Sales Forecast

What is a sales forecast?

A sales forecast helps you predict how much you’ll sell in the upcoming weeks, months, quarters, or years by analyzing sales data  — past performance and real-time data — and employing sales forecasting methods.

Generally, sales forecasts are based on:

• Historical sales performance data and metrics
• Market research — trends and fluctuations
• Current sales pipeline status

The goal of a sales forecast is to help sales leaders understand the probability of closing deals to get new customers and prepare for the future.

Why is sales forecasting important?

According to an Aberdeen Group study, accurate sales forecasting can help you be 7.3% more efficient in hitting your quota. 

It also accelerates your year-on-year (YOY) revenue growth by 10%.

With accurate sales projection, you can:

• Adjust your sales strategy
• Prioritize your time by deciding where to focus your efforts for maximum impact
• Identify and take advantage of new opportunities
• Predict whether you have enough resources to meet upcoming demand
• Improve your sales process 
• Plan effectively for upcoming challenges
• Coordinate with other departments (marketing, product, customer success) on more efficient sales planning and resource allocation

Who is responsible for sales forecasts?

Sales managers are responsible for understanding the sales revenue, cash flow, chances of closing deals and the overall sales cycle to project sales performance and estimate KPIs for sales teams. 

The IT team supports the sales managers by providing them with:

• The right forecasting tools
• Data from CRMs (customer relationship management tools) and marketing platforms
• Technical assistance

What are the various types of sales forecasting? 

Before learning how to forecast sales, let’s explore some of the most popular sales forecasting methods:

1. Historical data analysis

According to HubSpot, historical data should be used as a benchmark rather than the foundation of your sales forecast. 

That's because, in this method, you analyze your historical sales data to spot patterns and estimate future sales, provided the conditions remain the same. 

Historical forecasting using past sales data is one of the simplest sales forecasting methods and doesn’t require any complex forecasting models or software. 

It is ideal for short-term forecasting when external changes don’t lead to radical economic changes. It's also useful to assess sales performance for a specific time frame by comparing it to sales data from the previous years. 

However, the method doesn’t consider the uncertainties stemming from seasonality, market fluctuations or changes in buyer demands.

2. Qualitative techniques (or intuitive forecasting)

Qualitative sales forecasting techniques use information such as expert opinions or insights from your sales teams. 

Since the sales reps are always involved in customer-facing conversations, they can provide valuable insights on future sales performance.

However, since this method relies on intuition rather than data, it won't be very objective and the resulting sales projections might not be accurate. That’s why it’s a technique that you should use in addition to a more data-driven, scientific forecasting method.

3. Opportunity stage forecasting

The opportunity stage forecasting method assigns probabilities to each sales pipeline stage. 

As the deal progresses further down the pipeline, it's more likely to close. After assigning probabilities of closing each deal, you multiply it with the deal's overall monetary value and add all such values to estimate your total sales forecast.

The method is straightforward and a great way to assess the potential of your current sales pipeline. However, it isn’t entirely accurate as the forecasting process doesn’t consider the age of each opportunity or its worth.

4. Sales cycle forecasting

The sales cycle forecasting method calculates your predicted sales by analyzing the age of an individual opportunity. 

To get started, you must find out your average deal cycle — add the total number of days it took you to close each of your recent deals, and then divide that by the number of closed deals. The next step is to map how far along the sales cycle your reps are and estimate their chances of closing the deal within a given timeframe. 

Like the opportunity stage sales forecasting method, sales cycle forecasting is also straightforward and objective. However, it doesn’t take into account the age of each deal and its worth. 

Moreover, your sales reps must regularly and meticulously track and update all sales pipeline data for this method to be accurate. 

5. Pipeline forecasting

The pipeline forecasting method is a sophisticated yet reliable technique to predict sales performance accurately. It analyzes each opportunity in your sales pipeline to calculate its conversion rate using pre-defined variables such as opportunity size or win rate.

So, you can consider every factor, such as the deal age and value, to get more accurate results. 

