Value Added Services – AI-driven mobile data monitoring and offerings are now escalating the usage of many mobile VAS services. In the telecom industry, competition comes not only from other mobile network operators but also from “new frenemies” like OTT (over-the-top) players. Services like Netflix, Hulu, VoIP providers like Skype, What’s App and walled digital content gardens have excellent application stores for streaming services. With these services, subscribers can stream video/audio at almost zero cost.


AI and Data Science-Based Mobile VAS

Point to make a note with clear understanding is “The change or technology shift that 5G and subsequent technologies will bring will not be the same as from 3G to 4G”. The shift from 4G to 5G will change the whole game and will bring major aftermath & complexity for almost every industry.


Mobile Value-Added Services market is predicted to cross $1USD Billion in the next 5-7 years. In order to achieve the revenue numbers, a lot of diversity in its business model, applications, and style of content delivery is needed. The way it’s designed as on date where it just captures subscription and delivery static and monotonous content, it’s going to die soon. In order to proliferate the telecommunication users market where almost everyone has a smartphone, it won’t be easy without artificial intelligence and data science capabilities.

The vas service providers have to pick the correct needs and technology to make sure they go hand in hand with  4G, 5G, machine learning and big data-based services.


Telcos & Declining Revenues

Telcos face flat growth due to market maturity, demand saturation, commoditisation of connectivity services and advanced mobile devices. To counter attack these business challenges, telecom companies in all markets must beyond VAS (value-added services). This will not only bring differentiation for them but will also attract new customers and boost margins & ARPU (average revenue per user).

AI-based software helping to solve distribution channel challenges. With such software, after feeding data to them they can help to improve customer visibility, behaviour, patterns and controls. For financial transaction over the POS, it even helps to stop the fraudulent transaction in an automatic manner. Machine learning capabilities turning mobile operators massive issues like sales and service distributions.

From a pure business perspective, a mobile value-added service is an extra service for which subscribers pay extra. Content-based services are on rising example educational content for school & university books at very low-cost and various tips for health, Information technology, Day-to-day life, Astrology, Managing Relations, Business, Financial Advise etc and many more.


Contents Related Challenges

Challenge for content providers is to make sure contents are market & location specific and per subscriber profile otherwise, it would be a nuisance for the subscriber. As interest in video entertainment has grown, so will the desire for the high quality of experience, or QoE, especially if a viewer is paying a premium for it or it is accompanied by advertising, since the advertiser wants to make the best impression possible.

Study from google search shows, One example provided in the webinar is Orange France’s partnership with streaming music service Deezer. The partnership boosted Deezer’s French subscriber base from 25,000 to over 1.2 million.


Orange brings its audience, billing, and data analytics to the table, and reaps the benefits of a more compelling sales offering and increased data usage among subscribers. Machine learning algorithms were deployed to boost more sales and deliver taste specific contents.


Points to Note:

All credits if any remains on the original contributor only. We have covered some high-level engagement on Blockchain and Artificial Intelligence in this post. In next coming, blog posts will talk about each one these emerging bundles in details.


Books and Reference Material

  • This article has a contribution from Sheetal as part of this post comes from her post from last year in LinkedIn. This was originally written by Sheetal Sharma (“Content-based value-added services for mobile customers”).
  • Research through open internet, news portals, white papers and imparted knowledge via live conferences & lectures.
  • Lab and hands-on experience of  @AILabPage (Self-taught learners group) members.


Feedback & Further Question

Do you have any questions about Telecoms, AI, Deep Learning or Machine Learning? Leave a comment or ask your question via email. Will try my best to answer it.


=========================== About the Author ====================

Read about Author  at : About Me   

Thank you all, for spending your time reading this post. Please share your feedback / comments / critics / agreements or disagreement / remark for more details about posts, subjects and relevance please read the disclaimer.

Facebook Page                   Twitter                  Blog                       Linkedin Pulse     ==============================================================

Posted by V Sharma

Technology specialist in Financial Technology(FinTech), Photography, Artificial Intelligence. Mobile Financial Services (Cross Border Remittances, Mobile Money, Mobile Banking, Mobile Payments), Data Science, IT Service Management, Machine Learning, Neural Networks and Deep Learning techniques. Mobile Data and Billing & Prepaid Charging Services (IN, OCS & CVBS) with over 15 years experience. Led start ups & new business units successfully at local and international levels with Hands-on Engineering & Business Strategy.

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s