In order to calculate a valid forecast , a sufficient data basis is necessary, otherwise outliers will inevitably have an extremely distorting effect. Let's assume that your sales department contacts 100 leads, generates 20 appointments from them and you ultimately win two of them. This would mean that you have mathematically won 2% of your offers.
In contrast, to claim that you have a conversion rate of 2% would be extremely presumptuous. To claim that you win 4 orders from 200 leads and 6 from 300 would be statistically equivalent to rolling the dice. The result depends on so many factors (time of approach, mood belarus telegram screening of the customer, etc.) that a result of winning 2 orders again is just as likely as 1 from 8. Sales planning on such a small data basis is therefore more like looking into a crystal ball than a valid prediction.
Incorrect assessment of probability
It is of no use at all to enter the probability of winning an offer in the CRM software if the sales employee continually misjudges it. Always assuming your own success may signal self-confidence, but it distorts the planning. In addition, it is eyewash to enter values with small intervals of 5 or 10 percent as the chance of success. The probability is and remains nothing more than a feeling based on knowledge of people and the industry, in other words: experience.
The rule is, keep it simple. Don't give in to false precision.
The rule is, keep it simple . Don't give in to false precision, but rather rely on a rough division of, for example, 25, 50 or 75 percent. The meaningfulness comes from the number of offers as a data basis and from experience. Ultimately, you won't win an offer with 75 percent, but only with 100 percent or not at all.
confusion of correlation and causality
If an apparent connection (a correlation) is misinterpreted as a cause (i.e. as causality), sales planning quickly becomes ineffective.