PocketSuite uses Heap to increase mobile activation & retention

About PocketSuite

Formally launched out of YCombinator in 2016, PocketSuite is an iOS and Android app that helps self-employed services professionals run their business. The app gives professionals the power to schedule appointments, accept payments, and communicate directly with clients – all from a mobile device.

The product team at PocketSuite started using Heap for product analytics in early 2019, and since then has decreased paid user churn by 30%. We talked to Dan Mark, Product Manager at Pocketsuite, to understand how they achieved that accomplishment.

Dan Mark

Dan Mark, Product Manager

Shooting in the dark

Before Heap, I was shooting in the dark. I had no idea.

- Dan Mark, Product Manager

Before using Heap, PocketSuite’s product and engineering teams would have frequent meetings focused on implementing their analytics solution. Before any new feature shipped, they would have to spend precious time figuring out what to track, how to track it, and how to properly name events. The result? Huge gaps in the data and major difficulties understanding how customers used their product.

"For a company with massive resources, that’s how it’s done. At PocketSuite, we believe in being strategic and efficient about resources," says Dan.

A major driver in PocketSuite’s decision to invest in Heap was the agility that comes from Autocapture and Virtual Events. These features – which gave PocketSuite the ability to run analytics without having to decide in advance what they wanted to measure – were critical.

"Being able to go in, quickly form a hypothesis, and create new events myself if we forgot to track something is the major strength of Heap

Heap enables PocketSuite’s distributed team to get up and running with advanced product analytics very quickly, and spend more time developing the product. PocketSuite no longer has the bottlenecks associated with legacy analytics tools, like forgetting to track certain events or waiting for user properties.

Understanding user segments & increasing activation

PocketSuite’s product team is also using in-product behavior to understand more about their users. With Heap, they’ve been able to segment their users into two different categories:

  • Professionals with thriving businesses who want to get up and running on PocketSuite quickly

  • Professionals who are just getting started and need more onboarding assistance with PocketSuite

"Having all the data retroactive to when the SDK was installed is very powerful," says Dan.

The PocketSuite team now uses Paths and funnels to understand which features new users are engaging in, and figuring out how to make it easier for their user segments to get going in the app. Using Heap, they can now identify the characteristics of successful users, and what the in-product behaviors of those users are.One of the longstanding user activation metrics PocketSuite tracks is what they call their “Rising Star” metric. In this case, a “Rising Star” is a new user who has processed $1,000 in payments through PocketSuite. To create more Rising Stars, the team is now prioritizing a revamp of the app’s onboarding flow, and is adding a new dashboard for users. The goal is to encourage users to process more payments early on in their lifecycle with PocketSuite.

Moving forward

Overall, Heap has changed the way PocketSuite’s team works. No longer is the team slowed down by the bottlenecks associated with legacy analytics tools, like forgetting to track certain events or waiting for user properties.

The flexibility to ship something, and then say ‘I forgot this really important event’ and not worry about that is very critical for us.

- Dan Mark, Product Manager

Data is immediately available, and the team can use product data to inform the product team’s roadmap priorities, what types of users the team should be building for, and where to spend their time most effectively.


  • Deeper understanding of their user segments

  • Better activation for their new users based on the segment they fall in to

  • Less time spent using legacy analytics tools to query user behavior data

  • Faster development cycles informed by laser-focused user journey improvement and engagement priorities


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