1: A/B test as fast as you can. Frequency is Key
2: Ensure your reach of A/B testing is enabled. Meaning, across the entire customer journey. Top, Mid, Bottom of funnel.
3: Challenge your team to do advance a/b testing. Example, personalization, Multivariate testing.
Number 1 is key to ensure you understand what YOUR specific end users are responsive to, relative to the category of business you are in. Its different for each vertical.
Growth doesn't have to be complex. Measure some stuff and test some stuff. Go, go, go.
If you don't have enough traffic to A/B test. Then you have bigger problems to solve.
It's worth noting that the panel is largely made up of companies whose products seem strongly communal by nature. Slack, Pinterest, Instagram, YikYak, Facebook, and Twitter are social platforms. AirBnBs are shared with fellow travelers, Ubers with other riders (and on the supply side, driving as a side job or renting out a property seem likely dinnertable conversation topics). Stitch Fix, Fanatics, Square are the three that stand out as having a more 1:1 interaction between the company and the customer, where the nature of the business is a product/service being exchanged directly for $$ and isn't likely to rope other humans into the process.
Given this, not sure how well this early-growth-team framework generalizes. The article is a "Growth Guide: How to Set Up, Staff and Scale a Growth Program", but seems to be a model built to explain a somewhat homogenous data set, and I want to question how it would fare if applied as a template for early growth teams generally.
100% agree with the following:
- "Startups that have seen amazing growth have developed teams and processes that are intentional, exceedingly metrics-driven, and thrive on experimentation."
- "Scientific approach to growth"
- The retention checklist, picking core metrics, etc.
- Experiment dashboard, analytics tools, peer review, user research
- That all of the advice is well-suited to companies whose growth is (1) primarily driven by the product itself, esp. by referral/virality, and (2) for whom retention is especially important. (1) and (2) are certainly not true of all startups, and maybe not even true of most, though I'd trust YC to have a better statistical view on this than I do.
Less sure these heuristics are broadly applicable:
- Growth PM = first growth hire at a company
Depends on how we're defining "growth", but if we say "the first growth hire is the first person whose primary mandates are acquisition, activation, revenue, retention, referral", then it could make sense for a first growth hire to focus on e.g. paid acquisition if that is the highest-leverage growth driver early on. This was my experience at Upstart (ML-driven lending platform), where my mandate as the first growth hire was to do whatever it took to grow. It turned out that priority #1 was to build out targeted paid acquisition campaigns. If some flavor of performance marketing, or partnerships/sales, or content or in-person events are the strongest growth tactics at the early stages of scale, does it not make sense to build a growth team starting with those early hires, and add eng/PM/design/data science from there? This seems like a case worth mentioning if it's not extremely rare.
Perhaps this is just a semantic thing, where the panel would respond that the aforementioned first growth hires would would be called something other than Growth (i.e. you might build a 1-2 person Marketing or Sales team to deploy ad spend or build partnerships, and the Growth team would sit separately with Product)? Seems odd, but... maybe. I'm especially curious what YC has to say about this from observed patterns across many different business models and early growth team structures at companies in the 10-50 employee range.
- "70% of experts mentioned that referrals were the top channel within the first year."
This stat seems to follow from the homogeneity I mentioned; seems worth calling out that this doesn't mean it's 70% likely that any randomly selected growth-stage startup should focus on referrals in its first year. While any great product will be talked about and benefit from referrals, it's a stretch to say this will be the top channel for most startups, and I worry that the guide recommends a team structure that lends itself to virality-first growth when this isn't a template that applies as widely as the article implies
- The circle chart Sean called out (where 70% of the growth teams sit in Product)
I particularly disagree with this snippet:
"Traditionally, a company’s marketing team has been responsible for driving user acquisition (and the associated budget), so this is sometimes a default department in which to house a growth team. Often this evolves from prior functions that have lived in the marketing department (like performance marketing and user acquisition). In these cases, the Head of Growth would report to the Head of Marketing. The general sentiment about this approach is that the line of reporting is a bit rooted in the past, and most growth experts cited this as the least-favorable option."
I don't think the line of reporting is necessarily "rooted in the past" such that the orange 70% in the pie chart are the modern, smarter ones and the rest are the dinosaurs. Instead, I suspect that the type of growth those companies experience are more deeply rooted in the product itself, so it's natural for Growth to sit within Product, and this may be true of many modern companies. But it's not a function of modernity, it's a function of the nature of the product itself.
This is all coming from someone who has built growth frameworks largely from first principles (rather than direct mentorship from someone broadly experienced) with only a few years of personal experience, so I'm spelling this out as a request for someone to please point to any blind spots in my reasoning.
We struggle to attract the 'Ideal Engineer' to apply, most of our recruitment pipeline is filled with mediocre candidates. Do you have any tips or examples on how to communicate and attract the 'Ideal Engineer'?
Apply on your site or getting candidates you are interested in to actually interview? If you want the 'ideal' engineer, you need to identify them and go after them.
Hello Anu! How would you recommend selling these metrics to people focused on things like app downloads or user signups? Essentially, how would you recommend advocating for adopting these metrics?
It all comes down to knowing how a company makes decisions. What's the thing that sells. At most companies it is revenue, so you basically run experiments that correlate to revenue strongly and then use that causation to adopt new metrics. People like metrics that lead to their higher order KPIs a lot.
Great question. This really has to come top down and starts with the CEO. If the CEO urges the team to focus on the right metrics and asks questions on weekly reports then over time this will be in the DNA of the entire organization. Else it is really hard to get the organization to adopt these metrics
Great post and overview, Anu. Do you have any specific learnings for B2B companies and companies that generally have lower volumes of traffic for experimentation?
If you have only a small sample size to experiment with then you need to run experiments that can cause dramatic lifts (not minor changes like moving a link, etc.) Because if you have a sample size, then you need to wait much longer to measure the significance of these results and as a startup, time is not on your side.
I think if you can't get statistical significance than the growth team model is probably too early. You mostly need to be in the "invest" stage and not the "test" stage. That's not to say you can't try to hack merely that measuring through multivariate tests is a waste of time and effort.
Yes. We plan to! There are so many nuances with B2B that we felt it deserved a separate post. Having said that products like Slack (though B2B) is a lot similar to how a consumer app would scale. So it really depends on the type of product you are building
Number 1 is key to ensure you understand what YOUR specific end users are responsive to, relative to the category of business you are in. Its different for each vertical.
Growth doesn't have to be complex. Measure some stuff and test some stuff. Go, go, go.
If you don't have enough traffic to A/B test. Then you have bigger problems to solve.