Like many things in life, the VC/startup ecosystem is one of cycles. Looking back over the last decade it’s remarkable to see how the emphasis has shifted across cycles and what the overarching narrative was.

I believe we are in a denouement (the final part of a play, movie, or narrative in which the strands of the plot are drawn together and matters are explained or resolved) that will both signal a high water mark for many startups but also create an opportunity for patient, early investors who can think and act independently (more on this below). But let’s look back at the last decade in VC-backed startups… it’s easy to forget how predominant mindsets change throughout the cycle.

2009-2011: Retrenchment

The world is experiencing a global economic crisis of a proportion most living people have never witnessed. We’re only a few months past Sequoia’s famous “R.I.P. Good Times” presentation (Oct 2008).

VC funding for startups is drying up quickly. Aggregate VC investment in 2009 hits a low of roughly $20B, a figure last seen in 2003 in the wake of the bursting of the dotcom and telecom bubble and 2001 recession. Companies are retrenching, VC firms are going through their own upheavals, and IPOs are non-existent. Survival is the order of the day.

But there is also opportunity in lean times. Uber is founded and AirBnB goes through YC in 2009. Seed investing, as a distinct and truly enduring segment of the VC ecosystem, emerges during this period.

2012-2016: The Era of Blitzscaling

Somewhere in this period the word “blitzscaling” enters our lexicon, via Reid Hoffman’s class at Stanford and subsequent book. If you understand the premise of blitzscaling, it’s not truly growth at any and all cost… it’s a strategic mindset for building a company from scratch at previously unheard pace specifically where digital innovation enables capturing a large addressable market.

But during this period, many founders and investors do prize growth above most everything else. Year over year revenue growth rates are measured in multiples not percentages. Razor thin or negative gross margins are accepted (or even ignored) on the widely accepted view that growth and market share are what really matters in terms of value creation.

Facebook goes public in 2012 and Twitter in 2013. But overall this is a period where the IPO market remains largely closed to VC-backed startups. And even Facebook has a shambolic first day of trading and trades below its IPO price for over a year. During these years you do see the rise of  “cross-over” investment in private companies by large public market investors like Fidelity, T. Rowe Price, hedge funds, etc. Late stage rounds help keep companies private longer and eventually Facebook proves to be a blockbuster company… public equity investors hope to find the next Facebook pre-IPO.

On paper, VC portfolios perform well. Secondary transaction liquidity also starts to become a reality for founders and early investors. VC firms historically raised new funds every 3-4+ years, now it’s firmly down to 3 years or less

2017-2018: Rediscovery of Unit Economics

Roughly 18-24 months ago, people started to revisit the question of unit economics… what is the underlying profitability of a B2C transaction or a B2B SaaS contract once all the appropriate costs are factored in. Startup pitch decks now have an obligatory unit economics page, not just an up and to the right revenue graph. “Gross margin”, “contribution margin”, “unit profitable”, “LTV/CAC ratios” all reenter our collective lexicon. But there’s still ample capital funding companies with mediocre unit economics, on the promise of improvement with greater scale.

Simultaneously the IPO market finally starts to reopen for a wider swath of VC-backed companies. Snapchat goes public in 2017 and Spotify succeeds with a direct listing in 2018. Over 100 VC backed startups IPO in these two years, and the IPO is “back on” for many companies to consider.

SoftBank Vision Fund is announced mid 2017. Facebook becomes a $500B+ market cap company. US VC funding tops the $100B mark in 2018, and over 25% of this goes into $1B+ supersized private rounds. Many VC firms compress fundraising and deployment (initial investments) cycles from 3 years to 2 years.

2019: Profitability Rears Its Ugly Head

This year started off as the year of the IPO… eagerly anticipated companies like Uber, Lyft, and Slack all go public along with countless others (Pinterest, Zoom, Chewy, Datadog, Peloton, etc). VC backed funding continues full speed ahead, by midyear total US VC funding is on pace for >$120B, and 2018-2019 look to be shaping up as the first ever back to back years above $100B.

Then the WeWork debacle unfolds in the public eye. To be fair, public market investors were already discriminating heavily between recent IPOs in terms of their prospects for company level profitability prior to the failed WeWork IPO. And much of the story of WeWork is about founder behavior and corporate governance, but even these might have been overlooked had the business been robustly profitable at its core.

Early stage startups remain focused on unit economics and growth, but mid-late stage companies are now starting to thinking about company level profitability in ways that were uncommon only a couple years prior. Recently IPO’d companies like Uber spend much of their quarterly earnings cycle talking about when they’ll be profitable. And even for early stage startups, VCs raise eyebrows at companies that have modest gross margins.

2020 and Beyond?

As an independently minded investor, it’s sometimes a struggle to ignore the narrative and cycle. Of course one must be aware of the cyclical zeitgeist as it impacts the behavior of competitors, co-investors, and others. But one still has to seek out innovative companies with competitive moats that have a path to sustained (and sustainable) value creation.

The reality is growth, unit economics, and company profitability are not binary trade-offs. They all matter, even though their prioritization will change over the lifecycle of a company. There’s also no single formula for these in the creation of a valuable business, other than in the long run all businesses must be cash generative on their own.

The three most valuable companies in the world are Microsoft, Apple, and Amazon. Conventional wisdom is that hardware companies or low margin businesses aren’t that valuable. Two of the three have gross margins <50% (AMZN is 40%, AAPL 38%, MSFT 67%) and one has operating profit margins <5% (AMZN 4%, AAPL 22%, MSFT 34%). One generates the overwhelming majority of its revenue from one-time hardware purchases, despite its protestations it’s really trying to become a “services” company.

