What do you expect from a customer data platform (CDP) and how is it different from a customer master data management system? We’ll explore some key concepts that can hopefully make it clearer why you probably need to have both in your business.
Abbas Makhdum, a Senior Director of Product Marketing for Oracle Marketing suggested that the term “CDP” was first used in 2013 and that customer data platforms are the result of a need for ways to improve customer experience and support omnichannel initiatives. CDPs were supposed to be marketing’s solution to customer data lifecycle management.
Makhdum also suggests that MDM is an IT tool, however, his perspective is tied to the belief that MDM solutions are merely technology stacks deployed to consolidate, cleanse, and augment customer master data (and perhaps others) and synchronize it with other business applications, business processes, and analytical tools. This belief ties to a limited recognition of the different ways that MDM solutions can be deployed, or what are referred to as “approaches to MDM“.
CDP functionality
Per an article by Seth Earley on CustomerThink.com, the following diagram illustrates the ways in which a CDP can function and how it can be instrumental in digital transformation.
In the diagram, Earley suggests that each layer contains “necessary functionality” that may be facilitated by other systems or be an inherent part of the CDP.
It very quickly becomes clear that within the three elements of, data, signaling, and orchestration, some contain functionality that diverges from the needs across the business beyond the marketing team and those responsible for building ‘top of funnel’ demand generation. Accounting for example may not care at all about campaign history.
So the next question, is how does this view look different for MDM?
Needs for digital transformation
This has been discussed before, but it does well to remember that while technology adoption can be transformational, for businesses, the overarching purpose of implementing solutions is principally driven by a desire to improve organizational efficiency and effectiveness and that digital transformation is just one such way of doing this, using digital technologies.
You could argue that an engineering firm that moves from hand-drawn engineering drawings to computer-aided design (CAD) drawings, has undertaken a digital transformation of the design process and that is further augmented when there is the move from 2D drawings to 3D drawings. Implementing a digital library for cataloging the drawings with metadata tags based on what those drawings contain, extends the transformation initiative further. The library could be a part of the CAD initiative but could equally be independent. The library can catalog 2D and 3D drawings, it could even catalog digital scans of paper drawings.
In terms of raw functionality, the Pretectum CMDM platform for example, allows you to create master data definitions for the customer as Business Area specific schemas – you can have one or more definitions of the “customer” and then accompany the definition with validation criteria and characteristics that articulate what is acceptable in the shape, content, and form of the data.
Data is added as individual records or in bulk as datasets – you can add one or more connections to systems or datasets from files to start populating the underlying data structures that have been defined. You can then clone, abstract, extend that data as required, and maintain history and lineage around the data and data change
An optional review stage can be added, allowing participants to examine the data that has been added and compare, filter, and evaluate the data relative to the schemas that you have defined in the first stage.
Schemas and datasets can be edited and then, based on the results of an optional review stage, a user may choose to adjust the master definition or may wish to discard some or all the data or in fact change the data based on algorithmic criteria, in bulk or manually record by record, attribute by attribute. This same functionality can be extended for specific attributes to partners and end customers through CRM, CDP, ERP, Mobile, and Website integration using Pretectum CMDM APIs.
You are also able to determine and set the dominant characteristics that might influence the data master definition including the use of ranges, picklists, data types, and patterns.
Pretectum sees parallels with eCommerce, POS, ERP, CRM, CDP and MDM solutions. Each of these types of technology brings distinctive functionality that is used by different stakeholders in different ways to solve very targeted problems. Some of them solve many problems and the inevitable sometimes happens, wherein functionality bleeds over between systems making it hard for the business to decide which to choose or whether to live with redundancy in the processes and methods.
The transformation initiatives which involve customers can be viewed as either about customer management, transactions or reporting.
The MDM Focus
MDM focuses principally on the management aspects of the customer with a respectful tip of the hat in relation to the duties performed by those trying to grow the business through marketing initiatives (CDP), the transactional systems (ERP, CRM, eCommerce, POS) and the reporting, analytics, forecasting and insights platforms.
Pretectum believes that where these other systems fall short, is either in the complexity of their implementation when focused on data management tasks, or their inability to unify the relationship over common data. We know this is a problem because even when these other systems are implemented with supposed master record management capabilities, they’re found to fall short of the varied expectations of the diverse teams that are expected to use them, or, in fact perhaps worse, access to them is constrained to a few, exclusively.
The Customer Master Data Management (CMDM) can operate in a number of different ways within any given business depending on the deployment approach. This approach is determined by the upstream or downstream influences and requirements of either business units, processes or technologies.
The CMDM does not have to prescribe a single way for itself to be implemented since it can provide active or passive data management.
When active data management is adopted, the MDM is the starting point for all customer data creation tasks – this is the most straightforward, directed, and authoritative way of creating the best customer master data but this approach is quite rigorous and may be viewed as too restrictive by some areas of the business. But even with active data management, whether you choose to use the platform directly or via APIs is a matter of integration design and a focus on the type of experience you want the data capture entity to have.
Furthermore, how you decide to layer CMDM into things like audience management may be quickly defined as a challenge – audience management is a known strength of most CDPs. This might be particularly so if the audience is made up of prospects and customers.
For CDPs that focus heavily on prospecting, you may not have enough data about the prospect for the records to pass your data quality rules when integrated with CMDM.
For customers, you may have many more attributes than a CDP would ever need but that’s because some of those attributes are of specific interest to accounting, logistics, or compliance.
If you had any doubt about the nuanced complexity of comparing CDPs with customer-centric MDMs then consider the fact that even within the bailiwick of CDPs there are different classes. David Raab does a nice job of classifying them into three basic buckets in the article Why Are There So Many Types of Customer Data Platforms? .
Conclusions
We’re not advocates of technology proliferation, but we do believe that for certain organizations, there is an obvious and valuable role to be played by CMDM software solutions.
The capabilities of CMDM technology can help with a myriad of data-related problems that impact the business in cross-functional ways in the full lifecycle of customer engagement.
These start principally with being able to simply sell a good or service but they quickly become obviously valuable to marketing teams too, when the mission is to formulate repeat transactions, cross-selling, and up-selling. The level of integration and prescription that you will adopt will depend on the process maturity, integration capability, and general systems architecture of all customer data-related operations.
Just as for any other potentially far-reaching digital initiative, organizations need to examine the customer relationship in depth, together with the related processes and their maturity.
Implementation of CMDM is transformative in the back office first, but then with the potential for a complete shift in the customer experience in relation to the potential for personalization and customized engagement but for this to happen, you have to be confident that your business is ready to embark upon such a journey.