Data Management Platform(DMP) 2021: Complete Guide

What is a Data Management Platform(DMP)?

Data Management is a process whereby systems of absorbing, storing, organizing, and maintaining data created and collected by any organization, are set up. For any organization, it is of utmost importance to ensure that there is proper data management, so that crucial data is protected and never lost. Data Management in the context of DMP, involves managing 3rd party data.

Data security is an important element that makes up data management which aids in the safekeeping of people and organizations from data loss, breaches, or thefts. Modern businesses deploy several analytical programs to get better insights into making fact-based decisions, and future strategies, through case appropriate data management. Data Management in the context of DMP is not allowed to store Personal Identification Information.

The enormous growth of advanced data technologies has ensured that data management remains among the most demanding business differentiators for enterprises globally.

As per general data management trends in 2021, according to IDC (International Data Corporation), high-speed cloud service providers would enable Data as a Service (DaaS) to be available to a larger user base and that 90% of large enterprises will be engaged in revenue generation from DaaS. Further, more than 40% of data-based tasks are set to become automated and offer higher productivity.

Data Management Platforms are software systems that are harnessed for collecting, storing, organizing, managing, and interpreting data, from multiple sources.

Data Management Platforms not only sort and analyze data but also give useful insights

into customer demographics, psychographics, including what draws customers and influences them to make purchases, and helps businesses create strategies that best suit their target segments. A few good examples of data handled by a Data Management Platform are GPS derived locations, audience data from multiple channels, app usage data, consumption data from connected devices (IoT) among others.

DMP vs CDP

CDP is primarily focused on managing company owned data i.e first party data. DMP focuses on 3rd party data. Very often they integrate with each other. One of the main differences between a CDP and DMP is a CDP is all about managing an individual customer with a single profile, while a DMP is about managing segments of customers with anonymous profiles. DMP can not store Personally Identifiable Information as they are more about sharing audiences.

DMP is primarily used for ad targeting and its primary users include advertisers and marketing agencies. CDP is used by marketers for various marketing activities including campaigns, customer communication, and smarter engagement.

A few key benefits of using a DMP are as follows:

Simplifies Data Analysis

A good DMP allows you to gather and sort data to offer greater insights by interpreting the data easily to make important business conclusions without much hassle.

Offers Better Security

Data Management Platforms offer extensive encryption capabilities that can ensure that data is automatically and efficiently backed up and recovered. What’s more, several multiple users and any size of data can be easily and securely accessed using this software. This security and availability is a critical benefit of a data management platform.

Makes Data Actionable

A good DMP enables data to be collected from a wide array of sources including apps, social media, websites, emails, campaigns, and online searches. By collating these data results from third parties, Data Management Platforms help business users tap into new markets by gaining new audience insights, and improve user profile quality by enabling demographic data and purchase intention - thereby making data more actionable.

Handle High Number of Users

Having infinite computing power for an infinite number of users, a Data Management Platform can enable a business to easily ramp up and meet their growing business needs without having to lose control over their data.

Higher Performance

A DMP supports unlimited bandwidth, allowing businesses to run multiple computer clusters at the same time without slowing down.

Industries Using DMP

Usually, B2C businesses have a large volume of data in comparison to a B2B business. Other factors like security and compliances, data protection obligations, and the size and scale of the business, determine the need for a DMP.

In addition to technology and software product companies, some of the other industries that benefit from using a DMP include:

Publishers

This category of businesses usually owns and manages websites. They collect audience data from the websites and then harness it in advertising campaigns on these very portals.

Marketing and Media Agencies

They use Data Management Platforms to identify and classify audiences from various sources so that they can pitch the right marketing strategies around building a new customer base from it. Agencies also use Data Management Platforms to glean inputs about customers and to identify valuable customers which may ultimately lead an enterprise to an increased audience base. They then use these insights to drive marketing campaigns to reach the right customer and audience.

Users of DMP

While enterprises across the world can benefit from using a DMP, it offers the most benefits to upper corporate managers who need to make informed business decisions.

Data Management Platforms also aid IT or networking teams and professionals who can gain insights from the tools it offers in the selection of infrastructure and software.

Data-driven Decision Making

Consumers in today’s times need a business that can respond to their needs effectively. A DMP enables businesses to manage and integrate their data effectively, which brings together insights that help leaders make more effective decisions.

Improved Productivity

Large organizations don’t often have easy accessibility to data which can, in turn, affect business productivity. An efficient DMP allows employees and different teams to access data with ease and enables sharing of relevant insights across teams to reduce human errors and smoothen workflows, thereby boosting productivity.

Minimize Errors

Having an effective DMP ensures that potential errors are minimized and the damage caused by bad data reduced. This aspect is crucial to the health of an enterprise’s most valuable asset. Similarly, inaccurate, error-prone data can waste time, talent, and resources, so by deploying a DMP one can manage, update, enhance, and efficiently increase the accessibility of data.

Improved Data Quality

When businesses work with data from multiple sources, ensuring a unified version of the truth can be a challenge. Data Management Platforms bring together information from various sources and help avoid duplication by capturing, cleaning, organizing data. The outcome is better data quality and access leading to efficient decision making for the enterprise.

