Conversion rate: definition, calculation and how to improve it

What is a conversion rate?

Definition of conversion rate

The conversion rate represents the proportion of people who completed a defined action out of the total population exposed to, or eligible for, that action.

That action can vary widely depending on the context:

• a purchase;
• a sign-up;
• a download;
• a quote request;
• a booked meeting;
• an account creation.

Let's take a simple example.

A landing page receives 5,000 visitors.

150 people fill in the form.

The visitor-to-lead conversion rate is therefore:

150 ÷ 5,000 × 100 = 3%.

So a conversion is not necessarily a sale.

It all depends on the objective the company wants to measure.

In a B2B lead generation strategy, for example, a conversion may be the moment an anonymous visitor becomes an identified lead.

Why is conversion rate an essential KPI?

The conversion rate lets you tell volume and efficiency apart.

Let's compare two campaigns.

Campaign A

10,000 visitors.

100 conversions.

Conversion rate: 1%.

Campaign B

5,000 visitors.

150 conversions.

Conversion rate: 3%.

The first one generates twice as much traffic.

But the second one produces 50% more conversions.

Looking only at visits would therefore have led to the wrong conclusion.

The conversion rate shows whether a stage of the journey effectively turns its audience into results.

It also helps identify the main friction points.

For example:

lots of traffic + few leads → potential website conversion problem;

lots of leads + few opportunities → potential targeting or qualification problem;

lots of opportunities + few customers → potential problem further down the sales process.

In which contexts is conversion rate used?

Conversion rate can be used almost anywhere two successive stages can be compared.

In digital marketing:

visitor → sign-up

visitor → download

visitor → purchase

In lead generation:

visitor → lead

lead → MQL

In sales:

prospect → meeting

meeting → opportunity

opportunity → customer

In a sales pipeline, you can even measure conversion between each stage to pinpoint exactly where opportunities drop out.

Good to know

A "conversion rate" should always specify what goes into and what comes out of the calculation. Simply saying "our conversion rate is 5%" is hard to interpret if you don't know whether it refers to visitors becoming leads, leads becoming customers or opportunities being closed.

How do you calculate conversion rate?

The calculation itself is fairly simple. The real difficulty lies in choosing the right numerator, denominator and time period.

The conversion rate formula

The general formula is:

Conversion rate = Number of conversions ÷ Total number of eligible items × 100

For example:

Conversions: 80

Visitors: 2,000

Calculation:

80 ÷ 2,000 × 100 = 4%.

The conversion rate is therefore 4%.

The same principle can be applied to a sales team.

Example:

200 sales opportunities

50 sales

Conversion rate:

50 ÷ 200 × 100 = 25%.

Calculation example

Let's look at a complete campaign.

A company gets:

20,000 visitors

↓

1,000 leads

↓

250 sufficiently qualified prospects

↓

100 opportunities

↓

30 customers

You can then calculate several conversion rates.

These different results answer different questions.

The visitor-to-customer rate gives an overall view.

The intermediate conversion rates help you understand where the biggest losses occur.

How should you interpret the results?

A conversion rate must be interpreted in context.

A drop is not always a bad thing.

Imagine a company makes its form more demanding in order to better qualify incoming requests.

Before:

1,000 visitors → 100 leads → 10 customers

Visitor-to-lead conversion: 10%.

After:

1,000 visitors → 60 leads → 15 customers

Visitor-to-lead conversion: 6%.

The landing page conversion rate has gone down.

But the number of customers has increased by 50%.

Optimizing the form completion rate alone would therefore have led to the wrong decision.

You should always relate a conversion to the economic value of what it produces afterwards.

Good to know

A higher conversion rate is not automatically a business improvement. Making a conversion too easy can increase the number of form submissions while sharply reducing lead quality.

What are the different types of conversion rate?

The term covers several different metrics.

Website conversion rate

A website's conversion rate measures the proportion of visitors who complete an action considered important.

Depending on the company, this could be:

• a contact request;
• an account creation;
• a sign-up;
• a purchase.

A website can also track several conversions.

A B2B company might track separately:

content downloads;

newsletter sign-ups;

meeting requests.

It is better to keep these actions separate rather than lumping them into a single metric.

Landing page conversion rate

A landing page usually has a more specific goal.

