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Proved LinkedIn outperforms Google Ads for B2B pipeline by 3.7x. logo

Proved LinkedIn outperforms Google Ads for B2B pipeline by 3.7x.

Proved LinkedIn outperforms Google Ads for B2B pipeline by 3.7x.

RevOps Hub used cross-channel attribution to compare LinkedIn and Google Ads, discovering LinkedIn generated 3.7x more pipeline per dollar for their B2B audience.

· 4 min read
Abbas Venkataraman
By Abbas Venkataraman· Social Media Manager, Revenue Proven
Illustrative hero image for the case study: Proved LinkedIn outperforms Google Ads for B2B pipeline by 3.7x.

The Challenge

RevOps Hub split their $30K/month paid budget evenly between LinkedIn and Google Ads. Google generated more clicks at lower CPCs, making it look like the better investment in platform dashboards. But the sales team felt that LinkedIn-sourced leads were higher quality. Nobody had data to settle the debate.

The Solution

RevOps Hub used RevenueProven to attribute pipeline to both channels at the company level. For LinkedIn, the platform used native company engagement data. For Google, they tracked landing page visits matched to CRM companies via domain. Both channels were measured by the same standard: influenced pipeline.

The Results

The data was decisive: LinkedIn generated $556K in influenced pipeline ($37 cost per influenced deal) vs. Google's $150K ($139 cost per influenced deal). LinkedIn was 3.7x more efficient at generating B2B pipeline, despite Google's lower CPCs.

RevOps Hub shifted 60% of their total paid budget to LinkedIn and saw overall pipeline grow 45% in the following quarter.

Key Takeaway

Click metrics favor Google; pipeline metrics favor LinkedIn for B2B. The channel comparison completely flips depending on whether you measure clicks or revenue. Attribution data ensures you're optimizing for what actually matters.

The Challenge

Like many B2B teams, this company could see LinkedIn Ads activity and CRM pipeline, but could not confidently connect the two. Engagement lived in the ad platform, deals lived in the CRM, and the link between them was assembled by hand — if at all. That gap made it hard to defend spend, prioritise campaigns, or show leadership where revenue was really coming from.

The core problem was attribution at the account level. B2B buying committees are large and sales cycles are long, so the moment a deal closes is rarely the moment a campaign did its work. Without a company-level view, influenced pipeline stayed guesswork.

The Approach

Revenue Proven connects LinkedIn Ads engagement to CRM revenue at the company level, so B2B teams can prove which campaigns influenced real pipeline and closed-won deals. It pulls company-level engagement from the LinkedIn Ad Analytics API across five lookback windows (180, 90, 60, 30, and 7 days), matches those companies to HubSpot or Salesforce accounts by domain and name, and surfaces influenced pipeline and influenced revenue alongside a company-by-company journey timeline.

Rather than chase person-level signals, the team focused on the accounts their campaigns actually reached and on whether those accounts showed up in pipeline. Because B2B buying involves many people and many touches over long sales cycles, Revenue Proven uses multi-touch, company-level attribution rather than last-click, giving credit across the accounts an ad actually reached. This reframed the question from "which ad got the last click" to "which campaigns influenced the companies that became opportunities."

How Revenue Proven Attribution Worked

Revenue Proven pulled company-level engagement from LinkedIn across multiple lookback windows and matched those companies to CRM accounts by domain and name. Influenced pipeline and influenced revenue were then surfaced alongside a company-by-company journey timeline, so the team could trace how engagement preceded and accompanied real deals.

Because the analysis was grounded in the company's own connected data, the results were defensible. OAuth tokens are encrypted at rest, data is processed per workspace, and company-level reporting avoids the brittleness of cookie-based, person-level tracking. The reporting held up in front of both sales and finance, which is what turned it from a marketing dashboard into a shared source of truth.

The Results

The headline outcome is summarised at the top of this case study. Beyond that figure, the bigger shift was operational: marketing could finally point to specific campaigns and accounts and say, with evidence, that they influenced pipeline. That clarity changed how budget was allocated and how performance was reported.

With a repeatable, company-level attribution model in place, the team moved from defending spend after the fact to steering it proactively — investing in the campaigns reaching the accounts most likely to convert, and trimming the ones that generated engagement without progressing deals.

A note on measurement

Because B2B buying involves many people and many touches over long sales cycles, Revenue Proven uses multi-touch, company-level attribution rather than last-click, giving credit across the accounts an ad actually reached. OAuth tokens are encrypted at rest, data is processed per workspace, and company-level reporting avoids the brittleness of cookie-based, person-level tracking. Keeping connections active and syncing regularly is the simplest way to keep influenced pipeline and revenue accurate over time.

Why account-level reporting wins

Person-level tracking degrades as cookies and identifiers disappear, but company-level attribution stays stable because it follows the accounts your campaigns reached. That is what makes the reporting defensible in front of both sales and finance.

Turning insight into action

Once influenced pipeline is visible by company, the next step is operational: invest more in the campaigns reaching accounts that are progressing through the pipeline, and rework the ones generating engagement without movement. Revenue Proven connects LinkedIn Ads engagement to CRM revenue at the company level, so B2B teams can prove which campaigns influenced real pipeline and closed-won deals.

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