Google Ads benchmarks for B2B: CPC, conversion rate and cost per lead by industry

Business-to-business Google Ads benchmarks from a sample of 56 advertisers, all business-to-business, in 2025 put the cost per click (CPC) at $9.76, the click-through rate (CTR) at 6.33% and the click-to-lead rate at 1.9%, according to Metadata. Cost per lead was $524 spend-weighted and $920 for the middle advertiser. The often quoted $5.42 all-industry search CPC comes from mostly local and consumer campaigns and counts platform conversions.

What are the Google Ads benchmarks for B2B?

For B2B, the short answer comes from a B2B-only sample. Across 56 B2B advertisers on Google Ads in 2025, Metadata reports a CTR of 6.33%, a CPC of $9.76 and a click-to-lead rate of 1.9%. Cost per lead was $524 spend-weighted and $920 for the advertiser in the middle of the 34 with lead-generation leads.

Two definitions matter before you compare anything. In that dataset, a lead is a customer relationship management (CRM) record created from a Google Ads click, not a platform conversion. Brand and non-brand search are not split, so both are in the figures.

The other figures you will see quoted measure different populations:

The WordStream set behind it comes from 13,474 mostly local and consumer campaigns and counts every platform conversion. The two SaaS CPC figures are non-brand only, so they price a different auction from a blended account.

Turning a CPC into a cost per lead

The business-to-business figures connect through one formula. Cost per lead is click price divided by click-to-lead rate, and you can carry it one step further to the opportunity.

Cost per lead        = CPC / click-to-lead rate
Cost per opportunity = Cost per lead / lead-to-opportunity rate

Here is an example with round inputs, not a benchmark. For example, at an $8 click and a 0.04 click-to-lead rate, cost per lead is $200. In this example, at that $200 cost per lead and a 0.2 lead-to-opportunity rate, cost per opportunity is $1,000.

We think the practical use is this: pick the benchmark whose lead definition matches yours, then check your own click-to-lead rate against it before judging the click price. A cheap CPC with a loose lead definition will not survive the CRM. Cost per lead by channel is on our business-to-business cost per lead benchmarks page, and account structure is in the Google Ads playbook for business-to-business SaaS.

B2B and software search benchmarks side by side, with sample, year and definition

The business-to-business search figures that circulate come from samples that differ in size, buyer type and lead definition. Read the sample and the definition before the dollar figure.

In our reading, three columns carry most of the gap. The lead definition is the first: a platform conversion counts calls and forms, while a CRM record counts only what reached the sales system. Brand mix is the second: PipeRocket's non-brand cost per lead is more than double its blended one. Sample is the third, because one agency's book or a set of local campaigns is a different population from a business-to-business pipeline.

The closest LocaliQ row to business-to-business is Business Services, at a $5.87 CPC and a $93.69 cost per lead. Its conversion rate is determined by the number of leads you get divided by clicks, so it is a platform rate, not a CRM rate.

Metadata also reports what happens past the lead: 3.95x in CRM opportunity value per lead-generation dollar. That is sourced pipeline, not revenue.

Carry the comparison one stage further

In our reading, cost per SQL is the row that travels best between these sets, because it filters out low-intent form fills that platform conversions count. GrowthSpree's typical range is $800-$2,500.

Example inputs, not a benchmark:

cost per lead = CPC / click-to-lead rate
cost per SQL  = cost per lead / lead-to-SQL rate

For example, at a CPC of $8 and a click-to-lead rate of 0.04, cost per lead is $200. In this example, at that $200 and a lead-to-SQL rate of 0.2, cost per SQL is $1,000. That is why, in our view, a team should report both lines before calling search expensive.

Why published Google Ads benchmarks disagree

Two reports can both be accurate and still give a business-to-business advertiser click-through rates that differ by more than a full point. In our reading, three causes account for most of the gap: who is in the sample, which year the data covers, and how the metric is defined and summarized.

One disagreement, side by side

In our reading, that gap reflects the three causes below. It does not show that Technology ads improved between 2018 and 2023.

