Welcome MarTech professionals, experts, and executives!
This week we welcome new Australia, USA, Germany , Poland and Canada subscribers!
In today’s email, I’m taking the opportunity to celebrate our nomination to the TMW100 awards with you.
We’ve been nominated in the Business Innovation category through our work in the Engagement Fabric framework. All our subscribers can access the white paper we published earlier this year in this link.
As a business innovation, the Engagement Fabric is a tool to model highly scalable customer interactions and is created to future-proof business, data, and technology architectures.
We’re a super young company, and our knowledge hub concept for MarTech is growing daily. However, this nomination only inspires us to keep working hard to bring innovation closer to our community and make it accessible for anyone to take advantage of it.
A people’s choice voting is also happening in the TMW100 awards, and we would be grateful if you could register your vote for Enterprise MarTech 👉 here.
With that being said, please allow me to go back to what seems to be the MarTech industry's favorite topic: the Customer Data Platforms!
There was a recent three-part publication from Andrew Birmingham at Mi3 analyzing the current state of the market for CDPs in Australia and New Zealand. It’s a great piece of investigation and information, especially if you’re a CDP vendor or work for one. Perhaps it’s not as insightful if you are trying to determine if your current CDP investment could be improved or if you’re deciding when, why, or which CDP solution to implement.
No matter what, it seems we still need to talk and discuss CDPs. So here I leave you with an analysis and thoughts on the role of CDPs in the enterprise today.
What is a CDP?
In short, it is software that helps you collect customer data, individualize it, and share it. Anything else is adornment.
I’m being blunt because a lot of what drives the discussion around CDPs today is only semantics and is generally more of the marketing jargon utilized by vendors in trying to differentiate from other solutions. But I’ll flesh out some key aspects in the following sections of this article.
What’s the background of CDPs, and what has been their evolution?
Since the early 2010s, the need for customer data centralization was already evident. Though CDPs are not directly related to Tag Management Systems, the “centralized management” philosophy of TMS gave CDPs inspiration for what software solutions in marketing technology could look like by simplifying the management of scattered customer data to be centrally managed, available to marketers without engineering intervention and easily distributed across the ecosystem.
If you dig in the internet archives, you will find that some of the early entrants in the CDP market also had TMS solutions or were originally a TMS.
Approximately around 2015, CDPs were already a consolidated category. And the race was on.
Not long ago, CDPs were considered a “marketer-friendly” tool, meaning no need for IT or Engineering. However, the quick evolution of marketers' needs, regulations, and technology transformed that approach, and nowadays, CDPs are enterprise-level software. In other words, CDPs are part of the architects' toolset and not so much of the marketers’.
What are the different types of CDP?
The reality is that there’s only one type of CDP: the type that works for you. However, in recent years, we’ve seen vendors looking for an edge, adopting new approaches and creating new terminology, again trying to differentiate themselves in an increasingly competitive category.
For us in charge of making software and technology in general work for marketing, it is less relevant if a CDP is a “Real CDP,” “Packaged,” or “Composable.”
At the end of the day, as a component of the MarTech ecosystem, a CDP plays the important role of helping us understand our customers better by collecting the relevant data produced and/or stored anywhere during the customer’s relationship lifetime with the business.
What makes CDPs relevant as a component in an enterprise MarTech ecosystem?
I was asked this question by a Customer Data executive at a bank this week. It’s a very valid question because, in enterprise environments, businesses aren’t necessarily short on customer data, nor are they in data technology. So, why a CDP? What makes them relevant?
CDPs do three simple things at a high level. 1) Collect customer data, 2) Create and maintain individual customer profiles, and 3) Share customer data with other systems.
Now, all these functions are enhanced and elevated by the ability to collect data natively on digital channels and upstream systems, perform validations identification, apply business rules, expose APIs, and streamline operations with easy-to-use UI.
Of course, each vendor approaches all the above in a different way. This is what I always say: each CDP, and any other software solution, is an implemented opinion on how to solve a specific problem. So, the relevance of a CDP in your ecosystems is determined by your opinion on how a particular CDP helps you solve customer data use cases and not by their features.
How to determine the need for a CDP?
Implementing a software solution in an enterprise environment requires careful planning. However, a few clear signals indicate that implementing a CDP could be a good option for a business.
When reliance on data engineering and data warehousing is too evident in marketing operations, and the resources required to provide customer data for ever-evolving marketing use cases become a burden, it’s a good time to think of a CDP to streamline and enable marketing use cases.
Surprisingly, outside of the enterprise data world, for businesses with less complicated data architectures but equally dynamic marketing needs, considering a CDP as the cornerstone of the customer and marketing operations can pose an advantage and leap forward the ecosystem's capabilities.
Are there alternatives to a CDP?
This is an interesting question. The capabilities provided by modern CDPs are sophisticated; therefore, finding alternatives to a CDP is less about the solution than about the use case. We’ve seen large companies doing well without a CDP where data strategies are well aligned, and skills and capabilities around data management are mature. CDPs seem a right fit for others where these skills are not so mature, but onboarding becomes challenging.
On the other hand, as we hinted before, some other platforms or solutions have similar capabilities to CDPs. Given the convergence in terms of data ingestion, connectivity, customer profiling, and sharing of these platforms, depending on the use cases, they could be valid alternatives to a CDP implementation.
What’s the best approach to onboard a CDP into an enterprise MarTech ecosystem?
The number one prerequisite to onboarding a CDP successfully into the ecosystem is having a clear picture of which use cases a CDP will enable. As a reference, this could be one or many of the following:
- Media spend optimization: In this case, a CDP generally replaces a DMP to produce “better” audiences based on behavioral data and individualized analysis of customer profiles.
- Customer Profiling: This enables a complete understanding of individual customer profiles across their interactions with the business across all touchpoints.
- Customer data centralization: This is our least preferred approach; however, for many businesses, implementing a CDP to increase their maturity in customer data management could be a valid use case.
- Customer Journey Orchestration: In this less evident use case, a CDP can turbo-charge the implementation of customer decisioning and journey orchestration by doing the heavy lifting and providing immediate access to relevant customer attributes to orchestration engines. A big watch-out goes to the duplicity of functions of these two solutions.
In conclusion, what are the expected benefits of implementing a CDP?
Any modern MarTech ecosystem is expected to have CDP capabilities integrated to power advanced use cases.
We have explored some of these benefits at a high level, but at the very minimum, a CDP should enable an accurate and up-to-date view of individual customer profiles.
In simple terms, a customer profile should contain all the relevant data attributes of a customer throughout the life cycle of interactions with the business.
Building on this view, a CDP should enable insights into the customers of a business as well as the mechanisms to make those insights actionable in a contextualized manner at each customer interaction.
Don’t expect a CDP to be the silver bullet to all the customer and marketing use cases, and don’t expect it to be perfect from the beginning.
The path to a successful CDP implementation and operationalization is progressive and should be approached as an iterative process.
