Think of the last app you used today. For me, it was searching for the latest episode of Sesame Street on HBOMax for my toddler. For someone else, it was finding a YouTube video on how to bake a cake. Or listening to a song recommended by Spotify. All of these instances, steps we barely put any thought into, are examples of content discovery, the bidirectional process by which users and applications interact, ensuring users’ known and unknown content consumption needs are fulfilled.
As content is being generated at a nearly unfathomable and exponential pace (think 500 hours of videos uploaded to YouTube every single minute), catching and holding consumers’ attention with content is only going to become more difficult. Delivering great content discovery experiences that meet evolving customer expectations will be the only way to keep up.
Content discovery happens in two ways, resembling push and pull forces:
Push (recommendation engines): Content is suggested to the user. This can look like personalized landing pages or content recommendations.
Pull (search): The customer searches for content, typically via a search bar. The user leads the action, and a new opportunity for suggesting relevant content is created.
Consider how you consume content. Maybe you’re searching for a show you want to watch, or once that show is completed, the app you’re using recommends another similar show you might like. If media providers can master both of these processes – accurate search and intuitive recommendations – you can expect to fuel user engagement and decrease churn.
Simple enough, right? Unfortunately, developing and deploying cutting-edge search and recommendation engines is easier said than done. A few major challenges stand in the way, like integrating data from multiple sources with excruciating extract, transform, load (ETL) pipelines, adding and maintaining a separate search engine solution, reduction in both time-to-value and developer productivity, and more.
Having a unified application data platform that can handle analytics at scale and search natively is a massive advantage for effective content discovery. Let’s look at how an advanced application data platform like MongoDB Atlas makes the push and pull of content discovery possible.