Data Management Platform (DMP) is a centralized data management platform that –
- Stores audience and campaign first-party and third-party data
- Organizes data based on mutilple segments
- Accurately creates campaign to target audience across ad networks and exchanges
- Measures campaign performance
Using a DMP platform, a marketer or an agency can manage all their advertising activities from one dashboard – from campaign creation, audience profiling, media buying, and targeting, to optimization, measurement, and reporting. A DMP can scale to billions of data points, enabling marketers to gain insights into which campaigns are working across various channels, which exact audiences specific campaigns are reaching, and what changes to make to be more effective. DMPs help advertisers and agencies increase their ROI of their online advertising programs.
A DMP collects data from all possible information sources and aggregates data from first-party and third-party sources by cross-channel marketing. First-party data is the data generated from your own website and social media platforms while third-party data is the information generated from other websites and internet interactions.
The sole purpose of having a DMP is to collect data from all possible sources so as to have detailed information about customers and to create hyper-targeted ads which result in higher conversion rates and customer acquisition and retention.
Features of DMP
- Data Collection
With DMP, you should be able to collect your first-party audience data into one place. This is usually done by placing a single tag on your site that brings all of your first-party data into the DMP. It should also allow you to import data from third-party data providers, so you can compare these data points against your own first-party data in one centralized place. This will help in getting detailed information about the customer which can help in targeting the audience better. It should also allow you to import offline data like in-store purchases etc.
2. Data Classification
Once you have collected all the data, you should be able to classify that data depending on your business needs. This will help in creating distinct audience profile which can be used for targeting.
3. Data Analysis
Once the data is collected and organized as per business needs, you should be able to analyze the data and gain insights. For example, you can analyze this data based on their behavior, location, past purchases, income etc. You can then use these insights to create specific customer segments.
4. Data Transfer
Once you’ve collected, classified, and analyzed your data in your DMP, you should then be able to leverage that data by transferring it directly to the largest ad networks, exchanges, portals, DSPs, and trading desks to make accurate media buys targeting your pre-defined segments. Your DMP should work seamlessly with the largest players in the display, search, and social advertising ecosystems.
5. Scalability
With growing data, a DMP must be able to scale to millions of data points and analyze all of these simultaneously to deliver critical insights.
Who are the major DMP players?
Adobe AudienceManager, Oracle DMP, Krux and Lotame are some of the key players in the market today.