Product dev teams are stitching together half a dozen tools (or doing some of it themselves) when they build, ship and optimize consumer-facing products. The result? There’s no unification across the stack, so it’s hard to ship new features and evaluate if those features are actually driving the business.
What’s more, engineering teams are dealing with poorly defined and unstructured data in their data warehouses. When the data looks off, they need to allocate time to look into it which means they become less productive. Sometimes there’s more than one person dedicated to the data cleanup process - there’s an entire team involved!
The data only matters if it’s helping you decide if what you’re building is useful. What’s the impact of the features that you’re shipping? What’s the impact of the experiments that you’re running?
Instead of spending time cleaning up messy data, teams should be spending time on things that will create a competitive advantagecreate a competitive advantage for the company.
Causal’s founding team hails from TripAdvisor, the world's largest travel guidance platform and data-oriented company that iterates rapidly to improve their products. At TripAdvisor, we spent an enormous amount of time trying to get the data into the right format. It was really hard to maintain good, clean data and over time the data got messier in our data warehouse. We also spent a lot of time building and launching A/B tests, but it was frustrating to be doing that work and not knowing whether it was pushing the business forward.
These are problems that we’re very familiar with, and quite frankly, we had enough. So we built Causal.
It should be possible for any product dev team to build, ship and optimize products that have a real impact on the business. You deserve to know that you’re building stuff that matters to your customers. You should have a system that lets you run experiments and evaluate if it’s driving the business (or not). And everyone on the product dev team (engineering, product, analytics) should be able to see the same data and work off of the same tools. A process that used to be broken, but not anymore.
Causal is backed by Pear, Founder Collective and 186 Ventures with notable angels including founders and executives from Tableau, Adobe and Flywire.
“Causal makes it easy to make good decisions based on good data.”
Staff Software Engineer, Summari
We had four A/B testing platforms—none of which met our needs—and I’ve been trying for years to unify them and solve our problems across our stack. We’ve started eliminating those other platforms and Causal has increased the velocity of our experimentation.”
Co-Founder & Chief Data Officer, Jobcase
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