Reduce Errors in Your Sales Forecasting with Proven Methods

Aug 21, 2017

customer journey

Businesses are being more focused on accurate sales forecasting as deviations in forecast versus actual sales figure could cost them in terms of lost revenue opportunities. As a result of this, the production forecast and other business operations will also take a hit. Accurate sales forecasting enables the manager to cope with sudden changes in demand levels, counter competitive moves, and manage seasonality. For such reason, the sales forecast is no more a luxury but a necessity for an organization.

For customized solutions that enable accurate sales forecasting for your business, get in touch with us.

Here are some of the most popular forecasting tools used by organizations to accurately predict sales:

Opportunity Stages Driven Model

Every salesperson would be tracking his/her sales progress by analyzing the likelihood of converting a prospect based on their sales cycle. There is a higher chance of conversion if the client is progressed further down the sales cycle.

The Calculation

All opportunities are mapped out and assigned a probability for the deal to be closed. The further down the sales cycle a prospect is in, the higher the probability of conversion.


Expected Revenue = Deal Amount * Probability to close

All the leads or opportunities are then mapped out according to the stages they are at, and with its help, an expected revenue figure can be forecasted.

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Sales Forecasting Opportunity Stage Model

The manual calculation of this model can be tedious and time-consuming. Therefore, adopting a good CRM software will aid in sales forecasting by eliminating human error and simplifying the process.

The Lead Driven Model

The lead driven model focuses on the value of each lead and assigning a probability for those to convert into revenue.

The Calculation

The sales team must first figure out the average value of a lead.

Average Lead Value = Average Sales Price x Conversion Rate from Lead to Customer

Here, the conversion rate from lead to customer can be derived from historical conversion data.

The next step is to ascertain the number of leads required to achieve a target revenue. This can be estimated by:

Leads Required = Desired Revenue / Average Lead Value

For instance, if a business targets a $100,000 revenue with an average lead value of $1500.

Leads Required = $100,000 / $2,000

= 50 leads

The sales forecasting can now be done using CRM software; but it could also be carried out by identifying the expected number of leads and multiplying it by the average value per lead.

Request a free platform demo to learn how we help businesses with accurate territory-based forecasts that help standardize sales and pipeline reporting strategies.

Advanced Predictive Sales Forecasting

With the advent of software and devices with intense computing power and complex econometric models, it has become possible to assign a forecast figure by taking into account multiple factors affecting sales. By including multiple factors that influence sales, the sales team can come up with more accurate forecast. One such model is by using personal conversion rate of each employee, the average length of a sales cycle, and the probability of an opportunity closing into sales.

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