July 20, 2021

Written by

Collective[i] Team

  • Posted in
  • Sales Forecasting
  • Sales Forecasting Methods

What is the difference between qualitative forecasting and quantitative forecasting?

When exploring how to predict future sales, business executives have to choose the best approach for their company. Within the broad spectrum of sales forecasting, qualitative and quantitative approaches are the two broad categories. Let’s take a look at these traditional sales forecasting methods — and how modern sales teams are leveraging artificial intelligence (AI) for the next step forward in sales forecasting.

What is the difference between qualitative forecasting and quantitative forecasting?

Qualitative methods of forecasting are opinion-based and involve gleaning insights from individual buyers about their intent to purchase or from industry experts about how certain markets may behave in the future. Quantitative methods of forecasting generate insights from historical data — for example, by analyzing what sales looked like in a specific period of time in the past to project what sales might look like in a similar period in the future.

What are the qualitative methods of sales forecasting?

Qualitative methods are an important tool for contextualizing sales activity according to the instincts and opinions of sellers, buyers, and industry experts. Some of the top methods of qualitative forecasting are:

The Delphi method

In this method, a group of experts come up with forecasts by consensus in a structured, repeating process managed by a facilitator. First, a panel of experts is put together. The forecasting challenge is given to every expert, who creates a forecast and returns it to the facilitator with the reasoning. Each expert then receives feedback from the facilitator based on what others on the panel are saying, and then they all review and adjust their own forecast based on the feedback. That step repeats until the facilitator sees that the forecasts generally align. The final forecast is created by combining and aggregating the individual forecasts.

Market research

Market research is the process of collecting information on buyer behavior by polling customers through surveys, interviews, and more or mining data from customer touch points. Sales teams can utilize buyer insights to better understand how buyers perceive the value of their service or product, to learn about specific buyers’ intent to purchase in the future, and to inform their strategies and focus them on revenue streams that are most appealing to certain buyer audiences. Because market research is time-consuming, it’s often carried out by firms that specialize in it.

Expert opinions

This is the quickest and least expensive method of qualitative forecasting. It involves using the opinion of an expert, or a few experts, to create a forecast. Sales teams may interview internal subject matter experts for their opinions on which revenue streams have the most potential in the future or on how buyers may respond to new products or services. External experts, such as industry thought leaders and academics, can provide valuable perspectives on the broader market and a company’s place within it, informing seller expectations of buyer behavior.

What are the quantitative methods of forecasting?

The quantitative methods of forecasting are based primarily on historical data. Many of the most popular quantitative techniques represent time series methodology. Time series methods compare sales figures within specific periods of time to predict sales within similar periods of time in the future. For example, a Q1 2022 time series forecast would look at sales figures from Q1 of previous years.

A few of the most popular methods of quantitative forecasting are:

Naive forecasting

Naive forecasting is one of the simplest and most inexpensive forecasting models. The idea is that the next period of sales will match the last period of sales. For example, if sales in March were $10,000, then naive forecasting assumes that sales for April would also be $10,000.

Moving average

This technique generates a series of averages of two consecutive time periods based on historical data to predict trends. For example, if sellers have sales data for 12 months, they could take the averages of January and February, February and March, March and April, etc., and plot them on a graph. Visualizing the numbers this way reveals the trends and helps sales teams make predictions for the next period’s sales. The weighted moving average method is a variation in which the more recent data is given more importance, or weight, than older data in the calculation.

Trend estimation

Trend estimation is similar to the moving average method, but instead of averaging sales from two time periods, the sales of each period are plotted on a graph so the sales team can see the increases and decreases. The forecasts are based on the patterns observed, and those patterns can be simple or complex. In general, more complicated patterns translate to more uncertain forecasts.

What is the best way to combine qualitative and quantitative forecasting methods?

The short answer: with modern technology that transforms sales forecasts from predictions into prescriptions.

Collective[i]’s automated and adaptive forecasting tool, Intelligent ForecastTM, combines qualitative and quantitative methods to provide accurate forecasts that reduce human error and bias. The one-click forecast takes into consideration current market conditions, online buying behavior, your unique historical data, and a multitude of other variables to provide a more accurate prediction. More than that, Collective[i] uses artificial intelligence (AI) to build a forecast that provides sellers with clear next steps for driving revenue.

Intelligent ForecastTM is a sophisticated AI approach that will help you act quickly and increase your win rate. Experience the power of combining qualitative and quantitative forecasting with Collective[i].

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