Thanks to scientific models that allow complex analysis of databases, massive marketing campaigns give way to selective ones, which ensure more effectiveness by discovering which customers are more likely to consume a particular product. They also facilitate retention by alerting people to potential dropouts.
In a market where the offers of financial institutions multiply and occupy a large percentage of the commercial proposals that consumers receive daily, the challenge of those responsible for the Commercial area is to attract attention, to expand the client portfolio without excessively increasing the costs.
The best way to achieve this is not to waste effort, but to target the right people. But, how to previously detect in our database who would have a specific interest in a product?
This is one of the answers that Data Mining gives us ; set of techniques for the exploration and analysis of large volumes of data in order to extract implicit, previously unknown and potentially useful information.
It is interesting to recognize how its use has spread to the main references in different industrial sectors: distribution chains, financial services, credit or frequent buyer cards, customer loyalty systems, etc.
Data Mining for Sales and Crosselling
Faced with an audience overwhelmed by the saturation of messages that are often inconsequential to them, arriving with the indicated information is a gesture that surprises today and is highly valued by customers.
This tool allows, from the cross-linking of data from different sources that conclude in the act of buying any product / service, to identify the tendency of potential buyers to accept a product. It works making the most of the information available in the databases that companies have, crossing variables that allow finding correlations that are often unthinkable. Through Data Mining, significant patterns and relationships hidden among large amounts of data can be discovered.
Data Mining applications for campaign optimization allow working with narrow but much more effective contact lists, visibly improving the responses obtained and focusing accurately through suitable channels. This results in a reduction in costs and a substantial increase in sales.
Work on purchase limits
In times of price adjustments like the ones we live in, one of the frequent demands of customers towards entities that handle credit cards is related to the increase in purchase and financing limits.
The management of the appropriate parameters through specific Data Mining software enables a more instantaneous analysis of this point, carried out not only from the financial behavior of the client, but also from the habits of use that allow defining the user's profile.
Retention: targeting "dropouts"
Although companies may consider that a customer's decision to stop receiving a certain product / service is a sudden decision, there are actually subtle signals or warnings that can be readable from the different techniques used by Data Mining.
Bearing in mind that the cost of attracting a new customer is considerably higher than the cost of retention, it is a smart strategy that aims to detect those early signs. If we know which group of users are most at risk of being lost, we can consider targeted retention actions.
In summary, the key is that those companies that, due to their activity, collect information about their customers, learn to read it to use it for the benefit of both the company and the users themselves.
