Telecom and phone communications constitute an essential part of our lives nowadays, there are big companies in the Indian market primarily competing with each other to provide the customers with the best plans and services to gain profit.
With the rapid rise in the numbers and usage of smartphones and mobile phones telecom companies are flooded with data of various kinds which has the potential of increasing the profitability for the companies if decoded and understood properly.
This data can be a basis for all of the required operations if the proper conclusions are being drawn from it. For example, Big Data Analytics can tell the peak hours of data usage by the customers so the company can prepare itself to avoid any kind of slowdown or problems.
As data refers to the stored information and recorded operations which were performed by the computer in various forms, big data can be understood as the same data being present in huge amounts and numbers. This consists of information provided and both humans and the devices.
Big data is the collection of the data which is also growing exponentially with time. Big data is so large and complex in its size and storage that it is unable to be deciphered and understood efficiently by the traditional data management tools.
Big data analytics can be used to reveal pre existing ignored patterns by using analytical understanding and predetermined conclusions are sought after to be able to fetch the desired results and understand and decode the data in terms of existing issues.
Recommended Blog: Big Data in Media and Entertainment
Telecom companies have huge data available at their disposal already which is exponentially rising every day, the rise in the number of smartphone users, service providers can monitor regular customer profiles, device data, network data, customer usage patterns, location data, apps downloaded, call durations, etc.
Such data can be really insightful for the company in order to make adequate decisions and implementations in terms of customer experience, network optimization, operational analysis, and data monetization.
Big Data can be used by telecom companies to provide them with major benefits and the ideas to come up with many solutions.
Optimizing the customer experience is the key to the generation of a loyal customer base. Big Data can help in providing categorized all over user information which can further help in personalizing the experience for the customer.
The major way to keep a customer is by providing the best services and proactive help in the time of any breakdowns and resolving of queries, there are a lot of telecom service providers applications that come with an automated chatbot for the immediate resolution of the issues and induce the required action taken.
There are services and customer care numbers that are filled with a plethora of options for the customer to self-help themselves before contacting a real person.
Even when a real person speaks the company keeps a record of the consumer interaction recorded to enable their employees to be trained in accordance with better profitability.
The companies can record the issues raised from a particular location or area and can seek to improve network connectivity or internet speed issues in that location so as to not lose the customers and generate services for them adequately.
By the data of customers behaviour patterns, billing and problem redressal sought patterns the companies can not just seek to resolve the issue of the customer and retain it as a loyal customer and improve their services but as well as can target them for best services.
For example packs based on the amount of their previous purchases, extra data packs for people who don’t use it to lure them, free voice packs, ank extendaed day limit for the pack. All these can be understood and concluded from the prevalent big data and used for the benefit of the company.
Real time information of the pack expiry due date and data exhaustion before the renewable time in the day help the companies in providing the customers with a ‘best offer’ for them to be able to continue using the services.
Data such as customer demographics, purchasing behavior and clickstreams are being combined with attributes such as location and content preferences to create the most useful pack which can turn the viewer into the potential customer just by sending them the right push notification at the right time.
Recommended Blog: Big Data in Manufacturing Industry
Churn refers to is a measure of the number of individuals or items moving out of a collective industry over a specific period making it a real issue of any business or industry.
This can be due to several reasons like quality of service, network issues, social media trends, availability of other better options, sudden price hikes, unresolved queries. Understanding such scenarios with the data available can always be a preventive way of reducing churn.
The companies can proactively reach out to reduce the anomalies based on a larger area or a location for specific user’s inconvenience and can also reach out to repeated customers, who have complained about a series of quality of service issues or who shared a negative sentiment regarding the service in social media.
These issues can be addressed and discounts or service credits can be offered to prevent customers from swapping the service providers.
Setting up a telecom company and being a part of this industry means network expansion, modernized setups and huge regular investments.
By understanding the network usage and required extensions as the network might be getting congested during the peak hour, in order to not lose customers to compromise on the service quality available sources of big data can help in making strategic plans for the future by monitoring various needs and defaults.
The company can choose to invest in the resources and expansions pertaining to future connectivity needs, strategic objectives, projected RoI, forecasted traffic, customer experience etc.
Such planned investments can help in maximising the services with keeping the services of the competitors in check as well, in the case of any foreseen upgrade or price wars such things can be handled precisely with the help of big data and strategies with concrete evidence.
Role of Big Data in Telecom Industry
Big data can be used in investing tools for real-time data analytics so that the companies can monitor the real-time situation of the customers and based on that, real-time usage influenced heat maps can solve the data congestion by just telling the service provider during the peak data usage hours.
Network providers can increase or decrease the range of the cell towers to meet the demands based on the usage and users of a geographical area.
Also in the case of a decreased users and overflowing capacity that can be controlled on the basis of the data generated to prevent the wastage of the resources and save the revenue of the company.
In order to maintain the daunted cell towers and provide solutions to the network congestion immediately without a plan, companies lose a lot of revenue without even making any efficient sales in these terms.
Big data can provide a solution for these as this enables us to trace back the data for the years, not just for a few months and from all the locations.
This can prove to be of great help, pre-planning for the maintenance of the plants before they break down, regularly updating the systems based on market scenarios and extended customer base, upgrading and changing the obsolete techniques, etc can be done to save extra money from the companies to drain out or make any immediate compensatory expenditures.
The telecom companies are capable of collecting a lot of data related to the user like subscriber demographics, subscriber location, network usage, device details, application usage, currency, preferences, etc.
These data, in turn, are able to give insights into useful statistics which might not be used by the telecom companies themselves but they can be really useful for other businesses.
There are some terms and conditions of such information aggregation which the particular service providers need to comply with.
Without violating those, the telecom companies are really being mindful of providing data analysis services to business categories like retail, financial services, advertising, healthcare, public services etc to help them in their campaigns and retargeting motives while being able to also personalize them, making their business flourish.
Recommended blog - AI in Retail
Big Data can help the telecom industry in a myriad of ways. as its a well-known thing that customers might slip out if they do not get the redressal or the expected services, such insights of timings, quality, location, users traffic, a record of maintenance not just helps in being a good service provider ut if implemented correctly such measures can be of a huge revenue safety for the companies as they make the optimum use of resources invested in by them.
6 Major Branches of Artificial Intelligence (AI)READ MORE
Reliance Jio and JioMart: Marketing Strategy, SWOT Analysis, and Working EcosystemREAD MORE
8 Most Popular Business Analysis Techniques used by Business AnalystREAD MORE
Top 10 Big Data TechnologiesREAD MORE
Elasticity of Demand and its TypesREAD MORE
What is PESTLE Analysis? Everything you need to know about itREAD MORE
An Overview of Descriptive AnalysisREAD MORE
5 Factors Affecting the Price Elasticity of Demand (PED)READ MORE
Dijkstra’s Algorithm: The Shortest Path AlgorithmREAD MORE
What Are Recommendation Systems in Machine Learning?READ MORE