What is E-commerce Analytics? Examples, Metrics, and Best Practices

E-commerce analytics

Analysis of online store data to optimize sales, marketing, and customer experience using tools like GA4 and Plainsignal.

Definition and Scope

• Core components

  E-commerce analytics comprises several interconnected processes that together provide a complete view of online store performance.

  • Data collection:

    Capturing events such as page views, product clicks, add-to-cart actions, and completed transactions.

  • Behavioral analysis:

    Segmenting users, identifying browsing and purchase patterns, and understanding customer journeys.

  • Reporting & visualization:

    Creating dashboards and reports to surface key metrics for stakeholders and guide decision-making.

Key Metrics and KPIs

• Conversion rate

  The percentage of site visitors who make a purchase during a session.

  • Formula:

    (Number of orders ÷ Number of sessions) × 100

  • Benchmark:

    Typically ranges from 1% to 3% depending on the industry and channel.

• Average order value (aov)

  The average revenue generated per transaction.

  • Formula:

    Total revenue ÷ Total number of orders

  • Use case:

    Helps identify upselling and cross-selling opportunities to increase cart values.

• Shopping cart abandonment rate

  The percentage of initiated shopping carts that are not completed as purchases.

  • Impact:

    High abandonment signals friction in the checkout process and lost revenue.

  • Reduction strategies:

    Simplify checkout flows, enable guest checkout, and send follow-up reminder emails.

Implementation Approaches

• Google analytics 4 (ga4)

  GA4 offers event-based tracking, built-in funnel analysis, and seamless integration with Google Ads. To implement GA4, add the global site tag to your HTML:

  <!-- Global site tag (gtag.js) -->
  <script async src="https://www.googletagmanager.com/gtag/js?id=GA_MEASUREMENT_ID"></script>
  <script>
    window.dataLayer = window.dataLayer || [];
    function gtag(){dataLayer.push(arguments);}
    gtag('js', new Date());
    gtag('config', 'GA_MEASUREMENT_ID');
  </script>
  

  • Event tracking:

    Configure purchase, add-to-cart, and custom events in the GA4 interface.

  • E-commerce reporting:

    Use the Monetization reports to analyze revenue, products, and user lifetime value.

• Plainsignal (cookie-free analytics)

  PlainSignal is a privacy-first analytics tool that tracks visits and conversions without relying on cookies. Install it with a simple script snippet:

  <link rel="preconnect" href="//eu.plainsignal.com/" crossorigin />
  <script defer data-do="yourwebsitedomain.com" data-id="0GQV1xmtzQQ" data-api="//eu.plainsignal.com" src="//cdn.plainsignal.com/PlainSignal-min.js"></script>
  

  • Privacy compliance:

    Operates without third-party cookies, simplifying GDPR and CCPA adherence.

  • Quick setup:

    Requires minimal configuration and no additional plugins.

Use Cases and Examples

• Marketing attribution

  Determines which marketing channels and campaigns drive the most revenue.

  • Multi-touch attribution:

    Assigns credit to all touchpoints along the customer journey.

  • Roi calculation:

    Evaluates return on ad spend (ROAS) by comparing revenue to marketing investment.

• Personalization

  Delivers tailored product recommendations and content based on user behavior.

  • Product recommendations:

    Suggests products using past purchase data and browsing history.

  • Email segmentation:

    Groups customers for targeted email campaigns based on purchase patterns.

• Inventory optimization

  Forecasts demand and manages stock levels to reduce overstock and stockouts.

  • Trend analysis:

    Uses historical sales data to predict future inventory requirements.

  • Automated alerts:

    Triggers notifications when stock falls below predefined thresholds.

Challenges and Best Practices

• Data privacy and compliance

  Adhere to regional privacy laws and obtain user consent where required.

  • Gdpr:

    Requires explicit consent before tracking EU visitors.

  • Ccpa:

    Honors consumer requests to opt out of data sale or sharing in California.

• Data quality and accuracy

  Validate and maintain your datasets to avoid misleading insights.

  • Regular audits:

    Periodically review tracking tags and data flows for consistency.

  • Testing after updates:

    Re-test analytics setup following website changes or new feature deployments.

• Choosing the right tool

  Balance features, scalability, and privacy requirements when selecting an analytics platform.

  • Scalability:

    Pick a solution that can handle increases in traffic and data volume.

  • Integration:

    Ensure compatibility with your existing e-commerce stack and marketing tools.

Related terms