The worst mistake you can make on your facebook ads

Key Concepts:

• AI-driven ad performance
• Ad editing impact
• Learning phase reset
• Data-driven decision making
• Ad duplication strategy

The Peril of Editing High-Performing AI-Driven Ads

The core argument is that editing a live, well-performing ad, especially one driven by AI and generating significant spend and conversions, is detrimental. The speaker emphasizes that even seemingly minor changes, like correcting a typo or aligning with brand guidelines, can have severe consequences.

The Reset Phenomenon: Losing Momentum

The speaker highlights that editing an ad essentially resets it. This means:

• Loss of social proof: All likes, shares, and comments accumulated on the ad are lost.
• Re-entry into the learning phase: The ad algorithm starts from scratch, relearning the optimal audience and delivery strategy.
• Performance disruption: The ad's performance is likely to decline as it rebuilds its optimization.

Example Scenario:

The speaker presents a common scenario: An ad is performing exceptionally well, but a typo or branding issue is identified. The brand owner or client requests an edit. The speaker warns against making this edit directly to the live ad.

The Duplication Strategy: A Safer Alternative

Instead of editing the original ad, the speaker recommends a duplication strategy:

1. Duplicate the original ad.
2. Make the desired edits to the duplicated ad.
3. Run the duplicated ad in parallel with the original.

This approach allows for testing the impact of the changes without risking the performance of the proven ad.

Data vs. Subjectivity: Letting the Numbers Decide

The speaker stresses the importance of data-driven decision-making over subjective opinions. The point is that the element you want to change might be the very thing driving the ad's success.

Evidence and Statistics:

The speaker states that "nine times out of 10" the edited, duplicated ad does not outperform the original. This suggests a high probability of negative impact from editing.

Learning Phase and Algorithm:

The speaker mentions a separate video course that delves deeper into the learning phase and the Facebook algorithm. This suggests that understanding these concepts is crucial for effective ad management.

Notable Quote:

"Remove your subjectivity, let your data do the talking, and don't edit your ads once they're live." This quote encapsulates the central message of prioritizing data-driven decisions over personal preferences.

Conclusion:

The main takeaway is to avoid editing live, high-performing AI-driven ads. The risk of resetting the ad's learning phase and losing accumulated social proof outweighs the potential benefits of minor changes. The recommended strategy is to duplicate the ad, make the edits, and run it in parallel to test its performance against the original. Data should always guide decisions, and subjective opinions should be minimized.