A community is not simply a larger audience with a name attached. It is a group of people who find continuing value in a show’s perspective and have a reasonable way to take part. That can mean replying to a newsletter, attending a live conversation, recommending an episode, or contributing a question. The format matters less than the feeling that the show remembers why people came.
Pew Research Center’s work on how podcasts connect with audiences describes the many ways shows make themselves available and invite attention. A creator does not need to appear on every platform. The better choice is to identify one useful role for each channel. The audio feed delivers the core experience. A website offers durable references and search access. An email update can carry context that would be awkward to squeeze into an episode.
The promise should be specific. A history show might send source notes and corrections. A design interview program might share the guest’s recommended tools and one question worth discussing. A local news podcast might send a short guide to the public documents behind the week’s story. These ideas give listeners a reason to opt in without implying that the show will fill their inbox.
Write the promise in the signup form and keep it in the first message. If a show says it will send a thoughtful note after each episode, a daily stream of sponsor offers will feel like a bait and switch. Community grows when expectations are reliable. The language of the invitation should sound like the show, not like a generic growth campaign.
Ask questions that someone can answer from experience. Instead of requesting general feedback on the episode, ask which part they tried, disagreed with, or wanted explained further. A single focused prompt is easier to answer than a survey with ten boxes. Read replies as editorial material, not merely engagement metrics. They can reveal missing context, recurring confusion, and strong candidates for a future episode.
A reply deserves an acknowledgment when possible. For a small show, that may be a personal note. For a larger one, the host can summarize themes and explain what the team learned. If a listener contributes an idea that becomes an episode, seek permission before naming them. The aim is to show that participation affects the work, not to harvest free content from an audience.
Make it easy to decline. Some listeners want the show and nothing else. The audio feed should remain complete on its own. Supplementary material can deepen the experience, but it should not turn essential context into a reward for surrendering an email address.
Email gives a creator a direct way to deliver promised context without asking listeners to check a social platform at the right moment. It is particularly useful for material that benefits from being saved: sources, timestamps, event details, or a short essay expanding one idea from the episode. It also creates a channel for replies that public comment sections may not encourage.
When selecting newsletter software, a show should look for clear subscription records, simple segmentation by listener interest, and an easy way to see which issue prompted a response. Fancy automation is less important than a dependable sending process and a clean archive. If the show also sells merchandise or tickets, keep those offers distinct from editorial updates so the inbox still feels like an extension of the program.
A useful issue has a recognizable shape without becoming rigid. It might open with one observation that did not fit in the episode, give two or three links with a sentence explaining each, and end with a question. Another show may prefer a short letter. The format should be light enough to produce consistently and flexible enough to accommodate a quiet week.
Analytics can reveal where listeners start, where they leave, which episodes bring newcomers, and whether people return. Those signals are valuable, but they are not a script. A low completion rate may reflect a long introduction, a poorly labeled episode, or a topic that attracts casual curiosity. Listen to the episode again before concluding that the audience has rejected the idea.
Pew Research Center’s podcast audience research shows that listeners engage with shows in different ways. That is a reminder to measure more than one behavior. Some people listen closely and never click a link. Others save the newsletter and return weeks later. A small group may answer every question. Each form of attention can be meaningful without being interchangeable.
Use a simple monthly review. Choose one episode that performed above expectations and one that disappointed. Compare the topic, title, opening, length, and promotion. Then read a sample of listener replies or comments. Write down a hypothesis for the next experiment. Avoid changing five things at once, or the team will learn little from the result.
Participation needs boundaries. Tell people whether replies may be quoted, how to request anonymity, and who reads submissions. Do not imply that every note will receive a personal answer if the team cannot sustain that promise. If the show hosts a discussion space, publish rules about respect and moderation before conflict arrives. A well-run community is defined partly by what it will not ask members to tolerate.
Email deserves the same care. The Federal Trade Commission’s CAN-SPAM guide sets out requirements for commercial messages in the United States, including truthful sender details and a working opt-out. A creator should understand those basics before adding sales pitches to an editorial mailing list. Legal compliance is the minimum; respecting the invitation a listener accepted is the higher standard.
Do not expose a listener’s personal story simply because it would make a compelling segment. Ask what they are comfortable sharing and in what form. Some of the most thoughtful correspondence will be private. Treating it that way makes future participation more likely and keeps the show’s relationship with listeners grounded in trust.
Start with one invitation at the end of an episode: explain exactly what a subscriber will receive and where to sign up. Send a welcome note that delivers something useful immediately, perhaps a source list or a guide to the best starting episodes. Follow with a short note tied to the next release, then ask one question listeners can answer. Review the replies before planning a more elaborate program.
The point is to learn whether the promise is valuable enough to sustain. If few people subscribe, the offer may be unclear or unnecessary. If people subscribe but rarely open, the content may not match the promise. If they reply with questions, the show has found a path from broadcasting to conversation. Let those signals shape the second month.
A creator can also learn from what listeners do not say. If an episode about a specialized topic attracts new listeners but few return, the follow-up material may need a clearer path into the show’s broader themes. A short guide to related episodes can help. If longtime listeners respond to a guest but newcomers do not, a better introduction might supply the missing context. These are editorial choices informed by data, not commands issued by a chart.
For interview shows, prepare the post-episode material while researching the guest. Save the books, studies, and examples that come up in preparation. After recording, verify the links and ask the guest whether any recommendation needs correction. This produces a useful companion note without demanding a second round of research at publication time. It can also reduce the temptation to pad an issue with links that sound impressive but add little.
Keep a record of questions that recur across episodes. A creator may discover that listeners want more practical examples, shorter introductions, or a clearer distinction between evidence and opinion. Review that record quarterly and choose one change to test. The show still needs an editorial point of view. Listening to the audience is a way to sharpen that point of view, not hand every decision to the loudest respondent.
A podcast’s strongest asset is often the trust earned in someone’s ears over time. A newsletter, website, or discussion space can extend that trust, but only if each has a clear reason to exist. Give listeners something useful after the episode, listen when they answer, and make the next piece of work better because they did.
]]>General business applications rarely reflect the order variables found in promotional merchandise. A dedicated resource such as https://facilisgroup.com/ can account for product options, decoration methods, supplier schedules, artwork revisions, client approvals, shipping instructions, and changing quantities. Sales, service, production, and finance teams can work from shared information. Staff members spend less time adapting generic tools and more time managing the details that influence delivery, accuracy, and profit.
Order administration improves when each request follows a clear path. Product specifications, artwork files, pricing, delivery notes, and approval records stay connected throughout the transaction. Employees no longer need to search multiple inboxes or update several spreadsheets. Visible checkpoints expose missing information before production begins. That discipline helps prevent incorrect quantities, missed revisions, and costly delays from incomplete handoffs.
Sales representatives need dependable information before preparing a quote or recommending merchandise. A dedicated platform stores account history, previous purchases, open opportunities, product details, and pricing records in one place. Representatives can recognize buying patterns and respond more relevantly. Managers also receive a clearer view of pipeline movement, close rates, and forecasted income. Better records make follow-up more precise without creating extra reporting duties.
