Why we must Address Confusion and Complexity in the CDP Market  

We’ve seen several reports recently on the CDP market, notably from Forrester, Gartner and the CDP Institute. These point to a growing and dynamic market place, fuelled by many key factors, such as the greater importance of owned data, data-powered marketing, advances platform technology, AI and so on.

This is great news for the martech industry. But for marketers, what the reports point to is a market that’s getting bigger and more confusing. The platforms and tools that do well in some reports score very differently in others.

For example, in its quadrant for CDPs, Gartner Magic (02/24) had Salesforce and Tealium in the ‘leader’ category, whereas Forrester (Q/23) placed Tealium in the ‘contender’ space and Salesforce was not on the list at all for B2B CDPs. And eight different technologies completely disappeared from the Forrester’s CDP Wave map between Q4/21 and Q3/23.

And there is no clear consensus on the definition of a CDP. There are several different types of CDP, each with their own, overlapping, definition.  So if you look at Forrester’s taxonomy, they list Data Management CDP, Orchestration CDP, Automation CDP and Measurement CDP. However, Gartner has Marketing Cloud CDP, CDP Engines and Toolkits, Marketing Integration CDP and CDP Smart Hub. All have similar, but different definitions. Not so good for marketers having to navigate through all of these.

Added to this is the fact that CDPs can now do more things than ever – eg Identity stitching, deploying out-of-the-box AI models and multi-channel data activation – making comparisons more important but potentially harder than ever before.  And “CDP” is now a real buzz term, so just about every data management tool wants to call themselves a CDP, adding to the confusion for the marketer.

For marketers looking to invest in a CDP, all of this presents some really key issues that they have to address in order to cut through the complexity and to make the right decisions for their business.

Firstly, what do they want their CDP to do and what challenges will the CDP address? CDPs devour data and data requirements are use-case specific, so being laser focused on the operational use(s) is critical. And with so many different CDP categories, some platforms are strong in some of these uses, eg data management and analytics, and others are better in areas, such as integrations and orchestration. And beyond the definition of the challenge and identification of appropriate platforms, a base case for a CDP has to be built so that the company can evaluate the impact that technology onboarding will have on key areas such as data, content and channel activation. There’s a price tag with all of these – in terms of operative and change management costs – in addition to the expense of the technology license.

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Next, marketers need to understand how the CDP platform will integrate and work with their other technologies. CDPs are designed to integrate with a host of other third-party platforms, so from a technical feasibility perspective, all should be good. But if the company has legacy or custom tools – or on-premise solutions –  they will have to validate exactly what work integration will require in practice.

And as part of this type of assessment, it’s vital to understand where there may be overlapping features between tools. A company’s existing tech stack may have similar or the same features and capabilities as the CDP, at least on paper. For example, just about all activation tools have segmentation or segment-building features in them. But the depth of capability that tools offer differs significantly.

So it’s essential to know the potential usage of the new capabilities a CDP will offer versus what can be achieved with existing tools. You can then decide which process need to be moved to work with the CDP and which can remain in other tools. This might open doors for mitigating license costs if the utilization of some paid features  of other existing tools are left unused.

And once a marketer has worked through all this, they have to ask themselves whether they have the skillsets in-house to manage everything. Data literacy and data model understanding have become essential skill sets to have within operative teams simply to be able to leverage the full potential of CDPs. There is also an increasing requirement to understand the underlying business that the CDP is intended to serve.

And finally, a marketer has to understand how the introduction of a CDP will affect the processes and operations for the members of their marketing team. They will need to map out the operative process from planning to deployment, per channel – and define which tools are used for which parts of the workflow. New features and technical capabilities – especially in data management – a new user interface, and a new process to deploy operations from planning to go-live often creates skill gaps in marketing teams.

As the CDP market grows and offers ever greater opportunities to marketers, I believe we have to do more as an industry to help marketers. We need to move more towards consensus definitions – and maybe less of them. We need to consider the increasing complexity for the end user when we’re building in ever more features and options. And we need to take a more consultative approach to CDPs to take the pain out of the process for marketers and to ensure they get exactly want they need.

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Also catch; Episode 179 of the SalesStar Podcast: The Impact of Al in Sales and Marketing with Ketan Karkhanis, EVP & GM, Sales Cloud, Salesforce