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B2B Sales Forecasting Methods

August 24, 2020 DJ Team

b2b sales forecasting methods

Why Is B2B Sales Forecasting Important?

Sales forecasting is an essential element of any business plan allowing business owners to predict revenue and profit. Sales forecasting makes it possible to predict the support a business needs to meet expected demand. It helps with all aspects of a business from financial planning, supply chain management, inventory control, staffing needs, and informs marketing professionals about market trends.

Because sales forecasting is the cornerstone of a successful marketing campaign these are important characteristics of sales forecasting. The functions of sales forecasting allow you to estimate what you will sell over a specified period of time.

The Difficulties of B2B Sales Forecasting

The difficulties of sales forecasting come into play because the future is uncertain. There are a number of mitigating factors affecting sales forecasting including consumer demand, customer preferences, fluctuations in the economy, and even global events like COVID-19. Brand awareness also influences sales forecasts due to the quality and size of target customers along with products that may be at the end of their life cycle.

Factors Affecting Sales Forecasting

Because sales forecasting is not an exact science and involves a little art, using reliable data from the past and present helps to predict the future of sales with greater accuracy. The sales forecasting process begins by making a number of assumptions:

  • Is the economy growing or shrinking?
  • Is your market shrinking or growing?
  • Is there still consumer demand in your industry?
  • Are you launching new products or are any products at the end of their life cycle?
  • Are there any regulatory changes that might affect compliance?
  • Do you have a robust sales and marketing strategy?
  • Are you increasing your sales force?
  • Will you be raising your prices?

Calculating Sales Forecasts

There are a number of forecasting methods that can be used to predict your sales revenue more accurately using a forecasting calculator.

Lead Value Sales Forecasting

The sales forecasting process for this model is based on analyzing the accumulation of sales data from previous years. Analyzing historical sales data helps marketers spot trends in consumer behavior, their preferences, and seasonal purchases along with market trends. With this method, you gain a better sense of the probability that a lead will convert into a sale by assigning a value to each of your lead sources or types.

Average Lead Value = Average Sales Price x Conversion rate from lead to customer

Average sales price per lead

Opportunity Creation Sales Forecasting

This model for calculating future sales helps you predict the opportunities that you are more likely to close based on the behavioral and demographic data of your customer base and target market.

Expected Value of Opportunity = Average Sale Price x Average Close Rate

Historical Forecasting

An easier way to predict how much you will potentially sell over a given period of time is to look at sales during the matching time period in previous years. Providing market conditions haven’t changed that much, you would assume your sales should be equal to if not better than previous results.

Multivariable Analysis For Sales Forecasting

The most sophisticated method for forecasting sales is a multivariable analysis using predictive analytics.

How to Forecast B2B Sales Volume

The two types of sales forecasting techniques that are commonly used are quantitative sales forecasting and qualitative sales forecasting.

Quantitative sales forecasting uses historical data that can be extrapolated from a CRM system, marketing campaigns, and accounting records that rely on sound mathematical data rather than guesswork and opinion. These techniques include:

  • Trend Analysis: picking up on trends of past sales to predict similar fluctuations in the future.
  • Simple Moving Average: by extrapolating data from a set period of time and using this to predict sales over the same period of time in the future.
  • Exponential Smoothing: using a sales forecasting process making an exponentially considered average to predict future sales.

Qualitative sales forecasting takes into account human emotions using intuition, feedback from salespeople, and clients to make predictions about potential sales. Although it’s not as accurate as quantitative sales forecasting, it still has a place.

Which B2B Sales Forecasting Method Is More Accurate?

Which sales forecasting methods are more accurate depends on what suits your industry and business. Forecasting tools can make your life easier when it comes to predicting future sales revenue. Regardless of what method you use, all data must be clean and as accurate as possible.

Predictive Analysis is a forecasting tool using a sales prediction algorithm. Common predictive algorithms can be separated into two groups; sales prediction using machine learning and deep learning which is a subset of machine learning that takes into account other data points like audio, video, and images.

Using Salesforce forecasting tools that are built into the software allows you to learn which channels, messages, and content resonated with your customers giving you smart insights powered by AI analytics which you can use to more accurately predict future sales.

The next wave of sales forecasting innovation is coming from companies like Collective[i] with their network-based, AI-powered, sales forecasting software, which leverages not only your data, but also the data outside your walls (i.e., network data) which no other forecasting solution can touch.

DemandJump takes the guesswork out of digital marketing and removes blind spots by revealing more of the customer journey and competitive landscape than you could ever see before giving you the tools to calculate more accurate sales forecasting. Tap into our expertise in data analysis and marketing attribution making your sales predictions more effective. Contact us now and learn why leading marketers use DemandJump to improve ROI and fuel customer growth.

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