Revenue forecasting guide: models, tips, and more

When it comes to revenue forecasting, it’s all about your business

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Revenue forecasting is a critical part of any business plan and strategy. A solid forecast can help you take advantage of opportunities in your industry, make smart decisions about investments, and prepare for the future.

But how do you do it? What should be included in your forecast? What forecasting software can help? We’ve put together this guide to help you answer those questions and start forecasting the right way.

What is Revenue Forecasting?

Revenue forecasting (also called revenue projection in some cases) is a process of estimating the future revenue of a company. It’s typically based on historical data but can also be influenced by external factors like market conditions and economic trends.

The goal of revenue forecasting is to predict and plan for how much money will be coming in over the next few months or years so that you can decide whether you need to hire more employees or order more inventory, among other things.

Why Revenue Forecasting is Important

There are many reasons why you need to do revenue forecasting. Here are some key points:

  • It helps you predict how much money you’ll need to ensure your company has enough cash flow to keep running smoothly.
  • It enables you to predict when to hire new employees and scale up operations to meet the demand for your products or services.
  • It helps you avoid sales shortages by showing you how much inventory you need on hand at any given time.

Revenue Forecasting vs. Sales Forecasting

Sales forecasting and revenue forecasting are two important tools for business owners, sales teams, and marketers. They’re both used to help predict a company’s future, but the two terms have different meanings.

Sale forecasting refers to predicting the number of deals your business will close within a given period. It provides insights into how much you can expect to close over the next month or quarter so that you can plan your staff and resources to meet that projection.

Meanwhile, revenue forecasting takes into account the entire lifecycle of a deal, from start to finish. This means looking at things like the length of the sales cycle, payment terms, and any potential upsells or cross-sells.

Revenue Forecasting Models

There are many different types of revenue forecasting models. One common model is bottom-up forecasting, where you estimate the sales of each product or service, then add them all up to get an overall estimate. Another is the top-down forecasting model, which starts with the overall market demand and then breaks it down into individual product categories and subcategories.

Apart from these two models, you can also try the following ones:

1. Straight-line model

The straight-line method is a simple forecasting model that estimates future revenues based on past growth. The model assumes that the company’s revenue will grow at a steady rate, and it uses the average of the past two years of growth as a baseline.

For example, if you have $10 million in revenue this year and expect it to grow at 10% per year, your expected revenue for next year would be $11 million ($10 million × (1 + 0.1)).

The straight-line method is easy to use but has some drawbacks. The most obvious problem with this model is that it assumes every year will be exactly like every other one, which isn’t always true. More importantly, you can’t use this method if your company has experienced dramatic growth or a decline in the past few years.

2. Moving Average forecasting model

The moving average method is a revenue forecasting model that uses the average of a series of historical data points.

A moving average is calculated by adding up all of your revenue numbers from one year and dividing them by the number of months in that year (i.e., 12). This gives you an average monthly revenue amount for the year being analyzed. You can then compare that number with current revenue figures to predict what might happen next month or next quarter.

For example, if your current month’s revenue is higher than last year’s average monthly revenue, then you’ll probably see increased sales this month; if your current month’s revenue is lower than last year’s average monthly revenue, then you’ll probably see decreased sales this month.

How to Start With Revenue Forecasting Software

Today, companies use data to make better decisions about their future business growth and strategies. Using revenue forecasting software like Revenue Grid is a great way to do that because it allows you to see what’s coming down the pipeline, so you can plan accordingly.


Another benefit of using Revenue Grid is that it allows you to detect risks and opportunities right away. That means you’ll be able to act quickly when something goes wrong or capitalize on an opportunity before anyone else does. Hence, you can avoid costly mistakes and keep your company moving forward.


Revenue forecasting software also sends alerts when things aren’t going as planned so that you can address them before they become real problems. It’s a great way to stay on top of things that can help you close more deals, acquire more customers, and boost revenue.


How to Forecast Revenue

Follow the steps below to start doing revenue forecasting:

Step 1: Set goals for yourself and your team members.

Whether it’s a particular number of sales or a specific dollar amount from a customer over a given timeframe (like monthly), having specific targets makes it easier for everyone to contribute to the forecasting process.

Step 2: Review past performance.

What did your revenue look like last year? How much did it change year over year? And what were the biggest changes you saw? If there were any major changes, what caused them?

Step 3: Learn about your current customer base.

Who are they? Where do they come from? What kind of products or services do they buy from you? Are there groups of customers who have similar purchasing habits? If so, how can you better serve them by ensuring their needs are met?

Step 4: Make sure you’ve got all the data you need.

This includes financial data, as well as data about customer behavior and market trends. Use your revenue forecasting software to find it.

Step 5: Gather your team for a brainstorming session.

This is where everyone gets together and thinks about what might happen in the future. Maybe there’s been a shift in regulations that affects your business model, or perhaps an industry trend might make it harder for people to find your products or services. Then think about how those things will affect your revenue—will they increase or decrease it? And by how much?

Revenue forecasts are vital in setting goals, measuring performance, and informing strategic decision-making. It’s impossible to make well-informed strategic decisions without understanding what you can achieve in the future.

Improve your revenue forecasting with Revenue Grid

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    How to perform revenue forecasting with Revenue Grid

    Revenue Intelligence from Revenue Grid is a brilliant way to not only track forecasts and manage your pipeline in Salesforce, but also to quickly get insights on which deals need intervention. It does this by offering a set of analytics and predictive capabilities to answer important questions. Will you hit your revenue targets? Where are there risks in your pipeline? What can you do to close forecast gaps?

    Revenue Intelligence enables your company to:

    • Forecast sales with precision


    • Understand where to focus and communicate efficiently with your team about where to pivot for quick success.


    • See the pipeline growth during the selected period with pipeline evolution reports and adjust your revenue projections when needed


    • Guide your team at each stage of sales forecasting process with Revenue Signals


    Using our revenue intelligence capabilities, Revenue Grid will predict your revenue outcome with 96% accuracy.

    Improve sales forecasting with Revenue Grid now

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      Core UX Writer at

      Lavender Nguyen is a Freelance Content Writer focusing on writing well-researched, data-driven content for B2B commerce, retail, marketing, and SaaS companies. Also known as an Email Marketing Specialist, she helps ecommerce B2C brands develop high-converting, customer-focused email strategies.