Sales Forecasting: Small Business Guide

by Creating Change Mag
sales forecasting


Did you know there are various methods for sales forecasting? 

These methods include the following: 

  • Opportunity stage 
  • Length of sales cycle 
  • Intuitive 
  • Historical 
  • Multivariable 
  • Pipeline 

Here’s what you must know about each of these methods! 

Opportunity Stage Forecasting Method

This sales forecast strategy accounts for the sales process stages and where each deal is. 

The deals that are further along in the pipeline, the likelier they are to close. 

After choosing a reporting period (month, quarter, etc.), multiply each deal’s potential value by its probability of closing!

Opportunity Stage Forecasting Pros and Cons

The benefits of this sales forecasting method include: 

  • It’s easy to create a sales forecast 
  • The calculations are objective 

Regarding the downsides, you must consider the following things: 

  • Inaccurate sales data leads to inaccurate forecasts 
  • The calculations don’t consider the age or size of each deal 

Opportunity Stage Forecasting Example

Let’s say your team creates the following percentages based on your pipeline and how likely deals are to close: 

  • Initial call: 5%
  • Qualified: 15%
  • Product demo: 25%
  • Product Trial: 55%
  • Final call: 88%

According to this model, a $2,000 deal at the ‘Product trial’ stage is 55% likely to close. 

Therefore, the forecasted value of this deal would be $1,100. 

Length of Sales Cycle Forecasting Method

This method predicts future sales using the age of each opportunity to estimate when they’re most likely to close. 

This strategy relies on objective data. 

Therefore, companies are less likely to get an overly generous forecast. 

Length of Sales Cycle Forecasting Pros and Cons

The pros of this sales forecasting process include: 

  • The calculations are objective
  • It’s easy to integrate lead sources for more accurate forecasts 

On the other hand, the cons of this method include: 

  • The calculations don’t always take the size or the type of each deal into consideration 
  • The technique only works if teams carefully track the data 

Length of Sales Cycle Forecasting Example

Pretend your company’s sales cycle lasts an average of eight months. 

If a sales agent has worked on an account for four months, the forecast may predict they’re 50% likely to win the deal!

Intuitive Forecasting Method

Intuitive forecasting is an excellent method if you have seasoned sales agents. 

In this method, managers ask their agents to estimate the likelihood of closing each deal they’re working on. 

Intuitive Forecasting Pros and Cons

The advantages of this method include: 

  • It relies on your sales team, who work with your prospects the most (and know them better than anyone) 
  • You don’t need to use or track historical data 

Still, there are some downsides to know, which include: 

  • Calculations are subjective 
  • Each sales rep can forecast sales differently 
  • It’s impossible to scale or replicate this method 

Intuitive Forecasting Example

Pretend you want to forecast sales for a business without data because it’s your first time doing business with them. 

After assigning a sales rep to the account, they forecast $33,000 in sales within a year.

Historical Forecasting Method

The historical sales forecast methodology is simple. 

With this strategy, you observe how much you sold last quarter and assume the result will be the same or greater in the current period!

Historical Forecasting Pros and Cons

The benefits of this method include: 

  • It relies on historical data (which can be helpful in steady markets) 
  • It’s simple
  • It’s easy to implement

The downsides of this strategy include: 

  • It doesn’t consider seasonality
  • It doesn’t consider market changes 
  • It doesn’t consider account buyer demand 

Historical Forecasting Example

Let’s say your company sold $50,000 worth of products last April. 

Therefore, using the historical forecasting method, you’d predict your future sales will hit $50,000 (or somewhere close). 

Multivariable Analysis Forecasting Method

Using the multivariable method to forecast sales is more sophisticated than other methods. 

For instance, this strategy uses predictive analytics and other factors like: 

  • Average sales cycle length 
  • Probability 
  • Individual sales rep performance 

Multivariable Analysis Forecasting Pros and Cons

The pros associated with using this method include: 

  • It relies heavily on present and historical data 
  • It is one of the most accurate ways to predict future sales

The cons of this method include: 

  • It requires an analytics solution or a forecasting tool, which can be expensive 
  • Sales reps have to track and clean sales data consistently

Multivariable Analysis Forecasting Example

Consider a company that uses multivariable analysis forecasting. 

Alongside observing the current quarter, they also consider the average length of the sales cycle, the probability of deal closure, and the performance of individual sales representatives. 

For instance, if a representative usually closes deals within two months and has a closure rate of 60%, they take these factors into account. 

If a $10,000 deal is currently in its second month, the forecasted value of this deal would be $6,000. 

Pipeline Forecasting Method

Lastly, there’s the pipeline forecasting method. 

With this method, companies review each deal in the pipeline and calculate the odds of closing it based on unique company variables. 

Pipeline Forecasting Pros and Cons

The advantages of the pipeline method include: 

  • It relies on sales data, making it more accurate 
  • It considers the unique factors of each opportunity

However, the disadvantages to think about include: 

  • Predictions can be easily skewed because they rely on data so much 
  • It (typically) demands a sales forecasting tool 

Pipeline Forecasting Example

Say your team usually closes deals between $1,000 and $5,000 within 90 days. 

All your current deals in the pipeline have a high likelihood of closing. 

As a result, you can use the data to determine your monthly and quarterly forecast. 



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