Information is great, that is, if you know what it means and how to use it. The same could be said about data match rates. To know if you have a good rate, you first need to understand what a match rate is and how it is calculated.
A match rate is the percentage of users from a file that an onboarder is able to find and anonymously tag with data.
Knowing the match rate for your user set is critical for understanding the size of your addressable online audience, especially as data onboarding becomes a core part of marketers’ toolboxes.
Two vendors might boast the same data match rate, but does that mean the data has the same level of accuracy and value? Maybe and maybe not.
Match rates are one of the most important ways to analyze an identity resolution vendor. However, depending on the vendor, the service they’re providing, and their partners, match rates can mean several different things.
Two types of match rates
To get a better grasp on what a match rate is, you first need to know what kind of match rate you’re seeing — and ensure it isn’t being inflated.
A company uploads a list of purchased data with email addresses attached, sending it to a vendor who then looks for people associated with the purchased data and emails. With this type, the match rate is the amount of people the vendor identifies from their ecosystem as a percentage of the total data records given to them from the onboarding company.
Here’s the formula LiveRamp uses to calculate this type of match rate:
# of unique records that matched to at least one identifier / total # of unique records
It’s important to remember that the total number of identifiers is the number of unique records matched to an identifier, so vendors shouldn’t be counting those identifiers (ex. cookies, IP addresses, device IDs, etc.) — instead, looking only at the number of records matched.
Also, make sure the record used in the equation remains consistent. For example, if you give a vendor a list of addresses (meaning the denominator is measured in households) but the match is done by names (individuals), you will have an inflated rate because multiple people can live in a household.
Another type of match rate is when you calculate data based on web traffic. In this type, vendors use identity resolution technology to match anonymous traffic to known users in a vendor’s network — also known as website visitor identification.
This match rate is the percentage of the website traffic that the vendor can actually identify. The main use case for this approach is email retargeting, and the match rates can vary greatly. Typically, the higher the match rate, the lower the accuracy.
Why you need to understand match rates
While you might rely on a vendor to deliver the matches, you need to know how those are being calculated, where they are getting their online matches, and what approach they’re using. They might boast a high match rate, but if their calculations aren’t correct, you will be disappointed in the results. The last thing you want is an inflated, incorrect match rate, so ask questions from the start to make sure you are both on the same page.
Maximizing your match rate is an important component of delivering consistent customer experiences across all channels. The best way to do that is by properly managing your data — which means asking the right questions when looking for data management tools and vendors. That’s all a part of reaching your audience with the right message, at the right time, in the right place.