December 12th, 2017

Why Every CMO Should Care About Their DMP

*This article was originally published on Forbes.com on November 15, 2017.

 

It’s tough being a CMO today. Entire industries are being disrupted. CFOs demand accountability for every dollar spent. And being measurably “customer-centric,” the key to generating the kind of growth the job demands, is increasingly difficult when those very customers interact with your brand across disparate channels.

Imagine if there were a tool that could provide all the elusive insights necessary to drive that growth.

Guess what? That tool exists and there’s a good chance your organization has one. It’s a data management platform, or DMP. There’s also a good chance you don’t care at all about that DMP, thinking of it solely as the “programmatic” tool used to retarget your customers with hapless, incessant banner ads yielding a .02% click through rate.

Today’s new generation of DMP, however, does a whole lot more than just execute on digital media. In fact, Forrester recently noted that this new generation DMP “will offer holistic consumer management … making the DMP the brains of the overall operation.”1

It’s this DMP that can become your largest source of customer insights and help you determine:

1. Growth strategy: where you can grow with respect to, not just current customers, but prospects and previously unidentified consumers.

2. Media investment: certainty around knowing where you can invest more money and where there’s diminishing returns, tied to specific customer segments.

3. Brand insights: nuanced intelligence gives you not only marketing insights but customer, consumer, and competitor intelligence.

It’s this DMP that can combine intelligence from your CRM, your customers’ and prospects’ digital journeys, their media interactions, and the analytics to measure it all. This DMP will enable better intelligence across everything you do: planning, execution, optimization, and insights. And with this customer-centric focus, enable growth across the brand as a whole.

Plan with Real Customer Data

Imagine segmentation that is based on more than just demographics or the last campaign you executed, but combines your customer long-term value (LTV) models from your CRM with advertising channel response propensity, digital behavior, and geolocation.

For example, this DMP can yield a segment of a retailer’s best in-store customers, those who, say, receive a higher share of catalogs; conduct frequent, detailed searches in the category; respond to content on home design sites; and have an over 10-mile commute to stores. In other words, this DMP can help produce segmentation that is sophisticated, nuanced, contextualized, and timely.

Execute Not Just On Media, But Also Customer Experience

This DMP not only can execute on the aforementioned digital media, allowing you to control frequency of messaging. It can also serve as the engine for personalizing the whole customer experience, including contextualization.

So, using our retail example, after a customer or prospect views a sofa on the mobile app, and then visits the website a day later, the brand could not only serve the sofa ad, but also decide to surface longer reviews and larger images. And as connected TV becomes more integrated into this ecosystem, the possibilities for richer addressable marketing experiences increase — or, without the right data, decrease — exponentially.

Measure with Greater Precision

To be clear, most DMPs today do, at best, an adequate job of measurement. But this DMP has the capability of integrating Multi-Touch Attribution (MTA) into the very segmentation we discussed earlier, to inform contribution of various media channels, and help you construct a person-based journey against your segmentation. It can surface insights in real-time to help you adjust the advertising against those audiences, or tweak the audience segmentation itself. This DMP can send those adjustments to change media allocation, message, or creative.

Our retailer might now choose to pivot away from current sofa creative based on lackluster performance, and instead show creative for a whole new furniture style or color.

Gain Insights That Help You Attract New Customers

This DMP can not only tell you about the customers you know, but also offer insights about the prospects you want, including the competition’s customers. The anonymous, person-level data you get from your DMP can tie digital behaviors like website visits or email opens that can be used to conquest broader, look-alike audience segments.

To scale beyond today’s consumer base, our retailer can segment customers with similar household incomes, locations, and affinities to glean broader, more sophisticated insights. For example, knowing that a cross-section of consumers who bought modern furniture in-store and also bought outdoor, Adirondack-style, lounge chairs online delivered to a different address, might have two homes, suggesting double the retail needs.

How to Know What a Growth-Driving DMP Looks Like

Now that you know that a DMP can up your customer intelligence game, you need to understand a couple of important features to look for. These are two of the most crucial differentiators of a growth-driving DMP:

1. Built-in identity key. In order to give you accurate and consistent intelligence about customers, your DMP must be able to resolve the myriad data from disparate channels and interactions with customers, to a person. If it doesn’t do that with 100% fidelity, discerning accurate sources from potentially inaccurate, then you start the customer’s experience with a flawed understanding of that customer (To be clear, personally identifiable information is anonymized in the DMP in accordance with industry regulation compliance).

2. Able to produce customized models specific to your business, nimbly. Look for a DMP that not only applies advanced machine-learning out of the box, but one that allows you to leverage your proprietary, brand-specific knowledge to, in turn, inform the segmentation of audiences. Your data scientists should be able to easily leverage these complex data sets to write AI algorithms that make segmentation more meaningful, yet faster to compute. The key to enabling this is a data structure that is advanced, understandable and accessible.

To develop the kind of fundamental, foundational intelligence necessary to create a customer intelligence powerhouse, CMOs need to elevate the DMP to strategic status at the center of the marketing and analytics organizations, where it can facilitate wiser media investments, customer-centric brand strategies and, yes, growth.

1 Source: Forrester. “The Forrester Wave TM: Data Management Platforms, Q2 2017” June 1, 2017.

 

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