2023's Best Forecasting Methods, Techniques and Tools


2023’s Best Forecasting Methods, Techniques and Tools

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 an accurate 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 flying blind. And that can cost your business in so many different ways. 

Today we’re going to talk about what a sales forecast is. We’ll also let you know why you need one and then provide some examples. This way, you can begin forecasting your own numbers.  

What is a Sales Forecast?

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

A simple sales forecast is a prediction of how much sales you’ll generate in a given timeframe. The forecast uses data to determine what these numbers should be. A sales forecast is also known as projected sales forecasts.  

To make a sales forecast, you collect and analyze past data. 

This analysis is performed via quantitative or qualitative modeling. During analysis, you identify patterns relevant to your company.  

The results from the forecast can be used for business strategies, such as financial operations, demand planning, financial & marketing operations and production estimates                                       . 

Another important thing to know about forecasting is that methods for doing them can be very intensive and time consuming.  

But spending more time on time doing them can often avoid several expenses and pitfalls inherent to running a company. Also, partners are less likely to invest in your company if you don’t provide a set of well-thought-out forecasts. 

How are Projected Sales Used

Sales projections are your company’s plan for forecasting future sales. It forms the foundation for determining aspects such as expenses, future growth, profits and staffing.  

The in-depth report it provides can help predict how something like a company or teams of salespeople will perform. Through it, you have an idea of what sells annually, quarterly, monthly and weekly. You can use its data to course correct, make your businesses grow and more. 

So, a robust sales forecast strategy can help you develop yearly sales projections. You can also create weekly sales forecast and monthly and quarterly sales forecasts.  

Uncertainty as a Factor

Like all things that rely on looking into the future, a sales forecast is not set in stone. Even the best sales forecasts can be cast into disarray by unforeseen events. For instance, the Covid-19 outbreak shows how the best projections can be off base. All because of factors no one saw coming.  

A sales forecast is an excellent tool for predicting what will happen. Of course, it isn’t perfect, and the Covid example shows its Achilles heel.  

To formulate an effective business plan, you must always prepare for uncertainty. That goes for both positive and negative results. 

Which Factors Impact a Sales Forecast?

A sales forecast is like an educated guess. For one thing, it’s based on your knowledge of the company and the market. For another, it’s based on external factors that may affect sales. 

So, it’s essential to remember that sales forecasting has its limits. And there are an endless number of factors that can affect its accuracy.  

You have to start somewhere though. The most common factors that can influence your sales forecast are: 

  • A Lack of Sales History 
  • Your Industry 
  • External Factors 
  • Internal Factors 

Lack of Sales History

It may seem obvious, but sometimes we can forget that a forecast is estimation. With established businesses, sales forecasts are typically built using historical sales data.  

Businesses then take the data and analyze previous results to extrapolate and create predictions.  

If a business is starting out and lacks historical sales data, it is sometimes a struggle to put together a sales forecast that is accurate. This fact makes the forecasting process a challenge.  

However, the problem of not having sales history is not insurmountable. How else would many people open businesses otherwise? We discuss how you can get around a lack of historical sales industry data later in this article.  

Your Industry

Every industry has peak seasons and off seasons. 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 (or good comedy)! The pumpkins are way past their peak season by that point. 

This is an over the top example. But it demonstrates that you must take the peaks and valleys of your business’s sales into account. Failure to do so can impact the accuracy of your projections.  

External Factors

2020 will go down as the year where Covid-19 rendered everyone’s sales forecasts useless. Talk about an external factor that no one saw coming even a year prior! This outside influence ruined almost everyone’s forecast for 2020.  

Meanwhile, quarantine didn’t affect every business in the same way. Delivery companies like Amazon, InstaCart, Domino’s Pizza and DoorDash saw their numbers skyrocket. And far beyond what they’d projected in 2019 too.  

But many restaurants, bars, and gyms lost revenue. Some even went under, especially if they were tottering on the edge pre-Covid.  

