The past two years have given way to massive news cycles with COVID, Trump’s administration, and the withdrawal of US troops from Afghanistan. That means it’s only natural for this cycle to end. We’re already seeing a decline in page views across news sites as users are burnt out from online activities. What’s really happening is a normalization of page views, back to pre-pandemic levels. Now the key challenge will be to continue revenue growth with less page views; in other words, doing more with less.
It’s also been over three years since major browsers like Safari and Firefox announced their intention to fully phase out third-party cookies, the key mechanisms that have powered ad personalization on the modern web. With Google set to follow suit by the end of 2023, the death of cookies is now truly upon us, making the media owner industry very nervous about what will happen to their monetization strategies thereafter.
However, I can say with utter certainty that the digital media industry is adaptive, fast-paced, and always finds a way to survive. A shift away from cookies will be positive in the end as this will drive the industry to lean on machine learning and automation to achieve advertisers goals whilst respecting the privacy of users.
Social channels like YouTube and Facebook are completely AI-driven – meaning there’s no human contact for content recommendations and algorithms to control the feed. It’s rapidly changing the media landscape due to its host of benefits and ability to get even smarter over time.
By leveraging machine learning, we can find patterns based on a range of criteria such as audience behavior, context, aggregated learnings, first- and third-party data. It does this by considering all information about a given individual, such as demographics and online behavior, to make an informed decision on the type of content a user actually wants to see.
AI can deliver insights that inform editorial and advertising decision-making by going beyond traditional A/B testing to make data-based predictions about how creatives and messaging will resonate with customers. This allows advertisers and publishers to move from reactive to proactive in their approach as they are recognizing the importance of targeting the right person with the right ad to drive conversions.
Facebook and Google have grown because they have tailored their recommendations, making the whole experience engaging and to some degree addictive. Publishers can use a similar model by embracing machine learning as a way to not only maximize advertising revenues but also optimize user engagement with their own content.
At its core, publishing and creating content is an art. Content developers have engaged audiences for centuries, bringing stories and narratives to life. Great publishing and storytelling has always been about both art and science, and nowhere else can these two approaches collide so fluidly than in the digital space. AI and machine learning are relatively new contributors to the industry that can help publishers apply the latest technologies to zero-in on what truly drives engagement.
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