- To improve content discovery and user engagement across its news and mobile sites, Astro curated a more personal and relevant content experience for readers.
- The media publisher applied an automated content tagging system and created custom audience profiles based on reader interests.
- The personalized approach to content resulted in a 258% increase in article click-through rate (CTR).
- Astro is now considering expanding this personalized content strategy across the organization.
Astro—a leading media organization based in Malaysia with business holdings in satellite TV, radio, events, outdoor advertising, and video-on-demand—owns and operates hundreds of news websites and mobile apps to bring news, sports updates, and entertainment to Malaysians at home and overseas. With so much content being created and produced, one of Astro’s key concerns was making its digital content more relevant and engaging to audiences on its sites and apps.
At the heart of its content strategy is a newsroom where the digital analytics and editorial teams work hand in hand. The analytics team used Google Analytics 360 to measure daily performance—page views, bounce rates, and time spent—and user engagement on its sites and apps, which, in turn, informed the editorial team on what stories, videos, topics, and sections were resonating with readers.
But Astro wanted to move beyond measuring engagement metrics and instead curate a more personal and relevant content experience for readers. This, in theory, would lead to higher engagement on the sites, which would help Astro better monetize its sites by matching the right ad to the right reader and content.
Curating a more personal content experience
In order to prove its hypothesis, Astro’s digital analytics team worked on a pilot project with Kasatria, a Google Marketing Platform partner.
For each piece of content to be easily searchable, Astro’s editorial team used relevant content topic tags relating to each article or video, like “sports,” “football,” or “tennis.” But to properly scale and cover the full breadth of content its readers were reading and watching, Astro needed to automate a content tagging system that would relay this information to Analytics 360.
Using Google Tag Manager 360, Astro identified the type of content on each article every time the page was loaded and shared the information with Analytics 360. This was then connected with Google BigQuery in Astro’s machine learning algorithm, which built customer profiles based on their interests and recommended personalized content for each reader. For example, a person interested in tennis would be shown a video about Roger Federer or Rafael Nadal, while a reader interested in football would be shown the latest English Premier League results on the same website.
This is what the workflow looked like:
A successful pilot
This personalized approach to content recommendation proved that serving relevant content to the right users would increase audience engagement.
The pilot program resulted in a 258% increase in article CTR, and readers were also 55% more likely to share the content with their friends.
As a result, Astro is now considering expanding this personalized content recommendation strategy across its entire media organization.
"Through an insights-driven strategy, we were able to predict a visitor's interest with an impressive level of statistical certainty. This resulted in tailored content for each visitor based on their preferences and, more importantly, a more relevant user experience," said Mohd Ridhuan Sidek, Astro’s chief digital officer.