e-tailers have been using big data (aka data analytics for years improve the customer experience, boost sales and minimize churn. It's time the telco industry caught up, says big data company, Ezako.
Analytics, predictions, recommendations and customization are some of the innovations that have been 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 minimizing churn is crucial, 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 five 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 page, what is their purchase funnel, etc. Tools like Google Analytics and Piwik are very widespread, and enable websites to track their audiences.
In telecommunications a few agencies, MÃ©diamÃ©trie 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 consumption, and even analyze 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 data collected may be used to predict future outages, and thus help save on maintenance and customer service costs.
2. Making more effort over the last mile/last point of interaction
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.
For telecommunications operators the last mile has always been a grey area and the source of many network problems. They install gateway and set-top boxes in end users' homes to enable internet connection (ADSL, VDSL, fiber, 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 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.
3. 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 analyze 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 load time for a web page is between one and two seconds maximum. Any longer, and the visitor goes elsewhere. If Google's display time is longer than half a second, it has 20 percent less traffic.
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.
4. Implementing recommendation tools to increase loyalty
In e-commerce recommendation algorithms has been used by e-tailers for several years. Thirty percent of Amazon's turnover is generated by recommendations. Seventy five percent 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.
Despite the fact that some telecoms players have started to show interest in recommendations, these are still few and far between. A recommendation algorithm 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.
5. Pushing 're-targeted' advertising
In e-commerce user who recently surfed online to find offers of holidays in Bora Bora will be presented with ads for holidays in Tahiti. These retargeting techniques are now reasonably well accepted by consumers. If well targeted and not overly intrusive, they can help catching consumers who would have left without buying, and help to double or even triple conversion rates.
Telecoms operators could also offer customized advertising on their boxes based 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. 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. The company is able to deliver to operators a list of customers dissatisfied with their triple play service, to generate alerts, predict equipment failures and faults, and to offer a recommendation algorithm for set-top boxes. Its solutions change every day.
Ezako was set up in 2011 by two big data experts, a former IBM architect and a Google developer. They got together during an open data hackathon to create a data processing project for the City of Paris. Following the success of the project, they created Ezako to make their technical know-how available to companies, first e-tailers, then telecom operators.