Churn interview template
A churn interview template covering the decision timeline, causes, attempted saves, replacement behavior, and realistic win-back potential.
Questions and setup
Customize the placeholders and apply the setup notes in the study builder before launch.
- 01
Multiple Choice
Which best describes the most recent change your organization made to its paid [Product] account?
- Canceled the account and ended paid use
- Downgraded the plan or reduced paid seats
- Kept or expanded the paid account
- I do not know or was not involved
Setup: Screen out the last two options and analyze cancellations and downgrades separately.
- 02
Multiple Choice
When was that change finalized?
- Within the past 30 days
- 31-90 days ago
- 91-180 days ago
- More than 180 days ago
- I do not remember
Setup: For the default cohort, qualify the first two options and screen out the rest.
- 03
Multiple Choice
Which best describes your involvement in the decision?
- I made the final decision
- I shared the final decision with others
- I evaluated options or made a recommendation
- I was informed but did not participate
- I was not involved or do not remember
Setup: Qualify the first three options.
- 04
AI Question
Think back to the decision to cancel or downgrade [Product]. Walk me through what happened from the first sign that a change might be needed through the final decision.
Setup: Allow up to two follow-ups to establish dates, trigger events, people involved, and what the participant personally observed.
- 05
AI Question
What factors had the greatest effect on the decision, and how did each one affect it?
Setup: Allow up to two follow-ups. Elicit factors unaided; if price appears, distinguish budget, absolute price, realized value, and competing terms.
- 06
AI Question
Before the decision became final, did anyone try to address the issue or keep using [Product]? Walk me through what was tried, if anything, and what happened.
Setup: Allow one follow-up and do not suggest support, discounts, plan changes, or workarounds before the participant does.
- 07
AI Question
What options did the team consider after the issue arose? Which of those, if any, were seriously evaluated?
Setup: Allow one follow-up to distinguish awareness, active evaluation, trial, proposal, procurement, or migration.
- 08
Multiple Choice
Which approaches are you using now for the work [Product] previously supported? Select all that apply.
- Another product in the same category
- A different kind of product
- An internal or homegrown solution
- Spreadsheets or another manual process
- We still use [Product] in a reduced way
- We no longer do this work
Setup: Enable multi-select and the built-in Other response. Do not combine “We no longer do this work” with another choice.
- 09
AI Question
Before the decision became final, was there any realistic point when staying with [Product] was still possible? What would have needed to happen at that point?
Setup: Allow one follow-up and distinguish requests made at the time from ideas invented retrospectively.
- 10
Rating Scale
Assuming your organization needed a product in this category during the next 12 months, how likely would you be to include [Product] in the options considered?
Setup: Use a 1-5 scale from Not at all likely to Extremely likely.
- 11
AI Question
What is the main reason for that likelihood rating?
Setup: Allow one neutral follow-up.
- 12
AI Question
Is there anything else about your experience that would help us understand why you left?
Setup: Allow one follow-up only when it adds a new factor or event.
This churn interview reconstructs the decision behind a cancellation or downgrade. It confirms recency and involvement, then probes the timeline, unaided decision factors, attempted saves, evaluated alternatives, and what replaced the product.
What this template measures
The template follows one recent decision from first warning sign to final outcome. It deliberately asks for decision factors before mentioning price, competitors, support, or product gaps, reducing the chance that the interview plants the explanation it later reports.
Three Multiple Choice questions establish outcome, recency, and decision involvement. A multi-select replacement question captures mixed workflows, while a conditional 12-month reconsideration rating measures realistic future consideration rather than abstract willingness to return.
Who it's for
This template is for customer success, product, and revenue teams following up with customers who canceled or downgraded in the last few months, while the details remain clear. It fits a renewal review, a churn root-cause project, or an investigation into a change in a segment's cancellation rate.
How the AI moderator probes
The AI moderator begins with the participant's own account. If price comes up, it distinguishes budget pressure, price level, realized value, and competing terms. If a competitor appears, it asks what actions showed serious evaluation. If “the team decided” appears, it establishes the participant's firsthand role before accepting the claim.
Follow-ups adapt to each participant's answer. Add interviewer notes to direct probing toward a specific concern, such as a recent pricing change or a feature you are evaluating as a churn driver. AI follow-up questions explains the behavior in more detail.
Tips before you launch
Replace the "[Product]" placeholder throughout and send the interview within 30 to 90 days of the change. Add explicit screen-out rules for account outcome, recency, and decision involvement before launch.
Consider voice mode when you want churned customers to narrate the decision aloud. If you are building the screener questions from scratch, How to write screener questions that actually screen explains how to configure effective filters.
After a batch of interviews, use theme extraction to group recurring reasons and pull supporting quotes for renewal or roadmap discussions. Replace the product and plan placeholders, and adjust the alternatives question if you already know which competitors appear most often.
Frequently asked questions
How soon after a customer cancels should you run this interview?
Aim for within 30 to 90 days of the cancellation or downgrade, while the decision is still fresh. The second screener captures timing so older decisions can be routed out.
Should churn interviews be AI-moderated or a plain survey?
Use an AI-moderated interview when answers such as "it was too expensive" need follow-up. A plain survey is sufficient when you only need to record the initial reason.
How many churned customers should you interview?
There is no fixed number. Interview recently churned customers by segment or plan until the same two or three reasons start repeating.
Can you edit the questions in this template?
Yes. Use this outline in the study builder, replace the placeholders, add the listed screen-out rules, and tune the follow-up limits to the decision complexity.
Full reference
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