Companies that fall short may have to do some belt-tightening. These measures include reducing spending, and in a worst-case scenario, cutting jobs. 

Businesses that exceed their numbers have their own set of issues to address. They need to keep up with demand. They will also need to hire more people, ramp up production and more. 

These examples show that when numbers come up short of your projections or exceeds them, it’s not pretty. As in..your business will likely take a hit. These scenarios also show the importance of having contingency plans.  

The best sales forecasts factor in both the best and worst case scenarios. This way the company anticipates and reacts the best way, no matter what happens.  

Internal Factors

External factors in business are often harder to predict. But internal factors can also impact a sales forecast. Factors that can derail a forecast include:  

  • Changes in your manufacturing process 
  • Management team changes 
  • Equipment upgrades 
  • Consumer sentiment 

This list is the tip of the iceberg too. A whole host of factors can completely derail a forecast. 

Internal factors are typically less of a shock than external ones. But that doesn’t mean you shouldn’t be preparing for them as well. 

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

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 your 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 without incident—then again, you might fall off the cliff. 

Five Good Reasons for Creating Sales Forecasts

No one wants to fall off the proverbial cliff. To prevent this, here are key ways to use forecasts to keep you on the right path: 

1. Create a Budget and Financial Plan 

Sales revenue is how businesses make money. So, it’s bad news if you can’t even venture a guess on how much revenue you should make available in the coming year. If that’s the case, 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. Then, they can then budget accordingly. 

Sound financial planning makes everything run better. And having a detailed projection makes sure you’re spending wisely.  

2. Manage Sales Teams and Goals 

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

Knowing what you expect your sales to be for the next 12 months allows your sales team to perform their best. It allows them to come up with better quotas and decide where to best focus their energy. Management can also ensure that they meet and maintain proper staffing levels. 

Looking for help analyzing your data to forecast your sales goals and devise quotas? Sales enablement software can help! Many feature sales contact tracking and some complex artificial intelligence too. These features will help you predict customer behaviors and close more deals. 

3. Devise Marketing Strategies 

As you can see, sales forecasts can help you establish goals and quotas. They can help you with your marketing strategies as well. 

A detailed sales forecast can show you which products are underperforming. Armed with this information, your marketing team can decide a couple of things. One, do they need to bolster their efforts to promote the product? Or two, do they scale back and focus their energy elsewhere? 

At the macro level, you can also see that if projections show lower sales ahead. With that approach, you can direct your marketing efforts to help sales. 

4. Maintain Consistent Pricing Levels 

A lackluster sales forecast may cause your numbers to diminish. Unfortunately, you may immediately adjust by cutting prices out of fear. 

Utilizing a realized sales forecast can prevent this. It helps you maintain consistent and profitable pricing on your products and services. It also ensures you’re basing decision on actual projections and not giving into gut feelings and panic.  

5. Maintain Proper Inventory Levels 

A sales forecast can help you keep a proper inventory levels on-hand at all times. Without it, you could waste money carrying excess stock you don’t need. Or worse—you could find yourself out of stock on key items when demand is booming, leaving money on the table. 

It’s best to have a data-based idea of how your sales should play out in the future. That way, 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. 

A data-driven sales forecast can help your business navigate commerce in many ways. As you can see by these five examples, there are many important reasons for making accurate, detailed projections. 

Seven of the Best Sales Forecasting Methods and Techniques

Now you know what a sales forecast is and how it can benefit your business. Next, let’s cover forecasting techniques that get results. 

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 suitable forecast method is essential. 

The good news is there are a lot of different ways to craft a customized sales forecast for your business. For instance, generalized templates exist that you can use. There are also customizable analytics and more! 

In brief, there’s a sales forecasting method that helps you reach financial goals for everyone.  

