{"id":5232,"date":"2024-03-25T17:57:35","date_gmt":"2024-03-25T14:57:35","guid":{"rendered":"https:\/\/trackingchef.com\/?p=5232"},"modified":"2024-10-28T19:19:32","modified_gmt":"2024-10-28T16:19:32","slug":"facebooks-event-match-quality-explained","status":"publish","type":"post","link":"https:\/\/trackingchef.com\/facebook\/facebooks-event-match-quality-explained\/","title":{"rendered":"Facebook’s Event Match Quality explained"},"content":{"rendered":"\n
Working with many clients on Facebook’s Conversion API (aka CAPI), I often receive questions about how the Event Match Quality is calculated for these events.<\/p>\n\n\n\n
To explain this, I usually take a step back to explain how I understand Facebook’s user identification mechanisms work. The attributes used in the CAPI payload<\/a> open a window into these mechanisms that I’ll try to explain.<\/p>\n\n\n\n It’s also important to note that Facebook isn’t different from other ad platforms. Their advantage (along with Google) is widespread across multiple devices. With their apps installed on and integrated into websites, the amount of data they amass is beyond what any other ad network can compete. But that’s for another post.<\/p>\n\n\n\n Let’s dive in.<\/p>\n\n\n\n To fully understand how Facebook’s user matching works, we need to go back to Statistics 101 (or later, I don’t remember) and talk about two marching models – Deterministic and Probabilistic.<\/p>\n\n\n\n Deterministic matching is relatively simple – we have complete certainty of the user’s identity, so Facebook can easily attribute the ad view and conversion to a specific user. In the good old days, pre-iOS 14.5, Facebook had your iPhone’s IDFA paired with your Facebook account. This made it possible for them to attribute every single ad watched with a product purchased.<\/p>\n\n\n\n Probabilistic matching is slightly more complex. In a nutshell, it means making an educated guess based on statistical modeling that an anonymous visitor is a certain identified user. Facebook, or any other platform, collects multiple data points about the user’s activity to help feed the model when a new unidentified user is first seen.<\/p>\n\n\n\n Since the value below offers the best method of identification, Facebook will prioritize using these over anonymous data. Let’s break down these attributes:<\/p>\n\n\n\n When setting up the CAPI on Facebook, you can add multiple fields to the events sent, that can hold various user data.<\/p>\n\n\n\n These fields include:<\/p>\n\n\n\n These fields can help match the user to a specific Facebook user. For example, if you run an ecommerce business that offers phone transactions, you can report these as offline conversions back to Facebook with these attributes. Facebook will then look for that user in their database and attribute the ad activity accordingly.<\/p>\n\n\n\n In practice, only email and phone numbers are valid deterministic identifiers – only one person in the world owns a specific email address\/phone number, but many can share the same name.<\/p>\n\n\n\n Because of this, personal information is also used for probabilistic matching. For example, if you run a B2B business and want to trigger a down funnel conversion event back to Facebook Ads, you might use this type of user data.<\/p>\n\n\n\n Since the user data you have is most likely their work email and phone, it might not be matched with a specific user in Facebook’s database. However, the user’s full name, gender, and country might give a good enough estimate for Facebook to zero in on a specific user.<\/p>\n\n\n\n Another mechanism that Facebook uses is the Click ID (similar to Google’s solution). This ID is passed as a URL parameter that is appended to every outbound link from Facebook’s feed.<\/p>\n\n\n\n You can see that any link you click will be decorated in this manner:<\/p>\n\n\n\n<\/figure>\n\n\n\n
The basics – Types of user matching<\/h2>\n\n\n\n
Deterministic user attributes<\/h2>\n\n\n\n
Personal information<\/h3>\n\n\n\n
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Click ID<\/h3>\n\n\n\n