12 Post-Purchase Survey Examples for Shopify Stores

Most post-purchase surveys fail for one reason: they ask a question the store can't act on. A 14-question feedback form right after checkout gets abandoned, and the three responses you do get tell you nothing you can change.

The fix is to start from a decision. Pick something you actually need to know, then build the shortest survey that answers it. Below are 12 post-purchase survey examples, grouped by what they're trying to learn. Each one includes the question types and branching to build it in OrderSurvey, plus why it works.

For the full strategy behind these, see the complete guide to post-purchase surveys for Shopify. This page is the practical menu.

Quick reference

#	Example	Goal	Core question type
1	How did you hear about us	Attribution	Single-select + text
2	First order vs repeat	New-customer source	Single-select with branching
3	NPS	Loyalty / referral risk	NPS (0-10)
4	Detractor recovery	Save unhappy buyers	NPS + branched long text
5	Fit and sizing	Reduce returns	Single-select
6	Reason for purchase	Messaging / positioning	Multi-select
7	Gift purchase	Capture gift intent	Single-select with branching
8	Subscription intent	Predict retention	Single-select
9	Checkout friction	Conversion debugging	CSAT + text
10	Product feedback by SKU	Roadmap input	Rating + long text
11	High-value VIP	Concierge / segment	Single-select
12	In-store (POS)	Retail experience	CSAT + text

Attribution surveys

1. How did you hear about us?

The single most valuable survey for most stores. Pixels lost a lot of accuracy after iOS 14, so asking the buyer directly is now the cleanest channel signal you have.

• Question: "How did you first hear about us?" (single-select: Instagram, TikTok, Google, friend or family, podcast, other)
• Branch: if "other," show a short text field. If "podcast," show a dropdown of which one.
• Why it works: runs on the thank-you page while intent is fresh, before the buyer forgets the touchpoint.

Full build details live in the How Did You Hear About Us playbook.

2. First order vs repeat customer

Repeat buyers skew your attribution data because they "heard about you" months ago. Split them out.

• Question 1: "Is this your first order with us?" (single-select: Yes / No)
• Branch: if "Yes," show the attribution question. If "No," skip it and ask "What brought you back?" instead.
• Why it works: you only attribute net-new customers, which is the number your ad budget actually moves.

Use customer-tag targeting if you want to skip known repeat buyers entirely.

Loyalty and satisfaction surveys

3. Standard NPS

• Question: "How likely are you to recommend us to a friend?" (NPS, 0-10)
• Follow-up: one short text field, "What's the main reason for your score?"
• Why it works: one tap, an industry-standard metric, and a trend you can watch over time. See NPS for Shopify stores for benchmarks.

Put NPS on the order status page, not the thank-you page. The customer has had a beat to absorb the purchase, and the score reflects the experience rather than the dopamine of checkout.

4. Detractor recovery flow

This is where NPS pays for itself.

• Question 1: NPS (0-10)
• Branch: if the score is 6 or below, show "What went wrong?" (long text). If 9 or 10, show "Mind leaving a review?" with a link.
• Action: set a low-score alert so any NPS at or below your threshold fires a Slack webhook. Your team replies the same day.
• Why it works: you catch the unhappy customer before they post the review, not after. Walk through the full flow in turning detractors into repeat customers.

Product and fit surveys

5. Fit and sizing

For apparel, footwear, and anything returned for fit.

• Question: "How did the fit run?" (single-select: too small, slightly small, true to size, slightly large, too large)
• Branch: if "too small" or "too large," show "Want help with an exchange?" linking to your returns flow.
• Why it works: aggregate the answers by variant and you'll see which SKUs run off-spec. That's a sizing-chart fix or a product fix, and it cuts returns. More on this in reduce returns with surveys.

Target this only at apparel collections using product targeting so it never shows on a hat or a gift card.

6. Reason for purchase

Why someone bought tells you how to sell to the next person.

• Question: "What made you buy today?" (multi-select: price, reviews, looked the best, recommended, restock, gift)
• Why it works: multi-select captures real buying behavior (people buy for several reasons at once). The winning answers become your homepage and ad copy.

10. Product feedback by SKU

• Question 1: "How happy are you with [product]?" (CSAT, 1-5 stars)
• Branch: if 1-3 stars, show "What would have made it a 5?" (long text)
• Why it works: routed by product targeting, this becomes a per-SKU feedback stream straight into your roadmap. Export to CSV and sort by product.

Intent and segmentation surveys

7. Gift purchase detection

• Question: "Is this a gift?" (single-select: Yes / No)
• Branch: if "Yes," ask "What's the occasion?" (dropdown) and skip any product-feedback questions, since the buyer isn't the user.
• Why it works: gifters are a different audience. Knowing the order is a gift changes your follow-up email and protects your product-feedback data from people who never used the item.

8. Subscription or replenishment intent

For consumables and anything with a natural reorder cycle.

• Question: "How often do you expect to reorder this?" (single-select: monthly, every few months, one-time, not sure)
• Branch: if "monthly," show "Interested in subscribing and saving?" with a link.
• Why it works: you surface subscription demand from buyers who didn't see or skipped the subscribe option at checkout.

11. High-value customer (VIP)

• Trigger: target by order total above your AOV threshold (say, orders over $250).
• Question: "What were you hoping this purchase would help with?" (single-select or short text)
• Why it works: your biggest orders deserve a tailored question and a human follow-up. Targeting by order total means only those buyers see it. See segmenting surveys by order value.

Experience surveys

9. Checkout friction

• Question: "How easy was checking out?" (CSAT, 1-5)
• Branch: if 3 or below, show "What slowed you down?" (single-select: shipping cost, payment options, account required, too slow, other)
• Why it works: runs on the thank-you page so the friction is fresh. Just keep it to two questions so you aren't the friction. See surveying without slowing checkout.

12. In-store POS feedback

If you sell in person, run a survey on Shopify POS right after the sale.

• Question 1: "How was your visit today?" (CSAT, 1-5)
• Question 2: "Anything we could do better?" (short text)
• Why it works: in-store feedback is usually a black hole. A POS survey closes it. Note that POS surveys target by location only, not order rules, because POS exposes only the order id. Full setup is in running surveys on Shopify POS.

How to run several of these at once

You don't have to pick one. OrderSurvey supports multiple concurrent surveys with priority and a default-survey fallback, so you can:

1. Run the NPS survey on the order status page for everyone.
2. Run the fit survey on the thank-you page, targeted to apparel only.
3. Run the VIP survey on orders over your threshold, set to higher priority so it wins when a buyer qualifies for two.

A few rules that keep response rates healthy:

• One survey per surface per buyer. Priority + fallback handles the overlap so nobody sees two.
• Two to three questions max. Branching lets you ask the right follow-up without padding the form for everyone.
• Match the surface to the question. Hot, in-the-moment questions go on the thank-you page; reflective ones go on the order status page. See thank-you page vs order status page.

Every example here uses only the built-in question types (NPS, CSAT, single-select, multi-select, dropdown, short and long text) and conditional branching, all built without code on Shopify's native checkout, customer-account, and POS extensions. That means no broad data-access scopes on your store.

Pick the two examples that map to a decision you're making this quarter, build them in an afternoon, and let the data come in. When you want ready-made starting points, the survey templates cover each of these. The Free plan handles up to 100 responses every 30 days, which is plenty to validate whether a survey is worth keeping.