IT Leadership

Analytics & AI Game Changers for Media & Entertainment Industry: Zee CTO

Indian media and entertainment (ME) industry is today in the middle of a vortex. The uprising of digital platforms has transformed the entire competitive landscape. As traditional television channels compete with new age digital players and strive to stay relevant through adopting an omni channel avatar, the onus to succeed comes to rest on technology.

However, being the Chief Technology Officer (CTO) of a ME company in the midst of such exciting times may not be everyone’s cup of tea as the position calls for a unique combination and balance of responsibility and unrestraint. Rajneesh Mittal, CTO, Zee Entertainment, fits the bill perfectly as he strives to transition Zee from a traditional and diverse media house to a new age omni-channel (traditional and digital both) media conglomerate.

Mittal avers that the new age media, like OTT, is all about technology. Therefore, the focus for the company will be on investing in the latest technologies, whether it is honest and practical digital transformation, business data analytics, using AI-ML to enrich content metadata, getting content to the screens faster or giving viewers a great end user experience, wherever they are, irrespective of the connectivity they have.

For Mittal, most of the technology investment decisions today boil down to two key drivers – giving a great end user experience through understanding consumer behavior and monetizing content. Towards that end Artificial Intelligence/Machine Learning based analytics will play a critical role and is enlisted on the top of the company’s technology roadmap.

Mittal has identified a few use cases of AI and is in the middle of trialing them within the organization. One such use case is around movie acquisitions for its various channels. The decision around which movie to buy and at what particular price point is a complicated one and based on multiple factors like what is the current library, what’s our need, GRPs coming out of that library, how many rights of movies one has, when and what particular library is available in the market, past ratings and sales data consumer preferences, etc.

The analysis done today is based on the human intelligence – the people who know this trade. But this, as Mittal points out, is not a repeatable and scalable model as the data sets are exploding and it becomes humanly impossible to assimilate and derive patterns out of this vast data sea. He intends to use AI/ML to analyze all the data and let the systems throw up interesting hypothesis which then mixed with human intelligence can lead to better business decisions – in this case which movie to buy and what’s the right price.

In a related use case of machine learning and analytics being trialed, Mittal is trying to work out the automated scheduling of programs on various channels in the best and most optimized manner to achieve the pre-defined targets.

The company is eyeing use cases of machine learning on the content front as well. Today the meta tagging of the content is done manually, which means one has to tag all the content scene by scene, object by object to realize some important use cases such as contextual advertisements or efficient post production. With a repository of over two lakh hours of content, manually tagging the content is a humongous and time and resource consuming task. However, it is critical as tagging is key to monetizing the content effectively. The company is trialing automating this process through AI.

Another critical area where he is looking at using the technology is around understanding and analyzing the socio environmental factors, audience behavior and preferences, etc. to help determine what kind of content to commission. “As we have a huge presence in digital space, there is lot of data coming from there as well. One would know to the most granular level possible that this particular customer with this particular demographic details is interested in watching this particular content. Serious data analytics can help us really paint a picture of what kind of content is working and what is not, which can help guide our creative teams.”

Simultaneously the company is readying its backend to enable all these use cases. It is trying to organize its data in a flexible data lake & logical data warehouse based architecture where one doesn’t have to worry about the data schema anymore, or bother about what data will come and when it will come. Which means that one can just dump the data and analyze it when required. Thus, reducing the dependency of business users on IT and enabling them with self-served business analytics.

Mittal is quite bullish on analytics and AI as the big game changers for the ME industry. He believes that some of these technologies are perfectly suited for media industry and we can actually leap frog from here leveraging these. However, as Mittal rightly concludes, first and foremost is the content and everything else revolves around it and feeds from it too. The technology will digitally transform the entire content lifecycle and supply chain and power the change that’s upon us in this industry.

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