The more a company knows about its customer’s wishes, needs and habits and the more that company is able to tailor its proposition accordingly, the greater the value it will eventually provide for its customers. We all know that there are countless examples where defective, fragmented, or just plain poor customer data cause unnecessary costs, decrease in revenue, employee dissatisfaction or frustation, damage of the corporate image and many other unsdesirable or painful consequences.

Customer data quality and integration problems impact every area of the value chain of organisations. Far too often companies have a multiple view of their customers. Customer Data Integration (or MDM for Customer Data) is the key to providing companies with a single view of their customer. According to Gartner, Customer Data Integration (CDI) is a combination of technology, services and processes to deliver an accurate, timely and complete view of the customer across multiple channels, lines of business, departments and divisions drawing customer data from multiple sources and systems.

I think that the real “miracle” of CDI lies in the automated, intelligent matching of customer records. Mind you, I’m not questioning the importance of the various CDI-processes (for example, I think that the post of my colleague Ramon de Noronha on the creation of “golden” records is majorly important), I’m just saying that -whenever the integration of customer data is an issue- intelligent, automated matching is the key prerequisite for success.

The quality of your customer data integration solution is only as powerful as the quality of your matching engine. If this statement intrigues you, I strongly advise you to read the white paper “High Precision Matching at the heart of Customer Data Integration“. Enjoy!

HI Survey Results

Looking at the data can give you deeper insight in your data processes. Not only the processes in theory, but in practice too. How? By focusing on the exceptions!

For example, do you think the field ‘social security number’ is reliable because it is mandatory and uses a modulo 11 check digit? Maybe this field is filled with a fake-value like ‘111222333′ , or the social security number of the agent who entered the data. A frequency check on the values in this field will identify values that occur more frequently than others.

Why do people do that, cheat? One reason may be that staff at the front desk want to help their customer, or sell something, and the customer doesn’t know their social security number at that moment.

The same applies to all other fields. Address fields mandatory, but the customer doesn’t want to give their address ? Fill in the address of the office. Customer deceased? Put the text (deceased) after their surname. Ex-directory phone number? Use the email field for entering the text ‘ex-directory’.

Get to know your processes by analyzing your data!