May 12, 2021

Written by

Collective[i] Team

  • Posted in
  • Sales Forecasting
  • Sales Forecasting Examples

How do you calculate a sales forecast?

How do you explain sales forecasting? The idea of looking into the future and saying “this is how much we will sell” brings to mind cliched images of psychics. Most businesses use some version of sales forecasting in order to predict upcoming revenue, and the most successful businesses are those who use sales forecasting effectively and efficiently. There are many questions that need to be answered when attempting to calculate sales forecasts, and today we are going to take a deeper look at these questions and answers. The main question is, of course,“how do you calculate sales forecasts?” But before we get to that, we first need to answer a more basic question.

What are the basic types of forecasting?

The basic types of sales forecasting are qualitative, quantitative, and AI-enabled.

Qualitative: The opinion forecast

This is a very traditional method of forecasting that many B2B organizations utilize. Because it is organized around sales professionals’ opinions, this method used alone is not known for accuracy.

Quantitative: The data forecast

Quantitative data aims to spot patterns in historical data and use them to project future sales. This data might come from a CRM, from external sources like market prices, or even soft commitments from existing customers to make certain purchases in the future.

Many sales organizations combine both qualitative and quantitative data to predict their upcoming revenue streams. But there are new technologies and tools that are making forecasting both easier and more reliable.

AI-enabled: The prescriptive forecast

Utilizing deep learning on both structured and unstructured data, the prescriptive forecast is an emerging method that is able to better formulate accurate forecasts. Unlike other methods, both historical data and subjective factors like a seller’s network are combined with broader market data to provide insights and make recommendations on how to increase win rates going forward.

Essentially, the opinion forecast and data forecast methods are primarily developed by leaning on human understanding and narrow data, while the prescriptive forecast is starting to use broader data sets outside a company’s historical data to find patterns no individual seller could spot on their own.

How are forecasts calculated?

There are many different statistical methods of sales forecasting, including qualitative and quantitative, that are utilized by businesses. One sales forecasting example would be a historical analysis — looking at the percentage of growth of sales from January to February in order to predict the sales in March. While on the surface, this may seem like it is rooted in data/quantitative methods, it’s also based on a human opinion that the percentage of growth will remain the same.

Many traditional tools like Microsoft Excel utilize proprietary algorithms and formulas to identify patterns in sales data and predict future revenue. But more important than understanding how those formulas work is understanding how modern sales forecasting should work. Because no tool relying on historical data alone will be able to provide a truly accurate forecast.

AI-enabled forecasting: the future of sales forecast calculation

Imagine what sellers could accomplish if they were able to spend less time wrestling with forecasting calculators and more time actually selling? Sales forecasting takes a significant chunk of time and effort, and requires understanding and learning how to use complicated methodologies that aren’t accurate or efficient. What would it look like to shift sales forecasting to a method that offers better results while taking significantly less time?

Collective[i] has the first true AI-empowered and adaptive forecasting tool, known as Intelligent ForecastTM, that frees time and allows sellers to act quickly to create better outcomes for their organization.

Utilizing artificial intelligence, our prescriptive forecasting method can achieve a 98.6% forecast accuracy and productivity gains starting at 20%, delivering updates, recommendations, and risk alerts in addition to a highly accurate daily forecast. That’s a calculation worth paying attention to.

Our one-click forecast uses AI to turn historical data and current market conditions into next and best step recommendations and insights. Our probabilistic predictions that factor in both internal sales history and external data for a much more accurate forecast. Contact one of our forecasting experts to find out how Collective[i] can help your business.

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