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The CRM-Ready Data Warehouse

  • September 01 2001, 1:00am EDT
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This month I continue to look at the value proposition for the CRM-ready data warehouse in support of customer contact centers – the first of many major customer interaction systems I'll be reviewing. In my July column, we looked at the first category of value for contact center data: managing customer relationships for increased revenue. This month I'll take a look at four other areas of value for this data.

Make Marketing Promotions More Profitable

Because marketing promotions are costly, they must pay off. By collecting detailed data about contacts, including sales, and correlating the data to individual campaigns, promotions and offers, businesses can measure and improve the effectiveness of their marketing efforts. Business managers can compare sales from one promotion to the next or compare sales during promotion periods to sales during periods without promotions. Or, they can send promotional materials to one group of customers but not to another and compare the results.

In addition to showing whether a promotion is effective, data analysis can indicate the precise point at which an ineffective campaign failed. For instance, if a direct-mail campaign generates a flood of calls but only a few orders, managers can tell where interest dropped off and why. Long call-waiting times and a high percentage of abandoned calls might indicate the need for increased staffing in the contact center. A high number of completed calls that do not result in a sale might indicate the need for more agent sales training. With a contact center data mart, business managers can analyze promotions from beginning to end and refine them for maximum profits.

Data mart information can also indicate which contact channels and which agents are most effective. If a magazine ad lists both a telephone number and a Web address and most of the contacts come in over the Web, this information could be used to adjust contact center staffing to efficiently support future promotions. If data shows that the Seattle contact center is getting more traffic but the Tampa center is closing more sales, a higher percentage of calls could be routed to Tampa where the best closers are staffed.

Keep Agents Effective and Productive

Personnel costs account for 60 to 70 percent of contact center expenses. At the same time, contact center agents play a critical role in fostering the customer satisfaction and customer loyalty that are critical to business success. In order to keep staff levels as low as possible without jeopardizing customer satisfaction, managers strive to keep response times down, make transactions as short and efficient as possible, and ensure that as many transactions as possible are completed on the first contact. Achieving this requires complex data analysis, especially if contact center resources are distributed across geographic boundaries and contact channels.

A contact center data mart allows managers to view agent activity and performance by region, customer, contact channel, promotion, time of day and other factors. Analysis of the data can then be used to reduce talk time and increase the number of transactions completed on the first contact. If, for example, an agent is observed to be very efficient in handling queries for one product line but less so for another, the company could focus the agent's efforts on the product she knows best or offer her training in the product she knows least. Or, if agent effectiveness in general tapers off around lunchtime, a staggered lunch hour might improve performance. Data can also be used to measure aspects of customer contact not directly related to agent performance. Assume, for instance, that contact center agents are responding to e-mail queries using a sequence of three prewritten responses. It takes all three e-mails to complete a transaction, but data indicates that many customers are dropping out after the second e-mail. Some of the content of the third e-mail might need to be moved to the second to ensure completion of the transaction. Finally, a contact center data mart can reveal opportunities to improve agent job satisfaction through training and bonuses based on performance metrics, resulting in increased agent retention and improved customer service.

Develop More Successful Products

It stands to reason that good products sell better than poor ones, and contact center data can be a key indicator of product quality. By analyzing the number, contact channel and duration of support contacts, planners can identify products with quality problems. The higher the number of contacts and the longer it takes to resolve them, the more likely it is that product quality needs attention. A contact center data mart can make this kind of data available and also make it possible to perform "what if" analyses that can pinpoint specific quality issues and suggest product improvements. By correlating product attributes with support contacts, product planners can focus product development and quality control efforts on the attributes that need the most improvement.

Manage the Infrastructure More Efficiently

The contact center, both as a separate operation and as an integrated part of the enterprise infrastructure, is potentially costly. Therefore, efficient management is crucial to minimize costs. Contact center data, as part of the CRM-ready data warehouse can help contact center managers and IT managers run more cost- efficient operations.

Analysis of contact center data can show how effective the contact center is in generating sales or resolving service issues and can help to determine the effect of promotions and product announcements on contact volumes and service levels. The contact center infrastructure can then be adjusted to meet business requirements.

Furthermore, the design of the contact center data can be a factor in efficiently integrating the data mart into the enterprise information infrastructure. A solution based on open standards will integrate more smoothly with existing data warehousing solutions – reducing IT staff expenses and preserving the company's technology investments. A solution based on open standards will also accommodate future enhancements. By making business information users self-sufficient, it can also reduce the IT staff's burden of crafting custom reporting solutions and supplying data to decision-support applications.

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