Heap for Product Analytics
March 20, 2022
Heap for Product Analytics
Score 8 out of 10
Overall Satisfaction with Heap
We use Heap as our primary user behavior tracking and analysis tool. Before Heap, we didn't have a very clear picture of how users interacted with our product. Heap allows us to better understand how users engage with our product, what a typical user flow looks like, and where there are frictions in our product. Typical use cases include the new customer onboarding funnel, tool setup funnels, and the customer support ticket funnel. In addition to user behavior funnels, Heap has been a valuable tool to understand which features of our product are used more/less frequently as well as which support and documentation articles are most popular. Finally, we've used several of Heap's integrations to pull in data from other sources, like Salesforce and SendGrid. This allows us to improve our user segmentation in addition to investigating complex user flows, like what the most common user journeys are after receiving an error email.
- User Behavior Funnels
- Common User Paths
- Active User Calculations
- Account-level analysis is difficult
- Funnel analysis at the session level not supported
- Properties that change over time are difficult to use
- Improved focus on friction points of product
- Better understanding of important/less important features
- Improvement on onboarding flow
Heap stood out from other tools in the following ways: Comprehensive auto-tracking and "spotlight" tool allows us to add event attributes through their UI which greatly reduces the reliance on Engineering resources for instrumentation. Their "Effort Analysis" tool helps identify points of drop-off and automatically identifies users' bottleneck points in a user funnel. Their "Funnel" tool identifies events we may not include in our original funnel that could be important factors in a user's journey.
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Heap is a great tool to use for user behavior analytics, particularly where the user level is the primary level of account. This is typically the case with B2C platforms. Heap is more complicated to use for B2B platforms, where an account has multiple users and the same user can be a part of multiple accounts. Heap is also well suited for websites that aren't built on React. With React, engineering support is required to add data attributes to all clickable parts of your website, like buttons. This is an important distinction to make as you're evaluating product analytics tools as it adds complexity to the setup of your Heap instance.