In today’s world of advanced algorithms, online consumers have come to expect content personalization and accurate recommendations as a given from media companies. They want to feel that a company recognizes them, understands their needs and can deliver.
Netflix and Amazon are highly successful at doing this. They both employ AI-powered algorithms that use consumer data to make real-time recommendations based on that user’s specific interests.
Publisher’s can do this, too, with AI tools like enhanced user profiling, which allow them to:
- Tailor marketing campaigns to specific audience segments
- Give individual users entirely unique online experiences
- Dynamically configure products or services for each customer
The whitepaper also looks at how AI algorithms can be used to deliver personalized ads to consumers. This improves targeted advertising efforts by allowing publishers to offer advertisers highly specific and engaged audiences. In turn, this increases revenue potential.
How personalization efforts improve audience engagement
Through its ability to analyze vast amounts of data and tailor content to individual preferences, AI-driven personalization significantly enhances audience engagement.
Using AI tools to generate tailored content experiences, recommendations, and targeted ads also allows publishers to focus on tasks that require the human element, like crafting compelling narratives and ensuring cultural relevance is upheld. This is critical for creating personalized content strategies that truly resonate with audiences.
Other AI-driven personalization strategies discussed in the whitepaper include:
- Optimizing native ad placement: AI technology turns data into personalized ads that blend seamlessly with the chosen platform and drive higher engagemen
- Leveraging AI-driven subscription models: AI algorithms utilize customer data to allow publishers to curate their services to the unique needs of subscribers. Doing this can help you outperform peers by 85% in sales growth
- Community building: AI analyzes user data and facilitates audience segmentations so that publishers can excel at fostering engagement, building relationships and responding to feedback in a personalized and relevant manner
In the whitepaper, we analyze the New York Times’ 2021 case study on how they enhanced user engagement, increased click-through rates (CTR) and boosted subscriptions with a new AI-driven recommendation system.
Here’s an overview of the positive impact it had:
- The CTR on the Editor’s Pick module increased by 55% as the AI system was able to make regionally relevant recommendations
- NYT were able to achieve increased user satisfaction, longer session durations and improved user retention rates
- They also increased paid subscriptions to 9.6 million in 2022 and experienced an 11% revenue growth from 2021-22
Statistics on the value of AI-driven personalization
The value of AI-driven personalization strategies is seen in the following statistics:
- Companies that excel at personalization generate 40% more revenue
- 76% of surveyed consumers said personalized content encourages them to buy
- 71% of consumers now expect companies to deliver personalization
- Active personalization efforts increases engagement for publishers, including Gannett (60% increase) and Mediahuis (23% increase)
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