Grow reduces time to insight 81% by moving off of Google Analytics

Alan Winters is the VP of Product at Grow, and has been working on product teams in the space for decades, including leadership roles at Domo and Omniture. When he first joined Grow, Alan’s mission was to drive product changes based on clear, data-driven insights. He wanted to leverage data to learn what provides the most value to Grow’s customers, outperform his competition and drive customer satisfaction and retention.

Grow, Alan Winters

Alan Winters, VP of Product

Where to start?

Alan wanted to better understand Grow’s customer experience end-to-end. Grow’s core use case is enabling users to visualize key business metrics in easy-to-use dashboards. To do this, Alan needed to ask several questions: What product improvements would drive revenue and retention? How successful are users in their first attempts to use the product? What key obstacles prevent a great customer experience and a commitment to purchase?

Initially, Alan tried Google Analytics, but as the attempt was “just excruciating,” he says, “I couldn’t think of all the questions I needed to answer up front.” As a result, he spent significant time back-tracking as he learned, only to find that with each new question, he “had to go back to the drawing board to reimplement a new measurement, and then wait for Google Analytics to collect enough new data to provide an answer. At that point, I knew we needed something better.” His team also considered developing the capability in-house. Even if they could, he would still have to think through everything that needed to be tracked ahead of time.

Next, the product team compared Heap against Mixpanel. They evaluated both tools in tandem against a list of criteria, including time to first insight, speed of iteration, ease of use, and ability to answer crucial questions.

Bake-off: speed and quality

Heap demonstrated clear advantages, including faster implementation, the ability to ask questions more quickly, the simplicity of setting up actions and getting historical data, as well as a higher volume of better quality insights. “Immediately after implementation, we found answers to questions we thought would take a month to answer with Google Analytics.” Alan remembers that “there really wasn’t anything advantageous about Mixpanel—Heap was on par or better than Mixpanel in every scenario.”

Alan felt confident that Heap would enable more extensive and quicker iteration on their analysis. Heap also aligned well with their product roadmap and how deep he expected his team to go with the data, across both non-technical and power users.

The first insight

Once up and running with Heap, the team decided to dig into a fundamental question: What is the user experience building his or her first business dashboard? The team already had an idea of where to start based on qualitative feedback from select users. With Heap in place, the product team was able to measure the full extent of the challenge their users had when trying to create a new dashboard or bring in new data sources and format their visualizations. The first insight: Analysis in Heap showed that 62% of users would drop out of the build experience without completing their first data visualization.

Alan realized that “without Heap, we wouldn’t have been able to understand this was even an issue, or understand the points of significant friction, let alone measure the details of the problem,” which became clear within a week of using Heap.

From insight to action

Confident they could improve the experience, the product team set out to completely revamp the dashboard building experience. Using Heap to test, measure, and iterate as they went—without worrying about tracking code or developer resources—the product team pushed out a new beta to about half their customers.

Dramatic results

The results were better than they could have hoped for. Average time-to-completion of the new build experience was reduced by over 80%, down from 57 minutes to 11 minutes. With such a dramatic reduction, their customers’ time-to-value was significantly shortened, and their users began creating more dashboards, using more data, and ultimately deriving much more value from the Grow platform.

A data-driven culture

Since bringing on Heap, measurement is at the core of everything the Grow product team does, and even engineers are encouraged to access Heap. Together, engineers and product managers start their development plan with Heap data, helping Alan and his team determine what to work on next, measure success in their projects, and support product decision-making. With a weekly development cycle, “our product managers have adopted measurement in everything they do, and now, data is the central part of every discussion and decision.”


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