Everyone's obsessed with these all-in-one product analytics platforms. They're not magic. You're paying a premium for them to do the ETL you could build yourself.
Heap's auto-capture is just a giant firehose of events into their schema. FullStory's session replay is basically video hosting with a markup layer. The cost isn't in the feature, it's in the volume. Heatmap data is enormous. Event streams are enormous. They both charge for it, just in different columns on the invoice.
Seen too many teams get a nasty surprise when their MAU grows 20% and their bill grows 200%. The pricing pages are useless. "Contact us."
I want to know where the real cost traps are. For those who've implemented both:
* Is the session replay/heatmap storage the actual budget-killer with FullStory?
* Does Heap's "unlimited events" model just bury the cost in compute/scan fees when you query their warehouse?
* Anyone done a cost comparison against rolling your own with OpenTelemetry streams into a cheap data lake and using something like Metabase for the dashboards?
The vendor's answer is always "your data is valuable." My question is, is it *that* valuable?
SQL is enough
I'm a platform lead at a mid-market SaaS company (about 50 engineers), and we migrated from a DIY event pipeline to FullStory, then later piloted Heap. Our product sees about 400k MAU.
**Core comparison**
* **Real pricing structure:** FullStory's pricing is tied to "session equivalents," which bundle replay, heatmaps, and analytics. When we doubled our MAU, our bill increased about 2.7x because session length also grew. The storage for replay data is the silent budget-killer. With Heap, the "unlimited events" model costs you on the back end: their Data Warehouse query model charges per million rows scanned. A complex query joining multiple tables could easily scan 100M+ rows. At our scale, running our core dashboards daily in Heap cost roughly the same as our FullStory contract.
* **Deployment & integration effort:** Heap's auto-capture is easier to start with, but you'll spend significant time defining events post-capture and managing taxonomy sprawl. FullStory requires more upfront instrumentation to get real value beyond session replay, especially for tracking custom e-commerce funnels. Both require a dedicated resource to manage.
* **Where they break:** FullStory's session replay becomes economically unviable for long, complex sessions (like admin panels). We had to strategically exclude certain user paths. Heap breaks when you need to retroactively analyze a user property you weren't capturing before; their "auto-capture" doesn't mean you have all data.
* **Vendor responsiveness:** When we were at the ~$50k/year level with FullStory, support was excellent. At lower tiers, response times slowed. Heap's sales was aggressive, but their support for technical implementation details was slower. Both will push for an annual commitment.
**Your pick**
For a product team focused on UX and conversion funnel optimization, I'd lean toward FullStory, but only if you can strictly govern session recording volume. For a data or growth team that needs to ask ad-hoc questions across a huge event corpus, Heap is the better starting point, provided you implement strong naming conventions from day one. To make the call clean, tell us your team's primary goal (conversion rates vs. behavioral analysis) and what percentage of your user sessions you can realistically sample (1%? 10%? 100%).
That's super helpful, thanks for the concrete numbers. The "unlimited events" trap with Heap's query cost is exactly the kind of thing I'd miss. Makes sense why they push that unlimited thing so hard upfront.
So would you say, for a startup trying to keep costs predictable, it's almost better to think of both as having usage-based pricing? Just in totally different parts of the stack?
Also, which one had a steeper learning curve for your PMs to actually use day-to-day?