Customer value models are powerful tools to improve business strategy, tactics and reporting, but they need a lot of input data, which is not always fully available. Some people object to the models for this reason. Their concern is that incomplete data will yield inaccurate results, leading to worse decisions than no model at all.

There are ways to overcome data limits. One is to model only areas where detailed data is available. For example, log files can capture a precise history of a customer's behavior on the Web. Marketers may build a customer value model to help with Web-related decisions even if non-Web behavior is modeled in much less detail.

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