Which UX Metrics Actually Predict Ecommerce Revenue

Your weekly analytics report looks good. Bounce rate is down. Time on page is up. Pages per session improved.

Your revenue is flat.

This is a common situation. Engagement metrics and revenue metrics are weakly correlated for most ecommerce stores. A customer who spends 8 minutes on a product page and doesn’t buy drove your time-on-page up and your conversion rate down. A customer who lands on a product page, adds to cart in 45 seconds, and checks out has not improved your engagement metrics at all.

The metrics that actually predict ecommerce revenue are different from the metrics that look good in a dashboard.

The Vanity Metric Problem

Vanity metrics are measurements that are easy to report, hard to act on, and disconnected from business outcomes.

Bounce rate is a vanity metric for ecommerce. A single-page visit that ends in a purchase (possible with short checkout flows) registers as a bounce. A 0% bounce rate achieved by adding a newsletter pop-up that forces a second pageview tells you nothing useful.

Time on page is a vanity metric. A customer struggling to find the return policy spends more time on your checkout page than a customer who immediately found what they needed.

Pages per session is a vanity metric. A customer who cannot find what they are looking for visits more pages than a customer with excellent site navigation.

Traffic is a vanity metric unless segmented. 100,000 monthly visitors converting at 0.8% generates less revenue than 40,000 visitors converting at 2.5%.

These metrics are not useless. They provide context. They should not drive decisions.

The Metrics That Actually Predict Revenue

1. Revenue Per Visitor (RPV)

Revenue per visitor = total revenue divided by total sessions.

RPV is the single most useful top-level ecommerce metric because it combines conversion rate and average order value into one number that tells you what each visitor is actually worth.

A 2% conversion rate with a €40 AOV gives you €0.80 RPV. A 1.5% conversion rate with a €70 AOV gives you €1.05 RPV. The second store has a lower conversion rate and generates more revenue per visitor.

Track RPV by:

Device (mobile RPV vs desktop RPV reveals your mobile conversion gap)
Traffic source (paid search RPV vs organic RPV vs email RPV reveals your most valuable acquisition channels)
Product category (which categories are generating disproportionate revenue per visitor?)
Landing page (which entry points convert to higher RPV?)

RPV changes tell you when something meaningful changed. A 15% drop in mobile RPV after a site update tells you something broke on mobile. Bounce rate would not tell you that reliably.

2. Add-to-Cart Rate

Add-to-cart rate = sessions with add-to-cart event divided by total sessions.

This metric sits at the boundary between your product pages and your checkout. It tells you whether your product pages are convincing customers to take the first step toward purchasing.

Industry benchmarks:

Good add-to-cart rate: 8-12% for general ecommerce
Excellent: 12-15%
Below 5%: product pages or targeting has a serious problem

Segment add-to-cart rate by:

Individual products (which products are getting viewed but not added?)
Traffic source (are paid traffic visitors adding to cart at lower rates than organic traffic?)
Device (is your mobile add-to-cart rate significantly lower than desktop?)

A low add-to-cart rate indicates a product page problem. A high add-to-cart rate with low conversion rate indicates a checkout problem. These require completely different fixes.

3. Cart-to-Order Rate

Cart-to-order rate = completed orders divided by cart creation events.

This is your checkout funnel performance metric. If customers are adding to cart but not completing purchases, this rate tells you how severe the checkout problem is.

An acceptable cart-to-order rate varies by industry and price point, but for most ecommerce stores:

Under 30%: significant checkout friction that needs immediate attention
30-50%: common, with room to improve
Over 50%: strong checkout performance

Segment by device. A 45% cart-to-order rate on desktop and 22% on mobile tells you exactly where to focus.

4. Checkout Step Completion Rates

Cart-to-order rate shows you that checkout is losing customers. Checkout step completion rates show you exactly where.

