The CDP Shortcoming That The Industry Needs To Address

3D Isometric Flat Vector Conceptual Illustration of Client Profile Data Analysis, Customer Relation Management

In this guest post, Aaron Jackson, chief growth officer at Eyeota, discusses what needs to change in order for customer data platforms (CDPs) to keep up with the times.

As the global advertising community intensifies its focus on first-party data, many brands are turning away from data management platforms (DMPs) and turning toward customer data platforms (CDPs) as the linchpins of their data-driven marketing disciplines. 

The reasons underpinning this pivot make sense in light of current marketplace pressures, but there’s a problem: while today’s CDPs are adept at managing data on known users, they leave a massive gap in a brand’s marketing strategy as it relates to new customer acquisition.  

As a foundation for holistic data-driven marketing and advertising, CDPs aren’t going to get brands where they need to go without some serious added attention. Here’s what brands need to understand.   

The transition from DMPs to CDPs 

The ongoing transition away from DMPs toward CDPs makes sense, given that DMPs tend to be heavily reliant on third-party cookies, which will be all but irrelevant in the near future.  

In contrast, CDPs are heavily focused on first and second-party data assets and are exceptionally adept at helping brands get a handle on their known users in an omnichannel fashion.  

Unfortunately, in moving from a DMP to a CDP, the pendulum swings too far. CDPs are great for enabling direct-to-customer relationships and breaking down channel silos when it comes to customers. But, unlike DMPs, CDPs aren’t built to help brands find new audiences. That’s because, by default, they’re not focused on supporting third-party data that can be used to extend a brand’s understanding of its customers and help it find new audiences.  

At the heart of this conundrum is the deterministic/probabilistic data dichotomy. The challenge, as with a lot of dichotomies, is that the question of deterministic and probabilistic data is too often being discussed in “either/or” terms, when in reality most brands recognise that a healthy balance of both is needed. 

First-party deterministic data is essential when it comes to retaining customers and personalising messaging across platforms. However, without a strong base of third-party probabilistic data to enrich customer data, brands are limited in their understanding of their own customers and, worse yet, entirely unable to translate their audience understanding into prospecting and customer acquisition efforts.   

In prioritising known user management over data enrichment efforts, CDPs leave brands vulnerable. That needs to change.

Filling in the missing pieces 

When brands pivot from DMPs to CDPs, a lot of gaps open up. What they gain in identity resolution among their existing relationships tends to be offset when they consider what’s possible from an activation standpoint outside of their known users (i.e. very little).

In order to continue to reach new users, brands need to be able to enrich their CDP data with privacy-compliant third-party data sets, just as they did within DMP environments.  

At present, because most CDPs don’t support such enrichment by default, it falls to brands and their third-party data partners to push for these capabilities.

By layering high-quality probabilistic data on top of the first-party data within their CDPs, brands can solve first-party data challenges, including the following: 

  • Audience depth: Third-party data sets help enhance a brand’s understanding and identify new dimensions of existing customers. 
  • Reach: Data enrichment, when conducted in compliance with applicable privacy requirements, also helps expand the reach and scale of a brand’s prospect base by modelling first-party data with third-party audience profiles.While restrictions apply in a CDP environment, this can be particularly applicable in areas like email marketing.  
  • Engagement: A comprehensive approach that combines first- and third-party insights allows brands to engage with customers in omnichannel environments by activating newly enriched audiences on digital display, video, mobile and social channels.

When it comes to brand sustainability, new customer acquisition remains a vital part of revenue growth.

Yes, first-party deterministic data needs to be prioritised in today’s increasingly privacy-first marketing landscape. But it isn’t sufficient.   

A holistic marketing strategy requires a holistic approach to data, and today’s CDPs aren’t currently delivering on advertisers’ full range of needs.   

If CDPs aren’t going to be proactive in the support of third-party data for the purpose of customer acquisition and revenue growth, then it’s up to brands to demand the features that will preserve their ability to prospect.  

In time, if CDPs don’t start taking these needs into account by default, the industry will be moving on in search of a platform that does.

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audience measurment CDP customer data customer data platform data management platform Data marketing data privacy DMP Engagement first party data Reach third-party data

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