Lessons from scaling Ramp

I strongly, strongly believe that small teams of successful people can drive a lot more impact than larger teams of mediocre people. And so I strongly believe you have to design a system where you're able to reward 10X operators with 10X the comp.

What a great growth engine and a great growth team is one that where you set the culture, set very simple north star metrics, usually one, at most two. And you've created a culture of defining hypotheses that are data driven and a culture where that can be executed quickly and have an MVP mentality for product and non-product projects where people can fail and learn quickly and iterate quickly.

Revenue is, for better or worse, more important to the company, but also much farther down the line of whether or not the growth team can directly impact that. And so at Instacart, for example, our north star metric for growth was monthly active orders. And that's what we all rallied around and looked at every day.

MAO refers to Monthly Active Orders (or Monthly Active Orderers), which was Instacart's north star growth metric.

We created via the finance and data team, a translation layer for every team's metric into MAO. It would be like if you got one extra weekly order because of your checkout flow from the same customer, it would have point X impact on the company's MAO and then you would just roll up all project plans as well as project impact back into this singular MAO metric.

We don't work in years, quarters, weeks, we work in days. Each day matters and so never put out something tomorrow that you know can get done today.

I think what we've done differently is we've really focused on making all of those investments very much driven by technology and data. And so one example that I'll give you is that our sales teams are actually incredibly efficient by any metric that we look at and we obviously benchmark them. And the reason for that is because we actually have a growth engineering team that's dedicated to supporting that efficiency but including adjusting third party data and using AI to automate much of their workflow.

I do think there's actually a general path that most B2B companies take and should take. My view is you start off with founder-led sales, the early team needs to know how to actually sell. Then you hire your first couple of salespeople, then you start some very low cost targeted marketing efforts. So whether it's content, community, small scale events, and then PR, after all of that is when you start paid and brand effort and then SEO probably start around the same time that you start paid marketing efforts. The reason for the progression the way I've described it is the channels get more expensive as you go farther along and they get more effective as you understand more about your customers.

Ramp is a corporate credit card and expense management company. "The quota" refers to sales revenue targets that teams are expected to hit.

It's unique to Ramp where the engineers feel ownership of the quota. They're not owning product metrics or what have you, they're obviously of course interim and input metrics that are important, but they really do feel accountable for the pipeline driven and the efficiency driven by that team.

There's a fundamental flaw to it which obviously is that you're focusing on cost and not the value derived. And so when you focus on CAC and reducing CAC, what tends to happen is you actually might be doing something very damaging where you're succeeding in reducing CAC, but you're actually bringing in customers that are less valuable because those are the ones that you're able to attract with a lower CAC.

Growth experiments in my history are typically 30%-ish success rate. So the vast majority of things that you try don't work. And so you want to create a culture where people aren't afraid to take risks and aren't afraid to fail. And for me, failure is not that you didn't drive revenue, failure is not learning.