Production scheduling works best when available capacity, materials, labor, and promised dates are in one place. Dedicated software helps supervisors assign work according to actual resources and delivery requirements. Early visibility can expose a bottleneck before it affects a customer. In-house decoration teams also gain better control over artwork, job stages, and completed output. One reported result showed a 66 percent reduction in order processing time.
Billing delays often start with incomplete order details, incorrect charges, or late paperwork. Connected records can shorten those gaps by sending verified information to finance sooner. Staff members spend less time correcting invoices or requesting missing data. Payment status becomes easier to monitor, and managers gain a clearer view of unpaid balances. One reported outcome was a 14-day improvement in billing time.
Profit protection depends on current pricing, supplier terms, freight charges, and rebate information. A dedicated system keeps those figures visible before an order reaches production. Sales teams can quote from reliable data rather than outdated worksheets. Finance managers can review earnings by client, project, product type, or sales representative. Reported margin increases of 2 to 3 percent show how modest process gains can affect annual income.
Reports matter when they answer a practical management question. Purpose-built reporting can track processing time, repeat purchases, quote activity, production output, billing speed, and account profitability. Leaders can compare results by period, department, or client group. Those measures help identify weak points and set attainable targets. One reported comparison found five times greater year-over-year revenue growth than quarterly industry averages.
Expansion often exposes communication gaps between sales, service, production, warehousing, and accounting. A shared platform gives each department access to relevant updates while preserving role-based responsibilities. Employees can see progress, pending tasks, and ownership without relying on informal messages. New hires also receive a clearer view of daily procedures. Consistent coordination helps teams manage higher order volumes with fewer manual corrections.
Revenue can rise while internal procedures remain difficult to manage. Eventually, that imbalance strains employees and affects service quality. Dedicated software establishes repeatable steps for quoting, ordering, production, billing, and reporting. Standard processes help staff handle additional business without multiplying administrative corrections. Leaders can also see which accounts, services, or product categories deserve attention. Expansion becomes easier to measure because operating information follows a consistent format.
A purpose-built platform gives promotional product distributors practical control across the order cycle. Sales teams get faster access to account information, service representatives see complete records, production leaders manage capacity more accurately, and finance departments receive billing data sooner. Reported gains in processing time, billing speed, margins, and revenue growth indicate measurable operational value. For growing distributors, connected information can support reliable service without relying on staff memory for every additional order.
]]>The short version: if media flows directly between two browsers, your servers never see it. That is the entire selling point of peer-to-peer WebRTC, and it is also the reason server-side moderation cannot work on it. You cannot scan what does not arrive.
Most teams discover this after they have built the fast, cheap version.
For two participants, plain WebRTC is close to ideal. Signaling goes through your server, a session description gets exchanged, ICE candidates get gathered, and then the media stream establishes directly between the peers. STUN handles NAT traversal for most connections. TURN relays the ones that fail, which is typically somewhere between 8 and 20 percent depending on your user base and how many are behind symmetric NAT or corporate firewalls.
Your bandwidth cost for a successful P2P session is roughly zero. Your latency is the best you will ever get, because the packets are not making a detour.
Add participants and mesh topology gets expensive fast. Each peer maintains a connection to every other peer, so upload requirements scale linearly per client and connection count scales quadratically overall. Four participants is usually fine. Six is where laptops start getting warm. Eight is where you begin fielding support tickets about fans.
This is the point where teams move to an SFU, a Selective Forwarding Unit. Each client sends one stream up, the server forwards what each participant needs. Server bandwidth cost appears, latency increases slightly, CPU stays reasonable because the SFU forwards rather than transcodes.
An MCU mixes all incoming streams server-side into a single composited output. Bandwidth to each client drops to one stream, which is genuinely useful on poor connections. The cost is transcoding, which means CPU per room rather than bandwidth per room, and CPU is the more expensive resource by a wide margin.
| Topology | Server bandwidth | Server CPU | Media visible to server | Practical ceiling |
|---|---|---|---|---|
| P2P mesh | None | None | No | 4 to 6 peers |
| SFU | High | Low | Yes | 50+ peers |
| MCU | Moderate | Very high | Yes | Cost-limited |
That “media visible to server” column is the one that turns into a policy problem.
Post moderation is a solved shape. Content arrives, sits in storage, gets classified, and a decision happens before or shortly after publication. The latency budget is generous. You can queue, retry, and escalate to a human.
Live video has none of that. There is no artifact at rest, the harm happens during transmission rather than after it, and on a P2P connection the media never enters your infrastructure at all. Your options collapse to two.
Routing through an SFU gives you frames to classify. It also means accepting bandwidth cost per session, adding a hop of latency, and abandoning the claim that media is not touched by your servers, which is a real cost if privacy was part of your positioning.
Client-side inference keeps the P2P path intact. A model runs locally, flags frames, and reports metadata rather than content. It preserves the privacy story and adds no server bandwidth. It is also running on hardware you do not control, in an environment a determined user can tamper with, and the model has to be small enough to run in a browser tab without destroying frame rate.
Neither option is clean, and choosing between them is a product decision dressed as an infrastructure one.
Regulators have started treating live conversation platforms as in scope rather than adjacent. Ofcom’s June 2026 online safety bulletin recorded £2.17 million in penalties and five new investigations, two of them into chat services, examined over grooming risk and exposure to minors. One fine, £540,000 against 4chan, was specifically for failing to conduct an adequate illegal content risk assessment.
The relevant detail for engineers is that a risk assessment requires you to describe your moderation capability. “Media is end-to-end between peers and therefore unmonitored” is an accurate description of a P2P architecture and an unhelpful answer to a regulator.
Which means the architecture choice now carries compliance weight it did not carry three years ago. Consumer platforms in the one-to-one space, from language tutoring to a video call random girl service, sit in exactly this bracket, because their default session is two people and P2P is the obvious build.
What tends to hold up combines both approaches rather than choosing.
Keep P2P as the default path for the media itself, since it is cheapest and fastest and there is no reason to give that up. Run lightweight client-side classification on sampled frames, not every frame, reporting scores rather than images. Set a threshold that promotes a session to SFU relay when the client-side signal crosses it, so that server-side review only costs bandwidth on sessions that warranted it.
Then design the pre-session layer properly, because that is where most of the actual risk reduction happens and it costs nothing in latency. Age assurance before access. Video off or blurred until both parties act. Blocking that takes effect immediately rather than after a queue. None of that requires seeing a single frame.
The engineering instinct is to treat safety as something layered on after the media pipeline works. On live video that ordering does not survive contact with the problem, because the pipeline you build determines which safety options remain available to you. Deciding to relay media later means rebuilding the transport layer, and nobody has budget for that in the quarter a regulator asks.
Worth working out which topology you are committing to before the first user session, rather than after the first risk assessment.
]]>Unlike traditional PCs, the RTX Spark uses a single System-on-Chip based on the Grace Blackwell architecture. This means that all the CPUs, GPUs, neural processors, and shared memory operate within one power budget.
According to official specifications, NVIDIA RTX Spark consumes 240 W for the entire system. At the same time, the GB10 Grace Blackwell chip itself requires a TDP of 140 watts. The 100-watt difference is used for SSDs, networks, USB-C, and other components powered as required by the platform design. Therefore, NVIDIA recommends using the included power adapter.
