Picture this: Your newspaper's homepage is no longer a one-size-fits-all front page. Instead, it's a dynamic interface that knows each reader's preferences—giving them stories they care about while ensuring they don't miss breaking news that matters. This isn't science fiction; it's happening at one of the world's largest English-language newspapers.
In our latest episode of Newsroom Robots, I spoke with Ritvvij Parrikh, Senior Director of Product at the Times of India, who's been leading a groundbreaking transformation in how news is delivered to millions of readers. Over the past three years, his team has developed an in-house personalization system that has increased click-through rates by 85% on their website and 40% on their app.
What stood out to me most about our conversation was how the Times of India has solved a problem that many newsrooms struggle with: building AI systems that truly understand the unique rhythm of news.
Here are three key insights from our conversation that every newsroom should consider:
The Future of News is All About Personalization
Parrikh makes an interesting point: News media has always had a personal element. When newspapers launched regional editions, or TV stations created local programming, they were essentially personalizing content. The difference now is that technology lets us do this for each person.
"At the end of the day, users want what they want," says Parrikh. While social media platforms have mastered personalization, news organizations have largely stuck to traditional models. The result? We're losing the battle for attention.
What I found particularly insightful was how The Times of India balances editorial judgment with algorithmic recommendations. Unlike personalization on platforms like Netflix or Amazon, news personalization isn't just about user preferences – it's about maintaining journalistic integrity while serving reader interests.
Think Like a Mutual Fund Manager
Here's where Parrikh's insight becomes particularly interesting. He suggests that we start thinking about news content like a financial portfolio. Different revenue streams—subscriptions, advertising, affiliate content—are like different asset classes (such as stocks, bonds, and real estate). The key is to create a unique 'portfolio' for each reader based on their behavior and preferences.
For example, if a reader shows a high potential for subscribing, they might be shown more premium content. If they frequently engage with lifestyle content, they might see more affiliate opportunities. It's about finding the right balance for each reader while maintaining editorial integrity.
Data is Your Foundation (But You're Probably Doing It Wrong)
Many newsrooms rely on Google Analytics, but Parrikh argues this isn't enough. His team built their own real-time data pipeline because news moves too fast for day-old data. However, he emphasizes that collecting data is just the beginning—you need to manage it with the same rigor as a banking system.
In my conversations with newsrooms, I often find that the biggest barrier to AI adoption isn't the technology itself – it's the lack of proper infrastructure. Times of India's success shows why investing in these foundations is crucial.
The Road Ahead
The most provocative idea Parrikh shared? In the future, editorial teams will focus primarily on news gathering and verification, while AI systems will handle how stories are presented to different audiences. However, he cautions against jumping straight to the latest AI trends, like ChatGPT, without first building proper foundations.
"Recommender systems have been around in the market for almost 15 years, we've not fully adopted those," he points out. "Yet we're imagining we can participate in the LLM race."
This resonates deeply with what I've observed in the industry. While everyone's talking about generative AI, the real revolution in news might come from better recommendation systems that understand the unique dynamics of news content and personalizing a news experience for our readers.
"I foresee recommender systems becoming the operating system of the news business," says Parrikh. This means systems that can automatically balance editorial judgment, revenue optimization, and reader preferences – all in real-time.
As someone who spends every day exploring how AI can transform journalism, I find this vision compelling precisely because it's about building the infrastructure that lets great journalism reach the right readers at the right time.
The question isn't whether to embrace AI – it's whether your newsroom is structured to use it effectively.
🎧 Listen to the full conversation available now on Apple, Spotify, Google Podcasts, and other major podcast platforms.
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Personalization Vs. Editorial Judgment? At The Times of India, You Can Have Both: In Conversation with Ritvvij Parrikh