This next section looks at seven of the best sales forecasting models. They are:  

  1. Historical Forecasting 
  2. Intuitive Forecasting  
  3. Opportunity Forecasting 
  4. Pipeline Forecasting  
  5. Test Market Analysis 
  6. Length of Sales Cycle Analysis 
  7. Multivariable Analysis 

1. Historical Forecasting 

It’s helpful to know where you’ve been. That way, you can get to where you want to be. That’s the concept behind this first sales forecast example: Historical Forecasting.  

Many businesses use historical data to forecast their future sales. This is a very common practice across all industries. And for decades, many companies have used it.  

One such company that uses this technique quite often is Amazon. They use it to track the number of people who visit the website and estimate how much money they will make from online purchases at the end of each month. 

Using this approach allows you to see trends over time. You can then estimate and plan your sales without the best visibility.  

This method may not provide perfect forecasting. But it can give you a generalized overview of how your business performs yearly. And it won’t take a ton of effort on your part. 

2. Intuitive Forecasting 

We’ve all made jokes about crystal balls and psychics when it comes to sales forecasting. Still, you can’t discount intuition when it comes to predicting what will happen. Which brings us to intuitive forecasting, where intuition drives the sales forecast.  

As the name suggests, this approach relies on gut instinct (or rather your sales team’s gut instincts). And these gut instincts will form the foundation for what lies ahead. 

This approach raises some concerns. Relying on our gut instincts can be risky. That is especially true if we allow emotions to color our thinking. 

Sales forecasting tools are the best. However, if you have an experienced sales team and don’t have a lot of historical data to draw from, this method could work.  

Experienced sales people have a unique perspective from being in the trenches. Management would be wise to take this into consideration.  

Naturally, your forecast might veer from reality a tad. In other words, it is best to be conservative in your predictions.  

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 data in-hand, you can then visualize and score the opportunities in your pipeline. This approach helps you better understand their health and their energy. This approach also keeps inaccuracies from subjective interpretations away from your forecast.  

You’ll want to use the best forecasting software when you are doing sales projections too. AI used in sales management places responsibility of intuitive forecasting with management. It also grounds the forecast in actual buyer/seller activity data. This elevates the forecast from gut feeling to a well-informed, educated guess.  

3. Opportunity Forecasting 

Of the sales forecasting models we’ve covered so far, this one is a lot more detailed. And because of that, it can lead to much better results. It predicts the number of sales you can generate through your funnel and pipeline. 

To make this method effective, you have to understand how your sales pipeline works. First, determine the customer percentage that purchases at each stage of the pipeline. 

Business forecasting examples 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 

Taking these averages, you can determine your projected monthly sales moving forward. Then, you take the potential value of the deal multiplied by the percentage. Lastly, add them all up to come up with a figure. You could even run this out to make an annual sales forecast. 

This method works well for pipeline systems that track where customers are in the funnel.  

Also, consider implementing Sales AI and Sales Management AI solutions. These systems can make implementing this type of forecasting much easier.  

The next nugget of insight comes to us courtesy of our CEO Pete McChrystal. In it, we learn how to best execute opportunity and pipeline management.  

SEE ALSO: How Sales AI Improves Pipeline Management  

4. Pipeline Forecasting 

Pipeline forecasting makes detailed predictions that help run and grow your business. It works by building on the historical data the same way an opportunity sales forecast does. In comparison though, it goes more in depth with the data than opportunity sales forecast does. 

To explain, opportunity forecasts use historical data. Next, it combines that data with likelihood of sales percentages. Then, it takes the two and puts a potential dollar amount on deals. In contrast, pipeline forecasting takes many more elements into consideration. 

These methods look at historical closing rates relative to pipeline position. Then, they figure in aspects like salesperson effectiveness, seasonal variances and win rates. 

The benefit of pipeline forecasting is that is it yields much more detailed data. And as we all know, the more detailed your forecast, the more likely it is to provide accurate projections.  

Nonetheless, this isn’t a forecasting method that’s suited for everyone. To begin with, it requires a lot of work to be effective. You have to take a deep dive into analytics, sales metrics, your pipeline and more.  

