360° view of customers

It's common to have multiple systems with customer information stored in each. Systems that process sales, deliver customer service and market products and services. With multiple systems, you may have difficultly achieving a complete customer view.

Turning data silos into a marketing asset

A client had many views of customer activity, one for each business division. Each view was managed by a separate business system. None of these systems talked to each other!

As a consequence, the organisation didn't know how many customers it had. They could report customers from each silo, but they couldn't quantify the overlap. Without a clear understanding of customer needs there was:

• A danger of miss-judging customer situations
• Missed cross-sell opportunities

We delivered a data warehouse to integrate their customer silos. The results:

• Management had a 360° view of customers
• Concise information about which services and products a customer purchased
• Valuable cross-sales opportunities

Data warehouse provides 360° view of customers

Frustrated by not having a comprehensive customer view? The solution is to invest in a  data warehouse. A data warehouse combines data from disparate systems, providing a comprehensive view. Integrated with business intelligence, users have access to information from all business areas e.g.:

• Marketing communications
• Sales order processing
• Customer services

Considerations before implementation

Before implementing a data warehouse consider how it would work in your organisation:

• What systems do you have and what information is collected?
• How are customers defined in each system, how will they be integrated?
• Are there data quality issues, are all data requirements consistently captured?
• Review business intelligence considerations click here

Using these considerations, develop requirements to ensure you pick the right solution.

Data warehouse technology

With data warehousing there are many potential software components. The elements for your specific solution depend on your organisations needs. The principal areas to consider are:

• Data access to source systems
• Data quality, cleansing and reformatting
• Data transformation, manipulating the data ready for data analysis and reporting
• Data warehouse  database
• Data management, controlling data refresh processing