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How Did You Hear About Us Survey: What Buyers Say Unasked

By Daniel Derzic, founder of Adlicio · Oct 30, 2026 · 14 min read

On this page

• What we found
• What customers say when nobody gives them a list
• Should the question be required?
• How often the answer matches tracking
• What merchants say the survey showed them
• A better option list
• Where, when and how to ask
• How we got this data
• FAQ

A how did you hear about us survey asks each new customer one question, "Where did you first hear about us?", with a short list of channels (search, social, a person, a professional, a creator, an ad, a podcast) plus "Other". To see what that list should hold, we collected our own data: 28,726 brand-store reviews, 1,088 reviews of the survey apps merchants install, Reddit threads where shoppers say what they type, and every check of answers against tracking we could find.

What we found

• ✓Buyers rarely say how they found a brand: 201 statements in 28,726 store reviews.
• ✓When they do, 74 of 171 name a person or professional; only 14 name an ad.
• ✓The store matters more than the category: one store holds 10 of the 14 ad mentions.
• ✓Where a survey was required at checkout, 0 of 19 commenters say they answer honestly.
• ✓4 teams compared each answer with that person's tracking, and the two often disagreed.
• ✓14 of the 16 merchants who state a response rate say 50% or more.

What customers say when nobody gives them a list

201 statements in 28,726 reviews on 15 brand stores say how the buyer found the brand: 7.0 per 1,000. These are channels customers name unprompted, not the answer mix a survey gets and not the true channel mix. Reviews over-mention friends and professionals, and few people volunteer that an ad got them.

Supplement reviewers name a source about twice as often as skincare or pet reviewers: 114 statements in 9,965 reviews (11.4 per 1,000), against 43 in 8,847 (4.9) and 44 in 9,914 (4.4). In every category, most buyers never say how they found you unless you ask.

Which channels they name

Of the 171 statements that name a source, 74 name a person or a professional and 51 a creator, a social feed or an ad. Only 14 name an ad outright. Within those 51, Instagram is named most (21 times), ahead of YouTube (7) and TikTok (5). In their own words, buyers credit people far more often than ads. Our voice of customer statistics page has more numbers from unprompted customer text.

• ✓"The breeder sent one with our puppy and recommended them." (a pet brand's store review, 2025)
• ✓"I honestly don't remember how I stumbled upon these vitamins, but I have been hooked on them for some time." (a supplement brand's store review, 2023)

One supplement review names three touches: "I was curious about this product after seeing the Insta ads for a while and hearing [a creator] talk about it." The same buyer says a podcast finally got them to try it. A pick-one list keeps one of the three.

The store matters more than the category

Per store, the rate runs from 0.5 to 22.0 per 1,000. One store holds 10 of the 14 ad mentions, one skincare store 9 of the 26 creator mentions, and 3 supplement stores all 13 podcast mentions. Only "a person" shows up in almost every store (12 of 15). A category template will not fit your brand.

Professionals often explain the product type, not the brand. In pet, a vet or breeder recommended the type 8 times and the brand 4 times, so "my vet" can mean "my vet told me to buy this kind of product".

Next to survey figures

In a Toluna survey charted by eMarketer, 896 US adults who had bought from a D2C brand picked one answer from a list in 2019: ad on social media 34.6%, online search 24.8%, word of mouth 16.4%, ad on a news site 14.3%, out-of-home 6.5%, other 3.5%. The two ad options took 48.9%, against 14 of 171 in unprompted text. Neither is the true mix: a list invites the easy pick, and a review tells the story the buyer wants to tell.

In survey vendor Fairing's 2026 post-purchase data, reported in Total Retail, word of mouth comes first, "accounting for 19.88 percent of responses year to date". The Shopify blog says "38.3% of Americans discover new brands through word of mouth" with no source; the DataReportal brand discovery report puts word of mouth third worldwide, at "just under 3 in 10".

The Amazon check

The same phrase search found 92 statements in 2,375 Amazon reviews of 13 products: 38.7 per 1,000, or 5.5 times the brand-store rate. Longer and negative reviews do not explain the whole gap, so a rate from one source will not hold in another. To check your own products, you can read a live sample of an Amazon listing's reviews. One buyer: "Saw an ad for this during the Olympics." (melatonin gummy, 1 star)

Should the question be required?