Make no doubt though… we are entering a denouement, with the present startup cycle which has played out over the last decade entering its latter phases.

The practical steps for us early stage investors may be simple, if not always easy. It means evaluating startup’s potential across a range of financial benchmarks, even it’s still at a pretty early stage. It means looking for truly innovative companies that can build competitive moats for the very long term. It requires partnering with founders whose drive, invention, and ability to suspend disbelief allow them to embrace the innately unnatural pursuit we call entrepreneurship without succumbing to hubris and vainglory. It means rejecting whatever today’s standard dogma about startups may be or just looking for the simple analogy.

Time to get back to work with an open and independent mind…

The post Denouement appeared first on AGILEVC.

Another phrase we use internally at NextView pretty often is that of a “favorite future”.

Early in NextView’s history, when we were raising our first fund (e.g. sometime back in 2010 or early 2011) one of the limited partners we met with asked us what our “favorite future” was for NextView. We were excited to talk about our vision and aspirations for the new VC firm we were building, but also intrigued by this as a general question.

When meeting with founders we now often ask them what their favorite future is for their startup. This is one of those questions which is phrased as a “What” but really is a lot more about “Why” and “How” ultimately. We ask it in the hopes of gaining a deeper understanding of the founders’ long run vision for the business and to glean some insights into their underlying motivations for being an entrepreneur.

It’s worth noting that there is no specific “right” answer to this question. It’s not a litmus test for us to pursue an investment or not based on the exact wording or content of founders’ answer. But stuff you can often infer from founders’ responses include:

1. What their ambitions for this company are
2. Why are they working on this startup, vs another startup idea or doing any of a variety of other things with their time and energy
3. How they see their long run role as a leader in this organization evolving
4. How motivated they are to make the venture succeed, through thick and thin

You hear all sorts of fascinating things from folks when you give them an open-ended opportunity to talk about their aspirations for their startup. Sometimes it’s about an event earlier in the founders’ life that had a profound impact on them and motivated them to build this new company. One founder I work with talks about building a “100 year company” by which this person generally means a company that not only helps its customers on a daily basis but has a broader societal impact over a very long time. And again it’s not just the “what” here but really they “why” and secondarily the depth of conviction founders’ have about what they’re doing.

So what’s your favorite future?

The post Friday Funism – “Favorite Future” appeared first on AGILEVC.

Chewy has rapidly grown from a startup to a multi-billion commerce company, establishing itself as the leader in pet e-commerce. Chewy sells tens of thousands of products from many 3rd party brands, as well as its own private label brands (though latter remains <10% of sales). The company launched in 2011 and then was acquired by PetSmart for over $3 billion in 2017 (PetSmart itself owned by PE firm BC Partners), but Chewy is now preparing for life as a standalone public company.

I’ll break down Chewy’s business based on their recent S-1 filing here. I know some of the investors in Chewy prior to the PetSmart acquisition, but I am not a shareholder nor do I intend to purchase shares in the IPO. But the company is of particular interest to me given NextView is an investor in and I’ve been a board member of Grove Collaborative, another large and rapidly growing company in the consumer CPG space with a recurring purchase model.

Is Chewy Still a Rapidly Growing Business?

A $3.5B revenue business still growing >50% YoY? Check.

Embedded Growth From Existing Customers

One of the key features of Chewy’s business is the recurring nature of customer purchases. Consumers typically own a pet (or pets) for many years, so they are continuously purchasing food, toys, and accessories for their pet for an extended period.

Chewy now has over 10 million customers, repeat purchases by existing customers account for approximately 90% of their revenue today. But importantly Chewy keeps growing, even without acquiring any new customers, because their existing customers spend more money with them. This is analogous to SaaS companies like Slack or Dropbox, which have strong revenue growth just as their existing users consumer more of their service.

Chewy describes the “embedded growth” in this existing customer base in their S-1 so we’re able to glean the following:

1) Overall Chewy’s customers continue to buy more stuff from them each year

Average revenue per customer has steadily increased from $223/yr in 2012 to $334/yr in 2018. We can infer this increase is due to some combination of Chewy broadening their selection of products over time and increasing brand loyalty by customers, yielding a higher share of wallet for pet-related spend. This is separate from the dynamics of any underlying cohort itself (more on that below).

2) Impressive cohort growth & stability

Chewy helpfully provides some cohort data on both aggregate $ revenue, active customer spend, and LTV/CAC basis. The first is most salient, as it tells us how much revenue Chewy generates from a particular cohort as it ages… it basically nets out effects of some customers dropping out with those that stick around buying more stuff. For example, Chewy’s 2015 cohort (e.g. customers who made their initial purchase in 2015) generated 165% of initial cohort revenue in 2018. In other words, for every $1.00 spent by new customers in 2015, that same group (in aggregate) bought $1.65 worth of goods from Chewy in 2018.

FWIW Chewy’s 2015 cohort appears to be their best one which is undoubtedly why they highlight it in the S-1, but other years demonstrate similarly strong persistence and growth based on the data they provide. Cohort revenue appears to grow significantly from first year to second year, and then largely levels off but persists for years.

Annual Net Sales By Customer Cohort

3) “Autoship” is a conveyor belt into consumers’ homes

While Chewy’s embedded growth ultimately comes from many consumers sticking around and increasing their spend over time, one of the drivers of this behavior is Chewy’s “autoship” model. While slightly more flexible than a simple monthly subscription (autoship customers also can make ad hoc purchases), the program lets consumers set recurring purchases for consumables they continuously replenish.

