Hi! We are glad to have you back on our blog 💜. In fact, we are excited for you to read the second part of the previous article on Big Data.
In today's quote we will take a look at some examples of Big data. Are you ready? Let's get to it. 😎
Where does the data come from?
In the previous article, we talked about what Big data is and some of its characteristics, but we didn't mention an important point, the data! Where does it come from, or where do we get it from?
Data is basically generated from everywhere. Especially if you are connected to the internet, where it is possible to capture every click given (and every click not given), as well as all the texts that are generated. From this we save that there is structured and unstructured information.
On the other hand, IoT (Internet of Things) is a great source of data collection. Currently almost all products of daily use, such as cars, watches, cameras, voice assistants, among others, can be connected to the Internet (so they can generate data on each person in real time).
Nike has a line of products that monitor the data generated from exercise. Apple has something very similar with the Apple Watch.
Fields of application of Big Data.
According to Platzi's article, there are an infinite number of fields of Big Data application, so, let's see how your company can benefit from it:
- In the digital world, all information can be recorded and processed in real time. So from user information, personalized offers can be displayed for groups with common behaviors.
- User behavior analytics to create and improve the functionalities of a platform according to what the user does.
- A very interesting application is to avoid fraud in things like identity theft or card cloning.
- A well studied field is text mining for natural language processing (NLP). From this there are a lot of applications such as: sentiment analysis in marketing or the automatic classification of problems in the customer support department, with each complaint reaching the appropriate team.
- Calculate the commercial potential of different geographical areas in order to open new stores without affecting the sales of others. In the same sense, it also works the other way around to know when to close a store.
- For banking, many risk analyses are made to know which clients can be admitted or rejected, which credits can be approved or not, and even the analysis of the clients' portfolio to constantly analyze the aforementioned in case something changes in their credit history.
- In a call center it could help to know which customers to call, at what times and what kind of promotions can be made to them.
- It is easy to make a very precise customer segmentation to send them personalized campaigns, build customer loyalty and prevent them from leaving the company.
- It is also possible to identify problems before they happen and take actions to solve them before they even exist.
Big data + Insurance industry
At LISA Insurtech, we are specialists in the use of the most current and innovative technology😎 This with the aim of offering the insurance industry the impetus to evolve.
Our application cases contemplate almost all of the above list:
- We record all the information of the insured in real time to guarantee the insurance company possible customizable offers.
- We track how the client acts in front of the platform in order to improve it according to how the insured "moves".
- NLP is one of our greatest foundations, with it we make follow-ups and analysis to make decisions.
- We contribute to risk and fraud analysis.
- We are able to identify problems before they occur, which leads to a decrease in claims thanks to telemetry.
Impressive, isn't it?
We cordially invite you to learn more about our LISA Claims product and allow your insurer to benefit from big data and all the technology we have for you.