Heap for Product Managers
April 21, 2021

Heap for Product Managers

Anonymous | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Software Version


Overall Satisfaction with Heap

We use Heap across our entire organization to track front-end metrics that help us understand adoption, engagement, and retention with various aspects of our applications. Heap is our primary source of data for making key product decisions.
  • Provides retroactive metrics for things you didn't tag.
  • Solid charting interface.
  • Easy to create and share dashboards.
  • Trying to force the use of wizards for every user.
  • Usability bugs - too many rough edges on day-to-day tasks.
  • Cumbersome event definition process.
  • Increased product adoption.
  • Improved engagement with key features.
  • Reduced time to diagnose front end errors.
Heap is very usable if you want to create analysis that is aligned with what they designed the tool for. However, two things hold it back. First, they are trying to create more and more wizards which end up making everything take longer. Second, the ability to customize beyond the basic charts provided is very limited.
As long as you are fine looking at slightly stale data then the load times are fine. But refreshing queries to get the latest data can take some time depending on the complexity of the query and the size of the data set.
I was not the person who decided to use Heap, but I'm happy with the decision. Heap's ability to support analytics retroactively for any front end events is powerful and allows teams to move quickly. And the included pre-built chart templates are more than enough for most our needs. Compared to platforms like Looker that are more about custom analysis, Heap is easier to learn and get going with.

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Figma, Miro, Atlassian JIRA Align (formerly AgileCraft), Looker, Todoist: To-Do List & Task Manager, Zoom, Slack
Well suited:
- Understanding basic front-end interaction patterns
- Creating straightforward adoption/engagement/retention charts
- Basic triage for front-end bugs and errors

Less Appropriate:
- Any analysis which requires the use of back-end data
- Multi-user interaction
- Sophisticated analysis which requires customization beyond basic filters