Conversion rate examples: worked calculations for real store scenarios
Conversion rate = (conversions ÷ visitors) × 100. The formula is simple; applying it to real store data is where people get stuck. Here are worked examples across the scenarios stores actually run into, with the result interpreted each time.
Example 1: the textbook case
100 visitors, 4 buy.
(4 ÷ 100) × 100 = 4%
A 4% conversion rate is strong for most categories — roughly double the ~2% ecommerce average, and around top-performer level for fashion. Small samples are noisy though: at 100 visitors, one extra sale swings you from 4% to 5%, so don’t read much into a number built on so little traffic.
Example 2: a month of store traffic
14,000 sessions, 350 orders.
(350 ÷ 14,000) × 100 = 2.5%
This is the standard monthly ecommerce calculation, and the sample is large enough to trust. 2.5% sits slightly above the overall average — whether it’s good depends entirely on the vertical. See what’s a good ecommerce conversion rate by industry.
Example 3: revenue from a rate change
20,000 sessions, 2.0% conversion, £60 average order value.
- Orders: 20,000 × 0.02 = 400 → revenue 400 × £60 = £24,000
- Lift the rate to 2.5%: 20,000 × 0.025 = 500 orders → £30,000
Half a percentage point is £6,000 a month at the same traffic. This is the calculation that makes conversion work worth doing: you’re not chasing a decimal, you’re chasing the revenue behind it.
Example 4: mobile vs desktop, split out
Mobile: 9,000 sessions, 135 orders → (135 ÷ 9,000) × 100 = 1.5% Desktop: 3,000 sessions, 120 orders → (120 ÷ 3,000) × 100 = 4.0% Blended: 255 ÷ 12,000 = 2.1%
The blended 2.1% looks unremarkable and hides the real story: mobile carries three-quarters of the traffic at well under half the desktop rate. Averages conceal exactly this kind of problem — always split by device. See mobile vs desktop conversion rates.
Example 5: by traffic source
Email: 800 sessions, 48 orders → 6.0% Organic search: 6,000 sessions, 120 orders → 2.0% Paid social: 5,000 sessions, 35 orders → 0.7%
All three are “normal” for their channel. Email converts highest because the audience already knows you; cold paid social converts lowest because it interrupts strangers. Judging a paid social campaign against your email rate will make a perfectly healthy campaign look broken.
Example 6: add-to-cart vs purchase (micro conversions)
10,000 sessions, 1,200 add-to-carts, 250 orders.
- Add-to-cart rate: (1,200 ÷ 10,000) × 100 = 12%
- Cart-to-purchase: (250 ÷ 1,200) × 100 = 20.8%
- Overall: (250 ÷ 10,000) × 100 = 2.5%
Splitting the funnel tells you where the leak is. Here, plenty of people add to cart but only one in five completes — that’s a checkout problem, not a product-page problem. See checkout conversion rate.
Example 7: sessions vs users
5,000 sessions from 3,500 unique visitors, 100 orders.
- Session-based: (100 ÷ 5,000) × 100 = 2.0%
- User-based: (100 ÷ 3,500) × 100 = 2.9%
Same store, same orders, two very different numbers. Most tools and benchmarks use session-based — pick one and never mix them, or your trend line becomes meaningless.
Reading any conversion rate
Three questions turn a number into a decision:
- Is the sample big enough? Under a few hundred sessions, the number is noise.
- Compared to what? Your industry and your own history — not a generic average.
- Where’s the drop-off? The overall rate never tells you which step is leaking.
Skip the arithmetic: the free conversion rate calculator works out your rate and compares it to your industry’s average and top performers.
The bigger picture
Every example above measures how many buy — none of them say why the rest didn’t. Revyfix adds every leak (speed, checkout, CTAs, abandonment) into one score and ranks the fixes by payback. For the formula itself and its variants, see how to calculate conversion rate.