Overcome Data Silos

Many businesses struggle with siloed information - when data is stored in disparate units it does not connect to give decision-makers the big picture. Data silos slow down a business’s ability to respond to changes in environments, uncover new opportunities, and understand customer intentions. A DMP helps overcome data silos by enabling data to integrate and communicate with other systems.

Data Collection

Data Enrichment and Normalization

Data is normalized by organizing it into a common format and enriched through tagging, and bringing in third-party supporting data such as demographics or historic patterns.

Profile Merging and Building

Data Management Platforms reduce duplication of profiles by comparing incoming data to avoid creating new user profiles or merging them into existing ones.

Segmentation and Taxonomies

Grouping profiles based on certain features is segmentation, while taxonomies help in labeling different pieces of data that are similar in meaning. This feature allows users to search and retrieve data easily.

Audience Creation

Users can create customer groups and variations of the same audience by putting in markers to differentiate them. This enables them to create hyper-personalized messages or special offers that are relevant to each group.

Analytics & Reporting

Data Management Platforms offer users the ability to generate detailed reports based on large amounts of data ingested. These include insights on engagement, user behavior, mobile apps and it also aids users in uncovering new audiences.

AI in DMP

Both Artificial Intelligence and machine learning are transforming low-level data management platforms into intelligent systems. And this impact is being keenly felt in the data management industry.

Let’s look at some of the changes that AI is already making with Data Management Platforms:

Automation

AI helps drive automation, which for data management can help reduce a tremendous amount of manual work. Using AI, Data Management Platforms can transform from rule-based policies to goal-based policies, ensuring control of the data outcome without the monotonous work. An example is AI algorithms which are helping enrich technical metadata with business metadata so that business users can stay more informed.

Anomaly Detection

AI also helps detect irregularities in data loads by tracking changes in data volumes, and changes in data characteristics, etc. An example of this would be fake click programs being generated by hackers to target advertising platforms. AI can help recognize incorrect patterns in click data and alert users to monitor campaigns that are being targeted. The algorithm continues to improve over time, ensuring it gets more accurate in tracking and alerting businesses to anomalies.

Intelligent Search and Tagging

Using natural language processing and data mining technologies, data can be enriched with product information, codes, and industry-specific glossary terms. This helps in enabling a quicker and smarter search for information that is most relevant to a business.

Data Ingestion

As a DMP’s main use is to collect, store and organize data, it is essential to first understand the complete complexity of the first, second- and third-party data that the platform needs to ingest before investing.

Audience Segmentation

Before choosing a DMP, be sure to understand the supporting audience tools, algorithmic segment capabilities, and taxonomies, and how this will impact its performance to manage, categorize, and retrieve your data.

User Experience

The DMP will need to have a user-friendly and intuitive interface as it will be used across a variety of teams including sales, marketing, and senior management.

Media Integrations

Before activating data across a range of media channels, it is imperative to check which vendors the DMP has integrations with and for what period. Other things to consider are costs, timings, and limitations in media channels.

Report Generation

One must ensure that the DMP offers not only the right data but also the rich insights that one can glean from it. Therefore, the analytical tools the platform offers to measure audiences and media performance should be taken into consideration before choosing.

Data Privacy

Privacy laws of various countries along with compliance with legal and industry regulations should be adhered to and in place before an enterprise decides to invest in a DMP.

Scale

Some DMPs offer license-based capabilities, while others may be driven by the number of profiles that will be stored, and incoming traffic. It is important to understand your business’ current and future growth aspects before investing in the right DMP.

Challenges in Adopting DMP

Poor Data Quality

Many enterprises lack quality first-party data and often need to spend valuable time and resources cleaning or even digitizing their data before implementing the DMP.

Lack of Internal Expertise

The right human professionals to effectively manage, organize, and interpret the data efficiently is a must-have. Developers knowing JavaScript, HTML, CSS are crucial to the success of a DMP operation.

Integrating with Legacy Systems

Many modern Data Management Platforms are incompatible with legacy systems. It is, therefore, invaluable to ensure that your systems are in sync with the new platform and ready to hit the ground running once deployed.

Data Security

From following privacy regulations to understanding legal implications while dealing with customer data, protective measures need to be taken to ensure that there are no unauthorized collections of data, particularly by third parties. Businesses must have clearly defined rules and access protocols to ensure data security and enable the legal operation of their DMP.

ROI of DMP

While businesses certainly make considerable investments to implement a DMP, these platforms benefit the business in both direct and indirect ways.

Hyper-targeted advertising

Using a DMP leads to greater customer information and grouping capabilities. As a result, marketing teams can create hyper-relevant, real-time messages, and campaigns. Personalization results in more optimized ad spending with better results and ROI.

Benefits beyond marketing

Since many more meaningful data points about the customer can be gleaned from customer acquisition, it becomes pertinent to share the insights with not just the marketing team but also with product development, account management, sales, and many other teams. This means that rather than risk making ill-informed decisions, companies can use these data-derived insights and share them among multiple teams so that they can tailor their approach to customers.

Seamless cross-channel action

Seamless communication with existing and future customers is a direct benefit of deploying a DMP. With a DMP’s ability to integrate with many third-party systems like social media platforms, IoT and CRMs; the right data is aggregated and organized for taking action on as compared to organizations with siloed data flow, which in turn maximizes ROI for any company.