Customers in the autoship program generated roughly 66% of Chewy’s revenue in 2018. These customers also have a higher avg order value (AOV) than non-autoship customers, so they represent “better” customers for Chewy on multiple dimensions.

What Are Chewy’s Prospects for Profitability?

Chewy is unprofitable, on both a net income and EBITDA basis. Much of the press on the company’s IPO highlights this fact, which is easy to discern from a casual read of the S-1.

What I was curious to understand is what is the underlying potential for profitability for Chewy. How efficient is it as a business in terms of cash flow consumption or generation? Could Chewy reduce its marketing or other expenditures and be profitable now?

First, on an operating cashflow basis Chewy has been CF positive in some of the recent years. In 2016 they generated an operating cash profit of $7M, in a year where the company was still spending significantly on growth and grew revenue >100% YoY. In 2017 the company had an operating cash burn of roughly $80M, again in a year where the company did >$2B in revenue and grew >100% YoY. In 2018 Chewy was basically cashflow breakeven on an operating basis, with an operating cash burn of $13M on revenue of over $3B.

Operating cashflow represent the cash that’s generated or consumed by the business, excluding things like capital expenditures or year to year balance sheet changes in the level of inventories or payables. Chewy also appears to have cashflows going up to its parent PetSmart, which is owned by PE firm BC Partners. In the last two years cash has flowed both from Chewy to PetSmart and vice versa, but on a net basis Chewy has payed roughly $80M more in cash to PetSmart than has flowed from the parent company to Chewy.

To put this all into context, in the past four years Chewy has consumed $134M (negative free cash flow) over the last four years while growing from $200M to $3.5B in revenue. Chewy has spent roughly $750M in marketing over the last three years to fuel growth, and while it has strong LTV/CAC ratios it still takes 1-2 years to see payback on its initial customer acquisition spend. In other words, if Chewy had cut all customer acquisition spend it would have solidly cashflow positive for several years albeit growing at a slower rate, though still growing given embedded growth described above.

Chewy LTV/CAC Ratios By Cohort Year

So If Chewy Is Fundamentally a Profitable Business, How Much Operating Leverage Exists?

We talk a lot about operating leverage in a business, e.g. the ability to increase various drivers of profitability which can make the business more profitable either on a unit basis or overall. To understand what operating leverage may exist in Chewy’s business, it’s helpful to first understand its existing profit margins.

Today Chewy’s underlying gross margins are just over 20%. Chewy cost of goods (COGS) includes both the underlying cost of the products sold but also some fulfillment related expenses like freight and packaging. Gross margins have been steadily improving in recent years from 16.6% in 2016, to 17.5% in 2017, and 20.2% in 2018 and according to the discussion in the S-1 much of this improvement has been attributable to higher product gross margin. Chewy has also started to introduce some private label brands, which presumably will drive higher product gross margin, though this is still fairly early in development. Chewy discloses that private label represents “mid single digit percentage” of sales, i.e. >90% of Chewy’s revenue is from selling 3rd party brands.

The other way we often look at margins is contribution margin. There can be genuine philosophical or accounting differences in how different costs are allocated, but generally I strive to think about a true “fully loaded” contribution margin. So for a commerce business like Chewy that would include:

Contribution Margin = (1) Net Revenue – (2) Product Cost – (3) Shipping – (4) Packaging – (5) Payment Processing Costs – (6) Direct Fulfillment Labor – (7) Variable Costs of Fulfillment Infrastructure

If you look at Chewy’s financials you’ll see a line item for Net Sales and a line item for COGS which includes #2, 3, and 4 above. But Chewy accounts for items #5, 6, and 7 within Selling, General, and Administrative (SG&A). They also include customer service costs in this Fulfillment bucket within SG&A, as well as some fixed (e.g. non-variable) costs associated with fulfillment.

Not all of the items #1-7 above are specifically provided in the S-1, so we have to infer based on the data Chewy does provides. We know that the total “Fulfillment” cost that Chewy accounts for in SG&A was just over $400M in 2018, so a bit over 11% of revenue. That includes items that appropriately would fall into contribution margin, like fulfillment labor (pick/pack/ship employees),  payment processing costs (just shy of 20% of this Fulfillment bucket), and variable costs of fulfillment infrastructure like leases on warehouses. But there’s also probably some expenses in Fulfillment which are amortized fixed expenses for things like software or machinery in warehouses.

TLDR here is that it’s probably appropriate to add back a small portion of the expenses in the Fulfillment bucket Chewy reports in SG&A when trying to calculate fully-loaded contribution margin. So if you start with gross profit margin of 20.2% and subtract out the 11.4% in the Fulfillment cost bucket in SG&A, you get 8.8% which is probably a bit too conservative given it includes the amortized fixed expenses as I describe above. So it’s probably a fair assumption to say that Chewy has something like ~10% or slightly higher fully-loaded contribution margins, i.e. for every $1 of revenue roughly $0.10 in contribution profit is generated which can offset overhead and generate operating profit.

Conclusion

Bottom line, Chewy appears to be a pretty robust commerce business:

1. It has a solid leadership position in a large and growing category
2. It continues to grow rapidly, even at multi-billion revenue scale
3. Chewy’s business is a “conveyor belt into consumers’ homes” with strong repeat purchase and growth LTV
4. It’s core business is cashflow positive, excluding marketing spend for new customer acquisition
5. It’s underlying gross margins and contribution margins appear to be steadily improving

The post Chewy S-1: Category Leadership + Conveyor Belt Into Consumers’ Homes appeared first on AGILEVC.

Slack dropped their S-1 a couple weeks ago. Even before that, we all knew that it was among the most rapidly growing SaaS companies in recent years and a product used (and loved) by millions of people.

