Store Revenue Leak Calculator

Revenue per session is the number that nets everything out

Conversion rate and average order value move against each other often enough that reading either alone is misleading — a discount lifts conversion and drops AOV, a bundle does the reverse. Revenue per session is conversion rate × AOV, and it is the single figure that tells you whether a change actually made the store more money.

Session, not visitor. Shopify counts conversion per session, so this figure is per session too — one person browsing on Monday and buying on Thursday is two sessions and one visitor. Treating the two as interchangeable overstates what each individual is worth by however often your customers come back.

At 1.4% and $85, every session is worth $1.19. At 2.0% it is worth $1.70. That is the whole business case for conversion work stated in one line, and it is also what makes traffic spend decisions legible: if a session is worth $1.19, you know what you can afford to pay for one.

Read the lift relatively, not in percentage points

Going from 1.4% to 2.0% is not 'a 0.6% improvement'. It is a 43% relative lift, and that framing matters because it is the one that tells you how hard the work is. Relative lifts above 30% usually come from fixing something structurally broken rather than from testing button colours.

The tool flags a target above double your current rate as aggressive. It is not impossible — a store with a genuinely broken checkout can double — but a plan built on it should say which specific broken thing is being fixed.

What the benchmark tiers mean

Littledata's current Shopify set — 427 stores over the 90 days to 10 October 2026 — puts the median store at 1.4%, the top 20% at 2.6% and the top 10% at 3.6%. Mobile converts at roughly 1.2% against desktop's 1.9%, which is why a mobile-heavy store sitting at 1.4% is doing better than the headline suggests, and a desktop-heavy one is doing worse.

Those tiers move between cohorts, and the gap between the median and the top 20% is narrower here than in the sets published a year earlier. That is a reason to read your tier as a rough position rather than a grade, and a reason this page names the exact dataset it is quoting.

Benchmarks are orientation, not targets. A $400 AOV considered-purchase store converting at 1.1% can be far healthier than a $20 impulse store at 3%. Use the tier to know whether there is obvious headroom, then use funnel mode to find out where it is.

Funnel mode isolates one stage at a time

Each stage is raised to its benchmark while the other two are held exactly where they are, and the revenue is recomputed. That isolation is what makes the comparison fair — it tells you what fixing *that* stage alone is worth, rather than compounding three improvements into one flattering headline.

It also means the three gains do not add up to the gain from fixing everything, and they are not meant to. The number to act on is the largest one: it names the page type to work on first.

What each stage actually points at

A low add-to-cart rate is a product page problem: imagery that does not substitute for handling the product, missing information, unclear variants, a price that arrives without context. For fragrance specifically it is usually that the page has not made a scent legible to someone who cannot smell it.

A low cart-to-checkout rate is usually about cost surprise — shipping, duties and taxes appearing later than expected. A low checkout completion rate is the checkout itself: forced account creation, too many fields, missing payment methods. Baymard puts average cart abandonment at 70.22% across 50 studies, and finds the average large site could lift conversion by 35.26% through better checkout design alone.