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One of the main challenges faced by business leaders is a How to estimate sales of a new product effectively.
Although the absence of historical information may make it seem impossible, are there alternatives that provide us with an objective initial vision to be able to estimate potential sales and thus take advantage of market opportunities from the start.
In this article we'll show you everything you need to know about sales forecasting and how to project sales of a new product through different methods and with a clear step by step that will help you achieve it successfully.
When we talk about sales forecast or projection, we refer to an early estimate of future sales that a company will obtain in a specific period.
This type of analysis is based on various sources such as historical sales data, market trends, consumer behavior and other factors relevant to forecasting sales.
This is a crucial element for a company's strategic planning, as well as for decision-making. In fact, the sales forecast provides fundamental data for resource allocation, inventory management, pricing and even the financial planning of the business.
Therefore, it will be key when identifying potential opportunities or challenges, in order to anticipate and act strategically in the face of changes in the market.
There are a number of key elements that are part of the sales forecast or projection:
Depending on the needs of your company, or the type of information you want to obtain, it is possible to choose any of the following types of sales projection:
Remember that platforms such as Datup allow you predict demand and manage your inventories with an average of +95% accuracy in just 5 weeks.
Teams using Datup reduce forecasting errors by 15% to 30% and reduce their inventories by 5% to 25%. This is possible because Datup uses Artificial Intelligence to process internal and external information, suggesting scenarios for better decision-making.
It should be noted that there are different sales projection methods and you must select the suitable method according to the needs of your business. For that, we will detail all the alternatives below.
Time Series Analysis is a sales forecasting method that examines past patterns in sales data to identify trends, cycles, and seasonalities. It's ideal if your company has a stable sales history, allowing you to predict future fluctuations and plan accordingly.
By implementing this analysis method, you'll be able to identify how sales have changed over time, providing a solid basis for future forecasts.
Qualitative methods are based on expert judgments, surveys and focus groups to understand consumer expectations. Using this alternative, your company can gain valuable insights into future demand, especially useful for new products or in volatile markets.
In addition, something that is very interesting about these is that they capture subjective factors that can influence demand.
Another prominent method among company leaders, for sales forecasting, is linear regression, with which future sales are predicted using one or different independent variables such as pricing and advertising.
In its simple form, it analyzes the impact of a single variable, while multiple regression considers multiple factors, providing a more detailed analysis of how different elements affect sales.
TAM is a method that Average sales in recent years to forecast the future, assuming that demand remains relatively constant.
Although this is an effective method for visualizing long-term trends, may not capture sudden changes in the market or economy, limiting its applicability in volatile environments.
MMC are a sales projection technique that Calculate the average sales for recent periods, adjusting to detect seasonal patterns.
This method can be particularly useful if your company needs to adjust forecasts to seasonal fluctuations, although its accuracy may be affected by random variations in sales data.
This is a sales forecasting method that breaks down data into trend, seasonality and noise components to analyze and forecast each one separately.
It's generally a great sales forecasting technique if your business has clear seasonal patterns, allowing for precise adjustments in short-term forecasts based on identified seasonality.
Exponential smoothing consists of applying a weighted average to historical sales data, placing greater emphasis on the most recent data.
It is considered a simple method to implement for any company, and is useful for forecasting short-term sales, although its simplicity may not capture complexities in larger sales patterns.
Both machine learning and Artificial Intelligence for sales forecasting are considered revolutionary techniques that allow your company to analyze large data sets and detect complex patterns not visible to the human eye.
In fact, making use of these technologies in your business can help you to project future demand with high precision, considering not only historical trends but also external factors affecting the market, as are political and economic changes.
In addition, the implementation of advanced algorithms, including neural networks, allows companies to dynamically adapt to market changes, thus optimizing their production and marketing strategies based on an accurate and updated sales projection.
After learning about each of the sales projection methods that we presented above, it's time to share with you how you can apply any of them to estimate sales of a new product. To this end, we have prepared a step by step that will be of great help to you in this process.
In this first stage, you must do a preliminary data collection, where you will rely on a market analysis and in the identification of counterpart products.
This approach allows historical databases to be used to establish a starting point for sales projections.
By applying the method of identifying products with similar attributes, your company can apply past demand patterns to new releases, providing a quantitative basis for initial estimates. To do this, the following must be taken into account:
After collecting this information, your company will be able to make use of artificial intelligence (AI) models, where historical data are the basis for learning the system.
The advantage of AI models lies in their ability to adapt and learn from new data as it is collected.
When you already have a selected and customized AI platform, you can start the training with historical sales data for counterpart products and validation tests.
Although initially based on information from homologous products to make projections, these models evolve and adjust their predictions as they take data from the new product. This continuous learning allows models to provide increasingly accurate and less subjective forecasts, based on real market behavior and not only on assumptions or qualitative estimates.
This method, in which we make use of technology, not only takes advantage of existing data to create solid initial estimates, but also benefits from the ability to adapt and learn from AI models to generate projections based on real and current data.
In this way, companies can overcome the challenge of a lack of historical data and make more objective and informed sales projections. This will require an analysis of the results and constant optimization of the model.
In the case of a new company with no historical data, facing the challenge of making sales projections can seem daunting, especially without the possibility of directly exploiting artificial intelligence models, which rely heavily on previous data patterns to make accurate predictions.
However, there are effective methodologies and strategies that your business can use to estimate future demand and prepare a solid foundation for growth, even without AI. Here we share with you the steps you must follow to achieve this successfully.
Your business must carry out an in-depth analysis of the market to identify its target audience, understand their needs and evaluate the size and potential of the market. This step is crucial to estimate the potential demand for your product or service, and then to make a sales projection.
Study your direct and indirect competitors to understand their strategies, strengths and weaknesses. This will help you identify untapped market opportunities and to position your product effectively.
Use surveys and focus groups to gather information about the willingness to pay of your potential customers and their preferences. This data will provide you with valuable insights to establish a pricing and product strategy suitable for your business, according to your target audience.
Now it will be time for incorporate expert judgments, we recommend that you include opinions from industry veterans and consultants, to get a broader view of the viability and expected demand for your product or service.
Observe trends in the industry or sector of your business, as well as general economic data to adjust your demand expectations. Factors such as changes in legislation, consumer trends and technological developments can significantly influence future demand.
As we've seen throughout this article, making sales forecasts is essential for your company, and here's everything you need to know about these projections.
In the case of the estimated sales of a new product, we have demonstrated that, despite the absence of historical data, there are alternatives that provide an initial objective view to calculate potential sales and capitalize on market opportunities from the start.
We also explore sales forecasting techniques and provide you with a step-by-step process that will help you successfully project sales of new products without having to be afraid of uncertainty.
You have already seen that the use of Artificial Intelligence will take your sales projection to the next level, Dare to know Datup, the ultimate solution for accurate forecasts
