The new age of ‘customer’ data

The martech ecosystem needs a new class of tools for data buyers and sellers that curates and leverages data both online and offline.

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The martech industry seems to be constantly on the hunt for the next big thing, and understandably so. In an industry where we said goodbye to a handful of platforms and brands in 2018 (R.I.P. LittleThings, Go90s, Rocketfuel), the next big thing may be what keeps us all not only chugging along, but successful. For my big bet, I think the smart money is on an evolution of 2018’s darling, the customer data platform (CDP).

A 2018 survey by The Relevancy Group found more than 80 percent of firms had already engaged a CDP vendor or planned to. The Interactive Advertising Bureau (IAB) and Winterberry Group estimated U.S. marketers spent close to $5 billion on data management and integration products in 2018, further evidence of the market’s continued emergence.

However, leading analysts noted that 2018’s customer-data fever was limited in scope. CDPs, like data management platforms (DMPs) and demand side platforms (DSPs) before them, have a narrow focus on a specific subgroup. For CDPs, it’s brands’ existing customers. For DMPs and DSPs, it’s prospective customers, based on online intent data gathered from cookies. All of these platforms almost exclusively cater to consumer brands. I believe that in the maturing era of Big Data, there’s evidence of a new world order.

New class of data buyers and sellers

In martech’s latest epoch, consumer brands are not the only companies that curate, store, leverage and sell data. As such, they’re also not the sole purchasers of marketing technology. Publishers are just one recent example of a newer breed of data buyers and sellers coming to the table.

This new class of data buyers and sellers, already engrained in data commerce, include publishers, platforms and agency holding companies. They bring unique data challenges that CDPs, DMPs and DSPs weren’t built to solve. This new class curates data both online and offline. It also requires the ability to leverage and sell data that covers existing customers, active prospects and potential prospects yet unknown.

All of these needs require tools that offer visibility and insights into this data in ways we haven’t seen before. Data owners need technology to organize, visualize and package data sets at incredible speed and scale to activate within the martech ecosystem.

AI activation for large data sets

CDPs were bankrolled, in part, because of their ability to unify customer data and make it accessible to other systems, specifically helping brands target customers across channels and devices. Platforms, publishers and other data owners require different means of organizing and understanding the data they collect. Rather than collecting data in order to reach those users again, data owners have data that they can monetize or activate for clients, which requires an additional layer of analytics, beyond centralization and organization, in order to activate it.

The technology that we’ve already developed for the targeting use case can also serve the monetization archetype. Though it’s traditionally been used for targeting, artificial intelligence is a general activation tool for deriving insights and driving activation from large data sets, and therefore can serve both needs.

Holistic view of data management

The demand and technology exist. The timing couldn’t be better. The amount of data we create and money we spend to manage it continue to grow. But in order for our new class to embrace yet another tech stack component, three principles, scale, speed and control, must be present in the form this new platform takes.

Scale is an indelible component of marketing solutions in order to justify cost, and even more so in the automated programmatic age. Speed is integral because the longer technology takes to build, implement and start driving results, the lower the ROI. Finally, as data owners leverage new technology and data to monetize data sets, they’ll require increased visibility into data accuracy, coverage, security and more. This level of transparency shepherds an in-depth understanding of data governance practices, a requisite of an age where calls for transparency continue to crescendo in the aftermath of data-related scandals, GDPR and new stateside regulation.

The eras of Big Data, digital and single customer view have long been culminating in this new generation of holistic data management. We’ve been waiting for the technology with the capacity and range to activate this data. Now that it’s here, why should brands have all the fun? There is a new class of data owners, including publishers, platforms and agency holding companies, that can leverage this technology to bring new, unique data sets into the marketplace, which can drive incremental value across the entire ecosystem.

Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the martech community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. The opinions they express are their own.

About the author

David Dowhan
David Dowhan is founder and CEO of TruSignal, a TransUnion company. TruSignal is expert at using offline data and predictive score marketing to fuel digital campaigns, partnering with data providers, media companies, DSPs and digital audience hubs to help power their custom, people-based lookalikes, consumer insight dashboards, and bid-price optimization strategies.

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