Audyense·
Side-by-side record

FullStory vs. Mode

Built from each tool’s researched, reviewed record. Figures are checked against public pricing pages at research time — always confirm current pricing with the vendor before buying.

The short version

Mode starts at Free per seat, versus FullStory at Custom pricing. Mode carries the higher aggregate rating (4.5/5 vs 4.4/5).

Full comparison

FullStoryfrom Custom pricing
Modefrom Free
Audyense Score51AS*Low56AS*Fair
PositioningDigital experience analytics and session replayAnalyst-first BI combining SQL, Python, R, dashboards, and advanced analytics.
Free tierYesYes
DeploymentCloud / SaaSCloud / SaaS
Best fitSMB, Mid-market, EnterpriseSMB, Mid-market, Enterprise
Pricing plans
  • FreeFree
  • BusinessCustom pricing
  • AdvancedCustom pricing
  • EnterpriseCustom pricing
  • StudioFree
  • BusinessCustom pricing
  • EnterpriseCustom pricing
Session replayYes
HeatmapsYes
SAML SSOYes
AES-256 encryptionYes
Python and R notebooksYes
Interactive dashboardsYes
Reusable datasetsYes
Governed metricsYesSupports dbt Semantic Layer integration.
Custom data appsYes
Advanced analyticsYes
Role-based access controlYesEnterprise feature.
SQL editorYes
Integrations verified
Aggregate rating4.4 · 1.0k reviews4.5 · 330 reviews
Integrations
SnowflakeAmazon RedshiftGoogle BigQueryPostgreSQLMySQLMicrosoft SQL Server+6 more
Security & compliance
Pros
  • Unified setup
  • Comprehensive replay
  • Deep analytics
  • Native SQL, Python, and R workflow with results flowing into dashboards and reports.
  • Strong bridge between ad hoc analysis, advanced analytics, and self-serve reporting.
  • Reusable datasets and governed metrics reduce repeated analyst work.
  • Custom data apps and embedded analytics expand the use case beyond static dashboards.
Cons
  • Pricing based on sessions
  • Learning curve
  • The platform is optimized for analyst-led teams rather than pure business-user self-service.
  • Enterprise identity, access, and support capabilities are not part of the free Studio tier.
  • Pricing and packaging are less transparent for Business and Enterprise.
  • Python/R environments and warehouse performance still require data-team administration.
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