Clearing Up Customer Data Management Confusion

CDP 101|[wtr-time]

Clearing Up Customer Data Management Confusion

Developing a strategy to optimize and improve customer experience (CX) is not new. After all, Burger King launched its famous “Have It Your Way” campaign many decades ago.

Legend has it the fast-food chain even went as far as replacing all of the doors in all their locations so they opened both ways. (Let the customer decide if she wants to “push” or “pull” before ordering her tailor-made Whopper.)

Times have changed quite a bit since then.

The deep bench of customer data management (CDM) tech brands now have at their disposal to support strategic CX initiatives has evolved substantially in recent years.

Simply put, CX is now the ultimate competitive differentiator. But mastering it means mastering customer data management. Fail to do so, and you risk losing to competitors.

Specifically, those that collect data directly from individuals, ensure strong first-party data quality, and leverage that customer information accordingly across their teams.

It’s now a race to level the playing field with companies like Amazon and Netflix.

These businesses, and other major players like them, have already invested in best-in-class customer databases that unify first-party data in a central location and make the single customer view the center of their marketing and tech infrastructure.

single customer view

5 keys to customer data management

You’ve probably read dozens of studies on CDM and related data-driven tech tools.

But you’re probably swimming in acronyms that do little to provide clarity on a path forward. So, consider this post the CliffNotes® on customer data management.

1) Customer data management is a practice, not a type of technology.

When it comes to customer data management (and, in turn, improving customer retention and customer loyalty) the tried-and-true framework of ‘people, process, tech’ applies.


A chief data officer (CDO) or head of CX may lead a CDM effort. But it should really be a collaboration between marketing and CX and their counterparts in data science/analytics.

It’s vital both sides work to define the company’s data strategy and clearly define use cases that map to business outcomes. Otherwise, you’ll end up with incomplete, disconnected, or uncoordinated outcomes that don’t support your use cases.


Analysts also caution companies not to ignore the importance of establishing internal data governance standards. Especially in light of ever-changing privacy regulations.

Without this, you undermine your larger goal of unifying data into a single customer view to improve customer experience. These standards should answer questions like:

  • How will you maintain your CDM practices?
  • What checks will you put in place to enforce them?
  • How often will you revisit the policies?
  • Who is responsible for flagging necessary changes?

Once you have the people and processes to inform your data strategy and use-case roadmap, it’s ideal to evaluate customer data management technologies to enable them.

2) Stop trying to build a single customer view for everyone.

Most analysts will say capturing every possible data point for customers to be used in every business function (marketing, customer service, ecommerce) is not practical or necessary.

(Not to mention the undue risk it would create in today’s consumer privacy landscape where transparency around data collection and purpose is expected thanks to GDPR and CCPA.)

Instead, start building a single customer view explicitly designed for marketing/CX.

Companies that do this well don’t lose sight of what they are trying to do with the data — both in the short and long term. That means being thoughtful about unifying the data that actually matters for marketing- and CX-centric use cases.

Example #1

Does marketing really need to know every shipping address a customer has ever used when ordering online from the business? Or, is it more important, from a data activation perspective, to instead simply know where the customer lives and shops?

Example #2

Does marketing really need to know every single page a customer has visited on the website? Or, is it more helpful to know that a customer’s browsing behavior exhibits a high affinity for a specific type of content or certain product or service?

3) Identity should be the core of your customer engagement model.

You may be thinking about customer data management opportunistically for a digital transformation. Or perhaps because you need to address privacy compliance.

Regardless of the specific reason, your customer engagement model should be the central focus of your day-to-day customer data management efforts.

That is, design a model that puts the “identity” at its core. And that means managing customer data at an individual level and designing for an optimal customer experience.

To improve CX, Gartner noted it hinges on the ability to recognize individuals and their interactions with you across channels. However, not every type of CDM tech today is designed to do this with the speed, accuracy, and scale necessary to succeed.

This is why the pairing of confidence and utility is key when it comes to a unified, persistent customer profile or single customer view.

It’s not enough to get a tool that provides a unified profile with a high degree of confidence (in terms of accuracy and completeness) if it can’t be used when and where you need.

Conversely, there is limited value in activating lifecycle marketing programs and personalized experiences based on a unified customer profile that is incomplete.

(Or, worse, one that’s inaccurate or lacks individual consent preferences.)

single customer view

4) A best-of-breed technology approach is preferable to a one-size-fits-all strategy.

A recent Gartner report stresses your customer data management processes and infrastructure must be flexible and adaptable. And that applies to your CDP technology.

So, it’s no surprise Gartner’s marketing technology survey reveals many businesses now prefer a best-of-breed technology stack. (That is, as opposed to investing in integrated cloud suite with walled-garden limitations.)

The preference for a best-of-breed martech approach has led to increased adoption of customer data platforms (CDP) like BlueConic as the foundation for establishing a single customer view for marketing and other growth-focused teams.

When you unify all types of customer data in a CDP, which sits at the center of your tech infrastructure, you can orchestrate one-to-one marketing in every lifecycle stage. And that is the starting point for building a top-tier CX program.

5) Customer data management technologies don’t fit into distinct buckets.

Despite everyone’s best attempts, customer data management tools can’t be easily mapped to distinct buckets. That’s because there are overlapping capabilities among them, which is why there is so much confusion around CDM tools.

That’s why it’s important to clearly define your use cases before evaluating business technologies. It’ll help you better understand what you already have and what you still need.

This confusion has been particularly pervasive with CDPs in recent years.

Gartner covers this confusion in its 2020 Market Guide for Customer Data Platforms. It states much of the CDP’s functionality is not new because it exists in some form in legacy tools.

However, it is the productization of these features, along with the optimization for real-time use cases, that makes a CDP valuable, modern customer data management solution.

Adding to this confusion is the fact that CDP, as a category, is not homogenous.

Heritage and architecture matters. Some CDPs over-index on operational data management. But they also offer little value when it comes to utility and activation of first-party data.

On the flip side, some CDPs over-index on marketing personalization. (Particularly in web and mobile channels.) But they lack the ability to truly unify customer data across channels and sources with the high degree of confidence companies need today.

Only a pure-play CDP — such as BlueConic — is designed to deliver on both.

The right CDP (one built on a profile database architecture) won’t lock you into a narrow set of use cases. In fact, this CDP will enable you to get value quickly from use cases.

What’s more, it’ll offer your teams the agility and flexibility required to adapt to changing business conditions and future, yet-unknown use cases.

And, most importantly, the ideal CDP helps all your growth teams adapt without punitively taxing you for it — whether that comes in the form of time, resources or money.

Download Gartner’s 2020 Market Guide for Customer Data Platforms today to get insights into CDPs’ unique customer data management capabilities.

gartner research

See what BlueConic can do for you.

Whether you’re looking for operational efficiencies or improved marketing effectiveness through data activation, our customer data platform can help.