8 Sales Forecasting Methods For Accurate Revenue Predictions

One of the most important steps to forecasting sales accurately is to teach sales force members how to forecast accurately. In order to do that, an accurate forecast must be built. In order for a forecast to be accurate, it must build on a realistic foundation, and that foundation is sales.

A business can’t make a forecast and then go out to the market and buy a product. There are certain steps that need to be taken to arrive at a successful forecast. Forecasts are not just a series of numbers that are thrown together and then used as a basis to make a purchase.

Don’t you wish you could figure out how to predict the revenue for your company? If you’re not an expert yet, you probably know that it’s rather challenging. Well, you don’t have to worry anymore, because we have outlined 8 methods that can help you predict the revenue of your company.

It’s nearly as essential to obtain an accurate sales estimate as it is to meet the revenue goal. But, with so many various sales forecasting techniques to choose from, how do you know which one will provide you with the most accurate results?

According to CSO Insights, 60 percent of transactions predicted to close never do. Unsurprisingly, 25% of sales managers are dissatisfied with their prediction accuracy, according to the statistics. Choosing the proper forecasting method may make a big impact in your ability to estimate revenue effectively in the future.

In this article, I’ll go through three sales forecasting techniques that HubSpot has found to be successful. In fact, we’ve found that using a mix of all three has given us the most accurate results.

I’ll provide a high-level summary of each technique we employ, but I strongly advise you to test and modify them to suit your unique business model before implementing them with your staff.

What Are the Three Different Types of Sales Forecasting Methodologies?

Forecasting is based on the need for data and the use of that data to predict future sales. A sales estimate is only as good as the facts upon which it is built. In sales forecasting, forecasting experts utilize three different kinds of sales forecasting methods. The kind of input data utilized in predicting demand determines the forecasting method. The following are the three sales forecasting techniques:

  • Qualitative research methods
  • Analysis and projection of time series
  • Models of causation

While qualitative data is used in the qualitative method, time series analysis focuses on patterns and changes in patterns. The causal model is based on highly detailed and precise knowledge about system element interactions.

Because of the differences in the methods, the same methodology cannot be used to predict sales.

For example, time series analysis based on past data may be ineffective in predicting the future of a new product with no history.

So, what are the three kinds of sales forecasting methods’ general functions?

#1. Qualitative Methodologies

When there is a scarcity of data, qualitative sales forecasting methods are employed. When introducing a new product to the market, for example, qualitative methods may be used. There isn’t a lot of information about the product to utilize in making predictions about the future.

To convert qualitative data into quantitative estimates, the methods rely on human judgment and grading systems. The method’s goal is to bring all of the judgements and information about the variables being evaluated together logically and methodically.

When penetration rates and market acceptability of a product are unclear, qualitative methods may be used. You may also utilize them in emerging technological sectors where developing a product requires many innovations.

The following are five qualitative techniques:

Consensus of the panel

The simplest method is panel consensus, which is mostly utilized by business companies to predict the future of their products. It is based on the idea that a group of specialists in different areas may produce a better prediction than a single individual. There is no secret in the method, and the specialists are free to communicate with one another.

Method of Delphi

The Delphi method is a revenue forecasting technique that use surveys and questionnaires to estimate future sales. The Delphi approach aims to predict the likelihood of events occurring and the timeframe in which they will occur. The Delphi approach, like the panel consensus procedure, requires experts and a Delphi coordinator.

Technique for combining Salesforce data

The business wants its salespeople to generate predictions using the sales force composite method. The sales representatives are assumed to have direct interaction with consumers and other stakeholders in the distribution chain. As a result, they will have a greater understanding of a product’s demand.

Expectations of the buyer

You survey purchasing intentions and market intents in this sales forecasting method. If you wish to conduct a survey of purchasing intentions, you choose a sample of prospective customers and ask them about their future plans to acquire the goods. The overall demand prediction is then calculated by extrapolating the data.

research into the market

Market research is a method of predicting demand that is based on regular and formal procedures. It entails putting real-world market assumptions to the test.

#2. Analyze Time Series

When you have years of data on a product or product line, you may utilize the Time Series analysis sales forecast method. It may also be used when there are obvious patterns and connections about a product that are steady.

The forecaster calculates the present performance rate and change in rate using historical data on the product’s performance. The foundation of forecasting is the acceleration or slowdown of present rates.

