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Data monetisation in telecoms: 10 use cases

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Summary

This article explores the different data monetization models and use cases across 10 verticals in the telecom industry, including agriculture, manufacturing, retail, finance, insurance, healthcare, real estate and construction, telecom, media and technology, and utilities. It discusses how telcos can use customer movement insight to generate revenue, as well as IoT and other analytics for different industries. The article also outlines the different opportunities for telcos to add value to various services, such as predictive maintenance and the provision of analytics for autonomous vehicles in manufacturing, customer movement insight products in retail, and telematics products for insurance companies.

Q&As

What is the connection between big data monetisation in telecoms and IoT?
The connection between big data monetisation in telecoms and IoT is that many telco data and analytics products are linked to IoT solutions.

What strategies are telecoms operators using to take advantage of data monetisation opportunities in the manufacturing sector?
Strategies that telecoms operators are using to take advantage of data monetisation opportunities in the manufacturing sector include rolling out 5G capabilities quickly, creating flexibility in their offerings, and providing edge computing for manufacturing.

In what ways can telcos use customer movement insight data in real estate and construction?
Telcos can use customer movement insight data in real estate and construction to understand demographics, behaviours and requirements of a local community to improve development and investment decisions, to use for pricing, marketing and sales decisions within estate agents and brokers, and to use indoor data from small cell deployments within shopping malls to understand customer movement in order to position advertising, adapt opening hours according to foot traffic and change layouts to drive traffic to, say, food courts.

What opportunities are there for telcos to provide services for the finance sector?
Possible services for the finance sector that telcos can provide include location-based card authentication, customer movement insight to understand where to open a bank branch, customer movement insight to optimise the location of bank ATMs, and data and analytics services on high speed, complex customer and market data.

How can telcos use analytics to generate revenue in the healthcare sector?
Telcos can use analytics to generate revenue in the healthcare sector by providing smart devices which generate payload data, managing electronic health records, medical images, electronic prescriptions and insurance claims, providing collaboration platforms for clinical trials, and providing insight to entertainment/sporting venues.

AI Comments

👍 This article provides an incredibly thorough breakdown of the many data monetization opportunities across 10 different verticals, offering insight into how telcos can leverage customer movement insight and analytics to create additional revenue streams.

👎 This article may be too complex for most readers to understand, as it covers a lot of technical information about data monetization in the telecoms industry.

AI Discussion

Me: It's about data monetisation in telecoms and it explores ten different use cases. It breaks the use cases into two categories: those that are strongly linked to the Internet of Things (IoT) and those that are more independent. It looks at potential opportunities for telcos in each vertical, including agriculture, manufacturing, retail, transportation, finance, insurance, healthcare, real estate and construction, telecom, media and technology, and utilities.

Friend: That's really interesting. What are the implications of this article?

Me: Well, it suggests that telcos should consider data monetisation as part of their overall strategy in order to take advantage of the opportunities that are available in each vertical. It also highlights the importance of having a long-term strategy and understanding the sector when it comes to building new revenues in the healthcare vertical. Moreover, it suggests that telcos should focus on providing customer movement insight products, as these tend to be the most feasible and profitable projects. Lastly, it highlights the importance of investing in the right platforms, applications and smart devices in order to develop analytics, automation and AI capabilities.

Action items

Research the different data monetisation models and use cases across the 10 verticals discussed in the article.
Explore the opportunities for telcos to add data/analytics to IoT deployments in the retail, finance, insurance, healthcare, real estate, telecom, media and technology, and utilities sectors.
Investigate the potential for telcos to provide customer movement insight products, analytics, and A3 (automation, analytics and AI) services to enterprises in the various sectors.

Technical terms

Data Monetisation: The process of converting data into a form that can be used to generate revenue.
Big Data: A term used to describe large and complex datasets that are difficult to process using traditional data processing techniques.
IoT: Internet of Things. A network of physical objects (devices, vehicles, buildings, etc.) that are embedded with electronics, software, sensors, and network connectivity, allowing them to collect and exchange data.
5G: Fifth-generation wireless technology. It is the latest iteration of cellular technology, designed to greatly increase the speed and responsiveness of wireless networks.
AI: Artificial Intelligence. A branch of computer science that focuses on creating intelligent machines that can think and act like humans.
Telematics: The use of telecommunications and information technology to monitor and control vehicles.
B2B2X: Business-to-business-to-X. A business model in which a company provides services to other businesses, as well as to their customers.
PII: Personally Identifiable Information. Any data that can be used to identify an individual, such as name, address, phone number, etc.