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A Series A Project Management SaaS Cut Cost Per Qualified Pipeline by 41%

A project management platform was generating plenty of Google Ads leads, but sales kept flagging most of them as unqualified. Restructuring the campaign around intent, not volume, fixed it.

Challenge
The marketing team was hitting its lead volume targets every month, but sales was closing almost none of them. The campaign was built around broad keywords like 'project management software,' which pulled in a lot of clicks from people evaluating free tools, not buyers with budget.
Solution
We rebuilt the campaign hypothesis-first: narrower, higher-intent keyword clusters tied to specific pain points (team capacity planning, resource allocation across departments), each with a matched landing page, and a lead form that asked one qualifying question before submission.
Result
Cost per sales-qualified opportunity dropped 41%, and the sales team's lead-to-meeting rate roughly doubled

Lead volume had never been the problem. The problem was that almost none of the leads were the right leads, and nobody had gone looking for why.

Auditing the actual buyers, not the campaign

Before touching the ad account, we pulled six months of closed-won deals from the CRM and read through the discovery call notes. A pattern emerged quickly: real buyers weren’t searching “project management software,” a term dominated by evaluators comparing free tools. They were searching around specific operational pain, things like coordinating resource allocation across multiple teams.

Rebuilding around intent, not category

The new campaign structure organized keywords into clusters around those specific pain points rather than the product category itself, with each cluster pointing to a landing page written around that exact problem instead of a generic product overview page.

Results

Cost per sales-qualified opportunity fell 41% within the first full quarter of the new structure, and the sales team’s lead-to-meeting conversion rate roughly doubled, since the leads arriving now matched what real buyers actually searched for before purchasing.

FAQ
Didn't narrowing the keywords just reduce lead volume?

Total lead volume dropped about 20%, but sales-qualified volume went up, because the leads coming through were closer to a real buying decision. We optimized the hypothesis for pipeline quality from the start, not raw lead count.

How did you decide which keyword clusters to test first?

We pulled six months of closed-won deal data and looked for language patterns in the discovery call notes, then built keyword clusters around the actual problems buyers described, not the product-category terms marketing had been using.

What happened to the qualifying question on the lead form?

It stayed. Initial concern was that it would hurt conversion rate, and it did, slightly, by about 8%. But the leads that completed it converted to sales meetings at a high enough rate that it was a clear net positive on cost per qualified opportunity.

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