How Frequently We Analyze Meta Ad Performance

Happy Wednesday!

This week, we're diving into how often you should analyze your Meta ad performance to maximize your advertising performance and ensure you're not going against the Meta algorithm.

What you will learn today:

• What creative analysis traps many brands fall into

• How long you should wait for reliable data before making any changes

• Why you should avoid labeling ads as winners or losers too quickly

• What profitability and retention metrics you should analyze daily

• Our benchmarks for Hook Rate and Hold Rate

And much more…

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Top Content of the Week

• How to calculate the ROI of your advertising? Read here.

• How can you create more winning ads? Read here.

• Meta adds enhanced AI creation tools for Facebook and Instagram Ads. Read here.

Once you launch new ad creative on Meta or TikTok, how long should you wait before measuring their success or failure?

Common Pitfalls

Many brands fall into the trap of premature analysis.

For example, if your average order value (AOV) is $60 and your target customer acquisition cost (CAC) is $30, don’t turn off or change the ad when you’ve spent only $40.

Brands that pause or edit ads prematurely disrupt Meta’s learning phase and rarely see success with paid advertising.

The Learning Curve

Meta needs time to identify and target the optimal audience for new creatives.

Updating elements like headlines or ad copy too early can perpetually reset this learning phase, leading to suboptimal performance and wasted ad spend.

Recommended Practices for Analyzing Ad Performance

1. Wait For Reliable Data

Before making any changes to your ads, let them run long enough to gather reliable data.

Your ad should spend at least 2-3x your target CAC before you decide to scale or turn it off.

For example, if your CAC target is $40, allow the ad to spend upwards of $120 to ensure you have enough data to make informed decisions.

2. Early Success vs. Long-Term Performance

Avoid labeling ads as winners or losers too quickly. Initial successes will always stabilize once more data comes in.

For example, an ad achieving a 13X return on ad spend (ROAS) on day one may stabilize to a more sustainable 3-4X ROAS after a few days.

3. Meta's Ad Distribution

Keep in mind that Meta might not evenly distribute spending across all launched ads immediately. Some ads may receive more exposure initially, which can skew early data.

Ensuring that each ad has a comparable amount of data is crucial for fair analysis.

Analyze These Metrics

We categorize ad metrics into two main groups:

• Profitability Metrics

• Retention Metrics

Profitability Metrics

These are the core metrics that indicate the financial performance of your ads:

• CPA (Cost Per Acquisition): Measures the cost to acquire a new customer through a specific ad

• ROAS (Return on Ad Spend): Calculates the revenue generated for every dollar spent on advertising

• Purchases

• Ad Spend

These metrics directly reflect how much money your ads are making and are crucial for assessing overall ad performance.

Retention Metrics

This category helps you understand how engaging your ad content is to your audience:

• Hook Rate: Percentage of viewers who watch the first 3 seconds of your ad

• Hold Rate: Percentage of viewers who stay engaged beyond the initial hook

• Watched Video 25%

• Watched Video 50%

• Watched Video 75%

• Watched Video 100%

These metrics provide insights into how well your ad captures and holds attention throughout its duration.

Understanding Benchmarks

It's important to note that benchmarks can vary significantly across different brands and industries.

Each audience segment reacts differently and a direct comparison may not always be applicable.

However, benchmarks give us a starting point to measure the relative success of an ad.

Retention Metrics Benchmarks:

Hook Rate:

• Below 25% is considered low.

• 30% to 35% indicates good performance.

• Above 35% is excellent.

Hold Rate:

• Below 6% is considered low.

• 6% to 10% indicates good performance.

• Above 10% is excellent.

Retention metrics are especially useful for identifying where viewers lose interest.

For example, if you notice a significant drop-off between the Watched Video 50% and 75% metrics of your video, it's time to investigate.

Keep in mind that the Watched Video XX% metrics are relative to video length.

If your video has 60 seconds, the 50% mark is 30 seconds and the 75% mark is 45 seconds.

By comparing different ad variations, you can pinpoint what content keeps viewers engaged and what causes them to leave.

Optimization Example

If Variation 2 shows a major drop-off between 30 to 45 seconds, but Variation 4 maintains viewer interest in the same segment, consider swapping the content in Variation 2 with that from Variation 4 to potentially reduce drop-offs.

Conclusion

While profitability metrics offer a direct reflection of financial performance, retention metrics provide deeper insights into potential areas for optimization.

By continuously monitoring both profitability and retention metrics and understanding their benchmarks, you can make informed decisions that drive better ad performance.

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