Success metrics

For revenue, your goal is to increase total sales and average order value.

Understanding the revenue metric

What it measures: Total income generated by your store during the selected time period.

How it’s calculated: Revenue is the sum of all completed orders (base price × quantity) for all products sold during the reporting period. The calculation uses data from place-order events captured on your storefront.

Formula:

Total Revenue = Sum of (Product Base Price × Quantity) for all completed orders

Data source: Storefront events (specifically place-order events)

What’s included:

• All completed orders during the selected date range.
• Base product prices multiplied by quantities purchased.
• Revenue from all sales channels tracked by Commerce Optimizer.

Important notes:

• Revenue is calculated based on base prices captured in storefront events.
• The reporting period is determined by the date range you select in the report configuration.
• Revenue metrics update as new order events are processed.

Strategies

• Implement AI-powered recommendations: Use the optimizer’s recommendation engine to surface relevant products that drive higher conversion rates. Deploy Customers who viewed this also viewed and Bought this, bought that recommendation types to increase cross-selling opportunities.

• Create merchandising rules: Boost high-margin products in search results using merchandising rules. Pin best-selling items to the top of search results for high-traffic queries.

• Optimize product discovery: Use intelligent facets to help customers find products more efficiently, leading to higher conversion rates and increased revenue.

• Leverage seasonal opportunities: Create time-based merchandising rules to promote seasonal or promotional items during peak shopping periods.

To improve your conversion rate, your goal is to convert more visitors into customers.

Understanding the conversion rate metric

What it measures: The percentage of visitors who view products and then complete a purchase, indicating how effectively your store converts browsers into buyers.

How it’s calculated: Conversion rate compares the number of unique visitors who purchased products against the number of unique visitors who viewed products.

Formula:

Conversion Rate = (Total Number of Orders ÷ Total Unique Visitors) × 100

Data source: Storefront events.

How it works:

• Product views are tracked when visitors view product pages (using product-view events).
• Purchases are tracked when orders are completed (using place-order events).
• The calculation matches users who viewed specific products with those who purchased them.

Important notes:

• A visitor who views multiple products but makes one purchase counts as one conversion.
• The metric tracks unique visitors using browser-based identifiers.
• Product view events always include a click, so views represent genuine user interest.

Strategies

• Optimize search relevance: Implement synonyms to ensure that customers find what they’re looking for, even with different search terms. Use dynamic faceting to provide relevant filtering options.

• Strategic recommendation placement: Deploy recommendation units on high-traffic pages like product detail pages and category pages. Use Most viewed and Most purchased recommendations to build trust and urgency.

• Improve product visibility: Use merchandising rules to ensure best-selling and high-converting products appear prominently in search results.

• A/B test recommendation types: Experiment with different recommendation types and placements to find what works best for your audience.

To enhance engagement, your goal is to increase customer interaction and time on site.

Understanding the engagement metric

What it measures: How actively users interact with your store, tracking meaningful actions from initial browsing through the checkout process.

How it’s calculated: Engagement tracks all interactions that indicate active participation with your store, including product browsing, shopping cart activities, and checkout actions.

Data source: Storefront events

What counts as engagement:

Engagement includes the following event categories and actions:

• Product interactions: Product views, product clicks, and product comparisons.
• Shopping cart activities: Adding items to cart, updating quantities, removing items.
• Checkout actions: Initiating checkout, completing checkout steps.
• Category browsing: Viewing category pages, filtering by facets.
• Wishlist activities: Adding to wishlist, viewing wishlist items.

Event tracking details:

The system tracks engagement when events have:

• Category: product, shopper, shopping-cart, or checkout.
• Property: Product, Checkout, Cart, Category, or Wishlist.

Important notes:

• Higher engagement typically correlates with higher conversion rates.
• Engagement metrics help identify where users are most active in their journey.
• Use engagement data to optimize high-traffic pages and improve user experience.

Strategies

• Diversify recommendation types: Avoid showing the same recommendations repeatedly. Use a mix of Recommended for you, Trending, and Recently viewed to keep content fresh and engaging.

