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30 Jun 2008

dn:Director for Customer Insight

Bad Customer Data - Impact

Poor quality customer data can have a significant impact on customer service, operational efficiency and financial performance. Inaccurate and duplicated records can leave organizations with a fragmented, incomplete view of customers, which reduces the ability to recognize opportunities to sell new goods and services.

Companies usually take a reactive approach to managing customer data quality - addressing it on a project basis as part of a data migration or by instigating a data cleansing initiative when the impact of poor data has become obvious. This approach leads to short periods of intense activity followed by the slow decline of customer data quality.

The dn:Director Approach - Constant Data Quality and Control

dn:Director validates your customer data and maintains constant data quality by working at the point of data entry. This prevents invalid or duplicate records from effecting the value of your customer-facing applications.

dn:Director can be deployed in a service oriented architecture (SOA) to integrate seamlessly with CRM and Web self-service systems, enabling non-technical users - such as Marketing Managers - to identify errors and take corrective action.

Instead of requiring a user to learn how to query in SQL or other scripting languages, dn:Director comes with an easy-to-use family of simple ‘processors’, a palette or library of tools that can be dragged onto a canvas to build automated business processes from simple data profiling to complex data correction. The tools are represented as simple icons and these can be chained together to create solutions to specific data quality problems.

Users access a single, consistent and intuitive graphical user interface for every data quality task, optimized to produce fast results. Users with no previous data quality experience can deliver results within minutes, and experienced users can quickly define and refine processes, business rules, and reference data using:

• A simple graphical drag-and-drop interface
• Data-led approach to business rule definition
• Use of wizards to lead users through tasks
• Extensive use of defaults to minimize user input
• Multi-level undo/redo of the graphical process definition
• Visual indicators for issues requiring user attention

By automatically publishing results to a central web-based reporting tool (dn:Dashboard), dn:Director users can share the results of their work across the enterprise. It also allows data owners and other key stakeholders to keep constant track of customer data quality by monitoring trends over time.

Don’t Duplicate

Duplicate records in CRM systems may be difficult to prevent. There may be multiple points of data entry, with different processes for adding records - from web forms to call centers, trade shows and purchased lists.

Common causes of duplicate records include:

• Targeting data capture on the volume of information captured, for example in call centers. If users see identifying duplicates as an overhead they may deliberately circumvent it
• Unfocused matching returns too many duplicates to handle; it becomes too complex to merge records
• The inability to find duplicate records due to changes of name or address, or inadequate information
• Inadequate controls on record duplication when migrating data
• Customers re-registering on web forms when they forget their previous login details

Creating a Single View of Your Customers

dn:Director is a simple tool that uses sophisticated matching technology to identify duplicate customer data records from single or multiple sources.

It uses source-independent ‘match rules’ to quickly and flexibly establish the level of duplication in your customer data set. Once the match rules have been proven to deliver the right results, dn:Director enables you to create ’survivor’ and ‘update’ rules that are capable of gracefully transforming your source data into a single view of your customers.

dn:Director’s interactive reviewing capability also enables multiple users to review the results of the matching process and make manual matching and update decisions. All reviewing activity is audited and all decisions (both automatic and manual) are registered and can be recalled by the application on subsequent runs of the de-duplication process.

Find out more about the market’s leading Data Quality solution today…