How to Calculate Revenue Projections and Avoid Costly Errors

You can’t spend more than you make. Loans can help, but they must be repaid. If your expenses exceed your revenue, staying in business will be a challenge.

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Revenue projections help predict how much money your company will make over a specific period, ensuring you don’t overspend.

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97% of companies with top-notch forecasting processes met their sales targets, compared to only 55% without them. Businesses with accurate revenue projections are 10% more likely to increase revenue yearly and twice as likely to lead in their industry.

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Today, we will look at what revenue projection is and how to do it for your business to predict your future revenue growth:

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What Is Revenue Projections?

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While it’s known as revenue projection, you are not just looking at the sales team's efforts. Revenue projection examines numbers across your business from areas like HR, marketing, outreach, and other contributors to your income, beyond direct sales.

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Revenue projection is a mathematical process that uses a combination of quantitative and qualitative factors to create projection models and help your business understand its likely earnings.

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Why Is Revenue Projections Important?

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Revenue projection is a necessary part of any business plan. Without it, you won’t be able to decide how to spend your budget or what new ventures you could undertake. You wouldn’t be able to tell if your business might grow, stay stagnant, or shrink in the upcoming year. No matter the size or industry of your company, here are the top advantages to doing revenue projection for your business:

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1. Helps Create a Realistic Financial Plan

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One of the biggest benefits of doing revenue projection is being able to create a realistic financial plan for your business that you can rely on. Even though forecasting is just an estimate of your future finances, it gives you a range to follow. 

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2. Allows You To Predict Your Hiring Capacity

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With revenue forecasting, you get to know how much budget you can spend in each area of your business on a quarterly or monthly basis. Knowing this, you can predict if you can expand your team. You shouldn’t be expanding your team if you barely have enough cash to cover your current expenses. But you won’t know that unless you do a deep dive into your current financial situation.You also have to account for in which direction your company is headed. Are you planning to scale up your production or output? Did you just get a lot of new customers or sign a lot of new clients? If so, your revenue can go up in the future. And with more revenue coming in, you can think of expanding your team.

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3. Helps Set Revenue Goals

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The better you can predict your revenue, the easier it will be to set sales and marketing goals for your business. For instance, let’s say you project making $10,000 in a month for a startup. Based on your forecast, you can set goals by campaign for your marketing.You could also use the projection to set sales benchmarks for your sales associates. You can use them to set an expected quota for all of your salespeople or structure your bonus tiers.

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4. Gives You an Idea of How to Scale Your Brand

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Every business wants to grow. You are not doing hard work to watch your revenue stay stagnant. Most businesses want to scale up their sales, production, marketing, and other key areas. But that’s hard to do if you don’t have a budget for each area. 

Projecting your revenue helps you predict what revenue your business will generate over time based on the adjustments you make to different areas of your business and the current economic conditions in your industry.

This data will help you create a scaling sales strategy that makes sense for your business without growing too slowly or too fast.

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How To Project Revenue?

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1. Estimate Expected Income

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Calculate the expected income from all planned operations over a specific timeframe to begin projecting revenue.

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To do that, you will need to do the calculations twice, one for the worst-case scenario and the other for the best-case scenario:

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In the best-case scenario, both confirmed and potential projects will generate profits for the company. In the worst-case scenario, only confirmed projects will generate profits.

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For instance, if your company has 3 confirmed projects that will generate $300,000 income and 5 tentative projects that will generate $5,000,000, then your projected revenue calculations include $600,000 (according to best-case scenario) and $25,000,000 (according to worst-case scenario).

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2. Calculate Projected Expenses

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If you already know your income for a given period, you need to determine the expenses your company will cover in that same period.

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To check that, you need to add: 

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• The costs of any planned investments. 
• Estimated costs of work based on the project schedule or project scope.
• Project and company overheads, including taxes, bills, and non-billable departments (i.e. administration, marketing, sales).

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In the example we shared in the previous step, you will also need to repeat the calculation for the best-case scenario (minimum costs) and the worst-case scenario (with a maximum amount of costs).

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3. Subtract Expenses From Income

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Once you have calculated your expenses and income, you can start projecting revenue for different outcomes - good and bad. 

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You can test different combinations here, but in order to get a fixed range of possible profits: 

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• Deduct minimal expenses from maximum income. 
• Deduct maximum expenses from minimal incomes.

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Doing so will leave you with a range of income you can expect in a given timeframe. 

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How Often Should You Project Revenue?

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Most businesses project their revenue at least once a year. The most common times to do it are in the last quarter of the year or at the beginning of the first quarter to project revenue for the current year. Some businesses break the projection down into smaller chunks, such as looking at predictions quarterly or half-yearly. Others project far in advance, with three-year and five-year predictions.

