Data management platform

Data Management Platform (DMP) is a technology platform used for collecting and managing data, mainly for digital marketing purposes..^[1] It allows to generate audience segments, which are used to target specific users in online advertising campaigns.^[2]. The DMP may use Big Data and Artificial Intelligence algorithms to process big data sets about users from various sources. DMP is used for organizing and monetizing data in Real-Time Bidding system by licensing it to global selling platforms (DSPs). This technology is constantly being developed by entities such as OnAudience.com, Lotame and Oracle

Processing data on DMP

DMPs are used in the following areas:

1. Gathering data - the platforms are used for collecting data from many various sources. The data about users and their activity is gathered from:

• offline sources (e.g., CRM systems, surveys)
• online sources - mobile and desktop devices (e.g., mobile apps, online campaigns, landing pages, websites)

2. Integration - DMPs integrate data from various sources and create 360-degree customer view. By using Machine Learning algorithms, DMP gather data about users and integrate all data types: 1st, 2nd and 3rd party data.

3. Managing data - on DMP platforms companies organize data they own or gather from specific sources^[3]. The platforms allow to create custom clients’ segments and segment customers, e.g. by markets, online activity, favourite brands or bought products.

4. Activation - through DMP platforms collected data is activated in the marketplace, including adservers or DSPs. The data stored and organized on DMP platforms is used for targeting selected audience groups in online campaigns, across channels such as:

• digital display
• video
• social media
• search engines

Functionalities of DMP

DMP is used for profiling, analyzing and targeting online customers in digital marketing. The platforms are used in the following areas:

Ad targeting - creating audience segments and targeting specific users with personalized ad campaigns. For example, an automotive company that uses DMP can create a custom segment of clients who are interested in buying new SUV. Then, the company can license custom segment to DSP platform and run a campaign of new SUV targeted at users who are interested in buying the new car model.

User profiling - the DMP platform is used for profiling customers. A user profile is a set of data representing real person via user related information, e.g., needs, interests or behaviors. Profiles are created manually or by using Machine Learning algorithms, that automatically analyze and profile even billions of Internet users. To create a user profile, the machine uses i.e. content-based techniques to analyze what kind of websites users visit and on that basis - set relevant users interests, such as Technology, News, Sports, Arts & Entertainment^[4].

Look-alike modeling - is a methodology used for finding new clients who behave closely similar to current customers. DMP profile users who bought a specific product and allow to find a new group of customers with similar profiles (look-alikes) in external databases to display them targeted ads.

Business insights - DMPs deliver insights about customers or services. The platforms are also used for enriching internal CRM systems with external data. The CRM enrichment process integrates user data to create 360-degree customer view. New users’ data contain attributes, such as interests, purchase intentions, visited websites or online behavior. The DMPs supply other services, such as Google Analytics, to show purchasing process, i.e. how many times ad had been clicked before customer bought the product.

Audience analytics - DMPs are used for analyzing behavior and profiles of online customers (i.e. general interests, purchase intentions, behavior) to find the best converting audience group and target it in online campaign.

Ownership of data collected on DMP

Most common types of data are:

• 1st party data - data collected by the company itself, owned data, i.e. website data, mobile application data and CRM data.

• 2nd party data - data collected in result of cooperation. It includes on-line campaigns data and customer journey data.

• 3rd party data - data delivered by data providers, which is available on the market at a specified price.

Data collected on DMP is divided by types:

• Observed data - is a digital footprint of Internet users, i.e. visited websites or type of used web browser.

• Inferred (predicted) data - conclusions based on Internet users behavior. For example, by analyzing statistics of the ad campaign, machines find users who buy most frequently and target ads at them.

• Declared data - the data that Internet users declared by themselves, i.e. in online forms or apps (declared age or gender).

Key technologies for DMP

DMP uses machine learning algorithms and big data analytics for profiling customers and integrating data from various sources.

• Big Data Analytics - the big data technology is used for advanced analytics of online traffic and user behavior. It allows to find the growing trends, conduct look-alike modeling or analyze profiles of specific audience groups.

• Artificial Intelligence and Machine Learning algorithms - used for integrating data from many data sets and for segmentation of online customers. The machine learning algorithms define e.g. the interests and purchase intentions of Internet users basing on visited websites and online behavior.

Examples of DMP

• AdForm
• Eyeota
• LiveRamp
• Lotame
• OnAudience.com
• Oracle
• TheADEX

Global data and programmatic market

Data about online customers is used in programmatic advertising. Programmatic advertising market is growing rapidly on the US and EU markets. US marketers in 2018 will spend over 39 billion dollars for programmatic advertising^[5]. In Europe marketers spent for programmatic ads 8.1 billion euro in 2016^[6]. The global data market is growing at double-digit rate. Its value will reach 18.2 billion dollars in 2018, which is almost a growth of 35% YoY^[7].

Privacy issues - DMP and GDPR

DMP platforms help companies comply with European data privacy regulations - GDPR. Under the new rules, consumers must be afforded insight and control into companies’ storage and use of their data^[8] DMPs gives firms control over all collected data, which can be easily tracked, changed or deleted^[8] To comply with GDPR - regulations that among others expand the catalog of information that could be used for identifying a person - companies implement on DMPs an automatic anonymization process of the all processed data. It makes all the collected and stored data on the DMP anonymous, so none of the personal data is processed.

Notes

References

• Bongartz, Dino. "Data-Management-Plattformen: Was sie können und wie sie funktionieren". internetworld.de.
• Pena, Samantha. "What Is a Data Management Platform (DMP) and When Do You Need One?". HubSpot.
• Williams, Hugh. "Do You Really Need a Standalone DMP in 2018?". ExchangeWire.
• Treffiletti, Cory. "The 3 Layers of Modern Marketing: Data, Analytics, Activation". Forbes.
• Levy, Heather Pemberton. "How Does a Data Management Platform Work?". Gartner.
• Hayter, Luke. "Lookalike modelling: the ad industry technique demystified". The Guardian.
• Booth, David. "Cutting Through The Hype: 5 Points To Drive Value From A Data Management Platform (DMP)". MarTech.
• Simpson, Jack. "What are first-, second- and third-party data?". Econsultancy.
• Bailis, Rochelle. "Inferred, Declared, Observed... Demystifying Common Data Types". Hitwise.
• Blackford, Adela. "From big data to DMP: The Rise of data-driven marketing". IAB UK.
• LePage, Alex. "Why Every CMO Should Care About Their DMP". Forbes.
• "Data Driven Marketing. How efficient and personalized customer dialog will work in future?" (PDF). Deloitte Digital.