7 Sales Forecasting Methods Explained with Examples

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7 Sales Forecasting Methods Explained with Examples
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The sales team spends 2.5 hours each week of their selling time on estimations and predictions. However, they can typically achieve less than 75% accuracy with an effective sales forecasting technique.

Forecasting sales is an important business task. A business leader needs accurate sales predictions to enable business leaders to make better decisions relating to setting targets, hiring, cash flow, and budgets.

Meanwhile, inaccurate sales forecasts for sales managers bring uncertainty that makes timely detection of problems in the sales funnel impossible.

This article discusses particular methods, examples, and pointers to create a viable sales forecast.

Sales forecasts can never be accurate since this is an estimations or just a prediction. However, you can make your forecasts provide a realistic result.

Sales Forecasting Methods

Sales Forecasting Methods
There are several methods for forecasting sales for your company, and a company chooses a method depending on its requirements.

Most organizations simultaneously employ sales forecasting strategies to obtain more projections. It can provide you with both the best-case and worst-case scenarios.

Length of Sales Cycle Forecasting

The forecasting approach for the sales cycle length uses data on the time it takes a prospective customer to convert into a paying customer.

This form of forecasting is objective because it does not rely on the emotions of your sales staff. It is ideal for businesses to track when new customers enter their sales pipeline.

Number of Days of Combined Sales = Number of Days from the First Contact + Customer Conversion

“The most important thing is to forecast where customers are moving, and be in front of them.” – Philip Kotler, an American Author

Lead-Driven Forecasting

This algorithm analyzes previous sales data from each lead source to predict the future. You’ll need the following measurements: Leads per month for the preceding month. The average sales price varies depending on the source. Divide the total number of leads required in a given period by the average lead value.

The average sales cycle may vary depending on the lead source. Other business efforts may pact your conversion rates. Modify marketing plans in response to new information or trends. It syncs them to verify your predicted lead volume and conversion rates are correct.

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

Opportunity Stage Forecasting

This model predicts the likelihood of an opportunity closing based on the prospect’s position in your sales process. In this technique, you anticipate future sales by multiplying the amount of each opportunity by the probability of that opportunity closing.

Expected Revenue = Deal Amount x Probability to Close

This method needs a CRM system that automatically assigns win probability for each stage, essential for an accurate forecast.

Intuitive Forecasting

The intuitive forecasting method depends on your faith in your prospects’ opinions. Your salesman is the ideal person to ask whether the sale will go through or not. If the sales representatives are optimistic, they may make exaggerated predictions, and there is no way to evaluate the statistics.

You must rely on complete and accurate details to drive more realistic sales predictions.

Test-Market Analysis Forecasting

The forecasting method of Test-Market Analysis allows you to roll out your product or service to a specific set of people depending on their demands. You can use the rollout findings to produce a more accurate future market projection.

Historical Forecasting

Historical forecasting does not account for dynamic market developments. For example, if your competitors executed a promotional campaign, you might see a drop in sales. Using this strategy, you anticipate the MRR, assuming a 10% annual growth rate.

Multivariable Analysis Forecasting

Multivariable analysis forecasting is a fantastic choice if you want the most accurate forecasting method. It considers elements from different sales forecasting methodologies, such as opportunity stage forecasting and individual rep performance.

Because it requires complex calculations, this strategy may be impractical for small enterprises.

To bed, the Sales Forecasting methods, check out the examples.

Importance of Sales Forecasting

Importance of Sales Forecasting

  • Sales forecasting is all about accessing how much time you have left in your budget to spend on new items and services.
  • Accurate estimates impart market credibility to publicly traded corporations.
  • When sales leaders rely on forecasts, privately held enterprises gain confidence in their operations.
  • Sales forecasting identifies potential issues and allows you to avoid or mitigate them.
  • You can research and discover that there aren’t enough leads created for the sales team to convert.
  • Sales predictions can also assist in hiring and resource/inventory management decisions.
  • Assume your sales estimate predicts an increase in demand.

