Usable with a quick edit11 of 12 checks passed
The only missing element is marking what to cut if the call runs over, which a PM can add in a quick edit; otherwise the plan is complete and evidence-based.
Output
Churn Interviews: Recruit Plan and Guide
What the data already tells us
- The cancel form inflates "Too expensive." It is pre-selected, so we can't tell real price objections from people clicking through. Most cancellers left it on that answer.
- Most cancellers had stopped cooking before they left. Many cooked 0–2 recipes in their last four weeks and skipped several deliveries. Their free text points to fit, not price: "kept piling up in the fridge," "too much food for two," "didn't have time to cook." The comparison stat agrees: 81% of retained subscribers cooked 3+ recipes a week in month one, versus 34% of cancellers. That's a correlation, but it suggests a fourth hypothesis none of the execs named: the kit never became a habit.
- "Delivery problems" cancellers look different. Every one of them cooked 3+ recipes in their last four weeks, and several left within weeks 2–3. These are engaged customers we lost to an ops failure.
- Free text often contradicts the selected reason. For example, "Moving / travelling" sits next to "cheaper at the supermarket."
Six calls can't tell us how many people leave for each reason; the data does that. The calls are for understanding how people decide to leave, so we give each hypothesis a fair, clean case.
Who to recruit
| # | Primary | Backup | Profile | Why |
|---|---|---|---|---|
| 1 | S-8056 | S-8096 | Pre-selected price; cooked 12 (backup 9) in last 4 wks; "cheaper at the supermarket" | CEO's hypothesis at its strongest: an engaged user who says price. Was it really competitors' discounts? |
| 2 | S-8004 | S-8183 | Pre-selected price; 5 skips, 0 cooked, no free text | What the default hides. Was price the reason or just the first option? |
| 3 | S-8005 | S-8016 | Pre-selected price; 4–5 skips, 0 cooked; "too much food for two" / "piling up" | Portion and waste: the theory none of the execs named. |
| 4 | S-8036 | S-8282 | Pre-selected price; 5 skips, 0 cooked; "didn't have time to cook" | Time and habit. When did cooking stop, and why? |
| 5 | S-8133 | S-8057 | Chose "Recipes got repetitive"; 45–53 weeks; still cooking a little | Head of Food's hypothesis: a long-tenure user who picked this reason actively. |
| 6 | S-8097 | S-8072 | Chose "Delivery problems"; cooked 8–10 in last 4 wks | Head of Ops' hypothesis: an engaged user lost to a delivery failure. |
Contact backups only if the primary doesn't respond within 48 hours. Assign the experienced interviewers to calls 1 and 2, where people most easily give a stock answer like "it was the price." New interviewers take 3–6 and shadow one call first if the schedule allows.
Interview guide (30 min)
Rules for interviewers (read before every call)
- Ask about what happened, not opinions. Prefer "Tell me about the last box you got" to "Do you think the recipes are repetitive?"
- Don't mention their cancel reason or our hypotheses until section 4. If you say "price" first, you'll hear "price."
- Don't defend, explain, or offer anything. No discounts, no "actually you can skip weeks." If they ask, note it and say someone can follow up.
- Allow silence. Count to five before your next question. The best answers come after the pause.
- Use neutral probes: "Tell me more." "What happened next?" "Can you give me an example?" "Why was that?"
- Follow their story, not the script. The script makes sure you cover everything; you don't need to ask it in order.
- Write down exact quotes, especially words they use about money, time, food, and delivery.
1. Intro (2 min)
"Thanks for making time. I'm [name] from Sprig. We're trying to understand what Sprig was like to use, including the bad parts. There are no wrong answers, and I'm not here to win you back. Is it OK if I take notes or record?"
2. Their life with Sprig (8 min)
- "Take me back to when you signed up. What was going on? What were you hoping it would do for you?"
- "Walk me through a typical week with a box. When did it arrive? Who cooked? What happened to the food?"
- "How did that change over time?"
- Probe: "When did that start?" "What was different then?"
3. The decision to leave (10 min)
- "Tell me about the last few boxes before you cancelled."
- "When did you first think about stopping? What happened that day or week?"
- "Before cancelling, did you skip any weeks? What was going on then?"
- Probe for leftovers and waste: "What happened to meals you didn't cook?"
- "What did you do instead for meals? What does that cost and take?"
- "Was there one moment that tipped it, or did it build up?"
4. Checking the reasons (6 min)
Ask these only now. - "On the cancel form you chose [reason]. Is that how you'd describe it to a friend?" - If the reason was pre-selected, say: "That option was already ticked by default. Was it your actual reason?" - Ask about each of the following, one at a time, unless they've already covered it. Get a specific example for each. - "How did the price feel by the end? Compared to what?" - "How did you feel about the recipe choices?" - "Any issues with deliveries? What happened?" - "If you could change one thing, would you have stayed? What would it be?"
5. Wrap (4 min)
- "Is there anything I should have asked but didn't?"
- Thank them and explain any incentive.
After each call (15 min, same day)
Fill in the shared sheet with: - Their main reason, in their words. - When cooking dropped off: week, and the trigger. - Supporting quotes. - Whether the form reason matched their story.
After all six calls, I'll write up how each person's decision unfolded, mapped against the four hypotheses. I'll be clear that six interviews show how people decide, not how many decide each way. The write-up will also recommend changing the cancel form so no option is pre-selected; that one change will make the form data usable.
Grades and run details
Decision model 96 · LLM judge 92
Decision model checks
- passUses the supplied evidence correctly23%
- passAddresses the actual decision53%
- passRespects explicit constraints30%
- passIdentifies material uncertainty29%
- passAvoids unsupported claims31%
- passProduces the required deliverable68%
- passDoesn't trust the default reason59%
- passRecruits from the data100%
- passDesigned to falsify61%
- passAsks what people did, not what they think76%
- passDoesn't lead the witness70%
- partialMarks what to cut if the call runs over52%
Run
- Run
- #1
- Time to output
- 49 s
- Submitted
- 5 Oct 2026