What a conversion rate tells you
A conversion is whatever action you want people to take: a purchase in an ecommerce store, a sign-up on a landing page, a call booked, a form sent, an app installed. The conversion rate is the share of your traffic that took that action. It answers a simple question: out of everyone who showed up, how many did what you hoped they would?
Because it is a share, it lets you compare things of different size. A page with 4,000 visitors and one with 40,000 can be compared fairly, and so can last month and this month, mobile and desktop, or one ad and another.
Conversion rate formulas
An online store with 12,500 sessions and 300 orders in a month converts at 300 ÷ 12,500 × 100 = 2.40%, about one order for every 42 sessions. At an average order value of $65 those orders bring in $19,500, which is $1.56 of revenue per session.
The same numbers work backward. To reach 3% with the same traffic, the store needs 12,500 × 3 ÷ 100 = 375 orders, 75 more than today. And for a goal of 500 orders a month at 2.40%, it needs 500 ÷ 2.4 × 100 = 20,833.3 sessions, so about 20,834. The calculator rounds up, because you cannot get a fraction of a conversion or a visitor.
Visitors, sessions, clicks or leads
The number you divide by changes the answer, so pick it on purpose and keep it the same when you compare.
- Visitors or users count people. The rate tells you what share of people converted at least once. Google Analytics 4 calls this the user key event rate.
- Sessions count visits. Someone who visits three times before buying adds three sessions and one conversion, so a per-session rate is usually lower. In GA4 this is the session key event rate: the number of sessions with a key event divided by all sessions.
- Clicks are the usual base for ads. Google Ads defines conversion rate as conversions per ad interaction, so 50 conversions from 1,000 interactions is 5%.
- Leads are the base further down a sales funnel: the share of leads that became paying customers.
A note on names: Google Analytics now calls the actions that matter to your business key events. In Google’s wording, a conversion is a key event you use to measure ad campaigns in Google Ads, which is why GA4 reports show key event rates where older reports showed conversion rates.
Conversion rate examples
Made-up examples to show the math, not benchmarks for any industry.
| Scenario | Traffic | Conversions | Rate | One in |
|---|---|---|---|---|
| Ecommerce store, orders per session | 12,500 | 300 | 2.40% | 41.7 |
| Landing page, newsletter sign-ups per visitor | 4,000 | 360 | 9.00% | 11.1 |
| Search ads, purchases per click | 2,500 | 75 | 3.00% | 33.3 |
| Free trial, trials that became paying customers | 650 | 117 | 18.00% | 5.6 |
| B2B sales, leads that became customers | 240 | 30 | 12.50% | 8 |
We leave out average conversion rates by industry on purpose. Published averages mix sites that count sessions with sites that count people, purchases with free sign-ups, and paid traffic with returning customers. Your own history is the comparison that means something.
Comparing two periods or variants
Choose Compare two to put two numbers side by side: this month and last month, the old landing page and the new one, or variant A and B of a test. The calculator shows both rates, the change in percentage points and the relative change. Say A converts 12,500 visitors into 300 sales (2.40%) and B converts 11,800 into 342 (2.90%). That is 0.50 percentage points more, or a relative lift of 20.8%. At B’s rate, A’s traffic would have brought about 62 more sales.
A difference between two numbers is not proof that one version is better. With small numbers, chance alone moves rates a lot, and a busy week or a sale can lift a period without any change on the page. Before you declare a winner, run the numbers through the A/B test significance calculator; the Compare two result links straight to it with your numbers filled in.
Why small changes in the rate matter
A higher conversion rate works like extra traffic you do not pay for. Lifting the store above from 2.40% to 3% brings 75 more orders, $4,875 a month at the same traffic, exactly what 25% more sessions would bring at the old rate. The What if table under the result shows this for your numbers.
That is why revenue per visitor is worth watching next to the rate. It moves when either the conversion rate or the order value moves, so it catches a discount that raises the rate but lowers what each order earns. To see whether the ads that bring the traffic pay off, use the ROAS calculator; to see what each new customer costs, the CAC calculator.
Common mistakes
- Different date ranges or sources. Take traffic and conversions from the same tool and the same period. Orders from your shop system and sessions from analytics rarely match exactly.
- Counting conversions twice. A thank-you page reloaded or a tag that fires twice inflates the rate. If the rate jumps overnight, check the tracking before you celebrate.
- Bots and internal traffic. Spam visits and your own team’s visits pull the rate down. Filter them out where your analytics tool allows it.
- One average for everything. Mobile and desktop, new and returning visitors, and each traffic source usually convert very differently. A shift in the mix changes the overall rate even when no page changed.
- Judging too early. A few days of data or a few dozen conversions can swing a lot. Compare full weeks, and enough of them.
How to use the conversion rate calculator
- 1Choose what to calculate: your conversion rate, the conversions needed for a target rate, the traffic needed for a conversion goal, or a comparison of two periods or variants.
- 2Pick how you count traffic (visitors, sessions, clicks or leads) and enter your numbers for one date range.
- 3Add revenue per conversion, such as your average order value, to see revenue and revenue per visitor.
- 4Read the result and the stats, check the What if table, then copy the result or a link to share it.
Frequently asked questions
How do you calculate conversion rate?
Divide the number of conversions by the number of visitors, sessions, clicks or leads in the same period and multiply by 100. A store with 300 orders from 12,500 sessions has a conversion rate of 300 ÷ 12,500 × 100 = 2.4%. Use the same date range and the same source for both numbers.
What is a good conversion rate?
There is no single good number. It depends on what counts as a conversion (a purchase or a free sign-up), on price, on where the traffic comes from and on how you count visitors. Published averages mix all of that, so they make a weak yardstick. Compare with your own past periods, pages and channels, and judge the rate by what each conversion is worth to you.
What is the difference between percent and percentage points?
Percentage points are the plain difference between two rates. Going from 2.4% to 3% is a rise of 0.6 percentage points. Percent describes the relative change: 0.6 is 25% of 2.4, so the rate rose by 25%. Both are correct, but say which one you mean, because "up 25%" and "up 0.6 points" sound very different.
Should I divide by visitors or by sessions?
Either works if you stay consistent. Per visitor (user) answers what share of people converted; per session answers what share of visits ended in a conversion, which gives a lower rate when people come back several times before buying. Google Analytics 4 reports both, as user key event rate and session key event rate.
Can a conversion rate be higher than 100%?
Yes, when one visitor or click can count more than once. Google Ads, for example, notes that conversion rate can go over 100% when you count every conversion or track several conversion actions. For a classic conversion rate, count each visitor or session that converted once.
How many visitors do I need to get a certain number of sales?
Divide your sales goal by your conversion rate as a decimal. At a 2.4% conversion rate, 500 orders take 500 ÷ 0.024 = 20,833.3, so about 20,834 visitors. Choose Traffic needed in the calculator to work it out for your own numbers.
Is a higher conversion rate always better?
Not always. A big discount or a free offer can raise the rate while each conversion earns less, and cheaper traffic from a broad audience can lower the rate while profit goes up. Add your revenue per conversion and watch revenue per visitor too, it combines both effects in one number.