By Andre Felix Bakehe

Growth through improved results is the essence of any commercial enterprise of products or services. A company’s result is not only the result of a function with several variables, but also the culmination of a certain number of strategies, innovations, technologies, approaches, or even entrepreneurial methods.
One of the purposes of data science is to be a support tool for decision-making, and therefore more specifically for improving the quality of decisions, with the corollary of obtaining better performance. Data science is also the antechamber of Artificial Intelligence and therefore of the use of IT in the quest for business performance. In this dual capacity, data science represents one of the transversal approaches favored by a certain number of companies for the management and optimization of their internal and external activities.
By applying it in particular to the management of customer relations, data science is of a certain contribution, especially when it can count on a company of which one of the strategic cardinal points lies in the knowledge of its customers. Knowing your customers and using data science is therefore in itself an approach leading to the optimization and improvement of business results.

What does knowing your customers mean to a business?

A company’s customers are the end recipients, the very raison d’être of a company’s activity. Knowing customers is an ongoing activity through which a company builds its knowledge of the intrinsic characteristics of its customers. Said characteristics may be socio-demographic and economic types, relate to preferences and expectations, consumption habits or consist of psychological profiles among others.
In several respects and by way of example, knowing the name, age, sex, profession, residential address, marital status and other family information helps to approach the knowledge of its customers on the socio-economic level. demographic. Information relating to income, net worth, level of indebtedness and others are those allowing a better knowledge of the customers on the economic level.

Why should a company know its customers better?

Providing its customers with the products and services that are the subject of their qualitative expectations, at the right time and in the desired quantities is an ideal situation aimed at by any company. This is also one of the reasons for the necessary knowledge of its customers. The possibility of being able to send various communications as well as personalized and targeted offers to its customers is also an interesting prospect. One approach is to let the customer-product encounter take place on the initiative of the customer alone, another is to “provoke” the purchasing decision. This second approach is made much more efficient thanks to data science based in particular on a good knowledge of customers.

How do you go about getting to know your customers?

Due to the quantity and dynamic nature of the data that are characteristic of them, knowing its customers requires a company to have infrastructures for the collection and continuous updating of information about its customers. Apart from the storage infrastructures of said data, such as databases, several upstream and downstream strategies can be implemented within the framework of knowing its customers.
In terms of upstream strategies for collecting data on its customers, there is a good place to encourage them to enroll in loyalty programs, or to create customer accounts. A downstream strategy will however consist of the systematic collection of data resulting from any act of purchase, or even purchase intention/plan (baskets made on an e-commerce site) for example.

How will knowing your customers improve business results?

Data science is the tool par excellence for transforming data derived from the knowledge that a company has of its customers, into real operational results, such as increased turnover or improvement in the result of operations. More specifically and by way of example, the analysis of the market basket is one of the first added values resulting from data science based on customer knowledge.
Market basket analysis can increase sales and customer satisfaction. By using data to determine which products are often bought together by whom, how often, and sometimes what time of the month or year, retailers can optimize product placement, provide special offers, and create new product bundles. to encourage additional sales of these suits.