For example:

visit the page → fill in the form.

The calculation is then particularly simple:

Forms submitted ÷ Landing page visitors × 100.

Benchmarks published by Unbounce based on Q4 2024 data show a median of 6.6% across all industries, from a sample of 41,000 landing pages, 464 million visitors and 57 million conversions. This figure varies widely by industry, however: the SaaS benchmark reported by Unbounce, for example, drops to 3.8%. These figures are reference points, not universal targets.

A landing page that simply asks for an email address and a page requesting a demo for a €100,000 contract obviously cannot be judged by the same standards.

E-commerce conversion rate

In e-commerce, the main conversion is usually the purchase.

The formula is often:

Number of orders ÷ Number of sessions or visitors × 100.

You can also measure intermediate conversions:

product page → add to cart;

cart → checkout;

checkout → order.

This segmentation helps pinpoint the problem.

A low add-to-cart rate may point to a problem with the offer or its presentation.

A very high drop-off at payment may point to friction in the checkout process.

Lead conversion rate

The lead conversion rate can measure several transitions.

For example:

Lead → MQL

or:

Lead → Customer.

If a company generates 500 leads and 25 become customers:

25 ÷ 500 × 100 = 5%.

It can, however, be more useful to measure each stage separately.

An MQL makes it possible to isolate a first level of marketing qualification before the lead is handed over to a more sales-driven process.

Sales conversion rate

The sales conversion rate generally measures the proportion of prospects or opportunities that become customers.

Example:

80 opportunities → 20 sales.

Rate:

25%.

It can also be calculated by:

• sales rep;
• segment;
• source;
• product.

This reveals important differences.

One channel, for example, may generate lots of opportunities but convert far less than the others.

Email campaign conversion rate

In email marketing, the conversion must be defined precisely.

It may correspond to:

• a purchase;
• a sign-up;
• a download;
• a demo request.

One possible formula is:

Recipients who completed the action ÷ Emails delivered × 100.

But some analyses focus instead on post-click conversion:

Conversions ÷ People who clicked × 100.

The two metrics answer different questions.

The first mainly assesses the overall effectiveness of the campaign.

The second mainly measures how well the final destination converts people who are already engaged.

In a cold email campaign, it is therefore useful to separate deliverability, replies, meetings and final conversion rather than summing everything up in a single rate.

What factors influence conversion rate?

A conversion rarely depends on a single element.

Traffic quality

Not all visitors are equally likely to convert.

A company can attract lots of traffic with very generic content but get few relevant leads.

Conversely, a highly specialized search query may generate fewer visits but reach prospects much closer to having a real need.

So the first question to ask when facing a low rate is not necessarily:

"How should we change the page?"

But rather:

"Are the right people landing on this page?"

Poor acquisition can't always be fixed by conversion optimization.

Offer relevance

A perfectly built landing page won't convert well if the offer doesn't match the need.

The proposition should make it quick to understand:

• what is being offered;
• who it is for;
• what problem it solves;
• why the action is worth taking.

The smaller the gap between the visitor's need and the offer, the more natural the conversion becomes.

User experience (UX)

A poor experience creates friction.

Problems can include:

• confusing navigation;
• forms that are too long;
• a poor mobile display;
• unnecessary steps;
• information that is hard to find.

A visitor can be interested in the offer and still give up simply because the process takes too much effort.

UX should therefore make the action easier without removing the information needed for an informed decision.

Calls to action (CTAs)

The CTA should clearly explain what happens next.

Compare:

"Submit"

with:

"Get the guide"

or:

"Book my demo".

The second type of wording gives more context.

The CTA should also match the visitor's level of maturity.

Immediately asking:

"Talk to a salesperson"

of someone reading a very introductory definition may be too ambitious.

An intermediate resource may be a better fit.

Trust and social proof

The more commitment the requested action involves, the more important trust becomes.

Reassurance elements can include:

• testimonials;
• case studies;
• reviews;
• client references;
• guarantees;
• explanations of how data is handled.

An unknown company asking for several pieces of personal information must give visitors enough reasons to trust it.

In B2B, a case study that closely matches the prospect's industry can be particularly effective.

Speed of the buying journey

Every additional step creates another opportunity for drop-off.

