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In-Store Experience Survey
Evaluator agent · 2.2K uses
Evaluator Agent
Why Customers Abandoned Their Cart
Your funnel chart shows the drop. This shows you the money still on the table. Most teams watch the funnel chart and guess. This conversation reaches the shopper while the decision is still fresh, gets past "too expensive" and "just browsing" to what actually stopped them, and tells you whether you lost the sale to your shipping table, your payment options, or a checkout step that quietly broke.
Checkout conversion lifted
Recoverable carts identified
Broken steps caught early
Used 2,180+ 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 primary reason they abandoned, categorized for reportingThe reason in the shopper's own wordsThe exact checkout step where they stoppedCart value and what they were trying to buyWhether shipping cost or delivery timing was a factorTechnical problems, including device, browser, and stepWhether they bought from a competitor instead, and what wonThe save offer that would have completed the orderLikelihood to return and finish the purchase
Questions it always asks
The core fields every response captures.
Always ask what was on screen at the moment they stopped
Ask what specifically would have gotten them to complete the order
How it adapts
Follow-ups that change based on what people say.
If they say the price was too high, find out whether it was the item, the shipping, the total at checkout, or a competitor being cheaper
If they mention an error or a page that would not load, ask for the device, browser, and exact step so engineering can reproduce it
Where it routes people
Different paths for different answers.
Flag recoverable carts for a same-day lifecycle email with the matching offer
Send anything that looks like a checkout bug straight to engineering with the repro details
Automations it can trigger
Actions that fire the moment a response comes in.
Alert #ecommerce in Slack when the same checkout step breaks twice in a day
Update the contact in HubSpot with the abandonment reason and the offer that would have worked
Write the abandonment reason back to the Shopify customer record
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How this AI agent works
When a shopper abandons at checkout, they get a short conversation, either on exit or by email within the day. It asks what they were buying, what was on screen when they stopped, and keeps asking past the first answer until the real objection surfaces. If anything sounds like a bug, it captures the device, browser, and step so engineering can reproduce it. Your team gets the reason behind every abandoned cart, the save offer that would have worked, and an alert when the same checkout step breaks twice.
Getting started
- 1
Add the conversation to your checkout as an exit trigger, or send it by email within 24 hours of abandonment
- 2
List the objections you already suspect so the conversation can confirm or rule each one out
- 3
Set the save offers you are willing to test: free shipping, a discount, a payment plan, an extended returns window
- 4
Route technical problems to engineering and recoverable carts to lifecycle marketing
Template Details
- Agent Type
- Evaluator
- Category
- Retail and e-commerce
- Industry
- Retail & E-commerce
- Business outcome
- Convert more leads
- Job to be done
- Collect customer feedback
- Journey stage
- Exit & churn
- Replaces
- Survey tools
- Integrations
- Shopify, Slack, Hubspot
- Times Used
- 2,180+
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 one-question exit poll returns a reason code, not a reason. When a shopper picks "price," that single box covers someone who expected free shipping over 50 dollars, someone comparing against a competitor's sale, and someone whose budget was never going to stretch. Three different fixes, one useless data point.
- Fixed options only capture what you thought to list. If the real blocker was that your size guide left them unsure about fit, or that the only payment method they use was missing, and there is no radio button for it, that reason never reaches you no matter how many responses you collect.
- Static exit surveys cannot tell a pricing objection apart from a bug. A shopper who left because the payment form silently failed picks "changed my mind," because that is the closest option, and the broken step stays broken for everyone behind them.
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 asks the follow-up a form cannot. When a shopper says "too expensive," it asks what they compared it to, and hears that the item was fine but shipping added 14 dollars at the last step. You get the specific number that broke the deal.
- Because it is open-ended, shoppers raise blockers you never had a field for. Missing payment options, unclear returns windows, and a size guide that leaves people guessing surface as themes across thousands of abandoned carts, so you fix the actual leak instead of the one you guessed at.
- The AI separates a pricing objection from a technical failure. When anything sounds like a bug, it captures the device, the browser, and the exact step, so engineering gets a reproducible report instead of a vague complaint about the site being slow.
What is a cart abandonment survey?
A cart abandonment survey is the feedback an online retailer collects from shoppers who added items to a cart and left before completing the purchase. It runs either as an exit trigger at the moment the shopper leaves checkout, or as a follow-up message within a day of abandonment while the decision is still fresh. Baymard Institute puts the documented average abandonment rate at 70.22 percent across 50 studies, which makes this the single largest pool of lost revenue most e-commerce teams have. Analytics tell you which step shoppers dropped on. A cart abandonment survey is how you learn why they dropped, and that is the part you can actually fix. This template replaces the one-question exit poll with a guided AI conversation that probes past the first answer.
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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