Sales forecasting is the intentional manipulation of historical data, sales activity info, expertise, and predictive analysis tech to calculate an expected sales volume and revenue across a given period.
Every sales team worth its salt needs a proven method for forecasting sales. An effective sales forecasting method will help you answer crucial questions that’ll guide future approaches to scaling your business. You’ll finally have answers to “What should the revenue target be for the next year?” and “How many leads do we need to hit our sales target?”
These insights will provide much-needed direction and help you make decisions for business growth. That’s why sales forecasting is important to directors of sales, key decision-makers within a sales team, and people in sales management.
Great sales forecasting arrives at numbers using real-life data as a starting point. Consequently, the final numbers are more robust and remove the need for guesstimates. Here, we’ll provide a comprehensive guide to different forecasting methods that help you arrive at more accurate sales numbers.
Here’s what you need to know.
Factors Influencing Sales Forecasting
Accuracy during sales forecasting is not only a function of your method of choice. It also depends on the following:
Depending on your industry, policy changes can hurt or help your business’s ability to make sales. As such, any sales forecasting guide that doesn’t recommend planning for policy changes is insufficient. Highly successful salespeople consider potential sudden policy changes during sales forecasting.
Adding new features — or removing buggy or redundant ones — can affect your sales forecast.
Product changes can be a catalyst for more sales. A dedicated sales team can always use the product change to generate more conversions and close more negotiations, so be sure to consider them.
It is rare for anyone to find a business without rival companies in the same industry. For most, these other companies can offer the same product or service as you. But one thing is sure: your sales forecast can be influenced by how you and your competition moves within your niche.
For example, your competitor discovering the benefits of an on-premise system can boost their sales numbers. New tech innovations from the competition, promotional campaigns, and new designs can reduce your outfit’s market share. A reduced market share equals fewer sales and less revenue.
Customers are less likely to spend money during a market depression. Conversely, a strong economy spells increased sales for most businesses.
Comprehensive Guide to Sales Forecasting Methods
Here, we’ll provide a rundown of the best sales forecasting methods that guarantee accurate results:
This sales forecasting method involves the detailed analysis of each lead. You’ll isolate the lead’s source and use that info to assign a value to it. Typically, this value is a function of how well similar leads have performed.
The lead’s value will help you understand whether or not it’ll turn to a revenue-generating customer. The following historical data is required to make forecasting possible:
- Average sales price for each source
- Leads per month for past time-intervals
- The conversion rate for each source
While the lead value attached to each source creates accurate results, there’s an important con: the conditions lead values are assigned are subject to variation. Remember to review and update regularly.
Perhaps the marketing team needs to change its lead generation systems for conversion rate optimization. This change means your business is now getting leads from different sources. New lead sources mean new conversion rates; hence, the change will need to reflect in your sales forecasting efforts.
Opportunity Stage Forecasting
This method forecasts sales using each prospect’s position in the sales funnel as a major determinant. It starts by breaking your optimized sales funnel into strategic pipelines like prospect, interest, demo, price negotiation, and closing.
You can use the pipeline each lead falls into as a factor for calculating the probability of a complete sale. Typically, the further the lead is within the pipeline, the higher the likelihood of closing the deal.
Opportunity stage forecasting requires a detailed understanding of your business’s past performance. This understanding will form the backdrop against which you analyze and estimate success rates for each stage within the pipeline.
Here’s a good illustration of what we mean: say you’re working on a $5,000 deal that has reached the free-trial stage. In this example, your business’ past performance indicates there’s a 60% chance of closing the deal once the customer signs up for a free trial.
The sales forecast in that case should indicate $3,000.
While calculations for opportunity stage forecasting are straightforward, the results can be slightly inaccurate. It doesn’t account for individual lead characteristics like how long it takes to close negotiations.
Source: Engage Selling
The best sales forecasting method is often a function of the company’s strategy. Test-market sales forecasting is the answer for companies looking to roll out a new product. Perhaps you need to understand how the market will respond to the product. Or maybe yours is a startup doing its first soft launch for increased awareness.
