Psychometric Recommendations combined with User Entertainment

The current AI-market for Retail and E-Commerce platforms is all about search optimization and recommender systems, such as Amazon’s famous “People who bought X also bought Y.” The algorithms used to power these recommendation engines become more and more sophisticated and take various sources of data into account, including data about the products and data about the users. These improvements help consumers find the products they are looking for more quickly and with higher accuracy, making online shopping an increasingly efficient process.

However, sometimes the best purchases we make are those that we initially had not considered at all but were discovered via an inspirational journey. After all, this is the reason why many people still enjoy and often prefer shopping offline rather than online — not because it’s efficient, but because it’s fun and inspirational. Transferring this kind of offline shopping experience into the online world will be a key challenge for future E-commerce.

Offline Store Experience as an Inspiration for future Online User Experience 5.0

In contrast to a salesperson in an offline store, a recommendation engine behind an online shop is dramatically less likely to let you have a good time, inspire you, give you the feeling to be understood, or make you laugh (except, perhaps, when it fails miserably). Furthermore, while a recommendation engine may provide you with thousands of potentially highly relevant suggestions, a salesperson usually comes up with only a handful of highly relevant suggestions, some of which may surprise and inspire you. Because of the well-known paradox of choice, online shopping is much more likely than offline shopping to create frustration due to a never-ending search cascade involving thousands of products that you may really like. Ironically, the better the algorithms get, the more will the corresponding product suggestions be numerous and relevant, thereby increasing choice overload and its detrimental consequences.

Perhaps the most important difference between a salesperson and a recommendation engine is that when you first meet a salesperson, he or she quickly creates an impression of you, tries to capture your personality and style, and reacts accordingly. This will give you the impression that the salesperson will make suggestions because you are you and not because you are like others, as the recommender system would.

So where does this lead?

The E-Commerce market is familiar with the concept of gamification. But very few concepts were successful, and gamification approaches are -except for loyalty programs — often short-lived. So a more sustainable way to incorporate online entertainment and User Experience 5.0 with an impact on sales and brand loyalty is via a virtual shopping guide, just like in stores, that does not only help you find the products you were looking for, but moreover inspire you, entertain you and make personalized suggestions based on your personality and style.

So it`s not only about collecting real time intent data and past user history data. The ideal virtual sales guide captures personality and sensory preference (colors, fabric etc.) in no time and in an entertaining way, rewarding the user at the end with a preselection of product suggestions that fit to his personality and lifestyle.

How can this become reality?

Brandmind is currently working on a solution that embeds recommendation system features in an entertaining, playful environment that which draws upon a psychometric assessment of personality and motive dimensions (Psychology), sensory preferences (Neuromarketing) as well as a behaviorally informed suggestion mechanism (Behavioral Economics).

In the context of an ongoing Innosuisse innovation project in collaboration with the Center for Behavioral Marketing at the University of Applied Sciences (ZHAW SML), we found preliminary evidence for the predictive validity of a psychometrically based assessment developed by Brandmind. More concretely, the data indicate that our psychometrically informed recommendation model can predict preferences for fashion products significantly and substantially better than chance.

Where and when will that Online Shopping Guide be available?

Brandmind is now developing a minimum viable product (MVP) that contains the entertainment factor and the psychometric recommendation based on AI. This will go into production within this year. This MVP will be the basis for building a more advanced and sophisticated interactive Entertainment Guide, which we will develop in collaboration with our research partners.

If you are open to innovation and want to learn more, feel free to contact us:

Christina Hoffmann
Founder & CEO Brandmind GmbH
Lecturer in Neuromarketing, Psychology, Behavioral Economics, Brand Marketing at HWZ, Zurich Elite Business School and ZhaW.

Dr. Kurt A. Ackermann
Lecturer, Deputy Head of the Center for Behavioral Marketing and Program Director ‘CAS Behavioral Insights for Marketing’ at the Institute of Marketing Management at the University of Applied Sciences (ZHAW School of Management and Law)

About the Company:

BrandMind is a consultancy turning into a Marketing-Tech company that creates emotional experiences across all (digital) touchpoints. At BrandMind, everything is about triggering the emotions of consumers and providing an outstanding customer experience based on scientific know-how. We specialize in the combination of neuromarketing, psychology, and artificial intelligence. With in-depth knowledge from brain research and psychology, we can apply our know-how to all touchpoints and measure it in the future. Due to our scientifically founded tool, we can provide psychometric marketing for companies in the future with which the relevant Online-KPIs, such as (CR, Sales, etc.), can be massively increased.