Spot unhappy customers before they leave
A weekly early-warning brief that ranks customers by risk, so you call the right ones before it's too late.
- Time
- One day to set up, 20 minutes a week
- You'll need
- Your job, ticket or project tracker · Your inbox · An AI assistant · An automation tool
- You'll end up with
- A Monday brief that lists at-risk customers, why they're at risk and a drafted check-in for each.
The steps
- 01
Choose three warning signs
Pick signals you already have: late or reopened jobs, slower replies, fewer orders, a complaint, an unpaid invoice. Three good signals beat ten noisy ones.
- 02
Pull the signals weekly
Export or automate a weekly list of customers with their signals. Keep it to facts: dates, counts, amounts.
- 03
Ask for a ranked brief
Give the list to your assistant and ask for a ranked brief with a reason and a suggested next step for each customer.
Prompt Here are this week's customer signals. Rank the customers by risk of leaving. For each of the top five give: the reason in one sentence, based only on the data; a suggested next step; and a short, warm check-in message I could send. Do not guess beyond the data. [paste signals]
- 04
A person makes the call
Use the drafts as a starting point, but the outreach comes from you or the account owner. The AI prepares; people provide the care.
What breaks
- The brief flags the same healthy customers every week. Tune or drop the noisy signal.
- Sending the AI-drafted message unedited. Customers can tell.
Keep it safe
- Share only the signals the brief needs, not full email threads.
- Keep the brief inside the team; it's a judgment about people.
How you'll know it worked
- Customers lost per quarter.
- At-risk customers contacted within a week.
Do it with Hands
AI employees that work beside your team. Led by Coach.
Personal assistants, agentic staff and team augmentation, run by Coach, your AI chief of staff.
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