To get the accurate figure on how many watts the chosen PSU must deliver to the system, start with defining the maximum power consumption of every PC component. Include everything it contains – CPU, GPU, motherboard, fans, peripherals, and others. Then, sum them up and add an extra 20-30% power headroom to easily upgrade your build in the future or replace some components without losing the PSU power. Keep in mind that the noted 20-30% is a guideline, not a strict rule, as every configuration may require specific headroom volume.
Also remember that headroom doesn’t mean that your PC will take these extra watts all the time. This figure simply provides the power supply with a reserve for peak loads and also allows it to operate within the range of highest efficiency.
Since modern GPUs can consume significantly more watts in just seconds, the PSU should keep up with not only the average loads but also peak system loads. The ATX 3.1 standard includes requirements for handling short-term power spikes for exactly this reason.
Transient power spikes last for a very short time, but even a few seconds is enough to exceed the typical GPU power consumption. If the power supply doesn’t have sufficient headroom or doesn’t meet current standards, this may cause various system issues, reboots, or trigger a protection mechanism. That’s why Seasonic engineers advise looking for those PSU that has enough power headroom specifically for such power-jump cases, and ATX 3.1 support for new NVIDIA RTX Spark systems.
The power supply unit for the NVIDIA RTX Spark system should deliver a stable 240 W, according to the official technical specification. For this type of power source, a more efficient PSU wastes less power while converting AC to DC. This is especially important for a compact system.
RTX Spark can dynamically adjust its power consumption based on CPU, GPU, and AI computing loads. A well-designed PSU must keep the output voltage within the required limits during load changes.
Low ripple is also important for the RTX Spark as part of its overall power quality. That’s why: a stable DC voltage without significant ripple gives the sensitive GB10 electronics a more stable power environment. In ATX 3.1, the maximum ripple for +12 V is 120 mV peak-to-peak, and for +5 V and +3.3 V, it is 50 mV.
The PSU specs for NVIDIA RTX Spark builds should align with concrete output power and connection specifications:
– Output voltage of 48 V DC is a key requirement for powering the DGX Spark. A standard ATX +12 V output cannot be connected directly to the system.
– Maximum current is 5 A. Combined with 48 V, this results in a rated power of 240 W, which corresponds to the DGX Spark’s stock power adapter.
– The cable must be rated to handle the required 48 V / 5 A and physically match the system’s connector. There’s a warning from NVIDIA about using adapters or cables not approved for the DGX Spark.
– The RTX Spark has four USB-C ports, but only one of them supports Power Delivery. The total power available via USB-C is limited to 30 W.
The power supply unit should have a built-in set of protection mechanisms – against overloads, overvoltage, overcurrent, short circuits, and overheating. This helps prevent damage to core system components and unexpected PSU shutdowns.
During intensive use when working with AI models, the PSU may operate near its rated load for extended periods. Therefore, it should deliver 240 W of power output and provide thermal headroom. NVIDIA recommends using the RTX Spark and its adapter in a well-ventilated environment with a temperature of 5–30°C.
Follow this step-by-step guide:
– Match the exact power requirements: a stable 240 W the PSU should deliver.
– Use an NVIDIA-approved adapter for optimal performance.
– Check connector and cable compatibility.
– Consider thermal conditions, as NVIDIA specifies an operating temperature range of 5–30°C for RTX Spark.
– For GB10 partner systems, check the OEM specification.
Choosing a PSU for the NVIDIA RTX Spark should be considered from all sides. Don’t look only at the rated PSU power, but also at its stability, efficiency, compatibility, and the ability to operate reliably under sustained load. A properly selected PSU provides a stable foundation for the productive and long-lasting operation of the entire system.
]]>This page breaks down the numbers marketers need for planning budgets and content in 2026: user counts, ad spend, platform-level data, and where engagement is actually happening.
User counts vary more than most other stats in this space because providers measure differently. Some count monthly active users per platform and add them up. Others count unique global identities. Neither method is wrong, but they produce different headline numbers.
| Metric | Figure | Source |
| Global social media users | 5.2 to 5.8 billion | Range across DataReportal-based reports |
| Share of global population | 64% to 70% | Range across sources |
| Average daily time spent | 2 hours 23 minutes to 2 hours 40 minutes | Sprout Social and other 2026 reports |
| Platforms used per month, average user | 6.75 to 8 | Sprout Social and other 2026 reports |
Source: Sprout Social, “120+ Social Media Marketing Statistics for 2026,” and related 2026 industry compilations.
The range exists because platforms overlap. Someone active on Facebook, Instagram, and TikTok counts as one identity in a global estimate but three separate monthly active users when platforms report their own numbers. For planning purposes, the more useful figure is usually time spent and platform-by-platform reach rather than a single global user count.
Ad spend data is more consistent across sources than user counts, since most trace back to the same handful of forecasting firms. Statista’s advertising market outlook projects worldwide social media ad spending will reach $338.75 billion in 2026, growing at an annual rate of roughly 11.86% through 2030, when it is expected to hit $530.34 billion.
The United States accounts for the largest single share of that spend, projected at $126 billion in 2026 according to the same Statista forecast. Mobile is where nearly all of that money goes. Statista projects mobile will account for 82.9% of total social ad spending by 2030, up from an already high base today.
Social commerce is a growing slice of this spend rather than a separate category. US social commerce sales are on track to pass $100 billion in 2026, according to eMarketer estimates cited across multiple 2026 industry reports, as platforms like Instagram and TikTok continue building out in-app checkout.
Platform self-reported numbers are the most reliable figures available, since they come from company earnings releases rather than third-party estimates.
| Platform | Users (2026) | Source |
| Meta Family of Apps (Facebook, Instagram, WhatsApp, Messenger) | 3.56 billion daily active people | Meta Q1 2026 earnings |
| ~3.1 billion monthly active users | Meta, via industry reporting | |
| ~2.3 billion monthly active users | Meta, via industry reporting | |
| TikTok | 1.6 billion+ monthly active users | Platform-reported estimates |
| YouTube | ~2.9 billion monthly active users | Platform-reported estimates |
Meta’s own Q1 2026 results, reported by CNBC, showed Family daily active people at 3.56 billion for March 2026, up 4% year over year. That quarter also marked Meta’s first sequential decline in daily active people, which the company attributed to internet disruptions in Iran and a WhatsApp access restriction in Russia rather than a broader drop in usage. It is a reminder that even the largest platforms are not immune to regional disruptions, and that quarter-over-quarter dips do not always signal a structural decline.
Adoption among marketers does not always mirror user counts. Facebook remains the most-used platform among marketers at roughly 83%, followed closely by Instagram at 78%, even though both platforms have shed some of the growth momentum they had a decade ago. YouTube trails close behind at around 69% to 70% adoption among marketing teams.
This gap between user growth and marketer adoption makes sense. Facebook and Instagram carry mature ad infrastructure, detailed targeting options, and large established audiences, which keeps them the default starting point for most budgets even as attention shifts toward newer formats on other platforms.
Reach and engagement are not the same thing, and the gap between platforms is significant. TikTok posts the highest average engagement rate among major platforms at roughly 5.38%, well ahead of Instagram at around 1.41%, LinkedIn at 1.84%, and Facebook and X both under 0.1%.
