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Zee Entertainment’s Tryst With Data Science

Zee Entertainment’s Tryst With Data Science

With the entertainment industry getting quite competitive, new age technologies like artificial intelligence and analytics is helping it grow and widen its viewership. Zee Entertainment, owned by the Essel Group, is already making the most of it. From delivering a personalised experience to churning out customer insights into investments, they are in with the times.

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Analytics India Magazine caught up with Venkat Nettimi, who heads the strategy and consumer insights at Zee Entertainment, and has brought various analytical tools and processes at Zee. Having worked with the likes of Amex, Citigroup, CIBIL and others, he brings a diverse experience from across several geographies. As he shares, he has had the opportunity to see amazing changes in the world of analytics over the years — from manually tabulating results to using complex analytical solutions.

Over the last one year, Zee has implemented mobile-based analytical solutions which are enabling decision-makers to get access to critical information and cut down the analysis time by nearly 90 percent. He also strongly believes that AI and machine learning-based predictive analytics will help better understand the consumers and their content preferences.  

Entertainment Industry And Analytics

While Nettimi has an in-depth experience across industries like consumer packaged goods, financial services and media, the essence of using analytics has been the same — how can we solve a business problem x using data y? However, the shape of x and y varies according to the industry.

For instance, in the CPG industry, a lot of problems are solved using consumer feedback and transactional retail data. Financial services have a distinct advantage, thanks to the vast and exclusive transaction histories available to them. However, his journey in media has been different and exciting. As he notes, unlike other industries, the key information on which their business runs are the audience measurement data provided by BARC. It is both their monetisation currency and critical input for audience understanding. And unlike that for other industries, this data is not exclusive to any one player and is available to all.

“Thus, data and data availability is no longer the differentiator. It is purely the analysis you do with the data that differentiates you from the other and provides you the competitive edge. In some ways this hones your analytical ability like no other industry does,” he says.

Use Cases From Zee Entertainment

Nettimi’s focus at Zee has been two folds — to increase the breadth and usage, and the depth of analytics solutions within the firm. He shares that not everyone in the firm was comfortable with the use of data and analytical tools — especially the content and creative teams. “They were highly dependent on their insights people to extract and share the ratings data with them, which created bottlenecks in decision-making by taking time away from the insights team’s bandwidth for more value-added analysis,” he said.

Since then they have introduced highly visual and intuitive Tableau-based desktop and mobile dashboards that have truly democratised data usage within the firm. Especially useful are the interactive mobile dashboards, which address almost 90 percent of routine queries.

“To increase the depth of analysis, we have been focusing on adopting cutting-edge analytical tools, including AI and ML-based predictive analysis, image recognition based meta tagging etc.” he said. They are also adopting tools used in other industries such as for discrete choice modelling and market basket analysis for better decision making.  

“In addition to the use of advanced data analytics, we’re also augmenting our understanding of our consumers via more qualitative methods such as consumer immersions, ethnography, observational studies, Neuroscience etc,” he said.

Consumer Insights And Machine Learning

Nettimi is quick to add that one of the most interesting projects that he has ever led includes ML-based automated scheduling of their movies library. With over 10 Pay movie Channels, 3,500 library titles, 5,500 hours of movie scheduling per month in the category, optimal movie scheduling can provide an extremely important competitive advantage.

Since a majority of their titles are library content, historical data can be used to predict future ratings and this helps them in:

  • Manage their library more efficiently
  • Reducing the man-hours used in scheduling
  • Increase our ratings.

“So it’s one of those projects that addresses cost and revenue drivers at the same time,” he added.

He is also leading a project focused on harnessing content learnings using tech. With over 200,000 hours of content produced every year, they are trying to build an understanding of what content works best for them, for which AI comes into picture. “Using AI-based meta-tagging of video content (characters, emotions, setting etc.) and correlating it to the BARC ratings is enabling us to understand what content works – at scale,” he said. He also shares that they have started using algorithms for ratings and predictions, especially for their movie offerings. “I also see recommendation algorithms becoming more and more important in the near future,” he said.

Analytics For Making Investment Decisions At Zee

“Analytics is absolutely at the core of every decision we make at our firm. Considering our ratings information is also our monetisation instrument, it becomes an extremely important input for decision making,” he notes.

It helps them in understanding what content works for them, guides purchase decisions on shows and movie libraries, understand client (advertiser) needs and develop the best possible solutions to address their advertising needs. Importantly it helps them in large investment decisions such as the launch of new channels or rebranding and relaunch of existing channels.

Nettimi shares that their recent launches in English movies space (& Flix and & Prive) and upcoming regional channel offerings are the results of understanding viewer preferences and trends via ratings data.

Data Visualisation And Analytics Tools At Zee

Nettimi shares that currently they have a distributed model for the Insights function within the organisation, with each business having embedded and dedicated insights and analytics SMEs. There is a central team which drives key strategic initiatives and innovative analytical projects. There over 50 people working in this space within the Domestic Broadcast business (excluding Zee5).

“Tableau has been embedded within our organisation for a while now and we’ve members being trained in R as well. We also work with a wide array of small and large data analytics firms to help bring in fresh outside perspectives in analytics,” he shares.

Competing With Other Players In OTT Space With Analytics

Zee has always been a pioneer in the online and OTT space. Much before the launch of Zee5, Zee was offering Ozee and Ditto to address the consumer needs of Anytime TV and Catch Up TV (both of which have been integrated into the Zee5 platform).

“In addition to the rich viewership data available on the platform, which enables us to model consumer preferences and develop content recommendations, we also use other data sources to augment our understanding of consumers. For example, a key focus has been on using social media data to gain feedback on our shows, understand the broader narrative of topics which our viewers are interested in and, thus, enable us to have an ‘ahead of the curve’ listening ability on key themes which are important to our consumers. This helps us make better content decisions,” he said.

Challenges And Roadmap

“It’s an exciting time to be in the analytics space,” theorizes Nettimi. “The availability of different tools, techniques has increased exponentially over the last few years. However, in some instances the pace of adoption of new techniques has not kept up with the rate of pace of innovation of the same. Sometimes there is a tendency to fall back on “tried and tested” methods as opposed to new and innovative methods. As an analytics leader, a significant part of my work involves educating internal stakeholders on the benefits of these new techniques,” he says. On the flip side, sometimes there is a rush to adopt the “shiniest new toy” in the analytics space without fully understanding whether there is relevance of it to the business and whether it will add value.

Also with an increasing volume and velocity of data, one of the biggest challenges is to be able to make sense of it all to drive profitable business decisions. “One of the key initiatives in place is to bring all the data available across, not just media, but the Essel Group of companies onto a common Data Lake that will enable us to leverage opportunities across sectors. We’ll also continue to build our data analytical abilities and move some of the work from our partner agencies internally,” he said on a concluding note.

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