6 Ways to Create an Effective Sales Forecast

What is sales forecasting?

Sales forecasting is the use of current and previous sales data to predict your team’s sales activity during an upcoming monthly, quarterly, semiannual or annual period. You can use sales forecasts to identify internal or external sales issues and resolve them with enough time remaining to reach sales goals.

Because a sales forecast is a prediction, it relies on current knowledge to preview upcoming changes. As such, the following factors influence sales forecasts:

• Your industry’s recent growth or contraction rates
• The economy in general
• Your competition’s sales of similar items
• Your newest product or service launches
• Fluctuations in your usual operating costs or sales prices
• New regulations restricting your usual operations
• Your company’s marketing activities

Although sales forecasts extrapolate from current data, they are primarily concerned with future conditions. As a result, they constitute an integral part of your company’s larger sales plan and should be taken into account alongside your other expectations for the quarter or year.

How to create a sales forecast

Creating a sales forecast involves basic math and thorough knowledge of your typical sales cycle (although newer companies may lack this information and should conduct research instead). Follow these steps to create a sales forecast:

1. Choose your forecasting method.

Using the past to predict the future is essential to sales forecasting, but not all usage of past data is equal. Try one or more of these three prominent forecasting methods:

• Opportunity stage forecasting. This forecasting method pertains to your sales funnel. For example, if you know that 80 percent of past leads in the fourth stage of your funnel became customers and a current fourth-stage lead is inching toward a $50,000 deal, you can forecast the revenue you earn from this deal as $50,000 x 0.80 = $40,000.
• Historical forecasting. This forecasting method pertains to recent or seasonal data. For example, if you see month-to-month sales of $100,000 for a certain product, you can forecast that same amount for next month. If your company operates seasonally, use the numbers from the same month of the previous year instead of using the previous month’s sales. You can also incorporate growth trends into this method: Using the above example, if your sales typically grow 5 percent each month, you should forecast $100,000 + (0.05 x $100,000) = $105,000.
• Length-of-cycle forecasting. This method pertains to the period of time over which your sales funnel progresses. For example, if your sales funnel usually spans one month and you identify a lead with whom your team has been negotiating for three weeks, the sale has a likelihood of three to four weeks = 75 percent. If the sale would result in $100,000 in revenue, you can forecast $100,000 x 0.75 = $75,000 in sales.

Note that each of these methods has advantages and disadvantages regarding data accuracy, external factors and other considerations. That said, they are more straightforward and reliable (and less technical) than other methods, so they may still be best for your sales forecasts.

2. Identify what you’re selling.

This step may seem obvious, but a thorough sales forecast requires you to identify every item you’re selling. Excluding an item that you sell or including an item you’re no longer producing can lead to inaccurate sales forecasts.

3. Determine your sales prices and quantities.

Once you know what you’re selling, figure out your sales prices and the number of sales that you estimate will occur. The forecasting methods explained in step one can be used to quantify your sales. For example, the sale mentioned in the length-of-cycle example can be seen as a sale of 0.75 units.

4. Multiply your prices and quantities.

Likewise, the $100,000 x 0.75 operation in the above length-of-cycle example shows how to multiply your prices and quantities. This step looks a bit different if you’re using historical forecasting; in that case, multiply your previous period’s sale quantity by its number of products sold.

5. Factor in your costs.

Without taking sales costs into consideration, you can’t get a meaningful picture of your profit margins. That’s why you should also multiply the cost of making each sale by the number of sales.

For example, let’s say you use the historical forecasting method and predict sales for one month of $500,000 based on the previous month’s sales of 500 units at $1,000. Then, if each unit costs $100 to sell, your sales costs are 500 x $100 = $50,000. This means your profit forecast is $500,000 – $50,000 = $450,000.

6. Consider your inventory.

Now that you’ve seen the basic math of sales forecasting, you might feel overwhelmed. Maybe you’re wondering whether you really have to calculate these numbers for all of your items. The answer is usually yes, though if your inventory is large and diverse, you may need to condense revenues and costs into larger categories, as shown in this sales forecast table.

