What could be more personalised than letting the user themself pick the content they want to consume?

So, India’s HT built a chatbot that lets readers ask questions about business and economic news. It recently went live on one of HT’s sites, Mint, which specialises in financial news. 

Yudhveer Mor, chief product and technology officer at HT Media in New Delhi, said it was very important to his team to understand the source of the data. That was a challenge in abstract language models. “We are now using models that were trained on our articles.”

They have limited the use cases for chat to content that is suitable for Mint, he said. “For example, on Mint, I don’t want people to ask about the weather outside.” A user on the site is offered a list of sample questions to pick from, based on the biggest news stories of the moment.

HT has been impressed by the high click-through rate and level of engagement with its chat. 

“It’s a very big step in how people are consuming content,” Mor said. “Our devices tend to be very immersive. In a chatbot, you are nudging people to look at least five options and click on one of them, instead of just passively scrolling as content is streamed to them (as on Instagram). That additional user intervention is pretty hard. A user may spend five minutes on the Mint app and 50 minutes on Instagram. How to bring it naturally to them is my focus area.”

Another AI application is, of course, recommendation engines — but not just for the reader.

“How can we do content recommendations? For the user: What is the next article you should read? And for the content team: What is the next article you should write? This is something we were able to leverage. We fully understand the same size won’t fit all,” Mor said.

Almost 90% of the visitors to HT Media’s sites are first-time users, so personalisation cannot be based on specific information about that person, Mor said: “For first timers, what is the propensity to read further? OpenAI helped us a lot with that. We would put an article in ChatGPT and ask what they will read next. That started driving a lot of engagement for us.

“We haven’t yet achieved our full potential. We are just scratching the surface right now. It has opened our thinking process.” 

HT is also experimenting with text-to-audio and text-to-video features. They tried a feature where users could listen to articles in an Indian accent, but usage turned out to be low.

“The opportunity cost is very low now with all these tools,” Mor said. “This is a great time to do as many experiments as you can.”

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