Data Science

How to leverage causal inference models. Understand causal insight accuracy versus A/B tests. Learn how to make impactful decisions with less traffic, time, and cost.

The ultimate playbook for understanding your product KPI changes and avoiding loss.

It’s 2024 and analysts are still wasting time figuring out why their KPIs dropped. We know this from our interviews with 40 growth analytics leaders. They all said the same thing

Moments I call “change-led growth” ;) When Ido and I founded Loops, it wasn't to change the world, at least not all of it at once. We saw a specific problem.

The simple answer is yes. The not-so-simple answer is that Loops’ "Release Impact" offers a proven alternative to A/B testing. Let me elaborate.

For data and product professionals, one of the significant challenges we often face is conducting meaningful experiments when product traffic is relatively low, a known scenario in B2B products.

Until recently, AI was perceived as almost imaginative, only reserved for particular usages. But in a very short time, and with the emerging generative AI, we have an AI solution for almost anything - including Product and Growth teams.

Whether you’re looking to make product feature updates, increase customer retention, enhance the conversion rate of a particular stage of the customer journey, or penetrate an entirely new market segment, the “how” will start with a hypothesis. Just like other fields of scientific studies, product management and growth requires data to back up your hypothesis and ensure the insights gathered are accurate and yield the best decision.

There’s no doubt that in today’s data-driven digital landscape, the amount of raw data a product manager encounters on a daily basis is enormous. Analytical product managers and their team members alike spend hours upon hours, staring at dashboards analyzing data, as they pursue their “never-ending quest” in discovering valuable insights about how users interact with their product.

In today’s forward-thinking, customer-focused organizations, product teams are constantly evolving and changing. New teams and functions are created as a way to empower the specialized expertise that’s leveraged to establish a competitive advantage. As the issue of acquiring and retaining users is critical to a product’s success, the evolution of product growth teams that focus on moving the needle on critical success metrics of their products should come as no surprise.

The explosion in the use of data has upended the way product and growth professionals make critical decisions about how they build their products. Product teams do their best to leverage near-infinite amounts of data to discover insights that help them develop better products. They’re on a mission to gain clarity regarding how users interact with their products and more specifically, discover the features and flows that delight users to the point that they become ambassadors that drive viral growth.