Wouldn’t life be so much easier for sales leaders if they could nail their sales forecasts every single time?
But as we know, sales forecasting is rarely that straightforward. There’s always something that can throw it off—unexpected market shifts or unreliable data. And when the forecast is wrong, it can impact everything from hitting targets to managing budgets.
The good news? There are several sales forecasting methods, some more effective than others. The key is finding the right one for your organization.
This article will explore five common sales forecasting methods, highlighting their strengths and weaknesses. But before we do that, let’s cover the basics.
What Is Sales Forecasting?
Sales forecasting is the process of predicting how much your company will sell in the future. It helps you plan ahead by estimating the revenue you can expect to bring in over a certain period, like the next month or quarter.
These predictions are traditionally based on:
- Historical sales data
- Current trends
- The state of your sales pipeline
- Micro and macroeconomic factors
- Sales team performance.
The Importance of Sales Forecasting
Sales forecasting is crucial for any business. And that’s because a solid forecast helps you:
- Make strategic decisions—A good sales forecast gives you a clear picture of where your revenue is headed, making it easier to know when to invest or scale back.
- Set actionable, realistic targets—Instead of setting arbitrary goals, forecasts help you establish targets grounded in data. This keeps your team motivated and prevents burnout. If your team is trending toward $500K this quarter, you can set stretch goals that drive performance without overwhelming them.
- Improve financial planning—Forecasts tell you when to double down on growth or when to rein in spending to protect profitability. For instance, if a forecast predicts a slow sales period, you can tighten your budget or focus on higher-margin products to stay on track.
- Reduces risk and spots opportunities— A good forecast can help you identify risks or uncover opportunities. For example, if the forecast shows sales will drop, you can adjust your strategy early. On the flip side, it might show a chance to enter a new market and increase sales!
Reasons Sales Forecasting Can Be Challenging
Sales forecasting sounds simple: gather your data, crunch the numbers, and predict your revenue.
But as any sales leader knows, it’s rarely that straightforward. Fewer than 50% of sales leaders and sellers trust their forecasts' accuracy.
Why?
Because the variables that affect your forecast are constantly shifting—and not always within your control.
For example, take data inaccuracy. If the information in your CRM isn’t up to date, or if your team is inconsistent with data entry, your forecast will be off before you even start. Clean, reliable data is the backbone of any good forecast, but getting that level of accuracy is often easier said than done.
Then there’s the issue of market volatility. Economic shifts, changes in customer behavior, or even industry disruptions can all throw your forecast into chaos. A forecast built on last year’s trends might not hold up in a suddenly unpredictable market. Remember the sudden impact of Covid-19?
Finally, buyer behavior can be unpredictable. Even the most promising deals can fall through, and customers don’t always follow the expected path. Forecasting human behavior is tough, and uncertainty always exists, even with the best methods.
The key to overcoming these challenges? Start recognizing that no forecast is perfect—but you can get pretty close with the right tools, clean data, and adaptable strategies.
5 Commonly Used Sales Forecasting Methods
1. Historical Sales Forecasting
Historical sales forecasting is one of the simplest methods. It assumes that your past sales performance can help predict future outcomes. If your sales numbers have been consistent over time, this method can give you a reliable baseline for future estimates.
This method works well in stable markets where your business sees consistent growth. However, it may not be accurate during times of market volatility or if your sales process or products are evolving. It's a solid starting point but should be combined with other methods for a fuller picture.
When it works and when it doesn’t:
✅ Good as a benchmark and if you operate in a stable, highly predictable market.
❌ Relies on past conditions and assumes they’ll remain stable in the future.
2. Pipeline Sales Forecasting
Pipeline sales forecasting looks at the deals currently in your sales pipeline and estimates future sales based on their likelihood to close. This method is more dynamic because it focuses on what’s actively in progress, giving you a clearer picture of short-term revenue.
The idea is to assign a probability to each deal based on its stage in the pipeline. For example, a deal in the negotiation stage might have a 70% chance of closing, while an early-stage deal might only have a 30% chance.
The formula is:
Forecasted Sales = (Deal Value) × (Probability of Closing)
For instance, if you have a deal worth $100,000 and it’s 70% likely to close, your forecasted sales for that deal would be: $100,000 × 0.70 = $70,000
When it works and when it doesn’t:
✅ Effective when you have a well-structured sales process and reliable data on deal stages.
