How can MNOs make up for being 10 years behind in e-commerce?




By Bora Kizil and Julien Muller

Analytics, predictions, recommendations and customisation are some of the innovations used in e-commerce since the 1990s to sell the right service to the right customer.

Some VOD players in the telecom market have understood the importance of investing in recommendations, and are slowly gaining credibility in the market. In such a market where churn is a crucial stake, operators must look to the latest technologies and state-of-the-art knowledge to defend their market share, and even appropriate some from their competitors.

The French start-up, Ezako, has roots in the world of e-commerce and is a Big Data specialist in the telecom industry. The company gives us 5 key takeaways that telecom operators can learn from e-commerce.

  1. Understanding end users to refine their offering and anticipate failures 

In e-commerce: E-tailers use analytics tools to track their end users anonymously, and in real time: where they click, what pages they visit, how long they spend on each various page, what is their purchase funnel, etc. Tools like Google Analytics and Piwik are very widespread, and enable websites to track their audience.

How about in Telecommunications? A few agencies, Médiamétrie in France for instance, are able to recover audience data from a representative sample of the population. But today, we can do much better. If well managed, Big Data could already enable operators to know the number of people connected within one household, the channels they watch, the time they spend channel-surfing, OTT and VOD consumptions, and even analyse the quality of the service provided by monitoring the WiFi connectivity ratios, or macroblock issues for example. The Operators would not only be able to have a detailed view of the use of their network, but also of its condition. In addition, the Big Data collected may be used to predict future outages, and thus help save on maintenance and customer service costs.

  1. Making more effort over the last mile: the last interaction that is the closest to end users 

In e-commerce: Major efforts are made to improve the compatibility of e-commerce website display with all the browsers on the market, as well as the various devices: PC, Mac, tablets and smartphones. Technologies such as HTML5 and responsive design techniques have been invented.

How about in Telecommunications? For the operators, the last mile has always been a greyarea and the source of many network problems. They install gateway and set-top boxes in end users’ homes to enable internet connection (ADSL, VDSL, fibre, cable, WiFi), VoIP telephony and television (mainly IPTV or DVB) services. The brands and generations of this equipment are very diverse and difficult to maintain remotely. This material diversity may cause end-user frustration when using these services.  Operators need to be able to track the problems and understand how to solve them. A last-mile monitoring tool can turn out to be very useful for this.

  1. Upgrading end user interfaces to improve the customer experience 

In e-commerce: The interface and design of e-commerce websites change regularly. It is usual to analyse the data to study the customer’s visiting path in order to constantly improve it, offering a better experience and quicker browsing. Thanks to this data, we know that the acceptable display time for a web page is between 1 and 2 seconds maximum.  Any longer, and the visitor goes elsewhere. If Google’s display time is longer than half a second, it has 20% less traffic.

How about in Telecommunications? Telecom operators could do the same by measuring the activity of end users and understanding how they use telecommunications. They could change the interfaces of their set-top boxes to make browsing easier, for example, to avoid too much clicking or to choose the best positions for the menus and redesign remote control short-cuts.

  1. Implementing recommendation tools to increase loyalty 

In e-commerce: What could be better than a service that predicts what you want? Recommendation algorithms has been used by e-tailers for several years. 30% of Amazon’s turnover is generated by recommendations. 75% of Netflix’s traffic is generated by recommendations.  Furthermore, Netflix invests a significant amount of funds in predictive technologies: $150 million per year! It is now the leader on the SVOD market, available in 190 countries.

How about in Telecommunications? Despite the fact that some players have started to show interest in recommendations, they are still few and far between. This tool is a real conversion lever, one which makes consumers’ lives easier and which operators would be wrong to ignore. There are numerous possibilities: whether it be to offer a selection of films in VOD, to counter the Netflix effect, or OTT services. The margin of progression and possible earnings for operators is very high, as recommendations are a way to keep the end user interested in the services offered and improve their loyalty.

  1. Pushing “re-targeted” advertising 

In e-commerce: You have recently surfed online to find offers of holidays in Bora Bora. What do you see a few days later? Ads for holidays in Tahiti… These retargeting techniques are more or less well-accepted by consumers. If well-targeted and not overly intrusive, they will help catching consumers who would have left without buying and help to double or even triple the conversion rates.

How about in Telecommunications? Operators could also offer customised advertising on their boxes depending on the tastes of each customer, their media consumption, the films they watch and how they channel-hop. They could use this to better target advertising, offer new economic models and to ultimately offer a better service by increasing the conversion rates of their advertisers.

These are some examples of the best practices to be applied in the telecommunications sector. Thanks to its expertise in e-commerce and Big Data, Ezako has developed Big Data solutions dedicated to this sector, such as data collection, data analysis and monitoring, to accompany the telecommunications industry in this digital transformation. Precise use cases have been developed with prestigious customers.

(The authors are Bora Kizil – a graduate in Artificial Intelligence from Dauphine University, Paris, with an MBA from HEC Paris, ex-Director of Rocket Internet / e-commerce specialist  – and Julien Muller – a graduate in Artificial Intelligence from Dauphine University, Paris, ex-IBM – Big Data specialist and architect).




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