Adora vs Heap
Install once, capture everything from day one
Auto-capture: where both tools start
Traditional analytics tools require you to define every event before users generate data. Both Adora and Heap eliminate this. Install once, and all user interactions are captured from day one — clicks, page views, form interactions, navigation events.
Heap then lets you retroactively define events and build funnels, retention charts, and user paths from that captured data. SQL-based data access and warehouse integrations make it a powerful tool for data teams.
Adora takes the captured sessions and runs AI over them automatically — clustering sessions into journey patterns, detecting friction signals, and scoring issues by impact. No query-writing required. Patterns surface to product managers without analyst support.
How Adora and Heap handle auto-captured data
Features
| Features | Adora | Heap |
|---|---|---|
| Setup | Single JS snippet, live in minutes | Single snippet, similar setup |
| Data capture | Auto-captures everything | Auto-captures everything |
| Automated journey mapping | ||
| AI-scored friction insights | ||
| Session replay | ||
| Visual analytics on screenshots | ||
| Product Wayback Machine | ||
| Retroactive event definition | ||
| SQL / data warehouse access | ||
| Insights surface automatically | ||
| Built for product managers | ||
| SOC2 Type II, GDPR, CCPA |
Where Adora is different
- Journey maps generated automatically by AI — no funnel definitions needed
- Visual analytics overlaid on real screenshots of your product screens
- AI Insights continuously score friction patterns by impact level
- Session replays linked directly to the journey patterns they belong to
- Product Wayback Machine captures visual history across every release
- One-click Linear integration with session evidence pre-filled
Who each tool is built for
Different strengths for different teams
Adora is built for product managers and UX researchers who need to understand their product at a systemic level without SQL access or analyst support.
Heap is built to serve both product teams and data teams — its raw data access and warehouse integrations make it a strong part of a broader data infrastructure for organisations with dedicated analytics engineers.
Adora vs Heap at a glance
Adora vs Heap FAQs
What is the main difference between Adora and Heap?
Both auto-capture all user interactions. Heap stores them in a structured database for retroactive event definition and custom SQL querying. Adora runs AI over captured sessions automatically, generating visual journey maps and surfacing friction insights — no queries, no analyst required.
Does Heap do automated journey mapping?
Heap supports user path analysis, but paths are built from event definitions and presented as charts rather than visual maps. Adora's AI automatically clusters all sessions into journey patterns without any funnel definitions or event instrumentation.
Which is better for non-technical teams?
Adora. Journey maps, AI Insights, session replays, and screen analytics are all available without writing queries or defining events. Heap offers more capability for data teams, but non-technical users often depend on analyst support to get full value.
Does Adora have SQL access like Heap?
No. Adora surfaces insights through its AI-driven interface rather than raw SQL access. For teams whose analytical workflow depends on custom SQL queries and data warehouse integrations, Heap's data access is more appropriate.
Does Adora do retroactive event definition?
Adora doesn't use event definitions at all — its AI automatically identifies patterns across all captured sessions without requiring any event schema. Because everything is captured from install, all historical behaviour is available for AI analysis regardless of what was “defined” in advance.