How You Can Use AI Feedback Loops to Improve Your Messaging

Marketers/Writers/(fill in the blank) who don’t use AI will be replaced by ones who do.

One key AI concept you need to know is AI Feedback Loops.

Here is a quick primer based on what I’ve learned using AI Feedback Loops.

What are AI Feedback Loops?

An AI Feedback Loop is a process where AI systems analyze data, provide insights, and make recommendations. These are then used to improve or refine a specific task or strategy.

AI Feedback Loops have 6 key steps: (1) Data Collection (2) Data Analysis (3) Insight Generation (4) Implementation (5) Monitoring and Evaluation, and (6) Iteration.

Using AI Feedback Loops to Optimize Messaging Strategy – a Practical Example

1. Data Collection: Collect data on customer engagement with your messaging, such as open rates, click-through rates, and conversion rates.
2. Data Analysis: Use AI tools to analyze this data to identify which messages are performing well and which are not.
3. Insight Generation: AI generates insights suggesting messages with personalized subject lines and better calls to action perform better.
4. Implementation: Implement AI’s recommendations by creating new messages with personalized subject lines and improved call-to-actions.
5. Monitoring and Evaluation: Monitor the performance of the new messages.
6. Iteration: Collect the latest performance data and feed it back into the AI system.

Takeaway

Knowing how to use AI is no longer optional. It’s table stakes. AI Feedback Loops have wide-ranging practical applications. Spend some time learning how to use them.