Digital Data Management Platforms: Great Idea but Continued Evolution is Needed!


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Data Management Platforms (DMPs) provide a valuable service to online firms, especiallydigital online media organizations that generate most of their revenue through online advertising. What is a DMP? DMPs integrate online data sources, into one environment, in order to better empower online publishers and marketers’ media buying and online customer targeting decisions.

  • DMPs seamlessly consolidate online data sources: Online behaviors, ads, registration, personalization and eCommerce
  • They merge that data with offline data sources to help their clients gain greater insight into their online customers, through the use of segmentations, campaign tracking reports and audience insight dashboards
  • They use that insight to better target advertising and internal offers to both anonymous and known users online thus generating increased advertising revenue and/or increased user engagement.

DMPs are digital customer intelligence hubs. So then what is the difference between a DMP and a traditional marketing intelligence system?

  • Digitally focused: DMPs are focused on digital client needs predominantly however the data may be used to increase offline insights as well.
  • Online Customer Consolidation: DMPs provide a critical service used to tie online users together throughout online sessions and also integrate online users with offline users.
  • Tightly integrated: In the digital world customer communication decisions need to fire in as near real time as possible, which requires much tighter integration. DMPs seamlessly integrate the following to enable near real time digital communication decisions
    • DMPs track online behavior (tracking your online movements)
    • DMPs are tightly integrated with the communication deliver engines (eg. ad servers and content engines)
  • Traditional integration: Like traditional marketing databases, DMPs are integrated with other sources including email, eCommerce and order management.
  • Data Model & Segmentations: Most DMPs provide a standard online data model and out-of-the-box segmentations used to get the clients up and running as quickly as possible.

DMPs have done a nice job building out the required infrastructure … technically integrating with the available systems and consolidating user data. In the digital world this is the cost of entry however. DMPs have also done a good job creating standardized data models, segmentations and dashboards in order to minimize solution build time. Then what enhancements should we expect in the next year?

  • Greater customization: All DMPs know that they need to evolve and the first step in the evolution is to allow for greater data and reporting customization to better fit clients’ needs.
  • Greater use or proprietary data: As DMPs are used more and more the available out-of-the-box segmentations will continue to become more commoditized. To combat this, customized segmentations and models may be built and then used for even greater enhanced targeting which will demand an advertising premium.
  • Greater Insights: With the additional data, customization and proprietary segmentations the ability to generate greater digital customer insights will be available.
  • Offline and online customer intelligence hubs merge: DMPs are the digital customer intelligence hubs. Eventually, offline and digital customer intelligence hubs will merge and DMPs are well positioned to take on some of that work especially due to the added technical complexity of the digital environment that traditional marketing service providers (MSPs) lack in experience.

DMPs have blazed a trail and have set the standard for online consolidated databases. With many recent technical, online and analytic advances, DMPs are well positioned to continue to evolve if they so choose. However, regardless of the digital technical prowess DMPs have in-house, the key will always be to satisfy the end clients, which are predominantly digital marketers and advertisers … and this requires flexibility and ongoing customization.

Republished with author's permission from original post.

Roman Lenzen
Roman Lenzen, Partner and Chief Data Scientist at Optumine, has delivered value added analytical processes to several industries for 20+ years. His significant analytical, technical, and business process experience provides a unique perspective on improving process efficiency and customer profitability. Roman was previously VP of Analytics at Quaero and Director of Analytics at Merkle. Roman's education includes a Bachelor of Science degree in Mathematics from Marquette University and Masters of Science in Statistics from DePaul University.


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