With today’s big data analytics, machine learning, and AI technologies, correctly estimating companies’ potential future revenues is no longer a mystical art that can only be guessed by luck. With the help of continuously developing technologies, accurate sales forecasting not only helps to precisely determine targets but also helps managers identify where and how sales reps are losing deals.
Modern revenue teams are achieving unprecedented forecast accuracy by deploying AI-powered revenue agents that automatically monitor deal progression, analyze risk factors, and continuously update predictions based on real-time sales activities. These virtual agents can identify the subtle patterns and warning signs that human forecasters often miss, leading to dramatically improved accuracy.
In this article, we are going to explore what sales forecast processes look like, how to do sales forecasting, why accuracy is vital, and how it can be improved through implementing sales forecasting best practices.
"Sales forecasting is not about predicting the future; it's about making informed decisions today." - Chris Voss, author of Never Split the Difference: Negotiating As If Your Life Depended On It
Sales forecasting is a strategic corporate planning tool that not only aims to predict future sales, but also other key performance indicators such as customer demand, product performance, and market trends. It's a multi-layered process critical for making informed decisions in various business areas such as inventory management, workforce planning, financial budgeting, and marketing strategies. The main goal? To anticipate future market conditions and align the company’s operational and strategic plans accordingly.
The implications of effective sales forecasting are far-reaching. It allows companies to optimize their inventories – avoiding both surpluses and shortages – and helps align production plans with market demand. Accurate forecasting supports marketing teams in creating targeted campaigns, helps sales teams set realistic targets, and informs financial planning to ensure sustainability and growth.
The importance of accurate sales forecasting cannot be overstated. Inaccurate forecasts can lead to significant business disruption. For example, tech giant Cisco Systems faced a staggering $2.2 billion inventory write-down in 2001 due to an overestimation of demand caused by an inaccurate sales forecast. This not only led to direct financial damage but also affected the company's credibility in the market.
Similarly, BlackBerry's failure to accurately estimate the declining demand for its smartphones in the early 2010s resulted in a significant loss of market share and left the company with excess inventory.
"The accuracy of your sales forecast is directly proportional to the quality of your data and the sophistication of your process." - Tim Berry, author of The Profit Zone: How Strategic Business Planning Leads to Success
To understand the driving factors of forecasting accuracy, let’s explore the process of building a sales forecast:
Data quality is a key pillar for accurate forecasts. The more high-quality data available, the higher the accuracy. High quality data can be gathered from:
When evaluating your enterprise's financial projections, the level of accuracy is a crucial element. The necessary degree of exactitude varies depending on the forecasting maturity and scale of the company.
For a newly established startup, with many unknown factors and no rich historical data available, hitting a forecast within a range of 20-30% is realistic.
When a company reaches a more mature state and has a deep pool of data available, getting the forecasts more accurate is crucial. Businesses in this stage usually aim to be within 5% of their predicted numbers.
abecAI revenue agents like those in Terret's platform can automatically monitor these risk factors in real-time. They continuously analyze communication patterns to detect sentiment changes, track stakeholder engagement to identify relationship risks, monitor meeting attendance and response rates to flag dis-engagement, and ensure sales process compliance to prevent process-related surprises.
Overcoming such challenges and risks is particularly important to ensure that the accuracy of sales forecasts can be maintained at the highest possible level.
To improve the accuracy of your sales forecasts, objective metrics must be tracked and best practices should be implemented. These approaches focus on establishing concrete, quantifiable measures to enhance the reliability of forecasts. A key practice is setting and monitoring weekly and quarterly pacing against weighted targets. This strategy involves defining specific attainment targets for each period, providing a clear measure of the sales reps' progress on their quarterly forecasts. By breaking down the quarter into smaller segments, companies can better understand and manage sales performance by recognizing who is ahead or behind and having early, actionable conversations about deals and forecasts.
Another best practice is to review the historical accuracy of commitments and forecasts. By tracking for each sales rep, the percentage of revenue generated in previous quarters from their commit and best-case deals, you can better assess the health of the current forecast. This historical perspective helps to understand the likely outcome based on past performance.
In addition, it is critical to assess the coverage gaps in the pipeline for the current and upcoming quarters. Early monitoring of pipeline coverage is a good indicator of performance in the final quarter. Using historical data to calculate the pipeline conversion rate in the quarter allows managers to estimate the necessary pipeline volume each agent needs to meet its forecast.
To improve forecast accuracy, it's essential to adapt the key performance indicators (KPIs) of the forecast to the respective context. Segmenting forecasts by geographic region takes into account different work cultures and sales expectations and uses historical profit rates for accuracy. Different forecasting methods are recommended depending on company size, e.g. a 30-day cycle for small companies that focuses on deal volume, a deal-by-deal approach with intuitive estimates for medium-sized companies, and in-depth, weekly reviews for enterprises.
Key KPIs for forecast accuracy include Pipeline Coverage, with a general guideline of keeping three to five times the forecast volume in the pipeline, adjusted for different regions. It's crucial to monitor the forecast categories and their changes and to understand the dynamics of deals that are likely to close or are at risk. It's also recommended to focus on the age of opportunities and know that deals that exceed the average length of the sales cycle are less likely to close.
Terret's Virtual Revenue Fleet revolutionizes forecast accuracy through AI agents that automatically execute forecasting tasks rather than just providing analysis. These revenue agents continuously monitor all sales activities, automatically detecting the risk factors that impact accuracy—sentiment shifts, relationship changes, engagement drops, and process deviations.
The agents automatically integrate data from CRM software, emails, calls, and market signals while actively tracking deal health indicators in real-time. They can predict when deals are likely to slip, identify which opportunities need immediate attention, and automatically update forecast probabilities based on actual buyer behavior patterns.
Unlike traditional AI tools that require human interpretation, Terret's revenue agents automatically execute corrective actions—alerting teams to at-risk deals, suggesting interventions, and continuously refining predictions as new data emerges, achieving estimation accuracy up to 95%.
Sales Forecasting accuracy refers to the degree of closeness between projected sales and actual sales.. Highly accurate forecasts are crucial for aligning resources and setting realistic business goals. They alsoenable companies to avoid costly mistakes like overproduction or underproduction, ensures efficient inventory management, and informs financial planning.
Using Revenue Operations & Intelligence (RO&I) platforms such as Terret enables your company to achieve highly accurate sales forecasts through AI agents that automatically monitor deal health, track risk factors, and execute forecasting tasks without manual intervention.
An accurate sales forecast is critical for developing an effective business strategy. It ensures that resources like inventory, production, and staffing are aligned with expected market demand, enabling more efficient operations. In addition, accurate forecasting informs financial planning, helping companies manage their budgets and investments more effectively.
To forecast sales using historical data, follow these steps: