You use both shops. What decided this trip?
M
Competitor Store Research
Interviewer agent · 1.6K uses
Interviewer Agent
Why Customers Stopped Shopping With Us
Most of your win-back list is unreachable. This tells you which part is not. Sales are down at specific stores and nobody can say whether those shoppers are gone for good or simply drifted. This conversation reaches them, reconstructs the habit they used to have, finds what broke it, and separates the ones a service fix could bring back from the ones who moved away or aged out of the category.
Winnable customers identified
Win-back waste cut
The real lapse reason, per shopper
Used 1,128+ times
What's inside this template
Start from this conversation and adapt it to your team — change any question, add your own logic, and connect the tools you already use.
Information it collects
The habit they used to have: frequency, basket, occasionWhen the habit stopped and whether it was sudden or gradualThe specific reason or incident behind the lapseWhere they shop for that category nowWhat that alternative does betterConcrete conditions that would bring them backA winnable or structural verdict with the evidence behind it
Questions it always asks
The core fields every response captures.
Always ask what the habit looked like before it stopped, not just why it stopped
Ask what concretely would have to change for them to shop with you again
How it adapts
Follow-ups that change based on what people say.
If they say they moved away or the store closed, mark it structural and stop probing for a fix
If they name a specific bad experience, get the date, the location, and what happened next
Where it routes people
Different paths for different answers.
Send winnable shoppers to lifecycle marketing with the reason and the trigger attached
Flag repeated service failures at the same location to that store's manager
Automations it can trigger
Actions that fire the moment a response comes in.
Alert #retail-insights in Slack when the same store is named three times in a week
Update the contact in HubSpot with the lapse reason and the winnable verdict
Suppress structurally lost shoppers from future win-back sends
SOC 2 Type II and ISO 27001:2022 certified. Responses are encrypted in transit and at rest, and you own your data. View our Trust Center.
How this AI agent works
Lapsed shoppers get a short conversation that starts with the habit they used to have: how often they came, what they bought, why they went. It then finds the moment or the drift that ended it, probes what replaced you, and tests what would genuinely have to change for them to return. Your team gets a per-shopper winnable or structural verdict with the evidence behind it, so the win-back list is short and real.
Getting started
- 1
Pull the lapsed segment from your CRM or loyalty platform, typically no purchase in 6 to 12 months
- 2
Define what a realistic win-back offer looks like so the conversation can test it honestly
- 3
Set the rule that separates a fixable reason from a structural one
- 4
Send the link by email or SMS and route the winnable names to lifecycle marketing
Template Details
- Agent Type
- Interviewer
- Category
- Retail and e-commerce
- Industry
- Retail & E-commerce
- Business outcome
- Reduce churn
- Job to be done
- Interview customers & users
- Journey stage
- Retention
- Replaces
- 1:1 interviews
- Integrations
- Hubspot, Slack, Email
- Times Used
- 1,128+
Forms collect fields. Conversations capture context.
Static forms force complex situations into rigid dropdowns. Perspective captures structured data and the reasoning behind it — so your team makes better decisions, faster.
The static form
yoursite.com/intake
Category *
Select...
Details
Describe your situation...
Submit
Result:Category: "Other"|Details: "It's complicated"
No context. No follow-up. No next step.
- A lapsed segment is a date filter, not an explanation. It tells you someone has not bought in nine months and nothing about whether they moved house, had a bad experience, or simply found somewhere more convenient. Those three need completely different responses and the segment treats them identically.
- A win-back survey reaches the people who still feel warm enough to answer, which is exactly the group least likely to need winning back. The ones who left angry or quietly do not fill in forms, so the data you get systematically misses the customers the campaign exists for.
- Fixed-choice exit surveys offer reasons you already thought of. If the real cause was that the one product they came for got discontinued, or that the staff who knew them left, and neither is on the list, it never reaches you no matter how many responses you collect.
The AI conversation
"Tell me more about the timeline — when did this start, and is there a deadline your team is working against?"
Extracted & structured automatically
Category
High-priority
Urgency
Deadline: 2 weeks
Sentiment
Frustrated but hopeful
Next step
Route to senior team
Triggered: Slack alert sent| CRM updated
Right team. Full context. Instant action.
- The conversation starts with the habit rather than the lapse, so you learn what the relationship actually was before you ask what ended it. That context is what makes the reason interpretable: someone who came weekly for one category is a different loss from someone who came twice a year.
- Because it is open, shoppers name causes you never had a field for. Discontinued lines, a refit that changed the layout, a favorite member of staff leaving, and a competitor opening all surface as themes across thousands of lapsed customers rather than disappearing into other.
- Every conversation ends with a verdict: is this person realistically winnable, and if so what would it take. That judgment is made against the evidence in their own answers, not a propensity model, so marketing gets a short list it can actually believe.
What is lapsed customer research?
Lapsed customer research is the practice of going back to people who used to buy from you regularly and no longer do, to find out what changed. It sits between churn analytics, which tell you that someone stopped, and win-back marketing, which tries to restart them without knowing why they left. Most retailers skip it entirely and go straight from the lapsed segment to the discount email, which is why win-back response rates are usually poor. This template replaces that guess with a short conversation that reconstructs the old habit, finds the cause of the lapse, and judges whether a return is realistic.
FAQ
Frequently Asked Questions
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