$12.7M went to click campaigns. 99.4% of them recorded no lead at all.
The money bought clicks. The report counted leads.
$12.7M of 2025 B2B ad budget went to campaigns set to buy clicks and traffic, and the lead report shows 66 leads against it, $191,686 each. That is 22% of every dollar we analyzed, spread over 112 advertisers: the typical advertiser put 16% of its own budget there, and 61 of 153 put more than 30% there. It is the biggest block of money on the plan that nobody could judge. The limit, stated plainly, with the evidence for it: 99.4% of these campaigns recorded no lead at all, and only 4 of the 112 advertisers recorded a single one, they send traffic to a page with no lead capture wired to it. The $191,686 is therefore an artifact of missing measurement, not a price anyone paid per lead. This dataset also does not measure brand value. It is the wrong ruler, not proof the money vanished. Metadata’s 2025 benchmark: 153 advertisers, $57.6M of spend.
Pull every traffic and click campaign out of the cost-per-lead report this week, give each one its own budget ceiling, and write down the reason it runs and the number it has to hit. In metadata.io’s 2025 benchmark, $12.7M of click and traffic spend across 112 advertisers shows up as 66 leads at $191,686 each, against $202 a lead on LinkedIn campaigns set to collect leads. No bid change closes a gap that size. The report was pointed at the wrong thing.
2025 · 153 advertisers · $57.6M analyzed · 112 advertisers ran click and traffic campaigns · a lead means a lead record that reached the CRM · only groups with at least $50K spent · Methodology · Typical vs best-case: how to read this
Executive summary
- The measurement gap: the typical advertiser put 16% of its budget into campaigns set to buy clicks and traffic. Across the dataset that is 22% of 2025 spend, $12.7M across 112 advertisers, showing 66 leads, or $191,686 each. The number is evidence that the lead report cannot see this spend, not that the spend did nothing.
- The budget call: this is a budgeting and measurement decision, not a targeting one. 61 of 153 advertisers had more than 30% of budget on campaigns a cost-per-lead number was never going to judge fairly. Give that money a written purpose, its own ceiling and its own scoreboard, or stop funding it.
- The limit, stated plainly: click campaigns are not supposed to be lead engines, and any brand or awareness value they built is real but unmeasured here. A website sign-up they helped cause may never be recorded as their lead. Nothing on this page proves the money vanished; it proves the ruler cannot read it.
Playbook
- The play: split every traffic and click campaign out on its own, its own line, its own budget ceiling, its own report. Then write on the brief what it is meant to do.
- The setup: campaigns meant to collect leads get the lead setting and a form inside the platform. On LinkedIn across these advertisers, the built-in form made a lead for $193 against $346 when the click went to a landing page.
- The measurement: traffic campaigns come out of the cost-per-lead line entirely, and each one carries its own ceiling. A stated reason and a number it has to hit, or it stops being funded, $191,686 a lead is what the blended report reads when both kinds of campaign share a scoreboard.
What did the money actually buy?
Clicks. In 2025, 112 advertisers put 22% of the spend we analyzed, $12.7M. Into campaigns set to buy clicks and traffic, and the lead report shows 66 leads between them: $191,686 each.
The mechanism is not mysterious. When you set a campaign to traffic or clicks, the platform goes and buys the cheapest click it can find, and the cheapest click in B2B is rarely a buyer. Nothing in that loop is broken. The platform delivered exactly what it was asked for. The mismatch is upstream, between a budget that bought click volume and a report that then divided it by leads. That is why the honest label here is the wrong ruler rather than waste: lead tracking is the wrong measure for this spend, and this dataset has no second measure pointed at it, no holdout, no brand-lift study, no view-through. What the number does establish is how big the unjudged block is, and an hour spent checking what each campaign is set to buy buys more clarity than a quarter of bid and creative tuning.
Why did $12.7M show up as only 66 leads?
Because the setting you pick when you launch decides what gets bought. Pick traffic or clicks and the platform chases clicks and page views; pick lead generation and it chases submitted lead records. Same audiences, same creative, different instruction to the auction, and the lead count follows the instruction.
Two definitions matter for reading the number honestly. “Traffic / awareness” here means the goal field as it was set in the ad platform, not our judgement of the creative. And a lead means a lead record that reached the CRM, counted the same way whichever setting the campaign ran on. There is no looser lead definition applied to the traffic campaigns to make them look worse. What the traffic setting bought instead is visible in the media numbers: cheap clicks in volume, at a cost per click well below the lead campaigns, with nothing attached to capture a lead.
