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Sales forecast accuracy a guessing game? Learn how to improve it.Sales Forecast Accuracy, the ability of a sales organization to accurately estimate the number of sales they will close over a given period, is an excellent predictor of success and the likely growth of your business.


Business leaders cannot budget without understanding cash flowing into the business due to sales revenue.

For physical products, you either run the risk of too much inventory stuck on warehouse shelves or too little stock available to meet sales demands.

Inaccurate sales forecasts are a death knell for your business.

Alongside Sales Efficiency and Productivity, accurate forecasting is one of the primary measurements companies can use to understand the scalability of their business.

While you can read an overview of all three KPIs in our in-depth article on Enablement metrics, we are going to go deeper into sales forecasting in this article, covering:

  • What is a sales forecast?
  • What are the standard methods used for sales forecasting?
  • What are the issues with poor forecasting?
  • What is sales forecast accuracy?
  • How do you measure accuracy?
  • What is the Trust Enablement Forecast Accuracy Model?
  • How can you improve sales forecast accuracy with enablement?
  • Sales Behaviors that lead to bad forecasting

What is a sales forecast?

A sales forecast estimates the number of sales made over a given period.

Individual sales reps must learn to project their sales. Sales managers and other sales leaders must learn to do it for their teams. Ultimately, the CEO will bring the overall forecast from the Chief Revenue Officer and present it to the board and, for public companies, shareholders.

What are the standard methods used for sales forecasting?

Teams use several different methods for creating a sales forecast.

These methods include:

    • Pipeline Forecasting
    • Deal Length
    • Best Guess
    • Historical Data-Driven

Of course, other methods are often created as a combination of these other projection methods.

For this article, let’s focus on these three.

Pipeline Forecasting

With this forecasting method, each deal stage is assigned a probability of reaching a closed-won deal.

In the following example, we will use an overly-simplified model:

  • Discovery call Scheduled: 5%
  • Demo Delivered: 40%
  • Paperwork to Procurement: 80%

We can use these probabilities across all open deals to forecast. Again, keeping it simple, look at a deal worth $100,000 where the current stage has reached Demo Delivered.

We would forecast the deal value as:

(100,000*0.4) = $40,000

Of course, there are challenges with pipeline forecasting, but the most common to consider include:

  • It does not consider the average deal length from one stage to the deal-won point. For example, your average deal cycle from Demo Delivered to Closed Won is nine months, so you should not forecast this revenue in the current week/month/quarter.
  • The stage probabilities are often not created based on actual data. At least yearly, review deals from the prior year (or two) to determine the real chances and update your model.
  • Deal stage changes happen regularly.  If you are using pipeline forecasting, update your forecast weekly or bi-monthly to keep your projections accurate.

If you deal with these challenges, pipeline forecasting can be a good choice for your business.

Average Deal Length

This approach is not significantly better than the last one.

We look at the average deal cycle length in sales cycle forecasting and subtract each deal’s current amount of time in the funnel.

For example, if your average deal length is ten months, and you have a hundred thousand dollar deal, you have been working on for ten months; you would give it a 50% forecast value.

(100,000*0.5) = $50,000.

Much like opportunity stage forecasting, this model falls short due to a lack of data-driven modeling. At least yearly, look at the probability of closing based on the amount of time in the sales cycle.

You may learn that deals have a 70% chance of closing at the five-month mark, use these insights to improve your models.

Best Guess

Intuitive forecasting is only appropriate when you have no historical data — it is pure guesswork, and gut feel from each seller.

In a new startup, for example, about to create its first forecast, intelligent guesses are what you have.

But, as the forecast process matures along with the business, you must move aware of this approach. You can risk poor accuracy of your sales early on; you sometimes have no choice. But, if your forecasting processes do not shift to more accurate methods, expect to be looking for a new sales role sooner than later.

A sales manager who cannot accurately predict must learn to do so or find another role.

Historical Data-Driven

This approach to creating a sales forecast also has its pros and cons. You can quickly lose sight of seasonability, market changes, and other factors that invalidate the comparison. Comparing apples to oranges won’t work.