This matters for content planning. A platform with a large audience but a low engagement rate, like Facebook organic reach, generally needs paid support to move the needle, while a platform like TikTok can still generate meaningful organic engagement without the same ad spend behind it. Instagram Reels specifically outperform standard Instagram posts by a wide margin, generating roughly 2.6 times the engagement of static content.
Tracking social media’s business impact remains harder than tracking most other channels, largely because attribution spans discovery, consideration, and purchase across multiple platforms. When marketing teams do track ROI, they focus primarily on engagement, cited by around 68% of teams, followed by conversions at 65% and direct revenue impact at 57%.
Paid performance data offers a clearer signal than organic reach alone. Average return on ad spend on Facebook reached 2.79 during peak fourth-quarter periods, an improvement of roughly 11.6% year over year, showing that paid social continues to get more efficient even as organic reach on the same platforms keeps shrinking.
Customer expectations add pressure to treat social as more than a broadcast channel. Roughly 73% of consumers say they will switch to a competitor if a brand fails to respond to them on social media, which pushes response time and community management into the same performance conversation as ad spend and content strategy.
A few patterns are consistent across 2026 reporting:
The social media marketing statistics for 2026 point to a channel that keeps absorbing more ad budget even as user growth slows on the largest platforms. Meta’s own numbers show that scale does not make a platform immune to disruption, while TikTok’s engagement rate shows that reach and engagement are two different problems that need two different strategies.
For anyone planning a 2026 program, the practical takeaway is to treat platform choice as an engagement question first and a reach question second. The platforms with the biggest user counts are not always the ones producing the strongest engagement per post, and budget allocation should reflect that difference rather than defaulting to whichever platform has the largest audience.
Estimates range from about 5.2 billion to 5.8 billion people worldwide, depending on whether a report counts unique global identities or adds up monthly active users across platforms. Most reports agree the figure represents 64% to 70% of the global population.
Global social media ad spending is projected to reach $338.75 billion in 2026, according to Statista’s advertising market outlook, with the United States accounting for the largest single share at roughly $126 billion.
TikTok leads with an average engagement rate of around 5.38%, well ahead of LinkedIn (1.84%), Instagram (1.41%), and Facebook and X, which both sit under 0.1%.
Facebook remains the most-used platform among marketers at roughly 83%, with Instagram close behind at 78% and YouTube around 69% to 70%.
Yes, but growth has slowed. Meta reported 3.56 billion Family daily active people for March 2026, up 4% year over year, though that figure also marked the company’s first sequential quarterly decline, which it attributed to regional disruptions in Iran and Russia rather than a broader usage drop.
Automation adoption has climbed fast. HubSpot’s 2026 State of Marketing report found 86.4% of marketing teams now use AI in at least a few workflow areas, up from 67% in 2025 and just 41% in 2024. That is a 45-point jump in two years.
Reporting and analysis lead the way. HubSpot found 92% of marketers now use automation for data analysis and reporting, the single most common use case in the report. Content creation and media production follow, at 80% and 75%.
| Year | Marketing teams using AI in workflows |
| 2024 | 41% |
| 2025 | 67% |
| 2026 | 86.4% |
Source: HubSpot, 2026 State of Marketing report.
Only 1.7% of marketers report no AI use and no plans to adopt it, which puts holdouts firmly in the minority. Adoption at this scale is no longer a signal of a forward-leaning team. It is close to the baseline.
Company size still shapes how far that automation goes. Larger marketing teams tend to run more channels through automation at once, email plus social plus paid plus reporting, while smaller teams typically start with one channel, usually email, and expand only once that workflow is proven.
The 92% figure for reporting automation likely reflects this too: dashboards and reports are the easiest workflow to automate regardless of team size, which is why they lead every other use case.
Category revenue keeps climbing. Data from Statista shows global marketing automation industry revenue rose an estimated 12.6% to over $8 billion in 2024, with the market expected to grow more than 160% by 2032 to reach $21.7 billion. The marketing automation software segment alone brought in more than $5.9 billion in 2024.
Third-party market forecasts for this category vary widely, sometimes by a factor of five or more depending on how the researcher defines “marketing automation” and which adjacent categories, like AI agents or CRM, get folded in. Treat any single market-size figure as one estimate among several rather than a settled number.
The category itself is not new. Marketing automation as a defined software category dates to the mid-2000s, built to consolidate email, lead scoring, and campaign management into a single system. What has changed in 2026 is not the core idea, but how much of the execution now runs without a person triggering each step.
It also helps to separate two terms that get used interchangeably. Marketing automation, in its original sense, means scheduled or rule-based workflows: a welcome email sequence, a lead-scoring trigger, a drip campaign.
AI adds a layer on top of that: systems that adapt content, timing, or targeting based on what they learn, rather than following a fixed rule. Most of the growth in this category over the past two years has come from that second layer, not from more rules-based automation.
Email remains the anchor use case. Research from Ascend2’s State of Marketing Automation survey found 58% of marketers primarily use automation for email marketing, followed by 49% for social media management and 33% for content management.
Growth areas look different from current use. 29% of surveyed marketers are planning to add automation for social media management and paid ads over the next year, which suggests those categories are still catching up to email in maturity rather than replacing it.
Source: Ascend2, State of Marketing Automation.
This pattern makes sense given how automation platforms developed. Email was the first channel most tools automated well, and it remains the channel with the clearest, most measurable output, which keeps it at the center of most programs even as newer channels get added.
Automation is shifting from scheduled workflows to agents that act on their own. HubSpot’s 2026 data shows 19.2% of marketers are already using AI agents to automate marketing initiatives end-to-end, a small but fast-growing slice of the market.
Customer expectations are part of what is pushing this shift. Research from Salesforce’s State of Marketing report found 83% of marketers say customers now expect two-way, real-time conversations with brands, a bar that scheduled, one-way automation was never built to clear.
The gap between traditional workflow automation and full agentic automation is still wide. Most marketers today are running rules-based sequences, not autonomous agents, even as the 19.2% figure signals where investment is heading next. Expect that number to be one of the fastest-moving figures in this category over the next year.
Trust is the current bottleneck, not capability. Salesforce’s research found 81% of marketers say they would trust AI to respond to customers at scale, but most are blocked by disconnected data rather than a lack of confidence in the technology itself. That points to a data and integration problem sitting underneath the adoption numbers, not a willingness problem.
Measurement is the biggest blocker. HubSpot’s 2026 survey found measuring marketing ROI is the top challenge marketers report, cited by 33%, ahead of keeping up with platform changes at 29.8%.
Productivity gains are real but uneven. 26.5% of marketers say AI has significantly increased their productivity, while another 66.2% say it has increased productivity slightly or moderately. That means almost everyone reports some benefit, but only about a quarter call it transformational.
Data quality sits underneath both problems. The trust gap in the AI agents section above and the measurement gap here trace back to the same root cause: disconnected customer data across email, CRM, and ad platforms makes both hard to fix without first getting the underlying data pipeline in order.
The pattern across this data is consistent: tools are installed faster than teams can prove what they are worth. Fixing measurement, not adding more automation, is what closes that gap for most teams.
The marketing automation statistics for 2026 describe a category that has moved past the adoption question. With 86.4% of teams using AI in some workflow and 92% automating reporting, the tools are everywhere. What is not settled is proof of value: only 33% of marketers say they can reliably measure the ROI of what they have built, and AI agents, the next stage of automation, still sit at 19.2% adoption.
