How Do You Measure Returns on Investment in Ad Tech?

We Can't Be Obsessed With Clicks and Ignore More Nuanced Data

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"The path to CMO redemption is grabbing hold of a data-driven ROI strategy," says DataXu's Mike Baker in a recent article. He's right. At the same time, CMOs and other corporate buyers are struggling to define return on investment in a forward-thinking way when it comes to their ad-tech investments.

Our industry has a tradition of taking a narrow view of ROI. From the outset, digital marketers often focused solely on the last click to measure ad-campaign performance. Over time, we've expanded to occasionally incorporate measures like view-through analysis and more sophisticated attribution models. But brand advertisers and their agencies continue to be obsessed with the click.

In Lotame's prior business incarnation of delivering ad campaigns for brands, advertisers and their agencies routinely began with well-defined and relevant brand metrics toward which we agreed to optimize. Within days of launching, nearly every agency threw brand measures out the window, reverting to click worship. As an industry, we've spent more than a decade trying to dig out of this hole.

I won't re-hash the well worn debate regarding ad-campaign measurement and inadequate attribution technologies and methods. Instead, I want to look at the ROI question in relation to the newer wave of ad-tech offerings, such as Data-Management Platforms (DMPs).

Based on early returns, some data-management platform buyers -- ranging from publishers to marketers to agencies to ad networks -- are maintaining the traditional bias toward a narrow view of ROI, zeroing in on the number of audience-targeted impressions. On the plus side, this approach is relatively simple to measure. It enables the customer to attribute DMP value to a specific revenue-generating or customer-acquisition activity, and offers a straightforward transactional model for purposes of pricing and billing.

However, aren't those buyers falling into the same old myopic trap? A full-featured Data Management Platform is designed to serve as the infrastructure for collecting, aggregating, organizing and activating consumer-related data. Targeting a campaign to an audience created through a DMP is one way to derive value from the platform, though it's just the tip of the proverbial iceberg.

The process of aggregating and integrating consumer data from otherwise disconnected sources -- web, mobile, CRM, analytics -- creates valuable new integrated audience data for the customer to slice and dice. When it comes to activating specific audience segments, the customer can not only target ad campaigns, but use the segment to dynamically serve on-site content or promotions, synchronize cross-platform content and marketing, and even inform customer-service interactions. DMP customers are actively engaged in most of these uses today. And those clients have successfully equated their investments with the downstream ROI that those investments are yielding.

Granted, it requires a more nuanced analysis to connect many of these core DMP functions to specific financial outputs and thereby determine ROI. But ad-tech buyers can't afford to cut corners in these assessments. In the same way that shortcuts in campaign measurement and analysis translated into persistent under-investment by brand marketers in digital advertising, defaulting to the lowest common denominator in evaluating ROI for DMPs (and similar platform-level marketing technologies) will lead those publishers and marketers to a similar and costlier under-investment in audience-based marketing.

Adam Lehman is COO and General Manager at Lotame.
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