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Market Potential and Sales Forecasting

Market Potential and Sales Forecasting. Chapter 06. Forecasts versus Potential. Five major uses of potential estimates. To make entry/exit decisions To make resource level decisions To make location and other resource allocation decisions To set objectives and evaluate performance

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Market Potential and Sales Forecasting

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  1. Market Potential and Sales Forecasting Chapter 06

  2. Forecasts versus Potential

  3. Five major uses of potential estimates • To make entry/exit decisions • To make resource level decisions • To make location and other resource allocation decisions • To set objectives and evaluate performance • As an input to forecasts

  4. Deriving Potential Estimates

  5. Useful Sources for Potential Estimates • Government Sources • Trade Associations • Private Companies • Financial and Industry Analysts • Popular Press • The Internet

  6. New or Growing Product Potential • Relative Advantage • Compatibility • Risk

  7. Methods of Estimating Market and Sales Potential • Determine who are the potential buyers or users of the product • Determine how many are in each potential group of buyers defined by step 1 • Estimate the purchasing or usage rate

  8. Market Potential: Electric Coil

  9. Uses of Sales Forecasts • To answer “what if” questions • To help set budgets • To provide a basis for a monitoring system • To aid in production planning • By financial analysts to value a company

  10. Scenario-Based Forecasts

  11. Judgment-based Forecasting Methods • Naïve extrapolation • Sales force composite • Jury of expert opinion • Delphi method • Electronic Markets

  12. Summary of Forecasting Methods

  13. Graphical Eyeball Forecasting

  14. Customer-Based Methods • Market Testing • Situations in which potential customers are asked to respond to a product or product concept • Market Surveys • A form of primary market research in which potential customers are asked to give some indication of their likelihood of purchasing a product

  15. Time-Series Forecasting Methods • Moving Averages • Exponential Smoothing • Regression Analysis

  16. Potential Customers by Industry and Size

  17. Sample Data

  18. Times-Series Extrapolation

  19. Time-Series Regression Example

  20. Trial over Time for a New Product

  21. Model-Based Methods • Regression analysis • Leading indicators • Econometric models

  22. Forecasting Method Usage

  23. Use of New-Product Forecasting Techniques by All Responding Firms

  24. Developing Regression Models • Plot sales over time • Consider the variables that are relevant to predicting sales • Customer status and traits • “Our” marketing programs • Competitive behavior • General environment • Collect data • Analyze the data

  25. Cereal Sales Data (monthly)

  26. Cereal Data

  27. Cereal Data Correlation Matrix*

  28. Regression Results: Cereal Data*

  29. Format for Reporting a Regression Model Based Forecast

  30. The Impact of Uncertain Predictors on Forecasting

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