Survey example: Ecommerce Shopper survey about returns process

This is an example of an AI survey about the Returns Process for Ecommerce Shoppers—see and try the example in seconds.

Building a genuinely useful Ecommerce Shopper Returns Process survey is tough: vague feedback, low completion rates, and clunky forms sap your time and insights.

At Specific, we make this radically easier with conversational AI-driven survey tools, setting the standard for modern, actionable feedback.

What is a conversational survey and why AI makes it better for ecommerce shoppers

We've all hit walls with traditional survey forms when trying to understand the returns process for ecommerce shoppers: uninspired questions, surface-level answers, and too little detail to take action. What you really need is richer context—but manually chasing it down just isn't practical.

A conversational survey flips the script. Instead of static forms, you engage shoppers in a natural back-and-forth that feels more like messaging a helpful rep than completing a chore. Automated, AI-driven conversations make it easy to ask, clarify, and dig deeper on the fly.

Let's be honest: with online return rates averaging 24.5% in 2024, nearly triple that of in-store returns, there's simply too much at stake to rely on incomplete feedback. If you're in apparel, that number can hit 40%[1][2]. Without truly understanding the "why," it's impossible to fix the broken parts of your returns process.

Why use AI for ecommerce shopper surveys?

• AI probes for detail, delivering richer insights (without extra effort from you).

• Instant survey creation frees you from tedious question-writing.

• Personalized, chat-like experience increases shopper participation.

Specific offers the smoothest user experience in conversational survey design from start to finish. Our AI survey example for returns shows how frictionless feedback gathering can be—for both you and your audience. For more about designing strong surveys in this area, check out our guide on the best questions for an ecommerce shopper survey about returns process.

Automatic follow-up questions based on previous reply

One of Specific’s superpowers is its dynamic AI follow-ups. As soon as a shopper gives you an answer, the AI asks the exact right follow-up, in real-time—digging deeper just like an expert interviewer. This saves you the headache (and delay) of endless email chains or missed context.

• Ecommerce Shopper: "I returned my shoes last week because they didn’t fit."

• AI follow-up: "Can you share a bit more about what didn’t fit—was it the sizing, width, or something else?"

• Ecommerce Shopper: "The return process was slow."

• AI follow-up: "What specific part of the returns process felt slow to you—the approval, shipping, or refund?"

If you didn't ask these follow-ups, you'd be left guessing. Too often, surveys without follow-up questions give you data that's hard to interpret or act on. Specific makes sure you get the whole context, not just a headline.

This is a totally new experience—try generating your own AI survey example and see how much more clarity you get. Or customize it for any use case from scratch, if you need.

These follow-ups are what turn a survey into a real conversation. That’s the conversational survey difference. More about how this works is in our feature deep dive on automatic AI follow-up questions.

Easy editing, like magic

Changing your survey couldn’t be simpler. Just type what you want to change in plain language, and the AI will take care of the rest. Maybe you want to add a question about why shoppers "bracket" with multiple sizes (relevant when 63% of consumers buy products in multiple sizes and return what doesn’t fit [1])—the AI suggests the best way to ask and updates your survey instantly.

No hunting through settings, no fussing with logic trees. Edits happen in seconds, so you can focus on using feedback, not managing forms. Learn more about how frustration-free editing works in our AI survey editor tour.

Sharing: landing pages and in-product delivery

Delivering your ecommerce shopper returns survey is all about matching your feedback channel to your audience and moment. Specific supports two powerful methods:

• Sharable landing page surveys: Perfect for emailing past shoppers, embedding in post-purchase emails, or sharing on social. For example, after a shopper finishes a return online, send them a dedicated link to your survey. This works for one-off campaigns or regular feedback cycles.

• In-product surveys: Seamless when you want actionable feedback right after a return experience within your own app or web portal. Trigger it the moment a shopper clicks "Return Item" to capture fresh, in-context insights into what’s working (or not) in your returns process.

Returns process insights are best captured with targeted delivery. If your shoppers mostly interact via email after a return, go landing page. If your returns flow is in-app, choose in-product for immediate, embedded feedback. Both options feel like chat, not forms—so shoppers actually respond.

AI analysis: insights without the spreadsheets

Once responses come in, AI-powered survey analysis kicks in automatically in Specific. No spreadsheets, no tedious coding—just instant summaries, topic clustering, and conversational access to all your data. You get clear explanations of what’s driving high return rates, recurring pain points, and actionable ideas for improvement, thanks to features like automated survey insights and the ability to chat directly with the AI about your results.

If you want to dive deeper into best practices, our article on how to analyze Ecommerce Shopper Returns Process survey responses with AI is an essential read.

See this returns process survey example now

Try the real AI-powered conversational survey example—see how automatic follow-ups, instant analysis, and true shopper conversations work in practice. Experience feedback collection without bottlenecks or guesswork.