❌ Less accurate if deal probabilities aren’t consistently tracked or your pipeline is volatile with sudden deal shifts.
3. Test-Market Forecasting
Test-market forecasting allows you to launch a new product or service to a small, controlled group before a full-scale rollout. The idea is to gather data—how customers react, what the sales velocity looks like, and any potential obstacles—to forecast future sales more accurately.
For example, if you’re launching a new software, you might test it with 100 customers in a specific region. Based on their buying patterns and feedback, you can estimate how it will sell when you release it to a broader audience.
When it works and when it doesn’t:
✅ Works great when launching new products, letting you use real data to predict larger market performance.
❌ Falls short if your test group doesn’t reflect your overall target market, leading to misleading forecasts.
4. Multivariable Analysis Forecasting Method
Multivariable analysis forecasting is one of the most advanced methods. It uses multiple factors—such as historical data, deal size, sales rep performance, market trends, and sales cycle stage—to create a more comprehensive and accurate forecast.
When predicting sales using this method, you might weigh each deal in your pipeline based on the stage it’s in, combine that with market trends (such as seasonal shifts), and factor in how well each sales rep typically closes deals.
When it works and when it doesn’t:
✅ Works best when you’ve got strong data across multiple factors—like pipeline stages, rep performance, and market conditions—and are in a stable market.
❌ Falls short if your CRM is full of old deals or incomplete info. This method will only reinforce those flawed assumptions.
5. Regression Forecasting
Regression forecasting clearly shows how specific factors—like sales activities, deal size, and market trends—directly impact sales outcomes. By analyzing historical data, you can spot trends that show how adjustments in one area, like boosting outreach or changing pricing, affect overall revenue.
For example, if a 15% increase in outreach has consistently led to a 5% revenue bump, regression forecasting allows you to project future sales based on current activities.
Though it sounds similar to multivariable forecasting, there’s a fundamental difference. Multivariable forecasting combines multiple factors to offer a broader forecast rather than isolating each factor's individual impact.
In short, regression focuses on quantifying the influence of each variable, while multivariable forecasting pulls everything together for a comprehensive sales projection.
When it works and when it doesn’t:
✅ Regression forecasting excels at showing how specific moves—like ramping up outreach or tweaking pricing—directly impact your bottom line.
❌ It can fall apart if your data isn’t clean. Even minor gaps can completely skew the forecast and lead you off course.
The Importance of Accurate CRM Data in Sales Forecasting
No matter which forecasting method you choose, everything hinges on one thing: accurate, up-to-date CRM data.
Let’s face it—most teams struggle with data accuracy: outdated deal stages, missing details, or reps not updating close dates. These minor issues can throw your entire forecast off track. Even the most sophisticated forecasting tools can't fix insufficient or inaccurate data.
You can push for better data entry habits, but gaps will still happen. That’s why we built Momentum to help automate and maintain CRM data hygiene so you can focus on making accurate forecasts without worrying about what’s missing.
Momentum streamlines CRM updates by automatically pulling key insights from sales calls and logging them directly into your system. Your reps won’t need to rewatch calls or sift through transcripts. With AI-driven summaries, the most essential details are automatically pushed to Slack and Salesforce, keeping your data clean and ready to use.
On top of that, Momentum’s MEDDIC Autopilot syncs key deal info in real time, keeping Salesforce and Slack Deal Rooms in sync. Nothing slips through the cracks, ensuring your forecasts stay reliable, your data stays current, and your team can focus on closing deals—not updating records.
FAQs
1. How often should I update my sales forecast?
It’s a good idea to update your sales forecast regularly—at least every month, if not more frequently. As new data comes in and deals progress, adjusting your forecast helps keep it accurate and aligned with your current pipeline and market conditions.
2. Can small businesses benefit from sales forecasting?
Absolutely. Even small businesses benefit from forecasting. It helps plan resources, set goals, and avoid surprises. While small businesses may not have as much data, simpler forecasting methods can still provide valuable insights into future revenue and growth.
Start Making More Accurate Sales Predictions with Momentum
There’s a wealth of data in your sales calls. You’re just one step away from automating its collection and using it to inform your sales predictions.
Chat with our team today, and we’ll show you how Momentum can help you predict revenue with greater accuracy.