For planning purposes, treat this year’s data as a case for investing in measurement before adding more tools. Email remains the highest-maturity automation channel, agents are the fastest-growing one, and the gap between installing automation and proving it works is where most programs are currently losing ground.
86.4% of marketing teams use AI in at least a few workflow areas in 2026, according to HubSpot’s State of Marketing report, up from 67% in 2025 and 41% in 2024.
Global marketing automation industry revenue reached over $8 billion in 2024 and is projected to grow more than 160% by 2032 to reach $21.7 billion, according to Statista. Third-party estimates vary widely, so treat any single figure as one estimate among several.
Email marketing is the leading use case, cited by 58% of marketers, followed by social media management at 49% and content management at 33%, according to Ascend2’s State of Marketing Automation survey.
Not impossible, but it is the industry’s biggest current weak point. 33% of marketers name measuring marketing ROI as their top challenge in 2026, according to HubSpot, ahead of every other obstacle including keeping up with platform changes.
No, not yet. Only 19.2% of marketers currently use AI agents to automate campaigns end-to-end, according to HubSpot, meaning most automation in 2026 still runs on rules-based workflows rather than autonomous agents.
https://www.hubspot.com/state-of-marketing https://www.hubspot.com/marketing-statistics https://blog.hubspot.com/marketing/hubspot-blog-marketing-industry-trends-report https://www.statista.com/topics/10768/marketing-automation/ https://en.wikipedia.org/wiki/Marketing_automation https://backlinko.com/marketing-automation-stats
]]>This page collects the latest verified numbers on influencer budgets, creator pay, ROI, platform performance, AI use, and consumer trust. Most figures come from Influencer Marketing Hub’s 2026 Benchmark Report, a survey of 600+ marketing professionals, along with named data from CreatorIQ, Linqia, Aspire, IAB, and Forbes.
The industry has nearly doubled in three years.
| Metric | Figure | Source |
| Global influencer marketing value, 2025 | $32.55 billion | Influencer Marketing Hub, 2026 |
| Global influencer marketing value, 2022 | $16.4 billion | Influencer Marketing Hub, 2026 |
| US creator ad spend, 2026 forecast | $44 billion | IAB, 2026 |
| US creator ad spend, 2025 | $37 billion | IAB, 2026 |
Source: Influencer Marketing Hub, 35 Influencer Marketing Statistics, 2026, and IAB.
US creator ad spend grew 26% year over year, close to four times the growth rate of the wider media industry. Nearly half of creator ad buyers, 48%, now consider creators a “must buy” channel, placing influencer spend just behind paid search and social media in the budget conversation.
Confidence in the channel is running high, and the planned increases are large.
Source: Influencer Marketing Hub, 2026 Influencer Marketing Benchmark Report, and CreatorIQ.
A jump of 50% or more changes what a program needs to function. Brands cannot add that much spend on the same informal creator lists and spreadsheet tracking they used at a smaller scale. Rising creator costs are the top reported challenge, cited by 35.4% of marketers, ahead of every other single issue.
Most influencer work now happens inside the marketing team, not at an agency.
| Operating model | Share of brands |
| Entirely in-house | 66.33% |
| Hybrid (in-house plus agency) | 10.71% |
| Entirely agency-run | 10.71% |
| Do not run influencer marketing | 12.24% |
Source: Influencer Marketing Hub, 2026 Influencer Marketing Benchmark Report.
When brands do bring in outside help, they outsource the labor-intensive parts first. Creator discovery and vetting is the most commonly outsourced function at 19.44%, followed by content production at 15.28%. Reporting and analytics is the least outsourced task, at just 6.9%, which shows brands want to keep visibility into results even when they hand off the legwork.
Budgets are shifting toward smaller creators, not away from them.
Source: Influencer Marketing Hub, 2026 Influencer Marketing Benchmark Report.
Cost explains part of the shift. Around 80% of UGC creator rates fall under $500, along with about 55% of nano creator rates and 45.5% of micro creator rates. Macro and celebrity tiers show close to flat demand, with expansion and contraction intent nearly canceling out, which suggests most brands treat big-name creators as a selective layer rather than the daily production engine.
Rising budgets have not translated into even pay across the creator base.
Average creator earnings reached $11,400 in 2025, but the median was only $3,000, according to Forbes, which tracks the industry’s biggest names separately in its annual Top Creators ranking. The top 10% of creators receive 62% of all creator payments, and the top 1% alone receive 21%.
Total creator payments grew 59% year over year. The number of creators participating in campaigns grew 183% in the same period, which means supply is expanding faster than the money paid out. Two other numbers matter for anyone negotiating a rate: 99% of creators say creative control is important when working with brands, and 77% of brands now repurpose creator content in paid advertising, with 67% including usage rights directly in the original contract.
Influencer marketing earns a strong headline return, but proving it stays hard.
Source: Influencer Marketing Hub, 2026 Influencer Marketing Benchmark Report, and Linqia.
Promo codes remain the most common tracking method, used by 45.9% of marketers, ahead of affiliate links at 26% and native shopping features at 25%. Each method has blind spots. Codes can be shared outside the creator’s own audience, and links can miss purchases that happen on a different device or days later.
AI now touches most influencer programs, but marketers still limit where it operates.
95% of surveyed brands use AI somewhere in their creator workflow, according to CreatorIQ. The leading applications are caption generation at 45%, research at 44%, and video or graphic editing at 41%. Inside the influencer-specific workflow measured by Influencer Marketing Hub, creator discovery leads AI use at 36.67%, followed by content generation at 21.11% and brief development at 13.89%.
Trust drops sharply once AI moves into judgment calls. 89% of enterprise marketers avoid virtual influencers entirely, and fraud detection is one of the least automated tasks in the workflow, at just 7.22% adoption. Investor interest in virtual creator platforms keeps growing even so, as reported by TechCrunch, which points to a gap between where brands say they are comfortable and where the technology is heading.
The two platforms lead in different ways.
| Platform | Metric | Figure |
| TikTok | Most selected for 2026 investment intent | 31% |
| Brands currently using it for creator marketing | 85% | |
| Perceived ROI leader | 29% | |
| TikTok | Perceived ROI leader | 27% |
| TikTok | Median creator engagement rate | 7.4% to 8.1% |
| Instagram Reels | Median creator engagement rate | 4.5% to 7.9% |
Source: Influencer Marketing Hub, 2026 Influencer Marketing Benchmark Report, CreatorIQ, and an analysis of more than 5 million creator accounts by The Influencer Marketing Factory.
Video leads every other content format on effectiveness. 83% of marketers rank long-form video among their three most effective formats, and 80% say the same for short-form video. Social commerce is also concentrated on one platform: 32% of brands already sell through TikTok Shop, and another 25% plan to start.
Purchase influence and trust do not move together.
Source: BBB National Programs, Influencer Trust Index study, cited by Influencer Marketing Hub.
The pattern here is consistent. Consumers do not expect sponsorships to disappear. They expect the sponsorship to be disclosed and the opinion inside it to sound genuine rather than scripted.
