Sales Forecasting Examples

Accent Technologies

Sales Forecasting Examples

You wouldn’t head out for the beach or a night on the town without checking the weather forecast, would you? Of course you wouldn’t – so why would you plan for your company’s fiscal year without a sales forecast?

Forecasting your projected sales is a vital part of running a business – it allows you to create a realistic picture of what to expect in the weeks, months, and year ahead. Without it, you’re essentially flying blind – and that can cost your business in a lot of different ways.

Have no fear, though – today we’re going to talk about what a sales forecast is, why you need one, and then provide some examples so you can begin forecasting your own numbers…with way better accuracy than your local weatherman.

What is a Sales Forecast?

Before we get down to business, let’s take a moment to discuss a sales forecast definition

A sales forecast is essentially a prediction of how much sales you’ll generate in a given timeframe. It uses data to determine what these numbers should be, but like all things that rely on looking into the future, it’s not set in stone. 

Even the best sales forecasts can be cast into disarray by unforeseen events – the Covid-19 outbreak is but one example of how even the best projections can be off thanks to factors no one saw coming.

So, while a sales forecast is vitally important for determining projections for the month, quarter, or year, you must always be prepared for unplanned events – both positive and negative. 

Here are some of the most common things that can radically alter a sales forecast: 

•  Your Industry

Basically every industry has peak seasons and off seasons, and knowing that is vital to determining how to forecast as you peer into the future.

Think of The Simpsons episode where Homer talks about investing in pumpkins. His data shows pumpkin futures are up in October – but his plan to cash out in January? That’s a recipe for disaster. The pumpkins are way past their peak season by that point.

This is a ridiculously over the top example, but the peaks and valleys of your business’s sales cycle must be taken into account. Failure to do so can dramatically impact the accuracy of your projections. 

•  External Factors

2020 will go down as the year where everyone’s sales forecasts were rendered useless by Covid-19. Talk about an external factor – one that no one saw coming even a year prior…

And yet, while this outside influence certainly ruined almost everyone’s forecast for 2020, it didn’t affect everyone in the same way.

While restaurants, bars, and gyms have been negatively affected by the virus, companies like InstaCart and DoorDash have likely seen their numbers explode beyond what they’d projected in 2019.

No matter which way an external factor pushes your forecast out of alignment, it’s important to remember that you should have contingency plans. Whether numbers come up short of your projections or dramatically exceed them, it can impact your business.

Businesses that fall short may have to do some belt-tightening, including reducing spending and in a worst-case scenario, cutting jobs.

Businesses that radically exceed their numbers have their own set of issues to address – keeping up with demand, needing to hire more people, ramping up production, and so on.

The best sales forecasts factor in both best and worst case scenarios so the company is prepared no matter what happens. 

•  Internal Factors

While external factors are often harder to predict, things happening internally in your business can also dramatically impact a sales forecast.

Unexpected changes in your manufacturing process, management team changes, equipment upgrades, and a whole host of other factors can completely derail a forecast.

Internal factors are probably less of a blindside than the external ones, but that doesn’t mean you shouldn’t be preparing for them as well.

And really, that’s the main takeaway here – no plan or forecast is perfect. Preparing for contingencies is something that all good forecasts take into consideration.

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Why Do We Need a Sales Forecast?

Now that we know what a sales forecast is, let’s talk about why you need one.

The simplest answer is because not having one can lead to disaster.

A sales forecast is your tentative roadmap for what lies ahead. It provides goals to work towards, it gives you an idea of your revenue, and it allows you to plan for the future.

If the road to business success is a journey, then your sales forecast is basically the GPS. To not have one is like wandering down a narrow mountain path…in the dark, with a blindfold on. Sure, you might make it down to the ground safely – or you might fall off the cliff.

With that in mind, here are some of the key areas where a sales forecast can keep you on the right path.

1 Create a budget and financial plan

Sales revenue is how businesses make money – and if you can’t even venture a guess as to how much revenue you should have available in the coming year, then you’re likely to under- or over-budget.

A detailed sales forecast lets your CFO and financial team get an idea of what lies ahead – and they can then budget accordingly.

Sound financial planning makes everything run more efficiently. Having a detailed projection makes sure you’re spending wisely. 

2 Managing Sales Teams and Goals

Sound sales projections can also help you plan how your sales team will function. 

Having an idea of what you expect your sales to be for the next twelve months  allows your sales team to come up with better quotas, decide where to best focus their energy, and ensure proper staffing levels are met and maintained.

Looking for help analyzing your data in order to forecast your sales goals and devise quotas? Sales enablement software can help! Many feature not only sales contact tracking, but some utilize complex artificial intelligence to help you predict customer behaviors and close more deals.

3 Devise Marketing Strategies

Not only can a sales forecast help you establish goals and quotas for your sales teams, they can help you with your marketing as well.

A detailed sales forecast can show you which products are underperforming. Armed with this information, your marketing team can decide whether they need to bolster their efforts to promote the product, or scale back and focus their energy elsewhere.

At the macro level, you can also see that if projections indicate lower sales ahead then determine how to use your marketing efforts to help sales across the board.