However, just like the previous two methods, this technique works only if your sales team keeps track of all the essential sales data, preferably in real time.

It also relies heavily on historical data and the maturity of the sales organization, so the pipeline forecasting method might not be ideal for early-stage startups.

6. Multivariable analysis

The multivariable analysis method considers qualitative and quantitative data to predict future sales. It considers factors such as:

• The average sales cycle length and total sales volume over any given period 
• The probability of closing deals, depending on the type of lead, opportunity stage or marketing efforts
• The metrics of individual sales reps such as win rate, monthly sales, conversion rates, close rates and quota attainment

This method is sophisticated and one of the most accurate sales forecasting methods. 

However, it requires good quality and either real-time data or data that’s continuously updated by sales reps. It also warrants an advanced analytics tool that can perform predictive analytics using large volumes of real-time data from various sources. 

How can you run an effective sales forecast?

While there’s no sales forecast formula or magic pill to come up with accurate real-time sales projections, here are five steps to make sure that your sales forecasts are effective:

1. Establish a solid sales process

The first step is to set up a sales process with clear definitions of leads, opportunities, pipeline stages and other such elements of the sales funnel. 

The next step is to ensure that every salesperson is familiar with these elements and knows how to qualify leads and close deals.

More importantly, they must understand the importance of tracking and updating that information using your sales tech stack — be it a CRM, a marketing automation platform, or a conversation analytics solution like Clari Copilot.  

2. Choose a forecasting method depending on the purpose and use case

Before studying various forecasting methods or tools, it’s important to understand the purpose of the forecast and its use. That dictates the next steps.

After establishing the purpose and the use case, choose a sales forecasting method depending on your situation. 

For example, if you wish to improve your performance in a certain region, you can look at your past sales data and use statistical models to estimate future sales.

However, if you’re trying to understand customer demand for a new product or new business, you don’t have any historical data and must rely on market research, competitor analysis and insights from expert sales leaders within your sales organization. 

A forecasting method that relies on qualitative data might be better for such scenarios.

3. Understand the internal and external factors influencing the sales cycle and forecasting process

Internal factors such as changes to the company policy, operating regions, marketing strategy, sales process or overall business goals can affect your sales forecasts. 

Similarly, external factors such as economic changes, geopolitics, new legislation, market or demand fluctuation also influence the forecasting accuracy. 

While you cannot anticipate such events, it’s a good practice to run regular forecasts and simulate the impact of a wide range of scenarios that can affect your sales performance and total sales.

4. Ensure that the sales data is accurate and updated in real time

According to a report on sales forecasting accuracy, salespeople spend about 2.5 hours each week on sales forecasting, and for most companies, the forecasts are less than 75% accurate. Two factors can help improve this scenario — data and technology.

Clean, accurate and credible data is at the heart of any forecasting method. That’s why it’s a good practice to monitor and update sales data often, regularly and with adequate context. 

Moreover, you should consider consolidating data from other teams such as marketing, product, finance and customer success to build a more comprehensive data profile on each opportunity.

Likewise, pick a tool that automates real-time updates to the sales pipeline, monitors the performance of your sales reps intelligently with intuitive dashboards and integrates seamlessly with the rest of your tech stack.

5. Know when not to make a forecast

According to Paul Saffo, a Silicon Valley technology forecaster, the key to effective forecasting is knowing when to pause and wait for things to settle down, rather than jumping to conclusions. 

Black swan events such as pandemics or geopolitical tensions bring too much uncertainty along with them. During such scenarios, it’s best to take a step back, observe how things settle down and begin forecasting once the new world order emerges.

What’s next?

As mentioned earlier, your sales forecast is only as good as your sales process, reps and data. So, before choosing a sales forecasting method or tool, you must:

• Inspect your sales process and fix any gaps
• Train and mentor your sales team to be data-driven
• Collect and update real-time data on opportunity stages, sales pipeline, marketing efforts and crucial sales performance metrics

That's where a tool like Clari can help you make an effective sales forecast by surfacing all the signals that really matter.

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