How to use Big Data to increase sales?

How to use Big Data to increase sales?

This digital tool improves strategies to attract more customers.
This digital tool improves strategies to attract more customers.

Trends in the world are constantly renewed, all the time we are looking at how to do better what is already there or what alternatives allow us to reduce factors such as time, use of resources or occupation of human talent. Since his beginnings, man has never stood still, and thanks to his curiosity, today he has achieved great developments in different aspects of life. The business world is one of them, as is technology. In these two spaces there have been endless advances in recent decades, to the point that business is no longer done as before and the same computers or technological equipment of past generations are no longer used.

However, in recent years there has been an interesting fusion between the world of business, technology and virtuality. The clearest example came with the pandemic, where many merchants had to invent new strategies to avoid bankruptcy and with this there was a boom in online stores and purchases. In the midst of all this, there is an element that perhaps goes unnoticed by many, but that others have known how to capitalize on to achieve growth. It is about Big Data, which is nothing more than all the personal information that is delivered daily, whether it is from a personal email, through the name and cell phone number, to the same ID number.

All of this data is a gold mine for companies looking to grow their customer databases. According to a recent report by Allied Market Research, 75% of companies by the end of 2024 will switch to Big Data strategies, to increase their flow of customers and, consequently, sales. Thanks to this digital tool, merchants can know what a certain person likes , as well as what they need, what are the search trends on their cell phone or computer, how much they are willing to pay for a product or simply show themselves on their social networks and generate an interaction.

Taking into account the daily increase in the production and consumption of global data, Víctor Hoyos, commercial manager of CALA Analytics in Colombia, affirms that “data analytics is the engine of digital transformation”, however, he also points out that ” many of the companies still do not use it, an average company has 12 million GB of data, but only uses 3%”. Notably, according to the Mckinsey Global Institute, data-driven organizations are 23 times more likely to acquire customers, six times more likely to retain customers, and 19 times more likely to be profitable.

“After 2021 was recognized as the year with the most data production throughout history -it is estimated that as much data was produced as that which has been generated from the beginning of humanity until the year 2015- companies have almost forced to understand that those who have the ability to analyze business data will have a competitive advantage in the industry ”, added Víctor Hoyos, from CALA Analytics.

Seven key tools to go a step forward with Big Data

According to these experts, it is necessary to be constantly informed of the changes that are taking place in the world in this area, so that the course can be changed, as the market requests. They also shared the following seven practices to get you started. DATA for transformation: When a business uses and analyzes their data, they can see up to 30% annual growth. According to CALA Analytics, the most important trend is the use of data as an input for decision making, moving from description to true analysis. Artificial intelligence for sustainability: referring to data analysis for global benefit. Today, 120 countries have joined the “Global Responsible Artificial Intelligence Index” project, which represents an opportunity for many sectors and industries to develop social and environmental responsibility strategies, thanks to the use of analytics.

Artificial Intelligence for creation: this is a leap towards automatic content production. Everything will evolve so that artificial intelligence can generate content according to algorithms and DATA. The machines are already learning patterns and generating original content that is rewarded by the algorithm. According to CALA Analytics, by 2025 more than 10% of data will be created by AI.

Artificial intelligence for data management: the administration and operation of data in an organization thanks to AI, is positioned as a practice that companies and organizations should start implementing. According to figures, by 2023 more than 30% of companies will migrate to a data architecture that will allow them to administer and manage data correctly.

Acceleration of omnichannel to increase sales: companies are beginning to see the customer as the sum of different consumers, that is, it must be understood that a buyer is not different depending on the consumption channel. Efforts must be unified both online and offline, since, for example in the United States, today 40% of buyers of mass consumer goods are omnishoppers , that is, they buy both online and in person.

Collaborative data mining for innovation: Collaborative methods, shared computing, and working on data from different parties is key for organizations to take the lead across industry. An example of this is the development of vaccines against covid-19, a joint effort by several multinationals in the pharmaceutical sector.

Creation of new jobs for analysis: the environment is not enough and the demand for personnel for data analysis is increasing, due to this, there is an increase in the creation of new roles for these functions, some of them are: Data Artists, Data Translator, Data Product Managers and Data Scientist.

Samuel Edwards
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