Top 6 Methods for Forecasting to Get Accurate Predictions

Forecasting can make or break a business. Every major decision — from budgeting to expansion — depends on it. Get it right, and you’re poised to optimize resources and drive steady growth. Miss the mark, and you might scramble to cover shortfalls.

Success relies on your ability to make informed, accurate decisions, and that means gut instincts and rough estimates can only take you so far. To shape your company’s future with more precision, you need forecasting methods tailored to your business model.

In this guide, we’ll explain what forecasting is, explore the top methods for forecasting, and help you determine which one fits your needs best. Plus, discover sales forecasting and learn how Rox turns ambition into action.

What Is a Company Forecast?

A forecast anticipates future business outcomes based on historical data, current trends, and strategic goals. Forecasting is often associated with financial planning, but it’s more than a budgetary exercise — it’s a core business planning tool that drives smarter, more proactive decision-making.

Think of forecasting as a way to guide business strategy. Leaders use forecasts to prepare for opportunities and risks. When they understand the possibilities that lie ahead, they can set more realistic targets and allocate resources more efficiently.

Sales forecasting is another common type, improving sales processes by giving businesses the information they need to optimize pipelines and adjust strategies. This makes it easier to automate sales processes — when you know what to expect, you can use AI CRMs like Rox to streamline follow-up tasks.

Rox is the first agentic CRM. It gathers data from across the internet, automates routine sales tasks, and anticipates customer needs with the power of AI. Analyze important data and deliver personalized experiences for each prospect faster than ever.

The 6 Main Types of Forecasting for Sales

Sales forecasting methods fall into two broad categories: quantitative and qualitative. 

Quantitative Sales Forecasting Methods

1. Straight-Line Method

The straight-line method is the simplest way to forecast sales. This forecasting model assumes that sales will continue at a constant rate over time, using past sales growth figures to predict future performance. 

Here’s how to forecast using the straight-line method. Let’s say your business saw a consistent 10% growth in sales each month for the last six months — for instance, you sold 1,000 units in the first month, 1,100 in the second month, 1,210 in the third month, and so on. Based on this data, you’d forecast that sales will continue to grow by 10% each month for the next six months.

This method doesn’t account for sudden changes in market demand and external factors that affect sales, such as supply chain delays and economic fluctuations. It works best when sales growth is steady and predictable, which is rare. Most businesses will benefit from a more complex method.

2. Moving Average Method

Like the straight-line method, the moving average method relies on historical data for forecasting. But instead of assuming sales trends continue at a constant rate, it accounts for fluctuations by averaging sales over a specific period. This identifies long-term trends while minimizing the impact of short-term spikes or drops.

Say that last quarter, your sales figures were 1,000 units, 500 units, and 1,200 units. To calculate your moving average, you’d add those numbers together and divide by 3 (the number of months in the quarter). Your moving average would be 900 units, which would be your forecast for each month of the next quarter.

3. Simple Linear Regression

Simple linear regression is a more advanced forecasting method. It predicts future sales based on a single independent variable (such as marketing expenditure). By analyzing the relationship between past sales and that variable, you can forecast future performance.

If you’ve noticed that for every $1,000 spent on marketing, your sales increase by 200 units, you can forecast how future marketing spend impacts sales. If you plan to increase the marketing budget by $5,000, the model predicts that sales will increase by 1,000 units.

4. Multiple Linear Regression

Unlike simple linear regression, multiple linear regression uses several variables (like marketing spend, economic factors, and seasonality) to predict future sales. This results in a more nuanced forecast that accounts for multiple influences on sales performance.

Because it’s so comprehensive, multiple linear regression is generally more accurate than simpler models. It provides deeper insight into how different factors work together to impact sales, giving you a more reliable forecast. But it’s also more difficult to implement. You need a larger dataset and careful analysis to truly understand the relationships between variables.

Qualitative Sales Forecasting Methods

5. Market Research

During market research forecasting, you collect insights directly from a target market using techniques like surveys, focus groups, and interviews. Instead of looking backward at sales data, you gauge customer interest and buying behavior to predict future sales.

This method is especially helpful when you’re launching a new product or entering an unfamiliar market. In these contexts, you don’t have historical data to look back on, so you rely on what potential customers say they’re likely to do.

6. Delphi Method

The Delphi method gathers expert opinions to forecast future outcomes. Here’s how it typically works: A facilitator sends questionnaires to a panel of experts who have deep knowledge or specialized experience in your industry. After experts provide their answers, the facilitator summarizes their responses and returns them to the panel for review. This process repeats over several rounds, with the goal of reaching a well-informed forecast by consensus.

This method is especially useful in situations with high sales uncertainty. Say you’re pioneering a new industry where historical sales data doesn’t exist yet. The Delphi method can help you anticipate demand based on expert insight rather than guesswork.

How to Choose the Right Forecasting Method: 3 Factors to Note

With so many options available, it’s hard to know which sales forecasting tools are best for your company. Here are three factors to consider as you make your choice:

1. Data Availability

The amount and quality of data you have will shape your forecasting approach. If your business has several years of consistent sales data, you can use quantitative methods to generate reliable forecasts. But if you’re launching something new or entering an unfamiliar market, qualitative methods may be more appropriate.

2. Forecasting Objective

Different methods suit different goals. Your objective shapes the level of detail you need and how much time and effort to invest in building and interpreting the forecast.

If you’re looking for short-term operational planning, you need quick, actionable insights — simpler models, like the straight-line or moving average method, might be fastest. For long-term strategic forecasting, sophisticated approaches like multiple linear regression or the Delphi method offer broader, more layered insights.

3. Business Environment Complexity

The more variables that affect your sales, the more nuance your forecast requires. A business with seasonal trends, shifting customer preferences, and economic dependencies may benefit from more advanced forecasting models that consider all of these factors. In contrast, companies in stable industries with predictable demand can rely on simpler methods.

From Forecast to Action: How Rox Turns Predictions Into Results

The ultimate goal of any forecast is to turn insights into action. For sales teams, this means using accurate predictions to drive better outcomes. That’s where Rox comes in.

Rox’s AI-powered execution engine bridges the gap between forecasting and sales performance. By automating follow-up tasks, Rox enables sales teams to act on projections with minimal manual effort.

Whether your forecast is built into a spreadsheet, BI tool, or third-party platform, Rox makes it easy to operationalize. Using intelligent AI agents and execution logic, Rox automatically triggers the next best actions so your team can follow up on forecasted opportunities and achieve better sales results. Watch our demo to learn more.