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Benefits of Big Data Solutions in
the Telecom Industry

 

There are so many telecom players in the market today
and the competition is heavy. Every telecom provider is looking at reducing
operational expenditure, increasing revenue, reducing customer churn and
providing a superior customer experience as key business objectives.

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3.1
Improve customer experience

 

Traditional customer care solutions are disconnected,
reactive and not personalized. Big data solutions can help fix this. Dynamic
profiling and segmentation, clickstream analysis, detailed weblog inquiry are
some examples of big data use cases to improve customer experience 15.

 

3.2
Customer Segmentation

 

When the custom base grows larger, it is an efficient
marketing strategy to segment the customers into different groups based on
behaviour. This will allow to identify loyal customers for targeted marketing
and retention activities, create tailored products for customer segments to
increase customer satisfaction, identify high-value and long-term customers,
and identify potential customers 16.

 

3.3
Understanding new product potential

 

Telecom companies need to always be on the edge of
innovation; they have to innovate new products or services, or modify existing
products or services to make them more personalized 17.

 

3.4
Innovative business models

 

Digitally transforming organizations have a good
opportunity in putting big data collected to good use in innovative business
models. Exposing data via well-crafted APIs to internal and external parties to
the organization can bring new revenue to the business. Near field payment
services is another innovative offering, where telecom providers can engage
with retail chains to offer customers new services. Match demand and offering
nearly is another such innovative offering delivered together by telecom
providers and merchants 15.

 

3.5
Real-time Analysis and Decision Making

 

Analytics should not only support batch and real-time
analytics, but also need to provide real-time intelligence. Based on these
analytics, guidance have to be provided to the users of the system on the actions
that can be taken. Congestion control, location based and personalized
services, data interactive exploration and cybercop are some of the solutions
that can be provided by big data tools 15.

 

While most of the traditional analytics tools provide
analysis on who, what, how and when, the dimension those tools lacked was the
“Where”. Today’s advanced big data platforms are able to provide highly
interactive applications that bring in the “Where” dimension to the company’s
“real-time” solutions, mainly by integrating with a specialized Location
Analytics solution, which allow to view location data of transactions,
customers, channels and networks, which leads to better decision making 18.

 

3.6
Precise Marking

 

Predictive Analytics can help correlate data to
generate insight that can help marketing campaigns with offer optimization,
bundle packages with other products, etc. and also preemptively avoid customer
churn 1516.

 

3.7
Reduce Customer Churn

 

Unlike other industries, barriers to exit is very low
in the telecom industry. Switching from one telecom provider to another isn’t
much costly for a average user because in most countries number portability is
there and there are also no long term legal contracts. In order to reduce
customer churn, telecom providers have to get to know their customers better
and do target promotions, and high usage customers have to be identified and
incentivized.
With help of predictive models and machine learning algorithms, it is possible
to accurately identify customers who are likely to switch to the competition.
Bringing together data collected on customer usage, complaints, transactions,
social media, clickstream, they can create factors which can identify customers
at risk of moving out 19.

Today’s big data platforms can provide, online, close
to real-time marketing campaigns for direct 1 to 1 customer outreach 19.

 

3.8
Operational Efficiency

 

Main contributor for this is poor network capacity
planning. Next-generation infrastructure should be able to intelligently plan
network capacity, do cell-site optimization, predict and preempt customer
complaint and do subscriber-centric wireless offload 1516.

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