Experiment context
Hypothesis. Generic service/category semantics were expected to reach new non-game-specific audiences and generate additional transactions at acceptable ROAS/CPO/CAC.
How the test ran. The test was run in stages because initial efficiency was weak; query cleanup and exact-match refinement were part of the process.
Traffic split. 50/50.
Visual summary — after optimization
Acquisition costs after query cleanup and exact-match refinement.
The share of first payments in total transactions is explained by the nature of the keywords used: they tend to attract users who already use these types of services, including Overgear itself.
Performance results
| Period | Spend | Conversions (Google Ads) | Transactions | CPO (GA4) | First purchasers | CAC (GA4) |
|---|---|---|---|---|---|---|
| Before optimization (22.05 – 03.06) | 5,438.65$ | 44.46 | 32 | 169.96 | 4 | 1,359.66 |
| After optimization (03.06 – 09.06) | 321.00$ | 10 | 18 | 17.83 | 2 | 160.50 |
Conclusions
Generic service semantics generated incremental reach beyond game-specific queries, but performance should be judged against the same ROAS, CPO and CAC thresholds as core acquisition. Keep the structure isolated so budgets, negatives and bids can be controlled without distorting game-specific campaigns.
Limitations. The before and after periods differ in duration and the campaign setup was optimized between periods. Treat the result as directional rather than as a controlled A/B estimate.