“We must all be increasingly prepared for Big Data, due to the technological challenges it entails, and because of the often-intangible effects that will transform the way we work and live.”
Based on: “Descriptive Video on Big Ideas: Why is Big Data Important”
Big Data in the telecom industry has transformed and continues to transform, both internally in its forms of operation and externally in its relationship with customers and users.
The emergence of Big Data had a profound impact on all productive sectors, and the communications sector is an exception to this rule.
This article expounds on how Big Data has changed the telecom industry.
The telco industry requires data to function and needs to process and use that data in an efficient way.
The data represents a kind of oil in the sector because it is the heart of all its product development, especially since the leading telecommunications industries are on the Internet.
The web, social networks, telephone companies, streaming platforms, and third-party service companies (ATMs, software creation, CRM, storage clouds and a very long etcetera), among others, feed on data. Let’s see in-depth how they do it.
History of Big Data
Big Data from the 50s to the 80s
After World War II, we can classify the influence on Big Data in terms of its evolution as:
1956: The creation of Virtual Memory: physicist Fritz Rudolf Güntsch developed this idea that treated finite storage as infinity. This way could process data without a hardware memory limitation.
1962: William C. Dersch presents the ‘Shoebox’ machine. This system understands speech for the first time—precisely, 16 words and ten digits in spoken English.
1966: In the late 1960s, organisations designed more advanced computer systems.
1989: Erik Larson mentions Big Data because we know it today. This year, business intelligence tools became popular to analyse business activity and operations performance.
Birth of the WWW and the Journey of Big Data until Today
With the advent of the WWW (World Wide Web) and the Internet in 1989, massive data generation had new paths. This development derived from the first information management and storage systems in 1992. Today it allows us to be able to process and interpret Big Data.
From 2009 to 2011, companies such as Cloudera and Hortonworks appear. Both are born to achieve better data management. These services open a world of possibilities for companies. In 2012, Barack Obama used Big Data to find out the most undecided voters’ opinions and know what channels they used. In this way, he launched messages with a more personalised impact.
In 2016 Big Data reached a vital position in society. The hiring of Big Data experts is generalised, Machine Learning enters factories, and the Internet of Things begins to cover different sectors. By 2017 the data would reach the masses. People can find out about their rest patterns, their spending of money and are informed about, for example, about the possession of the ball of their soccer team. Data is everywhere, and the population is ready to use it.
The Importance of Big Data
Big Data is essential because of the technological challenges and the often-intangible effects that transform how we work and live.
Big Data is necessary for three straightforward reasons, which are closely related:
1st New Data: The Big Data generated, collected, and stored today contains an enormous amount of information that was not available before and was unknown to us.
Most Big Data has new content. An example of this is those related to the world of electronic commerce. Gone are the days when transactional data was captured by websites, such as purchase details, to improve demand calculation, stock supply optimisation, and price adjustments.
2nd Unlocking Value: Big Data’s value can be discovered through automatic analysis since it is digital data. Data analytics have the astounding ability to transform data into new information, leading to intelligent action.
Big Data by itself isn’t the only reason it’s crucial. Experts analyse these data to reveal the value they hold.
3rd Shaping The Future: We may soon be much more proactive because of the type, depth, and sophistication of analysis that is now possible. This efficiency influences how the future shapes up instead of just reacting to the unforeseen consequences of the past.
The type of information that Big Data contains has also allowed us to take some leaps, replacing the simple modelling of the future based on the continuum of its history with proper prevention and influence on future actions.
Benefits of Big Data in the Telecom Industry
Customer Service Experience
Customers are the primary source of information for any company. From them, we can know their level of satisfaction, the products and services they want and the elements in which the company is correct or incorrect when responding to their concerns.
All these interactions or data have the potential to improve efficiency. Telco managers have accurate information about the needs of their customers, their dissatisfactions and what they expect from the company.
Instrumentalizing that data to make services more efficient is the practice of a promising sector manager.
Increasing the company’s efficiency will directly impact the company’s profits and user satisfaction levels.
Better Customer Segmentation
The data allows us to know the target audience, in a new type of segmentation of much smaller audiences, with much more information about them. The microfocus is key to developing sales, retention, and loyalty strategies. You are halfway there if you know who your customers are and how you must address them.
When the personalisation of services has become a staple in any marketing strategy, segmentation is once again a great ally: companies now know their audience’s demands. They can improve and adapt their services to them.
