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Predictor

Commerce Server 2002

The Predictor, a feature in Microsoft Commerce Server Enterprise Edition, is a powerful data-mining resource that you use to provide predictive capabilities for your Web site, for example, to display product recommendations to a site user. You also use the Predictor to analyze the characteristics of the users visiting your site, and to discover relationships among the characteristics. You can then use this information to target content to users who have similar characteristics.

For example, using the Predictor you can provide the following features on your Web site:

  • Cross-sell and cross-browse. Provide real-time product recommendations for users to buy or browse as they shop for products on your Web site.
  • Targeted advertising. Target banner ads and e-mails that are personalized for each user based on their browsing and shopping behavior on your site.

You can use the analysis features of the Predictor to automatically segment your site usersbased on their buying and browsing behavior on your site, and then use the results of this analysis to target content to users. You can also make statistically informed guesses about the demographic makeup of every user based on the products they purchase and the pages they browse on your site.

The Predictor includes the following key components:

  • Prediction Resource Tutorial. Use this step-by-step tutorial to learn how to use the Predictor for cross-sell and cross-browse, demographic prediction, targeted advertising, and user segmentation.
  • Model viewers. You can analyze Prediction models using the Prediction Model Viewer accessed through Commerce Server Manager, and you can analyze Segment models using the Segment Viewer module in Business Desk. You can export the results of both prediction analysis and segment analysis as lists, so you can target content to users.
  • Prediction Model Configuration Wizard. You use the Predictor Model Configuration Wizard to set up the following model configurations provided with Commerce Server EE:
    • Transactions. Use to build analysis models that predict the products that users are likely to buy. For example, your site could present each user with a list of personal product recommendations.
    • Demographics. Use to build analysis models that predict the demographic characteristics that your users are likely to share. For example, you can use the demographic analysis models to improve your understanding of the registered users who visit your site.
    • Combined Transactions and Demographics. Use to build analysis models that predict likely relationships between demographic characteristics and product purchases. The accuracy of this model is directly proportional to the number of registered users on your Web site.
    • Product Browsing. Use to build analysis models that predict the products that your users are likely to browse. For example, you can place links on your site that are relevant to your users.
    • Ad Click. Use to build analysis models that predict the ads that your users are likely to click.

The following table lists key Commerce Server Help topics to help you learn more about the Predictor resource.

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