Published on : 27 April 20223 min reading time
Using date as key to understand the consumer :
Data reveals a major asset and key to understand any consumer. With the implementation of specific methods to analyse, understand and collect data, such as Machine Learning, Artificial Intelligence or statistics, the company will process each customer information obtained more efficiently and will improve on several aspects : maximised return on investment, ideal marketing strategies, improvement of actions according to market trends and opportunities. Even though a good number of companies have implemented some projects to optimise the customer experience, few of them see developments through the digitalisation of processes. However, as seen before : data will improve the customer experience and the company will be able to put the tools for that to happen in place. More details on the reference site https://www.goaland.com/.
The data-driven method, how to use it ?
Some consumers practice ROPO (Research Online Purchase Offline) before making a product purchase. Furthermore, it is possible to know all the purchase intentions of almost all the consumers who enter a physical shop. All this means that you know the consumers and their expectations. Organising a marketing strategy based on the understanding of motivations, the acquisition of data, preferences and needs in order to better predict behaviour is absolutely essential: this is known as a data-driven strategy. To understand better, you need to put the data and the customer it represents at the heart of your strategy and leave mass marketing techniques behind. You need to implement all this in your company.
How do you collect, analyse, implement and organise data ?
Collecting information from all consumers is a relatively well understood concept of business. Taking into account all the collection points that have been made available (Marketplace, loyalty cards, customer interfaces, etc.), all companies currently have an infinite amount of data. The interest is therefore to transform the quantity into good quality. Apart from the classic statistical and data analysis tools, it is essential to implement data visualisation or datamining tools to “make the data speak”.