When researching much of the digital advertising ecosystem, you’re bound to hear the phrase “match rates.”
The term seems simple at first, but did you know there’s no industry standard in calculating match rates?
This can cause a lot of confusion when comparing match rates.
For this blog, we’ll focus on defining offline-to-online matching and discuss the important questions you should ask so you can be sure you understand how your onboarder is calculating their match rates.
What is Offline-to-Online Matching?
Offline-to-online matching is the process of taking offline data and making it usable in online marketing platforms.
It starts with offline data tied to personally identifiable information (PII), such as email, name & postal address, or phone number. This type of data can sit in your CRM or an email subscription list.
The first step is to scrub the data of PII, to maintain anonymity of your customers, and replace it with some form of anonymous identifier, which is then resolved to an online identifier, such as a cookie, mobile or IDFA, or an IP address.
This is where the match rate comes into play: How many of those initial customer records were able to be matched to online identifiers?
The question seems straightforward, but each step of the process has variables that must be taken into account and can influence the end result.
Check out our infographic below to see some of the most pressing questions you should ask your onboarder to understand your match rates:
These are the some of the questions you’re going to want to ask to make sure you’re comparing apples-to-apples.
Changes in these can make match rates appear to go up, or down.
It’s important to note, however, that changes in these are neither good nor bad—they’re just about how a specific onboarder calculates their match rates.
If you want to learn more about what has made LiveRamp’s match rates go up, check out our blog post.
For more information on match rates and what you should know about them, check out our webinar featuring LiveRamp’s own match rates experts and Chris O’Hara, Global Data Strategist from Krux.