Before the internet and digital advertising, direct mail solicitation was perhaps the most technologically advanced form of data driven marketing out there. Even today, as much as interactive marketers like to poke fun at traditional media people, the direct mail industry is far more sophisticated at accurate audience segmentation and message delivery than most of the digital realm. Since everything in the snail mail world works off your actual name and address, data management is far simpler and can easily connect the data points in your life – the car you drive, your credit score, your age, gender, and plenty else from public records. Start adding information about your purchase habits from catalogs, your credit cards, and all the hotel and airline loyalty cards stuck in your wallet and the direct marketers can profile you three ways to Sunday. The truth is that it’s far easier to move data offline by matching on a name and address than to move it online with nothing but a cookie. That said, data companies and marketers alike have a huge incentive to try, because offline data is generally much more reliable and therefore valuable than its online competitors.
The challenge to moving data online however is matching to a cookie, which tends to be difficult because offline and online systems work on a different paradigm. Most online companies expressly do not collect PII due to privacy concerns, meaning they think in terms of cookies instead of actual people. This presents a unique challenge for online marketers because a single device might be used by multiple people, with no way to tell who is using it at any given time. Alternatively, the offline world functions entirely on PII and can easily differentiate between multiple people in the same household: they just mail it to a different name. Add in the fact that users can delete their cookies and the benefits of offline data emerge. People can move, but they can’t delete themselves from the real world. Offline data follows them everywhere they go, so it stays reliable and person specific, making it more valuable that most online data. If only you could attribute real-world behavior to digital tracking, right? That’s exactly what the data companies thought.
Cookie Syncing Creates a Common Key
The key to transitioning offline data to a cookie is, well, a key. A database key to be exact, which allows identification of the same user in an offline database as well as a cookie database. A database key is a common field between two systems; in the online world, a cookie sync creates a foreign key relationship on the cookie ID values that allow the DMP to cross reference the same user in different data sources. The concept is the same for the offline world, but the sync is a bit more complicated, and unless the client collects personally-identifiable information (PII) from online users, the sync typically requires an outside data company to perform what’s known as a match service, usually by using an email address as the key.
For example, eBay was a prime provider of match services to data management companies until they shut down the service in March of 2011. Since eBay was a digital marketplace, they were able to cookie every user and because they had an order management system that required users to register with their real name and email address before they could buy, they knew the name and email for their cookie. So eBay could serve as its own data provider. With PII married to a cookie eBay had a tremendous asset they could monetize by syncing other people’s offline data to online cookies. They’re out of the market, but plenty of other companies have the same data – any large site with user registration pretty much qualifies. I have no idea who is a current source of match data, but I would imagine the airline booking sites, large eCommerce sites, and even banks could provide the necessary information.
How the Match Provider Connects Identity
Whatever the provider, here’s how it works:
The match service, before it has any client, contracts with a data provider and has the data provider place the match service’s pixel on one of their pages where users frequently pass so they can run a cookie sync. Users who hit that page call the provider’s cookie, which then piggybacks a call to the match service. In a server-to-server integration, the provider uploads the PII for each cookie to the match service servers, who in turn attribute to their own cookie ID. This process just continuously runs, building a larger and larger data set for the match service, which pays the data provider for this information. Now, a a client wanting to move offline data to a cookie contracts with the match service, which has the client setup a cookie sync with them. When a user hits the client’s page, the client’s cookie fires and then piggybacks a call to the match service, passing it the client cookie ID on a query string. The match service records the client’s cookie ID, and checks for an existing cookie on the user. If that user has been cookied before by the match service, the user’s identity is known, and the match service can attribute the PII from the data provider to the client’s cookie.
At the same time, the client sends the match service a file of the offline database records. Now the match service can look for users with the same PII in an offline record as they have from the data provider. When they find a match, they already know what their own cookie ID on that user is as well as the cookie ID for the client is. Over time, as more and more users call these tags, the data builds up and the match is complete. Importantly, to satisfy privacy regulations, the PII known by the match service is typically stripped off before it is sent to the client. The client can know which users were matched in aggregate, but usually cannot know which cookie ID is which user. So the match is not anonymized, but the results are. Unfortunately, the overlap between sources tends to be small, typically 30 – 40% of the total offline records on a good day. It depends how often users delete their cookies, and how often they visit the site. Match services typically contract with more than one data provider and match against the aggregate records, but even then, the results are often not ideal. Cookie deletion also makes the match process a constant one to re-sync users who erase their online identifiers.
Still, the results can be powerful – Nielsen was one of the first companies to bring their offline data online, syncing PRIZM segments to cookies as far back as 2009. Polk, Experian, and other premier offline data companies have followed and as DMPs become more commonplace among marketers with deep data sets targeting will only improve. If you are interested in match services, look into LiveRamp, DataLogix, Datran, TargusInfo, or Acxiom for more details.