, clear headings, and clean lists are easy for a model to quote.

One more thing. Consistency compounds. A single data study might earn a burst of citations. A steady stream of useful, current pages earns a place the engines keep coming back to. Treat citation worthiness as a habit, the same way you treat publishing. The brands that win here are rarely the loudest. They are the most reliable.

Is AI Citation Tracking Just SEO With Extra Steps?

Fair question. The honest answer is no, though they are close cousins.

SEO chases rankings. AI citation work chases mentions inside the answer itself. The tactics overlap, yet the goal moves. You are no longer only fighting for a position on the page. You are fighting to be the source the model trusts.

Think of it as an evolution, not a replacement. Neglect SEO and your authority fades, so your citations fade with it. Ignore AI search and you hand the answer box to whoever bothered to show up. The smart play is to run both as one motion. Our take on large language model optimization goes deeper on that mindset.

Start Measuring Before You Optimize

You cannot improve what you cannot see. AI citation tracking gives you that view. Start small. Run a manual audit, build your prompt list, log who gets cited, and watch your AI referrals climb.

Then feed the loop. Strengthen your backlinks, refresh your best content, and publish things worth quoting. Keep an eye on the numbers so your authority keeps pace with the answers.

Do not wait for perfect tools or a tidy playbook. The teams winning AI visibility today started by simply looking. They asked the questions, wrote down the answers, and acted on what they saw. You can do the same this afternoon.

Search is shifting from links to answers. The brands that measure their place in those answers will own the next few years. So, ready to find out where you stand?

The post How to Track Your Brand’s Citations in AI Search (ChatGPT, Perplexity, and AI Overviews) appeared first on Linkody's Blog.

Anything labeled as organic eventually decays – veggies, fruits … even your blog posts.

That tutorial you published two years ago? Half the steps no longer work. Those software roundups? Some of the tools don’t even exist anymore.

And don’t get me started on your “latest trends” piece that’s still quoting stats from 2019 like they’re breaking news.

If you don’t bother to refresh your content, why should anyone bother to read it?

The truth is, even your best-performing content needs regular maintenance to stay relevant, rank well, and continue bringing in traffic.

We’ve talked to several experts and business leaders in the SEO industry to understand exactly what it takes to remain competitive in both traditional and AI-driven search. 

Keep reading to learn their content refresh strategies.

Why Refreshing Content Matters for SEO?

All successful blogs have one thing in common: they understand that updating old content is equally important to creating a new one.

Take Zapier, for example. They regularly update their “best apps” roundups to reflect what’s actually best right now. 

Better tools are added. Outdated ones get removed.

This one post about project management software was first published in 2017, and has been updated every year since.

Image source: Zapier

The result? It continues to rack up tens of thousands of visits almost a decade later.

Oriel Partners, a boutique recruitment agency, also experienced a spike in performance after updating one of its blog posts about working in Saudi Arabia.

The article reached the number one position for 23 keywords and secured AI Overview mentions for 17 keywords.

From these examples, one thing is clear: content refreshes are a powerful strategy to maintain and even improve SEO performance.

Let’s break down why that’s the case.

Users want up-to-date information

When people search for answers online, they’re looking for the most accurate, relevant, and current information available. 

There’s a reason why, for certain queries, Google shows the publication date or last update date in search results.

No one wants to read about “the latest marketing trends” from an article written in 2020.

It’s frustrating – and it damages trust. If your content is outdated, users will find a fresher alternative, and likely will never come back to your site.

Google prefers fresh content 

Content freshness is a known ranking factor. Especially for queries where information changes quickly, like news, trends, and stats. 

There’s even a term for it: Query Deserves Freshness (QDF). Basically, the more time-sensitive the topic, the more weight Google places on recency. 

Image source: Google

By updating your content regularly, you’re giving Google a reason to keep showing your page in search results. 

And now with AI Overviews (AIO) rolling out, that freshness can help your content get picked up there too.

A study by Seer Interactive confirmed that AI Overviews strongly favor newer content. In fact, 85% of sources in AIO are published in the last two years:

• 44% are from 2025
• 30% are from 2024
• 11% are from 2023 

LLMs have recency bias

It’s not just Google’s AI Overviews that crave fresh content. Large language models (LLMs) also have recency bias.

According to the same Seer Interactive study, 50% of Perplexity’s citations are content published in 2025 alone. 

That’s even higher than AIO!

Image source: Seer Interactive

Interestingly, ChatGPT shows a milder recency bias compared to Perplexity and AIO. But that completely makes sense, if the recent GPT-4o system prompt leak is true.

According to the leaked material, ChatGPT doesn’t browse the web by default – only when explicitly asked or when absolutely necessary. Most of the time, it relies on its training data, which is why you’ll often see sources from 2022 or earlier.

Still, when ChatGPT does pull in fresh data, it tends to favor pages that are recently published or updated. Around 70% of its citations come from content published in the past two years.

The takeaway? If your content is outdated, it’s less likely to be cited in AI-generated responses.

Existing content is easier to rank than new content

It’s easier, cheaper, and faster to fix a broken computer than to build the whole thing entirely from scratch.

The same logic can be applied to SEO.

Moving a post from position 10 to 1 takes significantly less effort and gives you a higher return than trying to rank a brand new URL from position 100 to 10.

Patrick Stox shared an eye-opening stat in a recent Ahrefs study: only 1.74% of new pages made it into Google’s top 10 within a year.

Image source: Ahrefs

Even when you filter for English URLs with actual content, that number only climbs to 6.11%. Most new pages never make it to the first page.

The truth? It’s becoming much harder to rank new content. Sometimes, updating what you already have is your best chance. 

How to Find Potential Content to Refresh

The most critical part of any refresh is figuring out what’s actually worth refreshing. 

And it starts with a comprehensive content audit, which helps you understand how your existing content is performing and where it’s falling short.

Patrick Langride, the SEO Director at Screaming Frog, shared this:

“I think the most important step in a content refresh is the very first one – undertaking a thorough and robust content audit. It’s critical to understand how your content is currently performing before making any drastic decisions around re-writing content, otherwise you risk doing more harm than good and you might damage important rankings as a result.”

Begin by using crawling tools like Screaming Frog or Sitebulb to gather all your content assets, including blog posts, case studies, and product pages.

Once you have the complete data, look for content with the highest potential. The kind of pages that could bounce back with just a few strategic updates.

Here are some of the examples.

High-performing pages on a decline

Have a blog post that performed so well in the past, but is now slipping in rankings? That’s a great place to start.

Rather than starting from scratch, Benjamin Rojas (the President of AIOSEO) suggests focusing your efforts on proven performers:

“Start with your highest-performing articles — the ones that have already done what you wanted them to do (bring traffic, get email sign-ups, generate sales, etc.). These content pieces have already proven to work, so updating them gives you the biggest return on your effort.”

You can use Google Search Console (GSC) to spot pages with declining performance:

1. Log in to your GSC dashboard and head to the Performance tab.
2. Choose a date range for your performance comparison (e.g. compare last 3 months to the previous period).
3. Scroll down to Pages to see which pages are dropping in impressions, clicks, average position, and click-through rate (CTR) over time.

If you want to learn more, check out this in-depth guide on how to investigate ranking drops in Google Search Console.

Pages that are losing clicks to AI Overviews

If you notice that some pages have high impressions but low clicks, they probably fall victim to AI Overviews. In fact, a recent Ahrefs study confirmed that AI Overviews reduce clicks by up to 34.5%.

This is especially true for informational blog posts. If your content answers common “how to,” “what is,” or “why” questions, chances are it’s competing directly with AI-generated summaries.

So how can you tell if AI Overviews are hurting your traffic? Here’s a simple way to investigate:

1. Open the Performance tab in your Google Search Console.
2. Set your preferred comparison date range and sort by Average CTR.
3. Navigate to Pages and look for pages with a lower CTR compared to the previous period. These are your likely victims.

If you find a way to get those pages included in AI Overviews, you might reclaim some of those lost visits.

Pages with a solid backlink profile

Backlinks are a sign of trust and credibility, especially if they come from authoritative sources. So, if you’ve got a page with tons of high-quality backlinks pointing to it, don’t let that equity go to waste.

Even if the content isn’t driving much traffic right now, it might just need a refresh to start pulling its weight again.

You can use a tool like Linkody to analyze the backlink profile of each page on your site. Simply sign up and enter your domain name. Once you’ve gained access to your dashboard, click the Landing Pages tab from the left sidebar.

You’ll see a list of all indexed pages on your site – along with how many backlinks each one has. If you want to assess the quality of those links, simply click on any number next to the URLs.

5 Ways to Refresh Your Content

Once you’ve got the full list of content pieces to refresh, then it’s all about making the right updates. You don’t always need to rewrite the whole thing. Sometimes, little tweaks can make a big impact.

Here are some low-hanging fruit tactics to refresh your content, in no particular order.

1. Match current user intent 

The first thing you have to do is make sure your content is still relevant to what people actually want.

Look at the top-ranking results for your target keyword. Are they listicles now? More in-depth guides? Do they target a slightly different angle? Your content should reflect what users want today, not what they wanted when you first hit publish.

In fact, this is the exact strategy SE Ranking used when refreshing their content:

“A crucial aspect we consider is re-optimizing our content for search intent. This ensures that our content is always in line with what our audience is searching for, enhancing their experience and keeping our SEO game strong,” said Irina Weber, Content Strategist at SE Ranking.

Here are some tips to match search intent better:

• Match the format of top-ranking pages: Look at the search engine results pages (SERPs) for your keyword, and determine whether an in-depth guide or a short landing page would be more suitable for the topic.
• Give users what they want immediately: If someone is searching for “best project management tools,” they probably want a quick comparison table – not a 1,000-word essay on what is project management. Get to the point fast.
• Optimize the headings: Make sure your title and headers reflect what users are typing into Google. Subtle wording changes can make a big difference.
• Answer real user questions: Dive into Reddit threads, Quora, and “People Also Ask” boxes to find the actual questions people are asking. Then answer them clearly in your content and FAQ section. This can help you show up in AI Overviews too.

2. Reverse engineer your competitor’s strategy

The top-ranking pages are there for a reason. Instead of guessing what works, reverse engineer their approach and use it to your advantage.