Should you stop running traffic campaigns?
No. Fix the reporting and the mandate, not the tactic. Traffic campaigns are legitimate brand spend, but here they were funded like lead spend and judged like lead spend. The rule that fixes it: a stated reason and a number it has to hit, or it stops being funded.
Concretely, three conditions before a traffic campaign ships. It carries a written purpose. The audience it is meant to reach, the belief it is meant to create, and the check that would show it failed. It has its own budget ceiling, so it cannot quietly absorb a quarter of the plan the way it did for 61 of 153 advertisers here. And it comes out of the cost-per-lead report, because a number it was never trying to hit can only ever slander it or hide it. Banning click campaigns outright is the wrong call and this dataset cannot support it. What the dataset supports is narrower: uncapped click spend, with no written reason and no scoreboard of its own, was the largest block of budget nobody could judge with the measure they had.
How could this number be wrong?
Two ways, and both are real. First, click campaigns can help sign-ups they never get credit for: someone arrives from a click campaign, comes back later and fills in a form on your site, and that lead record may carry no campaign on it at all, so our 66 undercounts. Second, and more fundamentally, brand and awareness effects are not in this dataset at all, no lift study, no holdout, no view-through, so a traffic campaign that worked exactly as intended would still show up here as almost nothing.
Three answers, in order of how much they concede. Both objections are true and we cannot size either. Which is precisely why we publish this as the wrong ruler rather than as money written off. Neither rescues the arithmetic: for 22% of $57.6M to break even against the lead campaigns on leads alone, the leads nobody recorded would have to outnumber the recorded ones by something like a thousand to one. And both argue for our recommendation rather than against it: if the value of a click campaign lives in effects the lead report cannot see, then it needs a written purpose, its own ceiling and its own measure. Which is exactly what we are asking for.
There is one other explanation we cannot rule out: the kind of advertiser who picks a traffic setting. They may also have run weaker offers, thinner capture and less mature measurement, so the gap prices the team as well as the setting. We cannot separate those, and we do not claim the setting alone caused anything. What we claim is narrower and harder to escape: this spend was reported inside the same lead numbers as lead-generation spend, and against that measure it reads $191,686 a lead. Which means the measure in use cannot tell you whether it worked.
What does a lead cost when you ask for leads?
Between $138 and $524 in 2025, depending on channel, Instagram $138, Facebook $145, LinkedIn $202, Google Ads $524. How you collect the lead moved the price almost as much as where you ran: LinkedIn’s built-in forms made a lead for $193 against $346 for landing pages.
What should you change?
Cap click and traffic campaigns at a stated share of the plan, and take them out of the cost-per-lead line entirely. 22% of $57.6M landed there with no ceiling on it, and 61 of 153 advertisers were over 30%, a budgeting and measurement failure, not a targeting one.
Move that budget onto the brand line with brand goals for one quarter, or spend it somewhere else. Brand work judged on lead price loses that argument every time; give it reach, frequency and recall goals, and give the lead line back to campaigns that ask for leads.
“Traffic spend is proven waste.” This dataset cannot support that, and it cannot support a blanket ban. What it supports is that 22% of the money sat on a setting the lead report cannot read, with no ceiling and no written reason. A stated reason and a number it has to hit, or it stops being funded.
Split every traffic and click campaign into its own campaign, budget and report this week. While they share a line with lead generation, the blended report reads $191,686 a lead on 66 leads across 112 advertisers, and no bid change fixes the wrong ruler.
Write the reason on the brief before the next traffic campaign launches: who it reaches, what it should make them believe, and the check that would prove it wrong. Then switch the lead-capture campaigns to the lead setting with a built-in form, $193 a lead against $346 on landing pages here.
“Switching the setting will fix our cost per lead.” The setting decides what the auction chases; how you collect the lead, and what the CRM shows afterwards, still decide whether those leads become customers. The audience-yield finding shows the cheapest lead was not the best one.
What are the exact numbers?