However, historical sales data, often extracted from your revenue or sales operations team’s CRM systems, can significantly increase your forecasts’ accuracy.

Generally, you take the past periods’ data, factor in planned growth, and develop your projected sales.

For example, if you had sales totaling $1.5 million in Q1 of 2023 and are seeing a growth of 5% year-over-year so far this year, you could forecast Q3 of 2021 as:

(1,500,000*1.05) = $1,575,000

Issues with Inaccurate Forecasting

Inaccurate forecasts can result in adverse outcomes like:

  • Missed sales targets
  • Disappointment in the market and lower stock prices
  • Reduced employee morale
  • Lower or negative profitability

Inaccurate forecasts can result in adverse outcomes like:

  • Employee layoffs – from the front line through the executive suite
  • Customers switching to competitors due to loss of confidence in your business
  • Investor pressure from wall street or venture capitalist

Inaccurate forecasts can result in adverse outcomes like business failure.

That is why it is vital to create more accurate predictions.

What is Sales Forecast Accuracy?

Sales forecast accuracy reflects your historical ability to predict the number of sales you will close.

Many businesses will forecast a quarter at a time, using weekly and monthly checkpoints to adjust the forecast as the quarter goes along.

Did you know that more than 68% of companies report missing their sales forecast by at least 10%?

How Do You Calculate Sales Forecast Accuracy

For this example, we will use quarterly data.

  • At the beginning of the quarter, provide your initial forecast (FORECAST)
  • At the end of the quarter, how close document the value of deals you won (FINAL).
  • Record the dollar value difference between FORECAST and FINAL (DIFF) at the end of the quarter.

The formula for sales forecast accuracy is:


If we begin the quarter with a forecast of $100,000 and we close $105,000 in sales, our sales forecast accuracy is as:

((1-(5,000/100,000))*100) = 95%.

Note:  Sales forecast accuracy can not be a negative number.

Easy, right?


The Trust Enablement Forecast Accuracy Model

Various research studies show that few forecasts are accurate within an acceptable margin of error.

Of course, you will never make a perfect projection, but we created a straightforward model to help you judge how well you are doing: The Trust Enablement Forecast Accuracy Model.

Based on your forecast accuracy over the last four quarters, take the lowest level of precision to determine where you are on the maturity scale.

  • World-class is within 10%
  • Elite is within 20%
  • The average is within 30%
  • Poor is within 40%
  • Random is anything worse than 40%.

How did you do?

How do you get better?

How Can Enablement Help You Improve Sales Forecast Accuracy

Enablement can provide the tools and processes to improve sales forecast accuracy.

Enablement should partner with operations and the customer-facing teams at every prospect and customer touchpoint. At these points in the journey:

  • Sales forecasts should be reviewed and updated as deals move through these stages.  This applies to all forecasting methods (e.g., pipeline forecasting).
  • You should analyze sales data to refine standard estimation techniques, ensuring that your forecasting process improves as each customer or prospect progresses.

Estimating future sales is complex, and teams should collaborate across every touch to identify trends impacting the ability to make an accurate estimate.

Agree on the forecasting model

Many outside the sales leader do not understand the sales forecast in many businesses. Ensure everyone in your go-to-market team is clear about the model used, how it works, what is expected of everyone to ensure accurate forecasting, and why a specific forecast matters.

Enablement and operations teams should train, reinforce, and document everything so veteran and rookie sellers are crystal clear.

Publicize the forecast

The forecast is not a state secret.

Publish the current estimates and any adjustments made.

Business can only improve their forecasting method when forecasts are visible and can be analyzed by all involved.

Analyze the forecast

Review the forecast for all managers and individual contributors. Based upon the model used, pinpoint opportunities for improvement.

How does the likelihood of reaching closed-won compare to the average for each rep, seller, and product?

For all of the following, consider the following:

  • What training is needed to reach an average or above?
  • What coaching would help?
  • Content?
  • Are processes being followed and enforced?

Pipeline Forecasting

If the probability at the Demo Delivered stage is 40%, do you have sellers, entire sales teams, or products much lower?

