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Forecasting for Marketing

Author

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  • Armstrong, J. Scott
  • Brodie, Roderick J.

Abstract

Research on forecasting is extensive and includes many studies that have tested alternative methods in order to determine which ones are most effective. We review this evidence in order to provide guidelines for forecasting for marketing. The coverage includes intentions, Delphi, role-playing, conjoint analysis, judgmental bootstrapping, analogies, extrapolation, rule-based forecasting, expert systems, and econometric methods. We discuss research about which methods are most appropriate to forecast market size, actions of decision makers, market share, sales, and financial outcomes. In general, there is a need for statistical methods that incorporate the manager's domain knowledge. This includes rule-based forecasting, expert systems, and econometric methods. We describe how to choose a forecasting method and provide guidelines for the effective use of forecasts including such procedures as scenarios.

Suggested Citation

  • Armstrong, J. Scott & Brodie, Roderick J., 1999. "Forecasting for Marketing," MPRA Paper 81690, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:81690
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    References listed on IDEAS

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    Cited by:

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    2. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    3. Bonache, Adrien, 2008. "Les ventes de produits innovants à la mode sont-elles chaotiques? Le cas des ventes de Game Boy au Japon [Are innovative and fashion goods sales chaotic? The case of Game Boy sales in Japan]," MPRA Paper 12964, University Library of Munich, Germany.
    4. Jung, Sang Hoon & Jeong, Yong Jin, 2020. "Twitter data analytical methodology development for prediction of start-up firms’ social media marketing level," Technology in Society, Elsevier, vol. 63(C).
    5. Canback, Staffan & D'Agnese, Frank, 2007. "Where in the world is the market? : The income distribution approach to understanding consumer demand in emerging countries," MPRA Paper 13854, University Library of Munich, Germany.

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    More about this item

    Keywords

    forecasting; marketing;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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