This doesn't mean every process should be reduced to a single click.

But every step must serve a purpose.

Ask yourself regularly:

"Is this information or this step really necessary right now?"

A company that asks for fifteen fields in a form but only uses four of them afterwards is probably creating unnecessary friction.

How can you improve your conversion rate?

Optimization should start by identifying the friction point rather than piling up changes.

Optimize your landing pages

A landing page must create a clear continuity between the promise that generated the click and the content displayed.

Focus in particular on:

• the headline;
• the value proposition;
• the benefits;
• the proof;
• the CTA;
• the form.

The hierarchy should help visitors understand the offer quickly.

Avoid piling several goals onto the same landing page.

A page designed to get demo requests shouldn't offer ten competing actions at the same time.

Qualify prospects better

Improving sales conversion isn't just about selling better.

It may also be necessary to improve the quality of the prospects entering the process.

Suppose:

100 opportunities → 10 customers = 10%.

After improving targeting:

70 opportunities → 14 customers = 20%.

The number of opportunities goes down.

But the number of customers goes up.

The quality of qualification can therefore have a direct impact on sales performance.

A B2B prospecting agency can, for example, work upstream on targeting and on generating conversations with companies that meet precise criteria.

Personalize your messages

A generic message tries to speak to everyone.

It often ends up speaking to no one in particular.

Personalization can be based on:

• industry;
• company size;
• job function;
• specific challenge;
• level of maturity.

For example:

"Grow your sales"

is extremely generic.

"Increase the number of meetings your SaaS sales team books"

speaks to a much more specific situation.

The faster visitors recognize themselves in the offer, the faster they can see its relevance.

Run A/B tests

A/B testing means comparing two versions of an element to see which one produces the better result.

It can cover:

• the headline;
• the CTA;
• the form;
• the key argument;
• the structure.

For example:

Version A: 8-field form

Version B: 4-field form

The test shows whether simplifying actually improves conversion.

However, you should change few enough elements at a time to be able to interpret the result.

A test in which the entire page changes at once can hardly explain why one version performs better.

Reduce friction points

Every step of the journey should be examined.

Ask yourself in particular:

• is the form too long?
• is the information requested actually necessary?
• is the CTA clear?
• does the page load quickly?
• is the mobile version easy to use?
• does the prospect know what happens after the action?

Some friction is, of course, necessary.

A B2B form may ask for a little extra information in order to filter out requests that are completely off target.

The goal is therefore not zero friction, but zero unnecessary friction.

Optimize the conversion funnel

Optimizing only the first page is rarely enough.

The entire journey needs to be analyzed.

For example:

10,000 visitors

↓ 5%

500 leads

↓ 20%

100 opportunities

↓ 30%

30 customers

Suppose the company raises the first rate from 5% to 6%.

With the following rates unchanged:

600 leads → 120 opportunities → 36 customers.

It gains 6 customers.

But if it instead improves the opportunity-to-customer conversion from 30% to 40%:

500 leads → 100 opportunities → 40 customers.

It gains 10 customers without increasing the initial volume.

This comparison shows why you need to identify the stage with the greatest economic potential for improvement.

Good to know

Optimizing conversion doesn't always mean working at the top of the journey. A small improvement close to the sale can sometimes have more impact on revenue than a big increase in form completion rate.

What is a good conversion rate?

There is no universal figure that defines a good conversion rate.

Differences between industries

Performance varies considerably depending on:

• the industry;
• the price;
• the action requested;
• the channel;
• the visitor's maturity.

The Unbounce benchmark based on Q4 2024 data shows a median of 6.6% for landing pages across all industries, but the industries covered in the study range from around 3.8% to 12.3%. For SaaS, the reported median is 3.8%, while business and professional services sit at around 6.1% in the same dataset. These gaps show why an overall average should be used with caution.

A complex SaaS demo request and a free sign-up do not represent the same level of commitment.

Differences between B2B and B2C

In B2C, some decisions can be fairly quick.

The customer sees a product, compares prices and buys immediately.

In B2B, the journey may require:

• several stakeholders;
• a demo;
• budget approval;
• negotiation.

The final conversion rate may therefore be lower at certain stages without necessarily indicating poor performance.

Deal size must also be taken into account.

