How an Austin SaaS company reached 3.8x return on ad spend
A fast-growing software firm was spending heavily on ads but couldn't tell which campaigns created real pipeline. We rebuilt tracking, restructured campaigns and redesigned landing pages.
The challenge
Around 41% of search spend was going on terms like "free" and "jobs". Conversions were counted from form fills, not qualified demos, so smart bidding was optimising for the wrong thing.
The goal
Lower the cost per qualified demo and prove how paid media contributes to sales pipeline.
The journey, stage by stage
- Stage 1 · Weeks 1 to 2
Audit and discovery
We reviewed 12 months of search terms, CRM data and landing page behaviour.
- Search term and wasted spend analysis
- CRM and pipeline data review
- Competitor ad and offer benchmarking
- Stage 2 · Weeks 3 to 6
Rebuild and tracking
We restructured the account around buying intent and fed real sales data back to Google and LinkedIn.
- Intent-based campaign structure
- Offline conversion import from the CRM
- 2,300 negative keywords added
- Stage 3 · Months 2 to 3
Landing page testing
Our conversion team built and tested new demo pages for each audience.
- 5 landing page variants tested
- Shorter demo form with calendar booking
- Customer proof added above the fold
- Stage 4 · Months 3 to 5
Optimise and scale
With clean data, we moved budget into the campaigns creating pipeline and added LinkedIn retargeting.
- Budget shifted to high-intent campaigns
- LinkedIn retargeting for engaged accounts
- Weekly bid and creative reviews
The results
Before and after our work, measured in the numbers that matter to the business.
| Metric | Before | After | Change |
|---|---|---|---|
| Monthly demo bookings | 96 | 259 | +170% |
| Cost per demo | $438 | $185 | -58% |
| Monthly pipeline created | $610K | $1.84M | +202% |
| Return on ad spend | 1.4x | 3.8x | +171% |
For the first time our ad spend lines up with pipeline. Sales trusts the leads, and finance trusts the numbers.