Analytics and Reports
Track product performance, AI search visibility, A/B test results, and conversion metrics.
Track your product performance, AI search visibility, and conversion metrics to understand the impact of your optimization efforts.
Overview
The Analytics and Reports section provides comprehensive insights into how your optimized content is performing. Track metrics across multiple dimensions to understand what's working and where you can improve.
Use these insights to refine your optimization strategy, improve content quality, and maximize your return on investment.
Dashboard metrics
Your dashboard provides an at-a-glance view of key performance indicators:
- Total Products: The total number of products in your inventory, including optimized and non-optimized items.
- Pending Reviews: Content items waiting for your review and approval before deployment.
- Data Quality Score: Overall quality rating of your product data, including completeness and accuracy.
Performance reports
Detailed performance reports show how your optimized content impacts key business metrics:
Conversion metrics
- Conversion rate improvements
- Click-through rates
- Time on page
- Bounce rate changes
Revenue impact
- Revenue per product
- Average order value
- Revenue attribution to content
- ROI calculations
Engagement metrics
- Page views
- User interactions
- Content engagement depth
- Return visitor rates
AI search analytics
Track how your products appear in AI-powered search results and voice assistants:
Search visibility
Monitor how often your products appear in AI search results for relevant queries.
- Search impression counts
- Query match rates
- Position in search results
- Visibility trends over time
Query analysis
Understand what queries lead customers to your products.
- Top performing search queries
- Query-to-product matching
- Long-tail keyword performance
- Voice search optimization
Experiments
The Experiments section A/B tests your content changes against a control group, so a result reflects what your content did rather than what the season did.
- Before and after: Traffic for every measured piece, with markers on the days enriched content went live.
- Control groups: When a run is large enough, a fifth of its products are randomly assigned to a control group and left unchanged. Comparing the test group against the control group over the same period is what separates your content changes from seasonality, promotions and everything else moving at the same time.
- Honest claims: How strongly a result is stated is decided by the evidence behind it, not by how good the number looks. A test with an intact control group can report that your content caused the change. One without a control group reports what happened and says so plainly.
- Gaps stay gaps: A day no source reported is drawn as a break in the line, never as a zero.
Experiments needs a connected traffic source. Without one, the section shows AI crawler activity and labels it as such, because crawler pull is not shopper traffic.
Quality metrics
Monitor the quality of your content and product data:
- Content Quality Scores: Track quality scores for generated content, including SEO optimization, readability, and brand alignment.
- Data Completeness: Monitor how complete your product data is, identifying missing fields that could impact optimization.
Data quality scores
Your data quality score reflects the overall health of your product data:
- Field Completeness: Percentage of required and recommended fields that are populated for your products.
- Data Accuracy: Validation of data formats, consistency, and correctness across your product catalog.
- Optimization Readiness: How well your product data is structured for AI content generation and optimization.
Exporting reports
Export your analytics data for further analysis or reporting.
Available formats
- CSV files for spreadsheet analysis
- JSON for programmatic access
- PDF reports for presentations
Report types
- Performance summaries
- Detailed metric breakdowns
- Time-series data
- Comparative analyses
Pro tips
- Review analytics regularly to identify trends and optimization opportunities.
- Keep the control group on when you launch a run. It costs nothing extra and it is the only way to know whether the content, rather than the season, moved your numbers.
- Focus on improving data quality scores to enhance AI content generation results.
- Export reports periodically to track long-term performance trends and ROI.