Proved ABM program drives 2.8x larger deals.

The Challenge

CloudBase had been running an ABM program on LinkedIn for a year, targeting 200 enterprise accounts with personalized campaigns. The program felt like it was working — sales reps reported warmer conversations — but leadership wanted hard numbers to justify the premium CPMs that ABM targeting requires.

The Solution

CloudBase used RevenueProven to track engagement across their 200 target accounts and compare deal outcomes for ABM-touched vs. non-ABM accounts. The platform matched LinkedIn engagement signals to Salesforce opportunities, providing a clear A/B comparison.

The Results

The data was decisive: deals from ABM-influenced accounts averaged $180K vs. $64K for non-ABM deals — a 2.8x difference. ABM accounts also moved through the pipeline 45% faster, likely because multiple stakeholders had already been exposed to CloudBase's messaging before the first sales meeting.

CloudBase expanded their ABM target list from 200 to 500 accounts and increased their LinkedIn Ads ABM budget by 60%.

Key Takeaway

ABM programs are expensive by design — you're targeting fewer accounts with higher-touch campaigns. Attribution data proves whether that premium investment generates proportionally larger returns, turning ABM skeptics into advocates.

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, company-level attribution 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.