The problem Analytics solves
Section titled “The problem Analytics solves”You run experiments, publish content, and launch campaigns — but without measurement, you cannot tell what is working. Page views alone do not explain whether visitors are converting. Experiment results do not show downstream revenue impact. And when data lives in separate tools, correlating user behavior across touchpoints requires manual effort that slows decision-making.
Optimizely Analytics provides built-in measurement across experimentation, content, and commerce so that every team — marketing, product, and engineering — works from the same data when evaluating performance.
What Analytics measures
Section titled “What Analytics measures”Analytics collects and reports on three categories of data:
| Category | What it tracks | Example metrics |
|---|---|---|
| Web analytics | Visitor behavior on your site | Page views, sessions, bounce rate, time on page |
| Experiment analytics | A/B test and feature flag results | Conversion rate, revenue per visitor, statistical significance |
| Commerce analytics | Purchase and revenue data | Orders, average order value, revenue attribution |
Web analytics
Section titled “Web analytics”Web analytics captures how visitors navigate your site. It answers questions like “which pages get the most traffic,” “where do visitors drop off,” and “what is the conversion rate for a landing page.”
Key capabilities:
- Real-time dashboards — See active visitors, top pages, and traffic sources as they happen
- Funnel analysis — Define multi-step funnels and identify where visitors abandon
- Traffic attribution — Understand which channels (search, social, email, direct) drive visits
- Page performance — Compare page views, engagement, and conversions across pages
Experiment analytics
Section titled “Experiment analytics”Experiment analytics is tightly integrated with both Web Experimentation and Feature Experimentation. When you run an experiment, Analytics automatically tracks the metrics you define and applies statistical analysis to determine winners.
Key capabilities:
- Stats Engine results — Always-valid sequential testing with false discovery rate control
- Multi-metric tracking — Monitor primary and secondary metrics simultaneously
- Segment breakdowns — Slice experiment results by audience segment, device, geography
- Revenue attribution — Tie experiment variations directly to revenue impact
Commerce analytics
Section titled “Commerce analytics”Commerce analytics connects purchase data to visitor behavior, enabling revenue-based optimization rather than click-based optimization.
Key capabilities:
- Revenue per visitor — The metric that matters most for e-commerce experiments
- Product performance — Which products generate the most views, adds-to-cart, and purchases
- Cart analysis — Abandonment rates, average cart value, items per order
- Attribution — Which experiments, campaigns, and content drove purchases
How Analytics differs from ODP
Section titled “How Analytics differs from ODP”Analytics and ODP both involve data, but they serve different purposes:
| Dimension | Analytics | ODP |
|---|---|---|
| Primary purpose | Measure performance and results | Unify customer profiles and enable targeting |
| Data model | Aggregate metrics (page views, conversion rates) | Individual customer profiles (events, attributes, identity) |
| Time horizon | Session and campaign timeframes | Full customer lifetime |
| Identity | Anonymous sessions (cookie-based) | Resolved identities (cross-channel, cross-device) |
| Output | Reports, dashboards, experiment results | Segments, audiences, real-time profile lookups |
| Audience | Marketers analyzing results | Marketers building segments, developers integrating data |
In short: Analytics tells you what happened. ODP tells you who did it and enables you to act on that knowledge.
Analytics dashboards
Section titled “Analytics dashboards”Optimizely provides pre-built dashboards that cover common reporting needs:
| Dashboard | What it shows | Who uses it |
|---|---|---|
| Overview | Traffic, conversions, revenue at a glance | Everyone |
| Experiments | Active experiments, results, winners | Product managers, marketers |
| Pages | Top pages, engagement metrics, exit rates | Content teams |
| Audiences | Behavior by segment, device, geography | Marketing, analytics |
| Commerce | Revenue, orders, product performance | E-commerce teams |
Custom reports
Section titled “Custom reports”When the built-in dashboards do not answer your specific questions, you can create custom reports:
- Custom metrics — Define calculated metrics (e.g., revenue per session, engagement score)
- Custom dimensions — Segment data by properties you define (e.g., customer tier, content category)
- Date comparisons — Compare performance across time periods
- Filters — Narrow reports to specific pages, audiences, or campaigns
Data export
Section titled “Data export”Analytics data can be exported for use in external tools:
- CSV export — Download report data for spreadsheet analysis
- API access — Query metrics programmatically for custom dashboards
- Warehouse sync — Send Analytics data to your data warehouse for cross-system analysis
Decision guide: which analytics tool to use
Section titled “Decision guide: which analytics tool to use”| Scenario | Recommended tool | Why |
|---|---|---|
| Measure experiment winners | Optimizely Analytics | Integrated Stats Engine with always-valid results |
| Understand individual customer journeys | ODP | Profile-level data with identity resolution |
| Track general website traffic | Optimizely Analytics or Google Analytics | Either works; Optimizely Analytics has tighter experiment integration |
| Build behavioral segments for targeting | ODP | Purpose-built audience builder with real-time segments |
| Enterprise BI reporting across all systems | Third-party BI tool + data export | Use Analytics API or warehouse sync to feed Tableau, Looker, or Power BI |
| Privacy-regulated environments | Optimizely Analytics | First-party data collection without third-party cookie dependency |
| Deep funnel and attribution analysis | Optimizely Analytics + ODP | Analytics for aggregate funnels, ODP for individual-level attribution |
When third-party analytics is still needed
Section titled “When third-party analytics is still needed”Optimizely Analytics does not replace every analytics tool. You may still need:
- Google Analytics — If your organization standardizes on GA for cross-property reporting
- Adobe Analytics — For enterprise analytics with custom data models and complex attribution
- Amplitude / Mixpanel — For product analytics with deep event-level behavioral analysis
Optimizely integrates with these tools through data export and event forwarding, so you do not need to choose one exclusively.
Getting started
Section titled “Getting started”- Marketers: Analytics dashboards are available in Optimizely One. No setup is required — data collection begins when you add the Optimizely snippet to your site.
- Developers: Use the Events API to send custom events that appear in Analytics reports. See the event tracking guide for implementation details.
- Architects: Review the data export options to plan how Analytics data flows into your broader data infrastructure.
1. A product manager wants to know which A/B test variation drove more revenue per visitor, with statistically valid results. Which tool should they use?
Optimizely Analytics provides integrated Stats Engine with always-valid sequential testing and revenue per visitor metrics, purpose-built for evaluating experiment results.
Optimizely Analytics provides integrated Stats Engine with always-valid sequential testing and revenue per visitor metrics, purpose-built for evaluating experiment results.
Review this topic →2. A marketing team needs to identify which specific customers abandoned their carts last week so they can send targeted re-engagement emails. Should they use Analytics or ODP?
ODP provides individual customer profiles with resolved identities, making it the right tool when you need to know WHO did something. Analytics tells you WHAT happened in aggregate.
ODP provides individual customer profiles with resolved identities, making it the right tool when you need to know WHO did something. Analytics tells you WHAT happened in aggregate.
Review this topic →3. An enterprise organization uses Tableau for cross-system BI reporting and wants to include Optimizely experiment results. What is the recommended approach?
Analytics supports data export through API access and warehouse sync, allowing enterprise BI tools like Tableau to incorporate Optimizely data into cross-system reporting.
Analytics supports data export through API access and warehouse sync, allowing enterprise BI tools like Tableau to incorporate Optimizely data into cross-system reporting.
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