The need to remodel the ‘personalization’ approach at scale
Personalization has been a buzzword in the business industry for some time now. However, gone are the days when it can fittingly suffice business goals and user expectations without remodelling itself. While plenty of businesses are jumping on the bandwagon of personalizing user-experiences, there are some that have been reimagining the approach to personalization thus far.
In the last century, mass production systems based on assembly lines and automation technology flooded markets with standardized products. The inherent inflexibility of the manufacturing processes resulted in hardly any room for uniqueness or customization.
And for them Friends fanatics..
Over time, with improvements in technology and availability of data, businesses recognized the value in and opportunities that personalization, and further hyper personalization presented.
To bring you up to speed, how often do you feel Youtube knows exactly what you want to watch and Spotify knows just the music you want to listen to?
Hyper personalization: Moving away from segmentation & towards individualization
For the longest, businesses have collected data about their end-users and segmented them into relevant buckets based on set criteria. Depending on the product/service and marketing strategies, these criteria could be demographic, geographic, psychological, cultural etc. These similarities determine how best to target a group of users.
An e-learning platform for example, may implement the user segmentation approach by grouping learners on the basis of their age, level of experience or subject/industry. By this logic, in the app development industry, college students may want to learn different coding languages whereas professionals in the same field may be more inclined towards learning about strategizing and flourishing their business.
User segmentation however, runs the risk of losing out on individual and nuanced differences. These complexities add multiple layers of meaning that the user attaches to the product/service. Every user treads a unique path with the products they own and services they utilise. To truly personalise a product/service, these targeted ‘individual journeys’ must be mapped.
For example, during a UX research study at Turian Labs, we were trying to understand the reason behind a high user churn rate on a global e-learning platform. A common theme that emerged amongst interviewees was that despite content being useful in general, it was not meeting their particular needs and context. How come they find the information useful yet not relevant to their needs and context? As one user stated, “The information is useful but not that much. I learnt different monetization strategies that can be introduced on an app but it is not relevant to the app that I want to grow a business from”.
As businesses are realizing the value in addressing individual users in propelling user engagement and retention, they are moving closer to what ‘real’ personalization is, that is, hyper personalization. This technique leverages Artificial Intelligence and real-time data to be able to sculpt the product, service, content or information in a way that is most relevant, contextual and relatable to the user’s needs. No longer do users expect businesses to respond to their needs and wants alone; they also want their interests and beliefs to be reflected in the products and services, and the experiences they promise to offer.
A notable way in which some of the businesses have implemented this is by including users in the process of designing products/services themselves. To take a case in point, Royal Enfield has embraced the DIY (do it yourself) strategy and come up with what it calls “Make Your Own”, a strategy applying mass customization wherein the end-user has the power and control to design the configuration and appearance of the helmet they wish to purchase. This includes choosing the type of shell, the internal fabric color and the final finish of the helmet from a set of vast options. Including the user in this capacity allows the user to best create what they desire in that they are able to co-create the product, have a greater sense of ownership, and own a product that truly represents their unique self and their particular taste.
Predictive hyper personalization
A more advanced way to hyper personalize product/service offerings is through employing predictive personalization. Businesses need to not only stay afloat with mapping user-needs and desires, but also must be capable of forecasting what they would probably expect in the future. This necessitates businesses to ask the question: what’s coming next?
In-depth user information in the form of big data, is now at the disposal of businesses. Currently, it is being used to locate collective patterns that inform the direction in which products/services can improve and innovate. What happens when this sort of information is used to peek into the future of a single user? A key question to ask becomes: How can we (read: business) make use of the present user information (including likes, dislikes, behavior, needs, wants, interests, beliefs, intentions, preferences etc.) to discern patterns that can inform relevant customization for a plausible future?
A number of organizations have already adopted this approach. To take a case in point, Netflix uses analytics and algorithms to capture user subjectivities and project personalized home pages to each of its users based on their ratings and watchlists.
Spotify on the other hand, curates a ‘Discover Weekly’ playlist for each of its subscribers. The differentiating factor between this feature and automated music recommendations is that the playlist is hyper personalized to the individual’s real-time music preferences. Every Monday, Spotify presents its users with a playlist of 30 songs they have not heard before and it is in the simultaneous familiarity and newness that subscribers find joy. This prospective approach to music listening is accompanied by a retrospective one wherein Spotify has introduced a feature called ‘Time Capsule Playlist’. It is a collection of songs that the teenage version of the user probably listened to. It is curated on the basis of their age, the country they live in and genres they like, to make the user reminisce about their teenage years. As more and more user data becomes available, complex human subjectivities will be captured. Through time, these playlists have the potential to become progressively accurate because personalization is only as good as user data.
What next
To be responsive to consumer needs and expectations, these innovative approaches to personalization must move from the margins to the core of how businesses across the world are imagined and implemented. Organizations need not only put the individual consumer first and think while wearing their shoes, but also proactively practice abductive reasoning and strategizing to foretell what they are inclined towards to determine the ‘what next’. This could become a recipe for trust and loyalty. What do you think?
