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What kinds of commonly used sales forecasting methods are described respectively?
The commonly used sales forecasting methods are as follows:

1, time series analysis: This method is usually used to predict future sales trends. By analyzing the historical sales data, we can understand the sales trend and make a forecast for the future sales.

2. Causality analysis: By analyzing the factors that affect sales, we can predict the future sales situation. For example, if the sales volume of a product has increased in the past week, it can be predicted that the sales volume will continue to increase next week.

3. Market research: By understanding the demand and trend of the target market, we can predict the future sales situation. Market research can help salespeople understand customers' needs and preferences, so as to better meet customers' needs.

4. Competition analysis: By analyzing the sales situation and marketing strategies of competitors, it can help to predict the future sales situation. For example, if competitors are offering discounts, then we can predict that future sales will increase.

5. Expert opinion: By consulting industry experts or experienced salespeople, you can get their predictions and suggestions for future sales. Expert opinion is usually more valuable than other methods.

The role of sales forecast:

1. Formulate sales strategy: By forecasting sales trends, enterprises can better formulate policies such as sales strategy, adjust sales plans and improve sales efficiency.

2. Optimize inventory management: Sales forecast can help enterprises to better manage inventory by putting vinegar, avoid inventory backlog or shortage, and thus reduce inventory costs.

3. Improve customer satisfaction: By forecasting customer needs, enterprises can better meet customer needs and improve customer satisfaction and loyalty.

4. Guide the production plan: Sales forecast can guide the production plan of the enterprise, adjust the production volume according to the market demand, and avoid overcapacity or shortage.

5. Auxiliary decision-making: Sales forecast can provide data support for enterprise decision-making and help enterprises make more informed decisions. For example, in terms of investment and market expansion, sales forecast can provide important reference for enterprises.