Use tools like Ahrefs, SurferSEO, or even a manual SERP review to analyze your competitors.

Focus on:

• Page structure: How is their content laid out? Are they using tables, comparison charts, jump links, or FAQs? Look for formatting patterns that improve readability and engagement.
• Content gaps: Are they covering subtopics, questions, or examples you’ve missed? Maybe they go deeper into a specific section or include case studies and stats that your content lacks.
• Missed keyword opportunities: Your competitors may be ranking for long-term queries you haven’t considered. Find out what those keywords are, weave them naturally into your content, and you might unlock new ranking opportunities.

You can also use Linkody’s free backlink checker to see which domains are linking to your competitors. 

The reason is simple: those sites might be willing to link to your page as well, especially if your content is fresher and better.

3. Enhance the content value

When reviewing your existing content, think of ways you can add more value for your readers.

Answer their questions. Give solutions to their problems. Satisfy their needs to the point where they don’t feel the need to go back to Google.

That’s the benchmark you should always aim for every piece of content.

Ivan Palii, Head of Product at Sitechecker, says it’s about adding what’s useful and removing what’s not:

“I check how much new value I can add to this page. Sometimes it may be adding new information, screenshots, and internal links to relevant articles. Sometimes it means deleting outdated information.”

Here’s what you have to do:

• Add depth and context: If a section feels too surface-level, expand it with examples, case studies, or real-life applications to give readers more insight.
• Use visuals to illustrate your points: Screenshots, charts, tables, and even short videos can make your content easier to digest. Visual content is also great to boost user engagement.
• Include expert perspectives: Quotes or commentary from credible sources can boost both trust and relevance (and help with E-E-A-T too).
• Link to useful resources: Add relevant internal and external links that help readers take the next step – whether that’s learning more or converting. You can use an automated linking tool like LinkStorm to help with the process.
• Update old information: Replace outdated stats, insights, screenshots, and links with newer ones. 

Using this exact content refresh strategy, HR Datahub managed to boost its blog post’s ranking from position 35 to 1 in just 4 weeks. It’s also featured in AI Overview for the term “pay trends in the uk.”

4. Improve readability and UX

Studies have shown over and over again that people are more likely to scan content than read word for word. That’s why you have to make it as easy as possible for readers to consume your content.

Benjamin Rojas shares some tips to improve content readability:

“Today’s readers scan content before they commit to reading, so break up long paragraphs into shorter ones, add clear subheadings that preview what each section covers, and include bullet points for key takeaways.”

Based on his advice, here are a few simple ways to make your content easier to scan and more enjoyable to read:

• Keep your paragraphs and sentences short.
• Use bullet points and numbered lists where possible.
• Break up walls of text with images, quotes, and subheadings.
• Add jump links for longer pieces to help users navigate the page easily.

Also, improve your site’s overall speed. Not only will it provide a much seamless user experience, but page speed is also a Google ranking factor.

5. Optimize for AI-generated answers

While Google is still driving most of your traffic, visitors from LLMs are converting much better:

• At Ahrefs, around 12% of their new signups come from LLMs – even though those visitors make up just 0.5% of total traffic.
• Semrush also found that LLM visitors are worth roughly 4.4x more than traditional search visitors.

Image source: Semrush

If you’re not optimizing your content for AI search, you’re missing out on high-quality leads who are actively looking to convert.

Here are some proven strategies on how to rank in Google’s AI Mode, AI Overviews, ChatGPT, and other popular LLMs:

Structure your content for AI parsing

• Use clear, descriptive H2 and H3 headers that match user queries.
• Give answers directly under subheadings in a few sentences before elaborating.
• Include bullet points for key takeaways.
• Implement FAQ sections with conversational, high-intent questions (e.g., “What’s the best tool for X?” or “How do I do Y?”).

Optimize for semantic relevance, not just keywords

• Use natural language variants of your target keywords.
• Incorporate latent semantic indexing (LSI) terms that surround your core topic. 
• Focus on topical depth: go beyond surface-level SEO and answer the “why” and “how” behind queries.

Demonstrate topical authority

• Make sure your content has clear E-E-A-T (Experience, Expertise, Authority, Trustworthiness) signals.
• Include expert quotes and add links to reputable sources in your industry.
• If possible, enrich the content with original data from your own research and experiments.

Make it easy for AI bots to crawl your content

• Ensure that your page is publicly accessible – not hidden behind a login, paywall, or gated form.
• Use static HTML instead of Javascript. Most AI models can’t render Javascript yet, with Gemini as the sole exception.

Protecting Your SEO During a Refresh

Updating your content can do wonders for your performance. But it can also turn into a disaster if not done right.

Follow these steps to protect your SEO during content refreshes:

Keep the same URL

When you change the URL of your existing content, you’ll lose all backlinks pointing to it, along with the SEO value they bring. Unless absolutely necessary, stick with the current URL to preserve your rankings and avoid unnecessary drops in traffic.

Only change if the current URL is misleading or completely off-topic. If you must, make sure to set up a redirect and update internal links.

Don’t remove sections blindly

Be very careful when removing or rewriting a section. That paragraph you’re about to delete might be the reason you’re showing up in AI Overviews, featured snippets, or People Also Ask boxes. 

Always double-check how your content is currently appearing on SERPs and AI-generated answers before making big changes.

Submit for reindexing in GSC

After your refreshed content is live, use the URL Inspection tool in Google Search Console to request reindexing. This helps Google pick up changes faster and can reduce volatility during the transition period.

Use version control

Keep backups of your content files or use version history tools (like in Google Docs or your CMS) to track changes. In case performance drops after the update, you’ll want the option to revert to the previous version.

You’ve Refreshed Your Content, Now Let’s Attract Backlinks to It

Refreshing your content is only half the battle. To make sure your article gets the attention it deserves, you also need to promote it. 

Guest blogging is a common content promotion tactic many SEOs have been using for years. By contributing to relevant, high-authority sites in your niche, you can earn contextual backlinks to your refreshed piece.

Of course, this strategy takes a lot of time and effort. But you can always outsource your link-building efforts to SEO freelancers or agencies.

Regardless of who handles your content promotion, you’ll want to track your backlink progress—and that’s where Linkody comes in.

With this tool, you can identify outreach opportunities by analyzing competitors, monitor the quality of new backlinks, and find out which links are actually hurting your performance. 

Try Linkody now for 30 days FREE—no credit card required, no strings attached.

Author bio:

Sean is the founder of Position Digital, an SEO & GEO agency that helps B2B companies grow their brand visibility across both traditional search and AI-driven channels. Over the past six years, he’s helped clients navigate algorithm updates, shifting user behaviour, and changing search trends. Today, his focus is on helping brands adapt to the rise of LLMs and AI-powered search.

The post Content Refresh: How to Stay Visible in Organic and AI Search appeared first on Linkody's Blog.

Zero-click searches have been around for years. 

Ever since Google introduced SERP features like featured snippets, knowledge panels, and map packs, people have relied less and less on organic results and focused more on what Google shows them upfront.

For the first time, zero-click searches surpassed organic clicks in 2019, with 55% of all searches ending without a click.

But zero-click searches are making a massive comeback in 2025. We might just see an all-time low in organic clicks as generative AI and LLMs take off.

When zero-click searches take over, will SEO even be necessary? Let’s discover the answer here.

What is Zero-Click Search?

A zero-click search happens when a user searches for something on Google (or another search engine) but doesn’t click on any of the results. 

Instead, they get the answer they need directly on the search results page. In the past, this primarily referred to SERP features like featured snippets, definitions, weather boxes,  knowledge panels, or local packs. 

Since 2024, Google has upgraded its search interface to include an AI-generated summary for queries, which includes links to pages used as references.

Think of it like asking a question and getting an instant reply without needing to dig deeper. While it’s convenient for users, it’s a challenge for websites that rely on clicks for traffic, leads, or sales. 

What are the Sources of Zero-Click Searches?

In 2025, zero-click searches extend beyond traditional search engines, such as Google or Bing. Any platform that satisfies an inquiry without users having to click through websites and read their content can be considered a source of zero-click searches.

Here we’ll look at the most popular alternative solutions where users get answers without clicking any organic search results:

1. AI Overviews

AI Overviews are AI-generated summaries that appear at the top of Google’s search results, giving users a quick, synthesized answer to their query. 

It is Google’s second iteration at integrating generative AI capabilities into the SERPs (the first was Search Generative Experience).

This feature uses generative AI to specifically and comprehensively address a user’s inquiry in a conversational and easy-to-read format. To incentivize content creators, Google also added links to the sources they used to generate the summary.

Here is AI Overviews in action:

2. ChatGPT

You could say ChatGPT started all this generative AI craze. It is an AI chatbot that lets users ask questions and get direct, conversational answers without using a traditional search engine.

ChatGPT is not a search engine, at least not in the traditional sense. But many users already use the tool for finding information. And that makes this AI chatbot a purveyor of zero-click searches.

In the past, ChatGPT relied primarily on its massive training data for coming up with answers. It’s recently been updated to have search functionality, allowing it to access data from the open web and retrieve real-time information.

3. Gemini

Gemini is Google’s AI chatbot response to Microsoft’s ChatGPT, which means it pretty much does the same thing: you key in a prompt, and it generates content. 

The only difference is that Gemini has access to the breadth of the knowledge found in Google’s index. In theory, this makes its content more refined than other AI chatbots, but its prose is a little weaker than ChatGPT’s.

Given that Gemini gives all the answers to a prompt, it is also a major contributor to zero-click searches and reduced website traffic.

4. Perplexity AI

Perplexity AI is a conversational search engine that answers questions using real-time web data. 

Unlike ChatGPT, Perplexity goes big on featuring sources in its generated content, giving users a sense of security that the tool isn’t making up the information.

While it encourages zero-click behavior, the dedicated Sources tab lets users click through any of the listed resource pages, resulting in website traffic.

5. AI Mode

As of writing, AI Mode is Google’s latest and greatest brainchild, which aims to fully replace the known SERP features (like the AI Overviews, local pack, and organic blue links) with an AI-generated summary. 

AI Mode still hasn’t rolled out globally, so only the Indian and North American markets can enjoy this new feature. 

But from what we’ve heard, this will likely radically change how search works, giving searchers answers to their questions directly and completely removing the burden of clicking through organic blue links. 

Why are Zero-Click Searches Rising in Popularity?

Zero-click searches are great if you’re just a user looking for answers. Here are some specific reasons why zero-click behavior is on the rise in search:

AI summaries deliver instant answers

To be perfectly blunt, AI summaries spoon-feed everything users need to know. It delivers instant answers by pulling key insights from multiple sources and presenting them right on the results page.

In that case, no more scrolling, endless reading, and clicking. All the information is handed to you in seconds, making it convenient and addictive.

Conversational search replaces traditional clicks

What makes LLMs stand out against traditional search engines is that they present what you need in a conversational manner. That means no more reading through blocks of unnecessary text only to extract a few essential sentences or insights.

Plus, if you have any follow-up questions, you can simply build on the previous content to receive real-time answers. Basically, generative AI tools are like your personal smart assistant that does the heavy lifting on your behalf. 

Faster user experience is prioritized

According to the New York Post, the attention span of a person on a single screen has dropped from 2.5 minutes in 2004 to 47 seconds in 2025. Soon enough, as we digest more information and get sucked into the grind, it will only get worse.

Given that statistic, it stands to reason that people want information quickly. To address this need for a faster user experience, LLMs surface quick answers. This saves time, making traditional website visits feel like an unnecessary extra step.

5 Reasons Why Zero-Click Searches Are a Threat to Online Visibility?

While zero-click searches are advantageous for users, they might not be as forgiving of websites trying to swim their way out of online obscurity. 

After all, ranking #1 for organic search is already challenging in itself. Imagine how difficult it will be to optimize content for LLMs, knowing we have zero clue about these tools’ AI citation algorithms.

Zero-click searches stemming from generative AI tools pose a threat to the position of traditional search engines as the sole source of information. By extension, this puts websites engaged in SEO (both large and small) in a predicament, especially when it comes to search visibility.

Here are 5 specific reasons why zero-click behavior is a threat to online visibility:

1. Declining organic traffic

As the name suggests, zero-click searches directly result in fewer, if not absolutely no, clicks on organic search results. This leads to fewer organic traffic coming into websites.

This decline stems from the fundamental difference between traditional search engines and modern LLMs. Users get instant answers from tools like AI Overviews, ChatGPT, Gemini, or Perplexity, meaning they feel no need to investigate further and click the original source.

This means even if your page ranks high, it might still see fewer visits. In other words, your content works behind the scenes, but the traffic never reaches your site.

2. Harder to Measure ROI

Analytics is a core pillar of any marketing campaign.

Knowing what works and what doesn’t gives you the essential insights you need to recalibrate your campaign to perfection. 

This distinction directly influences how much revenue you can make throughout the period.

That used to be the case with SEO.

However, measuring analytics and ROI has become extra difficult in 2025 because traditional metrics lose meaning, including:

• Clickthrough rate
• Page views
• Bounce rate
• Keyword rankings
• Domain authority

Your content may power an AI summary or influence a response, but you won’t always see that impact in your analytics unless users click the source page for that information. Unfortunately, not all LLMs are generous in including references.

This creates a blind spot for marketers and businesses trying to justify their SEO investment. When traffic doesn’t land on your site, proving value and calculating returns becomes murky.

3. Lower website conversions

Piggybacking off #2, lower website conversions are a growing concern in the age of zero-click searches.

If users fixate on the quick answers from the AI summary without bothering to visit your content, the conversion will plummet along with the decline in traffic. That means limited desired action taking place on your site, such as signing up, downloading, or making a purchase.

While Google and Bing allegedly claim that website traffic coming from LLMs is more engaged, of higher quality, and warmer than traditional organic traffic, Dan Taylor’s LLM vs organic traffic study challenges this.

The only sectors where LLM traffic’s key event conversion rate exceeds organic conversion rates are: 

• Careers
• Catalog websites
• Health
• Publishing
• Real estate and property

Meanwhile, the rest of the sectors lean toward organic traffic’s superiority in conversion rates. 

Here is a table summarizing the comparison:

Unfortunately, since we are transitioning to a zero-click-search-dominated industry, site owners and marketers are forced to divide their attention, optimizing both for LLMs and search engines.

4. Limited knowledge about LLM algorithms

It took SEOs decades before they managed to uncover the strategies and decipher Google’s major search ranking factors (although Google listed some best practices on their site). 

Since LLM technology is relatively new, knowing the quirks and algorithms of each generative AI tool might take a while.

Until then, most marketers will be left in the dark when it comes to optimizing for zero-click platforms. Unlike traditional SEO, where ranking factors are clearer and trackable, LLMs work behind many closed doors. 

This lack of transparency makes optimization feel like guesswork—tedious, experimental, and often expensive.

Without many large-scale studies available, marketers struggle to understand how their content is being used or prioritized by AI tools. 

As a result, the time and budget spent on content deliver little to no visibility or measurable return to websites.

5. Less incentive for content creators

If you’re an SEO copywriter or content manager, your goal is to boost a site’s visibility by increasing the organic ranking of its pages. That’s why you’re paid. 

High-ranking content equals traffic, which, if highly persuasive, can convert readers into buyers. 

But with LLM-based search engines that give answers upfront, fewer users visit the source. Add to the fact that LLMs citations do not always base on organic rankings, meaning even top pages might go unnoticed.

This can discourage creators, devalue their work, and even cost jobs. Worse, entire websites shift away from SEO-driven content altogether and redirect efforts to channels like email or social media, where visibility and ROI feel more within reach.

Data-driven Strategies to Combat the Zero-Click Threat?

At the end of the day, zero-click searches are double-edged swords: great for users, not so much for site owners, content creators, and SEOs (at least for now).

Given everything we know about this new era of search, how can content creators combat the threat posed by LLMs? 

Simple. We don’t combat it. We adapt. By showing up on LLM citations, you exponentially increase your chance of driving traffic from non-organic sources, which is still good, all things considered.

Several small-scale data-focused strategies have emerged in recent weeks, showing a list of ways to overcome zero-click searches by optimizing websites for LLMs. 

Here are a few:

• Free robots.txt and metadata from commands blocking LLM bots
• Phrase your content conversationally, as humans would phrase AI prompts
• Make your content comprehensive, adding more value and covering more concepts
• Improve readability, specifically its Flesch-Kincaid score
• Boost your positive brand mentions across the open internet 
• Build more backlinks from reputable sites
• Focus on increasing your domain authority or domain rating

Zero-click searches may feel like a threat now, but they also open new doors, especially if you start optimizing for AI citations and find ways to drive high-value traffic from LLMs. 

SEO is far from irrelevant, but it’s evolving fast. Relying solely on blue links is no longer enough. LLMs represent uncharted territory, and no website has truly mastered them yet.

The sooner you adapt your strategy for AI-driven search, the better your chances of staying visible. Otherwise, if you don’t, you might actually end up with zero clicks from both LLMs and traditional search.

The post Why Are Zero-Click Searches a Threat to Online Visibility? appeared first on Linkody's Blog.

The way people search is changing, and it’s happening fast. With the rise of generative AI tools, such as ChatGPT, Gemini, and Perplexity, along with the reimagining of SERPs thanks to AI Overviews, more users are skipping traditional “blue link” Google search altogether.

In fact, statistics show that 52% of Gen Z are already using AI to make informed decisions. Whether it’s for product research, recommendations, or everyday questions doesn’t matter. 

The point is this trend isn’t slowing down.

As users turn to LLMs for search, sticking to traditional SEO won’t cut it anymore. This shift calls for a new kind of optimization.

Enter: Large Language Model Optimization (LLMO).

To stay competitive, brands need to ensure their content is not just discoverable by search engines but also understandable, quotable, and usable by AI models. 

In this article, we’ll break down exactly how you can optimize your website for this new frontier in digital visibility.

What are LLMs, again?

LLMs, short for Large Language Models, are a subcategory of generative AI that’s trained to understand and generate human-like language. 

Depending on which tool you’re using, they can have advanced or basic underlying mechanisms that enable them to answer questions, summarize information, and even write full articles. 

LLMs can be further subdivided into two major categories:

A. Retrieval Augmented Generation or RAG

RAGs are LLMs with access to external sources. When you ask a question, they retrieve real-time information from the web or internal databases and then generate a response based on that fresh data.

This makes them highly accurate and current, perfect for fact-based or up-to-date queries. Gemini and AI Overviews fall under this category.

Here’s Gemini when asked who won between the Indiana Fever and the Golden State Valkyries on July 10:

P.S. The matchup happened on July 9, yet Gemini did not bother to correct my wrong question.

B. Self-contained LLMs

In contrast, self-contained LLMs rely solely on the data they were trained on, without fetching new info. Their responses originate from patterns they have already learned, which means they may be less current but still excellent for general knowledge, writing, or problem-solving.

ChatGPT (for a time) and Claude fall under this category. For instance, as of writing, Claude has a knowledge cutoff date of April 2024. 

Meanwhile, ChatGPT (GPT is short for “Generative Pre-trained Transformer”) now has features enabling it to connect to web browsing, even on the free version.

Here is ChatGPT when asked the same question as above:

ChatGPT did a more impressive job by correcting my incorrect date and adding references in their content, even including a highlight reel for good measure.

What is LLMO?

In the words of Bernard Huang, founder of Clearscope: 

“LLMs are the first realistic search alternative to Google.”

While Google dominated the search space for a long time, a fraction of the number is now turning to LLMs and generative AI. 

Sure, the number is dismal compared to the total population of Google users. But the active user base will only keep getting bigger and bigger, considering LLMs are now equipped with web search functionality, albeit not as refined as Google’s pristine index.

This brings us to LLMO or Large Language Model Optimization.

LLMO is a new approach to making your content more accessible and useful to generative AI tools, specifically those equipped with RAG, like ChatGPT, Gemini, and Perplexity.

Unlike traditional SEO, which focuses on ranking in search engine results pages, LLMO is about optimizing content so it is featured and cited by AI assistants for relevant prompts.

Search engines like Google and Bing have their very own algorithms that allow them to rank pages based on a plethora of factors. LLMs also have the same.

Thanks to recent findings, we get a sneak peek into some of the most important qualities that major LLMs look for when citing pages. And we’ll discuss them later.

