AI Product Analytics
Heap
SF 8.6Autocapture analytics for digital product teams
Free · PaidPro from $22/moFree plan available; paid plans scale by sessions.
AI Experience Analytics
FullStory
SF 8.4Session replay with digital friction insights
Free · PaidPro from $22/moFree plan available; paid plans scale by sessions.
Quick decision guide
Choose based on your workflow
Heap may fit better if...
- Autocapture Tracking
- Retroactive Events
- Funnel Reports
FullStory may fit better if...
- Autocapture Events
- Friction Signals
- AI Summaries
Overview
How each tool is described
Heap
What is Heap?
Heap is a product analytics platform that automatically captures interactions across websites and mobile apps, giving teams retroactive behavioral data for funnels, journeys, retention, and experience analysis without requiring every event to be defined in advance.
- Data capture: Autocapture records interactions such as clicks, taps, pageviews, swipes, screen views, and form activity. Teams can supplement this data with manually tracked, API-based, and server-side events when additional business context is needed.
- Analysis role: Journeys visualizes the paths users take before and after key actions, including alternate routes and conversion rates. Integrated Session Replay adds visual context so teams can move from an analytics finding to the sessions behind drop-offs, friction, or unexpected behavior.
- AI assistance: Sense Chat lets users ask behavioral questions in natural language, generate charts, review AI-written data summaries, ask follow-up questions, and inspect how the analysis was produced without manually configuring each report.
- Commercial considerations: Heap offers Free, Growth, Pro, and Premier plans. Session allowances, data history, account analytics, warehouse connectivity, regional storage, and other capabilities vary by tier, while Experience Analytics and Heap Connect are add-ons on some plans.
Heap is particularly relevant to teams that want to investigate product behavior retrospectively and answer questions using already captured interaction data instead of depending entirely on an event-tracking plan established in advance.
FullStory
What is Fullstory?
Fullstory is a behavioral analytics platform that captures how people interact with websites and mobile applications, then connects session replay with product analytics, journey analysis, heatmaps, and AI-assisted investigation.
- Behavioral capture: Fullcapture automatically records supported interactions without requiring teams to define every event in advance. That behavioral dataset can be explored through session replay, funnels, segments, heatmaps, metrics, and journey maps to investigate experiences that were not necessarily anticipated during instrumentation.
- AI analysis: StoryAI includes session and multi-session summaries, Ask StoryAI for questions grounded in Fullcapture data, and Opportunities for identifying and prioritizing behavioral friction. Newer StoryAI Agents can also investigate issues and monitor areas such as funnel performance and releases.
- Implementation checks: buyers should assess web and mobile capture requirements, privacy and masking configuration, session volumes, retention needs, integrations, user access, and which teams require replay versus broader analytics capabilities. Mobile capture is offered as an add-on within Fullstory's current packaging.
- Commercial considerations: Fullstory offers Business, Advanced, and Enterprise paid plans plus FullstoryFree. The free plan currently includes up to 30,000 sessions per month, 12 months of retention, and core replay and analytics features, while capabilities such as StoryAI and other advanced features require paid packaging or add-ons.
Fullstory is particularly useful when product, UX, engineering, support, and growth teams need to move from a conversion change, error, or friction signal to the actual behaviors and sessions that explain what happened.
Side-by-side
Key differences
Criteria
AI Product AnalyticsHeap
AI Experience AnalyticsFullStory
Best for
AI Product Analytics
AI Experience Analytics
Score
8.6/10
8.4/10
Pricing
Free · PaidPro from $22/mo
Free · PaidPro from $22/mo
Category / audience
AI Analytics Software › AI Product Analytics
- session replay
- funnels
- autocapture
AI Analytics Software › AI Experience Analytics
- session replay
- UX analytics
- experience analytics
OVERLAP
Where Heap and FullStory are similar
Both tools cover similar catalog signals. The deciding factor is usually workflow fit, implementation needs, and ecosystem fit.
1 capabilities0 workflows
Shared capabilities
Capability overlap
Feature check
Side-by-side feature check
Feature
Heap
FullStory
Autocapture TrackingRecords clicks and views without manual tagging
-
Retroactive EventsDefine key actions after data collection
-
Funnel ReportsTrack conversion steps across user journeys
-
Retention AnalysisCompare cohorts by product behavior over time
-
AI AssistantAsk guided questions about captured behavior
-
Autocapture EventsCapture behavior without upfront tracking plans
-
11 capabilities compared.10 differentiating rows are shown first.
Use cases
Who they're built for
Heap
- Find checkout funnel drop offIdentify where users abandon key purchase steps online
- Review confusing product user journeysWatch sessions tied to unclear navigation patterns quickly
- Measure feature adoption after launchTrack users engaging with newly released features weekly
FullStory
- Investigate checkout and form frictionWatch user sessions around abandonment and errors closely
- Debug issues with replay evidenceShare exact user journeys with engineering teams quickly
- Analyze rage clicks and dead clicksPrioritize interface problems causing repeated user frustration clearly
The trade-offs
Pros & cons of each tool
Trade-offs
Heap
Pros
- Autocapture reduces engineering work for analytics questions
- Retroactive definitions help teams answer new questions
- Replay context connects numbers with real sessions
Cons
- Autocapture still needs governance to stay trustworthy
- Pricing can rise quickly with session volume
- Strict schema-first teams may prefer other tools
Trade-offs
FullStory
Pros
- Replay quality helps teams understand real behavior
- Friction signals speed up issue discovery quickly
- AI summaries reduce manual session review time
Cons
- Session volume can affect paid plan costs
- Privacy configuration requires careful upfront planning steps
- Not a replacement for full business intelligence
Final verdict
Best fit depends on your workflow
Current catalog data shows meaningful overlap between Heap and FullStory. Use the signals below to decide based on workflow, ecosystem, pricing, and implementation fit.
Shared catalog overlap
Heap and FullStory share 1 catalog signal, so the decision should focus on fit rather than broad capability alone.
Differentiators available
Heap has 4 visible decision signals and FullStory has 4.
Score signal
Heap has the higher SoftFinders Score in the current catalog data.
Choose Heap if…
- Find checkout funnel drop off
- Review confusing product user journeys
- Measure feature adoption after launch
- Autocapture Tracking
Choose FullStory if…
- Investigate checkout and form friction
- Debug issues with replay evidence
- Analyze rage clicks and dead clicks
- Autocapture Events
TRY THEM YOURSELF
See which one fits your workflow
Both tools have their strengths, the best way to decide is to spend a few minutes inside each.