Sales forecasting method uses approaches based on past data and key criteria to anticipate future revenue. Learn how to use tools to forecast sales.
Forecasting sales is an important business practice. Accurate sales predictions enable company executives to make more informed decisions regarding goal-setting, budgeting, recruiting, and other cash-flow-related issues.
Meanwhile, an erroneous sales projection leaves sales managers unsure if they will meet quota. As a consequence, they might not notice any issues in the sales funnel in time to remedy them.
Let's take a look at what sales forecasting is and some of the fundamentals you'll need to succeed.
A sales forecast is a forecast of future revenue from sales. Forecasts for sales are typically based on historical data, industry trends, and the current state of the sales pipeline. The sales forecast is used by businesses to forecast weekly, monthly, quarterly, and yearly sales totals.
Your sales forecast, like the weather forecast, should be viewed as a strategy to work from rather than a precise prediction.
Sales forecasting and sales goal-setting are not the same thing. A sales forecast forecasts what will happen regardless of your aim, but a sales goal explains what you desire to happen.
What You'll Need for Accurate Sales Predictions
The most critical criterion for a strong sales forecast is good data. It is therefore critical to have accurate statistics.
New enterprises with little data on their own sales process may have to depend on industry norms or informed predictions. More established businesses, on the other hand, may estimate future performance using existing data.
Here's what you need to accomplish first, step by step, before you start thinking about how to anticipate sales:
1. Keep track of your sales process
You won't be able to anticipate if any given contract will complete without a fully documented sales process defining the activities and phases involved.
2. Establish sales targets or quotas
While your prediction may differ from your objectives, without a target, you won't know whether your forecast is excellent or terrible. As a result, each sales agent, as well as the whole sales team, need a personal quota. More information about quotas and sales targets may be found here.
3. Establish a baseline or current average of several key sales KPIs
Forecasting will be significantly easier if you have easy access to measures of the following basic sales metrics:
The amount of time it takes for a consumer to indicate interest.
How long does it take to complete a transaction?
The average cost of a transaction
The time it takes to onboard a new customer.
Average renewal rates, or the frequency with which you receive repeat business
4. Recognize the present state of your sales funnel
Make sure you know what's in your pipeline right now, and that your CRM is up to date and correct. Forecasting is more difficult, but not impossible, without a CRM.
Methodology for Predicting Sales
You may forecast sales using a variety of approaches. To develop a variety of projections, many organizations combine two or more sales forecasting methodologies. As a result, they have a best-case and worst-case scenario.
Methods for estimating sales include:
1. Relying on the advice of salespeople
"When will this contract close, and how much will it close for?" Many sales managers simply ask their salespeople.
While this is a viable option for generating a sales prediction, it is not advised. Salespeople have a tendency to overstate sales projections, and there is no consistent way to make a forecast using this strategy. Unfortunately, many companies continue to use this strategy to forecast future sales.
2. Making use of past data
You utilize a record of your past performance under comparable situations to predict how you'll do in the present with this strategy. For example, you could know that your company grows at a rate of 15% year over year and that you closed $100k in new business last month. As a result, you should expect $115,000 in income this month.
This technique is marginally more accurate, but it overlooks other aspects that may have changed in the past year, such as the amount of sales representatives you have or how your rivals are performing.
Also Read: B2B Sales in the Age of COVID-19
3. Making use of deal phases
You attribute a likelihood of closing a contract to each stage of your sales process in this forecasting strategy. You may then multiply that chance by the size of an opportunity to get an estimate of the revenue you can expect at any given moment.
This way of predicting is even superior, and it is quite popular due to its simplicity. It does, however, have a flaw: it overlooks the opportunity's age. Are two chances with a sales demo planned equally likely to close if one is three weeks old and the other is three months old?
4. Forecasting the sales cycle
As a result, rather than using the age of the sales opportunity, an alternative forecasting strategy is to utilize the age of the sales opportunity.
It compares the amount of time a deal has been in the works to the average time it takes to conclude a contract. If you have distinct goods and sales cycles based on whether you received a referral or are following up on a lead from prospecting, you'll need to break them out to get an estimate of how likely a deal will close.
This procedure requires precise data. Everything must be properly entered in the CRM so that you can see what type of lead it is and how long it has been in the system. If you don't have a CRM that can swiftly and simply capture all of this, your reps will have to enter a lot of data.
5. Forecasting pipelines
This approach is significantly more precise, although it still relies on high-quality data. It examines each opportunity in your pipeline and evaluates it based on a variety of criteria, including age, deal type, and deal stage.
This is a more advanced strategy, therefore it's unlikely to work without specific tools that can analyze what's in your pipeline.
6. Using a bespoke forecast model with numerous factors and lead scoring
This approach of predicting uses a mix of all of the above. It is comparable to the pipeline forecasting approach, but it is more comprehensive and sophisticated. To make these projections, you'll usually need an analytics tool or advanced CRM reports set up. You also need really solid data to begin with, so you're depending on your salespeople to submit a lot of reliable data.