Why is LLMO Important in 2025: 3 Reasons

As AI transitions to becoming an alternative way people find answers online, the rules of search are changing. Ranking #1 in Google isn’t the only goal anymore. Being understood by AI models is just as crucial for driving traffic and visibility to your website. 

Here are three specific reasons why LLMO matters more than ever in today’s AI-first digital landscape.

Reason #1. Traditional SEO is not enough in an AI-first world

For years, SEO has stood as the sole barrier to entry for search visibility. This strategy revolved around optimizing content for search engine crawlers through keywords, backlinks, and other technical data to climb the ranks.

However, for the first time, LLMs are challenging SEO’s position as an arbiter for search visibility. Given the popularity of AI chatbots like ChatGPT and Perplexity, it’s only fitting that Google integrates the same generative summary at the top of search results in response to queries (AI Overviews).

This created a bipartite challenge to traditional SEO:

• The first organic position will receive significantly fewer clicks and CTR
• You now have to perform SEO to rank high and LLMO to bag a spot in the AI snapshot

Faithfully sticking to either one strategy or the other wouldn’t cut it.

Reason #2. Zero-click searches are replacing traditional SERPs

AI Overviews on their own are already a problem. But Google is brewing a new SERP feature called AI Mode that seeks to completely replace the traditional search results interface with AI-generated content, complete with links to sources.

This only makes the argument for zero-click searches stronger.

Unlike traditional SERPs, where users are actively looking for answers, zero-click searches spoon-feed instant responses. That means no more need to click a website, and Google gives a comprehensive summary that answers your specific inquiry.

When that happens, your traffic and visibility depend less on rankings and more on being included in the AI’s generated response.

LLMO makes your content attractive to AI citations, improving your chances of being featured in those answer boxes.

Reason #3. Your content could be cited without ranking #1 in organic search

SEO and LLMO are not easy.

But for a small website in a cutthroat industry, we can argue that ranking for AI Overviews and other LLMs is way easier than outcompeting household names with unlimited SEO budgets.

Recent studies from Ahrefs reveal that traditional SEO metrics have not-so-great correlation with mentions in AI Overviews, ChatGPT, and Perplexity. This means that, while SEO metrics matter, you can blow past established brands on AI citations if you play LLMO right.

Here is what Patrick Stox discovered in his mention share vs. Ahrefs rank analysis of the top 50 brands mentioned across LLMs:

This new finding makes the playing field even more level. And below, we’ll look at data-backed strategies on how to do LLMO:

How to Do Large Language Model Optimization (LLMO)?

There isn’t an established consensus yet on the best practices for optimizing content for large language models. However, microstudies from various authors offered invaluable insights into creating this list.

Here are the resources we referenced for the curation of these strategies:

• What content works well in LLMs? By Kevin Indig (Growth-Memo)
• An Analysis of AI Overview Brand Visibility Factors (75K Brands Studied) by Louise Linehan and Xibeijia Guan (Ahrefs)
• Domain-Level Link Metrics May Not Be Good Predictors of AI Search Mentions by Patrick Stox (Ahrefs)   

1. Double-check if your site is unintentionally blocking LLMs from indexing your content

You could have the best, most AI-recognizable content, but if the technical aspects of your site are blocking your efforts, your page still wouldn’t appear as citations.

Check your robots.txt file if any commands are added there that might block LLMs from crawling your site.

Additionally, make sure your website is indexed in various search engines for maximum visibility, whether for traditional search or AI-generated content.

For example, the website OnlineDoctor.com is indexed on Google…

… but not on Bing:

In that case, relevant queries concerning OnlineDoctor’s niche may surface the website on Google’s AI Overviews and Gemini but not on Bing’s CoPilot.

Other technical issues that can prevent AI mentions include:

• LLM crawlers blocked by firewall or CDN
• Overlooked broken links disallowing LLMs from fully crawling your site
• Improper redirect implementation that confuses LLM bots
• Nofollow tags in your pages’ metadata

Technical inconsistencies like this can sabotage your LLMO efforts, so make sure your site is accessible to generative AI tools to increase your chances of getting cited.

2. Phrase your content as AI chatbot users would phrase their prompt

Think of your content as a direct response to an AI prompt. Users interact with LLMs by asking natural, question-based queries like “How does LLMO differ from SEO?”

So, your content should mirror those queries in structure and tone. Don’t go all ornate and overembellished on your prose because you’re not Shakespeare (unless that’s your entire schtick).

Otherwise, keep your content simple, which means: 

• Use conversational phrasing
• Answer questions clearly
• Include variations of how a prompt might be asked

In addition to proper content formatting, it’s equally crucial to phrase your content in a way that mirrors the language people use in AI queries. 

For example, Kevin Indig discovered that the term “best” triggers brand mentions in nearly 70% of prompts. Other powerful prompt triggers include “trusted,” “source,” and “recommend.”

In practice, here is an example of how that should look. Instead of saying, “We provide an automated internal linking SaaS for SEO,” you might write, “We’re a trusted SaaS company that offers automated internal linking tool that’s used by thousands of marketers.” 

This doesn’t just make your content more relevant, but even makes it AI-friendly.

There’s little research yet on the most common queries used on LLMs, so we can’t reverse-engineer anything yet with full certainty at this point. But microstudies like these give us insight into these machines’ internal workings.

3. Increase your word and sentence count without adding more fluff

Let’s get one thing straight: CONTENT LENGTH and CONTENT DEPTH are not one and the same. 

Just because an article is long doesn’t mean it’s valuable. Some 2,000-word articles can be compressed to 500 words and still get the same message across.

However, LLMs have a proclivity toward longer content, specifically because longer pieces have a higher tendency to offer complete, comprehensive, and well-explained answers to a query.

Here is a quick graph showing the primary differences between the top 10% and bottom 90% of pages cited in AI snapshots:

Conversely, shorter posts are likely (not necessarily) to be thinner in value.

Aim to extend the value of your content by making the following improvements:

• Cover additional or tangential subtopics relevant to your content
• Create original graphics if possible
• Add relatable or real-life examples
• Answer frequently asked questions
• Use bullet points, comparisons, and formats that AI can parse easily

The goal is to make your content dense and information-rich, satisfying intent, and making it more attractive for AI citations.

4. Improve your Flesch-Kincaid readability scores

Believe it or not, traditional SEO metrics like the number of backlinks, number of keywords, and total traffic does not matter that much for AI citations. At least, that’s what Kevin Indig found in his study.

AI tools like Perplexity and ChatGPT place more weight on Flesch readability scores.

If you’re not aware, Flesch Reading Ease is a 0-100 scoring system that measures how easy it is to read a piece of text based on the sentence length and word complexity. The higher the score, the easier it is to read the content.

Apparently, Flesch scores aren’t only for human readers but also for LLMs. Don’t get it twisted. AI can understand even the most complex run-on sentences. However, readability scores may be a stiff parameter that they take into account when citing resources.

To improve your content’s readability, here are a few tips:

• Keep sentences short and punchy
• Use more active voice and limit passive voice usage
• Break up long paragraphs
• Avoid jargon when possible

This isn’t about dumbing down your content. Think of it as simplifying complex ideas for easier comprehension, making your content attractive to AI tools.

5. Invest in a good PR strategy to amplify your reach (in a good way!)

In an analysis conducted by Ahrefs’ Louise Linehan and Xibeijia Guan, they discovered three metrics to have the highest correlation with AI Overview mentions: 

• Branded web mentions: How many times your brand name is mentioned across the open web 
• Branded anchors: How many times your brand name was used or integrated into anchor texts (backlinks, internal links, external links)
• Branded search volume: How many times your brand is searched on search engines per month on average

Here’s the breakdown of the factors influencing AI Overview citations:

Since LLMs source out content across multiple reputable sources, you want your brand to be all over the place. 

From a human’s perspective, seeing your brand plastered across the web associates your brand with reputability, this helps with brand recall. The same principle applies with AI. 

If your brand name is present across multiple touchpoints, LLMs are more likely to see you as a reliable source, increasing your chances of being cited.

A smart PR strategy can help distribute your content and brand name to places where AI models are more likely to find it. Think guest posts, media coverage, podcast features, and niche mentions.

6. Build more high-quality backlinks from reputable sites

Piggybacking off point #5, backlinks are still invaluable for AI discovery despite the downplay on traditional SEO metrics.

First, branded anchors is an important factor for AI Overview citations. This emphasizes the importance of building backlinks using branded anchor texts. It doesn’t have to be exact match per se, but including your brand name on the anchor text can already have a massive impact. 

Secondly, backlinks, much like other links, are channels for AI bots to discover your site. Focus on building backlinks from reputable sites since they are likely frequently visited by AI crawlers, which, by extension, amplifies your content’s chances of being discovered as well.

Finally, SEO aside, high-quality backlinks are still the most significant ranking factor for SEO to this day. That means actively engaging in link-building efforts lets you hit two birds with one stone: 

• Boosted traditional SEO performance
• Increased AI citation likelihood

7. Work on the factors influencing your brand’s overall popularity

According to Kevin Indig, popularity is the most significant criterion for AI citations, particularly with AI Overviews, Perplexity, and ChatGPT.

But what exactly does “popularity” mean?

Popularity is an overarching, multifaceted term in the modern digital marketing landscape. It refers to those brands that excel across various marketing channels, including SEO, content creation, social media, reviews, and digital advertising.

To maximize LLMO, you can’t afford to have tunnel vision, or primarily focusing on one or two marketing facets, then neglect the rest. 

Staying consistently active and successful on multiple channels increases your likelihood of being picked up and cited by large language models.

Is SEO Still Relevant in the Age of LLMO?

Thinking SEO is dead just because large language models have a growing user base of searchers is a big mistake.

SEO and LLMO are not mutually exclusive, but are interdependent.

Multifaceted marketing optimization, which includes SEO, is the backbone of LLMO. That means neglecting SEO puts you at a disadvantage if you want to appear in AI citations.

On the other hand, relying solely on SEO without adapting to how AI systems retrieve and present information also leaves you behind. Traditional SEO tactics are formulaic and focused primarily in ranking in SERPs, while LLMO ensures your content is structured, readable, comprehensive, and semantically rich to be cited in AI-generated answers.

That said SEO and LLMO complement each other. Think of LLMO as an evolution to SEO.

To thrive in today’s AI-driven search landscape, marketers must integrate SEO foundations with LLM-focused enhancements.