Sample mix

The WordStream data drew on a sample of 14,197 United States-based accounts in all verticals, and it reported a single B2B row: a search CTR of 2.41%. Databox has no B2B row. It splits that territory into several industries, including SaaS at 3.68% and Technology at 3.76% and Information Technology & Services at 3.59%. A B2B software company could match itself to any of these rows and get a different target from each.

Data year

The WordStream figures describe 2018. That year, the industries with the lowest average click-through rates were Consumer Services, Technology and B2B. The Databox figures describe one month, with a cross-industry median CTR for May 2023 of 3.94%. Over five years, auction pressure, ad formats and the advertiser mix in each industry all changed.

Definition of the metric

WordStream reported averages and separated the networks. Its cross-industry average CTR was 3.17% for search and 0.46% for display. Databox reported medians. A few accounts with very high click-through rates raise an average but barely move a median. A figure that blends search and display traffic will also come out lower than a search-only figure.

Checklist before you quote a benchmark

1. Sample: number of accounts, country, and the exact industry label used
2. Year: the period the data covers, not the publish date
3. Statistic: mean or median
4. Network: search only, display only, or blended
5. Metric definition: what counts as a click, a conversion, a lead
6. Match: does your account fit the same label, network and period

If any line stays blank, treat the figure as context for your own account, not as a target. For how the definition of a conversion changes what you count as a result, see our attribution models method.

What is the average CPC for B2B Google Ads, and why is it higher?

We think B2B search clicks cost more because the auction is set by what a buyer is worth, not by what a click is worth. The spread inside software alone is wide. GrowthSpree's 2026 vertical data, as republished by Aimers, puts cybersecurity near $18 and DevTools at less than half of that.

Prices are also moving. Involve Digital, cited in the same Aimers guide, reported that CPC is up 29% year over year for non-branded B2B SaaS.

Search clicks are not unusually expensive inside B2B media budgets. Metadata's 2025 B2B dataset found that Google clicks cost $9.76 against $9.39 on LinkedIn. In our reading, the higher number reflects B2B as a category, not search as a channel.

What drives the price

Two sets of drivers show up. The first is commercial: Aimers says the right benchmark depends on your vertical, ACV, sales cycle, geography, brand demand, and how cleanly your CRM data feeds back into Google Ads. ACV is annual contract value. The second is the auction itself: Google's own help page lists your bid, budget, ad quality, location targeting, product, abuse trends, and customer behavior in your industry as factors.

Read your CPC against your own vertical row before you call it high. Aimers makes the point directly: in project management software, an $18 click may indicate weak Quality Score, overbroad targeting, or an overly competitive keyword set. In cybersecurity, the same price sits at the vertical average.

We think Brand demand matters because branded queries price below category queries. The more buyers already search your name, the lower your blended CPC looks. That makes demand creation versus demand capture a budget question as well as a strategy one.

Check whether a CPC is affordable

A CPC only means something once it is carried through to a qualified opportunity. Here is an example with round inputs, not a benchmark:

Cost per lead = CPC / click-to-lead rate
Cost per SQL  = Cost per lead / lead-to-SQL rate

CPC $8, click-to-lead 0.04  -> cost per lead $200
Cost per lead $200, lead-to-SQL 0.2 -> cost per SQL $1,000

For example, at a CPC of $8 and a click-to-lead rate of 0.04, a lead costs $200. In this example, at $200 a lead and a lead-to-SQL rate of 0.2, an SQL costs $1,000. Compare that figure with the SQL value your ACV and close rate support. That comparison decides whether the click price is too high.

What conversion rate should B2B search ads get, and why it is not pipeline

The conversion rate in the Google Ads interface counts whatever you configured as a conversion action: a form fill, a call, a demo request. That number is not a lead in your CRM, and a lead is not pipeline. Report the three separately.

In Metadata's 2025 B2B dataset, the click-to-lead rate was 1.9%, measured as CRM leads over clicks. A lead there is a CRM record created from a Google Ads click, not a platform conversion. The same source sets that against WordStream's 8.18%, which counts platform conversions. In our reading, most of that gap comes from the definition, not from campaign quality.