Set up funnel tracking in GA4 for:

Cart page view
Checkout initiation (first step)
Shipping information entered
Payment information entered
Order confirmation

Each step has a drop-off rate. The step with the highest drop-off is your first priority.

In Baymard’s research, the most common checkout abandonment points:

Step revealing unexpected shipping costs (most common)
Account creation requirement
Payment information step on mobile (often form field and trust issues)
Order review step (if the total does not match expectations)

Knowing your specific drop-off point focuses optimization effort. Without step-level data, checkout optimization is guesswork.

5. Product Page Scroll Depth

Product pages have a hierarchy. Above-the-fold content (product images, title, price, Add to Cart) is seen by almost everyone who lands. Below-the-fold content (specifications, reviews, FAQ) is seen by a subset.

Scroll depth tracking shows you:

What percentage of visitors see your return policy (if it’s below the fold)
Whether your reviews section is being read or ignored
Whether customers are engaging with technical specifications
Where on the page customers tend to stop reading

If 70% of visitors never scroll past the product images, everything below the fold is invisible to most of your audience. You either need to move critical trust signals above the fold, or investigate why visitors are not engaging with the full page (often a sign that the above-the-fold experience is not compelling enough to warrant continued reading).

6. Site Search Conversion Rate

Customers who use site search purchase at 2-4x the rate of customers who do not, according to multiple independent studies of ecommerce behavior. They are actively looking for something specific.

Track:

Search-to-add-to-cart rate (are search results returning relevant products?)
Searches with no results (what are customers looking for that you don’t have or can’t surface?)
Searches followed immediately by exit (customers searched, found nothing useful, left)

No-result searches are a product catalog and naming problem. High exit rates after search are a relevance problem. Both have specific fixes.

Setting Up Proper GA4 Ecommerce Tracking

GA4’s enhanced ecommerce tracking captures all of the above metrics if configured correctly. Most ecommerce stores have incomplete tracking that makes funnel analysis unreliable.

Critical events to ensure are firing correctly:

view_item on product detail pages
add_to_cart when the Add to Cart button is clicked
begin_checkout when the checkout page loads
add_payment_info when payment details are entered
purchase when the order is confirmed

If any of these events are missing or misfiring, your funnel data has gaps. Validate each event by using GA4’s DebugView while manually going through the purchase process.

WooCommerce stores: WooCommerce Google Analytics Pro is the most reliable plugin for accurate GA4 ecommerce event tracking. The free GA4 integration has known tracking gaps in the checkout flow.

Shopify stores: Shopify’s native GA4 integration covers most events. Validate that add_payment_info is firing correctly — this event is commonly missing in default setups.

The Diagnostic Framework: Using Metrics to Find Problems

Metrics tell you something is wrong. They rarely tell you why. The path from “our mobile RPV dropped 20% last month” to “here is what we need to fix” requires a diagnostic process.

The Conversion Diagnostic Framework outlines a six-step process for moving from metric signal to root cause analysis:

Quantitative analysis (the metrics above tell you where the drop-off is)
Technical audit (is something broken?)
Heuristic evaluation (does something violate basic usability principles?)
Session recordings (what are customers actually doing on the pages where you lose them?)
Customer surveys (why are customers not completing purchases?)
User testing (watch real customers attempt to complete a purchase)

The metrics tell you which pages to investigate. The diagnostic process tells you why those pages are underperforming.

A Practical Metric Audit

If you are setting up proper measurement for the first time, start here:

Confirm GA4 enhanced ecommerce events are firing correctly. Validate all five key events.
Create a weekly RPV dashboard segmented by device. Mobile RPV should be tracked separately from desktop RPV every week.
Set up the checkout funnel report in GA4. Find the step with the highest drop-off rate.
Add scroll depth tracking to your top 10 product pages. Find out what percentage of visitors see your reviews and return policy.
Review site search no-results queries monthly. Fix catalog gaps and naming mismatches.

These five measurements, maintained consistently, tell you more about your store’s performance than any engagement metric in any weekly dashboard.