Once you do gather all the data you need, you can craft an accurate forecast. The method can yield very detailed and accurate projections if you put in the work. Of course, for some businesses the rewards will be worth the effort.  

Methods of Analysis  

Analysis is another area where Sales Management AI can shine and significantly enable your team. We explore analysis deeper in numbers 5-7 in the continued list below. 

SEE ALSO: How Sales AI Improves Pipeline Management  

5. Test Market Analysis 

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

Test market analysis is indispensable in these circumstances, especially when you’re a startup launching a new product. The method provides an accurate model to use, allowing you to gather initial data and figure out potential sales.  

From there, you can make any changes needed to ensure it has a successful rollout and that your inventory has enough stock.  

This method is not as robust as full historical or multivariable forecasting. Bu it does offer insight into how your customers will respond to a new product. 

Unknown variables will arrive after test marketing analysis and first full-on sales figures. That’s understandable. But 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, but it’s an excellent baseline. In situations with limited hard data, it can at least give you a ballpark estimate of what to expect. Afterward, you can use real data sets to tweak and draw conclusions.  

Bear in mind that test market analysis can be a bit pricey, depending on which market you’re in. Therefore, make sure your business has the budget and staff available to support limited launches and data gathering. 

6. 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. Then, compare that to your current funnel and extrapolate from there. 

As an example, say you have sales from a 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. Consider deals that are approaching the 20–day mark good candidates to close. It also means you can make projections based on that revenue and data. 

This is another technique that relies a bit more on projecting than hard data. All unforeseen events can impact sales forecasts. But this one is particularly susceptible to it, as 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.  

This method might not be a component of your sales forecasting project like others here. More importantly, it has value as a standalone metric and as part of a multivariable approach. 

7. 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. 

Many experts say multivariable analysis is the best forecasting method for sales. What makes this method effective? First, it combines analytics from all your other methods. Then, it creates visibility with projections that consider a wide range of variables. 

You’ll then collect historical and pipeline data, your sales cycle data and a wide variety of other sources. Finally, you will use them to craft a clear picture of what to expect from your sales moving forward. 

Multivariable analysis can be time-consuming and data-intensive. But short of adding a psychic to your analytics team, the results are the best you can get. 

Knowing how to calculate projected sales using multivariable analysis is invaluable. But seeing that its calculations are so intensive, it’s not right for every business. For instance, small businesses may not have enough data points for accurate predictions. Or need this level of granularity in their analysis. That’s not to say that small businesses can’t benefit from it in many cases.  

Larger companies can use streamlined data analysis infrastructure and sales enablement software to get the data they need. Once they take the plunge into multivariable analysis, they can expect stellar results.  

Historical Data’s Role in Forecasting Sales

The ability to use historical data in forecasting sales is one of the most powerful tools available when it comes to predicting future trends. If you are a company looking to use this tool, there are three steps you will need to take before starting: 

Step 1: Collect data from your past sales cycles.

Here, you look at sales data from the same time last year or in previous years. Taking that data, you can make a few assumptions. For example, say everything stays relatively the same in your business. Then, you can assume it should perform a small percentage better next period. Or at the very least, it should stay the same. 

Step 2: Look for patterns and correlations.

Next, look for patterns within that data. Try to find any sort of correlation between factors such as days of week or time of month. These are both common data points you can use.  

For example, if your business is very seasonal , you might see a spike in sales around the holidays every year. That way, next holiday season when people start searching for Christmas presents on Google or looking at Facebook ads about it, they will have an idea of what to expect based on previous years. 

Step 3: Analyze and compare.

At this step, you take all that data and analyze it. You can then compare your findings from the analysis with other similar companies to see what type of sales they had during a certain time period or how their business performed based on fluctuations in weather conditions (for example).  

However, keep in mind that this strategy comes with its own set of limitations. Just because you had a spike in sales for one reason or another during the holidays that doesn’t mean it will always happen again next year.  