So, ready to succeed in LLMO?

The post LLMO: How to Optimize Your Website for LLM Searches? appeared first on Linkody's Blog.

It all started with OpenAI’s ChatGPT, and many companies have begun riding the AI train since. Google included.

From Search Generative Experience to its rebrand, AI Overviews, now, the search engine giant is experimenting with a new SERP feature that will radically change how search works.

Introducing: AI Mode.

Google’s latest experiment, AI Mode, isn’t just another tweak to the SERP like AI Overviews. 

It’s literally removing the 10 blue links in favor of AI-generated content produced by a supercharged Gemini model capable of deeper reasoning and smarter comparisons, allowing it to fully answer complex and nuanced queries without users ever clicking a single link.

It’s really good. Kudos to Google.

While AI Mode favors the majority of searchers who just want quick and concise answers, for SEOs, this isn’t evolution but a disruption.

As Google pushes toward a zero-click, AI-driven search experience, many content creators and marketers will be left wondering: If Google answers everything while referencing only a select few, who still needs our websites? 

I’m all for progress and maximum user experience, but AI Mode threatens to reduce even some of the best-optimized pages to invisible contributors in a summarized box, and it’s scary.

We’re no longer fighting for first position. We’re fighting to be included at all.

That said, is this the death of SEO we’ve all been fearing? It might be. But we’re getting a little ahead of ourselves.

What is Google’s AI Mode?

AI Mode is an under-development feature that takes the capabilities of AI Overviews several steps further by replacing the entire SERPs with AI-generated content. 

That means no more traditional blue links, and the only links featured are the ones Google’s algorithm has selected as relevant for the specific query.

Since it is powered by Gemini 2.5, AI mode is better equipped to receive complex and nuanced questions and generate AI responses that combine advanced reasoning, comparison, and real-time information from across Google’s index. 

Unlike traditional search, AI Mode leans heavily into a zero-click experience, where users are encouraged to stay within the AI interface rather than visit external websites. 

A search bar is provided at the very bottom of the AI Mode screen for follow-up questions. This means sending a new query builds on your established conversation and doesn’t start your search journey from scratch.

While Google still features a handful of resources in its responses, much like AI Overviews, user clicks become optional, not essential.

AI Mode vs. AI Overviews: What’s the Difference?

Before we explore the differences, let’s look at the similarities first.

Similarity number one: AI Mode and AI Overviews are both built on Gemini 2.5, which means they have a better understanding of human reasoning and linguistic nuances. This helps them generate far more accurate responses to queries.

Similarity number two: AI Mode and AI Overviews cite relevant sources to their AI-generated content, adding a layer of factuality to back up their responses. 

And that’s as far as their similarities go. Now let’s look at their differences:

Difference number one: AI Mode is always present. 

AI Overviews don’t always appear in searches, especially when researching something too niche or very simple. In fact, Google shows the AI snapshot only when its system determines that a generative response would be helpful. This makes them very unpredictable. 

Conversely, AI Mode is more predictable since it is a dedicated tab found alongside All, Images, Videos, News, and whatnot. Google promised to show AI Mode as frequently as possible, but for questions in which it has low confidence, it might revert to showing a set of search results.

Difference number two: AI Mode has better reasoning capabilities.

While both are built on the same Gemini 2.5 engine and apparently use the same ranking system, AI Mode is better refined to improve its reasoning using novel approaches. 

This potentially makes it a better choice to answer more debatable or open-ended questions and navigate polarizing topics with more reasoning. 

Difference number three: AI Mode addresses queries more comprehensively.

AI Mode uses what Google calls the “query fan-out” technique. 

In other words, aside from addressing your primary query, the machine will also look at related searches surrounding the same topic. This makes their response more holistic, covering way more ground than AI Overviews or traditional searches ever could.

This also means you are less likely to dig deeper into the topic since AI Mode will have covered everything there is to know about. But in case you have something else in mind…

Difference number four: AI Mode has a dedicated search bar for follow-up questions.

Unlike traditional search, where every fresh query takes the search journey back to square one, AI Mode has a retention feature. That means it will retain previously discussed topics if you have a follow-up question.

The experimental feature has a dedicated search bar at the very bottom for any follow-up questions you might have. This makes your inquiries sound more natural and conversational, and less like a librarian as in traditional search.

Now, you might be thinking, “Follow-up questions? Cute. Doesn’t ChatGPT already do that?” 

Well, true.

The only difference is that AI Mode has direct access to the breadth of knowledge and real-time information across Google’s index, something ChatGPT has yet to have.

While AI Mode is in its infancy, AI Overviews might already see some improvements during this experimental season. 

Google CEO Sundar Pichai said in an interview with Lex Fridman that AI mode is part of a “continuum,” where features that work well will eventually “overflow” into AI Overviews and the main search experience.

This implies that AI Mode is not a test. It’s the future, just arriving in pieces.

How Will AI Mode Change How People Use Google?

As far as user experience is concerned, AI Mode is a massive leap toward better search experience for people.

Instead of going through several blue links to get your query satisfied, or painstakingly starting the conversation from scratch every time you search on Google, AI Mode answers everything in one fell swoop. 

It even gives you the freedom to ask some additional questions on the same subject without forgetting what you’ve already established in the preceding search.

Google’s UX Research Director, Claudia Smith, said AI has been naturally redefining how people use search, from using shorter queries (in the past) to asking longer, more complex questions (in the present). 

They expect the same trend to happen once AI Mode is rolled out globally:

Personally, AI Mode is a step in the right direction, from a user standpoint.

From an SEO perspective, it’s honestly a mixed bag. As an SEO myself, I can’t help but wonder what kind of future awaits our industry amid all these rapid changes, especially with search.

Do I blame Google? No. But AI Mode will put many SEOs out of work, especially those who specialize in cutthroat markets, but are paired with less popular websites.  

What are the SEO Implications of AI Mode?

AI Mode could either be a really good thing or an especially bad one, depending on who you’re asking.

For users, it could be the best thing ever because it makes searching more convenient and accurate than ever before.

For SEOs? Let’s just say the fight for visibility just got a little more intense. 

Now we’re no longer just vying for user attention, but also praying that Google’s AI systems see and feature our website on its generative snapshot.

Here are a few implications of AI mode on SEO:

1. Reduced organic clickthrough rates

One of the most immediate and concerning SEO implications of AI Mode is the potential for significantly reduced organic clickthrough rates. 

AI Mode marks a clear shift from traditional search behavior. Instead of having to read the generative snapshot from AI Overviews and scanning organic links for answers, AI mode spoonfeeds information to users—summarizing, comparing, and explaining on their behalf.

With highly detailed, synthesized answers right on SERP, the need to visit external websites practically becomes zero (although Google decided to keep that option open through links to references and helpful resources).

This brings us to #2…

2. Declining organic traffic despite visibility

Even at the early stages of AI Mode, it’s clear as day that search visibility will be contingent on two things:

• Users clicking the source pages referenced by the AI Mode
• Users opting out of AI Mode and explore traditional search results pages

Both are unlikely.

After all, why would users even bother when the machine tells them everything and more. 

What does this mean?

For content creators and site owners, AI Mode lowers the chances of attracting traffic, even if their content is being cited or referenced. And in a world where visibility doesn’t guarantee visits, ranking alone won’t be enough. 

Once AI Mode becomes the norm, publishers risk becoming invisible contributors by fueling Google’s AI answers without seeing a return in the form of user sessions or engagement. 

For many websites, this could mean a steep drop in organic traffic, meanwhile for SEO professionals, a fundamental rethinking of what “search engine optimization” even means.

3. Marginalization of blue links

For now, AI Mode is still an experimental feature within Google’s Search Labs. The standard SERP still includes AI Overviews, organic blue links, and familiar search packs, which means users may still explore links if the generative snapshot proves unsatisfactory.

However, once AI Mode takes center stage, the traditional blue link format could lose its schtick in how users interact with search.

And that’s a very bad thing.

In a zero-click environment, users will no longer feel the need to scroll through or click individual results even if they are listed. This is especially true as AI responses become more accurate and satisfying. Organic links will become nothing more than background noise.

4. Disincentivization for small publishers

Google claims there isn’t anything special we can do to increase our chances of ranking on AI Overviews, except the usual SEO essentials. But it seems like killer content is not enough to earn your keep on the generative snapshot. 

Ahrefs recently discovered that branded backlinks, branded anchors, and branded search volumes are among the biggest factors correlating with AI Overview mentions.

Now, if you’re a small website with a limited budget for link-building and only has good content to offer, your chances of making it on AI Overviews is slim to none. How much more for the AI Mode?

The marginalization of organic links and prioritization of big websites could disincentivize smaller sites to keep creating high-quality content. 

What for, if visibility will be concentrated on larger, more authoritative sites frequently cited by Google’s AI?

Without measurable ROI, be it traffic, conversions, or leads, many businesses may find SEO no longer worth the investment. 

5. Information monopoly risks

Imagine if #4 actually happens. Say, smaller websites ditch SEO to pursue other marketing facets that give them a fair shake at attracting traffic and encouraging conversions.

This could not only spell a huge decline in SEO content publication, but it can even put Google’s entire informational ecosystem in jeopardy. 

In perpetuity, if small publishers stop creating content and only the big, often-referenced websites continue publishing, Google’s entire index could be at risk of being monopolized by a select few.  

That is, Google acts as the gatekeeper and only a handful of dominant sources shape what billions of people see, read, and trust.

Just food for thought.

6. Greater demand for structured, clear, high-authority content 

AI Mode would take a toll on many websites primarily focused on SEO. That much we can be sure of. However, that doesn’t mean it’s smart to ditch organic search visibility entirely.

With AI mode pulling data from multiple sources to generate answers, only the most well-structured, topically authoritative, and well-linked content will make the cut. While being featured on the AI summary does not ensure traffic, it’s better than not being cited at all.

To be referenced, your content needs to be clear, organized, and easy for machines to understand. But structure alone isn’t enough, Google’s AI leans heavily to sources backed by relevance and citations, so make sure to set an effective link-building mechanism in place.

Additional word of advice: diversify your marketing channels!

Is this the Death of SEO We’ve Been Fearing?

The phrase “death of SEO” has been thrown around countless of times before, and each time, SEO has adapted and survived. 