Converting 1% of an audience into €50,000 contracts can create far more value than converting 10% into €20 purchases.

Your analysis should therefore combine:

conversion rate + value per conversion.

Why you should compare your own performance over time

Benchmarks are useful as a reference point.

But the most actionable comparison is often your own history.

For example:

January: 2.8%

February: 3.0%

March: 3.4%

Even if the industry benchmark is higher, the trend shows an improvement.

Also compare performance by:

• channel;
• device;
• segment;
• campaign;
• offer.

An overall average can hide significant differences.

One source at 1% and another at 8% can produce an acceptable average without immediately revealing the problem with the first one.

Which KPIs should you track alongside conversion rate?

Conversion rate should be read alongside other metrics to get the full picture.

Click-through rate (CTR)

CTR measures the proportion of people who clicked on an element out of those who were exposed to it.

It is used in particular for:

• advertising;
• email marketing;
• CTAs.

A high CTR combined with a low post-click conversion rate may indicate a lack of continuity between the promise and the landing page.

Bounce rate

In some analytics contexts, bounce rate can provide insight into engagement.

A high bounce rate should be interpreted with caution.

Someone can view a page, find exactly the answer they were looking for and leave, without the experience being a bad one.

Bounce rate should therefore be considered alongside:

• the type of page;
• time on page;
• conversions.

Customer acquisition cost (CAC)

CAC measures the cost of acquiring one customer.

Simplified formula:

Acquisition spend ÷ Number of customers acquired.

Improving the conversion rate can lower CAC at constant traffic or spend.

Example:

€10,000 in marketing spend.

Before: 20 customers.

CAC = €500.

After optimization: 25 customers.

CAC = €400.

The company gets more customers without increasing its investment.

Customer lifetime value (CLV)

Customer Lifetime Value represents the value a customer generates over the entire duration of their relationship with the company.

It puts the conversion rate back into an economic context.

A segment that converts less but produces far more profitable customers can be more attractive than a high-converting, low-value segment.

Return on investment (ROI)

ROI measures the profitability of the actions taken.

A conversion only has value if it contributes enough to results.

A campaign can generate lots of leads with an excellent form completion rate while producing very few sales.

ROI forces you to track performance further down the journey.

Closing rate

The closing rate measures the proportion of sales opportunities that become customers.

Example:

50 opportunities → 15 customers.

Closing rate:

30%.

This KPI separates the ability to build pipeline from the ability to close opportunities.

Here are the main complementary metrics:

Sales prospecting KPIs round out this analysis when the conversions relate more to the sales process.

Which tools can you use to measure conversion rate?

The right choice depends mainly on the stage you are looking at.

Web analytics tools

Analytics platforms let you track:

• visitors;
• events;
• forms;
• user journeys.

They are particularly useful for analyzing website conversions.

It is best to define each important event precisely.

For example:

form submitted;

account created;

purchase completed.

Without reliable tracking, the resulting rate can be misleading.

CRM

The CRM is better suited to measuring the sales side.

It can track:

• leads;
• meetings;
• opportunities;
• sales.

A company can then calculate:

Lead → Opportunity

or:

Opportunity → Customer.

The CRM also makes it easy to segment by:

• sales rep;
• industry;
• source.

Marketing automation platforms

Marketing automation tools let you measure:

• forms;
• campaigns;
• emails;
• lead progression.

They can also trigger certain actions when criteria are met.

Some sales automation features can then automate tasks on the sales side.

A/B testing tools

Experimentation tools let you compare several variants.

They are particularly useful for testing:

• CTAs;
• headlines;
• forms;
• page structure.

You need enough volume before drawing conclusions.

Stopping a test after just a few conversions can lead you to pick a variant purely by chance.

Reporting dashboards

When data comes from several tools, a dashboard lets you bring it together.

For example:

Traffic → Leads → Opportunities → Customers → Revenue.

A prospecting dashboard can centralize sales metrics and let you track how they evolve over time.

The goal is not to display as many metrics as possible.

A good dashboard lets you quickly understand:

where the problem lies and which action should be prioritized.

Mistakes to avoid

Several mistakes can lead to bad decisions, even when the calculation is technically correct.

Focusing only on traffic volume

Increasing traffic often seems like the obvious first fix.