The influencer marketing statistics for 2026 point to a channel that has matured past the experimental stage. Budgets are expanding fast, most programs run in-house, and spending is shifting toward nano, micro, and UGC creators rather than a handful of expensive names. AI has taken over the repetitive parts of the workflow, but marketers are still keeping judgment calls, fraud checks, and virtual creator decisions close to human review.
The open challenge is proving return at the pace budgets are growing. Attribution gaps and rising creator costs mean the next phase of influencer marketing will be decided less by who spends the most and more by who can measure results well enough to defend the spend.
The global influencer marketing industry reached an estimated $32.55 billion in 2025, according to Influencer Marketing Hub. In the US alone, creator ad spend is forecast to hit $44 billion in 2026.
Brands report an average return of $5.78 for every $1 spent on influencer marketing. Despite that strong headline number, 79% of enterprise marketers say they still struggle to measure ROI accurately.
Yes. 87.49% of marketers expect their influencer budgets to increase this year, and 72.22% expect that increase to be 50% or more. Only 5.55% expect a decrease.
Brands are shifting toward smaller creators. Over half of marketers plan to increase or start using nano and micro influencers, while demand for macro and celebrity creators has stayed close to flat.
Average creator earnings were $11,400 in 2025, but the median was only $3,000. The top 10% of creators receive 62% of all creator payments, which shows pay is heavily concentrated at the top.
Not yet, in most cases. 95% of brands use AI somewhere in their creator workflow, mainly for discovery, captions, and editing, but 89% of enterprise marketers still avoid virtual influencers for brand-facing campaigns.
Trust is limited but purchase influence is real. Only 5% of consumers completely trust influencer content, yet 55.5% have bought a product because of an influencer endorsement, and disclosed partnerships build more trust than hidden ones.
https://influencermarketinghub.com/influencer-marketing-statistics https://influencermarketinghub.com/influencer-marketing-benchmark-report https://www.forbes.com/sites/pr/2026/06/23/forbes-unveils-2026-top-creators-list-as-collective-earnings-surpass-1-billion-for-the-first-time/ https://www.iab.com/news/creator-economy-ad-spend-to-reach-37-billion-in-2025-growing-4x-faster-than-total-media-industry-according-to-iab/
]]>This page pulls together the numbers that matter for planning an email program in 2026: revenue and ROI, open and click benchmarks by industry, automation performance, and where the channel is headed next.
Email marketing ROI is usually reported one of two ways: as a single point estimate, or as a range self-reported by marketing teams. Both show the same pattern. Email consistently outperforms paid search, paid social, and display.
| Metric | Figure | Source |
| Average ROI, all industries | $36 to $42 per $1 spent | Litmus, Omnisend, industry aggregates |
| Retail and ecommerce ROI | $45 per $1 spent | Industry benchmark studies |
| Paid search ROI, for comparison | $2 per $1 spent | Industry benchmark studies |
| Marketing teams reporting 36:1 to 45:1 ROI | Self-reported band | Litmus State of Email 2026 |
Source: Litmus, State of Email 2026 report, self-reported survey of marketing leaders, United States and global.
Litmus asks marketers to self-report their ROI in bands rather than a single number, which is why its data looks different from platform-specific figures. Its 2026 survey found teams reporting returns anywhere from 1:1 up past 45:1, with a meaningful share landing between 20:1 and 45:1. Litmus also found that advanced AI adopters were 75% more likely to land above 45:1, which lines up with the wider trend of AI-assisted personalization pushing returns higher.
Platform-reported figures tend to run higher than the industry average. Omnisend reported that its merchants on paid plans averaged $76 to $79 per $1 spent in 2025, well above the general benchmark. Read platform-specific numbers with some caution, since they reflect only that platform’s customer base, not the market as a whole.
Email is not shrinking. Around 4.6 billion people worldwide used email in 2025, and that figure is projected to climb toward 4.8 billion by 2028, according to Radicati Group data published through Statista. That is more than half the global population.
Volume is climbing alongside the user count. Global daily email traffic is estimated in the range of 376 to 392 billion messages a year over year, and the growth rate has held at roughly 3% to 4% annually for several years running. For marketers, this means the inbox is more crowded than ever, which raises the bar for subject lines, timing, and relevance.
Benchmark reports disagree on exact numbers because each provider measures a different pool of senders. Two of the most cited sources, Mailchimp and Klaviyo, land in different places.
| Provider | Sample | Open rate | Click rate |
| Mailchimp | All-user historical benchmark | 35.63% | 2.62% |
| Klaviyo | 183,000 ecommerce brands, published Feb 2026 | 31% | 1.69% |
| MailerLite | 3.6 million campaigns, 2026 report | 30.1% to 55.71% by industry | 2.09% average |
Source: Mailchimp Email Marketing Benchmarks; Klaviyo 2026 Email Marketing Benchmarks by Industry; MailerLite Email Marketing Benchmarks 2026.
MailerLite’s industry breakdown shows the widest spread. Religion, hobby, and non-profit senders post the highest open rates, all above 52%, while travel and ecommerce sit near the bottom at 30% to 33%. This pattern holds across most benchmark reports: subscribers who signed up out of personal interest open more than subscribers who signed up for a discount code.
One caveat applies across every open rate figure here. Apple’s Mail Privacy Protection preloads tracking pixels for a share of Apple Mail users, which inflates reported opens regardless of whether a human actually read the message. Click rate and revenue per email are more reliable signals of real engagement than open rate alone.
Automated emails punch far above their weight. Klaviyo’s 2026 benchmark data found that automated flows generate about 41% of total email revenue while accounting for only around 5% of total sends. Flow click rates also run higher than campaign click rates, at 5.58% versus 1.69%.
This gap exists because automated flows, such as welcome series, cart abandonment, and post-purchase follow-ups, reach people at a moment of clear intent. Automation tools, according to research from Wikipedia, let marketers schedule and send messages based on specific user actions rather than a fixed calendar, which is part of why these emails convert at a higher rate than one-off campaigns.
The practical takeaway is straightforward. A program built mostly around scheduled newsletters is leaving revenue on the table if it has not built out welcome, abandonment, and post-purchase flows. These automations require setup once and then keep generating a disproportionate share of revenue with little ongoing effort.
Getting an email opened depends on more than subject lines. Deliverability benchmarks from GetResponse’s dataset of 4.4 billion messages found an average bounce rate of 2.33% and a spam complaint rate under 0.01%, figures worth checking against before assuming a drop in opens is a content problem.
Mobile now dominates how people read email. Roughly six in ten email users check their inbox mainly on a mobile device, which affects everything from subject line length to how emails render. A message that looks fine on desktop but breaks on a phone screen loses the reader before the content ever gets read.
Unsubscribe rates offer a useful health check separate from opens and clicks. Benchmark reports generally put a healthy unsubscribe rate at 0.1% to 0.3% per campaign, with anything above 0.5% signaling a mismatch between send frequency and what subscribers actually signed up for.
A few patterns show up consistently across 2026 reporting:
The email marketing statistics for 2026 point to a channel that keeps earning its place in the budget. ROI remains far ahead of paid search and paid social, the user base keeps growing, and automation continues to deliver outsized returns relative to the effort required to set it up.
The gap between top and average performers comes down to a few specific choices: building out automated flows instead of relying only on scheduled sends, tracking click and revenue metrics instead of open rate alone, and applying AI tools to personalization and send timing rather than content alone. Programs that make those choices are the ones showing up in the higher ROI bands in every 2026 benchmark report.
