How do you calculate conversion rate?

Conversion rate = (number of conversions ÷ number of visitors) × 100. A store that makes 100 sales from 5,000 visits has a conversion rate of 2%. The math fits on one line; what changes the result is the denominator, the period and the way you break the number down afterwards. This guide covers the formula with worked examples, the Excel calculation, segmentation, then what customer reviews change.

What is conversion rate?

Conversion rate is the share of visitors who take the action you want them to take, expressed as a percentage. The action depends on your business, not on the word "conversion". For an online store, it is the purchase. For a clinic, a garage or an agency, it is the quote request or the booking. For software, it is the trial signup. For a publisher, it is the newsletter subscription.

Most guides reduce conversion to the sale and forget the sites that sell nothing online. An osteopathy clinic that turns 6% of its visitors into appointments has a conversion rate, just like a cosmetics store. The term also works off-site: email campaign (orders ÷ delivered emails), Google Ads ad (conversions ÷ clicks), salesperson (customers signed ÷ prospects contacted).

It is also one of the three variables behind your revenue: traffic × conversion rate × average order value. At a 3% conversion rate, one extra point is worth a third more traffic, without paying for ads. For the third variable, our guide to calculating average order value follows the same method.

What is the conversion rate formula?

Conversion rate = (number of conversions ÷ number of visitors) × 100, both counted over the same period. With 100 sales from 5,000 visits in March, the result is 100 ÷ 5,000 × 100 = 2%. With March's 100 sales divided by the quarter's traffic, the result means nothing.

Three rules make the formula usable. Same period for the numerator and the denominator, no exceptions. Same data source: if your sales come from your e-commerce platform and your visits from Google Analytics, the two tools do not count the same things (time zones, cancelled orders, filtered traffic). And a conversion defined once and for all: a paid order, not an order created and then abandoned at payment.

Read the result as a percentage with one decimal. 2% and 2.4% do not tell the same story: on 5,000 visits, the gap is 20 orders.

Conversion rate, close rate, sales conversion: what is the difference?

Same formula, different denominators. "Conversion rate" is the general term: any goal, divided by the visitors, sessions or contacts who could have reached it. "Sales conversion rate" and "lead conversion rate" apply it to a pipeline: leads that became customers ÷ leads received. "Close rate" is narrower: deals won ÷ opportunities that reached the proposal stage. Because those opportunities are already qualified, it usually runs higher than the lead-to-customer rate. Before you compare your number with someone else's, check what sits in the denominator.

Physical retail follows the same logic: a store that counts 1,200 entries and 180 receipts converts at 15%. If you searched for "sales conversion rate" or "close rate", you are on the right page: the examples apply as they are, only the numerator and the denominator change.

How do you calculate conversion rate in Excel or Google Sheets?

Put your conversions in column B and your visitors in column C, one row per month. In D2, type =B2/C2, then apply the percentage format (the % button in the toolbar, or Ctrl+Shift+% in Excel). The cell shows 2.00% for 100 and 5,000. No need to multiply by 100 in the formula: the format does it.

To avoid the #DIV/0! error on a month with no traffic, use =IF(C2=0,"",B2/C2). It works the same in Excel and Google Sheets. For a cumulative rate over the year, divide the sum of conversions by the sum of visitors: =SUM(B2:B13)/SUM(C2:C13). Never the average of the twelve monthly rates, which gives the same weight to a month with 800 visits and a month with 40,000.

How do you calculate your conversion rate step by step?

Four steps are enough, and the first one is the one everybody skips: define what counts as a conversion. Then pick a period of at least one full month (a sales week gives you a rate that will not repeat), pull the numerator and the denominator, and divide.

Pull your conversions where they are accurate: the e-commerce platform for orders, the CRM for quotes and appointments, the emailing tool for signups. Pull your traffic from Google Analytics, with bots and internal traffic excluded. The figures in the table illustrate the formula, they are not market benchmarks.

Sessions or unique visitors: which denominator should you use?

The denominator can change the result by a factor of two, and neither choice is wrong. A session is one visit; a unique visitor (a "user" in Google Analytics) can make several sessions before buying. With 100 orders from 5,000 sessions made by 3,200 users, your rate is 2% per session and 3.1% per visitor.

Sessions measure how efficient the site is on each visit: the right denominator for comparing two versions of a page or two traffic sources. Unique visitors measure the share of people who eventually convert: fairer for a considered purchase, a quote or an appointment, where three visits before a decision is normal. What matters is keeping the same choice month after month. A per-session rate in January compared with a per-visitor rate in February invents a rise of about 55%.

Macro-conversions and micro-conversions

A macro-conversion is the final action that creates value: the order, the signed quote, the appointment. A micro-conversion is an intermediate step on the way there: add to cart, account creation, a visit to the pricing page, a guide download.

Micro-conversions help you locate the problem when the macro-conversion disappoints. Take the example from the table: 9% of sessions add a product to the cart, but only 2% buy. The site persuades; the checkout loses three quarters of the carts. Shipping costs revealed late, forced account creation, a missing payment method. Without micro-conversions, you would have reworked your product pages for nothing. Track two or three steps at most, the ones right before the purchase. Beyond that, the dashboard fills up and nobody reads it.

How do you segment your conversion rate so it tells you something?

An overall conversion rate is an average, and an average hides gaps that are worth more than the number itself. Four breakdowns give you most of the information, and all four exist in Google Analytics with no special setup.

By traffic source first: SEO, paid ads, email, social, direct. Visitors who come from an email or from a search on your brand name often convert several times better than those who come from a discovery ad. By device next: mobile and desktop do not buy the same way. By visitor type: new and returning, the latter having already cleared the trust barrier. If your returning visitors carry all your conversion, the topic becomes loyalty, and our guide to calculating your customer retention rate picks up from there. By landing page last: the homepage, a product page and a blog article do not have the same audience or the same job.