So, consider taking any new data points with a grain of salt and don’t be surprised if your business changes up its strategy at some point down the road. 

In other words, use historical forecasting to learn what factors influenced your previous years’ numbers. After that, make adjustments that make sense and provide insights. 

Step 4: Develop a forecast based on patterns or trends identified.

After the factors and their relationships are identified and clarified, forecasters can create a causal model of the system which captures the logic and facts of the situation, which is, of course, the foundation of sophisticated forecasting.  

Step 5: Put the forecast into practice.

This final step has you taking the causal models and their informed predictions and fleshing out your business strategies. For instance, if you know how to estimate revenue, you can take your figures and create a revenue projection chart. 


Where Does your Historical Sales Activity Data Live?   

  • Email exchanges   
  • Call logs   
  • Calendar invites   
  • Sale enablement platform   
  • Content Repository 
  • CRM   

What Do You Do When you Don’t Have Historical Data?

Here are eight valuable steps you can use for forecasting when do not have access to historical data: 

1. Consider your financial position: Start with expenses since they are easier to forecast and are adjustable. For example, if you know that your rent is going up next year and it accounts for a quarter of the company’s budget, then make sure to factor in an increase. But leave out any unexpected expenses since those are harder to predict due to their random nature (like earthquakes or fires). 

2. Study the competition: This allows you to determine how competitors are forecasting sales. Most of the time, company results are private, but there are things you can do to get around this. First, study how they are perceived in the market and the historical data they have. Next, study their actions and behavior to pinpoint patterns that can affect your business. 

3. Run scenarios: Several forecasting software applications are now available that can give you “what-if?” scenarios for your business by adding and removing variables and running a simulation. Be sure to run worst case/best case and conservative/aggressive mock-ups with the software. Enter variables such as staffing, price points, marketing & advertising and the number of to see how they change results. 

4. Survey customers: A survey can offer valuable insights into what customers and prospects customer think about your products or services. It will also determine if they are still looking for more and what you can do to serve them better. Taking the results, you can extrapolate future sales or change your strategy to improve sales. 

5. Research external factors. Existing industry trends, data from years previous and other industry leader’s knowledge can be your crystal ball. Studying and consulting with them can help you find out what is going on now and give you a glimpse into what could impact your business sector in the future—given certain economic cycles and market conditions. 

6. Account for everything. That means down to the minutiae since it all adds up and affects your bottom line. When it comes to figures that make up expense, revenue and margin numbers, you need to consider anything from salespeople’s time all the way down to office supplies. Dissect each number separately on the financial statement to find out what each figures mean and how they can affect your business’s future position.  

7. Scan for inefficiencies. The previous step of accounting for everything on financial statements comes into play here. For example, you learn more about how the company is really operating and where it might need a little finesse. Uncover and expose those places where you are not maximizing your spend or your time to forecast a more profitable future.   

8. Incentivize the data entry process. Create and enforce a data entry process for your sellers (incentivize or mandate CRM data entry for all activities). Enforce for at least six months to create a workable data set. You can also find a partner with the ability to connect to all your data sources and gather and categorize all buyer seller activities happening in the different channels. Then map the activities into your CRM system to backfill six month’s to a year’s worth of data.  

How do you know what numbers to put into your sales forecast?

For established companies, you can put historical data such as numbers from your business’s invoices, financial statements or any information that can have relative value to predicting future success for your company. As mentioned, there are ways startups can substitute these numbers from research and from starting a data entry process to collect new data.  

Sales Forecast Examples

Now that we’ve seen the theory, what about some rock-solid examples? Here, we take a look at what these sales forecast methods look like in reality. 

Sales Forecast for a Startup Business

Startups don’t have as much historical data as well established businesses do. But they can still use forecasting methods such as intuitive forecasting, test-market analysis forecasting and multivariable analysis forecasting to get the data to estimate base cases.  

