Quick answer
No, not as a current, apples-to-apples fact. LinkedIn's own marketing page still cites "28% lower cost per lead than Google AdWords," but its own footnote traces to an undated slide deck that measured one ad format (Sponsored Content), against a Google product that was renamed Google Ads back in 2018. Current third-party 2026 benchmarks show LinkedIn's raw cost per lead running higher than Google's, not lower, though LinkedIn does out-perform Google Search on return on ad spend once you follow the money to closed revenue instead of the first click.
The claim, and where it lives
I'm Hlib Storchak. I build outbound systems for B2B founders and sales teams, 2000+ meetings booked for B2B clients so far, and channel mix (where the marketing budget goes versus where the outbound budget goes) is a question I get from almost every client with any paid spend at all. LinkedIn's own site is part of why the question keeps coming up. On its current lead generation page, business.linkedin.com states plainly that "cost per lead is 28% lower than Google AdWords," with a small footnote number attached. That single sentence gets repeated, unattributed, across dozens of 2026 B2B marketing blog posts as if it's fresh, LinkedIn-verified data about how the two platforms compare today.
I went and read the footnote.
Tracing the footnote
LinkedIn's own citation for the 28% figure links to a SlideShare deck titled "LinkedIn: Your B2B Partner of Choice." I fetched it directly rather than trusting the secondary sites that repeat the number. The deck does contain the line, but it reads differently from how LinkedIn's marketing page presents it: "Cost Per Lead for Sponsored Content is 28% less than Google AdWords." No sample size. No date range. No methodology note on the slide itself, just a bar chart benchmarking LinkedIn against a demand-side platform, a couple of unnamed publishers, and an ad network.
That's the entire primary source behind a stat that's now cited on LinkedIn's own current page, in 2026, as if it describes today's market.
Tip. When a vendor's own site cites a number, check whether the footnote goes to a dated, methodology-disclosed study or to an old sales deck. LinkedIn's own page does the latter here, and it's worth checking before you repeat the number to a client.
How old is "28% lower," really?
The SlideShare deck carries no visible publish date in its own text, but there's a simple, verifiable way to bound it: it names the comparison platform "Google AdWords." Google retired that name on July 24, 2018, rebranding it to Google Ads as part of a wider reorganization of its ad products. Any claim that specifically names "AdWords" was written before that date, or is quoting something that was. That puts this benchmark at eight years old or more as of this article, built from ad auction dynamics, average CPCs, and a competitive landscape that has moved on more than once since. LinkedIn's own current lead-gen page still uses the old product name today, which is itself a small tell that nobody has refreshed this specific citation in a long time.
It was never about "LinkedIn Ads." It was about one format.
The second problem is scope, not just age. The original slide says "Sponsored Content," which is one specific LinkedIn ad format, the native feed posts that look like organic content with a "Promoted" tag. It is not the same as LinkedIn Ads broadly, which today spans Sponsored Content, Message Ads (paid InMail), Text Ads, Dynamic Ads, and Lead Gen Forms, each with a genuinely different cost structure and a different native conversion path. LinkedIn's own current marketing page drops that qualifier and presents the figure as if it applies to LinkedIn advertising in general. That's a second, independent way the number has drifted from what it originally measured, on top of the age problem.
What current, dated 2026 data actually says
Third-party 2026 benchmark write-ups on LinkedIn ad costs put average LinkedIn cost per lead in a wide range, commonly cited between roughly $35 and $130 for Lead Gen Form campaigns depending on industry, with a cross-industry average some of these trackers put around $94, up from roughly $87 the year before. Google Ads cost per lead for B2B search campaigns is commonly cited in the $8 to $15 range, though both numbers vary heavily by industry and none of these particular figures come with a disclosed sample or methodology, so I'm treating them as directional, not as verified research, consistent with how I treat any aggregator-sourced number on this blog. Read at face value, though, they point the opposite direction from "28% lower": LinkedIn's raw, unqualified cost per lead in 2026 tends to run higher than Google's, not lower.
That's not the same as saying LinkedIn is a worse channel. It's saying the specific "28% lower CPL" framing, taken as a current, general fact, does not match what current data shows either.
Why a higher CPC can still produce a lower CPL, in theory
The reason the original 2018-or-earlier claim was plausible at all is worth keeping, because the mechanism still exists even if the number doesn't hold today. LinkedIn's cost per click has always run well above Google's for most B2B queries, often several times higher. Cost per lead is a function of two things, cost per click and conversion rate from click to lead, so a channel with a higher CPC can still land a lower CPL if its on-platform conversion rate is high enough. LinkedIn's Lead Gen Forms, which auto-fill a member's profile data into a form without leaving the app, are the clearest example: they remove almost all the friction between a click and a submitted lead, and can post double-digit conversion rates where an off-platform landing page might convert in the low single digits. That mechanism is real. Whether it currently produces a 28% CPL advantage specifically against Google, in general, across formats, is the part that isn't backed by anything current.
