Table of contents
Meta reports the same conversion under several different names. Add them together and your revenue triples on paper. We found that in our own reporting while rebuilding these case studies: one account read at 16.66× return when the truth was 5.55×.
Everything below uses exactly one event alias, and on every one of these pages the individual campaign rows sum to the total we publish. If they did not, one of the two numbers would be wrong.
| Client | Headline result | Period |
|---|---|---|
| L'Entrepôt de la Réno | Spend 3.1× to CA$320k and ROAS still rose 2.65× → 5.55×; purchases 244 → 1,917 | 12 months |
| L'Exterminateur en Ligne | Launch: CA$32,236 → 2,120 purchases and CA$309,405 (9.60×) | 3 months |
| CFC & Elevate Health | CA$548,256 of spend → 16,387 leads at CA$33.46; best segment CA$11.18 | 12 months |
| Geo Stone | One campaign: 275 leads at CA$19.59 | Launch |
| MDF Mécanique Laval | CA$7,966 → 240 leads at CA$33.19 | Launch |
Two of these are launches, and we say so
Geo Stone and MDF Mécanique had no paid social history at all, and the pest-control account had none on Meta. There is no prior year to compare against, so those pages report absolute performance instead of a growth percentage. That is less impressive to read and considerably more useful if you are deciding whether the channel works for a business like yours.
One of these is not a growth story
The healthcare lead programme is the largest account in this set at over half a million Canadian dollars a year, and its lead volume was slightly lower than the prior year. We publish it anyway, framed as what it actually is: cost per lead held steady at high spend, with one brand segment delivering leads at a third of the programme average. Presenting that as growth would be a lie, and at this spend level holding cost is the harder achievement.
What actually moved the numbers
In every one of these accounts the lever was creative volume rather than targeting. Audiences saturate in weeks at meaningful spend, so concepts entered continuously against a named control and were retired on fatigue signals rather than on a schedule. The second lever was structural: consolidating fragmented ad sets so that every additional dollar fed one learning system instead of diluting ten, and separating prospecting from retargeting so the second could no longer flatter the blended return of the first.
How these numbers were verified
Every figure on this page is repeated from a case-study page, and every one of those was re-pulled directly from the platform that produced it — the Google Ads API, the Meta Marketing API, or Google Search Console and GA4 — rather than from a dashboard screenshot or an internal report. Three rules were applied without exception.
One conversion action, named. Where an account contained several conversion actions, we picked the single action that represents a real sale or a real lead and ignored the rest, even where that produced a smaller number. One account in this set carries more than 900,000 recorded page-view "conversions"; none of that appears anywhere here.
One event alias. Meta returns several aliases for the same event. Summing them inflates purchases and leads by two to three times. Each figure here uses exactly one alias.
Matched windows only. A year-over-year percentage is only quoted where both years have data for every month compared. Where they do not, the result is presented as a launch with absolute totals instead. That rule caused us to retract three claims we had originally drafted, and the affected case studies say so on the page.
