Ultimate Guide to Sales Forecasting: Using Sales Data to Level Up Your Sales Team
What kind of goals should you set for your sales team in the next quarter? You want to set realistic sales goals that also challenge your salespeople to grow.
That’s where sales forecasting comes in. It can pave the way for sustainable company growth while keeping your team motivated. Accurate sales forecasts help everyone, from sales leaders to sales managers to sales reps make intelligent business decisions.
However, most organizations struggle with forecasting. That’s because they base their numbers on intuition instead of data. A recent Gartner survey found less than 50% of sales leaders and sellers expressed high confidence in their forecasting accuracy.
No wonder forecasting and modeling stood at number four in terms of importance as a sales operations skill!
In this article, we’ll share the basics of forecasting as well as strategies to improve accuracy and overcome common challenges.
Download our free sales forecasting template to start projecting your future sales with precision.
Let’s start with the basics.
What is Sales Forecasting?
It tries to predict how much a company, team, or salesperson will sell in the upcoming month, quarter, or year.
If you want your forecasting models to remain on point, you need to conduct forecasts at least quarterly. You can benchmark your performance on historical sales but also take seasonality and other factors into account (which we’ll cover later in the article.)
A CRM like Close can streamline reporting for sales leaders. Its opportunity funnel report can analyze your pipeline health and show you how much revenue can roll in and for what duration. Plus, it can show you metrics like your overall win rate, sales velocity, and conversions. It also lets you project sales forecasts on your open deals.🙌
Why is Sales Forecasting So Important?
Accurate sales forecasting helps your company plan for the future, adapt to market fluctuations, and mitigate potential pitfalls. They can be leveraged across departments to help you make informed business decisions. Here are a few other benefits to accurate sales forecasting:
- Sales leaders can leverage forecasts to design challenging (yet attainable) quotas for their managers and SDRs. You can motivate your SDRs by setting weekly sales goals based on forecasting. If your team falters below them, you can take corrective action faster.
- Help your company budget for hiring, managing your workforce, launching marketing campaigns, etc. Does your forecast predict an increase in opportunities in the last quarter? Then maybe you need to start recruiting new customer success representatives to manage those relationships.
- Plan ahead to manage your cash flow, upgrade tech, and make other business decisions. Are you likely to be strapped for cash next year? Maybe you need to cut down on freelance assignments or end contracts for that software you never use. Accurate sales forecasting can help you better prepare for a surplus or shrink in funds.
Remember, your sales forecasts have some wiggle room for inaccuracy — but not too much. In the next section, let’s look at the factors that affect the quality of your projections.
Factors that Impact Sales Forecasting Accuracy
Good sales forecasts are data-driven. But internal and external factors (like the ones mentioned below) can impact their accuracy.
- The quality of historical data (on your past performance)
- Changes to your products or services
- Industry trends
- Budget allocation
- Marketing spend
- Economic conditions
- Customer satisfaction
- Political conditions
Every forecast has limitations, and you must remain mindful of the aspects that impact your forecast’s accuracy.
For instance, new businesses just starting their sales process do not have the luxury of past sales data. So, they might base their forecasts on industry trends or even educated guesses, which may be less accurate. (We’ll look at the different sales forecasting methods later in the article!) But first, let’s see how the sales forecasting process works.
5-Step Sales Forecasting Process for Data-Driven Predictions
Below is a forecasting process you can follow to move beyond trusting your gut to predict what next month’s sales will look like.
Step 1: Establish Goals For Sales Forecasting
What are the objectives you want to achieve with forecasts? If you’re a mature company with multiple offerings, you may want to set targets for a specific product line. On the other hand, startup sales forecasts may focus on demonstrating your new sales to get investors excited for your next funding round.
Step 2: Gather And Analyze Your Sales Performance Data
What do your total sales look like in the previous year (or your chosen forecasting period)? An easy way to start forecasting is assuming your growth rate remains the same and then calculate your revenue based on it.
However, factors such as seasonality and market conditions can seriously affect the accuracy of such forecasts. So adjust your forecast numbers accordingly. When you’re ready, consider leveling up to a more scientific approach (which we’ll talk about in the next step.)
