This is to become post 1 of a 4 part series on the concept and application of Customer Data Integration (hereafter referred to as CDI). This first post will go into the definition of a number of concepts that make up the field of CDI. The second post will deal with applying these concepts and defining an overall CDI approach. Post three will deal with key succes factors in implementing CDI. The fourth post will highlight some of the application solutions that provide CDI specific solutions.
What is Customer Data Integration
according to Gartner CDI is : ‘a combination of technologies, processes and services to develop and maintain an accurate, timely and complete view of the customer….across multiple sources of customer data..’ This is the definition that will be used during the remainder of these series. It’s important to stress that CDI is more than just technology to ensure a single view of the customer, it can involve a change in business processes and requires a company to focus on the need for correct customer data.
Challenges addressed through CDI
Ensure a single point of entry for customer data, enter your customer data only once, and have it available for use in all channels once the data has been entered.
All channels are provided with consistent and accurate data, through use of data quality tools.
By providing all channels with consistent customer data, one is able to enhance a customers experience and perception of level of service. The customer experience can be made consistent across all channels.
If your customer data is of higher quality, the reliability of data for segmentation and marketing is significantly improved.
A single source for customer data allows a company to better manage it’s customer data privacy. Ensuring compliance with laws and regulations is easier for a single system, as opposed to dispersed, diffuse customer date stored in multiple systems.
Elements of CDI
Customer Master Data Systems, a single source that stores your customers in a consistent way. Typically an application that is exposed to other application using EAI / SOA based tooling. A customer master data application provides a data model which allows storing all your customer related data, such as contact, account and address information (installed base information can also belong to this domain), whereas operation data, such as opportunities, leads, activities / meetings, are stored in operational CRM systems
Data Quality Tools, however strict the procedure you have for data entry is, one will always make mistakes such as duplicate entry of data, incomplete address information etc. Data Quality Tools can prevent common mistakes from being made, by providing data matching and data cleansing services. Data matching entails matching new entries to existing data, based on certain algorythms to determine potential and complete matches of data entered. Data cleansing tools provide automatic enhancement and validation of data, such as address information or names of companies based on postal code data or chamber of commerce reference information.
Enterprise Application Integration. In today’s world of SOA enable applications EAI plays an important role. A customer master application is worthless without it being exposed to other applications as a data provider. If your perfect model of customer data cannot be accessed through operational applications, the benefits of CDI cannot be reaped. Enterprise application technology provides authentication, transformation and transport for XML based services to and from your customer master system, to ensure the correct data is actually delivered on request, but only to applications that are allowed to access that data.
The second part of this series will deal with an application of these concepts.