GAPro
Collects pageview/custom events with privacy-first tracking model
Evidence source: Collect API and tracker SDK
Web Analytics
Use privacy-first analytics for product and growth decisions with operational guardrails around heavy reads and reporting.
What this solves
Combines core event collection and advanced insight surfaces in one system so teams can act without data silos.
Who is this for
- •Product managers tracking activation and retention
- •Growth teams evaluating acquisition and conversion
- •Engineering leaders controlling analytics read performance
Prerequisites
- •Tracking plan and key events defined
- •Goal and conversion model configured
- •Stakeholder reporting cadence agreed
Step-by-step
1. Deploy tracker and validate ingestion
Confirm event ingestion quality before broad traffic analysis and KPI reporting.
2. Configure goals and conversion mapping
Define activation and revenue-aligned goals for decision-grade reporting.
3. Analyze advanced insights
Use funnel, journey, retention and attribution surfaces to identify high-leverage improvements.
4. Share and operationalize results
Publish summaries and public-share artifacts for aligned product, growth and leadership decisions.
Operational outputs
- •Stats and segment trends by source, device and geography
- •Goal and conversion insights for activation loops
- •Journey, retention and attribution reports for decision reviews
Plan availability
- •Core analytics and goals are available from Pro tier
- •Advanced insights and operational surfaces are enterprise-weighted
- •Historical depth and heavy-query controls follow plan limits
Related capabilities
GAEnterprise
Advanced insights: funnels, journey, retention, revenue and attribution
Evidence source: WA insights endpoints and services
GAPro
Goal and conversion tracking for activation and revenue events
Evidence source: WA goals endpoint guarded by plan_limit_service.check_wa_goals_enabled
GAEnterprise
Operational WA surfaces: sessions, guardrails, cache and public share
Evidence source: WA sessions/public share/perf controls
Limits and guardrails
- •Control heavy read patterns with cache and rollout guardrails
- •Define event schema ownership to avoid reporting drift
- •Treat minute-level freshness as eventual consistency, not instant streaming
Expected outcome
- •Teams make faster growth and product decisions from one source
- •Conversion diagnostics become repeatable and shareable
- •Analytics operations remain stable under enterprise read load
Troubleshooting paths
- •If event gaps appear, validate tracker deployment and ingestion filters
- •If dashboards lag, review cache windows and heavy-query policy
- •If attribution looks inconsistent, verify campaign and source normalization
Certainty scorecard
web-analyticsSample size: 0Organizations: 0insufficient_data
Not enough evidence yet to show a reliable certainty score.
Proof
Web Analytics: Example WA insight payload
{
"endpoint": "/api/wa/insights/journey",
"totalVisitors": 248,
"steps": 5,
"top_path": "/pricing -> signup_click",
"cache_ttl_seconds": 60
}Escalation
Need analytics implementation support?
For enterprise rollouts, request onboarding help for schema design, dashboard governance and read-path performance.