Enhanced Digital Mass Customization
Mass customization in its early days involved the customization of a product, with the addition of optional items to the default package offered, in order to customize according to the user’s preferences.
It could involve the concept of Up Selling when adding a more increased item to replace that of the default offer, such as when buying a notebook and adding more memory, or in the case of the concept of Cross Selling, it could involve buying a item not directly related to the product category, as in the example cited, which may be the purchase of a notebook backpack.
In the Digital Economy or “Platform Economy”, the possibilities of mass customization have expanded exponentially, with the use of technological platforms that are based on the concept of “marketplace”, in which these companies develop applications for niche operations, with focus on solving specific problems, where they end up acting as a platform that connects who offers their products and services and who consumes them.
In these digital platforms, profitability grows with the increase in the number of users, that is, the economic viability of the operation of the “platform” occurs due to the network effect generated and by economies of scale.
And they generally act based on the logic of resolving “ bottlenecks “in sectors of the economy, that is, fully or partially automated processes help to stimulate the efficient allocation and pricing of products and services offered, also helping to reduce their idleness. For example, there are already startups in Brazil, which work to optimize the allocation and pricing of road cargo transportation.
The use of AI for Enhanced Customization
The greater level of customization on these digital platforms is achieved by implementing artificial intelligence in offering personalized services, which aim to provide a better user experience.
To make this feasible, they study the user’s past behavior both offline and online, crossing geolocation information provided by the application, history of transactions carried out, browsing information and online habits, as well as that provided by the user through satisfaction surveys a each transaction related to the quality of service, which will serve as a parameter for the customization of the offers and services of these platforms, and can even sometimes stimulate an impulse purchase, by detecting and anticipating any latent need and / or desire of the user.
The use of virtual service avatars through the voice interface that make use of natural language processing technology (NLP), is a growing trend in global retail and is capable of establishing an almost fluid communication with people and can facilitate the process of purchasing a product and / or service for those who are not familiar with technology or who find the process bureaucratic.
The integration of the voice interface into day-to-day devices that are connected to the Internet of Things through sensors, will also enable the collection of information about our habits that will help to further personalize the offerings of these digital platforms.
In E-commerce in general, the customization of a product can involve a wide range of options, with variations in terms of aesthetics and technical attributes, which end up making that product unique to the customer. Even generating a sense of belonging for some people.
As for services, as they are perishable and consumed at the time of delivery, personalization takes place through user experience, so the more information the platform has from that user, the more quality it will be able to provide, in theory, since turning the data into services of quality require the adoption of powerful analytical systems that can make use of Big Data technology in order to generate actionable insights.
In-depth customization
Many current digital platforms make use of the understanding of the user’s context, such as geolocation information and pre-selected information and / or inserted by the user to provide the service in question using algorithms that automate certain decisions, for example, such as the choice of a service provider that meets certain user-defined criteria.
A deeper degree of customization in my understanding, could involve the possibility for the user to choose, as a Digital Curator, which threshold criteria the algorithm will use to choose the service provider and / or for example the addition or elimination of some criteria that the default algorithm uses, in order to adjust the provision of services to the user’s taste.
Imagine, for example, being able to choose the service provider based on their grade or “score” on the platform and the pricing process being adjusted accordingly, or in the case of users who make certain restrictions explicit in their profiles, and the platform being able to understand and to act to this adaptively.
In this way, a greater degree of customization is achieved, avoiding the default profiles and the false security that we already know everything about the user or their preferences.
Another customization scenario, which could make use of virtual service avatars with a voice interface, involves understanding what is said during the service provider’s service, for example if the user complains during a ride from an Urban Mobility App, that the car suspension used by the service provider is too uncomfortable, or that the chosen path has many holes in the poorly maintained asphalt, so the program can record this information, and understanding the context of each one, in another race choose another vehicle model or choose another route in the same region.
Smart and adaptive Personalization in Digital Platforms
Personalization involves something being unique, the feeling of having all the attention of the service provider focused on meeting your needs and / or desires.
That is why successful digital platforms in the future will have to flee from what has already become a “commodity” and use conversational user interfaces that encourage them to reveal their tastes and capture what is left implicitly, whether through study of their consumption habits in physical or digital channels and / or in non-verbal communication signals, such as micro facial expressions for example, to cite an example used in Neuromarketing.
Service offerings are better adjusted iteratively, as the platform “learns” the tastes and preferences of users.
Finally, I understand that this greater degree of personalization and greater degree of excellence in meeting consumer needs and / or desires, involves a deep understanding of the user experience on digital platforms, and having the wisdom of what improvements to implement to achieve a better experience and a higher degree of customization, as well as having the technological infrastructure and analytical tools necessary to achieve this goal.
Obs.: This article is an English translated version of my 2018 original article in Portuguese.
About the Author — Renato Azevedo Sant Anna
Digital Business & Insights Consultant, Thinker and Curator about the VUCA World, with a natural curiosity about the World and its complexity, multidisciplinary knowledge and the ability to produce actionable recommendations and insights about the competitive landscape.
Also a Mentor, Content producer (content writer), Instructor and Speaker on topics related to The Digital Era, Innovation, Entrepreneurship, Technology, Future of Work, Artificial Intelligence Applications for Business and Consumer Behavior on digital channels.
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