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Estimating the potential of a market is very important for a company planning to enter a new market. This is a process where an organization estimates the attractiveness of the market for selling its products or services. Before venturing into a market and investing huge sums of money, it is very important to asses it in order to avoid irrecoverable losses. Besides studying the broad market factors such as the size of the population, GDP and the spending capacity of the market, firms should also analyze market specific factors such as customers'tastes and preferences, the cultural factors prevailing, their willingness to buy the products and so on.
The methods used in qualitative forecasting are user expectations, sales force composite, jury of executive opinion, Delphi technique and market test. The methods used in quantitative forecasting are time series analysis, moving averages, exponential smoothing, regression and correlation analysis, and multiple regression models. Selecting the appropriate forecasting method is of great importance for a firm. The method of sales forecasting is selected on the basis of factors such as accuracy, available time, costs, pattern of data, experience of the company and requirements of the software.
For effective forecasting, certain criteria in terms of accuracy, plausibility, durability, flexibility, availability of statistical indexes, organizational participation and demand patterns, should be met. Sales forecasting faces several difficulties such as lack of adequate sales history, lack of time, money and qualified personnel. The changing customer attitudes, and changing fashions and fads also act as hurdles to effective forecasting.
Importance of assessing market potential
Need to determine market potential
Analyzing market potential
Ability to buy
Willingness to buy
Sources of data
Importance and uses of sales forecasts
Sales forecasting methods
Selecting a forecasting method
Type of data available
Requirements of the software
Experience of the company
Criteria For Effective Forecasting
Availability of statistical indexes
Demand patterns in the market for the product
Difficulties associated with forecasting
Lack of adequate sales history
Lack of time
money and qualified personnel
Changing customer attitudes
Fashions and fads