Test-market forecasting involves rolling out the product to a specific group. The choice of group is the result of informed market segregation. For example, you can release the service within a specific geographic area and analyze the resulting sales numbers. Then, you can study the results and use them to make a sales forecast for the eventual product release.
Test-market forecasting offers a first-hand market response experience. With this experience, you can easily identify and fix any issues before the final product launch. But remember, all markets are not the same. Test-market forecasting may not always deliver the same results with a different market segment.
Sales Cycle Forecasting
This forecasting method focuses on how long it takes to convert a lead into a revenue-generating customer. It reviews past sales cycles, settling on an average number and assigning a maximum lead value to that number.
For instance, say it takes an average of four months to convert a prospect and there’s a lead that has been in the sales funnel for two months now. The probability of turning that lead into a customer is sitting at 50% because you’re halfway through the conversion period.
Similarly, sales cycle forecasting allows you to assign different lead values to potential clients based on their source. For example, it can take four months to close customers who discover you via email marketing. Conversely, it may take four weeks to close a referral prospect. Sales cycle forecasting allows you to separate each lead into different time categories, giving you a more factual representation of the sales forecast.
Using the sales cycle timeline as a forecasting tool offers accurate results because the process is usually objective. It’s not dependent on your sales rep’s gut feeling or promises from the prospect.
Sales cycle forecasting works best when you keep an eye on how each lead enters the sales funnel. It requires seamless collaboration between the sales and support team. Even a small data error can throw off your results by wide margins.
Source: ZendeskImage Source
This sales forecasting method relies on your sales rep’s gut feeling. After all, who better to predict whether or not a sale will happen than the guy in charge?
Intuitive forecasting requires you to actually ask the sales rep if they think a sale will happen. It relies on the gut feeling of whoever is in communication with the prospect. They’re more likely to understand what the prospect is thinking and may well be able to paint a near-accurate forecast.
While the premise is bright, intuitive forecasting is entirely subjective. Sales reps tend to be overly optimistic about customer satisfaction and their chances of closing a prospect. Plus, there’s no viable method to gauge client-rep interactions and verify the authenticity of their projections.
So, when is intuitive forecasting the best way to get an accurate revenue target? This forecasting method works best for startups without historical sales data. Companies in this position have to start somewhere — intuitive forecasting is that place.
Historical Sales Forecasting
Historical sales forecasting uses previous sales data to determine future sales numbers. You’ll need the previous sales numbers for the timeframe in question. Historical forecasting always assumes future sales will be equal to or greater than that number.
For example, say the Monthly Recurring Revenue in August was $60,000. Historical forecasting for September assumes the MRR for the next month will start from $60,000. Then, you can factor in the year-on-year growth rates (say 10%), and the sales forecast for September will be $60,600.
Historical forecasting doesn’t account for economic or market changes. If your direct competitors run a successful promotional campaign the next month, it may impact your sales numbers. Instead, historical sales forecasting should be a quick go-to that forms a benchmark for more in-depth forecasts.
Multivariable Analysis Forecasting
This sales forecasting method combines metrics like sales cycle timelines, opportunity stage probability, and lead source performance to determine the probability of a sale. Multivariable analysis is the most complex sales forecasting method. It often incorporates machine learning in sales and offers highly accurate results.
As an example, say two reps are working on a single account. Rep A is working on an $8,000 sale and has finished the demo stage. If the opportunity stage forecast puts the success probability at 60%, the sales forecast is $4,800.
Rep B is working on a $3,000 deal but has the prospect in the latter stage of the funnel. The opportunity forecast will be 80%, with the numbers sitting at $2,400.
The example above shows how straightforward it is to use the opportunity stage forecasting method. Multivariable analysis is the direct opposite and is best for established companies with the resources for it. It’s highly impractical for small businesses to keep up with the data requirements for this method.
Pick the Right Sales Forecasting Method
Above, we highlighted different sales forecasting methods and the situations in which they offer the most accurate results. Pick the one that suits your business’ unique profile.
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