Data analytics software case study: 51% lower cost per lead with paid media accountable to pipeline

The problem

Campaigns were live, but tracking, CRM connections and targeting had not kept pace. Nobody could see which campaigns produced real pipeline, and the ad platforms had no signal about which leads became customers.

What we found

• Lead quality was judged in platform dashboards, not in the CRM
• Generic website pages were receiving high-intent search traffic
• Targeting followed launch assumptions rather than the buyers who actually converted

Strategy

Make paid media accountable to pipeline, not clicks, and do it without pausing live campaigns. Messages were tested by audience; the winner positioned one specialist audience as the people leading the AI change.

What we implemented

1. Rebuilt measurement: forms, CRM and ad platforms connected so each lead’s path to a closed deal flows back to Google and LinkedIn
2. Defined the buyer: an ideal customer profile from closed-won data (enterprise scale, manager level and up, priority industries)
3. Built for conversion: purpose-built landing pages replaced generic website pages, and low-intent search traffic was cut
4. Let the data lead: every test starts with a hypothesis and a success metric, and campaigns are checked end to end before budget goes live

Results

• 51% lower cost per lead, with lead volume holding steady
• 9 in 10 leads meeting the client quality standard, verified in the CRM
• 77% of qualified search leads from purpose-built landing pages
• 100% of paid leads traceable from first touch to closed deal
• 0.77% LinkedIn click-through rate, above the top of LinkedIn’s own forecast range

Business impact

One definition of lead quality, verified in the CRM, now governs targeting on every channel, and bidding learns from real revenue instead of form fills.

What happened next

The winning message became the blueprint for the client’s programs in two further business functions.