As a marketer, you should be more than convinced about the importance of data to deliver value for your customers by now. You should have understood how precious data is flowing from every customer touchpoint. You should have spent some time (months, years) banging your head around problems such as trying to make sense out of data, different attribution criteria from different systems, customer data scattered throughout many systems, several IDs per customer, or that you have the data needed but fail to make it actionable.
Being a marketer these days has ultimately revolved around learning how to work with data. About being able to analyze customer behaviour, making data-driven decisions, and learning about new data technologies among other things.
When thinking about our clients’ challenges we have been asked this question: do I need a CDP or a DMP? Much has already been said about Customer Data Platforms (CDP) and Data Management Platforms (DMP) and, as new features are added and improved, it may seem like they are converging and addressing the same problems.
Both technologies handle data management, address the challenge of matching users with different devices – each in its own way – and are being requested specifically for marketing purposes and activities. If we go one step further to understand how they work, we can identify clear differences. Let’s have a look at the comparison below:
|CDP (Customer Data Platform)
|DMP (Data Management Platform)
|Known and anonymous profiles
|Customer ID (PII data)
|Cookie ID (tied to a browser)
|Main data types
|First-party data. CDP stores personally identifiable information such as names, email, mailing address.
|Third-party data. DMP works with anonymous tags such as IP addresses, devices, and cookies.
|Deterministic and Probabilistic
|Insights and analysis
|On an individual level
|On aggregated level (anonymous segments)
|According to company data retention policy
|12 months or as agreed with vendor
|Main promise / Designed to
|To organize customer data around a unified customer ID that is accessible to other systems enabling 1:1 communication with customers.
|To primarily enable efficient media buying by improving audience targeting capabilities for leads or prospects (prior to becoming customers).
A DMP can have a major role within companies that are focused on the upper funnel, i.e. customer acquisition, and are aiming to optimize their paid media investment. The DMP will improve targeting capabilities by offering a marketplace of third-party data providers to enrich your first-party data, “out of the box” lookalike models to amplify your prospecting efforts and better control of segments regardless of advertising platform. This will enable you to provide a more consistent message and brand experience across channels. Another valuable feature is that you can leverage multi-brand strategies in your organization by sharing segments between brands inside the DMP.
Since there is no PII-data (Personally Identifiable Information data) in the platform, all insights coming from the DMP are on an aggregate level (segment). The identity matching is more fragile compared to the CDP. This is due to the use of cookie data, which is more susceptible to change in the short term, and the approach relying mostly on probabilistic methods.
This makes it clear that even though some vendors may add PII data features, DMPs were not designed for 1:1 communication.
A CDP, on the other hand, can be a better fit if you are looking for a solution to get a deep understanding of your customers on an individual level and want to deliver better 1:1 communication. A CDP’s primary focus is on customer data and profile consolidation. Since you have historical/transactional data tied to a customer profile, this data can be used for 1:1 communication in marketing automation or customer service systems.
A key differentiator of the CDPs is that the solution is not limited to marketing technologies – it also connects to other data systems such as BI reports, customer service, call centres, etc. Also, a CDP is a better option if you wish to use customer data to build analytical models. Besides having data that is deterministically tied to a customer and that doesn’t expire, it provides better data capabilities such as building real-time integrations and processing semi-structured and unstructured data.
Like all technologies, CDPs and DMPs are ever evolving. That’s why I will leave you with no answers, but more questions on a few important things to have in mind when deciding on one or the other or, for some companies, both technologies:
- What use cases are you trying to enable?
- What skills and competence will you need in order to operate this new way of working?
- How would this new technology fit into your current martech stack?
- On a more long term note, how can you build your business to be even more centred around customer intelligence? How will you scale? What other enablers should be in the roadmap?
When we talk about marketing technologies, we are thinking about a new way to create value and deliver meaningful experiences for customers. As we are dealing with a very dynamic industry that changes constantly, it is about asking questions: the right, the important and the stupid ones.
Hopefully, this can empower you a little more on the journey to becoming more data-driven and tech savvy.