Sales forecasting using the sales cycles methodEssential for the performance and profitability of a company, sales forecasting allows it to have a global vision of its activity, both past and future, by taking into account its context (competition, strategic factors, changes in customer consumption habits, etc.).
Setting up a sales forecast is crucial, but choosing the most appropriate method for the company's operation and sector is just as important.
Indeed, there are different sales forecasting methods, all based on the analysis of different information: sales cycles, intuition, historical data, sales pipeline or the analysis of several variables.
The most popular method, especially in B2B sales, is the one based on sales cycles. It is based on the opportunities in each sales cycle and the age of each opportunity. Not clear on all of this? That's normal, and we'll explain everything about this method in the following.
Focus on the different sales cyclesDefining or identifying the different sales cycles in effect in the company is necessary to develop a sales forecasting plan according to the method that interests us here.
In addition, the implementation of a formalized sales process is essential for the efficiency of the sales and marketing teams. According to a study by Havard Business Review, companies that have clearly established their sales cycles experience a significant increase in sales (+18%).
Why do they do this? Because such a process allows for a precise follow-up of the customer's buying path and offers the possibility to set up adapted and/or personalized actions and to anticipate the necessary resources for each cycle. It is a sort of roadmap for the sales team, guiding them from customer acquisition to the conclusion of the sale.
Of course, the different stages of the sales cycle depend on the company's line of business, its products or services and its marketing or sales methods. A sales process traditionally includes 6 phases, which must therefore be adjusted to each company.
- Prospecting allows you to identify and establish contact with prospects (potential customers), such as telephone prospecting, e-mailing, participation in a trade show, etc. The prospecting cycle must create a constant and regular flow of opportunities.
- Qualification must allow the company to define if the prospect is really interested in the company and/or its offer and if they are a potential customer.
- The presentation, demonstration or sales meeting aims to demonstrate to the qualified prospect the advantages that the offer can bring them. The idea is to move from the simple interest of the potential customer to an intention to act (to think about the offer, to compare it to the competition, to buy the product, etc.).
- The proposal or argumentation is the phase that allows us to respond to the prospect's objections or fears in order to convince them that the offer is the right solution for them.
- The conclusion or purchase aims to negotiate the terms or price of the offer (if necessary) in order to obtain acceptance and thus transform the prospect into a customer.
- Loyalty corresponds to all the actions to be implemented to satisfy the customer during and after their purchase and, above all, to make them a loyal customer and an ambassador for the company (recommending it to others).
When developing sales cycles, the notion of temporality is also important. Defining the duration of the sales process and of each cycle makes it possible to set up a strategic plan over a more or less long term as well as adapted actions at the right time. A demonstration carried out prematurely in the sales process, when the customer is not yet "ready", will not have the desired effect on the buying process.
Application of the sales forecasting method according to cyclesThe forecasting method based on the sales process allows us to assign a probability of sale conclusion to each of the previously listed cycles.
To gain in reliability, the method also relies on the age of the opportunities to evaluate their probabilities, because, as we have seen, the notion of time is to be taken into account (maturation of the idea in the prospect). Thus, the probabilities increase as the process goes on, for example:
- 5% probability of prospecting;
- 20% to qualification;
- 50% on demonstration;
- 75% at proposal;
- 100% at purchase (closing).
The determination of the seniority and probability rate according to the cycle is calculated from the sales quotas achieved by the sales team, for example the average sales per month (or quarter, year, etc., depending on the established sales process) or the average conversion of the prospect into a customer. The periodicity of sales forecasts must therefore also take into account the length of the sales cycle specific to the company or its sector of activity.
It is from these variables that it will be possible to make a sales forecast for one or more products for a given period or a specific marketing action.
For example, let's say we want to make a sales forecast for a product sold at 1,000 euros. We need to determine the weighted values for each cycle. To do this, we simply multiply the potential (or actual) value by the previously determined probabilities of conclusion:
- probability of prospecting 5% multiplied by 1,000 euros, 50 euros;
- 20% probability of qualification multiplied by 1,000 euros, 200 euros;
- 50% probability of demonstration multiplied by 1,000 euros, 500 euros;
- proposal probability of 75% multiplied by 1,000 Euros, 750 Euros;
- 100% probability of purchase multiplied by 1,000 Euros, 1,000 Euros.
Of course, in order to develop a sales forecast for the company's entire offer, this process must be carried out for all the products or services it offers.
The sales process-based sales forecasting method is quite simple to implement, which explains its popularity. However, since it is essentially based on the analysis of historical data, this method does not take into account future changes (market, context, consumption habits, etc.) that have an impact on sales.
However, thanks to predictive models developed from artificial intelligence (algorithms and machine learning), it is possible to weight the results by integrating additional analysis factors, in particular changes, as well as the resources available in the company. This is the multivariate sales forecasting method.
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