But now we have a chance to really dig in and understand Slack’s business a bit better. I have friends who are execs or shareholders of the company, but I have no stake in Slack nor intent to invest in the IPO. One of the key questions for me was how might Slack stack up against other great SaaS companies when it comes to average revenue per user (ARPU), and how ARPU and total addressable market (TAM) might drive Slack’s long run market cap.

If you haven’t seen these already, here are some of the headline figures about Slack’s business:

• $400M in GAAP revenue in the most recent year (fiscal year ’19 ended 1/31/19)
• Revenue growth rate of 82% year over year
• 10M+ daily active users (DAUs)
• Gross margins of nearly 90% (~87% in FY 2019)

A somewhat unique thing about the Slack IPO is that they’re pursuing a direct listing on the NYSE. So, similar to Spotify, their shares will simply begin trading publicly without having an underwritten “primary” offering of newly created shares that raises additional capital for the company. Practically speaking this doesn’t mean that all of the shares owned by founders, investors, employees (RSUs), or others will be available to trade immediately as they will need to be converted and registered for public trading. But it does mean that traditional 180 day lock-up periods won’t generally apply to existing Slack shareholders.

My interest in digging through Slack’s filing was to better understand the business. So the things I was trying to broadly analyze include:

1. What are the current and future growth prospects for Slack?
2. How well does Slack monetize each paid user, relative to other SaaS companies?

1) What are Slack’s growth prospects?

Slack remains a rapidly growing company even though they already have meaningful scale (>$500M annual billings). On a trailing basis they’re growing >80% YoY. So even though they’re less than doubling and growth is decelerating (as is typical for rapidly growing companies as they reach scale), Slack will conceivably hit $1B in GAAP revenue less than two years from now.

Below the headline figures you can see that a key driver of revenue growth is “expansion” revenue of existing customers spending more each year with Slack. This is presumably occurring as companies using Slack expand their usage across different workgroups, departments, or geographic locations. You can see this both by looking at a cohort “layer cake” graph or by examining the net dollar retention. Here’s the layer cake:

Growth and analytics types who work with cohort analyses will be very familiar with these, but for those who aren’t this chart basically shows how much recurring revenue Slack gets from customers who became paid subscribers in a given year. Charts with no axis labels or numbers infuriate me, but companies are entitled to present themselves however they wish when providing supplemental data like this. But just eyeballing it you can see that the incremental ARR from existing customers (FY15–18 cohorts) in 2019 is probably at least as much (if not more) than than the total ARR from new customers (those who started paying in 2019).

Slack’s net dollar retention rate is an incredibly impressive 143%. This is the mythical “negative churn” that recurring revenue businesses all strive for, whereby your existing customers (overall as a group) pay you more each year than they did the prior year even after accounting for those existing customers who left. So Slack generated $1.43 in MRR in 2019 from existing customers for every $1.00 in MRR from customers at the end of 2018. Slack’s net dollar retention rate is decreasing, but is still a long way from dropping below 100%. So it is reasonable to assume that Slack will continue generating more revenue from existing customers for the foreseeable future (e.g. next 3–5yrs at least, barring massive changes in customer behavior).

Bottom line… Slack appears primed to continue growing strongly from its existing customer base. In terms of penetrating new customers, it you believe Slack’s product has broad applicability for both small and large organizations across a breadth of industries and functions, it seems they’re a good distance away from market saturation. We can have a debate about TAM but at 10M DAUs, it seems there are still many millions of new users that may adopt Slack in the coming years.

2) How well does Slack monetize paid users?

Slack employs a freemium model, with <15% of the organizations using the product as paying customers (88K paid customers out of >600K organizations). But I believe one of the key determinants of Slack’s long run enterprise value will be the amount of revenue per user they ultimately generate.

Self-serve pricing ranges from $7–15/user/mo, but given enterprise pricing may involve volume discounts (lowering ARPU) as well as custom services and integration (increasing ARPU) we don’t know precisely how much revenue per paid user Slack generates. In their S-1 they disclose total active users (>10M DAUs) and total paid organizations (88K), but not the number of users in these paid customers. But it’s safe to assume that the largest organizations (in terms of users) are primarily paid orgs and the smallest ones are primarily free. We’ll talk more about segmentation in the next bit, but 40% of Slack’s revenue comes from roughly 600 large enterprise customers that pay >$100K/yr.

For the sake of discussion, I’m going to assume that about 40% of Slack’s DAUs are within paying customer orgs. Slack previously disclosed that it had 3M paid users out of 8M total in May last year, but paid users as a % of total had been trending upwards. So let’s call it 4M paid users who generated $400M of GAAP revenue in the most recent fiscal year. That works out to ~$100/user/yr in revenue.

No two companies are a like, but we can draw analogies between Slack’s ARPU and other leading SaaS businesses. Also I’m making comparative judgements here between these companies to think about their long run scale, but all of them are very good businesses. The figures below are calculated or inferred from company reports, SEC filings, and public press announcements which disclosed revenue, customer, and user figures.

ARPUs/year

• Microsoft Office Commercial (non-consumer) = $180
• Salesforce = $2,200+
• Dropbox = $120
• Atlassian = $125
• Zoom = $180
• Adobe = $450+

Market Cap

• Salesforce = $121B
• Dropbox = $10B
• Atlassian = $28B
• Zoom = $20B
• Adobe = $137B

MS Office is obviously part of Microsoft overall which has many other huge businesses (Azure, Xbox, Windows, etc). But Office Commercial is a $24B a year revenue business on its own, and while a much older and more mature franchise than the others it’s still growing 25%+ annually. Also similar to Adobe, both Office 365 and Adobe’s Creative Cloud have pretty successfully transitioned from their legacy client software business models to SaaS. So it’s reasonable to assume that were it a standalone company, “Microsoft Office Co.” might have a market cap of $150B+.

