Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase. Demand forecasting involves techniques including both informal methods, such as educated guesses, and quantitative methods, such as the use of historical sales data or current data from test markets. Demand forecasting may be used in making pricing decisions, in assessing future capacity requirements, or in making decisions on whether to enter a new market.
No demand forecasting method is 100% accurate. Combined forecasts improve accuracy and reduce the likelihood of large errors. Other experts have shown that rule based forecasts are preferred over guesstimate forecasts.
Methods that rely on qualitative assessment

Forecasting demand based on expert opinion. Some of the types in this method are,

  • Unaided judgment
  • Prediction market
  • Delphi technique
  • Game theory
  • Judgmental bootstrapping
  • Simulated interaction
  • Intentions and expectations surveys
  • Conjoint analysis
  • jury of executive method

Methods that rely on quantitative data

  • Discrete Event Simulation
  • Extrapolation
  • Reference class forecasting
  • Quantitative analogies
  • Rule-based forecasting
  • Neural networks
  • Data mining
  • Causal models
  • Segmentation

Some of the other methods
a) Time series projection methods include:

  • Moving average method
  • Exponential smoothing method
  • Trend projection methods

b) Casual methods include:

  • Chain-ratio method
  • Consumption level method
  • End use method