This form of sales forecasting can be the most accurate if you have those resources. You may also consider an opportunity's age, present stage in the sales process, and the traits of the prospect that make them more inclined to buy.
Examples of Sales Forecasting
Reading about predicting isn't often as beneficial as looking at examples. Here are some fundamental hypothetical examples to explore in order to understand how sales forecasting works in the real world.
Example 1: Prediction Based on Sales Data from the Past
Let's imagine you made $150,000 in monthly recurring income last month, and your sales revenue has increased by 12% per month for the past 12 months. Your monthly churn has been around 1% each month throughout the same time period.
Your expected revenue for the following month is $166,500.
You take the previous month's revenue and double it by your predicted growth, then deduct your expected churn:
($150,000 * 1.12) - ($150,000 * .01) = $166,500
Example 2: Using Your Current Funnel to Forecast
Let's pretend you have three job openings this month:
One in which you've just received a brief phone conversation with a $1,000 estimated value.
One that has had a complete demo and is believed to be worth $1,500.
One with a $1,200 offer.
You've done the math and know that each of these steps has the following probability of closing:
"Connect Call" indicates a 30% possibility of shutting.
"Demo" indicates a 40% possibility of shutting.
"Offer" indicates a 70% likelihood of closing.
You multiply that chance by the deal's expected value and add them all together to get a total sales prediction of $1,740, as shown in the following example:
Example 3: Forecasting Using Multiple Variables and Lead Scores
You've done your homework and have lead scoring configured in your CRM. You divide your leads into three quality groups: A, B, and C. These factors influence the likelihood of a deal closing.
You may also be aware that businesses with less than 50 employees are less likely to close, whereas those with more than 50 employees are more likely to do so.
Using a table like this, you could then use typical opportunity sizes to compute the anticipated value of every specific chance:
Tools for Sales Forecasting
CRM software combines the database's storage and retrieval capacity with specialised sales features to assist sales people close transactions. Lead tracking, funnel analytics, call sequences, and reporting are examples of these functionalities. You should select a CRM based on the size and nature of your company. There's a lot you can do with your CRM to get the most out of it.
If your business is just getting started or has a small number of items, spreadsheet software like Excel should serve. It's versatile, conditional, and allows you to create amazing charts for a low price. However, it is time-consuming and prone to mistakes, therefore it may not be suitable for a bigger operation.
Platforms for Sales Insights
Platforms for Sales Analytics aggregate data from several goods and services, create projections, and provide deep analytics. Many of them also provide useful graphs and charts. Dedicated analytics tools also offer the benefit of being constantly updated. They can provide more information on sales pipelines, goods, and employee performance.
They can also provide more information about any gaps in the procedure. They may assist with anything from identifying development possibilities to determining which team members should be assigned to which clients.
Lead Scoring Tools
They assist you in determining which prospects are worth pursuing for sales and assigning them a priority. They allow you to rank prospects based on their behaviors on your website, the results of discussions, and any other factors that your sales team considers important. A lead scoring tool may also assist your marketing team with campaign segmentation by identifying who is ready to purchase and who requires more effort, as well as the amount and reason for involvement.
It may also assist with content customisation by assisting you in determining the prospect's current degree of interest in your company as well as the areas in which the prospect has already expressed interest.
Resource allocation tools for project management
The most critical component of your sales cycle is follow-through, since it is the only way to develop solid client connections. Project management software keeps your team on track and ensures that they have the resources they need to finish the job. Project management software eliminates most of the manual labor of keeping track of what's been done and when. They may also make it easier to collaborate with other teams who use the same technologies.
If you only need a fresh revenue projection, simpler solutions will suffice. However, the value of a sale is determined not just by the magnitude of the transaction, but also by the costs it incurs elsewhere in the company. You must comprehend the run-on effect in order to develop truly accurate sales estimates. You may need to integrate data from your accounting software in your forecasting exercise if you want to anticipate gross margins and account for cost of goods sold.
Sales forecasting is a method of projecting a company's monthly, quarterly, and annual sales totals based on historical data and common sense.
The sales estimate should be viewed as a working plan rather than a hard prediction by your team.
Estimate the length of your average sales cycle and conversion rate before attempting to develop a prediction.
You may create various different sorts of predictions. Within your company, test several ways for accuracy.
Please include examples as well.
A sales manager or vice president of sales should make informed decisions and plan their sales strategy based on sales forecasting reports, just like a stock trader adjusting his portfolio based on economic forecasts or a campaign manager plotting the candidate's election campaign route based on political forecasts.
However, being data-driven is essential for successful sales forecasting. Data-driven sales forecasting may provide you more control over your operations, assist you in avoiding mistakes, and even motivate your team to exceed your predicted goals.
So, in this day and age, data-driven sales forecasting is a must-have to run a successful organization.