Menu
Digital technologies have changed how brands and businesses understand and interact with customers. Today, data is being generated at an unprecedented rate from social media, mobile devices, websites, and more. This has resulted in a massive influx of data and has challenged marketers to make sense of it all.
To manage, analyze, and utilize vast amounts of data, marketers need a robust system that can handle and organize it. Data management platforms (DMPs) are designed to do just that.
To provide a comprehensive guide on DMPs, this article will explain every aspect of DMPs for businesses and marketers.
A data management platform or DMP is a centralized software platform that collects, stores, and organizes large amounts of customer and prospect data. The data can be collected from any source, such as websites, mobile apps, CRM systems, ad campaigns, etc. In short, a DMP acts as a central hub for all customer data, providing marketers with a unified view of their audience.
A data management platform or DMP is a centralized software platform that collects, stores, and organizes large amounts of customer and prospect data. The data can be collected from any source, such as websites, mobile apps, CRM systems, ad campaigns, etc. In short, a DMP acts as a central hub for all customer data, providing marketers with a unified view of their audience.
DMPs work by integrating data from various sources and creating unified customer profiles. These profiles contain demographics, behavior, interests, purchase history, and more. The DMP then uses this data to segment audiences based on specific criteria.
Once the audience is segmented, the DMP can create custom audience lists and export them to other ad tech platforms for targeted advertising. This creates a flow of data between the DMP and other platforms.
Furthermore, DMPs can also gather data from external sources such as third-party data providers. This allows businesses to enrich their customer profiles with additional information for targeted marketing efforts.
Here is a closer look at what a DMP actually does.
DMPs collect data from online and offline sources such as websites, mobile apps, POS systems, etc. Data formats can vary from structured (e.g., forms) to unstructured (e.g., social media posts). With the help of cookies and pixel tracking, DMPs also collect data on customer behavior.
Once collected, the DMP organizes and consolidates all data into a unified customer profile. This includes merging data from different sources, eliminating duplicates, and creating a single view of the customer. The data is then segmented based on various attributes such as demographics, interests, and behaviors.
Segmentation allows businesses to group customers into specific categories based on their similarities. The anonymous customer profiles created by the DMP can be segmented based on various criteria, such as demographics, behaviors, interests, etc.
DMPs can integrate with ad tech platforms such as demand-side platforms (DSPs), supply-side platforms (SSPs), ad exchanges, and customer relationship management (CRM) systems. The data flow between the DMP and other platforms enables businesses to deliver personalized and relevant customer messages.
Data activation is the process of using data for targeted advertising, content personalization, and audience insights. With the help of DMPs, businesses can activate their data across multiple channels and devices to reach their target audience more effectively.
DMPs can manage 3 main types of data: first-party, second-party, and third-party data. Each type of data has its characteristics and benefits.
First-party data is the most valuable type of data for businesses. It refers to customer data that a company collects directly from its sources, such as website visits, purchases, subscriptions, etc. This data type is reliable, accurate, and highly targeted since it comes directly from the source.
DMPs pull first-party data from CRM systems, email lists, and other internal databases. Sometimes, consumers submit personally identifying information (PII) when creating an account or filling out a form, which further enriches their profile. This data is then combined with other sources to develop a more comprehensive view of the customer.
Second-party data is first-party data that businesses acquire from another company. This usually occurs when two companies form a partnership or exchange data for mutual benefits. For example, an airline may share customer data with a hotel chain to create more targeted offers for their customers.
For businesses, second-party data is a valuable addition to their first-party data. The quality and relevance of this data are usually high since it comes from a trusted source.
Third-party data refers to data businesses purchase from external sources, such as data aggregators or providers. This data type includes a large group of individuals’ demographics, interests, and purchase behaviors. Third-party data is often used for targeting and personalization in advertising.
One of the main benefits of third-party data is its scale. It allows businesses to expand their reach beyond their first-party data and target a larger audience. However, third-party data is less accurate than first or second-party data since it is aggregated from various sources
A Mobile Data Management Platform (mDMP) is a specialized version of a traditional DMP that focuses on collecting, organizing, and activating mobile-specific data. With the ever-increasing use of smartphones and other mobile devices, you need a platform to capture and analyze this data to reach your target audience effectively.
Like a traditional DMP, an mDMP collects first-party data from various sources, such as mobile apps, websites, and other digital touchpoints. This data can include device IDs, app usage data, location information, etc. The mDMP ingests this data and combines it with other sources to create a more comprehensive view of the customer.
mDMPs use specific techniques to collect mobile-specific data, such as device IDs and location information. These identifiers allow mDMPs to track user behavior across different devices. For example, if a user browses a product on their phone and then makes a purchase on their laptop, the mDMP can connect these interactions and attribute them to the same customer.
Cross-device tracking is a critical feature of mDMPs. It allows businesses to track user behavior across multiple devices, including desktops, laptops, tablets, and mobile devices. mDMPs use device IDs, cookies, and other identifiers to connect user interactions across devices
Companies must accurately track interactions on different devices to understand customer journeys. This allows businesses to deliver a more personalized and seamless customer experience.
Since mobile data is highly dynamic, mDMPs must have real-time capabilities to activate this data effectively. An mDMP can segment audiences in real time based on user behavior and preferences to deliver relevant ads, offers, and content. To do this successfully, mDMPs use machine learning and predictive algorithms to analyze data and make real-time decisions.
