Every product team wants to know what makes their product thrive. They want to know how to optimize metrics and leave users the happiest and most engaged. Without a way to definitively understand user behavior, they must turn to anything they can. Enter the A/B test.
Ultimately, every A/B test starts from a hypothesis. The hypothesis could be, “If we did [blank], then we would improve conversion.” Or “Feature X should drive increased retention, let’s test out that assumption through…Continue
Added by Divya Parmar on May 23, 2017 at 8:00am — No Comments
Whenever we make a decision in business, we test a hypothesis, no matter if it is in product, marketing or sales, at the end we make assumptions that will guide our actions. When we say that we will implement the next feature, or run this campaign we make a hypothesis that this particular action will have some positive impact to what we have set as a goal. The goal could be our revenues, our signups, the time it takes for a customer to use the…Continue
Added by George Psistakis on August 11, 2016 at 1:30pm — No Comments
Over the past few weeks, we’ve had several conversations in our data lab regarding data engineering problems and day to day problems we face with unsupervised data scientists who find it difficult to deploy their code into production.
Fig. Dream team? Einstein, Fisher, Tufte and Jobs