Pipeline is one step further down. Sourced pipeline is every opportunity the CRM credits to an ad-generated lead, open, won or lost, and it is not revenue. The pipeline-per-dollar figure cited earlier on this page depends on that CRM link existing. Across the dataset, 42 of 132 advertisers running lead-generation spend had no CRM opportunity signal.

A worked example

These are example inputs, not benchmarks. In this example, at $200 per lead and 0.2 of leads becoming opportunities, cost per opportunity is $1,000.

cost per lead        = CPC / click-to-lead rate
cost per opportunity = cost per lead / lead-to-opportunity rate

Getting the sales stage back into Google Ads

Offline conversion import is the mechanism. Google Ads assigns a Google Click ID (GCLID) for every click that comes to your website from an ad. When the lead later converts offline, you give that GCLID back to Google Ads along with a few details about the type of conversion it was and when it happened.

1. Turn on auto-tagging, capture the GCLID on every landing page and store it on the lead record. The GCLID is case sensitive.
2. Create an offline conversion action for the stage you care about, such as a sales qualified lead or an opportunity. Set primary or secondary deliberately: Google warns that misconfiguring these settings can prevent Smart Bidding from optimizing effectively.
3. Connect the CRM. For Salesforce and HubSpot, Data Manager imports the last 14 days of data in the first successful run.
4. After creating the action, wait 4-6 hours before uploading conversions for that conversion action.

Enhanced conversions for leads adds hashed first-party data such as email. Google reports advertisers using it saw a median 10% increase in conversions compared to those using standard offline conversion imports. Uploads moved to the Data Manager API starting June 15, 2026. For stage-to-stage rates beyond the lead, see our funnel conversion benchmarks.

How to compare your account with the benchmark

A benchmark is only useful once your number and the published number describe the same thing. We run the comparison in five steps and write each one down as a single row, so the gap can be checked later by someone who did not build it.

Step 1: Match the segment, the year and the definition

Write down three things about the benchmark before you look at your own data: who is in the sample, which period it covers, and what counts as a conversion. Databox, for example, reported that the median Google Ads conversion rate for May 2023 was 3.42% across all industries. That is one month, all industries, and the platform's own conversion definition. If your conversion is a qualified form fill in a single B2B segment, record the mismatch rather than reading the gap as performance.

Step 2: Use medians, not averages

Consultus Digital advises using industry medians for CTR, CPC, CPA and conversion rate (CPA is cost per acquisition). Compute your own figure the same way: take the median across campaigns or months, so one expensive campaign does not set your account's number.

Step 3: Split brand from non-brand

We think Brand terms usually cost less and convert more because the searcher already knows you. Compare non-brand search only, and report brand on its own line.

Step 4: Check your expected CPC with Keyword Planner

Google states that forecasted impressions take your bid, budget, seasonality, and historical ad quality into account, and that historical metrics do not. The top of page bid range gives a spread: the low end approximates the 20th percentile and the high end the 80th percentile, using bid information from the last 30 days. In our reading, a forecast for your own keywords is a closer reference than any cross-industry table.

Step 5: Convert to cost per lead

For example, and not as a benchmark, a non-brand CPC of $8 and a conversion rate of 0.04 give a cost per lead of $8 / 0.04 = $200. Run the benchmark's CPC and conversion rate through the same formula only if both come from the same source and year.

| Metric | Your value | Your period | Your definition | Brand or non-brand | Benchmark value | Benchmark source and year | Benchmark sample | Benchmark definition | Statistic (median/mean) | Keyword Planner forecast | Match? (segment/year/definition) | Note |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CPC | | | | | | | | | | | | |
| Conversion rate | | | | | | | | | | n/a | | |
| Cost per lead | | | CPC / conversion rate | | | | | | | n/a | | |

Keep the row next to your pipeline reporting, for example in the demand gen dashboard template, and revisit it when the benchmark source publishes a new period.

