Webflow's Rosetta Stone 📊💬🔮
Tackling org-wide decision bias with a central repository of data on customers and markets, an account of the worst kind of platform risk, and (really) knowing most PMF answers before raising VC.
Welcome to the 56th edition of The SaaS Baton. A fortnightly newsletter that brings you three, hand-curated pieces of advice drawn from the thoughtful founder-to-founder exchanges and interviews taking place on Relay (curated with 💛 at Chargebee) and the interwebz. So, stay tuned!
In this edition, you’ll find following instructive and inspiring pickings:
#1: Webflow’s co-founder and founding CTO, Bryant Chou, outlines the research that’s housed in Webflow’s central “data book” and how that helps inform GTM decisions of all sorts.
#2: Rally’s (previously Carthook’s) founder, Jordan Gal, recounts a crushing tale of platform risks.
#3: Vanta’s co-founder and CEO, Christina Cacioppo, on the manifold reasons and gains of holding back on fundraising.
🗞 Recently on Relay:
Heuristics and Hunches — Why You Shouldn’t Build for an Obviously Large Market, and Other Notes on Creating a “Default Possible” Startup with Pulley’s Co-Founder, Yin Wu
“The way I think startups win is by betting on and building for markets that seem small today but would be non-obviously large in the future. The bet being: Why do you feel this vision of the world will materialize? And can you ride the wave as it does?”
#1: Webflow’s Rosetta Stone
(From: Webflow’s co-founder, Bryant Chou) (Source: CHURN.FM)
I describe the data book… as almost the Rosetta Stone to the company. We actually want to try as hard as possible to remove as much bias, as much room for interpretation from the data book as possible.
It has to be rooted in truth. And in order to do that, we actually have to remove a lot from the data book, it’s got to only contain information that we can attribute the source to.
And one of the really tough things about that is that we’ve actually done a lot of surveys and we’ve actually done a lot of different types of research. But those are things that we will try to weave in only if we feel like it’s unbiased.
Only if we feel like the way we’ve constructed the surveys is going to give us a very picture perfect clear view. So the approach that we’ve taken is, we actually kind of start from like, the first principles of like, what are the ideal outcomes of the data book?
And I think if any company goes about constructing a data book, without the ideal outcomes in mind, then you’re more or less just going to end up with just a bunch of raw data and no one’s gonna really kind of make sense of it all.
For us, some of the ideal outcomes that we had are, we want the data book to serve as a good foundation to work from for all sorts of pricing and packaging efforts.
To help us understand our go-to-market strategy better, specifically, who we want to target, which customers are the profitable customers, which customers are the less.
And then also from a product standpoint, trying to understand exactly what features people really care about, which ones are being used. And then also some of the psychological factors like of the things that we actually sell, which ones do people sell they value but don’t actually value.
…People say they value, you know, 10,000 CMS items, but they actually only use a couple hundred. So we kind of split things out that way.
And then the other thing that we also layered on, is we wanted to try and weave in the competitive analysis in addition to our understanding of the TAM. So those are all things that we felt we can provide extremely quantitative answers to, that didn’t leave a lot of room for interpretation.
So the first section of our data book is a TAM, where we kind of split by all the different segments that we’re currently aware of. We try to map out the revenue opportunity there. But then we try to weave in a little bit of qualitative understanding for our product-market fit in those particular segments.
So that’s where we kind of took some of the data that we ran from previous surveys, where we actually saw that [say] for companies that are 50 to 200 people, we actually have stronger product market fit than companies that are between 20 and 50. Just as an example.
So that that will give us not just a good idea of the TAM, but then the TAM also cut by how sticky our product is. That’s especially important for for our type of product because we see adoption from all parts of the stack. We see solopreneurs adopting us all the way up to fortune 500.
So that is information that we feel like is super valuable. It’s it’s still a work in progress, but we’re really, really happy about where it’s at. And then we’ve got a lot of feature usage data. We have a lot of firmographics data.
We’ve taken all of our Stripe subscriptions and we’ve cross-referenced that with Clearbit. We use Segment and then we have the Clearbit integration turned on.
That has made it very, very easy for our data scientists to enrich that data. So we’re actually pretty excited about where, where it is at and the insights that we can glean from it in the near future.
#2: “It’s not that Shopify is an evil group of people, it’s just the nature of centralized platforms”
(From: Rally’s founder, Jordan Gal) (Source: Above Board)
…It’s not that Shopify is an evil group of people….The issue is that this is the nature of a centralized platform. When you’re a big platform, you have a problem because you start off as a small platform.
When you have a small platform you have no network effects and that is the hardest thing to get going. So there’s an S curve in the life arc of a platform like Shopify. And Facebook. And Twitter. And others.
And it starts off with not much happening and then as you start to climb up the S curve is when traction happens not just from a product point of view but from a network point of view.
