You used to shop with us most weeks. What changed?
O
Lapsed Customer Research
Interviewer agent · 1.1K uses
Interviewer Agent
Why Customers Buy From Us Online but Not In Store
Your channels are not competing for customers. They are competing for occasions. A shopper who buys from you online and in store is your most valuable customer and your least understood. The channel split is not a preference, it is a set of rules tied to occasion, urgency, risk and basket. This conversation surfaces those rules so each channel can be built for what it actually wins.
Omnichannel LTV grown
Channel conflict settled with evidence
Each channel built for what it wins
Used 1,632+ 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
Recent real purchases in each channelThe occasion behind each purchaseHow urgent it was and how certain they were about the itemThe rule they apply when choosing a channelWhat each channel does better for themWhat they would have done if their preferred channel were unavailable
Questions it always asks
The core fields every response captures.
Always anchor on specific real purchases in each channel
Ask what they would have done if their preferred channel had not been available
How it adapts
Follow-ups that change based on what people say.
If they buy online for convenience, ask what would make the store trip worth it instead
If they buy in store for certainty, ask what online would need to show to remove the doubt
Where it routes people
Different paths for different answers.
Send channel-specific gaps to the team that owns that channel
Escalate genuine cannibalization evidence to commercial leadership
Automations it can trigger
Actions that fire the moment a response comes in.
Post occasion-level channel rules to #omnichannel in Slack
Update the customer record in HubSpot with their channel decision logic
Write channel preference signals back to the customer record in Shopify
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
The conversation asks the shopper about real recent purchases in both channels and works out the rule behind each choice: what the occasion was, how urgent it was, how certain they were about the item, and what would have happened if that channel had not been available. It stays neutral about which channel should win and lets the decision logic emerge from their own examples.
Getting started
- 1
Select customers with purchase history in both channels over the last year
- 2
Define the occasions that matter for your category so results are comparable
- 3
Decide what question the business is actually settling before you run it
- 4
Share the findings with both channel teams at the same time
Template Details
- Agent Type
- Interviewer
- Category
- Retail and e-commerce
- Industry
- Retail & E-commerce
- Business outcome
- Build the right product
- Job to be done
- Interview customers & users
- Journey stage
- Discovery & research
- Replaces
- 1:1 interviews
- Integrations
- Shopify, Hubspot, Slack
- Times Used
- 1,632+
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.
- Channel sales data shows where revenue landed and nothing about what the customer was choosing between. Two channels can look like they are taking share from each other when they are actually serving different occasions.
- Asking shoppers which channel they prefer produces a single answer for a behavior that is genuinely situational. Most omnichannel customers do not have a preference, they have a rule, and the rule depends on the occasion.
- Attribution models settle internal arguments with assumptions rather than evidence, which is why channel conflict tends to be resolved politically rather than factually.
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 anchors on real recent purchases in both channels from the same person, which means the comparison is within one customer's logic rather than across different populations.
- It captures the occasion, the urgency and the certainty about the item for each purchase, which are the variables that actually determine the channel choice in most categories.
- Asking what they would have done if the preferred channel had not been available is a direct test of cannibalization versus incrementality, and it is far more reliable than inferring it from transaction data.
What is omnichannel research?
It is research into how customers who use more than one of your channels decide which to use on a given occasion. It sits deliberately between channel analytics, which report outcomes, and attribution modeling, which assigns credit. Neither can explain the decision, because the decision is made against variables that do not appear in either dataset: how urgently the item is needed, how confident the shopper is about it, and what else they were already doing.
FAQ
Frequently Asked Questions
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Replace drop-off, poor qualification, and missing context with AI conversations that capture structured data and real understanding. Set up in minutes.
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