However, AI Mode feels too different. 

It’s not just another update. It’s a fundamental shift in how people interact with search. 

Given people’s natural proclivity toward speed and convenience, having to do fewer clicks and less reading is a blessing. Unfortunately, this also means the role of websites and SEOs could change dramatically, and for the worse.

Still, it is too soon to tell.

We’ve weathered paradigm shifts before, and we might again. What’s clear is that we’re entering a new era. 

SEO isn’t dead yet, but it is already evolving into something else (AI Mode) and we haven’t even fully deciphered it’s old form yet (AI Overviews).

What are your thoughts on this?

The post AI Mode: How Will SEO Fare in A Zero-Click AI-Focused SERP? appeared first on Linkody's Blog.

If you haven’t noticed yet, we are living in an era of automation. 

Ever since generative AI became mainstream, companies have made it their life mission to integrate artificial intelligence into their workflow and services. And for good reason!

AI shines in taking over repetitive tasks, leaving more room for humans to perform creative and strategic tasks. Even digital marketers and SEOs are turning to AI for menial responsibilities; internal linking is no exception.

Manually building internal links can be tedious, time-consuming, and easy to overlook, especially on growing websites. 

That’s where automated internal linking comes in.

It promises to simplify SEO efforts, improve site structure, and keep your content interconnected with minimal effort. But like any automation, it’s not without drawbacks.

In this guide, we’ll walk you through everything you need to know—benefits, limitations, and the best tool to supercharge your internal linking campaigns. Stay tuned!

What is Automated Internal Linking?

Automated internal linking is the process of using tools or software to create internal links across your website without doing it manually.

Instead of finding link opportunities and adding them one by one, tools do the heavy lifting on your behalf, including:

• Scanning your content
• Identifying relevant keywords or topics
• Embedding internal links to related pages automatically

Internal linking can feel repetitive and taxing, especially when dealing with larger websites. By automating, you significantly cut the time needed to maintain a well-connected site. But that’s just one benefit among many others.

Below, we’ll explore the specific benefits and drawbacks of automated internal linking, so you can weigh whether it’s the right investment for you. 

5 Advantages of Internal Linking Automation

Benefit #1. Saves time and manual effort

Manually adding internal links can quickly become a full-time job, especially if you’re taking SEO seriously.

If backlinks are the NBA, internal linking is like the G-League. Same sport, same rules, just slightly inferior players and less money generated for the overlords. Nonetheless, they fulfill the same goal. 

How so?

Like backlinks, internal links also transfer SEO value from referring to target pages. Internal links also serve as portals for web crawlers to explore your website.

But since you have more control over internal links, it’s easy to get lost in a sea of opportunities to manually embed them.

With automation, you no longer have to hunt down relevant pages or copy-paste URLs over and over again. This saves time and fatigue from doing the same thing repeatedly.

For example, here is what the CEO of eCommerce Fastlane had to say after using an automated internal linking tool:

If you don’t experience the same convenience, are you even investing in the right tool?

Benefit #2. Scales easily with growing content

As your website grows, keeping up with internal linking becomes harder. What starts as an easy-peasy-lemon-squeezy task with 20 pages turns bonkers once you hit 200 pages and more.

Meanwhile, automated internal linking can effortlessly and effectively scale alongside your content.

Whether you publish one article a week or dozens, automation tools can keep everything connected with minimal effort.

It’s like having a caffeine-fueled assistant who never sleeps and does your bidding without question. All you have to do is review their work, and in this case, approve or reject the internal link suggestions.

Benefit #3. Optimizes link equity distribution

When done right, internal linking doesn’t just connect your pages; it helps spread SEO value across your entire site. This is called link equity. 

Internal linking tools ensure link value doesn’t get stuck on just a few top pages. They do not discriminate against stale pages, but link to everything as long as contextually relevant and logically pertinent.

In other words, manually figuring out which pages to link where (a time-sink on its own), automated tools distribute internal links more evenly, giving love to older, possibly underperforming content. 

Over time, this balanced flow of link equity can lift rankings across more pages, not just your homepage.

Benefit #4. Minimizes human errors

Let’s face it—we suck compared to machines, primarily because we are predisposed to exhaustion. And when fatigue creeps in, that’s when mistakes happen.

Funnily, I recall my chemical engineer roommate in college who wrote some gibberish on his term paper when he had little sleep. The same principle applies.

But with automated internal linking, those slip-ups are far less likely.

These tools follow consistent rules and patterns, reducing mistakes that can hurt user experience or SEO performance.

That means no more double-checking every URL or wondering whether you linked the right page. 

Benefit #5. Frees up SEO resources

In the end, the biggest advantage of automating your internal linking campaign is that it serves your bottom line in the long run.

As mentioned above, manual internal linking can eat up hours, and every hour spent entails an additional snip off your income. 

In addition to that, manual internal linking also takes away from your SEO team the time for higher-impact tasks, such as content strategy, keyword research, technical SEO fixes, or conversion rate optimization. 

Remember, internal linking is just one facet in the SEO bubble!

So, don’t let your SEO team (or yourself, if you’re a one-man show) get lost in repetitive work. With automation, you can direct your time, talent, and treasure toward results-driven approaches.

3 Disadvantages of Internal Linking Automation

While automated internal link-building offers numerous benefits, it also has its drawbacks. Here are three you have to consider:

Challenge #1. Lack of editorial judgment

Automated tools are great at following rules, and that’s a good thing. Unfortunately, this leaves very little room for creativity, as a human editor would.

They don’t understand nuance, tone, or when a link actually adds value versus when it feels forced. Although some internal linking tools use semantic analysis, making their suggestions more effective, they still need some human oversight.

Lack of editorial judgment means some links may be placed in awkward spots. Sometimes, links could point to pages that don’t truly help the reader. 

AI just follows an algorithm, and while that’s efficient, it can lead to a clunky UX that feels more robotic than helpful.

Challenge #2. Risk of over-optimization

One of the biggest risks with automated internal linking is over-optimization. That happens when the tools repeatedly use the same keyword-rich anchor text across your site.

While internal links are great for SEO, too many exact-match phrases can start to look spammy to search engines. It’s the digital equivalent of trying too hard.

Over-optimization might raise red flags and, in extreme cases, lead to penalties. Automation doesn’t always know when to pull back or mix things up to create anchor diversity.

Challenge #3. Technical issues

Sometimes SaaS, much like SEO-oriented Chrome extensions or plugins, don’t play nice, technically speaking. Throw them all together into one website, and something ought to break.

In some cases, automated internal linking tools might experience technical hiccups, causing them to function improperly. This could range from suggesting irrelevant links or, worse, causing your website to behave erratically.

In addition, if something breaks natively on the tool, you might be left waiting on developers to troubleshoot or release a patch before things get back to normal.

What Makes A Good Automated Internal Linking Tool?

With all the perks and quirks that come with internal linking automation, their functionality shouldn’t be limited to just inserting links. 

“A good internal linking tool must amplify the benefits of automation while minimizing the downsides.” 

At the core, it needs to be smart and flexible. 

Specifically, that means:

1. Internal linking suggestions shouldn’t be boxed to exact-match anchors to avoid over-optimization, but have a stronger link-finding algorithm
2. Site owners or content managers maintain complete control over which links to accept or reject, and retain creative freedom over anchor text variation
3. The tool must work in harmony with your existing site structure, not against it, which means strong technical support, seamless integration, and a wide range of compatibility

Bonus points if it has a clean-looking interface, which makes internal link-building a breeze.

In short, a good automated internal linking tool feels like a helpful SEO sidekick: efficient, context-aware, and reliable even as your content library keeps growing.

Before settling on one, it helps to see the whole field: we keep a directory of 23 internal linking tools with verified pricing, platform support, and automation level for each, so you can weigh any option against the criteria above.

Our Top Pick for Automated Internal Linking: LinkStorm

We consider so many elements when it comes to choosing the right tool for internal link automation, as discussed above.

While many offer the same value proposition, not every tool offers the level of flexibility and context-awareness that we need. 

That’s why, for us, LinkStorm was the top pick. We’ll enumerate below the specific reasons that made us choose LinkStorm as the best automated internal linking tool:

1. Uses semantic analysis for smarter link suggestions

LinkStorm isn’t locked to matching keywords but understands meaning. 

The tool uses semantic analysis to identify relevant linking opportunities without relying on exact-match link text. 

Just take a look at the example screenshot below:

This keeps your anchor text profile natural and diverse, which is a major plus for long-term SEO.

Even better, it uses AI to interpret the context of both the source and target pages, so links are placed where they actually make sense. 

Also, LinkStorm arranges link suggestions based on its proprietary “relevance score,” so you can prioritize highly contextual links first and then work your way down.

Of course, not all links are acceptable. You can simply ignore or reject these links without worry. 

2. Gives you freedom over anchor text selection

Unlike many tools that auto-embed pre-defined anchors, LinkStorm lets you choose your anchor text before anything goes live.

This kind of editorial control is crucial if you’re aiming for varied anchor usage and avoiding keyword stuffing.

Honestly, it isn’t as potent yet since you cannot edit the text itself, but only change the highlighted anchor. Nonetheless, whether you prefer partial-match, phrase-match, or exact-match anchors, LinkStorm lets you make the call every time. 

3. Not a plugin, but a standalone tool

One of LinkStorm’s biggest advantages is that it’s not tied to any specific CMS. Since it’s a standalone tool, you’re not limited by plugin compatibility issues or WordPress-only setups.

Whether you’re using WordPress, Webflow, Ghost, static HTML, or a custom-built platform, LinkStorm integrates seamlessly. 

Despite being external, it offers near-instant functionality. After inserting the HTML snippet on your website’s <head> element, all it takes is one click to accept a suggested link, and it embeds directly into your content. 

This combination of flexibility and usability makes it a great fit for teams managing content across multiple sites or platforms.

4. Gives you a bird’s eye view of your existing links

Another great feature of LinkStorm is that it displays all of your existing links, both internal and external links.

In addition, the tool can be configured to show insights pulled directly from Google Search Console, like average SERP rankings, impressions, clicks, and anchor text used per page.

Here is an example:

This dashboard view lets you spot missed opportunities, outdated links, and top-performing pages, all in one place. It’s a practical way to monitor the impact of your linking efforts and make informed decisions. 