What each campaign was set to buy, then what a lead cost when the campaign asked for one. The first table is not a return comparison. The top row is spend the lead report cannot judge, printed so you can see how big that block is. No cost number appears without an outcome column beside it, even when that column has to read “withheld”.
| What the campaign was set to buy | Advertisers | Share of analyzed spend | Leads the CRM recorded | Cost per lead recorded |
|---|---|---|---|---|
| Traffic / awareness | 112 | 22% ($12.7M) | 66 | $191,686 |
| Leads | 132 | the rest of the $57.6M | 154,000 | , by channel below |
| Advertisers with over 30% of budget on traffic / awareness | 61 of 153 | — | — | — |
| Channel (campaigns set to collect leads) | Advertisers | Cost per lead | Beside it: cost per customer and what came back in year one |
|---|---|---|---|
| 49 | $138 | withheld, one advertiser held more than 40% of it | |
| 71 | $145 | withheld, one advertiser held more than 40% of it | |
| 138 | $202 | $63,312 · 0.57x back on the dollar (across 114 advertisers) | |
| Google Ads | 56 | $524 | withheld, below our publication minimums |
Cost per lead on click and traffic spend = all 2025 click and traffic media spend divided by the lead records the CRM recorded against it. For campaigns set to collect leads, cost per lead is averaged across every dollar spent within each channel. The 154,000 leads and their $29.4M of spend are the lead-collecting campaigns behind every pipeline number in this report. Numbers we withheld, and the reason for each, are visible in the interactive explorer.
How do we know?
Every number above passed the same publication gates before it reached this page. In brief:
- Advertiser minimums: at least 5 advertisers behind any published media number and at least 8 behind any pipeline number, plus at least 3 deals that actually closed. The click and traffic number rests on 112 advertisers; the channel numbers on 49 to 138.
- No one advertiser is allowed to swing a number: no single advertiser above 50% of a published media number’s spend, and none above 40% of a published pipeline number’s spend or outcomes. The Facebook and Instagram pipeline numbers broke that rule and were withheld, not estimated.
- Spend floor: we publish a number only where at least $50,000 was spent.
- Scope: $57.6M of 2025 paid media across 153 advertisers. What each campaign was set to buy is read from the goal field in the ad platform, and a lead means a lead record that reached the CRM, counted the same way whichever setting the campaign ran on.
- What this number leaves out, and why we call it a mismatch: brand lift, recall, view-through, and sign-ups on your own website that carry no campaign on them. We have no holdout, lift or view-through data, so what these campaigns contributed without being recorded is unmeasured, not zero. So the honest statement is about what you can see (16% of the typical budget produces nothing your CRM can show you), not about what it was worth.
- This is what happened, not a controlled test: every figure describes 2025 as it ran. Nothing here shows that changing the setting would have given these advertisers the results the lead campaigns got.
- What else could explain this: the kind of advertiser who picks a traffic setting. They may also have run weaker offers, thinner capture and less mature measurement, so the gap prices the team as well as the setting. Our claim survives that because it is a claim about the ruler: this spend sat inside the same lead reporting as lead-collecting spend, and against that measure it reads $191,686 a lead.
Full rules in the methodology, including what we refused to publish, with the exact reason each draft claim was killed. New here? Start with typical vs best-case: how to read any benchmark.
Cite as: Metadata 2026 B2B Ad Spend Benchmark (n=153 advertisers, $57.6M, 2025), metadata.io/benchmark-report-2026
What do you do different tomorrow morning?
One named change per seat. The columns reorder to match your reading lens; both are always on the page.
Put a ceiling and a purpose on brand spend
The one change: give click and traffic campaigns a stated budget ceiling and their own goals, and take them out of the cost-per-lead line.
- Ask what share of spend each campaign goal is taking, this month. Anything set to buy clicks or traffic with no written purpose behind it is the finding; the typical advertiser here carried 16%, and across the dataset it was 22%.
- Name the purpose for what stays: which audience, what belief, which check. Reach and recall goals, not lead goals. Brand work judged on leads loses that argument every time.
- Move the rest to the campaigns that ask for leads, then judge those on what the CRM shows rather than on lead price, the payback baseline is the scoreboard that matters.
Check what every campaign is set to buy, today
The one change: list every live campaign with its goal setting beside its spend, and split the traffic ones out of the lead report before the next stand-up.
- Sort live campaigns by spend and read the goal column. Anything set to traffic or clicks that is being judged on cost per lead comes out of that report today, the blended version read $191,686 a lead across 112 advertisers, which says more about the report than about the campaigns.
- Switch the lead-capture campaigns to the lead setting and collect the lead inside the platform: $193 a lead on built-in forms against $346 on landing pages here.
- For anything you keep on a traffic setting, write on the brief why it runs, the number it has to hit, and the check that would prove it wrong, and cap its budget separately. No written reason, no funding.