But if the page converts poorly, buying more visits simply amplifies the inefficiency.

For example:

10,000 visitors × 1% = 100 conversions.

Doubling traffic:

20,000 × 1% = 200 conversions.

But raising conversion to 2% also gets you:

10,000 × 2% = 200 conversions.

In this simplified scenario, the same result is achieved without doubling traffic.

Ignoring lead quality

Making conversion easier can sharply increase the number of leads.

But if those leads rarely become customers, the improvement is only superficial.

You therefore need to track the journey all the way to the final outcome.

For example:

Landing page A: 8% conversion, but 2% of leads become customers.

Landing page B: 5% conversion, but 10% of leads become customers.

The second one can be far more profitable.

Not segmenting your analysis

An overall average can hide major differences.

Segment in particular by:

• channel;
• campaign;
• device;
• audience;
• industry.

Suppose:

Desktop: 7%

Mobile: 2%

Overall average: 4.5%.

The overall figure doesn't immediately reveal the scale of the mobile problem.

Segmentation makes it much easier to pinpoint priorities.

Neglecting optimization tests

Changing a page based on intuition alone can work, but it makes it hard to identify what actually drove the improvement.

When volume allows, use structured experiments.

Formulate a hypothesis.

Example:

"Cutting the form from 8 to 5 fields will increase conversion without lowering lead quality."

Test it.

Then analyze both:

• conversion;
• quality.

This approach prevents you from optimizing an intermediate metric in isolation.

Comparing your results with irrelevant averages

A benchmark can be very reassuring or very alarming without actually being comparable to your situation.

Unbounce itself explicitly points out that its landing page data analyzes conversion events, not the individual economic value of each conversion: a rate below the median can therefore still be very worthwhile when each conversion has a high value. For a comparison to be meaningful, compare similar situations:

• same industry;
• same type of conversion;
• same channel;
• comparable price level.

A benchmark should help you ask questions, not automatically dictate a target.

Conversion rate FAQ

What is conversion rate?

Conversion rate is the proportion of people who complete an expected action out of all the people exposed to it or eligible for it.

That action can be:

• a purchase;
• a sign-up;
• a form submission;
• a download;
• a meeting.

For example, if 100 people visit a landing page and 5 fill in the form, its conversion rate is 5%.

How do you calculate a conversion rate?

The general formula is:

Number of conversions ÷ Total number of visitors, contacts or opportunities × 100.

Example:

40 sales from 200 opportunities.

40 ÷ 200 × 100 = 20%.

Always use a denominator that genuinely corresponds to the stage just before the conversion.

What is a good conversion rate?

There is no universal rate.

The right level depends in particular on:

• the industry;
• the channel;
• the price;
• the action requested;
• the level of maturity.

As a reference point, the Unbounce benchmark using Q4 2024 data shows a median of 6.6% for landing pages across all industries, compared with 3.8% for SaaS landing pages. These figures do not mean that a page converting at 5% is bad, or that a page at 8% is automatically excellent.

The value and quality of conversions must also be analyzed.

How can you increase your conversion rate?

Start by identifying the stage where you lose the most prospects.

Then work on:

• traffic quality;
• the value proposition;
• UX;
• CTAs;
• forms;
• personalization;
• qualification;
• social proof.

Use tests when volume is sufficient.

Finally, measure the impact beyond the immediate conversion.

A successful optimization should ideally generate more useful conversions, not just more superficial actions.

What factors influence conversion rate?

The main factors are:

• audience quality;
• offer relevance;
• message clarity;
• user experience;
• level of trust;
• journey complexity;
• prospect maturity.

Poor performance can therefore stem from the website, but also from the targeting or from the offer itself.

What is the difference between "taux de conversion" and "taux de transformation"?

In French, in many marketing and sales contexts, taux de conversion and taux de transformation are used as synonyms: both translate as conversion rate.

Both measure the move from one stage to another.

For example:

leads → customers

or:

opportunities → sales.

"Taux de transformation" is especially common in sales vocabulary, while "taux de conversion" is widely used in digital marketing.

What matters is not the term you choose, but the precise definition of the calculation.

A company should always state which starting population is converted into which final outcome.

That precision is what turns conversion rate into a genuine management tool rather than just an isolated percentage.