We raised $19.5M to bring Airbnb-caliber experimentation to all

We started Eppo in response to a few truths:

1. The fastest growing companies of the past decade all invested heavily in pervasive, rigorous experimentation. Just talk to employees at Airbnb, Netflix, or Uber and you’ll realize that experimentation is the most impactful activity of their data teams.
2. The most common experimentation stack is still a completely in-house build. Commercial experimentation tools are overly focused on marketing use cases. As a result, they all woefully lack support for enterprise product experimentation.
3. These in-house experimentation frameworks necessitate committing dozens of senior developers, requiring business leaders to stomach wasting precious engineering resources on an internal tool that is the same everywhere.

On its face, an internal tool that is high leverage but requires significant resources should be an obvious buy vs build decision when it is the same for every business. At Eppo, we are making that decision much simpler by building experimentation tooling that has given every Airbnb, Netflix, and Uber alumni a relieved sigh of familiarity. Finally, commercial product experimentation has arrived.

Recession-proofing your data team

When markets turn south, the name of the game is ROI. Speculative bets on net-new future product lines get put on hold as companies focus on core products and the bottom line. All technical tools - whether purchased or internally resourced - requires a clear answer for how dollars come out the other end.

We have already seen how these dynamics lead to an explosion of demand for experimentation:

• For any B2C or PLG company, confidently separating product launches that improve core business metrics from product launches that do nothing for business metrics (or even hurt them) is an incredibly high ROI activity.
• For a data team, the only way for charts, analysis, and dashboards to have ROI is to meaningfully change company decisions in a way that drives metrics. Experimentation is one of the few data team responsibilities that is intrinsically tied to decision-making.

We’re seeing this play out in the industry and among our customers. While some companies have had unfortunate layoffs, across the board, experimentation-centric teams have been relatively unscathed by market belt-tightening.

Bringing statistical capabilities of FAANGs to the market

Companies like Airbnb and Netflix aren’t just running experiments, they’ve developed a toolkit and a culture that is hard to fathom unless you’ve worked there.

We were excited to announce one of these capabilities this year, CUPED experiment acceleration. This econometrics method is used across the board on experiments at Airbnb or Netflix. If you’ve ever run an experiment at Uber, Lyft, or Microsoft, you’ve invisibly benefited by your experiments taking up to half the time to complete. And reduced experiment runtime is a huge deal. It means more ideas tested, more learnings, and more impact.

The reception among our customers for CUPED has been amazing. In addition to the very tangible ROI from gaining all of this time back, CUPED is a great example of how Eppo is bridging the experimentation gap between sophisticated experimentation cultures like Airbnb and Booking and earlier teams who struggle to get even a handful of experiments completed.

Privacy-oriented, data warehouse-native

Eppo is the first data warehouse-native experimentation tool. For people who live and breathe the modern data stack subculture, this is a big deal. For everyone else, there are two important pieces to know:

1. For once, data teams don’t have to fight their analytics tools to get it to use good data. Eppo natively reads from the same data sources as your most trusted tools like Looker and Mode- your data warehouse. Ask your data team how often they’ve been undermined by 3rd party analytics tools reporting bad data to know why a data warehouse-centric world is a great one.
2. Eppo puts privacy first. We don’t ask that you send terabytes of sensitive user data to us. We can provide world-class experiment capabilities while computing within your own cloud. Even our in-app randomization SDK leverages your existing eventing infrastructure so that you can have instrumentation without betraying user trust.

We are fortunate to live in a world where tools like Snowflake, BigQuery, and Redshift mean you can have great 3rd party analytics tools and still use trusted data in a privacy-centered way.  Eppo is happy to join the crowd of warehouse-native apps as the first experimentation solution.

Eppo is backed by the world’s leading data + product leaders

Our series A was led by Naomi Ionita from Menlo Ventures. Between her lead investments in Endgame, Matik, and Teamflow, and her teaching at Reforge, Naomi knows the stressors and joys of product growth leaders like no other investor. Naomi joins the lead investor from our seed round Sarah Catanzaro, one of the leading voices in the modern data stack with lead investments in Hex, Datafold, and Meroxa.

Run an experiment in Eppo!

We’d love to show you what we’ve built. Request access to Eppo and we’ll help you get a few experiments set up.

Join the team

Our team is made up of veteran product builders from Airbnb, Snowflake, Slack, Amazon, and Stitchfix. We’re on a mission to change corporate culture everywhere. Have a look at our open jobs. We’d love to meet you.

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