• Implement intelligent search: Use AI-driven dynamic faceting and result re-ranking to adapt search results in real-time based on shopper behavior.

• Create personalized experiences: Deploy “Recommended for you” units on the homepage and throughout the customer journey to provide personalized product suggestions.

• Optimize search experience: Use synonyms to improve search relevance and ensure customers find what they’re looking for quickly.

To acquire more growth, your goal is to attract more new customers and improve acquisition efficiency.

Understanding the acquisition metric

What it measures: The number of new, unique visitors coming to your store, helping you understand the effectiveness of your marketing and customer acquisition efforts.

How it’s calculated: Acquisition counts unique visitors based on browser identifiers assigned during their first visit to your store.

Data source: Storefront events.

How it works:

• Each visitor’s browser receives a unique identifier (domain_userid) via a first-party cookie.
• New visitors are identified when their session index equals 1 (first visit).
• The system tracks these identifiers to distinguish new visitors from returning ones.

Important notes:

This tracking method has some known limitations:

• Cross-device users: The same person visiting from different devices (desktop, mobile, tablet) or browsers is counted as multiple unique visitors since each device and browser receives a different identifier.
• Cookie clearing: Users who clear their browser cookies are assigned a new identifier and counted as new visitors again.
• Privacy settings: Users with strict privacy settings or cookie blockers may not be tracked.

Best for:

• Tracking new visitor trends over time.
• Analyzing marketing campaign effectiveness.
• Understanding traffic growth patterns.

Interpretation tip: While not perfectly accurate due to the limitations above, acquisition metrics are reliable for identifying trends and comparing periods when most users browse on the same device and don’t frequently clear cookies.

Strategies

• Leverage search performance data: Use the search performance report to identify trending products and popular search terms. Create merchandising rules to highlight these items.

• Optimize recommendation performance: Monitor recommendation performance metrics to identify which recommendation types drive the most traffic and conversions.

• Highlight new and promotional items: Use merchandising rules to boost new products or promotional items in search results to attract attention from new visitors.

• Track traffic sources: Use event data to understand which channels bring the most valuable traffic and optimize your marketing efforts accordingly.

To reduce the bounce rate, your goal is to keep visitors engaged and reduce single-page visits.

Understanding the bounce rate metric

What it measures: The percentage of visitors who leave your site after viewing only one page, indicating potential issues with user experience, page relevance, or site engagement.

How it’s calculated: Bounce rate compares single-page sessions against total sessions to determine what percentage of visitors leave without further interaction.

Formula:

Bounce Rate = (Number of Bounced Sessions ÷ Total Sessions) × 100

Data source: Storefront events.

How it works:

• A bounced session is counted when a visitor views only one page during their entire visit.
• The system tracks page views within each session to identify single-page visits.
• Sessions are determined by user activity and time between interactions.

What causes bounces:

• Visitors landing on irrelevant pages (poor search/ad targeting).
• Slow page load times.
• Poor user experience or confusing navigation.
• Finding information quickly without needing to explore further.
• Technical issues or errors.

Important notes:

• High bounce rates aren’t always negative—some pages (like contact information or specific product specs) may naturally have high bounce rates.
• Compare bounce rates across different page types and traffic sources to identify problem areas.
• Sudden increases in bounce rate often indicate technical issues or poor campaign targeting.

What’s a good bounce rate? This varies by industry and page type, but generally:

• 40-60%: Average for ecommerce sites.
• Below 40%: Excellent engagement.
• Above 70%: May indicate problems requiring investigation.

Strategies

• Improve search relevance: Use synonyms and intelligent faceting to ensure customers find relevant products quickly. Poor search results are a major cause of high bounce rates.

• Implement recommendation units: Deploy recommendation units on category and search results pages to provide additional product options and keep visitors engaged.

• Optimize product discovery: Use merchandising rules to ensure the most relevant and popular products appear first in search results.

• Create engaging homepage experiences: Use “Recommended for you” and “Trending” recommendation types on your homepage to immediately engage visitors with relevant content.