Resources

Talk of AI in Data Science is everywhere today, but what is the role is AI playing in product analytics today? This webinar explores how has AI has impacted Data Science and how it is being leveraged for Product Growth

A customer's own dashboards indicated their A/B test experiment variant was losing. Fortunately, they looked at the Loops validation analysis. Ultimately, it drove a 12% lift in Conversion to Paid

Snehal Karanjkar of Kong, and formerly of ProductBoard and Dropbox, discusses best practices for effective business reviews and the best analyses for streamlined reporting

This case study highlights that many firms may be losing money without knowing it. In this case, a customer of Loops avoided a $5M revenue loss by quickly identifying an issue before it impacted the majority of their client base.

Olga Berezovsky, author of the Data Analysis Journal and experience growth leader, offers detailed advice on defining KPIs

Ken Rudin, Executive Growth Advisor, shifts the focus from "actionable insights" to actual impact, describing the prerequisites of impact.

Casey Winters, renown Product Growth Advisor, and growth builder of EventBrite and Pinterest, shares his thoughts on build to a "Learning Machine" to drive growth

Enjoy the Product Analytics Leaders' Meetup sessions in this "Masters Mini-Series". First up is Tom Laufer on how to deal with the correlation / causation problem by leveraging causal inference models.

Recorded Aug 6, 2024: Learn from the experts who presented in this very special online event.

Got two minutes? Check out this snappy overview of Loops, hosted by Loops CEO, Tom Laufer

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.

Wow, what a night for Product Analytics Leaders at our San Francisco Meetup! It was great seeing all the networking happen...

Wahi has always had a focus on product analytics, but quickly determined that their correlation-based approach of formulating hypotheses, trying to optimize campaigns and the product, and waiting weeks to months on A/B tests trying to identify causation, was not optimal.

An insightful discussion amongst B2C Subscription Growth Leaders, Casey Winters, Phil Carter, Tablish Gilani and Tom Laufer

Using Loops, Atera’s analysts detected that a particular modification was the primary cause of a KPI decline. Armed with this newfound insight, Atera’s team was able to adjust their views about the success of a new feature release, ultimately implementing a third round of updates in the same product area. These subsequent changes resulted in a substantial boost in Atera’s funnel conversion rates. Thanks to the insights provided by Loops, Atera’s team rapidly learned from their previous iterations and could react accordingly until achieving success.

B2B experts discuss the top execution drivers for product growth in B2B businesses, in 2024

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

Generating hypotheses is a critical aspect of the data analysis team’s work at monday.com. However, assessing the worthiness of a hypothesis can be overwhelming, particularly for a team that conducts hundreds, if not thousands, of analyses daily.

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.

How data teams can move beyond building dashboards to actually moving the product and the business needle.

Andreas Gross started Life360 and scaled other businesses, such as Reddit and Credit Karma. Here he discusses "Why Loops."

Insights and hard truths about why so many product teams are misusing data and how you can break the cycle

Gad Allon, Loops angel investor and Jeffrey A. Keswin Professor, and Professor of Operations, Information and Decisions at the Wharton School ta;lks with Tom Laufer about "Why Loops"

Japna Sethi, a Loops angel investor and Director of Product Management, Growth at Calendly, tells us in her own words, “Why Loops."

We talked with Tabish Gilani, Growth at Kajabi and former Head of Product at Replit, who shared his thoughts on why A/B testing is so much more than an easy experimentation tool

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.

In this session, we asked Casey Winters, the former CPO at Eventbrite, about what opportunity he sees in Loops for product and data teams. Casey shares a lot of valuable tips about how to approach experimentations, how to align product managers and data teams, and shares from his vast experience working in companies like Eventbrite and Grubhub. Enjoy.

When 18Birdies started working with Loops, the platform presented an opportunity to improve on 18Birdies’ pre-set KPIs with the “Goal Driver” analysis. This analysis automatically identifies the features that maximize a company’s KPIs using causal inference models, which enable you to get significant results with minimal traffic.

In this article, Iyar Lin, data science lead at Loops, goes through the “behind the scenes” of one of our most used types of analyses: Release Impact.

In this session, we asked Adam Fishman, the former VP Product/Growth at Patreon, about what opportunity he sees in Loops for product managers, and to share some tips about experiments and alignment between product managers and data analysts. Enjoy.

A partnership between the firms aimed to identify more product growth opportunities by validating uDocz’s hypotheses using Loops’ unique causal inference models and analyses.

Hi, I’m Tom Laufer, and together with Ido Adiv, we founded Loops, a revolutionary analytics tool that helps product and data teams crush their KPIs by finding impactful growth opportunities hidden across their data.

Taboola is one of the leading ad-tech platforms in the industry, serving over 360 billion content recommendations each month.

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.