Data monetisation is about leveraging data sets to deliver ROO & ROI: LV Krishnan, TAM

At Knowledge Conclave organised by Advertising Club Bangalore, Krishnan, CEO, TAM Media Research, spoke on the 'Science & Art of Data Monetization' to elevate the customer experience

e4m by exchange4media Staff
Updated: Nov 30, 2019 9:41 AM


LV Krishnan TAM

"The audience media data sector is valued approximately Rs 1150 crores", said LV Krishnan, CEO, TAM Media Research. Krishnan was speaking at the knowledge conclave organised by the Advertising Club Bangalore. The theme of the conclave was titled Driving growth through the new era of measurement.

Krishnan spoke on the topic, 'Science and Art of Data Monetization' to elevate the customer experience in the Indian market. His talk was centred on the concept of data monetisation, the use cases and insights into how data monetisation can be done and what future holds.

“Before I talk about data monetisation, I was evaluating the kind of money that is being pumped into media audience data in this country. Today if I put all value creation from subscription-based data it stands at Rs 1150 crore and achieved a growth of 1500 per cent growth in 2 decades. The annual growth rate which is driven by fast-changing consumer habits is 20 per cent. The factors that cater to this growth are the rise of more distribution platforms, content explosion etc,” said Krishnan.

He continued, “The total amount of media spends that is happening in terms of advertising, subscription, licensing of content etc which is almost close to Rs 100,000 crore and the money which is used for research to make decisions on that amount is just one per cent. ”When we look at the pie of the top 3 media platforms, with segments such as cinema, outdoor etc added, it comes to Rs 160,000 crore. “Today with all the smartphones, set-top boxes etc, there is a plethora of data available with anyone. So, as we go along there is going to be new data flowing into the market. There arises a question of what are we going to do with these data and that’s where the concept of data monetization emerges,” said Krishnan.

Elaborating on the concept Krishnan said, “Data monetisation is all about leveraging existing data sets and creating new ways of harnessing new sets of data combined with analytics prowess- to deliver ROO (Return on Objectives and ROI (Return on Investments)“ Krishnan further spoke about the ingredients that will make data monetization happen.

“The first factor is extensive historic data, the more the past data you have in hand, the richer future data will be. The second ingredient is the multimedia platform. The more different media platforms throw up data, the more interesting it becomes to bring those data into one single exercise and deliver that for decision-making purposes. The third important element is the platform that enables you to aggregate data and put that data into place. These three ingredients power data monetization to a large extent.”

He continued, “To make data monetisation work you need extensive meta-tagging,” he said. Krishnan further elaborated the concept of meta-tagging.  “There are different layers to the meta-tagging that happens. When you see a video on YouTube, at the back end of the video, meta-tagging to the finest level happens. For example: When you do a search for sixes hit by Sachin Tendulkar, the video comes into play and that helps you to get a better view of particular content if the curation of that content is perfectly timed with your search in nature. But in meta-tagging, when you try to combine data, the problem comes in when you have tagged that in specific layering, the data that you are going to add together is tagged in a different manner completely. Therefore, each of the two databases does not talk to each other. Then you need to re-classify the data so that both work together in conjunction to give output.”

Krishnan further explained, “AI platforms allows you to mix those databases so that when you layer one on top of each other, it gives you an output which helps you in decision making”.

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