Why is Analytical CRM So Confusing?

I ‘found’ another article that I wrote back in 2002 when I was working in Product Strategy for Oracle’s CRM team.   The article was picked up in a couple of publications including The American Banker, CRMGuru and Information Management — and fortunately it still lives on as a link.  Before it disappears completely, I decided to add it to as a blog post in my Social Media blog.

Nearly 9 years later, the conclusions are still valid.  Analytics are more important than ever, ROI is still difficult to prove and elusive, and the market continues to be fragmented (especially with the advent of new social media monitoring and analytics tools).

The original article as it appears in Information Management is below.


Why is Analytical CRM So Confusing?

Why is analytical CRM so confusing? Most people agree that the analytical CRM market is growing rapidly – but there is no standard definition or agreement of what constitutes analytical CRM or CRM analytics. The hype has definitely arrived as witnessed by CRM analytics appearing at the top or “Peak of Inflated Expectations” in the famous Gartner Hype Curve (Scott Nelson and the Gartner CRM Symposium – February 2002).

Market Size and Growth

Some specific data points from multiple sources on the size and growth of the market include the following assertions:

  • IDC estimates that the CRM analytics market will surpass $1.5 billion in sales by 2005.
  • AMR Research estimates that investments in analytical applications will grow at nearly double the rate of operational CRM systems. The market will expand to nearly $4.4 billion by 2005, which represents 19 percent of the CRM market.
  • META Group’s recent survey of more than 400 enterprises found that in the next 12 to 18 months customer analytic solutions will be purchased more than any other type of CRM offering.
  • Jupiter Media Metrix says that more than one-quarter of all U.S. firms will spend at least $500,000 on customer-based technologies over the next two years. Much of the investment will center on analytic software ringing in at a healthy $8.7 billion in 2006.

Analytical CRM Definition

The market space for analytical CRM is ill defined and the term “analytics” is used differently by nearly every vendor. The definition of analytics ranges from simple concepts such as reports and reporting to more complex topics i.e., profitability, data mining and real-time personalization – and everything in between. The claims of most vendors are over-hyped in regard to their analytics capabilities and many vendors add to the confusion by including“analytics” in their product names. What is the right definition?

Ultimately, CRM consists of both analytical and operational components, and the goal is to maximize overall customer profitability while maintaining customer satisfaction. My analytical CRM definition is multi-faceted – analytical CRM is the critical foundationfor intelligent analysis and application of customer information across an enterprise. Analytical CRM also serves as the glueor connection between the operational customer-facing applications such as sales, service and Web channel and the analytical back-office systems, business intelligence solutions and customer data warehouses. Finally, analytical CRM is the feedback loopon the front end of real-time customer interactions or the back-end scorecard for analyzing what happened and how to improve the next customer interaction. Another way to look at analytical CRM is that it fulfills the critical first steps of the now-famous and often-copied Peppers and Rogers 1-to-1 approach to CRM. Their 1-to-1 mantra is IDIC or identify, differentiate, interact and customize. You cannot intelligently interact with your customers or customize your products and services until you identify and differentiate them.

Analytical CRM Components

Analytical CRM is also confusing because it consists of so many different components, many of which are not normally considered as CRM solutions or provided by traditional CRM vendors. Note that any one or all of these components could be considered an analytical CRM solution and that it is not necessary to include every single subcomponent in your own solution.

Data Warehousing – Data warehousing technology and a comprehensive customer data warehouse are keys to making analytical CRM work. Ideally, there should be a single customer repository for all transactions, behaviors, preferences, customer profitability and valuation, and segmentation treatments – but the reality is that most organizations have created silos of data and it will not be easy to coordinate all of the sources initially. Data warehousing technologies include the extract, transformation and load (ETL) functions to move data in and out of legacy systems and disparate data marts into the comprehensive customer data warehouse.

Data Enhancement – This is a broad category consisting of data cleansing, data enhancement and customer profitability. Data cleansing includes cleaning up, standardizing and linking the data as it is loaded from the legacy systems. Data enhancement involves adding external data such as demographic or spatial information. Customer profitability is the application of identifying historical, current and projected value of your customers and then using it to improve segmentation and to implement customer strategies. Customer profitability analysis is one of the most important and underappreciated components of analytical CRM.

Data Mining, Personalization and Segmentation – These solutions are related but are sometimes perceived as vastly different because of how they arrive at their answers. Ultimately, they are performing the same task – using various modeling techniques to predict, tailor and present customers with better messages and increase the odds of acceptance.

Business Intelligence – Business intelligence solutions range from ad hoc query and OLAP analysis to portals, standardized reports and balanced scorecards. Business intelligence provides users with access to the customer information and will be different for different types of users. Business intelligence is the window into understanding the analytical information.

Marketing – The marketing or campaign management application is generally seen as the link between the analytical and operational worlds. The marketing application manages the marketing process by creating, executing and tracking offline batch and real-time offers to customers. The execution of marketing offers is the link into the operational or customer-facing CRM solutions and the reason marketing is sometimes seen as the Trojan Horse of the traditional CRM world.

Data Movement, Workflow and Integration into other CRM Applications – This last category is the glue that will connect the analytical and operational solutions into a cohesive and seamless total solution. Without getting into too many details, the emergence of XML as a standard for integration will be a huge enabler. Workflow and business-rule driven capabilities are also key. Ultimately, suites of CRM applications will dominate the landscape and minimize the integration issues – but it will take time and money to swap existing systems for new systems.

What Does All This Mean?

In the short term, it means the following:

  1. The analytical CRM market will remain fragmented and confusing to both the initiated and the uninitiated.
  2. Analytical CRM is necessary and crucial for truly understanding customer’s needs and for generating sustainable ROI on CRM investments.
  3. Companies buying solutions and the analyst community will have to be diligent to keep the vendors honest about their capabilities.
  4. Companies will have to incorporate a best-of-breed or point solution approaches – no one vendor will be able to satisfy all of your business needs.
  5. Companies must plan for the future by defining their analytical CRM vision, but implement in a controlled and stepwise fashion.

In the long run, analytical CRM and operational CRM will move closer together. This will probably always be a multi-vendor solution due to the complexities and breadth of components required.


2 thoughts on “Why is Analytical CRM So Confusing?

  1. Pingback: Why is Analytical CRM So Confusing? « Social Media Musings by Tom … » Veille CRM

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