Facebook, TikTok, or Google? How to Allocate a Tight Budget and Avoid Common Pitfalls

I once managed an overseas project with a monthly budget under $3,000. My mistake was chasing "omnichannel coverage" by splitting the spend across Facebook, TikTok, and Google. Because the daily spend on each platform was too low, the algorithm never hit its learning threshold. Signals were fragmented, and we bled cash for two weeks. I realized that for small budgets, spreading thin just starves the algorithm of the data it needs to optimize.

To turn it around, I switched to an "80/20" priority strategy. I locked into one primary platform based on the product logic: for beauty/skincare, I slammed 80% of the budget into Facebook to feed the Andromeda algorithm, leaving just 20% for Google brand protection. I implemented a 30/70 testing rule—using 30% of the funds to vet assets and only scaling the remaining 70% into proven winners. I also banned content recycling, ensuring every ad was platform-native to avoid those high CPM penalties triggered by low-quality or repetitive content.

The results were immediate. Within two weeks of consolidating my data signals, CPA plummeted by 42%. With the data volume finally hitting critical mass, the ROAS climbed from 0.9 to a steady 2.5+. It confirmed a cold reality: with a limited budget, data concentration is far more profitable than the illusion of "total reach."

When your budget is tight, do you cling to multiple platforms for the sake of "coverage," or do you cut the secondary channels to let the algorithm actually learn in one place?