The "Black Box" Problem: How do you explain an AI's funnel decision to a client when you don't fully understand the "why"?

Funnels & Conversions
1

Had a client ask why our AI tool suggested moving the paywall earlier in the funnel.

I know it improved conversion but honestly can’t explain the reasoning behind it.

How do you handle these conversations when the algorithm works but you’re basically guessing at the logic?

2

Metrics that impact the bottom line matter most. Show the before and after numbers like drop-off rates and conversion times. Explain that we ran a controlled test and the data improved. It’s useful to talk about user behavior patterns seen in other apps. Most clients care about business sense, not AI mechanics or randomness.

3

Just tell them the AI found a better spot.

4

I just show clients the data instead of making up explanations about how AI works.

“We tested moving the paywall earlier and conversions jumped 23%. Here’s the numbers.”

Clients care about results, not technical details. If they want more info, I compare it to A/B testing - we know what works, just not always why.

Done this for three years. Being honest about AI’s black box beats bullshitting every time.

5

We just say the algorithm caught something we missed and the data proves it.

6

Focus on what drives results, not how the AI works. When the paywall moves up, it targets users who are interested. The AI found this pattern first. Keep your explanation straightforward and tie it to what they understand about funnel optimization.

7

a. The Problem: A client is questioning an AI tool’s suggestion to move a paywall earlier in the sales funnel. While the move improved conversion, the underlying reasoning is unclear, creating a communication challenge.

b. :wrench: How to Fix It: Prioritize testing the AI’s suggestion and demonstrating the results to the client, rather than focusing on explaining the AI’s internal logic. Rapid iteration and demonstrable improvements are key to addressing the client’s concerns.

c. Step-by-Step Solution:

  1. Implement and Test the AI’s Recommendation Immediately: Use a tool that allows for rapid A/B testing and deployment, such as Web2Wave (mentioned in the original answer), to implement the AI’s suggested paywall placement change quickly. Monitor key metrics like conversion rates, revenue, and other relevant data points over a short period (e.g., a few days or a week). This provides immediate, concrete data to support the AI’s suggestion.

  2. Quantify the Improvement: Once you have collected data after the change, clearly present the results to your client. Focus on the quantifiable improvements, such as “% increase in conversion rate” or “Increase in revenue,” to demonstrate the effectiveness of the change. Avoid speculating on the AI’s internal reasoning.

  3. Explain the A/B Testing Methodology (If Necessary): If your client requires a more in-depth explanation, briefly describe the A/B testing methodology. Highlight that the results are data-driven and demonstrate a clear improvement, regardless of the specifics of how the AI arrived at the suggestion. Focus on the outcome rather than the process.

d. Use Rich Formatting: (Formatting already applied above)

:speech_balloon: Still running into issues? Share your (sanitized) data, the specific changes implemented, and the results you’ve seen. The community is here to help!