Deal Length

If the average sale lasts nine months, do you have sellers, entire sales teams, or products much lower?

Best Guess

Are some sellers and leaders better at reading the forecast tea leaves?

Historical Data-Driven

Do some reps struggle more during different periods than others? Are their customers more seasonal in nature?

Sales Enablement can play a critical role in improving forecast accuracy. By partnering with operations and customer-facing teams, enablement can provide the tools and processes necessary to improve accuracy. Additionally, enablement should continuously review and analyze data to refine estimation techniques. With these efforts, your business can increase the maturity scale and improve sales forecast accuracy. Are there other sales forecasting methods like moving average forecasting?

How does your company compare to the average?

What is your forecast accuracy for products, sellers, and sales teams?

What are the opportunities for improvement?

Sales Enablement can play a critical role in improving forecast accuracy. By partnering with operations and customer-facing teams, enablement can provide the tools and processes necessary to improve accuracy.

Two Sales Behaviors That Impact Forecasting

Sandbagging and happy ears are two all-too-common sales behaviors that negatively impact your ability to create reliable forecasts.

What is sandbagging in sales?

Sandbagging in sales occurs when a rep chooses not to add a deal to the CRM forecast or simply not add it as a deal likely to close within a given period.

In other words, sandbagging removes the pressure to close the deal but provides tremendous upside to the rep as they appear to have worked magic to bring the opportunity into the quarter.

Everyone likes being a hero.

When you see your sellers doing this, squash it. You don’t need heroes. You need salespeople that are reliable, predictable, and successful.

What are happy ears?

Happy ears usually occur with inexperienced reps who falsely identify deals as ready to close, only hearing positive news and missing out on signals that the opportunity could be in trouble.

Happy Ears sounds like a new Disney character. All cute and cuddly and living with Snow White.

Happy ears are neither cute nor desirable within a sales team.  

When you see happy ears, coach and train the rep to have better discovery conversations, educate them to ask better questions, and help them understand the positive and negative signals within the deal.

Note: Happy ears and sandbagging in sales blow up your forecast, whether you use pipeline forecasting or any other method.  When you see these, put a stop to them immediately.

Sales Forecast Tools

The Right CRM

The smallest companies might track opportunities and customers in a spreadsheet, but many businesses use a CRM to track their pipeline.

The table that follows breaks down the most common CRM solutions.


CRMIdeal for Customers Like…G2 RatingsPros of This CRMCons of This CRMPricingTry Now
FreshsalesBusinesses making under $20M annually4.6/5.0
(958 Reviews)
Pricing from Free through $83/per user/month
Try Now
HubspotBusinesses making under $50M annually4.4/5.0
(8277 Reviews)
Top-of-the-line Marketing Automation Plus CRMFree CRM is solid but the least robust of the three. Adding in paid features becomes expensive.Pricing from Free through $120/user/month
Try Now
(145 Reviews)
PipedriveBusinesses making under $20M annually.4.3/5.0
(1498 Reviews)
Easy to use Contact and Deal FlowFewest Integrations — Use solutions like Zapier to close the gap.Pricing from $12.50/user/month through $99/user/month
Try Now
SalesflareBusinesses making under $2M annually4.8/5.0
(196 Reviews)
Very easy to use the system and works well with Microsoft Outlook, Gmail, and LinkedInOnly lightly customizable and with limited integrations. Pricing from $29/user/month through $99/user/month
Try Now
SalesforceBusinesses making more than $100M4.2/5.0
(12308 Reviews)
Customizable and Scalable to meet the needs of the largest businessesMost complex solution to learn.A vast number of options.
Try Now
SnovioBusinesses making under $2M annually4.5/5.0
(169 Reviews)
Pricing from $33/user/month through $615/user/month
Try Now
ZohoBusinesses making under $50M annually4.0/5.0

(2084 Reviews)
Pricing from $14/user/month through $52/user/month
Try Now


Sales Forecast Tools – Process and Scale

There is another category of sales forecast tools focused entirely on increasing forecast accuracy; tools like Funnelcast fall into this camp.  To learn more about tools like these, view our walkthrough of Funnelcast.

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