Why is sales forecasting important?

Sales forecasting gives you the information you need to adjust your company’s upcoming sales strategies and budget. An accurate forecast can point to gaps in your sales team’s methodology; areas where sales costs can be cut; or increases, decreases and trends in your sales. It does so while giving you more than enough time to make these adjustments and remain on track to meet your sales goals.

In addition, a sales forecast gives your sales team a target to strive toward. In sales, staying motivated is critical, and if your sales forecast sets a target, your salespeople will keep their eye on it. That’s especially true if you tie some sort of incentive to beating the forecast for a given period of time, such as team bonuses or boosted commissions for sales that exceed predictions.

What are some key sales forecasting challenges?

Here are some factors that may complicate your sales forecast:

• Sales history. Creating an accurate sales forecast requires thorough data on your recent company sales. This can present a substantial challenge for newer companies with little or no sales history. Without much past data to go on, several forecast influences — operating costs, sales prices, marketing activities — don’t yet exist for your company.
• Research. If your company doesn’t have an extensive sales history, you can patch this information gap somewhat via thorough research into your competitors, target market, industry and more. If your company does have an extensive sales history, this research remains important, though perhaps less so. In both cases, the time and money that go into research can pose sales forecasting challenges.
• Data accuracy. Sales forecasting assumes correct data sets, but in reality, human error — even with the use of customer relationship management (CRM) software — remains possible. When sales reps record inaccurate data in your CRM program, an incorrect sales forecast — and therefore poor planning — can result.
• Superficiality. In some cases, sales data only showcases numbers without explaining the reasoning behind fluctuations. Without these explanations, predicting future customer behavior can be tougher, which affects the accuracy of your sales forecast. Nearly every industry has a slow or busy period. A sales forecast for a busy period may be inaccurate if it’s based on a slow period, and even the most diligent sales executives can sometimes miss this discrepancy.
• Sales funnel inconsistency. Not only can two companies’ sales funnels look completely different, but the funnels that two sales reps within the same company use can also vary. Work proactively to prevent this internal discrepancy, as terminology gaps or unstandardized sales processes can result in misleading information and in turn skew sales forecasts.

What to do if you fall short of your sales forecast

Sales forecasts are predictive tools, and sometimes your team may fall short of predictions. If that happens, you should do two things: Analyze your forecasting methodology and review operations and market conditions for the period during which you missed the forecast.

First, take a closer look at your sales forecast and how you developed it. If it was grounded in lofty ambition rather than historical sales data, that may be a clear indicator that it wasn’t realistic. For example, if your team has historically brought in between $100,000 and $200,000 in revenue per quarter, suddenly expecting them to generate $500,000 without any demonstrable changes in operations is setting your team up to fail.

Similarly, if the sales forecast was built on a dependency that wasn’t met, that could explain the failure. For example, if your forecast was built on the premise that your marketing team would generate 20 percent more leads than it did in the previous period and the team only generated 5 percent more leads, it’s unlikely the resulting sales forecast could be met.

If your forecasting methodology appears sound — that is, it’s grounded in historical sales data and realistic assumptions about the upcoming period — take a look at market conditions. Has the economic landscape changed? For example, record inflation between 2021 and 2023 saw declines in consumer spending and reduced marketing budgets. Sales forecasts made before inflation impacted the broader economy are likely to miss the mark. In a case like this, it’s important to revise future sales forecasts once you understand why previous ones were not met. 

Sales forecasting supports financial planning and sets sales targets

Sales forecasting is important not only for benchmarking a successful quarter or year for your sales team, but also giving them a clear goal or target to surpass. While meeting a sales forecast is an important goal in itself — especially when that forecast is based on historical sales data and expected lead generation — eclipsing it can be a mark of great success. Sales forecasting is not only an important financial planning tool, it’s also a great motivator to get more out of your sales team.

Jacob Bierer-Nielsen contributed to this article.