Sales forecasting is the process of predicting the company’s revenue within a specific period in the future. Sales forecasts estimate the number of products the company will sell and the time period needed to do it.
In the article, we explain why sales forecasting is important and highlight its benefits. We provide the factors affecting sales forecasting and outline its methods and examples.
Why is sales forecasting important?
Companies with accurate forecasts are more likely to grow their revenue over the previous year and two times more likely to become the top company in their field. Such inspiring statistics show the importance of sales prospecting and its direct influence on the companies’ success. We explain this process is so powerful below.
A sales forecast is a benchmark that helps make more conscious business decisions. It allows businesses to predict their short-term and long-term revenue, and plan their investments accordingly. Companies can estimate their budget for a certain period and be sure that they will have enough costs.
Moreover, sales forecasting helps plan the usage of resources better. Business owners can make decisions about shipping the raw materials, hiring staff, and spending on marketing based on the forecasts. It allows them to optimize companies’ decisions according to the current situation in the market.
The sales forecasting process is an obligatory part of work in successful companies. Read about its benefits in the next section.
Benefits of Sales Forecasting
Some junior marketers may neglect sales forecasting and think this step is challenging and unimportant. However, it is not so. Below we provide the main benefits of sales forecasting and explain why this process is necessary.
- It helps estimate future revenue and plan the budget. Smart sales forecasting allows your company to develop a competitive strategy based on this information. Knowledge of the approximate future income lets you optimize spending, feel more confident in making investments, and avoid mistakes in budget planning.
- It shows the company’s needs in staff and resources. Sales forecast helps estimate the number of employees and raw materials your brand will need to work successfully. Forecasting allows you to ensure that the business has all the necessary resources and avoid problems with inaccurate management.
- It helps develop a well-defined marketing strategy. Sometimes revenue predictions may be dissatisfying, and it is the reason to consider changes in your promotions. Based on the current forecast, you can identify the roadblocks in the customer journey and improve them to close sales faster and smoother.
- It represents possible problems with your company’s health. By predicting future revenue for a certain period, you can find out some seasonal problems with demand. Sales prospecting is a great way to discover these possible issues and make necessary changes before directly affecting your revenue.
- It helps companies grow faster. Understanding brands’ future earnings is necessary for business owners to make informed decisions. You can use sales forecasts as benchmarks to focus on the most profitable products and audiences. Such a strategy leads to higher flexibility, increased revenue, and faster company growth.
Now you understand why accurate forecasts play an important role in business development. Continue reading to discover the factors that affect sales forecasting and their peculiarities.
4 Factors Affecting Sales Forecasting
Below we provide the most critical factors that affect sales forecasting accuracy you should consider.
1. Business conditions
These factors include the general economic and legislative state of the country. People tend to be more confident in their purchases and spend more money if the national economy is strong. Moreover, general trends for inflation or deflation influence consumers behavior and, consequently, sales forecasts. You should also pay attention to the general price levels and people’s income while predicting your company’s revenue.
One more factor is new laws and political changes. They can increase or decrease the level of your sales. Take into consideration the import and export policy if you use materials from abroad. Remember that we can not control general business conditions, so your company should be flexible and react to all these factors while developing a strategy and predicting future sales.
2. Industry changes
These factors include changes in market share, product innovations, new companies in the industry, and trends in product promotion. For example, if your competitors raise prices, some clients can switch the brand and start buying from your company, increasing predicted revenue. On the other hand, if your competitor suggests an innovative product, you may lose some clients.
Marketers should pay attention to the trends in the industry and change their strategies accordingly. It is important to improve your products constantly. Increasing average deal size with upselling and cross-selling can positively influence your sales.
3. Internal conditions
They include pricing policy, marketing strategy, number of employees, product quality, financial distribution, etc. Changes in these factors can increase or decrease sales and, consequently, affect the forecast of your future revenue. The good thing is that we can influence internal conditions directly.
For example, if you hire a new sales manager, the number of deals can also increase. On the other hand, the company may lose revenue if there are not enough workers in a certain department. To make an accurate forecast, you should consider all possible changes in the company and predict sales based on the existing development strategy.
4. Sociological conditions
Sociological factors include all the demographic information related to your clients. While making a sales forecast, you should take into consideration the size of the population, the level of your clients’ education, social status, personal income, etc. Public moods can sometimes be unpredictable, but they influence sales too.
One more important factor is seasonal changes in demand. For example, according to Cloudways, holiday shopping made up 19.5% of total annual income in retail. Moreover, even the weather can influence sales of such products as clothes, travel vouchers, coffee to go, etc.
Some of these factors are easy to predict, but some can be unexpected. You might be confused about doing an accurate forecast with so many variables. In the next section, we provide the most effective sales forecasting methods and techniques and explain how to use them with examples.
7 Sales Forecasting Methods and Examples
Continue reading to discover 7 sales forecasting methods to make your sales predictions as accurate as possible.