We counted 29 Reddit commenters who described what they type or pick. In the one thread where the survey was required to reach the order confirmation page, 0 of 19 say they answer honestly, and 18 of 19 type junk or pick at random.

Most come from that one complaint thread, so read this as what shoppers say they do, not as a test of required against optional. You can search Reddit comments by keyword to read more threads like these.

• ✓"I click other and type NO. Quite expedient." (r/assholedesign, 2025)
• ✓"When I'm forced to answer a survey, I answer RANDOMLY." (r/assholedesign, 2025)
• ✓"If it's a small, locally owned business then I tell them my legit answer." (r/Anticonsumption, 2026)

A marketer on r/AskMarketing agrees: "if you have it as a required field you get lots of BS" (2025). Optional has a cost too: Recast says "when you make the field optional, nearly 30% of people do not fill out the form" (getrecast.com, 2023). We would still keep it optional, because a fake answer moves budget and a blank does not.

How often the answer matches tracking

We found 4 teams that compared each answer with that same person's tracking, and none published a per-order match rate for a DTC post-purchase survey.

Where teams checked, answer and tracking often disagreed, so treating self-reported answers as the true channel overstates them. The error runs both ways: tracking misses private sharing and AI chat, while memory credits the last or easiest option.

• ✓"People mistake YouTube ads for podcasts or just click whatever option is easiest on the screen." (r/PPC, 2026)
• ✓"in home services, "google" almost never means google ads. it means the map" (r/DigitalMarketing, 2026)

3 of the 4 teams ran B2B or lead forms, and the one ecommerce check uses older affiliate data. If you run a DTC store, compare a sample of your own orders.

What merchants say the survey showed them

In 577 relevant Shopify App Store reviews of 4 how-did-you-hear-about-us survey apps, 19 name a concrete finding and 21 describe a budget move. None of this is verified, and vendors ask happy customers for these reviews: 1,065 of the 1,088 (97.9%) are 5 stars.

The most common findings were influencers or creators (4) and TV, radio or offline (4). Only 3 of the 21 budget moves name the channel: Facebook to Google (2022), scaling an instructor channel (2023) and guiding a TV strategy (2026). Few merchants report a finding they acted on, so plan time to read your own answers.

• ✓"We identified a big youtuber who was posting about us that we otherwise would have never discovered simply bc [the app] was there asking" (KnoCommerce review, 2023)
• ✓The dissent: "We've found that information is mostly available elsewhere" (Fairing review, 2019)

Response rates merchants state

14 of the 16 say 50% or more, and none says how the rate is counted. The vendors cite the same range:

• ✓Fairing, June 2026: "post-purchase surveys average a 50% response rate" (fairing.co).
• ✓An agency review of Fairing: "40-80% response rates" (ATTN Agency).
• ✓KnoCommerce: "We see an average 45% response rate at KNO", while its own benchmark calls 20 to 30% "good" for a post-purchase survey (knocommerce.com).
• ✓Enquire Labs (now Fairing), 2020: "We get about 60% response rates" (Honest Ecommerce).

Both sides gain from a high number. Plan around KnoCommerce's 20 to 30% "good" band and treat 50% as a strong result.

A better option list

Do not size options by the review counts; a list will not get those shares. Use them to decide which options exist. On Shopify, you can group a product page's public reviews and search the results for "heard about" or "recommended" to see your own customers' words first. The list we would start from:

Where did you first hear about us?

• ✓Google or another search engine
• ✓Instagram, TikTok, YouTube or Facebook (one option each, only the ones you use)
• ✓A friend, family member or coworker
• ✓A doctor, vet, trainer or other professional
• ✓A creator or expert I follow
• ✓An ad
• ✓A podcast
• ✓Other (tell us)

Split a person from a professional where professionals matter, as they do in supplements. Keep "a creator I follow" apart from "an ad", since buyers tell those stories differently. Add "podcast" only if you sponsor or appear on podcasts.

Then add one follow-up: "Who or what recommended us?" It catches the vet behind a product type and the friend behind an "Instagram" answer. That language also works in ads, as our supplement ad hooks written the way customers talk show.

