Boxever Tackles the Challenge of the Single Customer View to Personalize Across Channels
Vice President of Marketing
Boxever is a customer data platform and personalized offer engine specializing in travel. The company’s vice president of marketing, John Callan, spoke with eMarketer’s Nicole Perrin about the challenges of unifying customer data across channels—and why creating a platform to do so was a priority.
eMarketer: How has Boxever changed as a company since it was founded?
John Callan: The company was started with a very simple vision, and that was to allow marketers to take advantage of all the customer data assets at their disposal—to have personalized, omnichannel communications.
But very often, the data is not at a marketer’s disposal. It exists; it’s there within their own company’s four walls, or out there on the cloud—for example, on Google and Facebook. But it’s very, very difficult for marketers to access and take advantage of that data.
So, in attempting to address the omnichannel, one-to-one personalization problem, [Boxever’s] founders quickly realized that you need to address the data problem first. And that’s why, for the early part of the company’s history, a lot of time and effort was spent on building up what we now call our customer data platform. It’s one of the three main components of Boxever.
“What comes out of [Boxever’s] customer data platform is a single, real-time and—importantly—contextual view of every single customer.”
eMarketer: Can you explain what that platform does?
Callan: What comes out of that customer data platform is a single, real-time and—importantly—contextual view of every single customer.
We focus a lot on the context of the customer—not just understanding their historical transactional behaviors, but what’s going on right now. What are their behaviors, for example, on a website? What are they searching? What are they clicking on right now?
eMarketer: What other kinds of things do you track?
Callan: There are also more external factors. What is their status in terms of their service? In the case of an airline, are they experiencing a lost bag event, or have they crossed a geofence in an airport? Or, have they crossed a geofence in a retail environment?
That’s contextual data that adds a “secret sauce” layer to the body of information you have about a customer. And it’s only when you can capture that [data] that you can truly deliver an offer, or a message or communication that is relevant to that person at that point in time.
[Up to now, the approach that has been taken] has been very channel-centric: How do I segment my data for the purpose of email, or how do I handle tag and cookie data for the purpose of personalizing a website? How do I take anonymous third-party data from my [data management platform] DMP to deliver better ads?
We believe that way of thinking is going to go by the wayside. It’s [going to be] all about consolidating your data about your customer, deciding what should happen based on their context, and then—and only then—delivering [your] message, offer or communication to the most appropriate channel.
eMarketer: What are some of the challenges to this approach?
Callan: I think—first and foremost—it’s a really, really hard problem. A big part of the reason for that is, if you are a brand, you have data coming from three broad buckets of sources. The first is what I would think of as your system-of-record-type data. This is usually owned by an IT function. It’s usually slow-moving, transactional-type data, and it’s usually stored in arcane databases or in the systems themselves.
“We focus a lot on the context of the customer—not just understanding their historical transactional behaviors, but what’s going on right now.”
The second bucket is third-party data, which comes from the likes of Google, Facebook and Apple. The third big bucket of data is stored and managed and acted on by the channel point solutions.
eMarketer: What ends up happening in practice?
Callan: There is very little cross-talk between the channels. The marketing clouds are moving in that direction—toward allowing data to be shared from one channel solution to another. But these are three very different groups of data. They all use different systems. It’s difficult to access, and they may use different schemas for how their customer data is represented. Just at a technical level, it’s a difficult problem to solve.
There’s also the problem of how you deal with real-time data, and adding it to the profile of that individual. And [after that], how do you take action in real time?