To me, the question of whether Slack is a $20B market cap company or $50B or $100B+ in the long run is largely a function of ARPU and TAM. Public equity investors will measure it in the short term by the same metrics they judge other SaaS companies… multiples of revenue / EBITDA / bookings, growth rates, churn, sales efficiency, etc. But anyone contemplating a long term investment in Slack is implicitly making a bet on how many potential paid users there may be for Slack and how much revenue the company can extract from each one.

SaaS companies that become $50–100B+ market cap companies are either ubiquitous products like Microsoft Office which has 135M+ paying customers or they massively monetize certain segments the workforce but aren’t used as broadly. Salesforce and Adobe are unlikely have 100M+ paid customers for their core offerings, but they generate 4–10X more revenue per user than companies like Dropbox, Zoom, or Slack. Atlassian is a great business but interestingly has a modest ARPU but also a narrower TAM (software dev & IT professionals).

Bottom line, to believe that Slack could be a $50–100B+ market cap company in coming years you have to believe that it has a potential for ubiquity like Microsoft Office given it doesn’t monetize to the level that Adobe or Salesforce does (and seems unlikely to). I don’t think that’s a crazy bet or out of the realm of possibility btw… organizations that adopt Slack often consider it vital to their internal communication and workflow, and there’s a very broad range of orgs using Slack.

The post Slack S-1: Will APRU Drive Long Term Value? appeared first on AGILEVC.

2019 is off to an exciting start for IPOs of VC-backed startups. In just the last month or so we’ve seen Lyft go public (my analysis of the company’s S-1 here) and more recently, Zoom and Pinterest.

Zoom is a B2B company Pinterest and Lyft are obviously B2C companies. All three have different business models… SaaS, media/ad, and consumer transactional. All three are impressive and valuable businesses in their own right.

In some respects though Zoom has had the most “successful” IPO of the three companies, which has surprised some folks. All three companies had significant investor interest during their road shows and increased their IPO price ranges, but I believe Zoom’s increased the most by the offering. Zoom had the largest first day “pop” when it started trading (+72% vs +28% for Pinterest and +9% for Lyft). And Zoom has become the most valuable of the three in terms of market cap though daily fluctuations put it and Lyft fairly close ($16B+).

In the last decade or so, high profile consumer IPOs have often gotten lofty valuations. I believe this was primarily because public market investors believed there was some chance that these high profile consumer companies would be once-in-a-generation type companies. Google was a one such company when they went public in 2004 and Facebook was too at their 2012 IPO. I don’t follow the Chinese startup market as closely as I follow the US, but Alibaba’s 2014 IPO was a similar watershed moment.

But by definition, once-in-a-generation companies only come along say once in a generation or perhaps once a decade or so. Fairly frequently public market investors believe that a new consumer company is “the next X”. We first saw this with Twitter in 2013 when they went public and many (both retail & institutional investors) believed that company might be the “next Facebook”. Something similar happened with Snapchat in 2017 with their IPO. Despite hype in the run up to their IPOs and strong enthusiasm in early weeks and months of trading, neither Twitter nor Snap has proven to be anything like the next Facebook (FB’s market cap is >10X the combined market cap of TWTR + SNAP).

In finance there’s a concept called an embedded option… in short, beyond the baseline value of a bond or other security you also ascribe an additional bucket of value to something triggered by future events. In some respects, when public market investors describe a newly public company as the next Facebook or Google or Amazon they are implicitly embedding value to in the company’s stock beyond the core business. In many ways, high profile consumer startups that have gone public in recent years have benefitted from an embedded option on potentially being the next once-in-a-decade company.

But in observing the recent IPOs of Zoom, Pinterest, and Lyft it would appear that public market investors are no longer ascribing this option value to the high profile consumer companies. That not only bodes well for strong companies seeking to go public, regardless of whether they’re B2B or B2C. It also signals a potentially healthier IPO market, albeit one occurring in the midst of a decade long bull market.

Beware whenever a transformative company is described as the next Facebook, Google, or Amazon. There will always be exceptional once-in-a-decade or once-in-a-generation companies, that’s one of the great strengths of capitalism’s creative destruction. But Amazon was different than Microsoft before it and Google was different than Amazon and Facebook different from that. If history tells us anything, it’s that the next truly once-in-a-decade company ($100B+ value) rarely looks exactly like the ones of the past.

The post Why Do Consumer IPOs and B2B IPOs Get Treated Differently? appeared first on AGILEVC.

I’ve been looking thru S-1s for many years, out of intellectual curiosity to better understand how remarkable businesses work. This includes blockbusters like Alibaba (in three parts) and Facebook but also the likes of Square, Dropbox, Twitter, Blue Apron and going many years back Kayak and Groupon.

There are a variety of quick write-ups on the Lyft S-1 for basic figures like annual revenue, rider growth, or who the largest shareholders are. Here’s one from Pitchbook and one from TechCrunch. I’m going to try to dive a little deeper to assess how good of a business Lyft is and uncover interesting nuggets about the company disclosed in the S-1. If you are interested in a deeper understand like this read on. If you just want my TLDR perspective on Lyft as a business jump to the Conclusion section at the end.

Is Lyft becoming a bigger part of their riders’ transportation spend?

Early on, one of the key questions for all ride sharing companies was the breadth & depth of usage by their customers. When Uber started off as a more expensive “black car” service, people questioned whether it would eventually become a more mass market phenomenon or not. The Lyft and UberX models certainly did that, and shared rides pushed breadth and depth of usage even further as the per ride price point declined.

