PLATFORMS: We are running DataMind DataCruncher on a Pentium PC.

BACKGROUND: ADP Dealer Services Group, a division of ADP (NYSE:AUD), is the world's largest provider of computing, data and professional services to automotive and truck dealerships throughout the world. ADP Dealer Services provides turnkey systems to over 18,000 auto and truck dealers throughout the United States, Canada, Europe, Asia and Latin America. Customers use ADP's systems to manage their accounting, inventory, factory communications, scheduling, leasing, sales and service activities.

PROBLEM SOLVED: ADP's hardware services department fields approximately 12,000 support calls per month. As the cornerstone of our customer support system, we wanted to look at our line of phone support and determine what changes we could make in order to improve customer satisfaction. The discoveries we have made through DataMind's DataCruncher have led us to a new customer support paradigm--one in which we evaluate successful customer support from the customer perspective.

DataCruncher's findings motivated us to look beyond technical issues and focus our efforts on new management, staffing and training models. Through DataCruncher's sophisticated prediction and modeling capabilities we uncovered relationships we would have never learned on our own. For example, we learned that phone service reps with a broad technology background had a higher success rate than those with in-depth focused expertise. As a result, we changed our training programs toward broader, more general knowledge. Additionally, we determined that Monday is a heavier service day than the rest of the week, so we increased staffing on Mondays to offer faster response. Overall, DataCruncher's ability to uncover relationships and service patterns beyond human detection has given us the information to build an effective line of customer support.

PRODUCT FUNCTIONALITY: We use DataCruncher in the hardware engineering department to do month-to-month customer service level analysis. It lets us run ad hoc reports to see where we can better service our customers and enables us to scale large and complex amounts of data without sacrificing accuracy or fast response time. With DataCruncher, we can build data models and produce easy-to-read reports from which to identify support patterns.

STRENGTHS: DataCruncher is a very powerful, intuitive and flexible solution that allows us to play out scenarios repeatedly in order to see where we can improve customer service. Its prediction and analysis tools have led us to meaningful relationships we would not have discovered on our own. DataCruncher can also convert data mining reports into HTML files with a click of a button--making it easy to share information via the Web.

WEAKNESSES: DataMind could afford to improve its graphics, which are difficult to manipulate.

SELECTION CRITERIA: We were initially invited to be a beta client and were so pleased with the benefits that we did not look at other solutions.

DELIVERABLES: DataCruncher allows us to leverage vast amounts of data. The relationships we have discovered through prediction and analysis have changed the way we approach customer support overall and enabled us to raise the level of customer satisfaction.

VENDOR SUPPORT: DataMind's support has been very good. Whenever we have had a problem, the technicians have been interested in our feedback and very responsive to time-sensitive issues.

DOCUMENTATION: Documentation was sufficient. It is supplemented by excellent technical support.

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