5. See your anchor text distribution for appropriate action

Overusing the same anchor text can be risky, but most tools don’t show you how often a phrase is used or where. LinkStorm changes that. 

It breaks down your anchor text distribution (both internal and external links), so you can see patterns and take action where needed.

Clicking the numbers on the right shows the pages where those anchor texts originate. For instance, here are the pages using the anchor “cold emails”:

With this level of visibility, you’ll see which anchors need variety, catch anchor text overuse early, and fine-tune your linking strategy page by page.

6. Helps uncover SEO-damaging mistakes

LinkStorm goes beyond adding internal links. The tool also spots SEO-damaging mistakes on your website, including broken links ( helpful for broken link-building campaigns), redirects, and links marked with nofollow.

These problems often go unnoticed and can quietly chip away at your site’s SEO health. By bringing them to light, LinkStorm gives you a chance to fix them before they impact rankings or user experience. 

It’s a safety net that keeps your internal linking structure clean and effective.

Do You Need Internal Linking Automation?

Automated internal linking, while a huge leap toward the future, isn’t a must for everyone.

If you run a small website with a manageable number of pages, you can probably handle internal linking manually without much hassle.

It only becomes a necessity when you manage a large site with tons of content or multiple websites simultaneously. Automation can save you serious time and effort.

That’s where LinkStorm becomes a smart investment. It doesn’t limit you to a single site, so you can use it across all your projects under one plan. 

With pricing starting at just $30/month for up to 1,000 URLs, it’s a scalable and budget-friendly option for SEOs who want efficiency without sacrificing control.

Try LinkStorm now for 30 days FREE—no credit card required, no strings attached.

The post Automated Internal Linking: Everything You Need to Know appeared first on Linkody's Blog.

SEO mistakes are like termites in your walls. They stay silent, hidden, and slowly sabotage your SEO campaign from the inside while everything seems fine on the surface.

At least, that’s what I thought they were. 

But many websites do not share the same viewpoint. In fact, many SEO mistakes lists I’ve seen kept pointing out the obvious: Keyword stuffing, slow site speed, lack of mobile optimization, etc.

DUH! Are there even any websites in 2025 still not optimized for mobile? I don’t think so. 

The real SEO mistakes are not the glaring errors but the subtle ones. Those that feel right but quietly derail your efforts behind the scenes. 

In this article, we’re skipping the obvious and diving deep into the 10 most destructive SEO mistakes that often fly under the radar. Stay tuned!

1. Writing for the keyword, not the intent

One of the most persistent SEO mistakes that is still practiced in 2025? Obsessing over keywords while completely missing the intent behind them.

Ever since the Hummingbird update, Google’s algorithm has transcended from simply looking at keyword density and actually analyzing the context behind searches.

As such, it isn’t enough to sprinkle your target phrase 5 times in your blog post or use it in every H2. It must answer the actual question or need behind that search—that’s called search intent.

Otherwise, you’re just making noise that wouldn’t make it past SERP page 27.

Search intent falls into four buckets:

• Informational intent → the user wants to learn something (e.g., “is it okay to buy refurbished smartphones”)
• Navigational intent → the user wants to visit a specific website (e.g., “apple website” or “samsung website” or “gsmarena”)
• Commercial intent → the user wants to buy but is still comparing options (e.g., “best smartphones under $500” or “refurbished iphone 13 vs refurbished galaxy s23” )
• Transactional intent → the user is ready to take action (e.g., “buy refurbished samsung galaxy s24 ultra”)

If you’re targeting a keyword, it’s important to know two things:

1. The search intent of the query
2. The context behind the query

Let me explain:

Here’s an example of search intent mismatch: Say, you want to write an article for the keyword “buy refurbished iphone 13.” From the wording itself, you can easily see that the search intent is transactional, meaning the searcher is ready to buy the item. 

The SERP itself will be filled with websites selling the product and satisfying the transactional intent behind the query. 

You’re talking Apple, Amazon, CompAsia, and other phone recycling companies found on the web or local pack, as shown below:

Unless you also sell a refurbished iPhone 13 yourself, creating a post for this is pretty useless. 

But let’s just say you’re stubborn and wrote a blog post entitled “How to Buy a Refurbished iPhone 13?” Then, you filled it with a list of actionable tips on what aspects to look for in refurbished iPhones, complete with an introduction and conclusion.

Will it rank for the same query? Nope.

You wrote an informational-intent article to compete for a transactional-intent keyword. It was never going to work. 

Next, in addition to understanding the search intent, it’s also important to consider the context behind the keyword.

Here is an actual example of a context mismatch. 

There’s this company I used to write content for in 2021 that sells STEM toys for children. Take note, at the time, someone else handled the on-page SEO, and I only wrote the content (until she was let go, and I replaced her).

She asked me to write a blog post for the keyword “best investment gifts for kids.” 

Naturally, I had my complaints since we sell toys, not investments. But she had this idea to angle the article from the perspective that the STEM toys we were selling were an “investment” for the science-oriented future of the children. Okay.

So I wrote it:

Did it rank? It hardly got indexed.

If you look at SERP for the same keyword, all results talk about literal financial gifts that grandparents can bestow to their grandkids—college funds, Roth IRA, stock certificates.

No page talks about some toy they can buy that will magically instill scientific principles:

In other words, context matters. 

You can go all metaphorical or subliminal about your content, but Google will always treat it literally, just like every other result.

So, how do you avoid this SEO mistake? Just Google the target keyword and analyze the results. 

This will give you a well-rounded understanding about what type of content ranks and what insights to include. Then, just write a blog post in the same context as the results, but make yours better.

2. Neglecting ‘Experience’ in E-E-A-T

It’s no secret that AI has taken over content marketing, and Google hates it.

For the past years, Google has had a love-hate relationship with AI. 

They have initially voiced out that Google prioritizes content that’s written by people, for people. Some time later, Google changed its stance, expressing a more “inclusive” embrace of AI content.

But actions speak louder than words, right? If Google truly accepted artificial intelligence, it wouldn’t be recalibrating its algorithm to devalue content made using AI.

Case in point? Google started doubling down on what machines can’t fake: experience.

The new search rater’s guidelines, E-E-A-T, stands for experience, expertise, authoritativeness, and trustworthiness. While all four matter, experience is the one many websites overlook, especially in niches like product reviews, tutorials, or service comparisons. And that’s a problem.

Google’s evolving algorithm is now tuned to detect whether a real human has actually used the product or lived through the topic. 

Why? 

Because AI can summarize features, specs, or benefits pulled from the web. It can also rehash existing online reviews and create content using your own words, so it doesn’t feel regurgitated.

But it can’t really share what it feels like to unbox a gadget, troubleshoot an online tool, or taste a meal kit. 

One of the biggest SEO mistakes is asking AI to write an experiential content on a product you have never tried or a service you have never experienced.

Take a look at this really good makeup review:

Everything was detailed, from the unboxing to the materials used, even the dispense operation and faint smell were included. The screenshot doesn’t have it, but the author even included selfies showing how the makeup held up throughout the day.

AI can never replicate that kind of review, and that’s what Google wants.

Let’s say you’re writing a review on a standing desk. A generic, recycled piece might list out its dimensions, materials used, and motor speed. But content that ranks? It sounds more like:

• “After two weeks of use, I noticed less pain in my lower lumbar and had better posture. It is definitely a stark contrast from my old desk and monobloc.”
• “The motor is quiet enough that I don’t startle my cat, who’s used to sleeping on top of my desk while I’m working.”
• “Assembly took about 20 minutes since I did it alone, but if you had a friend with you, it would have been quicker and easier.”

These little details scream real experience, and Google eats that up. 

Without experience, your AI-generated “product review” will fall in Google’s bucket of lies, a.k.a. anywhere else except page 1 of SERPs.

So, how do you create content that demonstrates real experience? Experience it for real. Using AI is okay, as long as the insights, prompts, and experiences are all authentic. 

3. Thinking organic traffic is the end-all, be-all

Organic traffic is one of the most deceptive KPI that many SEOs fall into. Many marketers celebrate a spike in organic traffic, but overly fixating on it is one of the biggest SEO mistakes.

Here’s the hard truth: traffic without action is just a vanity metric.

If no one’s subscribing, buying, or signing up, what’s the point?

Organic traffic is only one part of the puzzle. It gets people in the door. But what happens after they land on your page is just as important, if not more. That’s where conversion optimization comes in.

Let’s break this down:

• High organic traffic + low conversions → wasted opportunity
• Moderate traffic + high conversions → efficient, ROI-driven SEO
• High traffic + high conversions → the dream

The problem is, many sites spend months chasing rankings without thinking about how they’ll turn those clicks into customers. 

To avoid falling into the “traffic trap,” here’s what you can do:

• Know your goal. Each page should have a dedicated purpose, whether that’s email sign-up, purchase, download, etc. Even informational-intent articles can have a CTA since there’s no rule against it.
• Optimize your CTAs. Clear, value-driven calls-to-action guide users toward the next step. Try doing some A/B tests to see which CTA works best for encouraging visitors to take your desired action. 
• Simplify the journey. Make forms short, checkout easy, and navigation intuitive.

Don’t let big traffic numbers become the end goal of your SEO campaign. SEO is a means to an end, not the end itself. If you’re not converting, you’re just creating a busy website, not a successful one.

4. Inadvertently or intentionally duplicating content

Duplicate content is one of those silent SEO killers that often goes unnoticed until your page drops in Google Search Console rankings.

Content duplication can happen accidentally or deliberately. The latter often happens when you intentionally replace stale content by publishing a newer piece without placing a 301 redirect, or simply just updating the old page.

Whichever the case may be, Google dislikes duplicate content because it is a clear indicator of content mismanagement or neglect. 

Plus, duplicate pages create keyword cannibalization—a case when two or more pages target the same keyword and satisfy the same search intent, creating a tug-of-war between your content. This confuses web crawlers about which page to canonicalize and prioritize for relevant queries.

So, how do you prevent or resolve this SEO mistake? Here are several ways:

First, establish a comprehensive content plan. Assign unique angles or keyword clusters to every blog post to avoid repetition.

Secondly, perform regular audits. Tools like Screaming Frog and Semrush can help you detect pages with overlapping content, which suggests possible duplication. 

