Sample case study for demonstration. This engagement is illustrative: the scenario is typical of the work Axoria does, and the results are described without figures until verified client data is published.
The situation
A B2B SaaS company selling workflow software to finance teams had grown through a product-led free trial and paid acquisition spread across Google Ads, LinkedIn, Meta and a handful of review sites. Each channel was run by a different person or vendor, each reported in its own platform, and added together those reports claimed more signups than the product database recorded.
The board had asked a question the company could not answer: how long does it take to earn back the cost of a paying customer, and which channels are driving it? Axoria was engaged to run the performance marketing programme with that question as the brief.
The challenge
Three problems compounded each other. Platform attribution was double-counting conversions, so no channel’s cost per trial could be trusted. Trials were treated as equal even though a large share never activated, so the metric being optimised was disconnected from revenue. And there was no mechanism for deciding between channels: budgets were set annually and defended by whoever ran them. The goal was not to cut spend but to know which spend was producing paying customers that would not have arrived anyway.
Research and analysis
We began by rebuilding the measurement layer. Trial signups were joined to activation events and billing data in the warehouse, so every trial could be classified as qualified (reached the activation milestone) or not, and every paying customer traced to its first and last touch. GA4 was reconfigured with server-side tagging so the same event definitions fed every platform.
We then compared platform-reported conversions against warehouse-verified ones. Paid social was over-claiming heavily through view-through attribution. Branded paid search was capturing demand that organic and direct would probably have caught. Review-site placements were under-credited because their traffic often converted days later through a direct visit.
Strategy
We proposed a coordinated system rather than a set of channel plans, organised around three commitments.
The trade-off was that incrementality tests deliberately withhold spend from some regions for a period, which costs short-term volume. The client accepted this because the alternative was continuing to allocate a large budget on numbers nobody trusted.
Execution
The first quarter was spent on tracking, the warehouse join and the first two geo holdouts. Branded search was tested first because it was simplest to isolate; paid social followed, with matched market groups selected on historical signup patterns. While those tests ran, non-brand search was restructured around qualified-trial imports so that Smart Bidding was learning from the right outcome.
In parallel, the CRO track focused on the gap between signup and activation. Session recordings showed most unqualified trials abandoned at the data-connection step, so the onboarding flow was tested with a guided sample dataset. Raising activation rate lowers CAC for every channel at once.
Optimization
The holdout results reshaped the mix. Branded search spend was reduced to a defensive floor. Paid social proved more incremental than the raw view-through numbers suggested but less than the platform claimed, so it was kept with a lower budget and a creative programme aimed at cold audiences rather than retargeting. Review-site placements and non-brand search absorbed the freed budget. Reallocation happened in monthly steps with warehouse-reported CAC payback as the check on each move.
Results (illustrative)
Figures are withheld until verified, client-approved data is published. Measured from the warehouse against the prior year, the movements typical of a programme like this are:
- CAC payback: shortening materially as spend moved away from non-incremental channels and activation rate rose.
- Qualified trials: growing on a flat total budget, with the qualified share of all trials improving through onboarding tests.
- Blended efficiency: blended cost per paying customer falling, with platform-reported cost per trial retired from the reporting pack.
What we learned
- Measurement is the strategy. Until every channel reports against the same warehouse-verified outcome, budget allocation is negotiation, not optimisation. Our analytics and tracking work is usually the first step for a reason.
- Test incrementality where it is cheapest to be wrong. Starting with branded search built confidence in the method before the harder paid-social test.
- Activation is an acquisition lever. Improving what happens after signup lowered CAC across every channel simultaneously, a pattern common to product-led SaaS.
- Move budget in steps. Monthly reallocation with a payback check avoided over-correcting on a single test result.