The more timeframe your projection covers, the more uncertain and less accurate it may be. Whether you are doing short- or long-term projections, it’s always helpful to update them as your audience's opinions, industry, and external factors change. This way, you are always dealing with the most certain projections possible.

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8 Forecasting Methods to Predict Your Revenue for Permanent Growth (+Examples)

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To help you find your ideal revenue forecasting approach faster, we have gathered the 8 top revenue projection methods so that you can start predicting revenue more accurately.

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1. Historical forecasting

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Historical forecasting analyzes sales data from previous months, quarters, and years to predict upcoming sales for that same time period. Use it when you have detailed access to your accurate historical sales data.

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Example

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If you wanted to create a Q3 sales forecast, you would look at the third quarter of the past three years and create an estimate based on year-over-year growth. 

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Pros

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• Accurate sales forecasts because you are using your own historical data.
• Fast and easy to calculate if you are familiar with your CRM tool, sales process, and reporting.

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Cons

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• Doesn’t factor in any changes you have made recently to your business, such as launching a new product or service offering that you didn’t have in previous quarters.
• External factors like economic changes or new competitors aren’t factored in.
• Growth isn’t always steady. Hence, making assumptions based on past data alone could lead to under or overestimating sales for an upcoming timeframe.

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2. Pipeline forecasting

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Pipeline forecasting, also known as weighted pipeline forecasting, predicts revenue based on opportunities currently in your sales pipeline and their likelihood of closing.

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Example

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Let’s say one sales rep is talking to 5 potential customers, each with the potential to bring in $5,000 in revenue. This rep estimates that the first two deals are 50% likely to close while the other 3 are 75% likely. So the sales forecast will be:

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Prospect 1 = $5,000 x 50% likely to close = $2,500

Prospect 2 = $5,000 x 50% likely to close = $2,500

Prospect 3 = $5,000 x 75% likely to close = $3,750

Prospect 4 = $5,000 x 75% likely to close = $3,750

Prospect 5 = $5,000 x 75% likely to close = $3,750

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= $16,250 is projected revenue for that quarter

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Pros

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• Not as time-consuming as the other forecasting methods.
• Requires sales reps to be realistic about opportunities when assessing the likeliness to close.
• Requires sales reps to always keep the CRM up-to-date to ensure accuracy.
• Sales reps can seek input from other departments to feed into their calculations based on what they know about customer acquisition.

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Cons

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• Sales managers rely on sales reps' gut feelings or intuition to predict sales, which can lead to inaccurate forecasts.
• The forecast doesn’t consider changes in market conditions, such as economic fluctuations, competitor activity, and customer demand, that can impact the prediction of future sales.

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3. Opportunity stage forecasting

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Opportunity stage forecasting predicts sales revenue by assigning a value to each sales opportunity based on its stage. The general idea is that the further your opportunities are in the sales funnel, the more likely they are to close. 

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Example

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Using historical data, you have fixed the following likelihood for deals to close based on your sales pipeline:

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• Incoming deals: 5%
• Qualified deals: 10%
• Product trial: 40%
• Product demo: 75%
• Proposal sent: 85%
• Closed deals: 100%

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Let's say you have a $1500 deal opportunity at the incoming stage, $1000 at the Product trial stage, and $2000 at the Product demo stage. The forecast for the 3 deals will look like this based on the probability for each of these deals to close:

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Deal 1: 5% x $1500 = $75

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Deal 2: 40% x $1000 = $400

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Deal 3: 75% x $200 = $150

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Total forecast amount for these 3 deals: $625

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Pros

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• Using the same percentages for stages of the sales funnel makes the calculation fast and easy.
• Factoring in how much was spent on lead generation or where those opportunities came from will increase your forecast accuracy.
• Similar to pipeline forecasting, you should ensure your CRM and stages are up-to-date to analyze your opportunities properly.

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Cons

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• The opportunity stage forecasting method doesn't account for the age of an opportunity.
• Overconfidence and unrealistic likelihood can be a hindrance to opportunity stage forecasting. 

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4. Opportunity creation forecasting

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Opportunity creation forecasting uses your current sales opportunities to predict revenue. The difference here is that you will dive into data around the closed deals and see what similarities exist among them.

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Then, you will compare that with your active opportunities. 

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To do so, start with the highest-value customers and identify what demographics, trends, and behaviors unite them. Then, apply an average close rate based on these factors by looking at your current pool. 

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Example

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If your best customers first discover you through blogs on your website and most often have 500+ employees, those two factors would increase the likelihood of closing similar opportunities.