Lyft helpfully provides the number of active riders, total number of rides, and average revenue per rider on a quarterly basis. What struck me was that the average frequency of rides per rider hasn’t actually changed much in the last three years.

Revenue per rider has more than doubled from 2016–2018 (from $15.88 to $36.04 per quarter), but the number of rides per active user has remained right around 9ish per quarter. So it’s not really the case that Lyft’s riders (in aggregate) are using the service more often, but rather Lyft is getting much better at netting more revenue per active rider. If you dig into the Management’s Discussion of the financials, it basically suggests that Lyft was able to increase their commission rate per ride and reduce pricing incentives to both rider and driver thereby extracting more net revenue per ride.

You can see this in a graph they provide of revenue as a percentage of bookings. For clarity, revenue is the portion of the transaction that Lyft keeps and bookings is the total amount of the ride charged to the consumer (excluding tips and tolls/fees). So you can think of bookings as a GMV type figure and revenue as true net revenue to Lyft.

Again basically Lyft has gotten dramatically better at keeping a larger portion of each transaction.

So what about those cohorts?

Lyft helpfully provided some very high level cohort data to help us understand the typical evolution of their riders’ usage. Again as I highlighted above, in aggregate Lyft’s users aren’t taking dramatically more rides today then they were 3+ years ago. So there isn’t a paradigm shift going on where overall people are relying on Lyft for more of their transportation needs.

If you look at the yearly cohort level though, you do see a pattern where on average people use Lyft more frequently the longer they are a customer. In their 2nd year as a rider, average users increase their number of rides fairly significantly but then this growth tails off or disappears beyond that.

Additionally we can see that more recent cohorts still grow total rides strongly in their first year, but that newer cohorts are growing rides less quickly than older cohorts. We only have total rides, not the number of riders which are still active in later years. But nonetheless, I think it’s fair to say that Lyft is doing a pretty good job of retaining riders and increasing their usage into their 2nd year of ridership. But it does not appear to be the case as of now that riders today overall rely on Lyft way more heavily than they did 3 years ago.

Does Lyft have a flywheel of money?

One of the powerful features of some businesses is that the strength of their product and brand creates a flywheel whereby they grow revenue perpetually, even without adding new customers. Nothing grows to infinity obviously, but as I noted in my Dropbox S-1 analysis that business had a powerful persistence whereby they increased revenue from existing customers each year simply as an effect of increasing storage consumption per user.

So does Lyft have a flywheel of money?

The simplistic way to do this is to zero out the Sales & Marketing line item in the financials and see what happens. In 2018 Lyft had an EBITDA loss of -$977M whereas their Sales & Marketing spend was $803M. So Lyft would be pretty close to EBITDA breakeven for 2018 if you use this methodology, though again it’s a crude approach and not as useful as digging deeper IMO.

With the pieces of data I picked out above, we can make a somewhat more informed assessment. In reality sales & marketing expenditure is for both acquiring rider customers and drivers, and even if aggregate rides grows without new riders there’s still some ongoing driver churn that requires recruitment spend. I made some rough assumptions about ride growth for recent cohorts based on year 1, year 2, and year 3 growth figures Lyft published and assumed older cohorts grew rides 5%. I also assumed that revenue per ride, which has risen substantially in the last several years, remains similar to 2018.

So there is a bit of a flywheel here, as revenue would grow something like 16% over 2018 just on existing riders based on my assumptions above. Lyft theoretically could be EBITDA profitable if they cut sales & marketing spend substantially (but not to zero) and didn’t add any new riders in 2019. In reality it wouldn’t make sense for the company to do this, and Lyft would probably grow some organically even with out rider marketing spend. But understanding how the existing business grows and could be profitable is useful in assessing the overall strength of the enterprise.

Lyft’s Biggest Cost “Driver” Isn’t the Driver

As described above, what Lyft recognizes as revenue is their portion of the transaction they keep so it excludes the payment to drivers. To be clear, the portion of the transaction the driver keeps is the largest absolute amount… Lyft booked roughly $8 billion worth of rides in 2018 and recognized approximately $2.1 billion in revenue.

But given they’re essentially recognizing “net revenue”, Lyft’s cost of goods (COGS, aka cost of revenue in S-1) is composed primarily of insurance, credit card processing fees, and software/tech hosting costs. Insurance is far and away the largest cost driver. While the S-1 doesn’t break these out individually in COGS, reading through the footnotes we can glean that insurance is the largest of these cost drivers. Lyft essentially operates it’s own internal insurance entity, so they deposit funds into an insurance trust periodically and then recognize expenses when claims are paid out.

Overall Lyft is driving their COGS down, from >80% of revenue in 2016 to roughly 57% of revenue in 2018. So they’re increasing the overall percentage of the transaction they take as revenue while simultaneously driving down their direct COGS to support that revenue. This bodes well for Lyft’s ability to continue to drive towards profitability in the coming years, even though they remain an unprofitable (albeit still rapidly growing) company today.

Conclusion

So what’s the bottom line? By breaking down rider economics, transaction splits, and cost drivers we have a richer understanding of Lyft as a business. This is a company which is currently unprofitable, but still growing at 100% YoY and it appears to have a modest “flywheel of money” by which its existing customers will continue to drive incremental revenue. Lyft is also taking an increasing % of each transaction and reducing its costs, so my conclusion is that this company has a pretty clear path to profitability.

