Case study · SaaS
Paid-search program for a vertical-SaaS scale-up
A complete restructure of a fast-growing SaaS company's paid-search program, intent-mapped landing pages, an account architecture that the algorithm could actually optimize, and offline conversion imports so Google Ads was finally bidding on revenue, not clicks.
The challenge
What we had to solve.
The company was spending six figures a month across Google Ads, with a CPL that looked great on paper and a CPM (cost per qualified meeting) that was quietly creeping up every quarter.
Half the demos were tire-kickers; the other half were the wrong vertical. Sales was burning hours qualifying out unqualified leads, and marketing was getting blamed for a metric they couldn't see.
The account had been built campaign-by-campaign over three years, with every keyword someone had ever thought of, broken down by ad group and shadowboxed by a half-dozen broad-match terms. The algorithm couldn't learn anything because the signal was buried in noise.
Our approach
How we tackled it.
We rebuilt the account from scratch around three intent layers: high-intent (vertical-specific category terms + competitor terms), mid-intent (problem-aware terms), and brand. Each got its own structure, landing-page family and bid strategy.
We connected the CRM to Google Ads via offline conversion imports. Now the algorithm bids based on closed-won revenue, not landing-page clicks. That single change shifted the optimization gravity.
Landing pages got rebuilt per persona, with a specific demo-form variant (industry-specific case studies, role-specific value props, custom calculator). Conversion rates roughly doubled on the high-intent traffic.
We layered LinkedIn ABM on top, matched accounts from the CRM, sequenced ad creative by funnel stage, and synced retargeting back into Google's audience layer.
Weekly reviews focused on CPM, not CPL. The new vocabulary changed the conversation with leadership entirely.
Deliverables
What we built.
Specific, named outputs, not vague "strategy".
Account restructureThree intent layers, clean ad-group hierarchy, broad-match consolidation.
Landing-page familyPer-persona variants with custom forms, case-study modules and trust signals.
Offline conversion syncCRM → Google Ads with closed-won + opportunity-stage signals.
LinkedIn ABM layerMatched account targeting with funnel-stage creative and Google retargeting sync.
Weekly + monthly cadenceCPM-led performance reviews, with sales sitting in every other week.
Outcomes
What it returned.
- Cost per qualified demo dropped 41% over six months, on flat spend.
- Demo-to-opportunity rate up significantly because the demos coming through the new account were better fit.
- Sales-marketing alignment noticeably improved because both teams were finally looking at the same metric.
- The CFO renewed the marketing budget without a meeting, the attribution story was self-explanatory.
The takeaway
What we learned.
Google Ads doesn't optimize for what you tell it to, it optimizes for what you give it data on. If your conversion signal is "landing-page form fill", you get more form-fillers. If it's "closed-won deal", you get more deals. The technical work was 30% of this engagement; the conversation about what to measure was the other 70%.
Services used
How we got it done.
Related work