What "apples to apples" would actually require
For a LinkedIn-versus-Google CPL comparison to mean anything for your own budget decision, it needs to hold five things constant, or at least disclose them: the specific ad format on each platform (Lead Gen Form versus a Google Search campaign with a landing page, say, not a category average blended across formats), the industry and average deal size, the time period, whether "lead" means a raw form-fill or something qualification-gated, and the sample size behind the number. The 28% figure fails on age, format specificity, and disclosed methodology all at once. Most of the current aggregator numbers I found fail on methodology too, they just fail more recently.
| The "28% lower" claim | Current aggregator estimates (2026) | |
|---|---|---|
| Primary source | An undated SlideShare deck, footnoted by LinkedIn's own current page | SEO/benchmark sites, methodology not disclosed |
| Ad format measured | Sponsored Content only | Usually blended across formats or Lead Gen Forms specifically |
| Named platform compared | "Google AdWords" (renamed 2018) | "Google Ads" |
| Direction of the gap | LinkedIn 28% cheaper | LinkedIn often more expensive per raw lead |
| Verifiable today? | No, sample and date undisclosed | No, but at least dated and format-labeled |
A better lens than CPL: return on the spend, not the click
Cost per lead, on either platform, only measures the top of a funnel that still has to survive qualification, a sales cycle, and a close. Dreamdata's LinkedIn Ads Benchmarks Report 2026, published March 10, 2026 and built from an aggregated base of 66 million-plus sessions and 3.5 million-plus customer journeys across its own customer base, measures something further downstream: return on ad spend traced through to closed revenue at the company level. By that measure, LinkedIn posted 121% ROAS, versus 67% for Google Search and 51% for Meta, making it the only one of the three with a positive return in that dataset. Among Dreamdata's own top-performing customers, the gap widens further: 279% for LinkedIn against 138% for Google Search and 133% for Meta.
I'd treat that report the same cautious way I treat any vendor-published benchmark: it's Dreamdata's own customer base, not a neutral, platform-agnostic sample, and "ROAS" defined at the company-attribution level is a specific methodology choice that shifts results versus a last-click or first-click model. But it's dated, it discloses its sample, and it's measuring something closer to what actually pays your bills than cost per lead ever did. If you're choosing where to lean on paid spend, a return-on-spend number that survives to revenue is a far more honest comparison than a cost-per-click-to-form-fill number from either platform.
Building your own channel-cost comparison
Rather than importing either platform's headline number, build the comparison from your own numbers. Here's the shape of it, with every input labeled as an assumption you should swap for your own:
Assume: a $6,000 monthly budget split test, $3,000 to each platform for 60 days; LinkedIn Lead Gen Form CPC of $7 against a 10% on-platform conversion rate to a raw lead; Google Search CPC of $12 against a 4% landing-page conversion rate to a raw lead; a lead-to-qualified rate of 30% on LinkedIn leads and 45% on Google leads, since search traffic tends to arrive with clearer buying intent.
Run the math: LinkedIn gets roughly 428 clicks and 43 raw leads for $3,000, at about $70 per raw lead; Google gets roughly 250 clicks and 10 raw leads, at about $300 per raw lead. LinkedIn looks far cheaper per raw lead here. But qualified leads change the picture: LinkedIn's 43 raw leads at 30% qualification produce about 13 qualified leads ($231 each); Google's 10 raw leads at 45% qualification produce about 4.5 qualified leads ($667 each). LinkedIn still wins on cost per qualified lead in this illustrative run, but by a much narrower margin than the raw-lead number suggested, and the gap would flip entirely if you moved the qualification rates or the CPCs by a plausible amount in either direction. That sensitivity is the actual point: don't trust either platform's headline ratio, trust the range you get from running your own numbers with your own qualification rate.
Key takeaways
- LinkedIn's own current marketing page still cites "28% lower cost per lead than Google AdWords," but its own footnote traces to an undated deck measuring one ad format (Sponsored Content) against a Google product renamed in 2018.
- Current 2026 third-party benchmarks put LinkedIn's raw cost per lead at roughly $35 to $130+ depending on format and industry, generally higher than Google's commonly cited $8 to $15, the opposite direction from the 28% claim, though these aggregator figures are themselves undisclosed on methodology.