How Lyft will be valued by public markets is a bit of a wild card. It appears they will beat Uber to IPO, so helpfully they can frame this new category of “transportation as a service” in the minds of public equity investors. Lyft has done a very good job of gaining market share in the last 2–3 years, which they estimate at 39% of ridesharing in US. But they remain #2 to Uber in the US and with a much more limited global footprint to their rival. When Uber’s S-1 drops, I will be curious to see what they may disclose in terms of rider frequency and revenue per ride.

The other overarching question about how Lyft will be valued is the embedded risks and upside. In the US, the regulatory framework has reached a fairly stable environment after a bumpy start when ridesharing began, so I see this as less of a risk today. When autonomous vehicles become a reality, there’s also a potential for companies like Lyft to further gain market share and reduce costs. But it’s not a given that Lyft will be a winner in an AV world, and it’s still quite uncertain how many years we are away from true Level 4/5 autonomy in the US.

But overall this is a solid business, helping pioneer a massive shift in personal transportation which is one of the biggest slices of the economy. I suspect Lyft will have a good IPO and will achieve profitability and continued growth in the coming years.

The post Lyft S-1: Kicking Off the Decacorn Bonanza of 2019 appeared first on AGILEVC.

Thanks in large part to Tim, the NextView family today includes exceptional founders of companies like Dia & Co, Timber, The Outline, and Parsec.  He’s been a champion and supporter of NextView’s portfolio broadly, a thoughtful voice in our investment team discussions, and a driving force in the continued growth of our presence in New York.  We’ve enjoyed watching Tim come into his own as a VC investor at NextView.

So it’s bittersweet for us to share the news that Tim will be moving on from NextView in order to take an exciting next step in his career.  I’ll leave it to him to talk in more detail about his plans when the time is right.  Tim will continue to be actively involved in the New York tech ecosystem and while we will miss working with him day to day as a colleague, he will always be a valuable friend to NextView.  As those who know him are aware, Tim is an exemplary human – driven, scrappy, smart, humble, and caring.  We wish him the very best on the path ahead.

The post Tim Devane’s Next Chapter appeared first on AGILEVC.

For those who follow my writings on my AgileVC blog or on Medium, you’ll know that I’ve been thinking about the autonomous vehicle space for some time.  I say “autonomous vehicles” rather than “driverless cars”… when my little daughter has a family of her own someday, the phrase “driverless car” will be an anachronism akin to “horseless carriage”.

Optimus isn’t yet describing their plans in detail publicly, so I won’t be letting their cat out of the bag.  But I’m thrilled to be able to partner with an extraordinarily experienced and talented group of co-founders.  The Optimus team has its roots at MIT and has been working on various parts of the autonomous vehicle stack for over a decade in both tech companies and university research settings.

The transportation market is among the largest spheres of commerce in the world, and network connected software and hardware will transform this industry in the coming decade and beyond.  The end goal is both tantalizing and simple – autonomous vehicles transporting people and goods with vastly greater safety and efficiency (energy costs & externalities, human time, urban infrastructure, etc).  The pathway to that end goal is both uncertain and extraordinarily complicated given the technological, economic, and societal developments that will be required.

We obviously believe that Optimus has the potential to play an important role along that path, and are excited to support the team as a hands-on investment partner.

The post The Road to Autonomous Vehicles & Our Investment in Optimus Ride appeared first on AGILEVC.

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So what are the different paths towards commercially available self-driving cars?  The way forward includes not only advanced vehicles themselves but also potentially shifts in road infrastructure, laws and regulations, and even business models for “mobility.”

In my first post earlier this summer, I highlighted the fact that we’re still a ways off from truly autonomous vehicles, despite many decades of technological advances to assist drivers.  The “Auto-Pilot” capability in Tesla’s Model S is currently the most advanced semi-autonomous (NHTSA Level 2) system you can actually buy, but it still has many limitations and to me, it’s closer to “awesome cruise control” than it is to a “self-driving” experience.  If you go on YouTube, you can find examples of lots of antics involving Tesla’s Auto-Pilot, but in reality, driver involvement is still an absolute must with this system.

Sadly, news came out shortly after I published my first post regarding the first fatality involving a Tesla in “Auto-Pilot” mode.  While all traffic fatalities are tragic of course, I’m hopeful that events like these will not be a setback for technical and regulatory efforts to bring truly autonomous vehicles to market.  It’s also a reminder that, for the time being, driver attention is required even as more advanced aids or semi-autonomous systems are developed (all categorized as ADAS – advanced driver assistance systems).  Tesla has already released updates to its Auto-Pilot software to further refine situations like this.  

FWIW, the first true competitor to Tesla’s Auto-Pilot ADAS system, Mercedes “DrivePilot”, has gotten terrible reviews.  Despite its limitations, Tesla’s system remains the clear best in terms of performance and driver comprehension.  And semi-autonomous/ADAS has applicability beyond passenger vehicles, as we have seen with companies like Otto focused on retrofit ADAS for semi trucks (Otto is being acquired by Uber).

There’s no one certain path towards autonomous cars.  But the way forward will undoubtedly require meaningful changes to some combination of the following:

Vehicle Development

The most obvious area which requires change is in the cars themselves.  For vehicles to be truly autonomous, they need to be able to perceive their environment in great detail, map their route, make decisions about what to do, and coordinate their actions at some level.

Arguably the biggest advancements in recent years have been in the area of perception.  Self-driving cars currently in development rely on some combination of laser / LIDAR, radar, ultrasonic proximity detectors, and cameras / computer vision to perceive their surroundings.  At their most basic, these systems help a car determine distance and speed relative to other objects (surrounding traffic, pedestrians, highway guardrail, etc.) or points of reference (painted lane markers on roads). In their more advanced forms, they can make determinations about the nature of an object in the surrounding environment (Is that thing 100 feet away a car, a large truck, a pedestrian, or a building?) and interpret context or meaning (the red octagon with lettering 50 feet away is probably a stop sign).