So you can also detect new opportunities in the market. For example, suppose the telco market promotes family packages, and you catch a need in a target of singles without family. In that case, you can go ahead and create services and campaigns primarily aimed at them. Segment and listen to your audience.
In this context, behavioural targeting is beneficial beyond traditional segmentation. We have gone from segmenting by sociodemographic characteristics to having data on people’s behaviour in our possession, in a digital world where we measure everything.
Focused Marketing Campaigns
Companies like Google and Facebook base their advertising algorithms on Big Data.
This use of Big Data is not only valuable for large companies. Any company could do the same.
Telco companies can project advertising in their branches and do it the same as digital corporations: guided by Big Data.
The data provided by customers serves to understand them and, therefore, is helpful to predict the type of advertising to which they would be most receptive.
Thus, companies in the telecom industry can use the Big Data of their customers and accordingly direct the advertising they offer in their branches.
And this includes the printed brochures that are always available in waiting rooms, to content on digital billboards, without neglecting traditional billboards and even the advertisements projected on televisions that are usually in branches of telecommunications companies.
Companies in telecom industry generate a growing stream of data that reveals customer demographics, spending behaviour, lifestyle, and social influences.
The analysis of this information allows us to adapt products and services to the needs and tastes of our clients. The personalisation of goods and services increases the customer’s satisfaction. Companies with the ability to understand their consumers will have valuable insights that will allow them to retain them.
As mentioned before, the data that a virtual operator client leaves on a website is worth analysing. It can provide helpful information to carry out actions that minimise churn, such as improving usability.
Personalising advertising and optimising user navigation is a pleasant experience. He perceives that the company remembers who he is and does not receive messages and impacts that do not interest him. In addition, the advertising is correct for each specific audience.
In addition, Big Data analysis provides personalised benefits and added value in the online experience because it makes it possible to make an optimised network available to the user with real-time response to traffic problems.
One of the most common uses for big data in the telecom industry is to evaluate customer behaviour precisely and in many vertical segments. It comes from billing records or interactions with branches or virtual service channels.
A thorough “reading” of the customer’s movements through online spaces is essential: understanding which messages they paid the most attention to, where the paused was longest, which specific buttons they clicked, what they liked about the content on social networks.
With all this information, we can model consumption habits, and it becomes possible to identify atypical behaviours and thus prevent fraud.
The telecom industry uses big data analytics to combat fraud which amounts to some $38 billion a year. To do this, these companies analyse daily call logs along with other customer data to create more comprehensive user profiles, thus detecting irregularities more effectively and quickly.
For example, mobile operators share GPS data from their customers’ smartphones with banks to monitor them to prevent credit card fraud by verifying a person’s card usage with their location.
Operators can obtain critical information about their customers, from location to personal interests. However, they have not extracted all the strategic value of said data for various reasons.
The data is structured (customer profile, service requests, pricing, technical incidents generated, etc.). It is also unstructured (documents, videos, images, Web content, location, presence, DPI, SIP / Diameter / SS7 signalling, logs, “contact centre” recordings, etc.). It is even partially structured (customer profile enriched with CDRs or “call data records” and external information such as blogs, forums, social networks, etc.).
Through DPI (Deep Packet Inspection), they can know how much bandwidth the user uses, when the connection starts, what websites they visit, what applications they use, etc. They could even obtain additional information in real-time on the tastes and interests of the client, although legislative issues on privacy and confidentiality currently limit these.
Big Data in the telecom industry offers attractive advantages in storage, analytics, and automation:
Before processing the data, you must have a place to save it, and there is so much data that there is no physical space to support it. Telcos extract structured, semi-structured and unstructured data from everything, starting from their contacts with customers
We have the data; now it’s time to analyse it. Big Data makes it possible to find patterns within them thanks to Data Mining and to carry out descriptive, diagnostic, predictive and prescriptive analytics that serve as the rudder with which to set the course of the telco. If you want to know more, consult this text on types of analytics in Big Data.
What does all this mean? Fundamentally, we are no longer walking blind. Accurate predictions make decisions with data, not a crystal ball. All these actions are automated: we have the data processed in real-time and anticipate market changes.
Big Data has represented a change in all productive sectors. Thanks to the irruption of data as a new raw material for the economy, banking, public services, and software companies are not the same today as they were a few years ago.
We can highlight the telecommunications sector as one of the most benefited from these transformations.
It is feasible to think that in the immediate future, these changes will continue, and telcos companies will have more and more Big Data tools incorporated into their internal structures.
It is a fascinating change that transforms this sector and, above all, our lives.