A time-series technique is a collection of raw data points that are sorted chronologically. A time-series analysis may help you understand:

  • The data’s trends
  • Performance patterns that recur every two or three years are called cyclical performance patterns.
  • Any systematic change or consistency in data over seasons
  • Data growth rates for different trends

Causal Models (#3)

When you have adequate historical data and analysis on a product, you may create causal sales forecasting models. The study should include the variables you want to predict as well as other economic and socioeconomic influences.

The causal model should be used if you require advanced sales forecasting models. It describes the relevant causal connection and may incorporate information from market surveys and other factors. A time series analysis may also be included into the method.

It takes into account the flow system’s characteristics and makes predictions about connected events like promotions and strikes.

What Are the Different Sales Forecasting Techniques?

#1. The Sales Forecasting Method Based on “Lead Value”

The idea behind this forecasting technique is to look at past sales data from each of your lead sources. Then, depending on the value of each source, you may construct a prediction using those data points.

A buyer’s trip’s commencement may reveal a lot about how that journey will finish. It’s like something out of a terrible romance comedy. You can generally anticipate how a movie will finish based on a few early, telltale indications if you’ve watched a few comparable films.

You may obtain a better idea of the likelihood of each of your lead sources or kinds converting into revenue by assigning a value to them.

The following metrics are required for this model:

  • For the preceding time period, the number of leads each month was
  • Conversion rate of leads to customers by lead source
  • Source-specific average sales price

The Methodology:

The average cost per lead

Simply look at the data set for your complete customer database and bucket them by lead source to obtain your average sales price by source.

For example, online leads may close at $1,000 per client on average, whereas leads who request a demo may close at $1,500 per customer.

If your CRM lacks this reporting capability, you may export the data to an excel file and calculate the average sales price from there.

Lead Value on Average

You multiply the average sales price by the average closure rate for that source to get the lead value per source.

Average Lead Value = Average Sales Price * Lead to Customer Conversion Rate

For example, if I know that my paid advertising leads spend an average of $2,000 with us and convert at a 10% rate, each of those leads has a lead value of $200.

$2,000 x 10% = $200 per lead

Number of Leads in Total

Divide your entire revenue target by the average lead value to determine the total number of leads required in a particular timeframe.

Desired Revenue / Average Lead Value = Number of Leads Required

Assume, for the sake of argument, that our sales staff has to generate $100,000 in revenue next month. Because our typical lead is worth $200, we’ll need to create 500 leads to meet our revenue target.

100,000 divided by 200 equals 500.

Note that lead values vary by channel, so check with your marketing team to see what future efforts they have planned and where they anticipate lead flow to come from.

After you’ve done the math in a spreadsheet, you’ll end up with something like this:

Sales forecasting models

Considerations:

While this is a good beginning point, there are additional variables to consider that may affect your final outcomes.

Each lead source’s typical sales cycle may differ. If you wish to utilize this kind of prediction, you’ll need to do some more research on time to buy (or sales velocity) and incorporate it into your forecast.

Other company efforts, such as sales process improvements, pricing adjustments or promotions, may affect your conversion rates. To keep current with other company developments, look at a moving average of lead value for each source over the last 90 days.

Marketing may make changes to its strategies as a result of new information or changing trends. To guarantee that your anticipated lead volume and conversion rates are correct, it’s critical to keep in touch with them.

It’s possible that you won’t be able to pinpoint a single lead source. If that’s the case, put them in the category of “other” and include them in your prediction.

#2. The Sales Forecasting Method of “Opportunity Creation”

Concept: Based on demographic and behavioral data, this model may help you forecast which opportunities are most likely to close.

Let’s return to our Romantic Comedy example. It’s frequently simple to guess what each character will do based on their look, behavior, and interactions with others.

Predicting the probability of a deal closing is comparable. We can obtain a better idea of the likelihood of closing and the anticipated value of the transaction by looking at demographic and behavioral data.

The Methodology:

The features of companies that have completed transactions in the past are examined in this model. Then, in our pool of prospective consumers, we search for the same qualities.

To demonstrate, I’ll walk you through how we use this approach at HubSpot.

We’ve discovered that looking at the size of the company is the most straightforward method to assess the probability of a deal completing. The number of workers and yearly revenue of a potential client are both good indicators of our success for us.

However, there are a slew of additional variables that may influence an opportunity’s destiny. Our contact’s position in the decision-making process, behavioral patterns, and prior contacts with HubSpot, for example, all have an impact.

It’s also crucial to examine past data for your most desirable clients, including not just those who close, but also those who stay and recommend others. These are the businesses you should concentrate on.

