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KILA Systems: “Who knows, OTT operators may distribute other content.”

Damien Tassel, VP, Marketing and Business Development, KILA Systems

Damien Tassel,
VP, Marketing and Business Development,
KILA Systems

IP&TV News talks to Damien Tassel, VP of Marketing and Business Development with KILA Systems. KILA Systems provides the most advanced big data predictive analytics solutions, specifically designed to meet the needs of the Media Industry.

IP&TV News: Would you say that, when it comes to big data & analytics, connected entertainment is yet to appreciate the full potential of this technology?

Damien Tassel: Yes, certainly! It is only the beginning. Players are interested in Big Data, but I believe they have  not yet realised that concrete solutions are available now that can greatly enhance their business.

A few companies (like Netflix) are already using it and consider it to be one of their main differentiators. Considering the success of Netflix, I believe it should make them realise how important and urgent it is for them to embrace the Big Data tool. Netflix is an example of a VOD type of operator, but other types of businesses can also benefit from using Big Data, like TV Channels that have online services, IPTV and pay-TV Operators, OTT operators, and Publishers that have Video Advertising space to sell.

Really, the full potential of Big Data is not yet used. It is most probably the new frontier where Media companies need to invest in. Big Data, and even more Smart Data (predictive analytics) is the powerful tool that is needed to shape connected businesses into the changing video entertainment environment.

Could you give us some concrete examples of how KilaSystems could help reduce churn for an OTT client?

Well, KILA can help in a lot of ways! Once you have the behaviour analysis and prediction capability brought by KILA Systems, you have a powerful tool to understand your users, and shape your business accordingly. For instance, KILA Systems proposes a number of concrete business oriented applications, such as the capability to create several Marketing Models, based on the KILA engine, which can be used as segmented real time projections, reflecting tastes, behaviours and needs. Such marketing models can be attached to various services, devices, user profiles, geographical areas etc. that operators want to address separately. This is a powerful way to increase service stickiness

What distinguishes KilaSystems from its competitors?

What make KILA Systems different is the behaviour predictive analytics engine at the core of our solution. The Smart Data engine.

It is one thing to build a big data warehouse and extract indicators from it. It is a totally different game to have a reliable, real time analysis of user behaviours that can be used and is actionable to really act on the service provider’s business. And yet, this is where the potential of big data really is. This is about knowing users, and disposing of actionable ways to shape the service, real time, for users. From adapting the service to user, raising the value of video target advertising, to optimising the content offering for users, or entering a personalised dialogue with them, KILA Systems help operators to really shape their business in the changing environment.

Secondly, KILA Systems’ solution is dedicated to the video industry. We understand TV, video and entertainment. There is an industry specific aspect to predictive analytics. If you look at the Big Data industry globally, best performing solutions are the ones dedicated to a specific industry. An example is in the target advertising field. The targeted advertising industry is very structured. Yet, individual web browsing is a very different user experience compared to the video entertainment experience, where users are looking for something different. This is recognized by the advertisers that value the TV advertising at a higher price. The usage of a person when searching the web actively, or even sharing socially some links with selected friends, does not help so much in predicting his behaviour within a video entertainment service, where he is more relaxed and looking for being entertained. KILA Systems’ Video DMP for advertisement is founded on video entertainment analysis. When it comes to targeting ads in that field, or predicting impressions, we play in the same ground.

Are there any really surprising uses of big data that might not occur to people already working with it?

Today, a lot of people working in the field of big data have not yet tried the power of behaviour predictive analytics. As we have done it, we are sometimes surprised by the precision of predictions, and how well it reflects user wishes. This is where the surprises are.

People do not lie in front of their TV or video entertainment. If they do not like what they see, they would just zap to something else. That is very interesting to observe, and opens the way to further applications for Big Data, especially once merged with semantic word analysis. KILA is working on these lines, but is not yet ready to go public on it.

Are there developments in other areas of connected entertainment that particularly excite you as providing new opportunities for the use of data and analytics?

Today, we are active mainly in the video space, but we believe that other areas like music, press, books, or games will benefit as well from what we do. And who knows, OTT operators, which are really video content distributors, may well distribute other types of digital content. If they know their customer well, they might well decide that they can perform in these fields as well.

When you look ahead a couple of years, how do you see this technology developing? How big a part do you expect it to play in the future connected entertainment ecosystem?

Smart Data will play a very big part in the future connected entertainment ecosystem. We are all witnessing that TV and video entertainment face a paradigm modification. Two different paradigms look to be opposed today, with little bridges between them, and little bridges between user experiences.

  • The Mass TV paradigm, where the editorial line is the key value brought to viewers
  • User-centric entertainment, where the personalization is the key value brought to users

In fact, players involved in these two paradigms can both benefit from a customization of their service for their audience. Such customization will take different formats. I believe the ecosystem will be mostly modified by this evolution. Smart Data will be a key tool for that, as it brings the user insight necessary for it to occur.

It’s just been announced that KilaSystems will be at TV Connect 2014. What kind of conversations are you hoping to have there with operators?

We hope first that operators are informed that it is now possible for them to have a deep, unprecedented knowledge about their users and how they behave, and that they can have actionable ways to shape their business accordingly. This is the main conversation we hope to have.

We believe that their business will greatly benefit from that capability, and we are firmly convinced that gaining this knowledge is a key to drive their business in this highly changing environment. Operators can now investigate the behaviour of users across the many new ways they access video. Furthermore, they need to have a way to reach them where they are (which screen), at any time, with offerings and proposal that are well suited to each particular user experience.

Last point? We hope that operators will consider that they need to build that capability now, in a way that is independent from Internet giants, so as not to become dependent on companies willing to enter their business and become their competitors.

KILA Systems will be appearing at TV Connect 2014, 18-20th March. For booking and more info go here

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