Capture customer language, goals, objections, and unmet needs for research that improves product and marketing decisions.
What were you hoping this product would help you do?
Start with the complete working structure, then adjust the language, timing, and incentive to fit your customers and brand.
Best used when
Your team has a specific decision or growth objective and needs a focused artifact to move from planning to launch.
What were you hoping this product would help you do?
open textWhy ask it: Captures the job the product was bought to do, in wording that is usually narrower and more concrete than the benefit printed on your product page. Mine the phrasing for copy, and flag any goal your product cannot actually deliver before it turns into a return.
Which feature or benefit mattered most to you?
open textWhy ask it: Tells you which single line of your product page did the selling, so everything else can be cut or moved down. When the answers name a benefit you barely mention, you have found conversion lift that costs nothing but a rewrite.
What nearly stopped you from choosing this product?
open textWhy ask it: Everyone who answers this got past the objection, which means the same objection is still stopping the shoppers who did not. Asked of buyers rather than browsers it stays specific, and it is the cheapest supply of product page and FAQ fixes you have.
What need is not fully met by the options available today?
open textWhy ask it: Points at the gap in the whole category rather than in your range, which is where new lines come from. Asked of existing customers it stays grounded in real use instead of wish lists, and a theme that repeats across dozens of answers is worth more than any single vivid one.
What is the one thing we could improve?
open textWhy ask it: Asking for one thing instead of general feedback forces a priority, so the answers arrive already ranked by what the customer cares about most. Count how often each theme repeats rather than reacting to the most articulate response, and carry the top three into the next planning cycle.
Is there anything else you would like us to know?
open textWhy ask it: The last question is where the unprompted things arrive: a packaging complaint, a size you do not stock, one support agent thanked by name. Keep it optional and last so it costs nothing in completion, and lean on AI analysis to group the themes once you pass a few hundred responses.
Generate a focused variation while keeping the expert-written version available as your baseline.
Add your goal and audience. If AI is unavailable, the complete template on this page still works as a practical starting point.
Your inputs are sent only to generate this result and are not stored by UserLoop.
Three specifics worth checking against your own store before you launch.
Start with the focused version, publish, and let the first answers steer the next iteration.
Run it as a research wave two or three times a year rather than leaving it on permanently
Sample on purpose: new buyers, repeat buyers, and lapsed customers tell three different stories
Read the AI summary first for the shape, then read fifty raw answers yourself for the language
Strong execution usually comes from removing ambiguity and keeping every action tied to the original objective.
Leading the question, so you collect agreement with your positioning instead of the customer's own words
Putting six open questions on the confirmation page, where nobody has time to type
Counting themes and never quoting the raw sentences, which is where the usable copy lives
Running one wave, presenting the deck, and never repeating it to see what moved
It is research rather than measurement. Instead of producing a score to trend, it collects written answers about goals, objections, and gaps, and its output is language and themes: the words customers use for your product, the doubts they carried, the need nobody in your category serves. Treat it as a study with a question you are trying to answer, not as a dashboard tile.
Group first, read second. AI analysis in Surveys summarizes open text and clusters the recurring themes, which turns four hundred answers into something one person can hold in their head, and it can do that per segment so new buyers and repeat buyers stay separate. Then read a sample of raw answers yourself, because the summary gives you the counts and the raw text gives you the sentence you will end up putting on the product page.
For themes, far fewer than for scores. New themes usually stop appearing well before you exhaust a few hundred answers, and once two consecutive batches surface nothing you have not already heard, the wave has done its work. If you intend to report differences between segments, size each segment on its own rather than trusting the total.
Reviews and tickets are self-selected: you hear from the delighted and the aggrieved about things that went visibly right or wrong. A voice of customer survey reaches the quiet majority and asks about things nobody writes in about unprompted, like the goal behind the purchase or the need your category ignores. Read all three, but only one of them is a sample you chose.
Collect useful customer insight with Surveys and grow your audience with Contests.
