I have often found a lot of interesting case studies and lots of content around using a variety of internal sales & transactional data in retail stores to manage category, assortments, inventory planning and customer cross-sell and up-sell opportunities. What these data always many a time miss or don't factor is the external variables that account for customers to make decisions to buy or not buy. This could play a critical role in driving sales.These in fact play an important role in customer shopping behavior.
Some customer or environmental behavioral drivers like whether it is a cold or a warm or a rainy day( and hence a decision to want to go to shopping or not), or sudden change in prices/promotions of specific products across categories in nearby shopping areas or stores, new choices of shopping destinations around the store, sports season etc. affect footfalls and purchases.
UK based Tesco has decided to use weather as an input to predict demand and therefore sales.After over 3 years of research, they have a software that identifies how shopping patterns change with every degree increase in temperature or every hour of sunshine! More here
My View: If information based decisions have to be made by marketers, the 'surrounding factors' around customers needs to be taken into consideration. It might well include traffic patterns, weather, attitudinal factors like health and welleness, enviromental concerns like green agriculture/organic farming etc. Marketers need to find methods to factor all these data into their analysis to forecast customer shopping behaviour.