Now that we’ve explored the specific features of mDMPs let’s look at the broader benefits of using a DMP for businesses.
With access to first-party, second-party, and third-party data, DMPs provide a 360-degree view of the customer. As a result, marketers can reach look-alike audiences, personalize messaging and experiences, and optimize advertising spend for programmatic advertising.
Marketers can also use DMPs to measure the effectiveness of their campaigns and make data-driven decisions based on real-time insights. This helps improve ROI on advertising spend and overall marketing efforts.
Media owners and publishers can use DMPs to monetize their audience data and increase ad revenue. DMPs help publishers better understand their audience, allowing them to create more personalized content and advertising. This leads to increased user engagement and loyalty.
Publishers can also use DMPs to gain insights into their audience’s behavior and preferences to inform content and distribution strategies.
Organizations can use DMPs to gain a unified view of their customers by combining data from different sources. This helps create a single customer profile that includes demographic, behavioral, and transactional data. A unified customer view helps organizations understand their customers better, identify new opportunities, and make data-driven decisions.
DMPs also help organizations comply with data regulations and ensure proper data governance by providing a centralized platform to manage and protect customer data.
To get the most out of your DMP, you need to collect relevant data points and organize them in a structured manner. Here are some key data points to consider collecting:
Identifiers such as cookies, mobile advertising IDs, and demographic data help identify individual users and track their interactions across devices. The demographic data can include age, gender, income, and location. This data allows for a more complete view of the customer journey.
Behavioral data refers to how users interact with your brand, such as website visits, clicks, and content consumption patterns. Behavioral data helps identify patterns and preferences, which can be used to personalize messaging and experiences for each user.
Contextual data includes website categories and keywords that provide information about the content users engage with. For example, a user who frequently visits sports-related pages would be classified as a “sports enthusiast.” For publishers, contextual data can help inform content and ad placement decisions.
A data management platform (DMP) and a customer data platform (CDP) are often confused as being the same thing. While both platforms deal with customer data, there are some key differences between the two:
A DMP mainly collects and manages third-party data, such as cookies and mobile IDs. On the other hand, a CDP collects first-party data directly from customers through interactions with the brand. This includes data from email marketing, website behavior, and customer service interactions.
A DMP is primarily used for advertising and marketing purposes, such as audience segmentation and targeting. Conversely, a CDP focuses on creating a unified customer profile for personalized experiences across all touchpoints.
A DMP mainly activates data through integrations with demand-side platforms (DSPs) and supply-side platforms (SSPs). On the other hand, CDPs can activate data in real-time for personalized experiences across channels such as email, website, and mobile apps.
Data ownership is a key differentiator between DMPs and CDPs. In a DMP, the data is owned by the platform provider, while in a CDP, the brand owns its first-party data. This allows for greater control and flexibility in managing and activating customer data.
Data ownership is a key differentiator between DMPs and CDPs. In a DMP, the data is owned by the platform provider, while in a CDP, the brand owns its first-party data. This allows for greater control and flexibility in managing and activating customer data
Some of the top DMP providers in the market include:
Amazon Redshift is a cloud-based data warehouse solution that offers fast and scalable performance. It integrates with other Amazon Web Services (AWS) products and has robust security features.
Adobe Audience Manager is a DMP that allows one to easily collect, organize, and activate data. It has advanced segmentation capabilities and integrates with Adobe’s marketing cloud. The machine learning algorithms also help in audience modeling and creating personalized experiences.
Oracle BlueKai is a leading DMP that offers strong data security and privacy features. It has advanced targeting and personalization capabilities. BlueKai educates you on entire customer journeys and behaviors, empowering you to make the best data-driven decisions.
Salesforce DMP, formerly known as Krux, offers a flexible and scalable solution for data management. It has robust integrations with other Salesforce products, making it easier to analyze and activate data across multiple channels.
Lotame is a DMP that specializes in data enrichment and audience segmentation. It has a user-friendly interface and provides customizable dashboards for easy data visualization. Lotame also offers advanced analytics features to gain insights into audience behavior.
Here are some essential features to consider when choosing a DMP:
Data security and privacy should be top priorities for any business collecting and managing customer data. A suitable DMP should have robust security measures to protect data from cyber threats and ensure compliance with data regulations. Encryption, access controls, and regular audits to maintain data privacy are some key features to look for in a DMP.
If you already have a tech stack in place, you want to make sure that your DMP can integrate seamlessly with your existing systems. This allows for more efficient data sharing and eliminates the need for manual data transfers. To ensure compatibility, look for a DMP that supports API integrations.
For programmatic buying and selling of ad inventory, DMPs need to integrate with demand-side platforms (DSPs) and supply-side platforms (SSPs). Ensure your DMP has integration capabilities with the DSPs and ad exchanges you use to maximize the value of your data.
As your business grows, your data management needs will also increase. A DMP should be able to handle large volumes of data and have the ability to scale as your business expands. Additionally, a DMP should have high performance to efficiently process and activate data in real time.
Human error is inevitable, and it can have a significant impact on data quality. A DMP with an intuitive user interface and easy navigation can help reduce errors and improve data accuracy. The learning curve should also be minimal so your team can quickly adapt and use the platform effectively.
