Abstract: Systems and processes are described for providing improved understanding of cardholder purchasing behavior, and/or for providing improved predictions of future consumer needs. In some embodiments, the payment card account receipts of panel respondents are matched to their survey question responses and processed to generate actual spending behavior data, which may then be analyzed to generate one or more predictions concerning future consumer spending behavior. In an implementation, a computer receives recent payment card account receipt data and self-reported survey data of a panel respondent member, tags that data with a unique cardholder identifier (ID), and determines that there is a match between the recent payment card account receipt data and data stored in a transactional cardholder database.

Abstract: A method and system for predicting consumer spending includes conducting a survey of a panel of individuals to obtain future anticipated spending data for a time periods; and tracking actual spending of the surveyed individuals for the time periods and tabulating. The method also includes calculating with a processor the difference in actual spending and the anticipated spending in the time periods to obtain spending normalization factors. The method further includes calculating the transitional probability of future spending for a time period beyond the surveyed time period to order obtain a preliminary spending prediction based on the survey results of the surveyed time periods. A prediction of consumer spending is determined by adjusting the preliminary spending prediction in response to the first and second normalization factor to determine a prediction of consumer spending for a future time period.