Digital Transformation (DT) and Customer Data Platforms (CDPs) both entail a great deal of confusing, ambiguous and catch-all terminology that does very little to help prospective buyers make decisions. In fact, it amounts to buzzword soup. The boundaries of digital transformation are vague, and the term seems to mean something different for every company. And despite the undeniable value of having the complete view of the customer that a CDP can provide, the industry does not actually agree on what a CDP is.
Yet the two are highly interdependent. The ability to have a comprehensive view of the customer is clearly a critical part of digital transformation, and at the same time, only in the context of a well-conceived digital transformation can CDPs provide their full value. This article is intended to sort out the definitions and functions of each one in a way that clarifies how digital transformations and CDPs should work together.
Has “digital transformation” lost its meaning?
The phrase “digital transformation” can mean anything and everything — tools, technology, business processes, customer experience, or artificial intelligence, and every buzzword that marketers can come up with. Definitions from analysts and vendors include IT modernization and putting services online; developing new business models; taking a “digital first” approach; and creating new business processes, and customer experiences.
The challenge with digital transformations is that they require a broad scope to achieve a focused goal. Streamlining the customer experience or moving more revenue to digital channels are two common goals for digital transformation programs. If the scope is streamlining the end-to-end customer experience, the scope may include every touchpoint and customer-facing technology along with supporting processes and back end technologies. The goal is to improve the customer experience. Sounds straightforward and – on the surface – focused. However, there are so many moving parts (departments, functions, technologies, data sources, processes, and more) that the scope can become very broad.
Since the scope is necessarily broad, getting sustained momentum and long-term support can be a major challenge. In one organization we worked with, sponsors were once again asking for a business justification – midstream in a multi-year initiative – although the business case had already been made to fund and approve the program in the first place two years earlier. Since much of the work was foundational and not directly tied to an ROI, the need for re-justification stalled the initiative and caused the loss of critical momentum. Programs that touch multiple processes and parts of the organization require a careful breakdown of sub-projects, each of which will likely have multiple workstreams. Identifying intermediate wins and ROI can go a long way in keeping sponsors and stakeholders engaged and should be a part of the planning process. CDPs can provide value in multiple contexts during large scale transformations.
Defining a CDP for your organization – understanding the boundaries of functionality
The term “customer data platform” has become equally ambiguous. While classes of CDP can be defined as providing particular functions, CDP as a broad description of a tool or piece of functionality is not very useful to business leaders. The real question is, what do you want CDP to do for you? That will direct you to the right combination of features and functionality.
CDP technology and functionality overlaps many types of software solutions that have addressed the issue of customer records and customer engagement in the past. These include Master Data Management (MDM), Customer Relationship Management (CRM), and Marketing Automation (MA) technologies.
Customer Master Data Management programs sought to have a golden record of the customer but did not necessarily include consolidation of interactions across systems except when those interactions altered the main customer record. MDM tools and programs are mostly aimed at a technical audience and do not typically provide the functionality to help marketers in their efforts to engage across various personas and segments.
CRM systems are focused on interactions at the account level as well as at the individual contact level. However, most CRMs are not purpose-built to integrate real-time or near real-time behaviors such as clickstreams or to feed that information back to other applications that require customer behavioral and preference data. As CRMs become more advanced and marketing automation systems that have personalization capabilities subsume a greater degree of functionality from other tools, we are seeing a convergence. For example, Hubspot, which began originally as an “inbound” marketing automation (MA) technology (used to bring people to the site through a range of approaches including SEO and content marketing) now includes CRM, social media integration, and many more functions that allow activation of more personalized interactions based on customers’ “digital body language.” They still fall short of the functionality found in CDPs on several fronts.
For one thing, CDPs can capture both anonymous data (from cookies and tracking pixels) and authenticated data. CRM and MA tools typically focus on known users. CDPs collect data on the entire customer journey, whereas CRMs tend to focus on sales and pipeline activity. CDPs are built for the integration and collection of large amounts of data.