Importance of Sales Forecasting

Sales Forecasting Examples

Ex. 1) Using Current Funnel

Assume you have three open positions this month: One with a brief phone call with an expected value of $2,000. Another believes it is worth $3,000 as he received a thorough demo, while another had an offer with a $2,400 estimated value.

The following possibilities could be there: “Phone Call” marks a 30% likelihood of closure. “Demo” may close at a 40% possibility while “Offer” has a 70% likelihood of closing.

To get a total sales prediction, you need to multiply the probabilities by the predicted value of the contract and add them all up to get $ 3,480, as shown in the following example:

Stage Win Probability Value Forecasted Amount
Position 1 Phone Call 30% $ 2,000 $ 600
Position 2 Demo 40% $ 3,000 $ 1,680
Position 3 Offer 70% @ 2,400 $ 1,680
Total $ 3,480

Ex. 2) Using Lead Scores and Multiple Variables

You can use a table to forecast your sales using lead scores and multiple variables. Use average opportunity sizes to calculate the anticipated value of any specific chance:

Divide your leads into three groups of varying qualities: A, B, and C. These variables impact the chance of a closing deal.

Assume that the organizations with 50 or fewer employees close at a little lower rate, whereas companies with employees more than that have more probabilities of closing the deal.

Lead Score Close Rate Close Rate Expected value per Opportunity created (average sales price = $ 8,000 )
0-50 51-100 Company size’
0-50
employees
Company size’
51-100
employees
A 25% 50% $ 2,000 $ 4,000
B 12.50% 25% $ 1,000 $ 2,000
C 2.50% 3.80% $ 200 $ 300

Ex. 3) Using Historical Data

Assume you had $300,000 revenue last month and that your sales revenue has risen at a rate of 12% per month over the previous year. Your monthly churn was approximately 1%.

Your projected revenue for the following month will be:

($300,000 * 1.12) – ($300,000 * .01) = $333,000

It is derived by multiplying the past month’s income by the projected growth, and from the resultant amount, you need to deduct the churn.

Factors Influencing Sales Forecasting

Factors Influencing Sales Forecasting

  • Economic conditions affect every firm and market. When the economy is in a slump, people/businesses lose money and are less likely to buy, whereas people are more likely to invest and buy when the economy is booming.
  • Policy changes or implementing new laws/regulations can benefit or hinder your firm. You must consider these when forecasting your sales for the coming month.
  • Changes in your product might have a significant impact on your sales estimate.
  • Factors such as new technology advancements, design, competitors running promotional offers, or new businesses entering the fray might modify and affect the industry’s market share – which will factor into your sales estimates.

4 Tips That Will Help You Forecast Your Sales Effectively

Improving the accuracy and efficiency of your sales projections and forecast technique is dependent on several things, including good organizational coordination, automation, reliable data, and an analytics-based process.

4 Tips That Will Help You Forecast Your Sales Effectively

1. Review Historical Data and Analyze Future Trends

To forecast your sales, you will need to understand the key details about similar products or services you are selling. You will also need to be careful about future trends to prepare from now itself.

The product you are selling has a raw material component that may lack in the future; you will need to have a backup plan.

2. Select Sales Forecasting Method

You must select the method that best explains your product or service to maximize your sales prediction. While predicting sales may look easy, selecting methods is more complex.

3. Understand Your Product or Service

If you are selling products or services of different categories, you need to identify them to predict their numbers better. If you include a product you no longer sell, your sales prediction may lead to incorrect results.

4. Multiply Sales Price and Quantities

Your sales price is fixed, and pre-determined. Hence, you need to estimate the number of units you will sell throughout the year. The prediction of the sales figures and their multiplication with the sales price will give you the sales prediction.

Final Words

A Sales forecaster must combine approaches with the managers’ knowledge and experience. The need is not for improved forecasting methodologies but for better utilization of the available tools.

While applying any forecasting technique takes patience, at Upmetrics, we help you optimize your sales forecasting process. Request your free demo.

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About the Author

Rudri                                                       
            Mehta

Rudri Mehta

Rudri is a passionate financial content writer and a Chartered Accountant by profession. She enjoys sharing knowledge through her writing skills in finance, investments, banking, and taxation while also exploring graphic designing for her own content.

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