A good sales forecast is more than just a prediction of what your sales will be in the next few months. It should also include information about how you can improve your sales forecasting process so that it’s more accurate and useful over time.
In this article, we’ll walk you through some widely-used sales forecast examples you can use for your business.
What Do You Need to Create a Sales Forecast?
Below are a few things you’ll need to create an effective sales forecast.
- Data: The first step in creating a sales forecast is to collect data. You can gather information from your teams, including sales, marketing, customer service, and other departments. You might also want to look at industry statistics to understand market trends and changes in customer behaviors.
- A sales forecast platform: A sales forecast platform includes tools for collecting data, analyzing it, and putting together an accurate forecast. Powered by artificial intelligence, it gives you access to data from your past and present operations as well as real-time insights about your business. Hence, you’ll quickly understand what your sales will be in the future.
- A sales forecasting process: When you’re trying to predict your future sales, it’s essential to have a well-designed sales process in place. A good sales process will help you understand how your reps have been doing to hit their sales targets, what stages they work most effectively, and where they need more support from them. By tracking your reps’ activities, you can provide them with the support they need to boost their productivity and sales performance.
Sales Forecasting Examples
Intuitive sales forecasting
When companies don’t have historical sales data because they are less than a year old or they are small businesses with not enough customer data, they have to rely on other financial planning methods to predict sales.
Typically, a company relies on sales projections from reps based on the rep’s current sales. This method of determining sales forecasts is often referred to as intuitive forecasting.
The intuitive sales forecasting method relies on the sales rep’s perspective and intuition about their pipeline. The rep reports the likelihood and timing of when their deal will close, as well the total worth of the sale. Some teams like this sales forecasting method since the rep knows the client best. So, their intuition is usually based on specific client communication and insight.
Reps typically rely on the following factors and data to create the intuitive forecasting:
- Seasonality of sales that refers to fluctuations in your sales revenue that are caused by external factors and occur on a predictable schedule around the same time(s) every year
- Market trends analysis that refers to the comparison of industry data over a set time period, designed to recognise any consistent trends or results that could be used to map your forecast – aligning it with the general direction of your industry.
- Monthly sales reports that are used to monitor, evaluate, analyze, and determine sales trends on a monthly basis.
As you can probably imagine, this method is incredibly hard to quantify since it relies heavily on the sales rep’s subjectivity. It’s also difficult to replicate since each individual thinks differently. However, this may be a helpful method for new businesses or ones that lack a large amount of historical data.
Here are five other analytical methods you can use to do sales forecasting in your organization. These methods are typically used in various types of businesses from SMB to Enterprise.
1. Historical Forecasting Example
Historical forecasting is a method of creating projections based on past data.
For example, a company looked at their historical data for the last three years and found that sales have increased by 20% each year. Based on this information, they projected that sales would increase by 20% this year.
2. Multivariable Forecasting Example
Another way to forecast sales is to use a multivariable model. It predicts future sales based on multiple factors such as current sales, previous sales, and other variables.
A multivariable sales forecasting model can take into account different factors like deal sizes, close rates, number of opportunities, and leads to produce a more accurate forecast. It’s becoming increasingly popular as businesses strive to increase their efficiency.
3. Length of Sales Cycle Forecast Example
The length of the sales cycle is the time between when a customer first expresses interest in your product and when they make a purchase. It’s important to have accurate forecasts because if you’re not aware of how long a customer will take to purchase your product, you’ll end up spending too much money on marketing and promotion.
Sales cycle length is typically measured in weeks, but it can depend on the type of customer you’re dealing with. For example, if you’re selling to businesses (as opposed to consumers), they may take longer to make a decision since they need approval from higher-ups first.
4. Opportunity Stage Forecasting Example
This method is a simple way to predict the likelihood of an opportunity closing. You can use it by looking at the following:
- How much time has passed since the opportunity was created?
- How many times have you interacted with the customer?
- How much money have you spent on the opportunity?
All these factors will help you determine whether or not your prospect will convert into a client.
5. Pipeline Forecast Example
Pipeline sales forecasting is a method for predicting the number of opportunities you can expect to close in your pipeline. It looks at each opportunity in your pipeline and analyses it based on several factors, which could include age, deal type, and deal stage.
The aim is to understand what will happen to your opportunities as they progress through their lifecycle. Hence, you can determine how many total opportunities are likely to convert into closed deals at any given time.
Sales Forecasting FAQs
What is an Example of Sales Forecasting?
Different companies can use different methods to forecast their future sales. Common sales forecasting examples include historical forecasting, opportunity stage forecasting, length of sales cycle forecasting, multivariable forecasting, and pipeline forecasting.
What are the Most Common Sales Forecasting Mistakes?
Sales forecasting can be a tricky business. But if you don’t know what you’re doing, it can be easy to make a mistake.
These are some of the most common sales forecasting mistakes:
- Not having an accurate picture of your current customer base
- Not using the right forecasting tool or methods
- Not updating your forecasts with new information as it becomes available
- Not learning from past errors and improving your forecasts accordingly
- Failing to take into account external factors that could affect your business
Which Forecasting Method is The Best?
There’s no one-size-fits-all sales forecasting technique.
While many methods can help you forecast your sales, they all have pros and cons. Some methods are more complex than others, some require more data than others, and some are better suited to certain industries than others.
To determine which method is best for your business, consider how much time you’re willing to devote to getting your forecasts right (and keeping them updated), how much data is available, and what technology you already have in place.
Now that you’ve understood sales forecast examples and how to use them. If you want to learn more about sales forecasting, check out these blogs: