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Rescue new traders who stall before they leave

You only find out a new customer stalled when they cancel, ask for a refund or never come back. This agent lists the customers who stalled each day and names the most likely blocker. You get draft nudges for each, and every nudge offers one next step that removes the blocker.

01Yield

What one run makes.

A daily list of stalled customers and draft nudges

Each run lists the new customers who stalled before a real start or went quiet after paying. For each one you see the stall signal, the likely blocker and up to 3 draft nudges. Your AI chat drafts the nudges, and a person reads and sends each one or calls instead.

02Ingredients

What you bring.

  • Your definition of a real start, with a deadline
  • At least a month of sign-up and activity data per customer
  • Your list of the usual blockers
  • A cap on nudges per customer
  • A rule for when a person calls instead of writing

03Equipment

What the run uses.

  • Usage data from your app or platform
  • Your email or messaging tool
  • An email tool with automatic cancellation and failed-payment emails
  • Your AI chat

04Method

Seven steps you can follow yourself.

  1. 1
    Set the stall rule and test it

    Write down the deadline for a real start, such as the first core action by day 7. Also decide when a paying customer counts as gone quiet. Test this stall rule before you switch it on.

    • Run the rule on 5 customers who canceled or left last quarter. Check that it would have flagged them in time.
  2. 2
    List stalled customers every day

    Each day, list the customers who match the rule and note each one's stall signal. Decide who reviews this list.

    • A stalled customer could be a broker client stuck at the KYC check. It could be a challenge buyer who never logged in, or a course buyer who never opened lesson 1.
  3. 3
    Name the likely blocker

    List the usual blockers, then paste that list and each stalled customer's activity data into your AI chat. Ask it to name the most likely blocker and say why.

    • Your list might include a failed login or document upload, or a tool that would not connect. Others are a step they did not understand, no time or a wrong fit.
    • Tell it to use only the data you gave it.
  4. 4
    Draft up to 3 nudges

    Ask your AI chat to draft up to 3 short, friendly nudges for each customer. Each nudge offers one next step that removes the blocker.

    • If they paid and went quiet, the step is their first real use of what they bought. That could be the first lesson, the first exercise or the first login.
    • The nudges never promise results, and never use fake urgency, invented usage numbers or trade ideas.
  5. 5
    Approve, then send or call

    A person reads every nudge and sends one at a time, only on a channel the customer agreed to. Set a cap on nudges per customer.

    • Decide when a person calls instead of writing. For high-value accounts, they call, if the customer agreed to calls.
    • If the blocker guess looks wrong, keep the message short and ask one question. Then add the case to the prompt.
  6. 6
    Check your automatic emails

    If you sell subscriptions or trials, check your automatic emails for canceled trials, cancellations after paying and failed payments. Each should be live and enrolling people, though consent and filters leave some out.

    • If cancellations happen daily but an email has no recipients for 2 days or more, enrollment is broken.
    • Note any email you switched off on purpose, so nobody reports it as broken.
  7. 7
    Close each case

    Stop when the customer takes the step or the nudge cap is reached. Never send past the cap. Move anyone still stuck after the last nudge to your churn-risk list.

05Ways to run it

Follow the method yourself today, or book a call.

Yourself
Free stepsFollow the seven steps above with your own tools.
One click
Not built yetAsk for it on a call. What owners ask for gets built and tested next.
On a call
Open nowBook a call and I reply by email to set a time.
Not tested yet. The steps come from my playbook library, rewritten for trading businesses. I have not run this version yet, so this page shows no cost or result.