What are the different elements of sales forecasting?
Without regular monitoring of market developments, sales generally struggle to take off. As a result, companies very rarely break even in their first few years of existence. In many cases, this is due to the lack of a sales plan. Thus, sales forecasting is the answer to any business strategy. It consists of a number of elements that will enable a company to achieve its financial goals, improve profitability and increase turnover. While data is an intrinsic part of a sales forecast, it is not the only component. A sales forecast also incorporates CRM software, sales procedures, sales quotas and targets and a sales pipeline.
Data at the heart of sales and process forecasting
Without data to analyse at a point of sale, machine modelling or CRM software will not be available, leaving business managers without interpretable statistics to build an effective sales plan and make accurate predictions. Thus, data is necessary for successful sales forecasting. But only if you have good data. In general, the company must ensure that it has not only historical internal data, especially on their customers, but also external contextual data.
The former refers to information known and more or less controlled by the organisation making the prediction. In fact, they are generally already part of its database. We also speak of endogenous variables. They are, for example, the location of a sales outlet, the sales force, the price of a product, the sales promotion mechanism, etc. However, the challenge here will be to successfully extract only the data that is relevant to the intended purpose. With a self-learning technology such as machine learning, this is easier to do.
Conversely, external contextual data or "exogenous variables" are unknown to the organisation and it has no choice but to accept them. However, to reduce the gap between forecasts and actual flows, they must be better understood. This is why most forecasters and other sales forecasting experts are interested in them. The most frequently used data are: seasonality, density of competition around a point of sale, customer behaviour, household purchasing power, local events, legislation, etc.
CRM software for accurate sales data
While it is not impossible, conducting a sales forecast without CRM software is difficult. This is because CRM software serves as a database for tracking opportunities. It is therefore essential for a company to use it for sales forecasting to derive precise and accurate data on customer behaviour, which is not necessarily guaranteed by manually prepared reports and calculations.
To carry out the exercise of sales forecasting, it is important to choose software that will be able to automate the process and produce performance reports. CRM software should also be able to calculate sales funnel conversion rates and anticipate cash flow requirements.
However, such software does not have the capacity to handle a large data flow. It is recommended that companies using Big Data use continuous learning technology such as machine learning to model customer behaviour. In concrete terms, the machine will generate predictions after learning (supervised or unsupervised) based on data partitioning (data clustering) or discriminant analysis.
Based on these predictions, the company will be able to anticipate product purchases by different points of sale in the retail sector, such as in mass distribution.
Sales procedures to define the basis for a sales forecast
Any commercial activity must base its marketing strategy on the sales process. These are the different stages a prospect goes through before becoming a customer. With such a model, the prospecting process is facilitated and the probability of customer conversion will tend to increase. It is usually sufficient for a salesperson to enter all sales-related information into CRM software for managers to have reliable data to make fairly accurate predictions about future sales.An 18% increase in revenue is even observed in companies that have standardised sales procedures. This is not the case for organisations that do not have a standardised sales process or where the process is not visible. The information that appears in a sales procedure covers:
- customer awareness and conversion time;
- elements from the sales funnel;
- retention rate;
- average cost of each product or service.
Sales quotas and targets as a reference for a sales forecast
The performance of sales forecasting can only be evaluated against measurable objectives. Thus, apart from sales procedures, a CRM software should contain information about the company's quotas and sales targets. These references will be used to determine whether there is any correlation between the predictions and the expectations that were formulated at the beginning of the process.If the answer is no, the company still has the opportunity to adjust its marketing strategy so that the gap between actual flows and predictions is significantly reduced. In doing so, it is assured of maximising its revenue on certain products and increasing its market share.
The sales pipeline to manage the sales forecast
The sales pipeline is often confused with sales forecasting. However, these two concepts have completely different objectives. The sales pipeline or "sales pipe" is actually a system that sales representatives and managers use to drive a sales strategy. It therefore serves as the basis for the sales forecast. The sales forecast will be able to draw on all the information it needs to predict which opportunities are likely to be successful in a given period based on information gathered by the sales team.Similarly, using the data in the sales pipeline, salespeople can see how close they are to their targets so they can anticipate threats and plan the right response. For example, if the forecast indicates that the sales team's quota is not being met, they are called upon to completely rethink their approach to customers. Company managers are also called upon to analyse the situation and to suggest to their teams ways of improving their approach to customers.
Ultimately, sales forecasting helps to overcome the difficulties that many companies face in their activities: rising product stocks, inappropriate assortment, abusive promotions, unsuitable pricing, etc. No sector is immune to this. No business sector is really spared from these hazards. However, for the results to be achieved, the sales forecasting process must be carried out in the right way.
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