Around 4.6 billion people worldwide used email as of 2025, a figure projected to grow to roughly 4.8 billion by 2028, according to Radicati Group data published through Statista. That is more than half the global population.
Most industry sources place the average return between $36 and $42 for every $1 spent. Retail and ecommerce brands tend to do better, averaging around $45 per $1, while some platform-specific cohorts report even higher returns.
A good open rate typically falls between 30% and 40%, though this varies widely by industry, from around 30% for travel and ecommerce senders up to 55% or more for religion and non-profit senders. Apple’s privacy changes have made open rate a less reliable metric than click rate or revenue per email.
Yes. Automated flows generate a disproportionate share of email revenue, around 41% from just 5% of total sends according to Klaviyo’s 2026 benchmark data, and they post higher click rates than one-off campaigns because they reach people at a specific moment of intent.
Yes, based on ROI data. Email consistently outperforms paid search and paid social by a wide margin, and teams using AI for personalization and send-time optimization report even stronger returns than the industry average.
Content marketing adoption among B2B teams is close to universal. The Content Marketing Institute and MarketingProfs surveyed 1,015 B2B marketers, drawn from a global pool of 1,229 respondents, between June and August 2025 for their 16th annual B2B Content and Marketing Trends report. Ninety-seven percent said they run from some kind of content strategy, documented or informal, the highest rate recorded in the survey’s history.
Adoption is not the same as commitment. A documented, written strategy still separates the teams that plan from the teams that just publish, and CMI’s own data shows that gap drives most of the difference in results below.
| Metric | 2026 figure | Source |
| Run from a content strategy | 97% | CMI |
| Rate content marketing as effective | 59% | CMI |
| Use AI-powered marketing tools | 95% | CMI |
| Use video as a marketing tool | 91% | Wyzowl |
Source: Content Marketing Institute, B2B Content and Marketing Trends: Insights for 2026 (fielded June 24–August 14, 2025, n=1,015); Wyzowl, State of Video Marketing 2026.
Investment intent is strong for 2026, even with budgets tight everywhere else in marketing. CMI’s data shows AI tools as the top planned investment area, with 45% of B2B marketers planning to spend more there. Events and experiential marketing follow at 33%, and owned media sits at 32%.
Human talent tells a different story. Only 9% of B2B marketers plan to increase investment in human resources, covering salaries, training, and development, making it the lowest-ranked category in the survey. Budgets are moving toward tools faster than they are moving toward the people who operate them.
Source: Content Marketing Institute, B2B Content and Marketing Trends: Insights for 2026.
This spending pattern only makes sense next to the effectiveness numbers below. Betting on tools while starving the team that runs them is a bet that AI can substitute for headcount, not just support it.
Effectiveness has not kept pace with adoption. CMI found 59% of B2B marketers rate their content marketing as somewhat or highly effective, but only 12% call it highly effective. That means most programs are getting partial credit, not full marks.
Among marketers who do call their program effective, content relevance and quality is the leading reason, cited by 65%. Team skills and capabilities rank second at 53%, followed by sales alignment at 45% and technology and tools at 43%. Sixty-one percent of marketers with a content strategy said their strategy’s effectiveness improved over the prior 12 months, which suggests the gap is closing, just slowly.
The pattern is consistent: quality and people outrank tools as drivers of success, even in a year when tool spending is rising fastest. Teams chasing effectiveness gains through software alone, without matching investment in strategy and skills, are working against what the data shows actually moves the needle.
AI tool use among B2B marketers reached 95% in CMI’s 2026 survey, up sharply from prior years and now effectively universal. That scale of adoption makes AI use a baseline expectation rather than a differentiator on its own.
Results have not caught up to adoption. Fewer than 40% of B2B marketers say AI tools are actually improving their performance, based on CMI’s 2026 data. Adoption is easy. Turning that adoption into measurable output is where most teams are still stuck.
Personalization shows the same lopsided pattern. Eighty-five percent of B2B marketers who use personalization apply it in email, the most common channel by far, while only 33% apply it on websites and landing pages. Account-based marketing tells a more positive story for the marketers who commit to it: 65% of B2B marketers using ABM say their campaigns outperform traditional marketing, even though most B2B marketers still operate without ABM at all.
Search itself has changed shape. Google’s AI Overviews reached more than 2.5 billion monthly active users as of its May 2026 I/O keynote, according to CNBC, putting AI-generated summaries in front of a majority of search users before they ever reach a traditional list of links. That shift is a big part of why content teams are rethinking what “ranking” even means this year.
Enterprises are leaning further into AI heading into 2026, according to TechCrunch, which surveyed enterprise-focused investors who expect this to be the year AI adoption moves from pilot projects to measurable business value. Content teams are part of that wider shift, not separate from it.
Distribution is spreading across more channels than it used to. CMI’s data shows in-person events (52%), webinars (51%), social media (42%), and company blogs (41%) as the most effective B2B distribution channels in 2025. Events and webinars now outperform blogs, a shift from the blog-first playbook most teams built their strategy around a few years ago.
Video keeps taking a bigger share of that mix. Wyzowl’s 2026 State of Video Marketing report found 91% of businesses now use video as a marketing tool, matching an all-time high, with 93% of those calling it an important part of their strategy. Reported ROI dipped slightly to 82% from 93% the year before, which points to more teams producing video of uneven quality rather than video itself losing effectiveness.
The content marketing statistics for 2026 point to a channel that has finished proving itself and is now sorting into winners and laggards. Adoption is close to universal, at 97% for having any kind of strategy and 95% for using AI tools, but effectiveness sits at just 59%, and only 12% of teams call their program highly effective.
Budgets are chasing AI tools faster than they are chasing skills, even though quality and team capability, not software, are what marketers who succeed actually credit. For planning purposes, treat this year’s data as a signal to invest in strategy and people alongside any new tool, not instead of them. The gap between adoption and results is where most programs are currently losing ground, and it is unlikely to close on its own.
97% of B2B marketers run from some kind of content strategy, documented or informal, according to the Content Marketing Institute’s 2026 survey of 1,015 B2B marketers. That is the highest adoption rate recorded in the survey’s 16-year history.
Yes, for most teams, though results are uneven. 59% of B2B marketers rate their content marketing as somewhat or highly effective, but only 12% call it highly effective, according to CMI’s 2026 data.
AI tools are the single biggest planned investment area for B2B marketers in 2026, with 45% planning to increase spending there, more than any other category including events, owned media, or headcount.
No, blogging is down in relative importance but not dead. CMI’s data still ranks company blogs among the top distribution channels at 41%, behind events and webinars, while Google’s AI Overviews now reach 2.5 billion monthly users, which is reshaping how blog content needs to be structured rather than replacing it outright.
