To run a business, you need not only transparency about the current sales deals and the likelihood of their closure but also a strong vision of the future pipeline.
This is where sales projection comes in, which is used to estimate the future performance of the company based on past indicators. In this article, we explore how to make sales projections, what the key tools are in the process, and how your business can benefit from understanding this future sales potential.
A sales projection is a forward-looking estimate that anticipates the sales revenue of a business over a specific timeframe. This forecast is crafted through a detailed analysis of past sales data, identifying trends and patterns to envisage future revenue outcomes.
Modern revenue teams are revolutionizing sales projections by deploying AI-powered revenue agents that automatically gather data from multiple sources, continuously update projections based on real-time pipeline changes, and generate more accurate forecasts than traditional manual methods.
In constructing a sales projection, several critical factors are taken into account, including the broader economic environment, the company's current market positioning, and the allocated budget for acquiring new customers.
Additionally, when launching new products or features, sales teams often prepare for multiple outcomes by creating best-case, worst-case, and most likely-case scenarios to capture a comprehensive range of future possibilities.
The role of sales projections extends beyond mere forecasting; they are integral to strategic business planning. By setting realistic sales targets, companies can monitor progress, adjust strategies timely, and make informed decisions on resource distribution.
These projections are also vital for accounting departments to set budgets, assess financial prospects, manage risks, and undertake holistic business planning. Without accurate sales projections, companies can fluctuate unpredictably between under- and over-achievement, creating a climate of uncertainty and making it difficult to achieve set targets effectively.
Calculating an accurate sales forecast is a multi-layered process that involves understanding your market, analyzing historical sales data, taking external factors into account, and applying certain calculation methods. Here you can find out how to approach the individual aspects:
Analyzing past sales data is the basis for predicting future sales. This involves identifying patterns, trends, and seasonal fluctuations in your sales history. By examining how your sales have changed over time, you can make reliable predictions for future sales. This analysis should take into account product life cycles, customer loyalty, and the influence of marketing measures on past sales.
External factors such as market trends, economic conditions, regulatory changes, and technological advances can have a significant impact on your sales projections. Keeping up to date with these factors and assessing their potential impact on your market and customer base will help you create more accurate forecasts. Both the macroeconomic environment and industry-specific trends need to be taken into account.
There are various methods for calculating future sales trends. Sales projection formulas range from simple linear models based on historical growth rates to more complex models that take several variables into account. Here's a breakdown of the most utilized formulas:
Choosing the right method depends on the availability and quality of your data, the complexity of your market, and your specific business requirements. When you combine these approaches with a clear understanding of your market, a thorough analysis of historical sales data, and consideration of external factors, you can create accurate and reliable sales projections.
Navigating through the myriad of tools available for sales projections can seem daunting, but if you know the general categories of these tools, you can make the process much easier. These tools range from sophisticated platforms that are deeply integrated with your sales data to simpler, more intuitive applications that allow you to quickly get started with forecasting.
Customer Relationship Management (CRM) and sales analytics platforms are essential for tracking and analyzing sales activity. Instead of the old sales projections templates, these platforms provide a central repository for all sales-related data, including customer interactions, sales transactions, and lead history. By leveraging the data stored in these systems, companies can gain insights into sales trends, customer behavior, and pipeline health to make informed projections about future sales performance.
Financial modeling software offers a more numbers-driven approach to sales projections, allowing companies to create detailed financial models and scenarios. These tools allow users to input various financial and operational data to simulate different future states based on assumptions about growth rates, market conditions, and business strategies. This approach is particularly useful for companies that want to align their sales projections with overall financial planning and analysis.
Artificial Intelligence (AI) and machine learning tools represent the cutting edge in sales projection technology. These tools analyze large amounts of data to identify patterns and predict future results with high sales forecasting accuracy. By incorporating factors such as market trends, competitor activity, and even social media sentiment, AI-powered tools can create dynamic and highly nuanced sales forecasts. This category of tools is particularly valuable for companies operating in fast-changing markets where traditional forecasting methods struggle to keep pace.
Terret's Virtual Revenue Fleet exemplifies this approach by deploying AI revenue agents that continuously monitor sales activities, customer engagement patterns, and market signals to automatically generate and update sales projections. These agents can process vast amounts of data in real-time, adjusting forecasts as new information becomes available and providing more dynamic and accurate projections than traditional methods.
Sales projections are forward-looking estimates that predict the sales revenue of a business over a specific timeframe. They are based on past sales data, current market conditions, and other factors such as economic trends and customer behavior.
Calculating sales projections starts by collecting and analyzing historical sales data. Segment the data by product, region, or sales channel and consider external factors such as regulatory changes, technological advances, and economic conditions to understand market trends. Depending on your business needs and the available data, you can use different forecasting methods like growth rate-based forecasts, acquisition-based forecasts, or simple annual sales forecasts for calculating sales projections.
Sales projections have an important role in strategic business planning. They help companies set realistic sales targets, monitor progress, adjust strategies, allocate resources efficiently, and make informed financial decisions.
The terms "sales projection" and "sales forecast" are used interchangeably. Both aim to predict future sales based on past data, market conditions, and other influencing factors.
Sales projection tools include CRM and sales analytics platforms, financial modeling software, and AI/machine learning tools. Each tool type offers unique capabilities to help businesses create accurate sales forecasts based on their specific needs.
Terret's Virtual Revenue Fleet offers AI-powered revenue agents that automatically generate forecasts, inspect deal health, and provide coaching insights. These agents continuously monitor sales performance and market conditions to provide businesses with real-time, accurate sales projections without manual intervention.
CRM and sales analytics platforms centralize sales-related data, enabling businesses to track and analyze sales activities, customer interactions, and sales trends. This data-driven approach provides insights necessary for accurate sales projections and strategic planning.
AI revenue agents continuously analyze datasets to identify patterns and automatically update projections based on real-time sales activities and market changes. Terret's revenue agents incorporate factors like customer engagement signals, deal progression patterns, and market trends to create highly accurate sales projections. They can also automatically account for complex revenue models, including usage-based projections—a trend that has grown significantly, with 125% more companies adopting usage-based revenue models over the last five years, according to Terret's 2025 Compensation Report.
Accurate sales projections help businesses set realistic targets, allocate resources efficiently, monitor progress, and make informed decisions. They are essential for strategic planning, budgeting, and risk management.