Sales: The Sense and Nonsense ofsales forecasting
Posted: Thu Jan 30, 2025 8:59 am
Most CRM (Customer Relationship Management) systems automatically prepare your offers so that you get this overview. How does this work? You maintain all your open offers with expected sales, target date and probability within the CRM software . The software now groups, for example, all offers for the next six months according to their target date.
These are all the offers that you could - theoretically - win. But of course it's not that simple, because unfortunately, not every customer accepts. Just how many people you've sent an offer to says relatively little. Depending on how you handle sending offers, more or fewer of them will actually lead to denmark telegram screening an order (last post: hasty offer ). To calculate the forecast more precisely, we also take into account the probabilities of the offers that you have stored to the best of your knowledge.
Expected value = Probability offer A * Sum offer A + Probability offer B * Sum offer B
By weighting your offers, you get a better idea of the sales you can expect. In the end, however, forecasting is a rough estimate and not an exact science. And that's how you should approach it. By estimating the parameters of the order amount and the probability of each offer as realistically as possible, you get the best possible forecast for your sales in the extrapolation.
Common sources of error in forecasting
Regardless of whether you create your forecast by hand in Excel or whether your CRM software already summarizes the data - there are some sources of error that severely limit the reliability of the forecast - here we list the three most common sources of error from our experience.
These are all the offers that you could - theoretically - win. But of course it's not that simple, because unfortunately, not every customer accepts. Just how many people you've sent an offer to says relatively little. Depending on how you handle sending offers, more or fewer of them will actually lead to denmark telegram screening an order (last post: hasty offer ). To calculate the forecast more precisely, we also take into account the probabilities of the offers that you have stored to the best of your knowledge.
Expected value = Probability offer A * Sum offer A + Probability offer B * Sum offer B
By weighting your offers, you get a better idea of the sales you can expect. In the end, however, forecasting is a rough estimate and not an exact science. And that's how you should approach it. By estimating the parameters of the order amount and the probability of each offer as realistically as possible, you get the best possible forecast for your sales in the extrapolation.
Common sources of error in forecasting
Regardless of whether you create your forecast by hand in Excel or whether your CRM software already summarizes the data - there are some sources of error that severely limit the reliability of the forecast - here we list the three most common sources of error from our experience.