CDPs core functionality is building out a unified database of customers, but they can also address multiple downstream problems depending, on the lens of the technology and the way the organization conceives the problem. It will also be influenced by how they believe their organization, function or department can solve the problem. CDPs can also manage customer engagement, provide analytics, attribution and segmentation, and enable personalization, message selection and campaign management.
Since CDPs come in a variety of flavors, the type of CDP needed by the organization will be determined by how they frame the challenge and the degree of maturity of supporting processes. For example, if an organization wants to provide a personalized web experience and wants to leverage CDP functionality, certain precursors will need to be in place, such as the correct content management system, high-quality data, and a detailed understanding of what personalization means to their target customers. What constitutes true personalized messaging? What are the details of a customer that will differentiate messages and offers? The CDP required for this scenario will require journey orchestration capabilities, which not every CDP has.
The following diagram illustrates the ways in which a CDP can function:
Each layer in this diagram represents necessary functionality that may be part of a CDP or that may be enabled by other systems.
Consolidating information at the bottom layer is how most people think about CDP functionality – data integration and normalization. The next “signal” layer interprets information from various systems as the customer’s digital body language and makes sense of it for the orchestration layer (where the user experience is generated). Note that the orchestration layer- where systems respond with offers, content, product recommendations or other interactions – feeds these interactions back to the signal layer of the CDP. The CDP can provide the mechanisms and intelligence behind a customized and personalized experience and be the source of dynamically assembled content and data or it can drive a customer experience platform where the digital assets are assembled and presented.
The lines of functionality have considerable overlap – making the definition of those boundaries critical when selecting, configuring and deploying a CDP.
What does a CDP bring to a digital transformation?
Any transformation that involves the customer (and most do) will need to harvest data about the customer and their interactions and operate on that data in some way. Think of the customer relationship as a dialog. Any interaction can begin that dialog. A website search can be part of that dialog, as can a phone call to a call center. Responding to an ad or email message is part of that dialog. Since the conversations and interactions happen across many different departments and touchpoints, think of the CDP as consolidating those fragmented conversations.
A CDP takes signals (the digital body language of the customer) and integrates those signals so that other systems and processes can respond. That response could be anything from an offer on a website to a personalized email, to how a customer service representative in a call center reacts to a problem. Extend this concept to everything from chatbots to social media marketing to customer support troubleshooting scripts and the CDP can potentially play an incredible wide role in the customer experience.
Because a CDP can function at any point of the customer journey and interact with any type of marketing, sales, or customer experience technology, the first step in a digital transformation program involving CDPs has to be a definition of the boundaries of the application and an understanding of the scope of processes, systems, and data to be part of the project. This advice could apply to any major re-evaluation of how applications are being used in the enterprise, but is particularly important when the system impacts so many other applications.
Data, Decisions and Delivery
In David Raab’s article on the range of different CDPs , he breaks down major functionality as building the unified view of the customer (data integration and consolidation functions), “decisions” – using metrics, analytics, and human judgment and creativity to determine what to say or offer in various customer situations and the actual delivery of content through various channels and devices. Whether these operations are rule-based or leverage machine learning and AI, human knowledge and insight are still at the core.
Technology can help with insights and evidence regarding decisions; however, an experienced brand manager, marketer, or customer specialist determines how to meaningfully engage. Delivery includes the automation, message assembly, distribution, and syndication of content including feedback loops that form the customer engagement engine. The degree of automation and adaptation based on customer responses will depend on the maturity, integration, and architecture of the full digital and off-line marketing ecosystem.
This calls out the need for the company to undergo a rigorous examination of customer journeys, customer lifecycles, supporting tools, data sources, and process maturity in the context of the organization’s market differentiation and go-to-market strategy. A good place to start is with an evaluation of the full marketing stack. The approach begins with a mapping of the customer journey, an exhaustive inventory of all technologies, a sanity check about the importance of each tool to the journey stage, and finally a health check of each deployment.
Using this approach to gain a holistic understanding of the customer engagement technology stack (and supporting processes) will help the organization understand where CDPs can provide specific value and guide the opportunities for focused interventions. The result will be a comprehensive definition of the organization’s requirements for a CDP and a clear plan for successful program execution.