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If the trend can be assumed to be linear, trend analysis can be undertaken within a formal regression analysis, as described in Trend estimation. If the trends have other shapes than linear, trend testing can be done by non-parametric methods, e.g. Mann-Kendall test, which is a version of Kendall rank correlation coefficient.
Sales data, presented in a graphic format, can provide regular sales trend information and highlight whether certain customer types need to be targeted or focused. Price information by product line, compare with competitors, can monitor market trends; analyzed by customer type, it can check price trends in customer groups.
Demand forecasting plays an important role for businesses in different industries, particularly with regard to mitigating the risks associated with particular business activities. However, demand forecasting is known to be a challenging task for businesses due to the intricacies of analysis, specifically quantitative analysis. [4]
Market research is an organized effort to gather information about target markets and customers. It involves understanding who they are and what they need. [1] It is an important component of business strategy [2] and a major factor in maintaining competitiveness.
The literature defines several areas in which market analysis is important. These include: sales forecasting, market research, and marketing strategy. Not all managers will need to conduct a market analysis. Nevertheless, it would be important for managers that use market analysis data to know how analysts derive their conclusions and what ...
It is important to note, however, that the accuracy and usability of results will depend greatly on the level of data analysis and the quality of assumptions. [1] Predictive analytics is often defined as predicting at a more detailed level of granularity, i.e., generating predictive scores (probabilities) for each individual organizational element.
Forecasting is the process of making predictions based on past and present data. Later these can be compared with what actually happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis.
Marketing mix modeling (MMM) is an analytical approach that uses historic information to quantify impact of marketing activities on sales. Example information that can be used are syndicated point-of-sale data (aggregated collection of product retail sales activity across a chosen set of parameters, like category of product or geographic market) and companies’ internal data.
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