Lead scoring is the name for the second layer of analysis. Typically, the sales and marketing teams collaborate to design and implement a lead scoring system.

At HubSpot, we rate our leads on a scale of one to one hundred, with one being the best match. For convenience of usage, we categorize scored leads into buckets labeled “A, B, C, and D.”

You can determine the projected worth of each opportunity in your pipeline after you’ve set up your scoring system.

Average Sale Price * Average Close Rate = Expected Value of Opportunity

With an average sales price of $4,000, here’s a basic estimate of anticipated value per opportunity based on lead score and business size. You’ll need to know the close rates for each of your lead buckets for this to function.

Sales forecasting models 2

*Primary attention is shown by a green arrow.

**Secondary emphasis is denoted by the color orange.

This approach is great because it displays the potential of each individual opportunity, which helps my representatives prioritize more critical possibilities.

Considerations:

To make this approach work, you’ll need well-defined criteria for creating opportunities. Even with everything in place, you’re counting on your sales representatives to stick to process and be consistent in their administrative tasks. As a result, you’ll have to keep an eye on it.

You’ll also need to create an opportunity scoring system or utilize a software to automate the process, which is both expensive and time-consuming.

Finally, you must have confidence in the data that your opportunity scoring system utilizes to give a score. Before rolling out the new system to the whole team, I suggest testing it with one salesperson for a specified period of time.

#3. The “Opportunity Stage” Method of Sales Forecasting

This is arguably the most popular of all the sales forecasting techniques in the world. Based on where the prospect is in your sales process, this model estimates the likelihood of an opportunity closing.

To begin, you must first determine your typical sales cycle. Then, if you’ve sketched out the phases of your sales process from high-level awareness to completed transaction, you may estimate their chances of closing during the forecasting period.

Here’s an example of the transaction phases you might utilize in your sales process, along with the related probability:

  • An appointment has been set up (20 percent )
  • Qualified to Purchase (40 percent )
  • The presentation has been completed (60 percent )
  • Contract has been sent (90 percent )
  • Won Closed (100 percent Won)
  • Lost and Found (0 percent Lost)

The Methodology:

You construct your prediction for future sales using this approach by multiplying the amount of each opportunity by the likelihood of that opportunity closing.

Expected Revenue = Deal Amount * Closing Probability

To make this forecasting method work, you’ll need a well-defined sales process that includes a comprehensive description of the actions that must occur in order to get the transaction closer to being completed. After you’ve defined your transaction phases, you’ll need to give each one a chance of closing.

You may use the template below to plan out your sales process. Here’s where you can get an editable version.

sales forecasting technique for opportunity stages

This is how the model should appear:

Sales forecasting model opportunity stage

A CRM system that enables you to automatically assign the win probability for each step of the sales cycle is required for an accurate prediction.

It’s also a good idea to check in with your team every six months to see whether their performance is greater, lower, or about the same as you expected when you established the likelihood. As your staff gets more productive and their conversion rate increases, you should modify the rates.

Considerations:

Old prospects that have been in your pipeline for months (or even years) may have an impact on your prediction. Make sure your data is up to date and that your opportunities are updated on a regular basis.

Because the probability component is so important in this approach, look at past data and compute it based on prior opportunities’ success.

Before a transaction can proceed to the next level, you must have a very well-defined set of activities that must occur. You lose accuracy if you don’t have clear guardrails in place for this phase of the process.

#4. Predicting the length of a sale cycle

The duration of the sales cycle forecasting technique utilizes information about how long it takes a prospect to become a paying client.

For example, if a sales cycle lasts six months and your sales person has been interacting with a prospect for three months, the transaction has a 50% chance of closing. Forecasting using this technique is objective since it is not influenced by your sales representatives’ emotions.

It also has the benefit of being able to be used on a number of sales cycle sources, making it an ideal match for businesses that keep track of when clients enter their sales funnel.

Calculation:

To figure out how long a selling cycle will last, you must first decide on a beginning point. After that, use the following formula:

# of days from first contact + customer conversion = # of days from first contact + customer conversion = # of days from first contact + customer conversion = # of days from first contact + customer conversion = #

The average duration of the sales cycle for your company is calculated by multiplying the total number of sales by the number of transactions completed.

Consideration:

Someone who downloaded an ebook from your website and then requested a demo months later is an example of a lead. As a result, they generate a second lead, which initiates communication with your sales representatives.

