The marketing landscape is littered with acronyms—DSP, DMP, ESP, SSP, SEO, PPC, CPM—the list goes on and on. Recently, DMP (Data Management Platform) has grown into one of the hottest acronyms in the digital marketing space.
While the technology behind Data Management Platforms is complicated, the basic high-level functions of a DMP are rather simple: It consolidates disparate data points then leverages those consolidated data points to create targeted user audiences.
And once all data has been consolidated and unified, the resulting audiences can be pushed to various activation platforms.
How a DMP Works
Having the ability to aggregate data from multiple marketing channels is like hitting a hyper-targeted audience gold mine.
A DMP layers first-party data like site-side user activity, mobile app activity, or paid media engagement on top of second-party data from a data sharing relationship and combines it with third-party data from vendors to create a full view of your ideal audience and what they’re doing.
By collecting and storing data from first-, second-, and third-party data sources, DMPs allow brands to deliver the right message at the right time to the right audience.
With all of that data flowed into the DMP and connections made to enable a single view of a brand’s customer, what happens next? Unlocking audiences and advertising to them directly through media spend optimization through suppression and onsite personalization.
Media Spend Optimization Through Suppression
You’ve seen it before. The display ad you can’t seem to get away from, no matter what webpage you’re on. These brands are guilty of not optimizing their media spend.
With a DMP, brands can drive acquisition through display ads by suppressing the audience who have already seen an ad or are existing customers. The quickest path to ROI from a DMP is to put recency (pace at which the user is shown the creative) and frequency (the number of times creative can be shown to a given user) caps in place.
For example, a retail brand launches a display ad campaign to promote their upcoming fall line. They could then create an audience of people who have already seen their ads and instruct their DSP (the software used to execute programmatic ad buys) to not show additional ads to this audience group. Additionally, this retail brand could create an audience of existing customers to ensure that their ad spend on their new line is not wasted on customers who have already purchased.
Combining these techniques creates a better user experience for their audience and, more importantly, optimizes their ad spend.
Consumer expectations for more personalized experiences are at an all-time high. As these expectations have grown, brands have struggled to keep up and make sure they are providing relevant and personalized content on their websites.
By leveraging a DMP, brands can create an audience based on multiple data sets from past website browsing behavior to CRM data—all enriched with third-party data—to create a truly detailed audience profile which can be leveraged to improve their user experience.
So, what does this look like in practice? For our retail brand with a new fall line, their data consolidation efforts have created an audience that is female, college educated, and early 30s. It also shows that, of this audience, current customers are purchasing in high numbers from their Texas location and frequently buy gift cards.
Armed with this information, the retailer could serve up a personalized website creative for this specific audience that highlights exclusive deals at the Texas location that also includes a promotion for gift cards that drives engagement, loyalty, and (most importantly) sales.
There are a myriad of ways to use a DMP and even more benefits for brands. Stay tuned for our upcoming post that further explores the many ways DMPs can bring more value to data.
By: David Koroghlian, Directory of Strategy & Business Architecture