Step 3: Select A Sales Forecasting Methodology
There are two broad forecasting models: bottom-up and top-down. In the first one, the company predicts the revenue by multiplying the number of units it will sell by the cost per unit. In the latter, you begin with the total addressable market size (TAM) and estimate the percentage your business can capture.
A bottom-up approach is preferred generally because you get granular data. It focuses on the specific unit economics of your business and your forecasts can quickly adjust with changes in variables like your team composition, the cost of your product, etc.
Your business model, the age of your business, the data tracking habits of your sales reps, the size of the sales team, and other factors generally dictate your methodology. We’ll look at a few top methods later in the article.
Step 4: Create A Sales Forecast
Depending on your sales team structure and the needs of your organization, sales leaders (VP, Director, CRO), managers, and SDRs can all prepare their own forecasts.
The numbers they report and are held accountable for may depend on the salesperson's seniority.
- The VP can establish the ground rules for forecasting and base their forecast numbers on what the downward leadership predicts.
- The managers will guide their directly reporting sales reps to prepare individual forecasts. Then they will combine all of the reps' forecasts together to prepare their own.
In addition to considering past sales data, you should also include the marketing, product, finance, and HR departments in your forecasting process. They can provide valuable insights about their individual strategy and help you create a more well-rounded forecast.
Step 5: Monitor The Accuracy Of Your Forecasts
Finally, make sure you track your forecasts against actual numbers at the end of the quarter (or your chosen time frame) and evaluate accuracy over time. You want to note the discrepancies and investigate their causes. Did your reps miss quotas and weren’t as productive? Were your projections too ambitious?
You want to iterate your forecasting process, transparently share your accuracy with your team, and try to improve your projections. A thorough understanding of your revenue will help the leadership make smarter business decisions about budget and spending.
How to Improve Sales Projection Accuracy
The usefulness of your sales forecasting is based on how accurate they are. Here’s how you can create accurate revenue forecasts:
Analyze Historical Sales Data
Your annual run rate (ARR) is a great baseline for predicting future sales. To calculate the metric, simply multiply your current revenue over your chosen duration. ProfitWell depicts the formula in the graphic below:
You can break down this number by reps, products, price, etc.
Incorporate Changes in Sales Strategy
Are you launching a new product? Maybe you’re changing your pricing schemes or have started getting traffic from a marketing channel that didn’t work last time. Any change in your business strategy, the launch of a new promotion, hiring of new sales staff need to be accommodated in your forecast.
Anticipate Conversion Rate Changes
Do you anticipate a recession? Maybe your competitor is going public or acquiring a company. Or your marketing team may have tested a new lead generation source that works well for them. All of these factors will affect your conversion rate.
As a sales leader, you want to anticipate any changes in market conditions, keep tabs on the competition, and ideally be able to re-forecast based on real-time market situations or demand changes.
Challenges Within the Sales Forecasting Process
To create a foolproof sales plan, you need a robust sales forecasting process. But here are the challenges you may encounter on the path to better forecasting. Watch out for these challenges:
Subjectivity of Sellers
While seller instinct is an asset in different situations, subjective opinions on prospective deals can throw off your accuracy.
Are the sales reps in your organization relying on their intuition about opportunities or on objective data and lead scoring? You need to coach your team to follow a formalized and analytical process.
Lack Of Quality Sales Data
Today, Customer Relationship Management (CRM) software comes with predictive capabilities. Close, for instance, can gauge the health of your pipeline. However, reps might not be entering data correctly, which can impact your data quality negatively.
Investing in a CRM such as Close — that’s built to improve your productivity — can help by capturing customer communications and notes in a single place. No more tedious data entry!
And hey, it integrates with your sales stack seamlessly, letting your team execute their sales process smoothly.
Sales leaders need to collaborate and gather input across sales roles and territories to prepare accurate forecasts.
If you rely on Excel sheets for forecasts (or if the CRM in your company has poor adoption rates), it can lead to inaccuracies. Your product, sales, marketing, and finance teams also need to use the same methodology and a consistent approach .
Knowing these challenges can equip your team to handle them confidently and make accurate projections.
Top Sales Forecasting Methodologies (and Examples)
You can use several sales forecasting methods to predict future sales, but some are more accurate than others. Below are a few methods you can start with to start projecting your future revenue.
