Forecasting in the marketplace is a challenging task because of the variations that prevail in the preferences of consumers, increased competition in the marketplace, and a broad range of products. The state of the macro economy also poses challenges in forecasting. In the dynamic marketplace, the utilization of tested approaches can make it possible to realize predictable and measurable outcomes (Gonçalves, Lourenço, & Silva, 2016) . When it comes to purchasing, therefore, certain approaches can be deployed, including business intelligence and buyer intention surveys.
Utilizing business intelligence would serve as one of the most effective ways of forecasting. In the event of the sales people, they are the ones close to understanding the needs of clients, hence should lay emphasis in understanding the preferences of consumers. During interactions between customers and salespeople, it becomes possible to gather vital information concerning the needs and wants of the clients (Chen & Tung, 2014) . In using information, such as CRM (customer relationship management) tools, therefore, firms would be able to change the specifications of the products according to the needs of consumers. Interacting with customers also provides firms with information on when frequency of purchases among clients, hence allow them to predict when next purchases would take place (Cheng & Huang, 2013) .
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Engaging in buyer intention surveys also assists in predicting purchases. Firms should ensure they understand the purchase intentions of potential customers because it determines whether their products will sell. In acquiring the information, a viable option would entail undertaking a focus group survey. These kinds of approaches target consumer segments based on how companies perceive prospective buyers. Here, the firms gather information regarding age groups, geographical distribution, purchase intensions, frequency of purchasing products, and the immediacy of acquiring a product. The approach also reveals the price that the consumers prefer to gain a clear picture of consumers and purchase requirements (Gonçalves, Lourenço, & Silva, 2016) . In this perspective, therefore, using business intelligence and undertaking using buyer intention surveys can play an essential role in forecasting purchasing.
References
Chen, M., & Tung, P. J. (2014). Developing an extended theory of planned behavior model to predict consumers’ intention to visit green hotels. International Journal of Hospitality Management, 36 , 221-230.
Cheng, H. H., & Huang, S. W. (2013). Exploring antecedents and consequence of online group-buying intention: An extended perspective on theory of planned behavior. International Journal of Information Management, 33 (1), 185-198.
Gonçalves, H. M., Lourenço, T. F., & Silva, G. M. (2016). Green buying behavior and the theory of consumption values: A fuzzy-set approach. Journal of Business Research, 69 (4), 1484-1491.
