In this first of Every Market Media’s short guides on translating technical data processes to real-world marketing applications, Rick Holmes unpacks the technical nugget of matching B2B data to B2C data.
Because sometimes you need technical answers to the tactical questions you have about doing better marketing and making more sales. But sometimes—because of the nature of how the marketplace has evolved, which is constantly—the solutions to marketing-based problems require marketers to do some hard thinking.
By which we mean to say, not everything is easy to access or explain. Such as the focus of today’s technical session.
Why would a marketer care about matching B2B data to B2C data?
Rick Holmes explains how Every Market Media’s attention got pulled toward the idea of B2B data and B2C data matching. It originally started when a client needed an application to onboard more B2B data in the various ecosystems for clients. (This application turned into an awesome product called Linkkey.)
For example, say you’re a marketer who wants to pair B2C data with an ISP-type email, someone’s B2B persona—but you run into a problem.
Here’s the challenge (and the reason you’d want a unified person approach): “The first thing that was interesting to Every Market Media clients was to take a B2B email and onboard it through a LiveRamp or a Neustar and push it out to various digital ecosystems,” Holmes said. “Only, the challenge was they found B2B emails were not as commonly used as registration information on the web.”
Because mostly nobody logs into social media with a work email. Womp womp.
Cookies or hashed emails are also not usually tied back to a person’s “B2B” persona, which means when you try to onboard your average B2B list, the match rate is “undesirable.” In other words, awful.
At this point, if you’re a B2B company without a B2C resource, you’re asking yourself, “How can we get more B2C data on here?” You could look for B2C marketing databases, but be warned. A B2C email marketer makes a lot of changes to their database that a digital marketer might not care to make.
Different Data, Different Goals
Another reason you’d want a unified person graph is to produce online identities for B2B folks at greater scale.
A short explanation is that when we build a database for email marketing, it’s not necessarily the ideal database for display marketing.
Here’s why. B2C email marketers try to build a database that has compliant and fully consented email addresses in it. Most of us also keep extra data like IP addresses, time and date stamps, URLs of purchases, and other pieces of information like that. This helps us to craft email campaigns for clients and explain where our data came from.
But digital marketers play by a different set of rules. To them, the concern of IP address cleanliness or of deliverability is just not there. Some email verification services will remove records of a list that digital marketers don’t want to have removed.
This is the main point—that there are degrees of connection in matching B2B data to B2C data.
“The first thing everyone thinks about in B2B to B2C matching is individual matching only,” Holmes said. “But there are several gradients to the idea of ‘best match.’”
B2B, Meet B2C
When ABM (activity-based management) became popular, everyone suddenly got interested in targeting on a company level. Instead of wanting individual matches, they considered company matches to be a win.
“On the high end is an email marketer who needs an individual match that comes from deliverable, safety checked, opt-out processed, do-not-mail processed data,” Holmes said. “On the low end is companies that build graphs with data points that are anonymous. Either way, you end up needing a range that pretty much runs through individual level match down through an address level match.”
The range of match degrees is threefold, in descending levels of confidence in the match.
- Household or Office/Workplace
There are a few other fine points within an individual level match, generally based with name and geography logic of some type. Households are usually last name and a bunch of logic types. And address matches are where a lot of logic stops.
Having all of these ranges makes the data suitable across multiple applications. Essentially, you can jump from matching B2B data to B2C data and back again.
The Bottom Line
Whether you’re a B2B or B2C marketer, you’re looking for the other side of the equation because you want to do more email marketing or display marketing to that segment in order to generate more sales, impressions, prospects, whatever.
When that connection happens on an individual level, you can contact online or offline with high confidence. If you start to roll the quality back a little bit, you can count it a success when you display to the household or company. This allows an even looser match and even more scale.
“So you give one B2B record and you’re almost getting back two new matches,” Holmes said. The address is waiting all the way back there for you, too—useful if you want to build a graph or match organization level characteristics.
Matching B2B data to B2C data can help you contact groups of individuals, households or workplaces, or addresses at individual or household level.
Every Market Media knows we aren’t the first people to build people graphs for marketers, but we think we’re the first to build it affordably without any crazy proprietary data sets. That said, we’d love to hear your take on building people graphs!
Sneak preview—our next technical session is a full podcast about reverse IP lookups!
If you’ve got questions, fill out our contact form on our webpage. Or message Rick Holmes at LinkedIn, or email him at email@example.com.