Read "Other" every month and promote repeat answers. One merchant did: "Having a few customers using "other" and typing in Reddit as the discovered channel in our survey. We added Reddit as its own checkbox" (KnoCommerce review, 2023).

Where, when and how to ask

Ask at a moment of commitment, such as the thank-you page, signup or the first sales call. Read the answers next to your analytics, not instead of them. Ask first-time buyers, or add "I've bought before" so repeat orders do not count as acquisition.

Randomize the option order and keep "Other" last. Ruler Analytics reports for one client that "47% of the leads selecting the first option in the list were inaccurately attributed" (2022, vendor). A B2B SaaS marketer: "On the signup form itself people just pick whatever option sits at the top of the list, and a day later they will type out the real podcast name." (r/B2BSaaS, 2026). Another moved a client's favorite channels off the top of a drop-down: "Once removed the main answer changed to YouTube" (r/marketing, 2024).

How we got this data

On 2026-09-23 we read the newest reviews (up to 2,000 per store) of 15 DTC stores, 5 per category, that use the same review widget, from its public data. We picked the stores for that widget and for having no tie to our clients, not at random; most are US brands, and we name none. Of 29,937 reviews, 29,744 were in English; removing 948 seeded reviews by rule ("gifted", "received free"), 69 found while reading and 1 duplicate left 28,726, dated 2021 to 2026. 5,712 of the fetched reviews carry an incentive flag, so store reviews skew positive. A phrase search pulled 696 candidates; the 628 that passed a plain rule were coded against a written code book in one AI-assisted pass, with no second coder. A review counts only if it says how the writer first found or came to try the brand. The search misses other wordings, so the rates are lower bounds.

We show counts, not percentages, because 43 and 44 statements are too few for shares. The supplement gap holds without each category's busiest store (8.8 per 1,000 in supplements, 3.3 in skincare, 3.4 in pet), and it is the only category claim this data supports.

The Amazon check covers 2,375 English, non-seeded reviews of 13 supplement, skincare and pet products we had already collected before 2026-09-24, a convenience sample, with all 224 candidates read. Sort order was not recorded, so we report a pooled rate only. Without the 14 statements that name only Amazon itself, the rate is 32.8 per 1,000. Among reviews of 250 characters or more it is still 65.8 per 1,000 on Amazon against 19.7 in the stores, and the 1 to 3 star rate (35.5) is below the 4 and 5 star rate (41.3).

The Reddit data is 3 consumer threads from 2024 to 2026, with 98 comments and posts read on 2026-09-23. Only the 29 that describe the writer's own answer count, and one commenter can count in several columns. Some answers are jokes, and these audiences dislike marketing.

For tracking, we kept every same-person comparison we found in articles and threads on 2026-09-23 and 2026-09-24. Both Reddit replies sit under threads started by one survey-tool vendor account ("In my in-product survey tool"), so we count only the independent replies and drop two similar templated posts. We left out a B2B team that says "the ratios line up with our tracking" (r/B2BSaaS, 2026), an aggregate match rather than a per-person one, and TrackRev's "62% of B2B SaaS buyers" figure, because its page gives no sample or method.

The app data is all 1,088 public Shopify App Store reviews of Fairing, KnoCommerce, Grapevine and Zigpoll, read on 2026-09-23 and dated 2017 to 2026. The relevant 577 are every text review of the first three apps plus the Zigpoll reviews about attribution or post-purchase surveys. Taking each stated response rate at its low end, the median is 50%.

FAQ

What are good options for a "how did you hear about us" question?

Search, the social platforms you use, a friend or family member, an ad and "Other" with a text box. Add a professional, a creator or a podcast where your customers name them.

What should I ask after "how did you hear about us"?

"Who or what recommended us?" Then, if you have room: what made you buy today and what almost stopped you.

How do I answer "how did you hear about us" on a job application?

Name the real source in one line: a job board, the company's site or a referral, with the person's name if someone referred you.

Before you write your option list, collect the words your customers use when nobody asks. Adlicio is one way to do that: it pulls verbatim comments and reviews from public sources such as Reddit, Amazon, YouTube, TikTok, Instagram, Trustpilot, G2 and the App Store, and groups them into pains, objections, desired outcomes and phrases for ad angles. Start with our guide to voice of customer research.