Conversion rate by business sector: wide disparities in 2026

5.13% across all sectors, from 1.9% for travel to 7.9% for automotive and legal (Ruler Analytics, 2026), as a qualified lead or sale conversion rate: that is the sector reading we have. It does not measure the conversion of a web session, and it sets no target.

This page is for the business leader or marketing director who wants to place their conversion rate by business sector. It gives the full reading, explains where the gaps come from and in what order to compare yourself. The shared reference points (denominator, history, profitability) are set out in the guide to a good conversion rate.

The qualified lead or sale conversion rate, by industry

Here is the reading, and first of all what it measures, because that is what decides everything else. The values are qualified lead or sale conversion rates, which count:

• a qualified lead or a sale, not a session;
• conversions attributed under multi-touch attribution, across several touchpoints;
• conversions online as well as offline.

This is not the conversion rate of a web session: a line in this reading therefore does not compare with a rate calculated on the sessions of a site. The table gives the thirteen industries and the overall value; the detail is on our digital marketing statistics.

These lines do not compare with one another: they are read one at a time. No ratio between two industries, no ranking, no conclusion drawn from the gap between two lines. Scopes, volumes and business models differ too much from one industry to another for a division to mean anything.

A precaution on the “all industries” line: it is the overall value of this reading, calculated on the companies it observes and on the quantity it measures. It is not an average conversion rate for the web, and it is set against no site average.

The legal line does not match the one First Page Sage publishes for B2B legal services, and that is not a contradiction: one counts qualified leads or sales, the other unique visitors converted into a contact request.

A sector reading remains a photograph taken under precise conditions: two readings published in the same year can give very different values for the same sector without either being wrong. Five parameters determine the figure you read, and the value moves as soon as one of them changes:

• the channel: paid, organic or all channels;
• the calculation base: sessions, users or contacts;
• the panel: the sites the publisher observes, never the web as a whole;
• the period: high season or a quiet month;
• the definition of the conversion: the heaviest parameter.

These parameters are covered in detail in the article on the average website conversion rate, suggested at the end of this page.

Hence the question to ask of any sector value, including those on this page: what is this figure the rate of? If it does not say, it is not taken up. And two readings that do not answer that question in the same way cannot be ranked against each other: you keep the one whose conditions most resemble your own.

What a sector conversion rate compares

A conversion rate divides conversions by sessions. The numerator counts conversions, meaning actions tied to revenue, such as a completed order or a qualified contact request, never items sold. Micro-conversions, such as adding to basket, are tracked separately. If the formula escapes you, it is set out in the definition of a conversion rate.

The calculation is immediate; its interpretation is not. A rate means nothing until it is set against another value, and that value has to meet three conditions:

• count the same action as yours;
• cover the same population;
• be measured under the same conditions.

This is where a sector reading comes in. A reading does not replace an impossible comparison with a perfect one: it replaces it with a debatable one, which is already a step forward. A reading that counts sales is not read like a reading that counts quote requests, and a reading built on sessions is not read like a reading built on contacts entered in a CRM. The quantity measured comes before the sector.

Correctly read, a sector reading supports several decisions:

• understanding the market and the trends of business sectors better;
• determining how profitable commercial activities are;
• assessing marketing and advertising effectiveness against the type of products sold;
• spotting opportunities quickly and deciding on better informed grounds.

These four uses have one thing in common: none of them consists of setting yourself a target by copying a line. A reading places you, it does not decide for you.

Why the gaps between sectors are so wide

A gap against your sector’s line is not an underperformance, and a gap between two sectors is not a league table. Five factors explain most of these disparities:

• the type of conversion measured: sale or lead, two actions that do not compare;
• the complexity of the buying decision: one visit for an impulse purchase, several for a structural commitment;
• the average basket: its level most often weighs on how long the deliberation lasts;
• the level of online competition: it pushes companies to work on their pages and on the qualification of their traffic;
• the digital maturity of the sector: it works in the same direction as competition.

The type of conversion is dealt with separately, because it rules out certain comparisons whatever the figures. The other four factors are read together.

Sale or lead: two rates that never compare

While in e-commerce the conversion generally comes down to the sale of a product or a service, it can be something else elsewhere: it all depends on what you expect from your visitors. This is the first source of difference between sectors, and by far the most misunderstood: two sectors that do not count the same action are not measuring the same difficulty.

The two quantities differ on every point that matters:

The exceptions are many: a sign-up that requires a full application is given less readily than a purchase costing a few euros, and a quote that commits you to seeing a salesperson is turned down more readily than a free trial. What can be stated without exception is narrower: the two rates do not count the same action, so they do not compare. The gap between them measures first a difference of definition, and only then, perhaps, a difference of performance.

The consequence is a rule, the most useful one on this page: comparing a conversion rate by business sector only makes sense if the definition of the conversion is identical. If the two definitions differ, the comparison is not made, even within a single sector. The case of companies selling to other companies is the clearest, since the sale there comes weeks after the lead: it is handled in the average B2B conversion rate.

The complexity of the decision and the maturity of the sector

The other four factors are read together, and the complexity of the buying decision comes first: a structural commitment is decided over several visits, with different people and sometimes months in between. A rate measured over a short window records the impulse purchase and misses the long commitment, with nothing in the figure to say so.

Their effect on the sector value can be summed up as follows:

The average basket is a tendency, not a rule: an expensive but repeated purchase from a habitual supplier is decided faster than a small purchase from an unknown brand. The amount is checked before drawing a conclusion from a gap; it sets no ceiling on the rate.

A sector with little online competition can show lower values simply because nobody has worked on the subject yet: seen from the inside, that is an opportunity and not a handicap.

