It’s the crisis period. A worldwide lockdown was thrust upon you. While you’re already used to sitting on that couch occasionally to ‘Netflix and chill’ after a tiring workweek, this time you don’t have other alternatives for entertainment beyond that couch. You’re browsing through the content across all OTT platforms and eventually end up binge-watching innumerable shows. All of these suited to your taste, almost tailor-made for you.
In the end, you’re possibly a satisfied consumer of the content. Better still if you belong to the other end, the one involved in serving this content.
Understanding consumer behaviour is imperative when providing tailor-made solutions to users and AI plays a major role in generating favourable outcomes. Machine learning algorithms are fed with data segmentation through various patters. Continuous learning of these complex data sets enables machine learning (ML) algorithms to predict and recognize similar patterns at a future stage. According to the Netflix Research Centre, machine learning impacts many exciting areas throughout their organization, personalization being the most well-known area. Recommendation algorithms are also powered by ML that drive you towards the content of your choice.
1. Crafted for you- Personalization is possibly a major differentiator when serving a customer. Tailor-made recommendations suiting customer needs are being driven at scale using AI. You’re almost finished watching Special Ops, an investigative drama on Amazon and before you know it, the next recommendation is Criminal Justice, another series; similar genre. You cannot help but give it another look! You’re caught!
2. Immersive Experiences- Satisfying the need for human involvement in activities, immersive content powered by AI through augmented and virtual reality(AR and VR) make you co- creators. Imagine playing the PlayStation with your children.
3. Analyzing RoMI- AI enables gauging return on Marketing Investments and helps in analysing user consumption patterns so you may serve the customer effectively.
4. Sourcing and Optimizing Content- This includes transforming content delivery through predictions and optimising delivery along with procuring digital rights, securing the rights and preserving the IP.
That said, AI adoption in Media and Entertainment comes with its own set of challenges.
1. Data Engineering at Scale– Engineering & governance is required for unstructured data along with licensing third party content at scale and this can be a costly proposition.
2. Filtration- Content Filtration for the society, especially with respect to children remains a challenge for most AI powered entertainment channels.
3. Biased Algorithms- Predictions through data also involve a significant bias and thus lack consistency with respect to the results.
The world is at the helm of business transformation. There cannot be a better time than now for businesses, especially the media industry to prioritize and strategize AI related initiatives.
How would you approach strategic AI implementation across your organization?
Come on, you cannot read this and get back to scrolling the screen for your next binge.
Tell us what you think in the comments below!
Read the full report on Uncovering the True Value of AI to understand how AI impacts key industrial sectors.