1. Relying on Your Sales Team’s Opinions
One of the most common ways to create forecasts is by trusting the opinions of your sales reps. You ask them how much a deal might be worth when it closes and when they expect it to happen. Given that reps try to have regular communication with prospects — they are the most likely to know how things are on the ground.
However, salespeople tend to overestimate sales forecasts. So relying purely on intuition and an inconsistent process invites inaccuracy.
2. Using Deal Stages
When using deal stages for forecasting, you assign a probability of a deal closing in each stage of your sales process. You can then multiply that probability by the size of the opportunity to estimate the sales revenue to expect.
For instance, if you are selling training webinar software packages for large corporations, you might assign a 2% chance of closing if you receive a reply to your initial cold email.
You can raise it to 50% if your prospect agrees to a product demo and up to 75% if you book a meeting to show your pitch deck to the company’s key decision-makers.
The bottom line is that the further the prospect is down the pipeline, the higher the odds of closing the deal, as shown in the example by Akucast below:
One of the main disadvantages of using deal stages for sales forecasting is that it doesn’t consider the passage of time. Whether you presented a demo to a prospect three weeks ago or yesterday — they are treated the same even though the probability of these two deals closing is widely different.
3. Length of Sales Cycle Forecasting
This is an alternate forecasting method that helps to provide a more accurate picture than using deal stages. When assessing the strength of a particular pipeline, this method takes into account the age of the sales opportunity as opposed to the probability.
You compare the time a deal has been in the pipeline to the time it normally takes to close a deal. The formula for calculating the length of the sales cycle is the total number of days it took to close recent deals and divide them by the number of deals.
An advantage of sales cycle forecasting is you can apply it to a lot of sales cycles (depending, of course, on the source). For instance, a cold email outreach prospect might take three months, whereas a referral client might take three weeks. (Don't know where to start with your cold email outreach? Let our AI-powered tool, the cold email generator, take care of it for you. Automate your email templates and simplify the process!)
If you run a large business like Wix or Shopify, which deals with different sales cycles (or different products), you will have to create separate sales cycles to get a more accurate prediction of how likely the deals are to come off.
This method requires accurate data, which makes it extremely valuable to companies that religiously track everything about how and when a prospect enters the sales pipeline.
The good news is that it's easy to log all the data easily and correctly with the right CRM without requiring the sales reps to enter loads of data (that’s Close!)
Many businesses employ two or more forecasting techniques to create a range of sales forecasts. This gives them both the best-case and worst-case scenarios. You can start with one of the above methods or consider even more sophisticated ones, such as multivariable analysis forecasting, which we share in the startup sales forecasting article.
How to Choose the Right Sales Forecasting Software Tools
The right sales forecasting tools can improve your accuracy, automate tedious data entry tasks, and improve your forecasting process. Here are the features you should consider when you’re ready to move beyond an excel sheet and invest in professional sales forecasting software.
- Customizable sales forecasts and revenue projections: The main feature you'll want to look for is the ability to easily create custom forecasting metrics based on sales performance drivers and revneue streams.
- Ability to model fluctuations: If seasonality, political, economic, or other situations arise, then the software must be able to model and analyze them. It can help you prepare for them better.
- Forecast across territories and product lines: As you’ll prepare sales quotas for your reps based on geography, product, and a group of accounts, you want to have the software create sales forecasts by factors such as city/state, specific product, etc.
- Track progress against your sales targets: Once you have a forecast, the software must be able to import your sales data and show your performance against your sales goals.
- Integrations with third-party sales software: Your software should be able to import sales data from spreadsheets and integrate it with other tools that are part of your sales team’s workday.
For accessing advanced forecasting capabilities, enterprise companies typically need dedicated software. However, for most SMB, customer relationship management software (CRM) is sufficient to gain an accurate view of your sales activity and your pipeline’s current health and project future revenue.
Why Close is the Best CRM Choice for SMB
Close is a robust CRM that provides an accurate view of the entire business to sales leaders. It comes with built-in sales reports and real-time dashboards to track the sales activities of your team.
You can use it to forecast the revenue in your pipeline. On top of the software, you can also leverage sales forecasting templates to track important KPIs for your team.
Close also lets sales reps call, text, email, and SMS from a single place. Their customer interactions are automatically logged, saving your time, and ensuring high-quality sales data (without any headaches.)