How companies use data analysis: 6 examples from different sectors

Companies have always tried to find the best techniques to maximize their profit: what products sell the most, what marketing strategies attract more customers, what days more sales are made, etc.

Thanks to technology, the amount of data that is collected and used has grown exponentially. The way it works Big Data (or big data) are changing the way in which companies relate to their customers, since they allow a much more exhaustive and complex analysis of the individual profile of each of them.

Each sector has specific needs regarding the data it collects and subsequently analyzes, so there is no single way to define data analysis. In fact, even within the same company, the use of data varies significantly between departments. For example, the HR department will focus on data analysis to improve the hiring process of new employees and evaluate the performance of each worker, while the advertising and marketing department will seek to optimize the way in which different campaigns are carried out. advertising to attract new customers and/or increase sales.

Data analysis is not only something exclusive to large companies, retailers can rely on it to analyze the web traffic their store generates or create specific promotions. Likewise, data analysis can help optimize shipping-related costs or find expenses that can be reduced.

The demand for a greater quantity of food while asking the sector to be sustainable and respectful of the environment has led agriculture to use data analysis to transform traditional agriculture into new forms of smart agriculture, such as agriculture precision.

This new smart agriculture is based on satellite data and others collected by different devices such as field sensors or drones, to which different algorithms are applied (for example, vegetation indices) that allow us to understand the real situation of the field and the crops. You can find data analytics-driven solutions for field management here.

Data plays an important role in the industry, both in older and modern processes. In old processes, the data collected by sensors installed on the equipment can help to understand the efficiency in the production chain, both of the robots and of the employees. In modern processes, thanks to advances in automation and robotics, data analysis can indicate which processes are faster and more efficient and which require some change.

Likewise, it is not unusual to see manufacturers include some type of data collector in their products, which allows them to know first-hand how customers use them and the performance they can provide.

Retailers need to follow the lead of large corporations and use data analysis to maximize their business and understand what their customers’ needs are. From data related to purchases or the number of visits made to their comments on social networks and forums, through interest in loyalty programs or during sales times, all this data shows a general idea of ​​which products the customer should focus on. business and what aspects are most relevant when carrying out a personalized advertising campaign.

The telecommunications industry has a powerful ally in data. Data analysis allows them to understand the level of customer satisfaction and think of different ways to improve their experience. But the data is not only useful for that, it is also useful for analyzing how the network management is being and improving what is not working, seeing the distribution of customers geographically and carrying out specific promotions in areas where they want to increase the number of them, etc. .

Those sources of non-renewable energy, such as gas or oil, may encounter unforeseen situations caused by political instability in the area, new taxes on extraction and/or transportation, or even the end of the reserve from which it was extracted. .

For this reason, the energy industry relies on data analysis to understand where it is most profitable to extract based on the moment, estimate the extraction volume and, consequently, decide the sales price.

When it comes to security, there is no way to predict what may happen in the future, but you can take advantage of the data collected by surveillance devices to evaluate possible dangers and where in the area or facility these are most likely to occur. These are just a few examples where the Big Data is revolutionizing the way we work, but they are not the only ones. Over time, data analysis will become a standard in all businesses and those who know how to use it properly will become the leaders in the sector.