Merchants join. Agencies start to migrate over because there’s economic opportunities. Then app developers start building and that attracts more merchants which attracts more agencies which attracts more app developers.
And then you get this beautiful cycle of everyone climbing up the S curve, generating an enormous amount of value where everyone’s winning and everyone’s happy. It’s like early-days Facebook, early-days Twitter, name your platform.
At some point though and not coincidentally that point usually or often coincides with going public, at some point it turns. And the pie doesn’t grow quite the same way and the relationship between the platform and its participants goes from cooperation to competition.
That is what’s happening in the Shopify ecosystem. We were caught up in that. Maybe we were at the tip of the spear because we were playing around right at payments which is their business model.
But this isn’t just happening to us. It’s happening all over the place. If you look under the hood a little bit into the Shopify app ecosystem, what you’ll find is fear. Widespread fear.
‘What’s going to happen?’ ‘Are they going to buy us?’ ‘Are they going to invest in our competitor?’ ‘Are they going to launch their own feature?’ ‘Can we become friends with someone?’ ‘Can we get listed?’ ‘Why are they getting listed?’
…
They limited our functionality to such a degree that I personally found it no longer interesting. They basically said, “you can keep your customers, but you can’t add any more customers.”
Right there what you’ve done is destroyed the enterprise value of a software company. You can’t have growth. We had a software product that was doing $550K a month. Growing like crazy. And if you stop it’s ability to add a new customer, you just destroyed all the enterprise value.
You didn’t destroy the cash value, it’s still going to make money, but there’s no growth. There’s no future. What they forced us to do is build a new post-purchase offer app that just focussed on that one feature and we had to build it inside of their checkout.
In reality, we taught them how post-purchase should work. They built it into their API and then they commoditized it. And now there’s a bunch of copycat apps all over the App Store. I had no interest in being in that position.
#3: “…investors want to fund businesses that actually don’t need funding”
(From: Vanta’s co-founder, Christina Cacioppo) (Source: Same, Same but Different)
I finished school and graduated into the 2008 recession, basically, and was really fortunate to get a job, generally, and then get a job at an early-stage VC firm.
And it was just really clear that not just the folks I went to work for, but generally, investors really wanted to fund businesses that actually did not really not funding. And conversely if you wanted to be funded, the best way to do that or achieve that is to actually not needing funding.
So that got baked into me very early in my career.
When we finished YC, we did have that seed round and were operating toward cashflow breakeven, not profitability but breaking even. The idea was, again, that we really wanted to build an actual business that in some ways didn’t need funding so we could get it funded more easily.
And honestly, we wanted to make sure we were truly building something that people wanted. Having been in early-stage VC you see a lot of folks working on things that people may or may not want.
But when you have much money you’re not forced to confront that reality. This was another way to have a check on: ‘Are we building towards product-market fit? Do we think we have it at this stage?’
That was really helpful and really important too.
Because I really think, for founders in particular, it’s a very pernicious failure mode. We can work on something for years and if no one actually ends up wanting it, if you don’t get to PMF, it’s really frustrating to have spent all this time on something that ultimately people don’t want and certainly doesn’t achieve the goals you probably had when you founded the company.
Having done that several times in my career, having built things that I thought people wanted but actually didn’t. That’s just really frustrating.
We really wanted to orient Vanta around that not happening.
…
The thing I told investors and it was mostly true as obviously there’s a little bit of posturing. If I take that money and put it in the bank account, Series A from whatever firm at whatever valuation, everyone at Vanta will feel very good.
And then we will wake up and realize ‘oh we actually don’t know how to spend that money, so we can’t spend it.’ ‘Now we’ve just diluted ourselves for 10-20% for a couple of days of feeling good.’ That’s not good.
Kind of jokey, but there was a real point there. In theory, we knew what to do with the money. You hire people. You spend more on marketing. Sure. We were hiring as quickly as we could. I would say early Vanta wasn’t the best at hiring either but we were hiring as quickly as we could
‘Will more money help us hire more people?’ Not really. We’re almost trying to bankrupt ourselves right now by hiring. And it’s still not going fast enough.
Similar with marketing. Probably we should do more marketing. We need a marketing person. We had no marketing people [back then]. It was kind of a point of pride in the early days but also a tremendous embarrassment.
I think there was a really pragmatic piece to it for me which was again, we can take this money and feel really good for a couple of days. But then we’d be delusional and kind of be in the same place.
‘So let’s not take that money until we know we can actual use it.’ So we can reset recruiting, find a few tremendous early marketing people which we did.
That sort of pragmatism coupled with the confidence (from the early-stage VC experience) that unless we go horribly off the rails ourselves, investors will still want to fund us.
Waiting longer makes them want to fund us more and kind of puts us in a stronger negotiating position. So, it’s good if you can wait and justify it with the business.
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Until next time,