{
 "title": "Platform over-claim tracker: Meta, Google Ads and TikTok against your shop's orders",
 "url": "https://www.causalityengine.ai/free/platform-overclaim-tracker",
 "checked": "2026-11-05",
 "answer": "Meta, Google Ads and TikTok each credit a purchase to their own ad when the buyer clicked or saw it inside their own window, so one order can be claimed by all three and the claims add up to more than your shop took. The tracker sums the claims week by week against your real orders; the platforms' own rules are quoted below.",
 "why": "A customer who clicked a Meta ad on Monday, a Google Shopping ad on Wednesday and bought on Friday is one order in your shop. Meta credits it (a purchase within 7 days of a link click), Google Ads credits it (within its 30-day click window), and GA4 gives it to a channel by its own model. Nobody is lying; each platform answers only \"did this buyer touch my ad inside my window?\". Add the claims up and the same order is counted two or three times.",
 "rules": [
  {
   "platform": "Meta",
   "point": "What a purchase is credited to",
   "quote": "Actions taken off your ad, such as a purchase on your website or shop, are attributed back to your ad if they happened within a certain number of days after someone viewed or clicked on your ad. By default, we show these actions based on the attribution setting on the ad set level.",
   "source": {
    "label": "Meta Business Help Center: About Facebook's attribution system (458681590974355)",
    "url": "https://www.facebook.com/business/help/458681590974355"
   }
  },
  {
   "platform": "Meta",
   "point": "The click window",
   "quote": "Click-through: Counts events that occurred within 1-day or 7-day after a link click on your ad.",
   "source": {
    "label": "Meta Business Help Center: About attribution models and attribution settings (2198119873776795)",
    "url": "https://www.facebook.com/business/help/2198119873776795"
   }
  },
  {
   "platform": "Meta",
   "point": "The view window",
   "quote": "View-through: Counts events that occurred within 1-day after an impression of your ad.",
   "source": {
    "label": "Meta Business Help Center: About attribution models and attribution settings (2198119873776795)",
    "url": "https://www.facebook.com/business/help/2198119873776795"
   }
  },
  {
   "platform": "Google Ads",
   "point": "What a conversion window is",
   "quote": "A conversion window is the period of time after an ad interaction (such as an ad click or video view) during which a conversion, such as a purchase, is recorded in Google Ads.",
   "source": {
    "label": "Google Ads Help: About conversion windows (3123169)",
    "url": "https://support.google.com/google-ads/answer/3123169"
   }
  },
  {
   "platform": "Google Ads",
   "point": "The default click window",
   "quote": "If you don’t customize the click-through conversion window when you create a new conversion, the default window is 30 days.",
   "source": {
    "label": "Google Ads Help: About conversion windows (3123169)",
    "url": "https://support.google.com/google-ads/answer/3123169"
   }
  },
  {
   "platform": "Google Ads",
   "point": "The default view window",
   "quote": "View-through conversion window: You can select a different window for view-through conversions. This lets you choose how long to track conversions after an impression of an ad. If you don’t customize the view-through conversion window when you create a new conversion, the default window is 1 day.",
   "source": {
    "label": "Google Ads Help: About conversion windows (3123169)",
    "url": "https://support.google.com/google-ads/answer/3123169"
   }
  },
  {
   "platform": "Google Ads",
   "point": "Why two reports never agree",
   "quote": "Even when using these columns, differences may still exist due to varying attribution models, lookback windows, and how each platform processes data.",
   "source": {
    "label": "Google Ads Help: Understand your conversion tracking data (6270625)",
    "url": "https://support.google.com/google-ads/answer/6270625"
   }
  },
  {
   "platform": "GA4",
   "point": "A different model again",
   "quote": "Keep in mind that Google Analytics defaults to data-driven attribution, while Google Ads uses ad-centric models.",
   "source": {
    "label": "Google Ads Help: Understand your conversion tracking data (6270625)",
    "url": "https://support.google.com/google-ads/answer/6270625"
   }
  },
  {
   "platform": "GA4",
   "point": "One purchase per order",
   "quote": "The transaction_id parameter helps you avoid getting duplicate events for a purchase.",
   "source": {
    "label": "Google for Developers: Recommended events, purchase",
    "url": "https://developers.google.com/analytics/devguides/collection/ga4/reference/events#purchase"
   }
  }
 ],
 "quotes": [
  {
   "quote": "Facebook is showing several times more attributed revenue than Shopify shows from Facebook.",
   "who": "r/FacebookAds poster (Shopify store)",
   "where": "Reddit r/FacebookAds",
   "date": "10 Sep 2026",
   "url": "https://www.reddit.com/r/FacebookAds/comments/1wcf53j/facebook_shows_several_times_more_revenue_than/"
  },
  {
   "quote": "We’re using the native Shopify integration and the purchase events are massively overblown. Like 3x.",