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Pros

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• This method gives you a fairly accurate forecast if you have overwhelmingly clear customer trends.
• It requires upfront research and reporting to understand what you are looking for in opportunities.
• After that, analyzing opportunities with your benchmarks will be efficient.
• Using CRM data for the forecast also helps you learn more about your best customers and even influences your future sales and marketing efforts.

Cons

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• Opportunity creation forecasting can lead to inaccurate forecasts if market conditions change or if assumptions are overly optimistic.
• Without sufficient past data on new opportunities, the model can be less reliable.

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5. Lead-driven forecasting

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Lead-driven forecasting analyzes and compares your current leads to your best-converting leads historically.

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It’s similar to opportunity creation forecasting in the sense that you will need to compare leads by source and look at the conversion rates for all of your leads to assess them accurately. 

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You will need to maintain close relationships with other teams, including marketing, to stay informed of new lead sources or campaigns. 

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Example

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Let’s use historical data and conversion metrics to project potential revenue for each lead source.

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Using Q1 data, we calculate the value per lead and forecast revenue for Q2 based on the expected number of leads:

Pros

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• By tracking the lead progression through the sales funnel, your sales teams can better predict revenue flow and identify stages in your sales funnel where leads may drop off.
• This method helps to closely monitor conversion rates at each stage of the sales funnel, which makes it easier to optimize your funnel with insights.

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Cons

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• The reporting on leads can take time as cross-department efforts are involved.
• Any new lead sources, such as an affiliate program, will lack the historical data to assess them accurately.
• It only works if there are similarities across leads and if you have enough of a leads base to analyze.

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6. Length of sales cycle forecasting

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Length of sales cycle forecasting looks pretty straightforward on the surface: you consider your average sales cycle length. You will use that data to determine how likely a deal is to close as a benchmark. 

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Example

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Imagine you have recently closed 3 deals. Calculate the number of days it took to close each deal and then add up the numbers:

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• Deal 1: 60 days
• Deal 2: 63 days
• Deal 3: 55 days

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Total time: 178 days

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Next, divide the total number of days (178) by the number of deals closed (3), and you will see that your average sales cycle is approximately 59 days long. 

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Now you know that your average sales cycle takes approx 2 months, you can apply it to other sales opportunities in your pipeline. For instance, your forecast predicts a 50% chance to close if a sales rep has been talking to a prospect for a month.

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Pros

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• This method is not based on subjective factors like a rep's gut feeling.
• Simple and easy to track for businesses with similar sales cycle trends or a single product.
• You can separate leads into different buckets based on their sources, such as referral clients or cold email outreach clients.

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Cons

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• The accuracy of length of sales cycle forecasting depends on the precision of the data used. Inconsistent or unreliable data can lead to inaccurate forecasts.
• This method doesn't always consider the size of the deal, which can lead to inaccurate forecasts for deals that are larger than the average.
• Sales cycles can change over time, especially as a business grows or during a slow economy.

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7. Multivariable analysis forecasting

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Multivariable analysis forecasting is about collecting as many data inputs as possible and feeding them into a formula to calculate an accurate forecast every time.

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As you have likely noticed, many of the forecasting approaches mentioned above focus on one avenue to create predictions, such as your pipeline. But multivariable analysis pulls in information about your market, seasonality, active pipeline, historical sales data, and more.

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This way, you get a more comprehensive picture of what your revenue will be in the future. 

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Example

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Imagine having two sales reps, each working on a single account. Your first sales rep has sent a proposal to a potential customer, while the other rep gave a product demo to a different customer.

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With your first rep's win rate for the proposal stage with the expected deal value of $10,000 and the chance of the deal closing is 55%, the forecasted amount is $5,500.

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Your second rep has the expected deal value of $8,000 and 25% as the chance of the deal closing. This leaves you with the forecasted amount of $2,000.

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Add up the forecasted amounts of each of your sales reps to get to a sales forecast for this time period. In this case, your sales forecast would be $7,500.

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Pros

• It’s accurate compared to other revenue forecasting methods as it factors all of the most crucial factors in prediction! 
• The ability to shape the future of your business based on accurate revenue prediction because you know you have all of the most crucial factors accounted for in the forecast.

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Cons

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• Because of the complexity, multivariable analysis forecasting is not feasible for a new business or smaller company.
• It’s time-consuming and a bigger lift than other forecasting methods.

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8. Test-market analysis forecasting

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When you are ready to launch a new venture or product, test-market analysis helps you see how well it might perform for a small target audience segment. You can then take these findings to either make adjustments or fully launch. 

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Along with test-market analysis forecasting, you can also survey or field customer feedback to improve your product. This way, you will glean more than simply projected revenue from this endeavor. 

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Example

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If a software company is ready to launch a new product, it can apply test-market analysis to their existing customer base to test the market response. A second-time startup founder can use this method to do a soft launch of their product and identify their ideal customer profile.