- A higher CPC can still produce a lower CPL if on-platform conversion is high enough, which is the real mechanism behind LinkedIn's native Lead Gen Forms, even though the specific 28% figure doesn't hold up as current evidence of it.
- Dreamdata's dated, disclosed-sample 2026 report found LinkedIn at 121% ROAS to closed revenue versus 67% for Google Search and 51% for Meta, a more useful comparison than cost per lead because it survives past the first click.
- Build your own cost-per-qualified-lead model with your actual CPCs and qualification rates before trusting either platform's headline ratio; the gap between raw CPL and qualified CPL can be large enough to change the decision.
The two claims, side by side
To restate the core distinction plainly: "LinkedIn's cost per lead is 28% lower than Google Ads" is an unverifiable, out-of-date, format-specific claim still sitting on LinkedIn's own current page. "LinkedIn produces a better return on ad spend than Google Search once you trace it to revenue" is a separate, more recent, more disclosed claim from an independent third party, and it's the one I'd actually put weight on. They get conflated constantly because they both sound like "LinkedIn beats Google," but they're answering different questions with different evidence behind them.
When I'd actually lean on LinkedIn over Google
Independent of either headline stat, the pattern I see across client accounts is that LinkedIn earns its higher sticker price when the buyer has a specific, narrow professional identity you can target directly (a VP of Engineering at 200 to 1,000-person companies, say) and the deal size is large enough to absorb a higher cost per lead while still paying back. Below a roughly $15,000 to $20,000 average deal size, or when the buyer persona is broad enough that search intent alone finds them (someone actively typing "outbound agency pricing" into Google, for instance), Google's lower cost per click and higher-intent traffic usually wins on absolute ROI. This is the same call I make when a client asks whether to add paid social to a cold email and LinkedIn outreach program: I look at deal size and targeting specificity first, and treat both platforms' own headline cost claims as a starting hypothesis to test, not a verdict to act on.
My take
I don't think LinkedIn is being deliberately dishonest here so much as institutionally lazy: a stat from an old sales deck got baked into a marketing page years ago and nobody has gone back to refresh or retire it since, even as the underlying market moved on. That's a common failure mode for any vendor-published number, not just LinkedIn's. The fix isn't to distrust every stat a platform publishes, it's to check whether the footnote goes somewhere dated and methodical, or somewhere old and thin, before you let it steer a budget decision or a client conversation.
A checklist for the next stat you're handed
Run any vendor-published comparison stat through these before you repeat it:
1. Does the footnote go to a dated source? If there's no date anywhere, treat it as old until proven otherwise.
2. Does it name a specific format, or a whole category? "Sponsored Content" and "LinkedIn Ads" are not interchangeable, and neither are "Search" and "Google Ads" broadly.
3. Does the comparison partner's own branding match today's? A stat that still says "AdWords" hasn't been touched since mid-2018 at the latest.
4. Is a sample size or methodology disclosed anywhere? If not, it's a marketing claim, not a benchmark.
5. Does it measure the stage you actually care about? Cost per raw lead, cost per qualified lead, and return on spend to closed revenue can each point a different direction from the same underlying spend.
FAQ
Is LinkedIn's cost per lead really 28% lower than Google Ads?
Not as current, general fact. LinkedIn's own footnote for that claim traces to an undated slide deck measuring one ad format (Sponsored Content) against "Google AdWords," a product name Google retired in 2018. Current 2026 third-party benchmarks generally show the opposite direction, LinkedIn's raw cost per lead running higher than Google's.
Why would LinkedIn ever have a lower cost per lead despite a much higher cost per click?
Cost per lead depends on both cost per click and click-to-lead conversion rate. LinkedIn's native Lead Gen Forms remove most of the friction between a click and a submitted lead and can convert at double-digit rates, which can offset a higher CPC. That mechanism is real; whether it currently produces a 28% advantage specifically is unverified.
What's a better metric than cost per lead for comparing ad platforms?
Return on ad spend traced through to closed revenue, not just the first click or form-fill. Dreamdata's 2026 benchmark, based on a disclosed sample of 66M+ sessions and 3.5M+ customer journeys, found LinkedIn at 121% ROAS versus 67% for Google Search and 51% for Meta.
Should I stop using LinkedIn ads based on the higher raw cost per lead?
No, not on that alone. Raw cost per lead ignores qualification rate and deal size. Build a cost-per-qualified-lead model with your own numbers, and weigh deal size and how narrow your target persona is, before deciding channel mix.
How do I spot a stale vendor stat like this one in the future?
Check whether the footnote leads to a dated, methodology-disclosed source, whether it names a specific format or a whole category, and whether any comparison partner's branding in the claim still matches its current name. A citation with no date and an outdated product name is a strong signal the number is old.