The Customer Data Platform’s Position in Digital Transformation (CDP)

Both Digital Transformation (DT) and Customer Data Platforms (CDPs) have a lot of overlapping, vague, and catch-all terminology that doesn’t help potential customers make decisions. In reality, it’s a jumble of buzzwords. The definition of digital transformation is hazy, and the word seems to mean different things to different companies. Despite the undeniable importance of providing a 360-degree view of the consumer that a CDP can offer, the industry cannot agree about what a CDP is.

Despite this, the two are very intertwined. The ability to provide a holistic view of the consumer is obviously a vital aspect of digital transformation, but CDPs can only have their maximum value in the sense of a well-thought-out digital transformation. This article aims to sort out the meanings and roles of each so that it’s clear how digital transformations and CDPs can interact.

Is it possible that the term “digital transformation” has lost its meaning?
The term “digital transformation” can refer to a variety of things, including tools, technology, business processes, customer service, artificial intelligence, and every other buzzword that marketers can think of. IT automation and bringing services online are among the definitions offered by analysts and vendors, as are developing new business models, adopting a “digital first” strategy, and developing new business processes and consumer interactions.

The difficulty with digital transformations is that they necessitate a wide reach in order to accomplish a specific objective. Streamlining the customer experience or moving more revenue to digital channels are two common goals for digital transformation programs. If the goal is to improve the end-to-end customer experience, the reach could include all touchpoints and customer-facing technology, as well as supporting processes and back-end technologies. The aim is to increase customer satisfaction. On the surface, it appears to be straightforward and centred. However, with so many moving parts (departments, functions, technologies, data sources, processes, and so on), the complexity can quickly become overwhelming.

Since the spectrum is so wide, maintaining momentum and securing long-term support can be difficult. Sponsors in one group we partnered with were calling for a business argument again – in the middle of a multi-year campaign – despite the fact that the business case had already been made to finance and approve the programme two years prior. The need for re-justification slowed the initiative and created a lack of vital momentum because much of the work was fundamental and not specifically tied to an ROI. Programs that touch various systems and areas of the business must be broken down into sub-projects, each of which would possibly have multiple workstreams. Identifying intermediate wins and ROI will help keep sponsors and partners involved, and it should be done as part of the planning process. CDPs can be useful in a variety of situations during large-scale transformations.

Understanding the limits of functionality when defining a CDP for your company
The phrase “customer data portal” has also been a bit of a misnomer. CDP as a broad definition of a tool or piece of functionality is not very useful to business leaders, even though classes of CDP can be described as having specific functions. What you want CDP to do for you is the real issue. This will point you in the right direction for the right mix of features and functionality.

Many forms of software systems that have tackled the problem of customer records and customer interaction in the past overlap with CDP technology and features. Master Data Management (MDM), Customer Relationship Management (CRM), and Marketing Automation (MA) are only a few of the technologies available.

Customer Master Data Management programmes aimed to create a single customer record, but did not always involve the consolidation of interactions across systems until those interactions changed the key customer record. MDM software and programmes are generally geared toward a technical audience and do not typically provide features to assist marketers in their efforts to communicate through multiple personas and segments.

CRM systems are designed to monitor interactions at both the account and individual communication levels. Most CRMs, on the other hand, aren’t designed to incorporate real-time or near-real-time behaviours like clickstreams, or to feed the data back to other applications that need consumer behavioural and preference data. We are seeing a convergence as CRMs become more sophisticated and marketing automation systems with personalization capabilities subsume a greater degree of functionality from other tools. Hubspot, for example, which started as a “inbound” marketing automation (MA) application (used to carry people to the web through a variety of methods such as SEO and content marketing), now incorporates CRM, social media integration, and a slew of other features that allow for more personalised experiences based on customers’ “digital body language.” On many fronts, they also fall short of the features found in CDPs.

For one thing, CDPs may collect both anonymous and authenticated data (via cookies and tracking pixels). The majority of CRM and MA software focuses on known users. CRMs prefer to concentrate on revenue and pipeline operation, while CDPs collect data on the entire customer journey. CDPs are designed to capture and integrate vast volumes of data.

CDPs’ main functionality is to provide a single database of customers, but depending on the technology’s lens and how the company views the problem, they may also solve a variety of downstream issues. It will also be affected by their perceptions of how their organisation, role, or department should address the issue. Customer interaction, analytics, attribution, and segmentation are all available via CDPs, as well as personalization, message delivery, and campaign management.

The type of CDP required by the company will be dictated by how they frame the task and the sophistication of supporting processes, as CDPs come in a variety of flavours. If a company wants to provide a personalised web experience and use CDP functionality, for example, certain prerequisites must be in place, such as the right content management system, high-quality data, and a thorough understanding of what personalization means to their target customers. What does real personalised messaging entail? What are the characteristics of a customer that distinguish messages and offers? This situation would necessitate the use of a CDP with journey orchestration capabilities, which not every CDP has.

The following diagram depicts the various functions of a CDP:

Each layer in this diagram represents required functionality that may be included in a CDP or provided by other systems.

Most people think of CDP features – data integration and normalisation – as a way to consolidate information at the bottom layer. The next “signal” layer decodes data from different systems as the customer’s digital body language and provides it to the orchestration layer (where the user experience is generated). It’s worth noting that the orchestration layer, which is where systems react with offers, content, product suggestions, and other interactions, feeds these interactions back into the CDP’s signal layer. The CDP can either drive a customer engagement network where digital assets are assembled and presented, or it can provide the processes and intelligence behind a tailored and personalised experience and be the source of dynamically assembled content and data.

The lines of functionality have considerable overlap – making the definition of those boundaries critical when selecting, configuring and deploying a CDP.

What value does a CDP add to the digital transformation process?
Any transformation that involves the customer (and most do) will need to collect and process data about the customer and their interactions in some way. Consider the consumer partnership to be a conversation. That conversation can start with any interaction. A internet quest, as well as a phone call to a call centre, may be part of the conversation. Responding to an advertisement or an email message is a part of the conversation. Consider the CDP as a way to bring together disparate discussions and experiences that happen through multiple departments and touchpoints.

A CDP receives signals (the customer’s digital body language) and incorporates them so that other systems and processes can react. The answer may be anything from a website offer to a personalised email to how a call centre customer service representative handles an issue. When you apply this definition to everything from chatbots to social media ads to customer service troubleshooting scripts, the CDP has the ability to play a huge role in the customer experience.

Because a CDP can operate at any point in the customer journey and interact with any type of marketing, sales, or customer experience technology, the first step in a digital transformation programme involving CDPs must be the definition of the application’s boundaries as well as an understanding of the scope of processes, systems, and data to be included. This advice is applicable to every significant re-evaluation of how applications are used in the enterprise, but it is especially relevant because the framework has such a large effect on other applications.

Decisions, Data, and Delivery
In his article on the various CDPs, David Raab breaks down major features such as creating a unified view of the customer (data integration and consolidation functions), “decisions” – using metrics, analytics, and human judgement and creativity to determine what to say or off, and so on.

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