Post by account_disabled on Nov 26, 2023 5:33:10 GMT
This is an intuitive sales forecast. On the one hand this approach takes into account the opinions of those closest to your prospects: your salespeople. Sales reps, on the other hand, are naturally optimistic and often provide overly generous estimates. There is also no scalable way to validate their assessments. To know whether a prospect is as likely to close as the salesperson says her sales manager needs to listen to her calls, track her meetings, and or read her conversations. This approach is most valuable in the early stages of a company or product when historical data is close to zero.
Pros Cons It relies on the input of the sales team closest to your potential customers. You don't need Phone Number List historical data. Calculations are subjective and each sales rep's forecast may differ. You cannot extend or replicate this method. Visual Forecasting Example Suppose you want to forecast sales for a brand new business. You have only been operating for three months and have no historical data. You have two salespeople on your team so you ask them to use their intuition to forecast sales for the next six months. Each salesperson reviews the deals in their pipeline and the opportunities they plan to pursue in the coming months. Based on their analysis they forecast sales in USD for the next six months.
Historical Forecasting Methods A quick and dirty way to forecast sales for a month, quarter, or year is to look at matching time periods and assume that your results will be equal to or greater than those results. This is a historical sales forecast. There are some problems with this approach. First it doesn't take seasonality into account. Secondly it assumes that buyer demand is constant. But if anything unusual happens your model won’t hold up. Ultimately historical demand should be used as a baseline rather than the basis for sales forecasts. Pros Cons It relies on proven historical data which helps stabilize.
Pros Cons It relies on the input of the sales team closest to your potential customers. You don't need Phone Number List historical data. Calculations are subjective and each sales rep's forecast may differ. You cannot extend or replicate this method. Visual Forecasting Example Suppose you want to forecast sales for a brand new business. You have only been operating for three months and have no historical data. You have two salespeople on your team so you ask them to use their intuition to forecast sales for the next six months. Each salesperson reviews the deals in their pipeline and the opportunities they plan to pursue in the coming months. Based on their analysis they forecast sales in USD for the next six months.
Historical Forecasting Methods A quick and dirty way to forecast sales for a month, quarter, or year is to look at matching time periods and assume that your results will be equal to or greater than those results. This is a historical sales forecast. There are some problems with this approach. First it doesn't take seasonality into account. Secondly it assumes that buyer demand is constant. But if anything unusual happens your model won’t hold up. Ultimately historical demand should be used as a baseline rather than the basis for sales forecasts. Pros Cons It relies on proven historical data which helps stabilize.