We investigate the information content of business tendency surveys for key macroeconomic variables in Switzerland. To summarise the information of a large data set of sectoral business tendency surveys we extract a small number of common factors by a principal components estimator. The estimator is able to deal with mixed-frequency data and missing observations at the beginning and end of the sample period. We show that these survey-based factors explain a relevant share of the movements of key macroeconomic variables, i.e., CPI inflation, GDP, employment, and an output gap. In particular, questions about the current and future expected situation are informative. However, backward-looking questions, for example questions about the situation compared to the previous year, do not contain additional information. We then examine the economic dimension of the data set. Questions about prices, real activity and capacity constraints contain important information for the corresponding macroeconomic variables. Finally, we estimate a dynamic relationship to produce forecasts for our factors and these key macroeconomic variables. It turns out that the predictive ability of our survey-based factor approach is quite encouraging. In a pseudo out-of-sample exercise, our approach beats relevant benchmarks for forecasting CPI inflation and an output gap and adds information to the benchmark forecasts for GDP and employment.