Naomi Ionita: belief

Transcript context

…I am. I love it. There's so much school stuff happening there and I'm really excited. Yeah. Yep. Cool. I think another layer in the stack is experimentation. So this is really critical infrastructure, in my opinion, for these cross-functional product data growth teams to A/B test hypotheses and understand their impact on the business. How do you know if you make a change in the product or your pricing, whether you succeeded or failed without having infrastructure like this along the way? Category creators like Optimizely really paved the way. I was an early buyer of Optimizely and they targeted marketing personas, and it was just game changing to be able to start to A/B test things and bring hypotheses to life. I'm also biased as an investor, but some of the modern tools here, like Eppo, which offers experimentation for the modern data stack. So unlike Optimizely, which focused on more kind of click through metrics, Eppo ties directly to the metrics in your data warehouse. So tying an experiment result to things like subscriptions or revenue or margins, really like board level metrics that you're trying to move. They make that full trip really convenient and understand the impact on those business KPIs directly. So it's a lot of automation around the experimentation, results. And analysis they used to live off to the side in Excel or Jupyter Notebooks now is automated away with Eppo. I think you're familiar with that one. Yeah, we definitely didn't plan this, but Eppo's both a happy sponsor of this podcast. I'm also an investor in Eppo. Go Eppo, but this was not planned.…

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