Customer data integration (CDI) combines customer information acquired from all internal and external sources to...
generate a single up-to-date version. A subset of master data management (MDM), CDI, helps organizations to get a consolidated view of each of their customers.
This Quick Guide to Customer Data Integration looks at important aspects ranging from definition, implementation tips, to available options to buy.
- Customer data integration illustrated
- Benefits of deploying CDI solutions
- Customer data integration project challenges
- Tips for evaluating a CDI solution
- Available CDI offerings
- Further reading on customer data integration
Businesses collect lot of customer data over time but cannot use that effectively due its being fragmented across departments (and not necessarily integrated with each other). The compaction of customer information acquired from various internal and external sources (applications, systems, etc.) resulting in a single, current version is known as customer data integration (CDI).
CDI’s central component is known as customer data hub. It is the master container with built-in data correction, correlation, and quality facilities.
Customer data integration offer the following benefits:
1) Improvement in sales. For example, cross-selling/ up-selling based on a customer’s profile or accurate marketing campaigns.
2) Improved customer service.
3) Data management becomes simpler as updates to customer records need to made only once.
4) With availability of current and complete customer data at any point in time, organizations can make effective business decisions and reduce the chances of compliance violations (do not call, customer consensus, etc).
5) A central repository with single owner instead of data silos across different departments can be achieved to simplify data management.
Undertaking a CDI program is fraught with a few challenges. The CIO needs to carry out due diligence before investing in the program.
1) Unintentional data inaccuracies in customer data hub: Accidental update to customer record in the hub would result in inaccurate version of the data being used by all departments/ subsystems dependent on it.
2) Single point of failure: In the absence of backup and recovery mechanism for the customer data hub, organization’s business can be adversely impacted.
3) Data model rigidity: Vendors design data models to be best suited for their applications, thereby restricting the scope for changes that the organization may need.
Before buying a customer data integration tool, a few aspects need to be assessed. Do not jump-start the project without considering the following:
1) Do you have a cross-functional team with representatives from business and IT sides? This is crucial for success of a customer data integration program.
2) Organization-wide data governance: Another must have ingredient for customer data integration’s success. The policy should contain the mapping of the departments versus the customer data type they own and can change. It should also contain details on how the roles of various data owners would change post-implementation.
3) Assess if you need customer data integration or would modifying the data warehouse solution suffice, instead.
4) Weigh your options: Build or buy
Building in-house is cost-effective initially but requires maintenance and skilled resources in an ongoing basis. Buying a customer data integration solution might result in a high upfront costs but maintenance/ support becomes simpler.
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5) Data sources and data model:
There must be an agreement between departments (including distributors/ channels) about which source(s) hold accurate customer data. This is needed to create concurrence on business rules and data quality metrics. The selected departments would need to part of the customer data integration project. The identified customer data sources should be used to create a comprehensive data model.
6) Is the CDI solution you intend to deploy based on services-oriented architecture (SOA)? SOA offers flexibility, modularity, and scalability. Check that with your vendor first.
7) Check how well the customer data integration solution equips you with customer identity management.
8) Assess the infrastructure requirements of deploying it.
9) Check if the tool you intend to buy is scalable.
Customer data integration vendor
Dun & Bradstreet Purism Data Hub
Identifies customers, vendors, and other entities across corporate data sources. Creates a master version of every identified entity and synchronizes this information across the enterprise.
IBM IBM Initiate Master Data Service V. 9.5
Tailors views of trusted information from multiple source records. Automatically resolves and manages data quality issues.
Kalido Kalido MDM
Offers capabilities to model, manage and govern master data. Eliminates customized interface development costs by automatically generating the appropriate user interface.
Informatica Informatica MDM
Enables companies to leverage ‘Single Customer View’ to improve their operations and reporting. It can also enable ‘Extended Customer View’ which consists of customers, their accounts, products and services, as well as their previous relationships with other customers.
SAP NetWeaver MDM
Creates a single source of truth for customer data. Eliminates manual rework caused by incomplete/ bad data. Rationalizes redundant systems.
Definition from Whatis.com: Customer Data Integration (CDI)
Tutorial: Learning guide and business advice
Answer: MDM vs CDI
Answer: CDI initiative: Where to begin?
Answer: Origins of CDI