Worked example: turning CPC into cost per opportunity

The benchmark tables earlier on this page stop at the lead. Your pipeline number does not. This section carries a click price through to cost per opportunity, then checks it against what a deal is worth. The inputs below are round example figures, not benchmarks.

The arithmetic, step by step

The first step is the one metadata.io states plainly: cost per lead is click price divided by click-to-lead rate. The second step applies the same division one stage further down the funnel.

For example, take a CPC of $8 and a click-to-lead rate of 0.04. In this example, cost per lead is $8 / 0.04 = $200. Now suppose a lead-to-opportunity rate of 0.2.

Use CRM leads and CRM opportunities for both rates, not platform conversions.

Why the second division matters

Aimers argues that for SaaS, cost per SQL is usually more useful than CPL, because "A cheap lead that never becomes sales-qualified is not actually cheap". The same logic holds for opportunities. Two campaigns with the same cost per lead can sit far apart once their lead-to-opportunity rates differ.

For a published reference point at the qualified stage, GrowthSpree's 2026 data, as reported by Aimers, puts the typical cost per SQL at $800 to $2,500. Read that as a range to locate yourself in, not a target.

Checking it against deal value

Cost per opportunity only means something next to annual contract value (ACV) and win rate. Expected revenue per opportunity is ACV multiplied by your win rate. If cost per opportunity is a large share of that figure, the channel cannot pay back before the rest of acquisition cost is added. Pull your own win rate from the CRM, and compare it with the business-to-business win rate benchmarks only as context.

Fill-in template

INPUTS (from your account and CRM, same date range)
  Spend ............................ $______
  Clicks ........................... ______
  CRM leads from paid search ....... ______
  CRM opportunities from those leads ______
  ACV .............................. $______
  Win rate (opportunity to closed won) ______

CALCULATIONS
  CPC                    = Spend / Clicks
  Click-to-lead rate     = CRM leads / Clicks
  Cost per lead          = CPC / Click-to-lead rate
  Lead-to-opp rate       = Opportunities / CRM leads
  Cost per opportunity   = Cost per lead / Lead-to-opp rate
  Revenue per opportunity = ACV x Win rate
  Cost share of revenue  = Cost per opportunity / Revenue per opportunity

To run it backward from a pipeline target instead, use the reverse funnel calculator, then fold the result into customer acquisition cost.

Steps to measure Google Ads against pipeline

The benchmarks earlier on this page stop at the lead. These steps carry each click through to a CRM stage, so Google Ads can be judged on pipeline. Do them in order. A gap in step 1 cannot be repaired later.

The setup, step by step

1. Turn on auto-tagging and capture the GCLID. Google's setup guide lists the first requirement plainly: auto-tagging must be enabled, because it lets you import offline conversions. Add a hidden field to every lead form, write the GCLID from the landing URL into it, and store it on the CRM record next to the email.

2. Enable enhanced conversions for leads. This sends hashed form data, such as email, alongside the click ID. In Data Manager, GCLID and user-provided data can both be used as match keys for data imports.

3. Read the diagnostics report weekly. Google names the usual faults: "Common issues include missing or incorrectly formatted user-provided data, or incorrect in-page code implementation." Remember that imported conversions report on the original click's impression date and may take time to appear, so last week's opportunity count will keep rising.

For API builds, Google's listed best practices include sending all available data, batching requests, using job_id for diagnostics, and avoiding custom variables with user data.

A field map to agree with sales ops

Agree this map before launch, and write the stage definitions into your marketing and sales SLA. Credit rules are covered in sourced versus influenced.

CRM field              -> Google Ads use
gclid (hidden form)    -> click match key
email (hashed)         -> enhanced conversions match key
stage name             -> one offline conversion action per stage
stage change timestamp -> conversion date time
opportunity amount     -> conversion value (opportunity and closed won only)
primary vs secondary   -> decide per action, document owner and date

What this page does not cover

This page does not set benchmarks for Display, Performance Max or Microsoft Ads on their own, and it does not cover bidding strategy, ad creative or keyword selection. It does not tell you what your budget should be. It is not financial or legal advice.