Data analytics use cases and how to get the most out of it

In Mexico, data analytics or Data Analytics is a need of which, little by little, organizations have become aware.

In figures, the motivations that have produced this change translate into an increase of up to twenty times in attracting customers, up to six in the possibility of retaining them and in a 2.6 times greater probability of increasing the return on investment.

What is data analysis and data analytics?

Big Data analytics is a discipline that consists of examining large amounts of data that companies receive, in order to find correlations and patterns that are difficult to identify with the naked eye.

As a business intelligence strategy, it allows you to obtain answers from these volumes of data, practically immediately, which in turn facilitates crucial decision-making and improves the detection and exploitation of business opportunities.

Importance of data collection and analysis

Unlike traditional analytics that were already in use in the 50's, contemporary systems allow companies to work quickly, efficiently and without errors, giving them a competitive advantage that years ago was unimaginable.

Other benefits of what is also called Data Analytics are more efficient operations, higher profits and satisfied customers.

Processing and Data Analytics: Use Cases

1. Prevention of customer churn

Big data technologies such as cloud analytics help reduce losses associated with customer churn. What happens when a company begins to experience this phenomenon goes beyond not perceiving the profits that those customers represented; It also implies a strong investment in attracting new ones, which is more expensive than building loyalty.

Now, you wonder how Data Analytics helps to control this situation. And the answer is that, by generating satisfaction indicators, you will always have a clear orientation to make decisions aligned with what interests or satisfies your customers the most and even understand which segments are more likely to leave and what needs to be corrected to retain them.

2. Identification of clients that will add value in the long term

One of the biggest challenges for any company is to identify early the consumers who will make the largest investments in a sustained and long-term way. In this sense, data collection and analysis allows companies to optimize their marketing, directing it to those segments that will add value indefinitely.

3. Market segmentation

Each company defines a different market and segments it in order to obtain more value from the products and services it offers. Data Analytics makes possible a greater precision in this task, allowing to identify the most receptive segments to your proposal and even markets with potential that you did not imagine existed.

4. Speed and certainty in decision making

Today, companies obtain the information they need immediately, with the help of technologies of Data Analytics, BI and machine learning, which allows them to take quick, informed and risk control actions.

This, because the systems analyze everything from purchasing patterns to consumer behavior and interactions on social networks.

5. Generation of new products and services

Data processing and Data Analytics provide companies with the tools to identify their customers' needs even before they are aware of them. This encourages investments in the development of products and services that are correct and with a high probability of success.

This is possible thanks to product propensity analysis, which combines data on shopping activities and behaviors with social media and e-commerce metrics. In this way, data is correlated to provide information on the effectiveness of a campaign or the sales potential of a product.

A particular example is the use of Data Lake and data analytics in Fintech companies, companies that, as their name indicates, have adopted financial technologies to anticipate market needs and improve the supply of products and services in the sector.

In your case, some of the advantages that the implementation of these systems has meant are the active management of data from the securities markets and the automation of the data collection and transformation process, which results in the proposal of creative solutions to attend to the needs of new users of financial services or those that were neglected by traditional institutions, as well as in greater efficiency and better risk management.

However, in a context marked by competition between companies that offer similar products and services, where customers are more connected with brands and the consumer demands attention based on knowledge of their preferences, Data Analytics systems have stopped be an innovation that was seen from afar, to become an essential factor for competitiveness.

With this in mind, in Codster We transform your data into strategy through data science and analytics solutions that will allow you to make strategic decisions based on data, have centralized information for better use, maintain greater control to guarantee data security and finally, achieve a segmentation of market that represents more opportunities for your company.

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