E-commerce analytics reviews provide essential insights into online store performance, shopping behavior, and revenue optimization, enabling data-driven decisions that directly impact sales and profitability. Whether you're analyzing product performance, evaluating shopping behavior, optimizing checkout funnels, or measuring marketing effectiveness, this comprehensive checklist covers every aspect of conducting thorough e-commerce analytics reviews. From pre-review preparation through e-commerce data verification, revenue and transaction analysis, product performance evaluation, shopping behavior analysis, checkout funnel optimization, traffic source analysis, customer analysis, mobile performance, promotions analysis, and reporting, this guide ensures you extract maximum value from your e-commerce analytics data.
This detailed checklist walks you through pre-review e-commerce preparation, e-commerce data verification, revenue and transaction analysis, product performance analysis, shopping behavior analysis, checkout funnel analysis, traffic source and channel analysis, customer analysis, mobile e-commerce performance, promotions and marketing analysis, and reporting and optimization. Each phase builds upon the previous one, ensuring comprehensive analysis of your e-commerce performance. Follow this systematic approach to transform e-commerce data into actionable revenue optimization insights.
Effective e-commerce analytics reviews begin with proper preparation specific to online store analysis. Schedule your e-commerce analytics review meeting with relevant stakeholders. Set calendar reminders for your review date to maintain consistency.
Verify access to your e-commerce analytics platform whether it's Google Analytics with e-commerce tracking, Shopify Analytics, or another platform. Verify e-commerce tracking is properly configured and functioning. Review your previous period's e-commerce report for comparison context.
Set the date range for your review period. Identify any promotions or sales during the review period that may have affected metrics. Gather business context and sales goals to provide proper interpretation of the data. Prepare your e-commerce analytics dashboard or template. Verify product catalog and inventory data accuracy.
Accurate e-commerce data verification ensures reliable analysis and decision making. Verify your e-commerce tracking code is firing correctly on all relevant pages. Check transaction tracking accuracy by comparing analytics data to payment processor data.
Verify product data is being tracked correctly including product names, SKUs, categories, and prices. Check revenue tracking accuracy to ensure financial data matches. Verify tax and shipping tracking if applicable to your business.
Check for missing transactions or data gaps that could affect analysis. Cross-reference e-commerce data with payment processor data for accuracy. Verify enhanced e-commerce features if enabled. Check product category and brand tracking. Document any data quality issues discovered.
Revenue and transaction analysis measures the financial success of your e-commerce store. Review total revenue for the period. Compare revenue to the previous period to track growth. Compare revenue to the same period the previous year to account for seasonality.
Calculate revenue growth rate to measure progress. Review total number of transactions to understand sales volume. Calculate average order value (AOV) to understand purchase behavior.
Compare AOV to the previous period to track trends. Review revenue per visitor to measure efficiency. Analyze revenue trends over time. Review refund and return rates to understand product satisfaction.
Product performance analysis identifies which products drive revenue and which need optimization. Identify top selling products by revenue to understand what generates the most income. Identify top selling products by quantity to understand volume leaders.
Review product performance trends over time. Analyze product conversion rates to understand which products convert best. Review product page views and engagement to understand interest levels.
Identify underperforming products that may need optimization or discontinuation. Analyze product category performance to understand category trends. Review product brand performance if applicable. Analyze new product performance to measure launch success. Review product inventory turnover to optimize inventory management.
Shopping behavior analysis reveals how customers interact with your store. Review shopping cart abandonment rate to understand where customers drop off. Analyze shopping cart abandonment by step to identify specific friction points.
Review add-to-cart rate to measure product interest. Analyze product views per session to understand browsing behavior. Review internal site search usage to understand customer intent.
Analyze site search queries and results to identify product opportunities. Review product list views and clicks to understand navigation patterns. Analyze product detail view engagement to measure interest. Review promotion and coupon usage to understand discount effectiveness. Analyze wishlist or save-for-later behavior to understand purchase intent.
Checkout funnel analysis identifies where customers abandon the purchase process. Review checkout funnel conversion rates to measure overall effectiveness. Analyze checkout abandonment by step to identify specific drop-off points.
Identify highest drop-off points in checkout that need optimization. Review checkout completion rate to measure success. Analyze checkout time and duration to understand process efficiency.
Review payment method preferences to optimize options. Analyze shipping option selections to understand customer preferences. Review guest checkout vs account creation rates to optimize registration requirements. Analyze checkout error rates to identify technical issues. Review checkout optimization opportunities based on analysis.
Traffic source and channel analysis reveals which marketing efforts drive revenue. Review traffic sources driving e-commerce revenue. Analyze conversion rate by traffic source to understand effectiveness.
Review revenue by traffic channel to measure contribution. Calculate ROI by marketing channel to optimize budget allocation. Analyze customer acquisition cost by channel to measure efficiency.
Review organic search e-commerce performance. Analyze paid advertising e-commerce performance. Review email marketing e-commerce performance. Analyze social media e-commerce performance. Review direct and referral traffic e-commerce performance.
Customer analysis reveals who your customers are and how they behave. Review new vs returning customer revenue to understand customer value. Analyze customer lifetime value (CLV) to measure long-term value.
Review customer acquisition trends to track growth. Analyze customer retention rates to measure loyalty. Review repeat purchase rate to understand customer loyalty.
Analyze average orders per customer to understand purchase frequency. Review customer geographic distribution to understand market reach. Analyze customer device preferences to optimize experiences. Review customer segment performance to understand different customer groups. Analyze customer purchase frequency to identify opportunities.
Mobile e-commerce performance analysis is critical as mobile shopping continues to grow. Review mobile revenue and transactions to measure mobile performance. Compare mobile vs desktop conversion rates to identify optimization opportunities.
Analyze mobile shopping behavior to understand mobile user patterns. Review mobile checkout performance to identify friction points. Analyze mobile product page engagement to measure interest.
Review mobile site speed and performance for user experience. Identify mobile optimization opportunities based on analysis.
Promotions and marketing analysis measures the effectiveness of your marketing efforts. Review promotion and discount performance to understand impact. Analyze coupon code usage and effectiveness.
Review email campaign e-commerce performance. Analyze social media campaign e-commerce performance. Review paid advertising campaign e-commerce ROI.
Analyze seasonal campaign performance. Review affiliate marketing performance if applicable to your business.
Effective reporting transforms analysis into actionable optimization. Compile key e-commerce metrics summary highlighting most important findings. Create visualizations for revenue and conversion metrics to make data accessible.
Document key insights and findings that inform decision making. Identify optimization opportunities based on analysis. Prioritize optimization actions by potential impact.
Create comprehensive e-commerce analytics report. Include recommendations for next period based on findings. Save report in accessible location for team reference.
Throughout your e-commerce analytics review process, keep these essential practices in mind:
E-commerce analytics reviews provide essential insights for revenue optimization and business growth. By following this comprehensive checklist, preparing thoroughly, verifying data accuracy, analyzing all relevant e-commerce metrics, documenting findings effectively, and translating insights into actionable optimizations, you'll maximize the value of your e-commerce analytics data. Remember that effective e-commerce analytics reviews are not just about reporting performance but about understanding what drives sales and how to optimize every aspect of the customer journey to increase revenue.
For more analytics review resources, explore our monthly analytics review checklist, our quarterly business analytics review guide, our marketing campaign analytics review checklist, and our website performance analytics review guide.