Marketers’ new big data problem: cross-device and cross-channel targeting

Although mobile data usage has risen 69 percent in the last year, tracking users across devices and channels continues to be among the biggest challenges for today’s marketers. Only 3 in 10 reported using cross-channel tracking to eMarketer, and 65 percent shared that they do not understand how their customers use devices differently, let alone know how to track customers across different devices while logged into the session. While cross-channel strategy creates the opportunity to utilize highly specified and relevant targeting, best practices for implementing this tactic must first be understood for advertisers to truly take advantage of its benefits.

The cross-targeting opportunity

Gartner forecasted that 4.9 billion connected devices will be in use this year — desktops, laptops, tablets, smartphones, wearables, and more — and brands have an immeasurable opportunity to reach consumers on a more engaging, personal level. For example, some of today’s most savvy marketers secure repeatable engagement by delivering tailored content at a time of day and location that’s relevant to each individual consumer.

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When it comes to cross-device and cross-channel practices, the prevailing sense is that there is an abundance of data out there to mine and harness for widespread targeting. However, most of the data today’s marketers employ for these efforts is not used optimally to deliver the best user experience and content to consumers. By failing to take relevant data and utilize it specifically for more effective and appropriate cross-device and channel targeting, many marketers are leaving money on the table.

Data confusion

While most marketers are interested in carrying over the retargeting models that have been effective on desktops to a mobile environment, not many understand how difficult it is to actually be successful with these methods without proper data.

In fact, a marketer’s ability to collect data varies from device to device, with mobile representing unique challenges never posed with desktop targeting (where a reliance on cookies is more effective). For any cross-targeting program, the most valuable — and accurate — data is first-party data, i.e., data directly from companies regarding each consumer that has logged into their applications or websites and on what devices that interaction took place. This can also include data about location, buying patterns, demographics, and more. And while this seems intuitive, many companies are hesitant to share this information with their advertising partners, hamstringing their ability to properly target similar users.

In addition, many practitioners blend this powerful first-party data with unpredictable second- and third-party data, which is information gleaned from a variety of entities that do not have direct relationships with the consumers. They want to create a larger list for their targeting efforts by combining different data sets, but without careful management, they can seriously reduce the efficacy of a campaign. The downside to this approach is that these pooled lists are often misconstrued as being more powerful, accurate, and relevant than they truly are. What’s more, accuracy rates for these lists can be misleading. First-party data is close to 100 percent accurate, as brands know exactly where it’s coming from. But third-party data may be billed as 80 or 90 percent accurate without clear definition of how the data was collected and from where. This discrepancy can make all the difference to targeting and retargeting efforts.

Crossing the chasm

There are many approaches to cross-device and cross-channel matching, including using time, location, and IP address data to narrow down devices used by the same consumer or household, but these methods are not without fault.

The best way for advertisers to maximize their cross-device and channel targeting efforts is sharing and leveraging first-party data. The more information advertisers can provide, the better vendors can classify the end users and evaluate the intersection between the data set provided and those that the vendors already have. This drives a greater degree of confidence in any vendor claims. Advertisers can be conservative about the information they share with their partners, but without this data, the chances of success drop dramatically. Another key set of information that advertisers can share is a list of users that should be omitted from the targeting exercise. For instance, if there is a subset of users already routinely completing purchases across devices, there’s little reason to target them.

The industry buzz around cross-device and cross-channel targeting is already outstripping the actual technology. Marketers who hope to successfully pursue retargeting campaigns must strive to better understand how their target customers interact across multiple platforms. They must also shift from a one-message-fits-all approach to one that’s contextually tailored to the platform in question. Further, they must recognize that as additional device platforms continue to emerge, like the Apple Watch and enterprise wearables, the practice of specialized targeting will only become more complicated.

The bottom line? Today’s marketers need to understand that while this side of advertising technology is immature and requires partnership between brand advertisers and DMPs to improve its quality and efficacy, the opportunities are lucrative for those who take cross-device or cross-channel targeting practices seriously and choose to invest in its longevity.

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Barry Coleman is the SVP of Engineering at Manage.