In the past few years, I have written about CDPs, what they are and what their value is – or rather can be. My definition of a CDP that I laid out in one of my column articles on CustomerThink is:

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.

Everyone (and their dog) tells you that you need a 360-degree view on your customer, right?

According to Techtarget, the “360-degree customer view is the idea, sometimes considered unattainable, that companies can get a complete view of customers by aggregating data from the various touch points that a customer may use to contact a company to purchase products and receive service and support.”

And you are fully sold to this famed concept and term.

In this case, I am sorry for spoiling your day. You in all likelihood do not have it, you do not need it, and here’s the kicker: You do not want it. The 360-degree view on the customer is just another case of too many people using too many too big words.

You are asking why? Let me explain.

I fully get it. The customer is your North Star, the guiding light, the one reason for your company to exist. Your company is customer centric, you are looking outside-in. Your company’s purpose includes to help your customers fulfilling their needs and desires, thereby making a profit. And you are successful doing this.

No doubt, you are on the right way.

And indeed. What is needed to follow this way in reality involves collecting data about your customers. A lot of data. Master data, transactional data, behavioral data, consent data, structured and unstructured; you name it. Over time, this becomes a veritable treasure trove, if collected and used correctly.

Even if not.

When doing it right, you have already broken down many, ideally all, of the data and organizational silos that prevent you from communicating with your customers effectively and offering them the information and solutions that they want, the way they want it.

Don’t get me wrong: This is commendable, the right thing to do if done with the customers’ interest at heart (apart from being within the limits of what is legal and not creepy, while also keeping own commercial interests in mind), and a precondition for what you really want.

But then, what you have implemented until here is something akin to what big data was. A data lake. Yet another concept of earlier days. This is not helpful. What this result resembles is the big box of unsorted Lego blocks that my kids have in their playroom – yours likely, too.

It is an unsorted collection of data, maybe even all data about the customer that there is. Some of it is valuable, some of it is not. Some of it loses value over time. Some of it is valuable only in some situations.

And here we are touching the crux of the matter. This data is valuable only if it is applied to a situation and with a purpose.

Of which there are mainly the following four:

• The customer’s current situation or position in her particular journey
• The customer’s objective: the job she wants to achieve at this very moment, along with her state of mind
• Your current situation and ability to support the customer’s journey
• Your objective: providing the best possible solution for the customer first in this step of her journey, then for her destination

Combined, these four points make up the main part of the context of the interaction. And this context is crucial for meaningful interactions that potentially need to happen in real time or near real time. All the more if the interactions shall happen in an automated way and/or at scale.

What you really want

Let me exemplify this with two analogies.

What you want to achieve is similar to navigation. Just, for the sake of the example, let’s simplify navigation a little as it is quite a science.

The customer is your North Star. The North Star provides you with all the data that you need. The customer’s and your current situations give the current or starting position, your respective objectives provide the destination. In between lies the customer journey. In order to get from the current position to the destination you need to keep the North Star visible, not obscured and at a constant angle. In other words: You need to have a certain view on it.

Another way to explain is an analogy used by Nicole France in a conversation that we recently had: What an ER doctor needs to know about a patient is different to what a GP needs to know. The purposes of the visits and what needs to be done are totally different. Still, to make good decisions, both doctors need to have a good base of customer data.

What you therefore really want and need, is not a 360-degree view, but a contextually relevant and actionable view on the customer. At any given relevant point in time, via any channel, whether the customer initiates an interaction or whether you initiate it. At any given point in the customer journey.

Jon Reed, co-founder of diginomica finds that a 360-degree view is aspirational, we “at best can try to anticipate what they are looking for in a focused moment” and that ”opt-in data, earned over time reduces the need obsess about fully understanding the customer every moment” He continues with the question “Which contexts can we help them with?”

The goal is contributing to the fulfilment of the customer’s job to be done.

This requires having a comprehensive and accurate view on the customer as a precondition. It is therefore also important that the customer voluntarily and explicitly provides information to reduce the guesswork that algorithms need to do and to increase the accuracy of your actions and replies.

You see? You do not want a 360-degree-view on the customer, but something far better.

What do you think? Ask me!

#CRMKonvos #17 - The dark side of the Cloud - danger, hope, liability, subscription, privacy ... are they all gone? Quo vadis on premise and managed services? We are looking at the dark side of the cloud, its effects, chances and possibilities.

We are also analysing the acquisition of Emarsys by SAP, do a little breakdown of the Microsoft cloud services that got announced last week (MS Teams anyone?) and general perspectives. Is the coveted 360 degree on the customer an illusion? And there is some harsh reality facing some suboptimal corporate structures. Fair play, as lived by Zoho, is another topic to be covered ...

Expectations towards SAP and its Customer Data Platform CDP++ are going towards the next level. Is SAP planning to destroy the silos to create more transparency? Is CDP really some BS (hint: not really) or can it be used in a valuable (for the customer) way)? A CX platform or at least a #COTP (Customer oriented Transaction Platform) are possible ways.

Lots of ground to be covered.

This episode is in German

During this episode we talked with Mitch Lieberman who has quite some experience in the CRM industry, on the vendor- and analyst side. He was with Epiphany, Sugar, and with G2, to name but a few.
He has the insight and the sharp mind that makes this conversation particularly interesting, without me diminishing the other ones, though.
Mitch certainly got our grey matter into high gear during our conversation that started with CX, went into a solid discussion of the value (what is it?) of Customer Data Platforms, CDP, on to conversational systems - and back. Btw, what is a CDP? Let Mitch provide his interesting view.
We learned a lot.
You can, too.
This conversation is in English, apart from a few minutes at the beginning and the end.

The Single View on the Customer is the Holy Grail

What does It Mean

• Has open interfaces to support the real-time connection of current and future source data systems in order to stay abreast of activities, behaviors, and intents. The data streams received by the system are continuously used to feed and refine models that determine the contextually right information to the customer
• Collects and meaningfully manages this data and creates a rich and dynamic customer record, so that the customer’s context, behaviors and interests can get used to provide positive experiences to the customer by execution applications. This rich and dynamic customer record is used in combination with other data to deliver contextually relevant messages to the customer
• Offers an advanced analytics engine with predictive and learning capabilities in order to create micro-segments and segments of one in real time, using intelligent, predictive models, and that can discover in real time opportunities of interest for the customer, based upon the current context. This engine is responsible for continuously adapting to changing contexts and interests, so that the company’s messaging stays relevant. It is the core of the system.
• Has open interfaces to support the real-time connection of current and future, not only marketing, execution systems that ask for and deliver the right content, based upon the models’ results, in real time, and via the right communications channel.

The Solution?