How to estimate and plan the future sales of a product?
In order to write a convincing commercial offer and to deploy its marketing strategy, every company must forecast its sales. These forecasts must be regularly updated as part of a business plan. The more the company improves its sales forecasts, the more it will have quality information on which to base its management decisions.
Given the many variables that can influence sales forecasting, this can be a difficult task. The forecasting method depends primarily on the current presence of the product in the market. The sales team will need to forecast the sales volume of an existing product, a similar product, or an entirely new product on the market.
Forecasting sales of a known product on the market
What is the product for which we want to estimate sales?
On the one hand, the company can forecast the sales of a product it is already selling, in order to evaluate its profitability over the coming period. If there is a drop in demand and therefore in sales volume, the company can decide to stop production in order to avoid costly investments. Conversely, if sales increase, the company can anticipate the amount of resources needed to meet future demand. If sales stabilize, it is the importance of the product in question in the company's strategy that will condition the decision to stop or continue production.
On the other hand, the sales forecast may concern a product with similar characteristics to another product already on the market (same sector of activity, same quality level, same price level, same targeted customers). The forecasted turnover linked to the sales of the product in question will be more or less the same as that of the equivalent product, whether it is the company's own product or that of a competitor.
Make forecasting assumptions based on historical data
In order to forecast product sales, companies can rely on the analysis of existing products to make assumptions. Since the product has already been introduced to the market or is comparable to another product, the company has historical data on which to base an estimate of future sales volume.
Among the data that may be of interest to the company in developing its forecast is the product's sales cycle. The forecasting team then analyzes the effectiveness of the sales prospecting, lead qualification and customer relationship management processes. Was the conversion rate high enough that they could afford to do the same for the product they want to sell in the future? Do you need to change your process to boost sales?
The sales of a product are also influenced by the performance of competitors. This is why it is important for companies to observe their competitors (pricing policies, average sales figures, etc.) in order to gauge the assumptions of their business plan and deduce the sales potential of their product.
Another factor that influences the sales figure of a product is the production capacity of the company. Given the difficulty of improving this capacity, the forecast must be largely anticipated if the company wishes to adapt its processes. In most cases, the production capacity observed at the time of the forecast is the one that must be taken into account for future sales.
Finally, the analysis of the customer portfolio gives an approximate idea of the future demand for a product. The company should study the level of sales for each customer in previous years, the average gain or loss of customers each year, and the rate of purchase of the existing or similar product.
Verify forecasting assumptions by performing a calculation
The best way for the company to verify its assumptions and ensure the rationality of the forecasts made is to make objective and precise calculations. For this purpose, many calculation methods are available to the forecasting team, including:
- the method of extreme points or average points;
- the linear regression method with the equation of the least squares line;
- the moving average method;
- the exponential smoothing method;
- calculation of seasonal coefficients by month or by quarter.
Forecasting sales of a totally new product
When forecasting sales for a product that is new to the market, the sales team cannot base its revenue estimates on historical data. The lack of historical data forces companies to operate in a different way, including conducting market research.
Market research at the heart of sales forecastingWithin the framework of a sales forecast, the market study allows a company to estimate the sales potential of its new product, and to orientate its global strategy to try to increase its market share by differentiating itself from its competitors. This market study is all the more complex as the proposed product is innovative.
A quantitative and qualitative market study consists in analyzing:
- the market (size, trends, opportunities, competitors, customers, etc.)
- the demand (number of customers, demand segmentation criteria, etc.);
- the offer (competitors' business plan, market leaders, etc.);
- the environment (political, economic, legal, social, ecological, technological).
In most cases, this market study is entrusted to a service provider: the company pays for the data collection used for the study. If the company decides to do it internally, the marketing department will do it.
The importance of a marketing strategy adapted to the forecastSales strategy and marketing strategy are inseparable in a company's business plan. To successfully market its product and reach its sales objectives, the company must develop a marketing plan.
The mastery of the marketing mix, characteristic of the offer proposed by the company, is one of the success factors of the marketing plan. We usually speak of the 4Ps of the marketing mix, for:
- the product policy (product);
- the price policy (price);
- the distribution policy (place);
- the communication policy (promotion).
Accurate sales forecasts combined with a coherent marketing plan are a prerequisite for the sustainability of a company's activity. Today, many management tools (predictive models, CRM software, Excel, etc.) allow to automate the sales forecasting process.
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