Improving Customer Data Integration by Enhancing the Customer Data Matching Process
Information Management Special Reports, December 2005
Gaining a better understanding of customers is critical for any company. However, there are often obstacles along the way. Diverse product and service offerings (as well as other events, such as mergers and acquisitions) often result in segmented, overlapping customer views and data housed in disparate systems. The solution is to consolidate and integrate customer information to create a single view of the customer.
Customer data integration (CDI) is a goal every company should strive for to create a holistic customer view. An essential step in reaching the CDI goal is customer data matching (CDM). CDM is the process of performing customer data consolidation so that customer data housed in multiple, disparate information systems can be combined into a single view. It also includes matching new customer data to existing customer data so that customer records retain their uniqueness.
Obviously a match rate of 100 percent is the ideal. However, due to different data, data standards and data quality levels, the reality is that most companies spend significant dollars to improve their match rates without realizing this nearly impossible goal. The goal then becomes to allocate resources wisely to achieve realistic CDM rates that meet business needs and support the overall CDI effort.
Advertisement
The Business Needs
Without sufficient CDM rates, it is difficult to meet business needs. For example, it is often challenging to cross- or up-sell existing customers because of inadequate knowledge about current product mixes. Good CDM rates are also necessary to measure critical performance indicators accurately, such as customer profitability and customer lifetime value (CLV), so that companies can identify and better serve their most profitable customers.
The applications of CDM also span the enterprise. Improved CDM is a building block for improving most enterprise-wide key processes. Figure 1 below depicts key processes that can be improved through a better understanding of the customer.
Figure 1: Key Processes Affected by the Customer Data Matching Process
For example, in the "market and manage products and services" process, improved CDM can enable companies to:
- Better tie customers to products to determine profitability per product and invest in those with highest yields,
- Understand the behavior of customers with multiple products, and
- Create product development and retirement schedules and determine their impact on various customer segments.
For the "manage customer relationships" process, improved CDM can provide companies with a holistic customer view so they can:
- Determine their most profitable customers, and
- Design more effective customer retention policies and service levels.
Other processes impacted positively by improved CDM include: product and services sales, order management and billing.
Barriers to Achieving Desired Customer Data Matching
Different business units often have different definitions of the term "customer," and these definitions must be coalesced into one enterprise-wide definition. It's essential that all the business units agree on a common definition of the customer, as well as rules for matching customers in different systems and departments. The definition of and the rules for matching customers must also be understood and driven by business needs, not by the IT department.
Additionally, a biproduct of today's merger and acquisition activity is that numerous information systems hold customer data, making it difficult to match customers adequately. As merger and acquisition activities increase, the problem will only be exacerbated.
Poor data quality and inadequate data standards also help create a segmented, inaccurate customer view. Seemingly small variations in a street name, such as "Broad Brook Blvd" and "Broadbrook Blvd," can cause problems in determining whether customer records are truly unique. Incomplete or incorrect customer data matches have significant consequences, including poor customer experiences and incorrect calculation of such metrics as customer lifetime value.
Overcoming the Barriers: Defining the CDM Process
As stated earlier, a 100 percent match rate is practically impossible for most companies - and the effort to achieve that impossible goal can be futile and expensive. As can be seen from Figure 2 below, as more dollars are expended on the process to achieve higher CDM rates, the percentage of matched data per dollar spent decreases dramatically.
Figure 2: Diminishing Returns in the CDM Process
Instead, the focus of the CDM effort should be on maximizing capital investment by trying to achieve CDM rates that help meet business goals, thus obtaining a balance between satisfactory CDM rates and expenditures.
It's also important to examine the root causes of poor CDM rates. The first step in this root-cause analysis is to assess the current CDM process from a business and technical perspective. This means assembling a team with deep knowledge of both the business and data to 1) assess the needs of each business unit that uses the output of the CDM process, 2) evaluate the business objectives and 3) set reasonable CDM goals.
The results of the CDM process assessment should reveal current CDM rates, determine whether business needs are being met, and provide a gap analysis between those needs and the current state. At this point, management should define and quantify the business benefits that can be achieved by further improving CDM to determine the long-term strategy for implementing the work ahead.
The CDM Process Assessment, In Depth
The CDM process assessment can be divided into two parts: requirements gathering and a technical assessment. Figure 3 provides an overview of the process that can be followed when evaluating the current state of the company's CDM process for a single data source.
Figure 3: The CDM Rate Analysis Process Requirements Gathering
Page 1 of 3.
