Taboola agency
Newbie
- Oct 24, 2025
- 12
- 6
1 Product: Prepare at least 5 videos + 5 images for the first wave
Step 1:
Series ①: 1-1-10
Series ②: 1-1-Flexible (10 assets)
Step 2: Expansion and Scaling:
1. Copy all non-spending ads from Series ① 1-1-10 into a new 1-1-N series. Set a bid cap for this series with a generous threshold. If its performance outperforms Series ①, adjust the cost-per-conversion bid upward by $5-$20 based on results. Fine-tune until the daily budget is fully spent. Testing shows this new 1-1-N series often uncovers profitable new creatives. This method was discovered by accident this year—cloned ad sets often outperform the original Series ①.
2. For high-spending, high-performing ads in Series ①, test interest audiences and lookalike audiences using the original post. Develop these audiences yourself. This directly controls the variables: the creative is fixed, leaving only the audience to test.
3. If flexible ads in Series ② perform well, identify the top-performing, highest-spending ad by reviewing Facebook posts with comments (focus on those with most likes/comments). Again, use the original post to test interest audiences, lookalike audiences, etc.
Summary: This approach comprehensively covers core factors like creative testing, audience testing (interest keywords, lookalikes), original post performance, and bid caps—making it quite thorough. However, this approach assumes you already have creative assets ready in the first step. What if you lack strong assets in most cases? Then prepare another round: 5 videos + 5 images. The number of rounds depends on how much you value this product.
If you're testing mass-market products for bestsellers, you might select one product, test 10 assets in one round. If no assets perform well, move directly to the next product and repeat the process. If still no success, proceed to the next one.
For brand sites where product selection is fixed, it's an endless loop until quality assets emerge. Once found, proceed with scaling and expansion.
This approach prioritizes testing assets over audience interest due to their critical importance.
Feel free to critique or discuss if you disagree.
Step 1:
Series ①: 1-1-10
Series ②: 1-1-Flexible (10 assets)
Step 2: Expansion and Scaling:
1. Copy all non-spending ads from Series ① 1-1-10 into a new 1-1-N series. Set a bid cap for this series with a generous threshold. If its performance outperforms Series ①, adjust the cost-per-conversion bid upward by $5-$20 based on results. Fine-tune until the daily budget is fully spent. Testing shows this new 1-1-N series often uncovers profitable new creatives. This method was discovered by accident this year—cloned ad sets often outperform the original Series ①.
2. For high-spending, high-performing ads in Series ①, test interest audiences and lookalike audiences using the original post. Develop these audiences yourself. This directly controls the variables: the creative is fixed, leaving only the audience to test.
3. If flexible ads in Series ② perform well, identify the top-performing, highest-spending ad by reviewing Facebook posts with comments (focus on those with most likes/comments). Again, use the original post to test interest audiences, lookalike audiences, etc.
Summary: This approach comprehensively covers core factors like creative testing, audience testing (interest keywords, lookalikes), original post performance, and bid caps—making it quite thorough. However, this approach assumes you already have creative assets ready in the first step. What if you lack strong assets in most cases? Then prepare another round: 5 videos + 5 images. The number of rounds depends on how much you value this product.
If you're testing mass-market products for bestsellers, you might select one product, test 10 assets in one round. If no assets perform well, move directly to the next product and repeat the process. If still no success, proceed to the next one.
For brand sites where product selection is fixed, it's an endless loop until quality assets emerge. Once found, proceed with scaling and expansion.
This approach prioritizes testing assets over audience interest due to their critical importance.
Feel free to critique or discuss if you disagree.