In Google Analytics, conversions are now called "key events". The Google Analytics help center explains how to define and break them down. Cross two dimensions at most, otherwise the segments get too small to conclude anything.

Worked example: 2% overall, 0.8% on mobile, 3.5% from email

Illustrative example, built to show the mechanics, not a customer case. A store shows a 2% conversion rate on 10,000 sessions in March, which is 200 orders. By device: 6,000 mobile sessions for 48 orders (0.8%) and 4,000 desktop sessions for 152 orders (3.8%). By source: 1,200 sessions from email for 42 orders (3.5%), 5,500 SEO sessions for 110 orders (2%), 3,300 paid ad sessions for 48 orders (1.5%).

The 2% overall looked fine. The breakdown shows two specific projects: a mobile journey that converts almost five times less than desktop, and advertising that brings in poorly qualified traffic. Email is the channel to feed. Three decisions from a single number, provided you broke it down.

How do you interpret your conversion rate?

Between 1 and 3%: that is the range for most online stores, all industries combined, and enough of a benchmark for a first read. Below 1%, look for a checkout or traffic problem; above 3%, your traffic is highly qualified or your offer very clear. A quote or appointment site often sits higher, because the action you ask for costs no money.

Before you draw conclusions, rule out the calculation errors behind most sudden swings. Bot traffic inflates the denominator: a spike in visits with no orders drops the rate while nothing changed for your customers. A period that is too short amplifies chance: 3 sales from 90 visits on a Sunday do not make a 3.3% rate. Double counting distorts the numerator: an order recorded by your platform and by an ad pixel counts twice. A tracking change (consent banner, new tag, tool migration) breaks the series: only compare months measured the same way.

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Why do customer reviews change your conversion rate?

A visitor converts when they have a reason to buy and no remaining reason not to. Customer reviews work on the second half: they remove the hesitation at the exact moment the product page or the quote page creates it. That is why they weigh more on conversion rate than on traffic.

83% of consumers have abandoned a purchase because of negative reviews, according to an Ifop study (January 2026).

The same study finds that 93% of consumers read reviews before buying. In other words, almost all of your traffic goes through this step, whether you planned for it or not. A visitor who finds no reviews on your site will look for them elsewhere, and does not always come back. Two places concentrate the effect: the search results, before the visit even starts, and the product page, at the moment of decision.

Google rating and stars in search results

The stars shown under your Google result act before the visit: they change the click-through rate, and therefore the quality of the traffic that reaches the site. A visitor who clicked a result showing 4.6 stars and 800 reviews arrives already half convinced. The same visitor on a result with no stars arrives in verification mode.

The rating itself does not read in a linear way: a 5.0 listing with 12 reviews inspires less trust than a 4.7 listing with 600 reviews. We detail that threshold in our article on the Google rating that maximizes conversions. To get the stars on your own pages, our guide on activating star rich snippets covers the markup and the conditions Google sets.

Social proof on product pages

On the product page, reviews answer the questions your description does not ask: does the size run large, does delivery arrive in two days, does support answer when things go wrong. According to the Ifop study cited above, 54% of consumers look first at the detailed content of reviews, ahead of the overall rating (42%) and the volume (33%). A three-line review that tells a real story of use converts better than a string of silent 5-star ratings.

Two practical consequences. Show reviews where the decision happens, next to the add-to-cart button, not at the bottom of the page. And reply to reviews, positive ones included: 58% of consumers prefer businesses that respond to reviews, according to the same study. The full mechanics are in our guide on social proof and customer reviews.

How do you measure the effect of reviews on your conversion rate?

Compare the conversion rate of pages with reviews against pages without, over the same period and for comparable products: same price range, same age, same traffic source. It is the simplest method, and enough for a first estimate.

The rigorous method is the A/B test: half of your visitors see the page with the review block, the other half without, for at least two full weeks and until each variant has a few hundred conversions. Below that, the gap can come from chance. Order of magnitude for a base rate around 2%: with 5,000 sessions per variant, a gap under 0.5 points is inconclusive; beyond one point, it almost always is conclusive.

Fictional simulation, not a customer case:

Read the gap in points and in relative terms: +0.5 point looks modest, +28% orders without one extra visitor does not. At 12,000 sessions per variant, the gap is conclusive.

How Review Collect increases the volume of reviews that convert

Review volume is the variable you control most directly, and the one most sites leave to chance: when the request goes out by email alone, 2 to 3% of customers respond, based on what we see among merchants who join Review Collect.

Review Collect sends the review request by SMS or WhatsApp after every order, in your brand's name, then routes each satisfied customer to the platform you chose, Google, Trustpilot, Avis Vérifiés or another, one platform at a time. On average, 40% of customers contacted by SMS or WhatsApp respond. Result for equipped merchants: 30 times more reviews in 30 days, from the first month.

Unhappy customers (1 to 3 stars) land on a feedback page in your colors. Your customer service receives an alert with the details, and the customer always keeps the choice to publish their review. Every published review gets an AI-written reply in under 60 seconds, positive and negative alike. Onboarding takes 48 hours, no developer needed. Details on the review collection page and, for displaying reviews on your pages, on the social proof and UGC solution.

To size that volume against your orders, with your own visits and your current rate:

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How much can reviews earn your brand?

Orders per year

20,000

Average order value

75 €

Realistic scenario

+44 K€

of additional gross margin per year

+62 K€ additional revenue

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Conservative assumptions (Google +17% CTR, Spiegel +270% conversion). Non-contractual estimate.

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