This article will guide you on how to create an ecommerce shopper survey about the returns process. With Specific, you can build a powerful, conversational survey in seconds—just generate and start gathering rich feedback, effortlessly.
Steps to create a survey for ecommerce shoppers about returns process
If you want to save time, just click this link to generate a survey with Specific. The whole process is incredibly simple:
Tell what survey you want.
Done.
You honestly don’t even need to read further if you’re looking for speed. The AI brings expert knowledge to craft the right questions instantly, and it will even ask respondents smart follow-ups to extract valuable insights—no manual setup or tweaking required. Prefer to start from scratch? Just head to the AI survey generator and prompt it with what you need for any audience or topic.
Why returns process surveys for ecommerce shoppers matter
If you’re not running returns process surveys, you’re probably missing out on crucial insights that shape both your customer experience and bottom line. Returns play a surprisingly massive role in ecommerce, affecting loyalty and revenue far more than most realize.
In 2024, eCommerce return rates averaged 24.5%, with consumers returning $362 billion in merchandise from online sales—that’s a staggering volume of customers, each with their own reasons and frustrations. [1]
During the 2023 holiday season, return rates spiked by 5.66%, highlighting how dynamic and costly the process can be if not managed well. [1]
But here’s what separates winning brands: 76% of first-time customers who had a smooth return experience would shop with that retailer again. [2] That means your return process is more than a problem to “fix”—it’s a massive opportunity to create loyalty.
The benefits of ecommerce shopper feedback on returns are clear:
Spot friction points that drive lost revenue
Uncover trends (like why clothing returns are sky-high—as much as 40% for apparel [3]) and how to address them
Surface hidden causes (like unclear policies, sizing doubts, or “bracketing” behaviors—63% of shoppers now buy multiple sizes and return what doesn’t fit [1])
Boost satisfaction and repeat purchase rates
Importance of ecommerce shopper recognition survey work is skyrocketing. If you aren’t capturing granular, context-rich feedback here, you’re leaving valuable insights (and profits) on the table.
What makes a good survey on returns process?
A good returns process survey does two things: collects wide-ranging, high-quality responses—and makes respondents feel heard. That means:
Clear, unbiased questions that never lead or confuse
Conversational tone to encourage honest, thoughtful responses (no intimidating “test” vibe)
Asks about real customer experiences with the ecommerce returns process, not just “Did you like it?”
The true measure? Both quantity and quality of responses. If your survey feels robotic or too rigid, people bail—or just click through. But if it’s friendly and chat-like, you get deeper, more actionable feedback.
Bad practice | Good practice |
Confusing jargon | Use simple, everyday language |
Only closed questions | Mix open and multiple-choice |
No space for details | Encourage sharing “why” and stories |
Long walls of text | Conversational brevity and clarity |
Pay attention to response rates and comment richness—that’s how you know your ecommerce shopper survey is working.
Question types and examples for ecommerce shopper surveys about returns process
Great surveys use a blend of question types to capture both “what” and “why” behind user actions. For more inspiration and tips, check out our article on best questions for ecommerce shopper survey about returns process.
Open-ended questions let people tell their story in their own words—great for uncovering motivations, frustrations, or unexpected pain points. Use these at key moments to let shoppers elaborate:
In your own words, what made you decide to return your recent purchase?
What would have made the returns process easier for you?
Single-select multiple-choice questions are fast and provide structure, revealing trends at a glance. Perfect for basics—then follow up for detail.
What was the main reason you returned your item?
Sizing/fit issues
Item was not as described
Damaged or defective product
Changed my mind
NPS (Net Promoter Score) question works well for benchmarking customer loyalty after a return. If you want a ready-to-use NPS survey for ecommerce shoppers about returns, generate a custom survey here.
How likely are you to recommend our store to a friend or colleague, based on your recent returns experience? (0 = Not likely, 10 = Extremely likely)
Followup questions to uncover "the why": Always a good practice after getting a basic answer—this is where you dig for context that unlocks solutions. Ask when responses are vague, inconsistent, or need clarification. For example:
You mentioned “the returns process was slow.” What aspects made it feel slow to you?
Can you describe a specific moment in the process that frustrated you?
If you want to dive even deeper, explore effective follow-up question strategies here and see more real-world examples.
What is a conversational survey?
Unlike stiff, form-based surveys, a conversational survey feels like a real chat. Each question flows naturally, responses get instant feedback, and follow-ups are tailored based on input. With Specific’s AI survey generator, you create these surveys in seconds—not hours—by describing what you want. The AI handles structure, language, and tone.
Manual survey | AI-generated survey |
Manually write each question, review for bias/error, build logic for follow-ups, format & test | AI drafts expert-level questions, adapts tone, writes smart follow-ups, and is ready to go immediately |
Lots of tedious copy/pasting | Conversational, customizable in real time via chat |
Why use AI for ecommerce shopper surveys? An AI survey example isn’t just easier to make; it’s more effective. AI adapts questions on the fly, making every respondent feel understood. That’s how you get richer feedback—without guesswork or wasted time.
If you ever want to tweak your survey questions further, the AI survey editor makes it as simple as describing your changes in chat.
Specific delivers the best-in-class user experience for these conversational surveys. For both creators and shoppers, it feels more like a helpful dialogue than a cold data grab. If you’re new to building these surveys and want a detailed walk-through, see our guide on how to create great surveys and analyze responses.
The power of follow-up questions
Many forget that the first answer is rarely the whole story. Automated follow-up questions transform a simple “rate us” survey into a goldmine of context. Specific’s AI follows up naturally, in real time, based on someone’s previous response and the unique context, just as an expert interviewer would. No more chasing unclear responses over email—the survey digs deeper, gathering full stories instantly.
Ecommerce Shopper: “I returned my shoes because they didn’t fit.”
AI follow-up: “Was it a sizing issue, or something about the fit/comfort specifically?”
How many followups to ask? Usually, two or three follow-up questions dig out the full context, but you don’t want to overdo it or make things feel repetitive. Specific lets you control how many you want and can skip to the next question once you’ve got your key info.
This makes it a conversational survey: dynamic, adaptive, and never boring. Respondents stay engaged, and you get data that actually helps you act.
AI survey analysis, qualitative data analysis, conversational survey insights: AI makes synthesizing all those nuanced, unstructured responses easy. Curious how to turn all that text into insights? Check out our guide on how to analyze responses using AI.
These automated followup questions are still new for many—try generating a survey and see what real conversation (and real insight) looks like.
See this returns process survey example now
Ready to see what a conversational, AI-built returns process survey can do? Take action now—create your own survey and discover how easy it is to unlock deeply useful feedback from ecommerce shoppers.