Finally, a rate is read alongside what each conversion brings in: sitting below your sector’s line is not a problem if the cost of acquisition stays compatible with the margin per conversion, the economic reading developed in the guide to a good conversion rate cited at the start.

Who to compare yourself with, really

Placing yourself against “your sector” does not get you far. The sector, in the sense of an activity directory, is almost always too broad a category: it gathers into one line companies that share neither the same model, nor the same prices, nor the same way of counting a conversion. As for competitors, their rates are not accessible and therefore do not constitute a benchmark.

The right order of comparison starts from your own data and ends with the reading:

The sector line therefore comes last, as a background. A change of definition or tracking opens a new series, kept alongside the old one without recalculating it. The cadence for reading that series is covered in the article on conversion rate KPIs.

To choose the published line that resembles your situation, four criteria come before the sector:

• The business model: direct sale, lead generation or subscription. A site that sells, a site that collects requests and a site that signs people up are not measuring the same event and have no reason to show neighbouring levels.
• The price range: two merchants in the same sector, one selling at €30 and the other at €3,000, do not compare. It is the most discriminating criterion.
• The type of conversion counted: purchase, quote or meeting. Two otherwise identical companies will show widely different rates if one counts orders and the other counts forms.
• The share of brand traffic: a site where a large share of visitors arrive searching for its name converts better, because those visitors have already decided. That share comes from awareness, not from the page: isolate it in your segments.

It is also how the classic objection is answered in a steering committee, “we are below the sector average”. You do not contest the figure; you proceed in three steps:

• say what the figure counts: a qualified lead or a sale, under multi-touch attribution;
• say who it covers: the panel the publisher observes, not the web as a whole;
• present your history and your segments, measured with a constant definition.

The discussion then turns to your progress, and not to a line that does not describe your company.

What generative answers do to sector gaps

Generative AI amplifies these disparities: sectors with a strong informational component, such as health, finance, tech or legal, are covered more by AI Overviews, which changes the structure of incoming traffic before it even reaches the site. A sector reading published today therefore no longer describes quite the same landscape as one published two years ago.

The share of traffic referred by generative engines, which has neither the volume nor the maturity of classic organic traffic, is worth tracking separately; its published benchmark appears in the table of the guide to a good conversion rate.

A confusion often creeps in here, and it is better named: a web conversion rate does not measure exposure. It relates conversions to sessions, and the people who read your brand in a generative answer without coming to the site appear in neither of its two terms. An answer without a click reduces the number of sessions and therefore moves the rate, without making it a measure of awareness.

What becomes of exposure is tracked with other indicators, counted separately and never added to the rate:

• citations of your brand in generated answers;
• the queries covered by those answers;
• the visibility of your brand in AI answers.

That is one more reason to hold your own history as the main reference.

Continue reading

Depending on what this reading has told you, here is the article to read next:

• You cannot find your sector: a general average, with its benchmarks by channel, is read before going down into a cut, in the article on the average website conversion rate.
• You sell online: your unit is the order and the sector split no longer explains your gap, as shown in the e-commerce website conversion rate.
• You only have an overall rate: break it down by channel, entry page, device and campaign before placing yourself, with the conversion rate KPIs.
• Your own figure is not reliable yet: produce it cleanly before comparing it with anything, by configuring Google Analytics.
• You have placed yourself and want to act: which page to start with, how to prioritise and how to measure the effect belong to optimising the conversion rate.

To calculate your rate by channel and by page type and track your own series instead of borrowing a line from a reading, the performance reporting module brings these cuts together in a single dashboard.

Frequently asked questions (FAQ)

What is a good conversion rate in my sector?

Between 1.9% and 7.9% depending on the sector, with 5.13% across all sectors (Ruler Analytics, 2026), as a qualified lead or sale conversion rate. Your sector’s line places you without setting a target. Your rate is good if it keeps the cost of acquisition compatible with your margin per conversion and if it progresses against your history with a constant definition.

What are the conversion rates by business sector?

Conversion rates by sector run from 1.9% for travel to 7.9% for automotive and legal (Ruler Analytics, 2026). They count a qualified lead or a sale, under multi-touch attribution, online and offline, and not the conversion of a web session. The thirteen industries in the reading and its overall value appear in the table at the top of the page.

Why does the conversion rate vary so much between sectors?

Five factors explain the gaps: the type of conversion measured, the complexity of the buying decision, the average basket, the level of online competition and the digital maturity of the sector. The type of conversion weighs most, because a sale and a lead do not count the same action. The other four lengthen the decision or change the quality of pages and traffic.

How do you compare yourself with your sector’s benchmarks?

Compare yourself first with your own history, over at least 12 months with a constant definition, then with your segments: channel, device, page type. The sector reading comes last, as an order of magnitude, and only if it counts the same action as you do. Finally, take your price range and your business model into account.

What conversion rate should you aim for in your business sector?

Aim at progress on your own series, not at a line in a reading. Measure it with a stable conversion definition, prioritising pages with high traffic and high intent: offer pages, comparisons, pricing. A rate target only makes sense alongside a value target, because lowering a price raises the rate while reducing what each conversion brings in.

Do conversion rates by sector include traffic from AI (GEO)?

Not always. Answers generated without a click reduce the volume of sessions, and the share of traffic referred by AI changes the composition of a sector’s traffic. To read a conversion rate by business sector correctly, track post-click traffic (sessions) and GEO signals, such as citations, AI visibility and queries covered, separately.

What is the difference between an e-commerce conversion rate and a lead conversion rate (B2B)?

An e-commerce rate generally counts purchases, a B2B rate counts leads: form, meeting booked, demo request. The first depends heavily on price, catalogue and the buying experience; the second is also judged on lead quality (MQL/SQL) and cost of acquisition. The two never compare, even within a single sector.