Moreover, Keyword cannibalization tools, such as FeedMyRank, visually show which pages are cannibalizing for what keyword:

This makes it easier to track cannibalizing pages.

Finally, vet guest posts properly. Some authors don’t bother to check whether you’ve already covered the submitted guest post on your website. This can create near-identical blogs if you’re not careful. 

To prevent this, clearly indicate in your guest post guidelines that topics shouldn’t already be covered on your site, and, just to be safe, run submissions using Google search operators and plagiarism checkers to ensure authenticity.

Once cannibal pages are identified, consolidate the content into one stronger, updated piece, and set 301 redirects.

5. Forgetting to update older pieces of content

Piggybacking off #4, it’s easy to get caught up in publishing fresh content on the same topic, but it isn’t always necessary. You can revive stale posts gathering dust in your archives by simply updating the content, data, and insights to keep up with the times.

Another big SEO mistake is treating older content like they are set in stone. 

While it’s true—outdated pages slowly lose relevance, fall in rankings, and experience a decline in traffic over time, especially if competitors are publishing fresher, more up-to-date alternatives.

However, many site owners mistakenly create a brand new article covering the same topic as an older post, thinking that newer content equals better rankings. Not necessarily.

Moz once made this mistake, as shown in the screenshot below:

Moz published a blog post in 2019 that tackled “keyword cannibalization” and then recreated the same some time later.

And as we’ve pointed out earlier, re-publishing the same topic on a different page only leads to content cannibalization, which hurts your SEO further. 

The quickest fix to breathe new life into a stale page? Give it a well-needed update.

Updating older content can be just as powerful, if not more, than publishing something new.

Why it works:

• It signals freshness to Google
• It keeps previously built backlinks and established page authority intact
• It helps maintain your position in the rankings without having to reinvent the wheel

So, what are some actionable steps to update content?

• Cite more recent statistics. Avoid citing resources that are more than 3 years old unless you have to. Fresh statistics make your content appear more recent than it actually is.
• Update outbound links. If your post has several external links, make sure those destinations are still active. Almost half of all links lead to broken pages after 7 years due to link decay. By refreshing your external links, you ensure a good user experience for site visitors.
• Include more current examples. Using the COVID-19 pandemic as an example today wouldn’t be as relevant as it once was in 2020-2021. The same principle applies. Make sure your example aligns with the current events to make it look updated. 
• Build fresh internal links and backlinks. Links are access points for search engines to crawl a page. By adding more internal links and backlinks to a stale page, you’re urging web crawlers to revisit and re-index the updated page.

Updating content is a good habit to practice, but you know what’s better? Creating evergreen content from the start. These pieces of content stay relevant regardless of trends, staying valuable from year to year.

SEO is time-consuming as it is. To win the SEO race, you must be efficient. That means ensuring the longevity of old content, so it keeps working for you.

6. Having poor internal linking practices

Internal links are often the most neglected in the link-building family, with backlinks getting the most attention. However, while internal links seem like a minor detail, they are one of the most underrated SEO levers you can pull on your website.

As mentioned earlier, internal links are not just about connecting pages, but also serve as passageways for web crawlers. 

When Googlebot lands on a page, it follows the links to discover and index new content. So, if you published a new article but didn’t link to it from existing pages, it might remain invisible for weeks. Worse, never get indexed at all.

Here is a diagram showing how the Google indexing process works:

But that’s just the technical side.

Contextually relevant internal links also strengthen your website’s topical authority. 

When you link related content together, you’re building a “web of meaning” that helps search engines understand the depth and breadth of your knowledge in a given niche. These groups of interrelated content are called “topic clusters.”

Here is a hypothetical example:

And don’t forget about link juice. Internal links, much like backlinks, pass authority from the referring to the target page. 

So if you’ve got a high-performing blog post, you can use it to funnel ranking power toward newer or underperforming pages.

While manually building internal links is doable for a smaller website, this isn’t scalable when you start growing your business and publishing more content. 

This is where automated contextual linking tools, such as LinkStorm, come in.

Using AI and semantic analysis, LinkStorm automatically finds internal linking opportunities across your website on your behalf. All you have to do is accept (or reject) the suggestions, and they’ll instantly embed in your content.

Here is a screenshot of LinkStorm’s interface:

7. Not optimizing images

Image optimization often gets brushed aside as an afterthought, and this is a huge SEO mistake. Neglecting image optimization can undermine your SEO efforts and user experience.

Take note: optimizing images is not limited to shrinking file sizes to make your page load faster (though that’s part of it). True image optimization goes much deeper.

Let’s discuss them one by one:

Let’s start with the basics. Yes, your images should be compressed and in the right format (like WebP or JPEG) to keep load times snappy. Slow-loading pages can frustrate users and drag down your Core Web Vitals score, which Google considers a ranking factor.

There are plenty of free online tools for shrinking image sizes without sacrificing quality, like TinyPNG:

But technical tweaks aren’t enough. Many websites still make the mistake of including generic stock photos that add no real value to the content.

Look at this image:

What does it even mean? It’s a few people looking at some BS graphs that their production manager told them to hold. 

Many stock photos serve no other purpose than being visual fillers. Readers (and Google!) are getting better at recognizing when an image actually supports the content versus when it’s just… there.

Say, for instance, you are writing a product review. The real gold lies in experiential images:

• Photos of the product in your space
• Screenshots showing setup, usage, or results
• Side-by-side comparisons
• Annotated visuals to guide users through a process

These types of images build trust, enhance engagement, and signal authenticity, something stock photos can’t do. Use descriptive file names and alt text for additional SEO value. 

But what if you don’t have access to actual, authentic, original images?

Then grab images from external pages. It’s fine. Just make sure to properly attribute the original source. Just take a look at some of the images used in this article.

8. Mismanaging backlinks

Even after over 2 decades, backlinks still remain as SEO’s strongest signals. And if you aren’t actively building backlinks to your website, then you’re already committing an atrocity.

While backlinks are essential, they can also be one of the biggest liabilities if left unmanaged. 

Why?

Because not all backlinks are good backlinks.

Some backlinks can be toxic, which hurts your SEO more than helping it.

Here are the types of backlinks you want to avoid:

• Links from spammy directories
• Links from low-quality websites
• Links from irrelevant sources
• Links from websites with a high spam score

Worse, your website can fall to negative SEO attacks, where bad actors flood your site with spammy backlinks to tank your rankings.

There isn’t an easy way to monitor backlinks without an actual tool. Sure, plenty of free backlink checkers exist, but none of them provide you with a big picture of your backlink profile. The only option is to use paid tools. 

Thankfully, there’s a tool that helps you do just that without breaking the bank: Linkody. 

Linkody is a reliable backlink monitoring tool that gives you all the backlink information you need to take appropriate actions. Aside from listing your existing backlinks, Linkody also includes the following:

• Anchor text used
• Referring page URL
• Domain authority
• Follow attribute
• Spam Score
• Top-Level Domain

Here is an example screenshot of Linkody’s interface:

These insights give you headroom to decide whether to maintain or disavow a backlink from your profile.

9. Primarily focusing on SEO 

Let’s be very clear: SEO isn’t dead. But primarily relying on SEO as your only growth engine is a risky move in 2025.

While optimizing for search is still a smart, long-term strategy, don’t put all your eggs in this unpredictable basket. Google is shifting. With the rise of zero-click searches, especially in the advent of AI Overviews, fewer users are clicking through to websites.

In a podcast with Lex Fridman, Sundar Pichai, Google CEO, said AI Mode is the future of search, where Google will comprehensively answer the query, pretty much nullfying the purpose of the 10 blue links.

AI Mode is basically AI Overviews on steroids:

In many cases, Google provides tailored, comprehensive answers directly at the top of SERPs. This leaves high-ranking blog posts with a shiny #1 spot and a bunch of crickets. 

That’s why modern marketers are embracing omnichannel marketing strategies that go beyond SEO, such as:

• Email marketing → Build direct, reliable connections with your audience by landing straight in their inbox, which is perfect for nurturing leads and driving repeat visits without relying on algorithms. You can also do email marketing even with a tight budget.
• Social media marketing → Engage with your audience in real time, spark conversations, and amplify your content where your community already spends their time. 
• Video and podcast content → Tap into high-consumption formats that build trust, showcase expertise, and reach audiences beyond traditional search engines. 
• Pay-per-click advertising → Get instant visibility and drive targeted traffic by placing your message in front of the right people at the right time, no waiting for rankings.  

10. Not investing in the right SEO tools 

In 2025, SEO is no longer a guessing game. It’s a data-driven discipline that requires the right insights at the right time. And not having the right toolkit at your disposal is one of the biggest SEO mistakes you can commit.

Can you still succeed? Sure.

But it’s like trying to build a house with your bare hands—painful, unbearably slow, and likely to collapse (without you even realizing it because you have no tools).

Stop trying to wing it using free trials, outdated methods, or relying solely on gut instinct. SEO success hinges on precision. Precision ranges from knowing which keywords to target to spotting technical issues, and tracking what’s working and what’s not.

We’ve mentioned Linkody, LinkStorm, FeedMyRank, Screaming Frog, Semrush, and Ahrefs earlier, but they’re hardly the only tools out there that can support your SEO efforts. Here are a few others to consider:

• Google Search Console for sitewide metrics analysis
• Google Analytics for tracking the behavior of site visitor on your site
• Google PageSpeed Insights for optimizing website speed
• KWFinder for keyword research and more
• GMB Everywhere for local SEO

Aside from SaaS, you can also opt to download browser extension for SEO if you’re a little frugal in the budget department.

The Real SEO Threats are the Ones You Don’t See

So, there you have it—the 10 biggest SEO mistakes and how you can work around them. 

If you notice, many SEO issues don’t come from what you don’t do, but from what you think you’re doing right. Get it?

For example, writing for keywords instead of intent, or ignoring internal links to prioritize backlinks. 

These subtle missteps can quietly drag down your performance. Next thing you know, you’re left wondering why you fell 10 positions in search engine results.

The good news is you can fix, if not prevent them from happening. It starts with this list.

And SEO tools like Linkody make it easier, especially for managing your backlinks and keeping your backlink profile spam-free.

Try Linkody now for 30 days FREE—no credit card required, no strings attached.

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