Analysis of customer behavior in the telecommunications sector


With increased competition in the telecommunications market, it has become even more vital for telecommunications operators to be proactive in providing services to their customers and to position themselves accurately in the complex market. Indeed, operators generally have shifted their attention from customer acquisition to customer retention, because with the market almost saturated, it is simply deemed more profitable.

Once big data enters the scene, operators have a head start in understanding their customers and making accurate business decisions. By using the right technology, telecoms can access the information they are looking for in near real time.

Why analyze?

We would be hard pressed to find another industry with as easy access to a wealth of user data as telecommunications. Traffic, user behavior, location, etc. are easily accessible to the supplier. With this information, providers can analyze which services their users use, for how long they use them, and when. They can offer precise upgrades, price their services accurately, and deliver a superior experience that can retain this extremely volatile market.

By deeply understanding consumers, businesses like Clear history data Where Computer science can create targeted advertising campaigns, understand when and where customers need certain services, create data packages that better match usage patterns, and save their customers money. They can even fix service issues before customers know they exist.

This information also helps telecommunications operators manage their resources; the data enables them to investigate network incidents, uncover system misuse, prevent cyber attacks, and more. Maintaining flexible access to data is an absolute necessity.

What are the obstacles ?

The biggest opportunity for telecoms – the huge amount of data they have access to – is also the most difficult hurdle when trying to analyze the numbers: there is so much data! A huge volume of information, coming from many different points, must be stored, analyzed and accessible in near real time. Working with massive amounts of customer behavior data can lead to many problems, including the “correlation problem”(Just too many statistically significant answers), figuring out how to analyze the richness of the data, and finally, figuring out how to turn data on customer behavior into practical, usable information. How do you start to analyze customer behavior?

First of all, ask yourself the right questions.

You know who is talking to whom, for how long and when; you know where they are; you know how your network works; you know how long and when your customers are accessing data; you know how customers interact with your business; you know a lot of things. But it can only be useful if you know how to analyze this information. Ask the right questions as you determine what you want to accomplish.

Are you trying to create happy and loyal customers? You need to know what they like, what services would appeal to them, their weak points. Do you want to increase the ROI? Find out what customers need to be able to sell additional services. Asking the right questions helps you organize data in a way that you can achieve your goals.

Find the right software

Data collection (collection), data storage and analysis are three separate things. Companies have been collecting and storing data for a very long time now; there is nothing new about it. They’ve even been analyzing data for a long time, but not the massive amounts of data businesses are working with now. Data evolves and technologies are underdeveloped to manage it or extremely expensive.

Next-generation GPU-powered analytics technologies were designed to address challenges such as those mentioned above,offering flexibility and the ability to handle huge amounts of data, at record speeds.

Applications such as geolocation analysis, customer profiling based on behavioral metrics (simple like where you spend your time, what are their interests, what networks they use and upgrade, what motivates them, etc. ), help businesses personalize the experience for their customers. Telecom operators can learn what their customers need and want, making it a fantastic tool for sales and retention.

When looking for powerful analytics software, look for a GPU database that can ingest data from multiple sources like tweets, texts, CDRs, POIs, IoT sensors, customer information, network events and WiFi / 3G / 4G traffic in a single point of knowledge, and analyze all aspects of interest in near real time. This type of database, like BD SQream – a GPU (SQL) database designed for range from tens of terabytes to petabytesprovide analytical capabilitiessuch as customer mobility, device discovery, location analysis, customer behavior, advertising optimization analysis, network monitoring and security. SQream’s software helps carriers optimize their infrastructure, analyze deep historical data, identify opportunities, automate marketing activities, and uncover security and abuse issues, among others.

By selecting an extremely efficient technology in terms of infrastructure, data that was previously thought impossible to analyze is now accessible in near real time. This is an advantage that telecom operators cannot afford to pass up.


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