Is Personalized Discovery A Feature, Category Or New Paradigm

What do you do when you don’t know what you want to read, watch, listen to or do next? What do you do if you don’t know what to search for? Or can’t describe clearly what you’d be interested in next?

There are so many great choices available in the digital realm, and new stuff is pouring in every second. Many times we feel helpless in front of such an abundance of endless possibilities.

Nevertheless, so far no one has created a solution that would automatically bring all the interesting options to your fingertips without you asking for it. A universal personalized Discovery solution doesn’t exist yet. Why?

Personalized Discovery Today

There have been various attempts and approaches to crack personalized Discovery — at least partially.

StumbleUpon has been around for a while. The app provides content based on selected categories and other “Stumblers” you follow. Flipboard’s personalized magazine has transformed into a social news platform. You personalize your own experience by curating content sources and following people. Pinterest, too, has a follow model for people, their content and topics. Its Guided Search with combinable keywords works as an additional interface alongside the curated feed.

Pocket recently released its Recommended section that provides content based on the things that you saved for later. Google Now delivers useful information based on your previous actions and historical data. And Facebook is just entering the game with its M that supposedly recommends actions and content.

Most of today’s Discovery solutions resemble social media’s friendship or follow paradigm. You follow people and their content or you follow selected keywords and categories to personalize your own experience. However, this paradigm tends to reinforce our existing information silos. By directly customizing things for ourselves, our social and personal biases restrict the way we expose ourselves to new information.

Additionally, it becomes hard to estimate how much personalization actually happens automatically and how it helps us in discovering things. The wider the pool of information, the more we have to work to detect the signal from the noise.

At the same time, the user experience of a purely machine-powered approach hasn’t still crossed the “uncanny valley.” A machine telling us what we should be seeing and doing next has a dystopian aura, even in very mundane circumstances. Many times the algorithmic suggestions that don’t directly reflect our social environment or past interactions appear to be too obtrusive or outright ridiculous. Indeed, machine-powered Google Now focuses on delivering useful information instead of new explorative choices.

Discovery currently exists as a category of Internet services and apps, as well as a functional feature in some content-specific platforms (e.g., Spotify and Snapchat). But no one has come up with a universal Discovery paradigm for the mainstream audience.

The Unsolved Discovery Puzzle

There are five main challenges faced by the universal Discovery solution:

Clear Value Proposition And Use Case. Universal Discovery lacks a clearly defined value proposition, and thus a crystal clear use case. Why do you need universal Discovery in the first place? In Search we are looking for specific and relevant answers. In Social we’re connecting and communicating with other people. But how do you define a universal value proposition and use case for something so highly subjective and contextual as Discovery?

People don’t think consciously that they are “discovering” something. They might not even recognize a need for “discovery.” On the contrary, a discovery happens often as a by-product of some other activity.

Frictionless User Experience. Current mainstream user interfaces and experiences haven’t been designed, developed or optimized for Discovery. For example, the news feed and its variations provide a very linear and limited way of presenting information. Personalized Discovery requires a new design approach because finding interesting choices includes potential effort and friction.

Trial and error can form a significant part of the exploration process. Friction emerges when we encounter unexpected choices or when we need to wait for something to happen. Additionally, the experience should proactively pique our curiosity, simultaneously outweighing our personal and social biases.

Technologies For Adaptive Personalization And Content Presentation. Creating a universal Discovery solution brings together two major technological challenges: unobtrusive personalization and sleek content delivery. Adaptive personalization requires an unseen level of automated customization based on our intricate selves. To achieve this, the system needs to be able to capture our meaningful interactions and utilize our diverse personal data.

Current applications of personalization using human curation, algorithmic systems and machine learning methods — or their combinations — don’t yet learn or deliver fast enough, nor do they let us express ourselves as unique individuals. Concurrently, the various forms and types of digital content are messy, and require a lot of sophisticated processing to be presented fluently in various screens and devices.

Accessible Data And Content. The almost infinite sea we call the Internet has become a collection of confined ponds with their own walls and rules. Platforms build their own understanding of you, and usually they don’t let you control how your data could be used for your own benefit in other places.

Simultaneously, an increasing amount of content is becoming platform-exclusive. Major social platforms are becoming content silos, enabling exploration on their own terms and only inside their own boundaries. Media houses are locking their content behind specific access points.

Discovery Paradox. Additionally, there’s an inherent tension in combining personalization and Discovery. Personalization is about customizing your experience, guiding your choices and serving information based on your needs and personal preferences. Then again, discovery refers to the things that are somehow new and surprising. Indeed, discovery can be as much about questions as it is about answers. It can be as much about irrational and serendipitous as it is about rational and relevant.

The things that you recognize as meaningful discoveries aren’t necessarily what you expect them to be. You might encounter something you didn’t know you wanted or you didn’t even know existed. A discovery can be very personal and context-specific, thus being meaningful only to you.

So, is there a way to overcome this multitude of complex challenges? Or is the universal Discovery solution just a Fata Morgana of the early age of personalization?

How Could Personalized Discovery Work?

A truly smart universal Discovery system makes sense. The amount of information is exploding, and we need better methods to make sense of it. At the same time, the current tools provide only a restricted access to the information that is beyond our personal and social bubbles.

Personalized Discovery can find a balance between relevance and serendipity, as well as rewards and friction, by creating favorable discovery conditions for you as a unique individual. The system understands your articulated and ambient interests by mapping the unique connections you see around you.

A universal Discovery system provides choices instead of the one specific answer. By understanding your interests, the system can expose you to things that you find surprising, even challenging. Simultaneously, it provides meaningful information in easily digestible chunks that let you choose your preferred level of engagement. The presentation is modified based on content form, type and context. To serve content from diverse sources, the Discovery system taps into the free as well as paid content pools on your behalf.

As the amount of potentially discoverable information is almost infinite, human curation and algorithmic methods are used to complement each other. Curation can be made a seamless part of the basic Discovery flow. Your actions curate content for other people and educate the system at the same time. The nuanced human assessment of quality is thus interwoven to the machine-powered dynamics such as prioritizing recommendations and presenting information.

In Discovery, goal-driven and casual experiences can coexist. The system brings together various content and action categories such as books, music, movies, travel, food, dating and news. By understanding your preferences with movies and the latest pop culture news — and being able to detect your current mood — the Discovery system recommends new interesting music choices. Also, it can surface interesting weak signals and unseen opportunities. By understanding your daily activities, it can serve a surprising micro-eureka moment when you get trapped in your mundane routines.

Maybe Discovery itself is an ambient system. It’s present and available in the background, only activating when it makes sense to you. Time-consuming complex stuff is hidden under the hood. The system notifies you when something is happening or already waiting for you. Such a Discovery solution is your never-sleeping intelligent extension that doesn’t need continuous actions from your part.

This would be more in tune with our natural experience of discovering new, interesting things almost coincidentally. When digital and physical become more and more entangled, ambient Discovery can be the new user experience paradigm for VR.

However, could any Discovery technology help us to find anything truly new and meaningful if we’re not open to exploration ourselves? Maybe a well-tuned Discovery system could educate us to be more open toward diversity and serendipity. And, potentially, finding the right dynamics for personalized Discovery could be the key for creating more human-centered and diverse digital experiences for all of us.