1. Intuitive forecasting
The essence of this method is that business owners ask their sales managers to predict the company’s future income based on their feelings and subjective opinions. Intuitive forecasting is rarely accurate because many employees tend to be optimistic and can not pay attention to all possible affecting factors. Moreover, such predictions are difficult to scale. However, many business owners use intuitive forecasting when they only found their company and do not have enough resources to make more complex forecasts.
Imagine that your company has 2 managers and you ask them to forecast your sales for the next year. One manager predicts 2000$ of revenue, the other one — 3000$. The arithmetic mean of these two predictions is 2500$ a year — it will be the intuitive forecast for your company.
2. Historical forecasting
This method is a quick way to predict future income based on historical data. For example, if you want to forecast sales for the first quarter, your manager may look at the results of the previous years and assume that demand will be the same or a little higher. The disadvantage of such a method is that it does not consider changes in the market and your own sales pipeline.
For instance, your revenue in spring 2021 was 1400$. You can assume that in spring 2022, your company will earn 1400$ too. If your sales are constantly increasing, you can add historical growth. Imagine that you grow 10% a year, so in spring 2022, your revenue may be 1400 + 1400*0.1 = 1540$.
3. Forecasting based on the length of the sales cycle
Marketers use this method to predict future revenue based on the time needed for the clients to make a purchase. You can use it if your company has a limited number of potential clients. Moreover, if there are a few different pipelines for different products, you can separate leads and predict the total company’s revenue. The advantage of this method is that it is completely objective and can be scaled. The disadvantage is that continuous new data tracking is required to make accurate forecasts.
For example, if the approximate amount of time your clients need to make a purchase is 2 months and four leads have been considering for 1 month, there is a 50% possibility that they will buy your product. Imagine that you have only these four leads and the cost of the purchase is 5000$, so your sales forecast is 10000$. ((4*5000$)*0.5)
4. Opportunity stage forecasting
This method is similar to the previous one, but it is based on the lead’s stage in the buying process. You can divide your sales cycle into several parts and assign the percentage of the probability that the customer will make a purchase to them. Then you multiply the potential cost of each purchase in the period of purchase by the likelihood of its closing and sum up all the results.
The advantage of this method is that it is rather objective and easy to calculate. On the other hand, if there are any changes to your strategy, the forecast will be inaccurate. Moreover, it can be based only on the limited number of potential clients.
For instance, your company has two potential clients. One of them is in the first stage and 30% likely to purchase the products for 2000$. The second one is in the last stage and is 80% likely to purchase for 4000$. The sales forecast will be 3800$ (2000*0.3 + 4000*0.8).
5. Portfolio forecasting
This method combines all the previous ones. To use portfolio forecasting, marketers take into consideration the historical data, the length of the sales cycle, the number of leads, the possibility of closing each deal, and the sales representatives' intuitive predictions. A combination of all these factors shows a more holistic picture of the company’s sales. On the other hand, this method requires lots of data that is rather difficult to combine accurately.
Imagine that the company sold products for 6000$ during the same quarter in the previous year, which is a historical forecast. Now there are four clients that may buy products for 2500$ each that are 50% likely to make a purchase. Consequently, the opportunity forecast is 5000$. At the same time, sales managers predict 7000$ in revenue. Based on these numbers the simplified portfolio forecast is 5000$ ((6000+5000+7000) / 3).
6. Test-market analysis forecasting
Marketers use this method to predict the success of the products based on pre-launch testing. Usually, companies suggest their new goods to the limited groups of potential clients divided into a few segments. According to the market response, businesses can predict the approximate demand and the number of products sold within a set period.
Test-market analysis results are easy to scale. This method allows you to increase consumers’ brand awareness and attract their attention to your product launch. However, this method does not take into consideration market trends and internal factors, such as pricing policy changes. It is also very important to keep in mind the period when the customer needs to repeat the purchase.
For example, you sold 100 products that cost 5$ each to 300 people during a pre-launch. Your total revenue is 500$. The total number of your target audience in the country is 30 000 consumers, which is 100 times more than the number of consumers in pre-launch testing. Consequently, your revenue after the launch will increase 100 times, and your company will earn 50 000$ before the consumers need to repurchase.
7. Multivariable analysis forecasting
This is the most accurate but the most complex method for sales forecasting. It requires lots of historical data, sales cycle length, test-market analysis statistics, the possibility of closing the deals at all customer journey stages, individual sales managers’ performance during the stated period, etc. Companies use analytical tools and different machine learning algorithms to reach the best results in revenue predictions.
The advantage is that multivariable analysis forecasting is reliable. AI calculates all the forecasts, so marketers do not need to deal with lots of numbers. However, tools for sales forecasting may be rather expensive for small businesses. To get accurate forecasts, you need to update data regularly. Moreover, it is sometimes difficult to understand the principles used by AI to make sales predictions.
Congrats, now you know what sales forecasting is and why it is important. You understand how to use the prediction methods and what factors affect your forecasts.
Last Updated: 02.07.2024
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