4 Maintain Consistent Pricing Levels

With a poorly constructed sales forecast, you might see your numbers are lower year over year and immediately adjust by cutting prices out of fear.

Utilizing a fully realized sales forecast can prevent this and help you maintain consistent and profitable pricing on your products and services by ensuring you’re basing decision on actual projections and not just gut feelings and panic.

5 Maintain Proper Inventory Levels

And finally, a sales forecast can be an invaluable tool when it comes to keeping proper inventory levels on-hand at all times.

Without a sales forecast, you could waste thousands (or millions) of dollars carrying excess inventory you don’t need. Or you could find yourself out of stock on key items when demand is booming, leaving money on the table.

If you have a data-based idea of how your sales should play out in the future, it’s much easier to make sure you keep what you need in stock and never actually run out of an item when it’s in demand.

There are many other ways a data-driven sales forecast can help your business navigate the tricky waters of modern day commerce, but these five are some of the most important reasons for taking the time to make accurate, detailed projections.

Sales Forecasting Methods

Now that we know what a sales forecast is and how it can benefit your business, let’s look at how to forecast sales using some of the most common methods.

Since there’s a wide range of businesses out there, no one sales forecast method fits every company. If you have a single physical location, your needs are different than an e-commerce giant. Finding the right forecast methodology is important.

The good news is there are a lot of different ways to craft a customized sales forecast for your business. From generalized templates to fully customizable analytics designed specifically for your company, there’s a sales forecasting method that will help you reach your goals.

Here are some of the most popular.

•  Historical Forecasting

We kick things off one of the most commonly used methods of predicting future business: Historical forecasting.

As the old saying goes, it’s often helpful to know where you’ve been so you can get to where you want to be, and that’s the basic idea behind this methodology.

In its simplest form, historical forecasting looks back at the sales data for the same time period from the previous year or years.

Armed with that knowledge, you can then assume that if everything is relatively the same your business should perform a small percentage better in the coming period. Or at the very least, it should stay the same.

Using this approach allows you to see trends over time and plan accordingly based on your previous data.

The downside of this approach is that it assumes everything will stay relatively the same as far as your sales go – which can be a pretty risky assumption.

That being said, if you use this approach and really look at what factors have influenced your previous years’ numbers and adjust accordingly, it can provide insights.

Overall, this is not the most sound approach to forecasting – but it can give you a generalized overview of how your business performs year over year without requiring a ton of effort on your part.

•  Intuitive Forecasting

We’ve made jokes about crystal balls and psychics when it comes to sales forecasting, but there is something to be said for good old intuition – which provides the backbone of our next forecasting method: intuitive forecasting.

As the name suggests, this approach relies heavily on your gut instinct (or more accurately, your sales team’s gut instincts…) to formulate an idea of what lies ahead.

Obviously, this approach should raise some concerns – relying on our gut instincts can be dangerous, especially if we allow emotions to color our thinking.

But if you have an experienced sales team and don’t have a lot of historical data to draw on this method could be an option for you.

Naturally, your forecast might vary wildly from reality (meaning you might be better served to be conservative in your predictions), but good sales people have a unique perspective from being in the trenches – one that management would be wise to take into consideration.

Another way to approach this method is to leverage sales AI to gather and collect all buyer/seller engagement data (emails, calls, calendar, etc.). With this data in-hand, you can then visualize and score the opportunities in your pipeline and better understand their health and their energy.

This protects your forecast from the inaccuracies that a wide range of subjective interpretations would presentUsing AI in sales management places the responsibility of intuitive forecasting in the hands of the managerAnd grounds the forecast in actual buyer/seller activity data. This elevates the forecast from a “feeling” to an well-informed, educated guess. 

•  Opportunity Forecasting

Our next sales forecasting model is a lot more detailed – and because of that, it can lead to much better results.

Opportunity forecasting operates on the idea that you’ll predict the number of sales you can generate through your funnel and pipeline.

To make this method effective, you’ll really have to understand how your sales pipeline works, meaning you’ll need to figure out what percentage of customers go on to make a purchase at each stage of the pipeline.

An example might look like this:

New Lead: 15% likelihood of completing a sale.
Qualified Lead: 25% likelihood of closing a sale
Request Proposal: 40% likelihood of closing a sale
Negotiation: 75% likelihood of closing a sale
Contract Stage: 95% likelihood of closing a sale

Using these averages, it’s entirely possible to predict your sales moving forward. You simply take the potential value of the deal multiplied by the percentage, then add them all up to come up with a figure.

This method is great for companies with a robust pipeline system that tracks where their customers are in the funnelIf you’re not already doing this, there are Sales AI and Sales Management AI solutions that can make implementing this type of forecasting much simpler. We explore deeper how to best execute opportunity management and pipeline management in the below linked post (authored by our CEO, Pete McChrystal).

SEE ALSO: How Sales AI Improves Pipeline Management 

•  Pipeline Forecasting

You might find yourself thinking “didn’t we just discuss this in the last method?” and the answer is…sort of.