Many of the sensors and systems for vehicle perception are made by large Tier 1 suppliers like Bosch and Delphi, but new players like Mobileye (founded in 1999 and now a $10 billion market cap public company) have also emerged.  There are also significant startups like Velodyne, Quanergy, and others that are seeking to become major component suppliers of various sensor technologies.

Perception isn’t the only area of vehicle development that will require significant advances.  There are also significant efforts in AI / decision-making systems, improved mapping, vehicular coordination systems, and other technologies which will be needed to enable level 4 autonomy.  These are all mutually dependent. For example, if autonomous vehicles can effectively coordinate their actions (e.g. “convoying” with other nearby cars or detecting transponders of other vehicles), then theoretically they could be slightly less sophisticated in terms of their individual ability to perceive the environment.

Various existing and aspiring vehicle manufacturers are taking different paths towards autonomy.  Some like Tesla, GM, Mercedes, Volvo (both on its own and in partnership with Uber), and others are developing ADAS features that will enable level 2 or level 3 autonomy first, presumably as a stepping stone to fully autonomous vehicles.  Others like Google and Ford have talked publicly about a strategy of focusing on level 4 autonomy completely, without intermediary development of ADAS.

The $500+ billion dollar question* is of course this: When will fully autonomous vehicles be available for use by the general public?  The honest answer is nobody, even vehicle OEMs, really knows for certain.  Part of the problem is that, for all the focus on the technology and vehicle development, autonomy also requires fairly meaningful changes to road infrastructure, laws and regulations, and other non-technical matters…

Road Infrastructure / City Planning

Most of the focus in terms of press, investment, or consumer enthusiasm is currently focused on vehicle technology development.  But the pathway to fully autonomous cars and trucks will almost certainly require substantial changes to our road infrastructure and city planning.

If you think about a road in the broadest sense, it’s in fact a system that encompasses the tarmac surface itself, lines or pavement markers (raised reflectors, Botts’ dots, etc.), various signs conveying context, traffic control mechanisms (stop lights, etc.), and more.  And this entire system was engineered for human-driven vehicles.  If one were starting from a blank sheet of paper designing for a world with autonomous cars, you probably wouldn’t have most of this stuff.  Theoretically, an autonomous vehicle could be programmed to stop at any intersection if the car detected cross traffic. The intersection would be conveyed by GPS map or “smart” road transponders, while the detection of traffic could be handled via computer vision, vehicle coordination sensors, or several other viable options. 

Additionally, designing from scratch for autonomous vehicles would mean that, instead of a series of hanging lightbulbs, an intersection could feature a sensor to detect approaching vehicles and a transmitter to send instructions to each vehicle: “slow,” “stop,” “maintain speed,” “safe to turn left,” and so on.

Of course, in reality, we’re not going to rip up the millions of miles of existing road infrastructure and start with a new system of “smart” roads embedded with sensors, transponders, and such.  But in places where new development is taking place, you may see “smart” road infrastructure deployed instead of conventional roads (just as you saw some developing areas “skip” copper telephone lines in favor of wireless telecoms).  

In all of this, there’s also a key role to play for city planning in enabling vehicle autonomy.  We will likely see certain stretches of road or certain zones within a municipality created to facilitate various forms of autonomous vehicles even before we truly have “anytime/anywhere” full autonomy.

Ch-Ch-Ch-Changes

When it comes to vehicle autonomy, we are and will remain in a state of transition for many, many years.   I believe you will see more widespread adoption of semi-autonomous / ADAS features in cars over the next 0-5 years, but it’s likely true that anytime/anywhere autonomy is much further out into the future.  

While history doesn’t repeat, it does rhyme, and we forget that cars and horses coexisted on public roads for several decades in the early 20th century. So even when fully autonomous cars finally become commercially available, they will likely have to coexist with human driven vehicles for some time. Even then, self-driven cars may only be usable in autonomous mode under certain circumstances based on road situations, local laws, weather conditions, etc.  

There is indeed a pathway forward where a fully autonomous vehicle could be created just through tech development and advancements. But without other system-level changes like road infrastructure, vehicle coordination, and laws and regulations following suit, it could be a much steeper path.

* Sales of new cars and light trucks in the US were approximately $576 billion in 2015.

In my third post, I will tackle how the legal framework, insurance, and business models for mobility will change with the rise of autonomous vehicles. The best way to keep up with this series is to follow NextView’s Medium publication, Startup Traction, here or to all our content via email here.

The post Autonomous Vehicles: Can You Get There From Here? (Part 2) appeared first on AGILEVC.

Today we announced our investment in The Outline, a new digital media company founded by CEO Josh Topolsky.  The company plans to launch publicly later this year, but Josh talks about his vision for The Outline in this WSJ article.

We like to back authentic founders here at NextView… entrepreneurs who have experience and unique perspective on the market they’re trying to transform.  My colleague Tim Devane was the first one on our team to build a relationship with Josh, and Josh certainly fits this mold.  The internet is about 20 years old but most digital media companies simply replicate the model of legacy print media businesses only without the printing press.  Josh penned a widely read manifesto earlier this year that laid out the challenges with this approach and foreshadowed his thinking on the model for The Outline.

We’re excited to be in business with Josh and his founding team, as well as a great group of co-investors with experience in digital media.  And as consumers, we can’t wait to experience The Outline… if you’re interested the waitlist is here.

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