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Once the analysis is run on a limited set of audiences, study the results to make full-fledged predictions before the full release.

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The only caveat is that you should not assume that all markets behave the same way toward each new product or service. You must be mindful of extrapolating the forecast data from one market to another owing to the differences in their psychographic, demographic, and technographic variables.

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Pros

• It can be very informative. You can share rich qualitative data obtained from conducting the forecast with your product, operations, marketing, and leadership teams.

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Cons

• Time and labor intensive as it requires introducing, tracking, and collecting feedback from prospective customers to generate your forecasts.
• While a test market can provide clarity into future sales, other factors can still arise as you roll out the product to everyone.

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6 Revenue Projection Mistakes to Avoid

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Understanding some of the most common revenue forecasting mistakes businesses make will help you better project revenue numbers for your business.

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1. Relying on Inaccurate Data

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You must analyze accurate data to forecast revenue for the coming months and years. However, it can be challenging to sort through your various data sources and determine which are the most accurate ones.

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Pay attention to data sources that have closely aligned data. You can bring your sales team together to analyze your collected data. They may be able to identify the causes of discrepancies and help you to reconcile the differences.

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Providing your sales team with a good forecasting tool will help you automate the process. This can save time and produce more accurate results. Because inaccurate forecasts can be detrimental to your business’s future.

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2. Disregarding Past Sales

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The only times you should deviate from using past sales numbers in your future forecasts are when you are just starting out or when you have drastically upgraded your product.

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Specifically, you can review historical data to determine how long it takes for your sales team to close a deal, what your conversion rates are and more. Through your analysis of past performance, you can better estimate the revenue that your business may produce going forward.

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Historical metrics, such as your company’s previous conversion rates, will help you estimate sales volume and revenue numbers more accurately in the future. Pay attention to seasonable fluctuations, adjustments to sales numbers when different marketing channels were used, and other patterns to identify opportunities to take advantage of them in the future.

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3. Not Defining the Purchase Journey

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Regardless of the industry you work in, every sales process has different buying stages. To maintain steady sales, you need to analyze customers’ purchase journeys in each stage of the pipeline and manage their progression through the different stages.

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To accomplish this, you must understand how your customers interact with your brand and predict when they may be ready to make a purchase. Analyzing how customers react to different marketing methods is necessary for this.

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More than that, you must analyze touch points in the past to accurately determine how a typical customer may react if your team takes specific steps. When you can predict behavior and adjust your efforts accordingly, you can better manage customer behavior and improve sales forecasting.

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4. Failing to Adjust and Refine Consistently

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The data you use to make accurate forecasts is not static. It can change quickly, and you should adjust your forecasting efforts accordingly. All forecasts must be continuously reviewed and recalculated.

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Regardless of the time and effort you use to create a forecast, it is useless if you do not update it based on the most recent data available. A smart idea is to use a CRM to collect, track, and gather more accurate information about customers’ behaviors, their status in the sales pipeline, and more.

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You don’t need to recreate the wheel each time you update your data. Since you already have the right analytical tools and a substantial amount of relevant data, you must update your data fields accordingly.

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5. Relying on intuition instead of sales data

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No sales forecast will be completely accurate, but those based on actual behaviors and data perform better than those based on feelings.

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6. Failing to define KPIs

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Deciding on specific metrics that sales teams and management agree on is crucial if you don't want constant forecast debates. With clearly defined KPIs (key performance metrics), everyone will measure the same data and work towards the same goals.

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4 Barriers to Accurate Revenue Projection

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There are a few factors that consistently interfere with ensuring accurate Revenue projection:

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• Data Problems: The wrong data, not enough data, or data based on potential deals that may or may not close.
• Excessive Positivity: The tendency when creating a revenue forecast is on the most positive possible numbers and receivable or sales increases, even when those numbers are the least likely
• Disconnect Between Forecasts and Reality: Businesses that consistently use sales professionals’ forecasts without reviewing how accurate those forecasts really were at the end of the term may encourage reporting without accountability
• Evaluating Sales vs. Costs: The data on the cost of sales must be included in a full picture of sales forecasting. Of course, the depreciation of current assets can also impact the total cost of goods.

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If you are looking to forecast your revenue with precise data, check out our comprehensive guide to Revenue Intelligence to learn more about how it can boost your forecasting accuracy and help you reach your sales goals faster.

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Final thoughts

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When done right, revenue projection becomes your company's most powerful ally. It lets you impact sales outcomes, make better decisions, manage resources, and address any challenges that come your way by helping you understand what drives your business.

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Revenue is what helps businesses move forward at the end of the day. Without making the effort to forecast revenue as accurately as possible, you risk leaving important business decisions up to guesswork.