You paid a creator to post about your product. Some sales came in afterwards. But were they from the influencer, or would they have happened anyway?
That question is what attribution answers. And the mechanics behind it are simpler than most people think.
The basic chain
Attribution connects four events into a sequence: a creator posts, someone clicks a link, that person lands on your product page, and then they buy. If you can tie those events together, you know the influencer drove the sale. If you can't, you're guessing.
The whole system depends on one thing: giving the creator a link that's different from every other link pointing to your product. Not different in where it goes — the customer still lands on the same page. Different in that it carries an identifier, a tag that says "this click came from Creator X."
When someone clicks that link, the attribution tool logs the click along with the identifier. If that same person goes on to make a purchase, the tool matches the purchase back to the click. Creator X gets credit for the sale.
That's it. That's the core of how attribution works. Everything else is implementation detail.
How the matching happens
The tricky part is connecting a click to a purchase that might happen minutes, hours, or even days later. Different tools handle this differently, but there are really only two approaches.
Device fingerprinting looks at details about the visitor's device — screen size, operating system, browser version, language settings, timezone — and creates a rough profile. If someone with matching characteristics makes a purchase within a certain window, the system assumes it's the same person. This is probabilistic. It works reasonably well at scale but can misattribute individual sales, especially on iPhones where many devices share identical configurations.
Click-to-install matching takes a more direct approach. The click is logged with a timestamp and basic device info. When the app is installed or a purchase is made, the attribution tool checks its log for a recent click that matches. Apple's App Tracking Transparency framework complicated this in 2021 by requiring user consent for cross-app tracking, but link-based attribution still works because it tracks the click on the link itself, not across apps.
Some tools — LinkOwl included — skip the probabilistic guessing entirely. They use webhook integrations with payment processors like RevenueCat. When a purchase happens, RevenueCat sends a webhook containing the transaction details. The attribution tool checks whether that customer arrived through a tracked link. If they did, the sale is attributed to the creator whose link they clicked. No fingerprinting, no probabilistic matching, just a direct connection between click and purchase.
Attribution windows
Not everyone buys immediately. Someone might click a creator's link on Monday morning, get distracted, and come back to buy on Wednesday evening. Should the creator get credit for that sale?
Most attribution tools use a window — typically 7 to 30 days. If the purchase happens within that window after the click, it's attributed to the creator. After the window closes, the sale is treated as organic.
There's no perfect window length. Too short, and you miss legitimate delayed purchases. Too long, and you start attributing sales that had nothing to do with the creator. Seven days is a reasonable default for most consumer products. Expensive items where people research for weeks might warrant a longer window.
What attribution can't tell you
Attribution tracks the last click before a purchase. It can tell you which link someone used to reach your product. What it can't tell you is the full story of why they bought.
Maybe someone saw your product mentioned by three different creators over two weeks. The first mention planted the idea. The second built familiarity. The third, whose link they finally clicked, closed the sale. Standard attribution gives all the credit to that third creator, even though the first two did real work in getting the customer there.
This is called the multi-touch problem, and honestly, for most small brands running a handful of influencer campaigns, it doesn't matter much. You're not running enough simultaneous campaigns for overlap to significantly distort your data. But it's worth knowing about so you don't over-index on the numbers.
The practical takeaway: attribution data is accurate enough to make better decisions. It tells you which creators drive purchases and which don't. That's enough to stop wasting money on the wrong people and double down on the ones who convert.
First-party vs third-party attribution
Third-party attribution tools — AppsFlyer, Adjust, Branch — sit between the advertiser and the ad networks. They use SDKs embedded in your app to track installs and post-install events, then match those back to ad clicks across various networks. These tools were built for paid advertising at scale. They're powerful, but they're expensive and complex. Monthly minimums start in the hundreds, and integration can take a developer days.
First-party attribution is simpler. You create tracked links yourself (or through a lightweight tool), hand them to creators, and match clicks to purchases using your own data. No heavy SDK, no network integrations, no monthly platform fees eating into your margins.
For brands working with influencers rather than running programmatic ads, first-party attribution is usually the better fit. You don't need to integrate with ad networks because there are no ad networks involved. You need to know which creator's link drove which purchase. A tool like LinkOwl charges per attributed sale rather than a flat monthly fee, which makes more sense when you're doing five influencer deals a month rather than running campaigns across dozens of ad networks.
Setting it up takes less time than reading this article
The actual setup process is short. Create an account with an attribution tool. Register your app or website. Create a tracked link for each creator. Hand them the links. Connect your payment processor via webhook so purchases are automatically matched.
If you're using RevenueCat for in-app purchases, the webhook integration takes about two minutes — you paste a URL into your RevenueCat dashboard and you're done. Purchases flow in automatically.
For Shopify stores, it's a similar webhook setup. When an order is placed, the attribution tool checks whether the customer arrived through a tracked link and credits the right creator.
From there, you check your dashboard when you want to see results. Which creators drove clicks. Which of those clicks converted to purchases. How much revenue each creator generated. No spreadsheets, no manual counting, no guessing.
The brands that struggle with influencer marketing aren't the ones picking bad creators. They're the ones who never set up tracking, so they have no idea which creators are good and which aren't. Fix the tracking, and the creator selection fixes itself over time.