> ## Documentation Index > Fetch the complete documentation index at: https://docs.datalyr.com/llms.txt > Use this file to discover all available pages before exploring further. # Attribution > How campaign context reaches a conversion, and what breaks the chain. Attribution links a conversion back to the click that produced it. This page names every value we capture, and every stage where you can lose one. ## The chain ```text theme={null} ad click → landing page captures the click ID → identity persists → conversion carries it ``` Every stage writes to first-party storage on your own domain. Nothing here is reconstructed later, so protect the capture stage first: a click ID the landing page never saw can't be recovered. ## What the tracking script captures ### Click IDs | Parameter | Source it maps to | | --------------------------- | ----------------- | | `fbclid` | facebook | | `gclid`, `gbraid`, `wbraid` | google | | `ttclid` | tiktok | | `msclkid` | bing | | `twclid` | twitter | | `li_fat_id` | linkedin | | `sclid` | snapchat | | `dclid` | doubleclick | | `epik` | pinterest | | `rdt_cid` | reddit | | `obclid` | outbrain | | `irclid` | impact | | `ko_click_id` | klaviyo | Two platforms use a different name on the landing URL. The script normalizes both. | Real landing parameter | Stored as | | ---------------------- | --------- | | `ScCid` or `sccid` | `sclid` | | `irclickid` | `irclid` | On the web, pass `oppref`, the OpenAI Ads click ID, as an event property. The iOS and React Native SDKs read it from the landing URL for you. ### Campaign parameters The script captures `utm_source`, `utm_medium`, `utm_campaign`, `utm_term`, and `utm_content`. It also captures `lyr`, `ref`, `source`, `campaign`, `medium`, and `gad_source`. ### Ad cookies The script reads and writes `_fbp`, `_fbc`, `_gcl_aw`, `_gcl_dc`, `_gcl_gb`, `_gcl_ha`, `_gac`, `_ttp`, `_ttc`, and `_scid`. These are marketing-scoped. After a marketing denial, the script neither writes nor sends them. It keeps `utm_*` and the Google Analytics cookies, which are analytics-scoped. The browser attribution window is 90 days. ## How a conversion finds its click Datalyr searches in this order and stops at the first hit. | Order | Where it looks | | ----- | ---------------------------------------------------------------------- | | 1 | The conversion event's own click ID field | | 2 | The click ID column on the event's attribution row | | 3 | Earlier events in the same `session_id` | | 4 | Earlier events with the same `distinct id`, inside the platform window | | 5 | Every visitor linked to the same `user_id` | Step 5 is what carries a web click through to a server-side purchase. It works only after your code calls `identify()` on both the browser and the server with the same ID. That one call is usually the difference between a purchase that credits a campaign and one that reads `direct`. | Platform | Window used for steps 3 to 5 | | -------- | ---------------------------- | | Google | 90 days | | Snapchat | 28 days | | Meta | 7 days | | TikTok | 7 days | | OpenAI | 7 days | The default model is first click. A rule can select last click instead. A same-session match always wins over both. ## Verify one journey 1. Open your site in a private window, with `?utm_source=doctest&utm_campaign=doctest` appended. 2. Open **Live**. Confirm the visit appears within 30 seconds. 3. Complete a sign-up so your code calls `identify()`. 4. Open **Users**. Find the user. Confirm the touchpoint reads `doctest`. 5. Complete a purchase. 6. Open **Conversions**. Confirm the row's `attribution_type` is not `none`. ## When it does not work | Symptom | Cause | Check | Fix | | ----------------------------------------------------- | ------------------------------------------------------- | ---------------------------------------- | -------------------------------------------------------- | | The visit has no campaign | The landing URL lost its parameters | The URL after every redirect | Keep the query string through each redirect hop | | Click ID present on the visit, absent on the purchase | The purchase came from a webhook with no linked visitor | The `user_id` on both rows in **Events** | Call `identify()` with the same ID on browser and server | | `attribution_type: none` on every mobile conversion | The app never carried a click ID | The app event payload in **Events** | Set up deep links so the click ID reaches the app | | Snapchat conversions carry no click ID | The landing page dropped `ScCid` | The landing URL of a real Snap ad | Stop stripping unknown query parameters | | OpenAI conversions carry no click ID | The web event carries no `oppref` | The event payload in **Events** | Pass `oppref` as an event property | | Attribution stops after a consent banner | The visitor denied marketing consent | `consent.marketing` on the event | Nothing. This is the correct behavior | | Datalyr and the ad platform disagree | Different windows, models, and timezones | The six rows below | Align each one before comparing | ## Before you compare totals Align all six of these. Any one of them alone explains a large gap. | Setting | Why it matters | | ---------------------------- | ----------------------------------------------------------------------------------- | | Date range and timezone | Datalyr reports in the workspace timezone | | Conversion definition | One rule's trigger event against the platform's action | | Gross against net revenue | Superwall and RevenueCat report different bases | | Currency | Non-USD values are summed at face value, so compare a single currency on both sides | | Attribution window and model | Google looks back 90 days, Meta 7 | | View-through inclusion | Meta counts 1-day view. Datalyr counts clicks | ## Next * [Conversion delivery](/advanced/conversion-delivery): how the resolved click ID reaches the ad platform. * [Conversions](/product/conversions): read `attribution_type` on one delivery row. * [Integrations](/integrations/index): connect the platform whose clicks you want to match.