#5: Predictive Intuition

Concept: Your salesman is the ideal person to inquire about whether or not the transaction will go through.

As a result, you may inquire with your sales representative about their confidence in completing a transaction and when they expect to do so. Your sales representatives are the ones that have the most contact with your prospects and are the ones who know how things are progressing. As a result, the intuitive forecasting technique depends on your faith in your prospects’ opinions.

The method’s most important flaw is that it is subjective. If the salespeople are optimistic, they may give unrealistic estimates, and there is no way to evaluate them.

Calculation:

There is no formal formula here, but a sales representative would use intuitive forecasting to describe the monetary amount they anticipate to bring in over a certain time. For instance, I want to bring X amount of money in X number of days.

Consideration:

The sales representative will evaluate the sale and provide an estimate of its potential worth. Before providing estimates, the sales representative should examine all variables.

#6. Forecasting based on test-market analysis

The concept behind the Test-Market Analysis forecasting technique is that it allows you to roll out your product or service to a specific set of people depending on their requirements. You may test the product by moving it to a different place.

The rollout’s findings may then be utilized to create a more precise prediction of the future market. The technique is excellent for large corporations that want to launch a new product but want to gauge consumer reaction beforehand.

Calculation:

To roll out the product, you split the market into two areas using this technique. The test market is where the product is introduced to the public without being advertised.

Then there’s the control market, which is where the product is promoted. The difference in sales between the control and test markets is investigated. The gap analysis aids in forecasting future product sales.

Consideration:

The Test-Market technique is a quantitative approach that requires a significant financial commitment. It’s perfect for introducing new goods or breaking into new markets.

#7. Forecasting based on the past

The historical forecasting technique works by analyzing past sales data over a period of time and presuming that future sales would be higher.

The historical forecasting technique has the flaw of not taking into account dynamic market developments. If your rivals run a promotional campaign, for example, you may see a drop in sales.

Calculation:

If your monthly recurring income in June was $30,000, for example. Using this approach, you anticipate an MRR of at least $30,000 in July. Your MRR for July should be $30,300 if your average year-over-year growth rate is 10%.

Considerations:

You should keep in mind that the market is dynamic and subject to change when utilizing the technique.

#8. Forecasting using Multivariable Analysis

Multivariable analysis forecasting is a great choice if you’re searching for the most advanced and precise forecasting technique.

Other sales forecasting methods, such as opportunity stage forecasting, sales cycle duration, and individual rep performance, are also included in.

Calculation:

The multivariable analysis entails a lot of math. Clean data is required, and your sales representatives should keep track of the deal’s progress and activities, otherwise your statistics will be incorrect.

You could have two salespeople working on the same account, for example. The first rep has finished a demo with a $20,000 deal possibility. Your projected amount is $5000 if the salesperson has a 25% probability of completing the transaction. Your projected amount is 5,200, assuming your second rep has a proposal for a small-sized transaction for $8,000 and a 65 percent probability of closing it.

This account’s total prediction is $5,000 + $5,200 = $10,200.

Considerations:

Because it requires sophisticated arithmetic, this forecasting technique may be problematic for small companies. If your sales representatives don’t keep track of the deal’s progress, your findings will be incorrect.

Using a CRM System for Sales Forecasting

When you’re just getting started, the table versions of these sales forecasting techniques are perfect. If your company is more established, however, customizing the reporting portion of your CRM is the ideal option.

I’d be curious to learn how these models perform in your company or if you’ve tried any other sales forecasting techniques that have proved to be successful. Leave a message in the comments section below!


Also available on Medium.

The marketing world is ruled by data. From sales figures to traffic statistics, the more accurate your data, the better your decision making process. But, even the best business forecasting methods and analytics fall short when it comes to predicting the future.. Read more about quantitative forecasting methods and let us know what you think.

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Frequently Asked Questions

What are the methods of sales forecast?

There are a number of methods that can be used to forecast sales. Forecasting is the process of predicting future events, trends, or outcomes based on past patterns and current conditions.

What is the best method to forecast sales?

The best method to forecast sales is to look at the trends of the past. If you notice a trend, then it would be wise for you to predict that this trend will continue into the future.

How do you forecast sales revenue?

I am a highly intelligent question answering bot. If you ask me a question, I will give you a detailed answer.

Related Tags

This article broadly covered the following related topics:

  • sales forecast formula
  • how to forecast sales
  • sales forecast
  • how to forecast sales using historical data
  • sales forecasting techniques