Magazine article CRM Magazine

Improving Business Performance: With Automated Customer Lifecycle Analytics

Magazine article CRM Magazine

Improving Business Performance: With Automated Customer Lifecycle Analytics

Article excerpt

The pressure on your organization to acquire and retain customers, as well as cross-sell and up-sell to them, is increasing. To meet this challenge your marketing campaigns must be more focused and effective than ever before. And you must not only understand customer behavior, but also predict it at increasing levels of detail.

Unfortunately, first-generation data mining tools require your analysis team to spend a great deal of time and effort to manually create and maintain a very limited number of predictive models, making it cost-prohibitive to dig further into the data for better results. Out of necessity, you are forced to make do with just a few models and apply a "one-size-fits-all" approach to your campaigns.

KXEN's Data Mining Automation Solution is the next generation in modeling technology. It frees you from the productivity constraints imposed by first-generation tools, giving you the power to understand and predict customer behavior at a speed and levels of detail previously out of reach.

KXEN's customers often experience a 200-300 percent increase in overall conversion rates on their campaigns. They are able to execute more targeted and precise campaigns in a shorter time than with first-generation tools. And because KXEN automates the modeling process, customers can then free valuable analyst resources to address additional opportunities for generating value.

CUSTOMER LIFECYCLE ANALYTICS

Increasing the value of your customer relationships is the primary goal. The ability to understand and predict customer behavior at each stage of the customer lifecycle is critical--the more detailed and focused your analysis of future behavior, the better the performance. Customer Lifecycle Analytics is your primary tool to achieve this.

At each stage of the customer lifecycle, you must make a decision about whether to actively try to acquire or maintain that relationship, or whether to let that customer go because they aren't likely to meet profitability goals. For customers identified as targets for retention or acquisition, you must perform a predictive analysis of what products and services to offer through which channels.

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Many businesses rely on first-generation data mining tools for this predictive analysis. …

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