They can also use historical forecasting as long as they have data on theiraverage or estimated growth rate. Then, factor the rate in to reach the predicted sales forecast for the startup business. 

Tim Berry’s Standard Business Plan   

Source: Tim Berry, bpplans.com 

Tim Berry is the founder of Palo Alto Software, and he provides an example of a startup sales forecast on his website. This is a great exercise and unmissable reading for new entrepreneurs dreaming up a new venture. 

Berry describes future entrepreneur “Magda,” who wants to open a café. Through this example, he establishes a base case. From there, he estimates monthly capacity and the sales the café can expect to take in.  

He shows Magda’s month-by-month estimates for the café’s first year and also estimates her direct cost. 

Try it on your own: https://timberry.bplans.com/standard-business-plan-financials-sales-forecast-example/ 

Toptal Research: How to Attractively Engage Sales Teams 

Toptal Research understands that a startup must use more creative sources of information to predict the future. Their article, “What Is Sales Forecasting?” walks you through methods of building your own sales forecast.  

In addition, the visuals and data in the “Sales Forecast 1 Yr” in their article gives you a good idea of what things will look like when you put your sales forecasting efforts together in an attractive package. Through this method, you can attractively forecast sales while informing and engaging your sales teams.  

Ttry it on your own: https://www.toptal.com/finance/tutorials/what-is-sales-forecasting 

Forecasting in Excel 

Source: spreadsheetweb.com 

The linear regression function in Excel is often used by companies for forecasting. Its linear approach makes it unsuitable for data that has seasonality or other cycles. Yet it is useful for causal forecast modeling because of its simplicity. 

Try it on your own: https://www.spreadsheetweb.com/forecasting-in-excel/ 

Here are a few other important tips and ideas for when you don’t have the luxury of experience: 

  • Start simple. When your business is just starting out, it’s easier to forecast expenses than revenues. Therefore, you’ll want to start with estimates for the most common expenses like fixed costs, variable costs and overhead.  
  • Forecast revenue with conservative and aggressive cases. We touched on this with forecasting software earlier. However, different forecasting techniques and tools can be used to do this. Even Excel formulas such as the straight line method can be used to figure the constant growth rate of revenue.  
  • Use key ratios. These are good for sanity checks and strategy development. They include:   
  • Gross margin. The ratio of total direct costs to total revenue. Pay close attention to assumptions that cause the gross margin to go up 10-50 percent. If direct sales expenses and customer service are expensive now, they will likely be expensive for the long haul.  
  • Operating profit margin. The ratio of total operating costs, direct costs and overhead (sans financing costs) to total revenue. Expect positive movement with this check. Also, don’t make the mistake of setting your break-even point too early. 
  • Number of staff per client.  Get this by dividing the number of staff by the total number of clients. The results are especially significant if you are a solopreneur, as all those hats you’ll be wearing as the business takes off will start to get old.    

Final Thoughts

The beauty of sales forecasting is that it can be as complex or as simple as your business requires. You can go with your gut when making projections. Or you can easily break down mountains of data with scores of variables. 

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 possible to customize any of these so that they fit your exact needs. A robust sales enablement software solution can streamline this process. And it can reduce a lot of the guesswork, making everyone’s life a little easier. 

Key Takeaways

The key takeaway here is that sales forecasting is a valuable tool. It 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 your business. Armed with this, you avoid overspending, lost revenue and supply and personnel shortages. 

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

We hope you found this article helpful and can use it to conquer the business world. Want to learn more about sales and marketing? Be sure to subscribe to our blog! 

About Accent Technologies

Accent Technologies is the first and only SaaS company to bring together Sales AI and Content Management in a true Revenue 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 demo to see it in action.   






By Accent Technologies

10th April 2023

Forecasting the Accent Way

Accent Technologies is the first and only SaaS company to bring together Sales AI and Content Management in a true Revenue 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 demo to see it in action.