Purchase intentions are routinely used to forecast sales of existing products and services. While past studies have shown that intentions are predictive of sales, they have only examined the absolute accuracy of intentions, not their accuracy relative to other forecasting methods. For example, no research has been able to demonstrate that intentions-based forecasts can improve upon a simple extrapolation of past sales trends. We examined the relative accuracy of four methods that forecast sales from intentions. We tested these methods using four data sets involving different products and time horizons; one of French automobile sales, two of U.S. automobile sales, and one of U.S. wireless services. For all four products and time horizons, each of the four intentions-based forecasting methods was more accurate than an extrapolation of past sales. Combinations of these forecasting methods using equal weights lead to even greater accuracy, with error rates about one-third lower than extrapolations of past sales. Thus, it appears that purchase intentions can provide better forecasts than a simple extrapolation of past sales trends. While the evidence from the current study contradicts the findings of an earlier study, the consistency of the results in our study suggest that intentions are a valuable input to sales forecasts.