How Did You Hear About Us? The One-Field Checkout Trick That Reveals Your Real Traffic Sources

You post on four or five platforms a week, you drop your link everywhere someone might click it, and then a sale comes in — and you have no real idea which one of those platforms actually produced it. Was it the TikTok that got 40,000 views, or the tweet that got 12 likes but landed in front of exactly the right person? Was it a friend's story repost, a Google search, or that podcast you guested on three months ago that you'd honestly forgotten about? Most creators answer this question with a shrug and a guess, because the honest tools for answering it — UTM links, tracking pixels, multi-platform analytics dashboards — feel like a part-time job nobody signed up for. There's a simpler way, and it doesn't involve a single link tag: you just ask.

Why analytics alone don't answer 'where did this sale come from'

Traffic analytics are genuinely useful — Google Analytics on a Pro plan will tell you how many people visited your storefront and roughly which platform sent them. But visits aren't sales, and referral data breaks down constantly in exactly the situations creators care about most. Someone screenshots your product and texts it to a friend — no referral data. Someone hears you mention your store on a podcast, forgets the link, and just types storename into Google later that night — shows up as "direct" or "search," tells you nothing about the podcast. Someone sees your link in a group chat, in a Notes app, in a bio they saved three weeks ago — every one of these real, valuable paths to a sale looks identical to analytics: a visit with no story attached.

This is the gap self-reported attribution fills. It's not a replacement for analytics — it's the layer analytics structurally cannot see, because it depends on what actually happened in someone's head and their group chat, not what a tracking script logged. And the tool to collect it is already sitting inside your checkout, waiting to be turned on.

The one-field trick: adding 'How did you hear about us?'

store.fan lets you add custom checkout fields to any product — a text box or a short dropdown that appears right before payment. Most creators use this for order-specific details: a shirt size, a Discord username, a shipping note. But the same feature doubles as the cheapest attribution tool you'll ever set up. Add one optional field, labeled plainly, and let every buyer self-report in the ten seconds before they pay.

1. 1Open the product you want to track and find the custom fields section
2. 2Add a new field labeled exactly "How did you hear about us? (optional)"
3. 3Set it as a short-answer text field, or a dropdown with your top 5-6 channels plus "Other"
4. 4Mark it optional — never required — so it never blocks a sale
5. 5Publish, then check responses weekly once orders start coming in
6. 6After a month, tally the answers and compare against what your analytics told you separately

What the answers actually tell you

Once you have even 15-20 responses, patterns start to separate themselves from noise. The channel with the most views in your analytics is often not the channel showing up most in these answers — and that gap is the entire point. A platform can generate huge reach and near-zero self-reported sales, while a smaller, slower-growing channel quietly punches way above its size because the audience trusts you more there, or the content format naturally leads to a purchase decision rather than a scroll-past.

This is exactly the kind of finding that changes what you post next, not just how you feel about it. If half your answers say "YouTube video" and you've been treating YouTube as a side project compared to your daily Reels, that's a direct, low-cost signal to shift effort — no ad spend, no A/B test, just paying attention to what buyers volunteered for free.

Keep the field light, or it becomes friction

The entire value of this trick depends on it costing the buyer almost nothing. An optional field that takes three seconds is invisible to someone who already decided to buy; a required field, a long dropdown, or a field that reads like a survey will quietly tax your conversion rate to get data you could have collected for free. Treat this the same way you'd treat any other step in your checkout — every field earns its place, or it gets cut.

Analytics tells you what happened. A checkout field tells you why. Most creators only ever get the first half.— store.fan team

Turning answers into a habit, not a one-time experiment

Run this for a full month before drawing conclusions — a week of data is usually too small a sample, especially if you launch a product mid-week or post inconsistently. Once you've got a real batch of answers, pull them into a simple note or spreadsheet and count them by category: platform, word-of-mouth, search, other. Compare that tally against your own gut feeling from a month ago, and against your analytics dashboard if you're on a Pro plan with Google Analytics connected. The gap between what you assumed and what buyers actually said is usually where the real insight lives.

This also pairs naturally with your broader customer list and any campaign emails you send — knowing that a chunk of your buyers arrived through word-of-mouth, for example, is a strong signal to add a referral-style nudge to your next broadcast, since you already know that channel converts even though no pixel ever recorded it. If you want to see how a clean, low-friction checkout with a single well-placed custom field actually looks in practice, a live example store is worth a scroll before you build your own.

None of this works, though, if you don't have a real storefront collecting real orders yet. The field is only useful once buyers are actually reaching a checkout to answer it — which means the actual first step, if you're still deciding, is simply to create your store and get a product live so the data can start rolling in.

You don't need a marketing degree or a stack of new tools to figure out what's actually working — you need one honest question, asked at the exact moment a buyer is already paying attention. Add the field, let a month of orders roll in, and read what your customers tell you for free. It's the cheapest, highest-signal research you'll do all year, and it starts with a single field inside the checkout you already have.