No, video is growing but running alongside written content, not replacing it. 91% of businesses use video as a marketing tool per Wyzowl, while CMI’s data shows blogs and written formats still hold a meaningful share of B2B distribution at 41%.
https://contentmarketinginstitute.com/b2b-research/b2b-content-marketing-trends-research https://stats.conversationalgeek.com/analysis/content-marketing-institute-2025-b2b-marketing https://stats.conversationalgeek.com/analysis/content-marketing-institute-2025-marketing-effectiveness https://www.marketscale.com/industries/marketing-tech/b2b-content-marketing-in-2026-ai-adoption-is-near-universal-but-performance-gains-are-not https://wyzowl.com/video-marketing-statistics/ https://blog.google/innovation-and-ai/sundar-pichai-io-2026/ https://www.cnbc.com/video/2026/05/19/google-ceo-pichai-ai-overviews-now-has-over-2-point-5-billion-monthly-users.html https://techcrunch.com/2025/12/29/vcs-predict-strong-enterprise-ai-adoption-next-year-again/
]]>This page pulls together the latest verified numbers on video adoption, ROI, platform performance, AI use, and consumer behavior. Every figure below comes from the organization that published it, mainly Wyzowl’s 2026 State of Video Marketing report and HubSpot’s 2026 State of Marketing report.
Adoption has climbed back to an all-time high after a small dip in 2025.
| Metric | Figure | Source |
| Businesses using video as a marketing tool | 91% | Wyzowl, 2026 |
| Marketers who see video as an important strategy piece | 93% | Wyzowl, 2026 |
| Non-users who plan to start video in 2026 | 67% | Wyzowl, 2026 |
| Businesses using video in 2016 | 61% | Wyzowl, 2026 |
Source: Wyzowl, Video Marketing Statistics 2026, surveyed 266 respondents in late 2025.
The 9% of businesses still not using video mostly cite cost or time, not doubt about results. Both “not needed” and “too expensive” tie at 24% as the top reasons for skipping video. Only 10% say they are unclear on video’s ROI.
Adoption has grown steadily for a decade. It went from 61% in 2016 to 91% today. That is a near 50% increase in nine years.
Live action video remains the most common format, but the mix is broader than most people expect.
| Video type | Share of marketers |
| Live action | 51% |
| Animated | 23% |
| Screen-recorded | 19% |
Source: Wyzowl, Video Marketing Statistics 2026.
Social media video is the single most common use case, cited by 69% of video marketers, just ahead of explainer video at 68%. Testimonial video follows at 57%, then presentation video and video ads tied at 48%. Product demos, sales videos, and training videos each sit in the 20% to 40% range, which shows most teams are producing several video types at once rather than betting on one format.
Production has shifted in-house. 59% of marketers create their video content themselves, without an outside vendor. Only 10% rely exclusively on external production, and the remaining 32% use a mix of internal teams and agencies depending on the project. Cheaper cameras, editing software, and AI tools have made in-house production realistic for teams that once needed an agency for every video.
Yes, according to marketers who use it. 82% report a good return on their video investment in 2026. That is down from an all-time high of 93% the year before, but it still shows a strong majority getting results.
Video also drives measurable outcomes across the funnel:
Source: Wyzowl, Video Marketing Statistics 2026.
Marketers track ROI in different ways. Views lead at 67%, followed by engagement metrics like likes and shares at 63%, then leads and clicks at 52%. Only 32% tie ROI directly to bottom-line sales, which suggests many teams still measure video by attention rather than revenue.
YouTube remains the platform marketers use most and rate as most effective.
| Platform | Usage | Rated effective |
| YouTube | 82% | 69% |
| 70% | 50% | |
| 69% | 56% | |
| 66% | 55% | |
| Webinars | 56% | 42% |
| TikTok | 40% | 29% |
Source: Wyzowl, Video Marketing Statistics 2026.
TikTok sits low on both usage and effectiveness compared to the older platforms. Snapchat, X, VR, and 360 video round out the least-used and least-effective list. These platforms have large audiences but have not converted that scale into strong marketer results yet.
Short-form video is the format marketers reach for most.
HubSpot’s 2026 State of Marketing report found short-form video is the most used content format among marketers, cited by 60% of respondents. It also drives the highest ROI of any format. Short-form, long-form, and live-streaming video rank as the top three ROI-driving content formats overall, at 49%, 29%, and 25%.
Length still matters. 71% of marketers say videos between 30 seconds and two minutes work best.
Video length changes engagement too, according to Wistia’s analysis of videos hosted on its platform:
Shorter is not automatically better for every goal. Longer videos still hold viewers for more total minutes, which matters for training or in-depth product content.
AI tools have moved from experiment to standard practice in video production, as reported by TechCrunch.
63% of video marketers say they have used AI tools to help create or edit marketing video in 2026. That is up sharply from 51% just one year earlier. Wyzowl expects this share to keep climbing as AI video tools mature.
Separately, HubSpot found close to 75% of marketers use AI for media creation broadly, including video and images. The most common AI video use cases are smart video and audio editing (42%) and dedicated video or animation generators (44%).
Budgets are holding steady or growing, even as marketers debate whether production costs are rising.
Source: Wyzowl 2026 and Statista, cited in HubSpot’s 2026 Marketing Statistics report.
On the cost question, opinion is split. 38% of marketers say video production costs are rising, 32% see no change, and 30% say costs are actually falling as tools get more accessible.
Most marketers keep video spend modest relative to total budget. 46% put a third or less of their marketing budget toward video content, and 17% admit they are not tracking video spend closely enough to know.
Consumer behavior backs up what marketers report on their end.
Source: Wyzowl, Video Marketing Statistics 2026.
When consumers were asked how they would prefer to learn about a product, 63% chose a short video over every other option. Text articles came in a distant second at 12%.
The video marketing statistics for 2026 tell a consistent story. Adoption sits at an all-time high of 91%, ROI remains strong even after a slight dip, and consumers keep rewarding brands that invest in quality video. Short-form content and AI-assisted production are now standard parts of the workflow, not experiments.
For any team weighing video against other formats, the data points one way. Video drives awareness, leads, and sales at a higher rate than marketers report for most other content types. The open question is not whether to use video, but how to keep quality high as more competitors flood the same platforms with content.
Meta description: Video marketing statistics for 2026: adoption, ROI, platform data, AI use, ad spend, and how video shapes buying decisions.
91% of businesses use video as a marketing tool in 2026, according to Wyzowl’s annual survey. This ties the highest adoption rate the report has recorded in 12 years of tracking.
Yes. 82% of marketers report a good ROI from video, and most say it has increased brand awareness, leads, sales, or website traffic. Results vary by execution quality, so consistent, well-targeted video performs better than occasional, unplanned content.
Most marketers, 71%, say videos between 30 seconds and two minutes perform best. Shorter videos under one minute get the highest average engagement rate, around 50%, but longer formats still suit training or in-depth product walkthroughs.
YouTube is both the most used platform, at 82% of marketers, and the one most marketers rate as effective, at 69%. Instagram, Facebook, and LinkedIn also rank highly for both usage and results.
Yes, 63% of video marketers used AI tools to help create or edit video in 2026, up from 51% the year before. AI is most commonly used for editing and for generating short animated or promotional clips.
41% of marketers spent money on video ads in 2025, and global video ad spend is projected to top $236 billion in 2026. Most marketers, 92%, plan to keep spending the same or more on video through the rest of the year.
https://wyzowl.com/video-marketing-statistics/ https://www.hubspot.com/marketing-statistics https://wistia.com/learn/marketing/video-marketing-statistics https://www.statista.com/outlook/dmo/digital-advertising/video-advertising/worldwide
]]>