FullStory vs Looker: Analytics Comparison (2026)
Looker and FullStory both offer free tiers for their analytics platforms, but they cater to different use cases. FullStory focuses on behavioral data and session replay with a limit of 30,000 monthly sessions and core capabilities for 10 users in its free plan. Looker, on the other hand, provides a robust SQL-based modeling language (LookML) and integrates deeply with the Google Cloud ecosystem, intended for more complex data analysis and Business Intelligence scenarios.
AI Citation Scorecard
How often each is cited by major AI engines when buyers ask analytics questions. Last 90 days across ChatGPT, Perplexity, Gemini, Claude, and Copilot.
Probes run hourly; each (engine × query) combo retests every ~3 days.
Pricing
Key Features
- ✓30,000 monthly sessions
- ✓12 months of analytics retention
- ✓Session Replay
- ✓Basic analytics
- ✓Debugging tools
- ✓Core capabilities for 10 users
- ✓LookML for SQL-based modeling
- ✓Integration with Data Studio
- ✓Cloud infrastructure on Google Cloud
- ✓Prebuilt and custom integrations
When to choose FullStory
FullStory is more suitable when the primary need is to understand user behavior through session replay, basic analytics, and debugging, especially for small teams (up to 10 users) needing 12 months of data retention and a completely free plan.
When to choose Looker
Looker is more suitable when complex data modeling is required using SQL (LookML), data analysis is performed within the Google Cloud infrastructure, and integration with Data Studio is a priority. It is designed for users who need customizable reports and dashboards and are comfortable with a solution that is not a standalone free product and requires a Google Cloud account.