Pipeline forecasting builds on the historical data you’d find in an opportunity sales forecast, but goes way more in-depth with the data.

Where an opportunity forecast mostly just uses historical data and likelihood of sales percentages to put a potential dollar amount on deals, pipeline forecasting takes many more elements into consideration.

Not only will this methodology look at your historical closing rates relative to pipeline position, it can also factor in things like salesperson effectiveness, seasonal variances, win rates, and more.

The benefit of this approach over opportunity forecasting is that it’s much more detailed – and as we all know, the more detailed your forecast, the more likely it is to provide accurate projections.

That being said, this isn’t a forecasting method perfectly suited for everyone. To begin with, it requires a lot of work to be effective. You really have to take a deep dive into your analytics, your sales metrics, your pipeline, and more to gather all the data you need to try to craft a truly accurate forecast.

Of course, for some businesses the rewards will be worth the effort. Pipeline forecasting can give you some very detailed and potentially very accurate projections if you put in the work.

This is another area where Sales Management AI can significantly enable your team. We explore this deeper in our other post.

SEE ALSO: How Sales AI Improves Pipeline Management 

•  Test Market Analysis

So, maybe you’re not worried about forecasting all your sales for the upcoming quarter or year. Or maybe you’ve already done that, but you’re about to launch a new product that came into existence after your forecasts. How can we forecast those sales when we have no historical data to draw upon?

One way is to utilize what we call test market analysis.

Prior to actually launching the product, you can do a limited roll out or a test market run to see how it performs and extrapolate from there.

While not as detailed or robust as full historical or multivariable forecasting, test market analysis forecasting can offer some insight into how your customers will respond to a new product.

And while there are many variables that can come into play after test marketing analysis and those first full-on sales figures, we can at least glean some idea of how a new product will perform based on smaller data sets.

Is this the ideal method for forecasting? No. That being said, in this situation where hard data is limited, it can at least give you a ballpark estimate of what to expect until you actually have enough real data to draw conclusions. 

•  Length of Sales Cycle Analysis

Do you know how long it takes your team to close the average sale from first contact to payment? If so, you can average those figures to determine your sales cycle and compare that to your current funnel and extrapolate from there.

As an example, say you have sales from a time period that look like this

Sale A: 10 days
Sale B: 20 days
Sale C: 30 days
Sale D: 20 days

Simple math there tells you the average sale takes 20 days to complete.

Armed with this information, you can compare to current in-progress sales. Deals that are approaching the 20day mark can be considered good candidates to close – meaning you can make projections based on that revenue and data.

This is another one that relies a bit more on projecting than hard data. And while all sales forecasts can be knocked off course by unforeseen events, this one is particularly susceptible to it because it doesn’t consider a lot of different variables.

Despite that, it’s great for your sales management team as far as figuring out lead times for sales. So, while it might not be the main component of your sales forecasting project, like everything else on this list, it has value both as a standalone metric and as part of a multivariable approach.

•  Multivariable Analysis

Speaking of multivariable approaches, the title alone should give this one away. For this method, we’ll be tracking a wide range of data to get the most accurate analysis possible.

What makes this one truly effective is that combines analytics from all your other methods to create a complete picture with projections that consider a wide range of variables.

You’ll use your historical data, your pipeline data, your sales cycle data, and a wide variety of other sources to help craft a crystal clear picture of what to expect from your sales moving forward.

This one can be extremely time-consuming and data-intensive, but the results are probably the best you can get short of adding a psychic to your analytics team or investing in crystal balls.

Given that multivariable analysis is so intensive, it’s not right for every business. Small businesses are less likely to have enough data points to make a wholly accurate prediction – or need this level of granularity in their analysis.

However, larger companies with a streamlined data analysis infrastructure and sales enablement software can take the deep dive into this method of forecasting and expect stellar results. 

Final Thoughts

The beauty of sales forecasting is that it can be as complex or as simple as your business requires. You can simply go with your gut when making projections or break down mountains of data that take hundreds (or thousands…) of variable into consideration.

You can do it in a simple meeting or you can use complex sales enablement software to crunch the numbers. The options are limitless.

We’ve mentioned some of the most common types of forecasts, but it’s entirely possible to customize any of these so that they fit your exact needs. A robust sales enablement software solution can streamline this process and reduce a lot of the guesswork, which makes everyone’s life a little easier.

The key takeaway here is that sales forecasting is a valuable tool that can help you ensure your business isn’t blindsided by market fluctuations.

Having an idea of how much sales revenue you will generate in any given timeframe can help you avoid overspending, supply and personnel shortages, and lost revenue.

No sales forecasting system is 100% accurate, but having some insight into the future is better than having none at all. It’s better to be safe than sorry.

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Accent Technologies is the first and only SaaS company to bring together Sales AI and Content Management in a trueRevenue Enablement Platform. We provide both sales and marketing with better visibility into the performance of their teams. This drives revenue through intelligent recommendations for complex sales scenarios and provides the data for rich analytics that power better coaching, forecasting, and long-term customer support. Learn more about our solutions or request a live demoto see it in action. 

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