What is a DMP: How to augment your DMP with a CDP
Create a dynamic martech stack capable of collecting, transforming, and activating customer data by using a CDP to augment your DMP. Learn how you can leverage these technologies to help you turn your customer data into a growth asset.
When it comes to managing, analyzing, and activating user data, many different solutions can help marketers achieve their goals in some capacity or another. Implementing a system that produces so-so results or creates operational bottlenecks is relatively easy; the real challenge for marketers is to discern which system would serve their business needs best and expedite insight into customer data to inform future interactions. This research process often leads marketers to ask: What is the difference between a Data Management Platform (DMP) and a Customer Data Platform (CDP), and which is right for me? This blog will take you through the finer points of how both CDPs and DMPs work, how they differ from one another, and how you can leverage these technologies together to help you turn your customer data into a growth asset.
What is a DMP and what can it do?
DMPs consolidate data through non-deterministic processes from a company’s disparate systems across channels to create a statistically likely profile of customers. While some DMPs can collect and store some first- and second-party data, DMPs mainly rely on third-party data to create audiences. The first- and second-party data that is collected by DMPs is anonymized and hashed before being stored and organized for use by brands. DMPs gather data in three ways:
- Onboarding - This is a largely manual process where customer information determined to be significant is put together into a CSV file, then fed into a DMP. These files usually include fields like attributes, attribute IDs, attribute types, banding rules, and a description. Attributes are aspects that can be attached to people, like age or gender or whether they are signed up for a loyalty program. These then have attached attribute IDs and attribute types to help keep the information organized, with banding rules helping to define the attribute value further. Descriptions are put in place as a reminder to brands as to the source, value, or importance of that information. Once onboarded, all of this data is then stored for future use.
- Tags or cookies — DMPs collect anonymized, hashed customer information through embedded JS code in web and mobile sites. Tags perform specific tasks, like recommending products or chatting with customers, while collecting behavioral data on each customer. Cookies and tags are efficient collectors of customer data, but they are limited to digital properties where the tags can be triggered. Tags also have an expiration date, and so are ephemeral data sources.
- APIs — DMPs can collect formatted data objects from other platforms or services a company may be using to manage customer data through a server-to-server exchange.
DMPs take all of this data and create audiences full of anonymized proxies with similar characteristics, depending on what kind of audience a marketer is trying to target. Marketers can then take these audiences and feed them into their demand-side platform (DSP) to inform ad buying.
Measurement and adjustment
Finally, a DMP manages campaign activity and audience data and measures them to help optimize ongoing campaigns as well as establish best practices for future campaigns.
The right tool for the right job
All of this is to say that DMPs are very useful, particularly for marketers looking to acquire new customers through advertising. But, for all they do well, DMPs do have some shortcomings that make them an imperfect solution for brands looking to not only acquire customers, but also convert, engage, and retain current customers. However, that’s difficult to do unless you know who you are marketing to on a one-to-one basis and be able to provide customers with what they want in real time.
How can a CDP help?
CDPs provide marketers with a single platform from which to collect, manage, transform, and activate all of their customer data, regardless of the source.
Data collection and normalization
Instead of relying on third-party data, CDPs collect first-party data and second-party data in real time through an API, normalize and cleanse it, then make it available to the different BI tools and service platforms brands may be using. Using an API means that marketers can collect data from across all of their data sources automatically, and centralize it in real time. Data collected from all of your sources is then cleansed and normalized to improve insight; data cleansing may include removing characters, data elements, or entire records to isolate and highlight significant information.
Customer data collected by a CDP is attributed to a persistent profile that doesn’t expire to inform future interactions based on that specific customer’s history. By keeping data for extended periods, customer profiles and histories can become more and more robust as customers interact with a brand across different channels.
Unlike DMPs, CDPs can collect personally identifying information (PII) securely as well as data generated during online and offline interactions and match them to a single customer profile. When customer data is collected, a set of deterministic data points—like an email address, a mobile ID or number, or a Facebook ID, to name a few—are used to match data across all of their touchpoints to give marketers a view of the entire data set. Notably, CDPs can profile interactions from invisible or anonymous customers retroactively once a customer becomes known using this process.
Identity resolution allows marketers to understand who their customer is, as well as their customer journey. Using this information can help marketers act in the moment and learn how customers progress through their journey to improve and streamline future customer journeys.
Because data is centralized and normalized in a CDP, second- and third-party data becomes even more valuable. Customer profiles are enriched with second- and third-party data for additional context, which creates better, more accurate, and more timely interactions. For example, by enriching a customer profile with location data from a partner, marketers can provide a customer with a highly targeted email or push offer when he or she is close to a physical store. This tactic is used successfully by companies like Chik-fil-a to time order completion and maintain their standard for freshness.
Audiences and personalization
No two companies are alike, and no two business strategies are alike. Audiences created in a CDP are highly customizable, allowing marketers to home in on precisely the customers the need to target. In a few clicks, marketers can define custom audiences without having to stick to the rigid audience types of a DMP, and use data from all online sources as well as offline sources like call centers, IoT devices, or even point of sales solutions. Segments can be created based on behavior, propensity to purchase, likely purchase amount, lifetime value, and so on, then used to create better, more personalized campaigns.
Orchestration and activation
Audiences created in a CDP can be forwarded directly to any of the leading marketing, sales, and BI platforms and services, including social platforms, demand-side platforms, and email and push providers, among others.
With a CDP, marketers can configure audiences once then upload everywhere with just a few clicks, instead of having to upload the data to services one by one manually. Because marketers don’t have to rely on engineering to query the customer dataset then upload manually, marketers are free to test initiatives around marketing offers, product layout, and product features, and measure their impact on customer service metrics, order volume and value, and customer lifetime value among other factors.
Together in perfect harmony
It’s a part of human nature to look for a panacea, and that is just as true when it comes to implementing marketing technologies. Instead of thinking about a CDP versus a DMP, marketers that have a DMP in place already can look at a CDP as a foundational stack layer that helps to amplify the benefits of a DMP, as well as address some of the gaps in data persistence; identity resolution; data activation and acquisition; and customer engagement, conversion, and retainment. If you prefer to implement a CDP rather than a DMP, a CDP can offer you all of these benefits and more. If you’d like to learn more about CDPs, read our Complete Guide to CDPs or feel free to reach out!
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