   "who": "r/FacebookAds poster (Shopify store owner)",
   "where": "Reddit r/FacebookAds",
   "date": "18 Sep 2026",
   "url": "https://www.reddit.com/r/FacebookAds/comments/1wjzd59/massive_over_reporting_with_the_pixel_purchase/"
  },
  {
   "quote": "Events Manager shows 306 ATCs, 23 Checkouts and 8 Purchases for the same period. We actually had 7 real WooCommerce orders",
   "who": "r/FacebookAds poster (WooCommerce store; Ads Manager showed 1 purchase, so the same platform both over- and under-counted)",
   "where": "Reddit r/FacebookAds",
   "date": "6 Sep 2026",
   "url": "https://www.reddit.com/r/FacebookAds/comments/1w8uptg/huge_difference_between_events_manager_and_ads/"
  },
  {
   "quote": "We used to do well on Google but i have noticed its been claiming sales from meta/organic, so we have been overspending.",
   "who": "r/googleads poster (jewellery store owner)",
   "where": "Reddit r/googleads",
   "date": "5 Sep 2026",
   "url": "https://www.reddit.com/r/googleads/comments/1w7zua8/ad_rehaul_advice/"
  }
 ],
 "columns": [
  {
   "key": "week",
   "label": "Week starting (Monday)",
   "where": "One row per calendar week, Monday to Sunday. Set every platform's date range to exactly those seven days.",
   "kind": "input"
  },
  {
   "key": "meta_purchases",
   "label": "Meta purchases",
   "where": "Meta Ads Manager > Campaigns, date range the week, column Purchases, all campaigns. Write the attribution setting it shows in the notes column.",
   "kind": "input"
  },
  {
   "key": "meta_value",
   "label": "Meta purchase conversion value",
   "where": "Same report, column Purchases conversion value.",
   "kind": "input"
  },
  {
   "key": "google_conversions",
   "label": "Google Ads conversions",
   "where": "Google Ads > Campaigns, the week, column Conversions, with only your purchase action set as Primary.",
   "kind": "input"
  },
  {
   "key": "google_value",
   "label": "Google Ads conversion value",
   "where": "Same report, column Conv. value.",
   "kind": "input"
  },
  {
   "key": "tiktok_purchases",
   "label": "TikTok purchases",
   "where": "TikTok Ads Manager > Campaign, the week, the purchase conversion column you optimise on. Leave empty if you run no TikTok ads.",
   "kind": "input"
  },
  {
   "key": "tiktok_value",
   "label": "TikTok purchase value",
   "where": "Same report, its conversion value column.",
   "kind": "input"
  },
  {
   "key": "ga4_purchases",
   "label": "GA4 purchases",
   "where": "GA4 > Reports > Monetization > Ecommerce purchases (or Engagement > Events > purchase), the week, the Purchases total.",
   "kind": "input"
  },
  {
   "key": "ga4_revenue",
   "label": "GA4 purchase revenue",
   "where": "Same report, Purchase revenue. Check first whether it holds VAT: causalityengine.ai/free/ga4-revenue-vat.",
   "kind": "input"
  },
  {
   "key": "shop_orders",
   "label": "Shop orders",
   "where": "Your shop admin > Orders, the week, paid orders only; test and cancelled orders left out.",
   "kind": "input"
  },
  {
   "key": "shop_revenue",
   "label": "Shop net revenue excl. VAT",
   "where": "Your shop's sales report for the week: after discounts and returns, excl. VAT and shipping.",
   "kind": "input"
  },
  {
   "key": "claims",
   "label": "Claimed purchases (Meta + Google + TikTok)",
   "where": "Formula: the three platforms' purchases added up.",
   "kind": "formula"
  },
  {
   "key": "claim_ratio",
   "label": "Claims per shop order",
   "where": "Formula: claimed purchases ÷ shop orders. 1.00 means the claims add up to exactly your orders; 2.00 means every order is claimed twice over.",
   "kind": "formula"
  },
  {
   "key": "value_ratio",
   "label": "Claimed value per € of shop revenue",
   "where": "Formula: the three platforms' values added up ÷ shop net revenue. Only meaningful when the platforms and the shop are on the same VAT basis.",
   "kind": "formula"
  },
  {
   "key": "ga4_ratio",
   "label": "GA4 purchases per shop order",
   "where": "Formula: GA4 purchases ÷ shop orders. Far below 1.00: consent or a missing tag; above 1.00: the purchase event fires more than once.",
   "kind": "formula"
  },
  {
   "key": "trend",
   "label": "Against the previous 4 weeks",
   "where": "Formula: this week's claims per shop order minus the average of the four rows above it. A jump after nothing changed in the shop is a platform change, not more sales.",
   "kind": "formula"
  },
  {
   "key": "notes",
   "label": "Notes",
   "where": "Attribution settings, campaign launches, tracking changes, with dates.",
   "kind": "input"
  }
 ],
 "next": {
  "line": "The tracker shows that the claims overlap. It cannot say which claim is true, because every platform answers \"did the buyer touch my ad?\", not \"would they have bought without it?\". The free first finding on /start reads your GA4 Attribution paths export in your browser and shows what last click gave each channel; the read shows what each channel caused.",
  "href": "https://app.causalityengine.ai/start?utm_source=lm_overclaim_tracker&utm_medium=free_file&utm_campaign=lead_magnet",
  "price": "€99 excl. VAT, once, with a full refund within 30 days, and you keep the read."
 }
}