Analytical CRM vendors need to emphasize the fundamental importance of Data Quality.

Although the marketing messages used by most vendors imply that true analytical CRM can be sold in an off-the-shelf packaged solution, this simply does not reflect reality. These pretenders are unlikely to succeed in the long term because customers that buy their so-called analytical technology rarely see the benefits that can be realized with sophisticated analytical CRM packages and so become disillusioned. The winners in this market are those vendors that work with companies to design and deploy tailored solutions, rather than the ‘grab the money and run’ approach used by some.

The phrase ‘garbage in – garbage out’ is more true of analytical CRM than of any other technology. Analytical CRM uses the data in the data warehouse to precisely segment and define customer groups and target outbound marketing. Without a solid data foundation for this, it cannot work effectively. Data Quality (DQ) is the process of consolidating and cleaning every byte of data within an enterprise. The quality of data directly affects the effectiveness of outbound marketing, analytics and customer loyalty and, more fundamentally, the ability to do business. A common misconception is that DQ addresses verification; more accurately it is customer identification. As such it is critical to Analytical CRM.

If a hypothetical enterprise has 100,000 customer dialogues on record, an error rate of 5% means 5000 customer data sets are inaccurate. Some of these can be seemingly trivial, caused by life events, such as moving house, changing jobs or getting married. However, when companies use inaccurate data, this could annoy, upset, and potentially lose a customer. Furthermore the incorrect information may be about credit history and the customer could be mis-sold a product.

Vendors who offer analytics without emphasizing Data Quality and its fundamental importance may be misleading the market. Customers need to be careful that they do not buy a solution that will not work at 100% effectiveness, while vendors need to be careful that they do not become embroiled in long projects where DQ issues are insurmountable.

Related research: Datamonitor: Analytical CRM (DMTC0868)

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