A Customer Data Platform is a software that creates persistent, unified customer records that enable business processes
that have the customers’ interests and objectives in mind.
It is a good thing that CDPs evolved from its origins of being a packaged software owned by marketers, serving marketers.
Having looked at CDP’s as a band aid that fixes the proliferation of data silos that emerged for a number of reasons, I have ultimately come to the conclusion and am here to say that the customer data platform as an entity is increasingly becoming irrelevant – or in the typical marketing hyperbole – dead.
Why is that?
There are mainly four reasons for it.
For one, many an application has its own CDP variant already embedded as part of enabling its core functionality. Any engagement solution that is worth a grain of salt needs the analytical capabilities that a CDP offers, and hence offers them itself. Why do the additional investment of buying things that one already has once more? This only increases cost and IT landscape complexity while acquiring capabilities that partially are already available.
In addition, there is no real and concise definition anymore, with even the CDP Institute differentiating use types and/or scopes of CDPs. If you are looking at what other vendors (Salesforce, Oracle) or analysts (here: Gartner) are saying, the water becomes even more muddy.
The third reason is that focusing solely on customer data simply falls short of requirements. Yes, there needs to be a consolidated and enriched customer record that informs about customer preferences and about their current priorities and behaviors. But this is jumping too short. Good engagements need more than this, but also need to leverage other business data, starting with products, etc. Secondly, “current” is the operative keyword here. Good engagements are in-moment. Interests can change a lot in short periods. This means that older behavioral data is likely to be too old and hence no more really required, let alone helpful. It might outright lead into the wrong direction. There are also GDPR implications: Collecting data for possible later use, even under the pretense of legitimate interest, affects the customers’ data sovereignty. There is the right to be forgotten, and the obligation to collect and use of data for a stated purpose. The purpose has probably become invalid a long time ago. And “legitimate interest” is not covering the storage of data “just in case”, either.
But most importantly, the benefit of a customer data platform lies in advanced analytics applied to consolidated data. And, apart from above mentioned engagement solutions, almost every company has the foundation for both in place already, by means of its analytics platform, a data lake, or a lake house solution. Of course, the necessary machine learning and/or the corresponding queries to fully take advantage of this treasure trove might not be set up yet. But this is not necessarily a reason to go out and buy YAC – yet another CDP.
The future of the CDP
The purpose of a CDP is the activation of data to enable effective customer engagement across departments. This can happen more effectively, if not parts of relevant, necessary data are left aside.
Driven by, and heavily invested into AI, major vendors like Microsoft, Salesforce, or SAP and others have understood this. They are building and providing data platforms and data graphs that help not only in the ingestion, consolidation (and understanding) of customer data but all business data. They support this with a zero-copy approach and are underpinning this with the development or acquisition of sophisticated data management capabilities. After all, it is unreasonable to assume that all business data lies in one single database, with the possible exception of a data lake. At the same time, their applications themselves offer CDP capabilities, especially when looking at modern CRM suites, or marketing systems like personalization engines or (multi-/omnichannel) marketing automation or even customer journey optimization systems. The increased availability of AI strengthens their approach as AI heavily relies on good and complete data.
Vendors like Snowflake or Databricks, again amongst others, are doing something similar, but come from the data lake house angle. They largely rely on their partner ecosystem to complement their capabilities and to consume or leverage the activation capabilities that they offer.
What all these vendors are building is essentially a superset of a customer data platform that I would call a consolidated data platform to repurpose the acronym.
Still, for these vendors as well as all the other ones that the CDP Institute lists, composability and integration are key for success. The reason for this is that in the foreseeable future vendors need to be able to interact across different ecosystems. They need to be able to deliver their capabilities in a modular fashion and/or with a pricing model that supports the modularity that their customers need. Many of them will already have some CDP capabilities and as stated above, they will not want to acquire and pay for capabilities that they already have.
What does this mean for buyers?
Buyers need to follow a think big – act small approach, as the CDP game will increasingly become a platform game. This is a necessity that is mostly driven by AI, which needs data. They need to collaborate, evaluate and iterate.
Collaborate: Buyers need to consider what they already have and what they want to achieve. This sounds easier than it is, as the awareness of what is already available is often missing, especially on the business side. Hence, it is paramount to work with IT.
Evaluate: The CDP game will become more of a platform game. This means that businesses need to think long term as the best results for them likely cause some lock in. Therefore, it is necessary to sit down with at least the main ecosystem partners to identify which of their platforms shows the best – and affordable – fit as a consolidated data platform. Their offerings need to fit now and, more importantly, later. Key criteria in this evaluation are the own inventory of capabilities, the own planned capabilities, and the vendor’s and their ecosystem’s strategy. Also, it is necessary to check for flexibility with a what-if analysis, as the own, as well as the vendor’s strategy, is likely to change over time.
Iterate: Once there is a decision. Implement. Stay agile. Implement in small iterations that deliver value fast. Don’t boil the ocean. And continue to work with your trusted partner to maintain a strategic alignment.
The CDP is dead.
Long live the CDP.
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