Rippling Operating Lessons, #1: Learn the Business
How obsessive curiosity leads to greater impact
A lot of advice for people working at startups isn’t very helpful. Tactical advice gets outdated fast; and rosy post-exit narratives are hard to apply to the day-to-day grind.
The type of advice I’ve always found more helpful, is more general: operating principles that you can use in any situation.
I just wrapped up 3 years in growth & GTM at Rippling, during a period of 5x revenue growth. My teams worked on marketing to fuel that growth, from scaling cold outbound, to rebuilding our cross-sell motion, to taking new products to market. It was the most intense learning experience of my career.
There’s certainly no avoiding the late nights and trial & error of working at a startup. But, there were some things I wish I’d known, especially early in my career. Over a set of posts, I’ll try to share them.
Lesson #1: Learn the Business Yourself
Most people at work just wait for assignments then do as they're told. But the real secret to success at startups is forming such a deep understanding of the business that you can set your own priorities, spot opportunities your boss missed, and take work off their plate.
At Rippling, I spent countless late nights sprawled on my couch in un-ergonomic positions, scrolling through seemingly random things: Tableau dashboards, Outreach replies, Gong calls, deal notes, marketing collateral. I even studied executives' Google Calendars, curious about their focus areas. Rippling’s compound startup approach, with so many products and buyers and a massive TAM, makes the business more complex than most SaaS businesses, so I spent a lot of time constantly learning.
The people who rise fastest in hyper-growth companies develop an independent view of how the business works - beyond what’s assigned to them. This is the attitude that leads to promotions - responsibility at higher levels requires independent judgment. When you’re early in your career especially, it’s easy to assume that leadership knows everything. But they simply can’t maintain that much context. You are ultimately closest to your work, and leaders want you to own it.
For example, when I started working on scaling our automated email program, our head of growth was convinced the big unlock was building a coordinated system to reach multiple decision-makers at an account, simultaneously. But after digging into the data myself, I realized we had a more obvious problem: volume. Our database wasn’t capturing everyone Rippling could be targeting. So I focused on negotiating contracts with data providers and working with engineering to integrate the new data. That became one of the biggest things we did to grow the channel. The coordinated system barely moved the needle.
The mindset is simple: assume hidden opportunities exist. Fast-growing companies miss things constantly. In high-growth environments, nothing is sacred. Systems built six months ago are probably ripe for improvement. Ask "why are we doing this?" and "why aren't we doing this?" Push back on your manager when evidence points elsewhere. I loved when my reports did this - it meant they were thinking independently.
Sometimes this means stepping outside your function. High-growth companies reorganize constantly. An org chart is the company's best guess at how people should work together at that point in time, and it won't be perfect.
Major levers often cut across functions. If you can spot these and push them forward, you'll be invaluable. An example: we discovered customers were getting too many product notification emails and were starting to generally tune out comms from Rippling. We worked with product to cut the noise massively - well outside my "official" remit.
What should you be digging into?
This is going to vary by what function you’re in. You’ll need to figure out what’s relevant for your role, but these examples from marketing should give you a sense of the range of investigation you might want to do. Obviously deploy Claude and ChatGPT to help you extract insights fast.
Analytics dashboards. Our VP of data came up to me one day impressed that I was one of the top 10 Tableau users in the whole company, even though I wasn’t in engineering or data science. Come up with your own questions about the business (what channels are driving the most revenue? where are customers spending the most time in the product?) and try to answer them. When you can’t, build your own reporting (more on that below.)
Product demo. Understand the product end to end and how it solves customer problems. Get a demo account and spend unstructured time playing around in the product. Report bugs to the engineering team and scout for opportunities.
Sales demo recordings. It’s important to hear in the customer’s own voice what their problems are. This can lead to unexpected insights. For example, we realized after looking at initial demos, that Rippling IT had surprising product-market fit with CTOs dealing with IT tasks - but we hadn’t initially prioritized them..
Strategic plans (functional, financial). Quarterly and annual planning were some of the times when I most rapidly accelerated my understanding of the business. Understanding a GTM forecast and budget, and building your own, will force you to break down the business like a system. Understand the funnel (e.g. leads, demos, revenue), key assumptions, and risk areas. Also look at your function’s plans which lay out the strategies and the key initiatives that ladder up to them. E.g. if you’re in Growth, look at the entire Marketing team’s plans and budget to understand how all of the parts work together.
Chatting with people. Dashboards are great, but so much insight just comes from conversations. Meet with all the people related to your role and come with a list of questions. Run your initial hypotheses by them and get their reactions. When Bao onboarded into a new role on cross-sell marketing, she sent out a Google Form survey to our whole Account Management team to get their insights on how we could market to customers better.
Campaign replies & deal notes in your CRM. I was constantly reading through replies in Outreach to get a read on my campaigns. I built analytics to to automate this process. I also spent a lot of time reviewing pipeline with sales.
Databases and tooling. Snowflake tables, function-specific systems or tools. From poking around in various databases, Noah found pools of “stuck” TAM in different parts of our GTM systems that were being suppressed from our marketing efforts.
Competitors and broader ecosystem. How does your company win at the broader scale? How are you differentiated from competitors? What is your product strategy? What are competitors up to in their product, GTM, etc. and how will you win? It’s important to zoom out of day-to-day execution and look at the macro.
How to build this into your day-to-day
Ship quickly to validate your ideas: You should feel almost like a researcher digging around to come up with new ideas. But the cool thing about being in an operating role at a company is that you can prove or disprove your hypotheses nearly immediately. Have a hypothesis on a better pitch for sales reps? You can go out and test it, today. This is one thing I love about company-building: it’s easy to thrive if you’re insanely curious. Dig around, come up with new ideas, and test them!
Own your own onboarding. I think onboarding is ultimately the task of the employee, not the manager. Whether it’s your first role as a new company, or a role change, view it as your responsibility to get onboarded effectively. Keep a doc with an ever-expanding list of questions, and update your answers as you learn. Balance being a sponge with forming your own opinions. The more senior your role, the more you'll be expected to onboard yourself. Start practicing it now.
Carve out ongoing time to poke around. Rippling has made this into a value called "go and see." I tried to carve out 1-2 hrs/week to do this as a standard practice; for example, regularly looking at recently launched campaigns and deals in the pipeline. While you can automate much of this analysis, don’t lose sight of the “store” too much - you should still go and check on the raw data. For big, open-ended problems, I’d block much more time to learn.
Build your own analytics. This gets faster with practice. You should learn SQL rapidly if you don’t know it, and you should also be comfortable in Excel. ChatGPT and Claude help a lot here. Apart from specialized creative roles, like brand designers, the most effective people I worked with were typically very comfortable with analyzing data.
If there’s one thing to take away from all of this, it’s this: be obsessively curious. For me, this is one of the most underrated parts of operating. People often assume that building a company must be much less intellectually stimulating than, for example, being an academic researcher, or a journalist. But I think that for the most effective company-builders, that doesn’t have to be true at all. They never stop learning.
Great read and epic advice!