SALES JUDGMENT CHALLENGE 003

THE ACTIVITY
SCORE

Six weeks into an AI-prescribed activity mix, your coaching platform shows the highest activity score yet. The numbers don't all agree on what that means.

What would you do?

THE SITUATION

Every number went up. Except one.

Six weeks ago, your AI coaching platform prescribed a new activity mix based on two years of your data.

You followed it exactly. First meetings are up 34%. Pipeline value is up 9%. Your activity score is at a record high.

But qualification conversion dropped from 40% to 22% — and you have a coaching review this afternoon.

The AI prescribed this activity mix. You followed it exactly. The numbers don't all agree.

MAKE THE CALL

What do you do?

Choose before you continue.

A

Keep the target.

Six weeks is a small sample against two years of data. Watch whether conversion recovers on its own.

B

Lower the target.

Return first-meeting volume closer to its previous level and see if conversion moves back.

C

Tighten qualification.

Keep the higher activity level, but raise the bar for what counts as a first meeting.

D

Break down the divergence.

Compare the new meetings against the historical ones before changing the target at all.

WATCH THE CHALLENGE

Coming October 12.

The video for this challenge publishes October 12. Check back then — or work through the situation and questions below in the meantime.

THE JUDGMENT PROBLEM

A pattern is not a guarantee.

The AI found a real pattern in two years of your data. Then its own recommendation changed the behavior behind it.

It studied past behavior, found a pattern, and prescribed behavior to reproduce it. You followed the prescription. Then the results diverged: 34% more meetings produced only 9% more pipeline.

More activity. Not more efficiency.

The relationship between meetings and pipeline isn't broken — it's holding at a fraction of the efficiency it had before. That's a different problem than "the AI was wrong."

THE ACTED-ON PATTERN

The question is whether it survived being acted on.

A pattern discovered in historical behavior and a pattern reproduced on demand aren't automatically the same thing.

Once you act on a pattern at scale, you can change the very relationship the pattern was built on — the same lever that produced 34% more meetings may not produce meetings of the same quality.

THE JUDGMENT DIFFERENCE

Rising is not the same as working.

THE SCORE ASKS

Is the score going up?

JUDGMENT ASKS

Did acting on the pattern change it?

Pipeline value up 9% — proof the strategy is working? It depends what it cost in selling time to produce that 9%.

BETTER QUESTIONS

Before you trust the score, ask:

01

What relationship was this pattern built on?

02

What's different now that you're producing more of it?

03

Where exactly does the divergence show up — certain sources, certain prospects, or everywhere?

This isn't about whether the AI got it wrong. It's whether the pattern survived — and breaking that down isn't stalling, it's finding out what's actually inside the 9% and the 22%.

SO, WHAT WOULD I DO?

D

Break down the divergence before changing the target.

Not because the AI got it wrong, and not because the higher activity level is the problem. I don't yet know what's inside the numbers.

I'd compare the new meetings against the historical ones before touching the target at all — what did producing that additional 9% actually cost in selling time?

THE SALES JUDGMENT TAKEAWAY

01

Don't mistake the score for the goal.

02

Check whether the pattern survived being acted on.

03

Weigh what the gain actually cost.

A pattern can survive being acted on. Or it can quietly stop paying for itself.
Judgment is what tells you which one you're looking at.

BRING THE CHALLENGE TO YOUR TEAM

Make judgment visible.

Judgment Challenges can be explored with your team through a private 90-minute Judgment Lab, turning the scenario into a practical conversation about targets, pattern drift and what a rising score actually proves.