Personalized Recommendation Engine (for Fashion)

Source: Business of Fashion, Mar 2011

BoF: Do you think Google’s Boutiques.com effectively leverages Web 3.0? Is anyone in fashion doing this well?

SM: No, Boutiques.com is not set up to do what I am talking about. You need an expert system powering the backend engine, not just “I like this” and “I don’t like this” type of input from consumers. Frankly, I haven’t seen any site that is really doing a good Web 3.0 implementation in fashion.

BoF: Offline, the best personal shoppers have up to the minute knowledge of fashion and can offer intelligent recommendations based on complex inputs like your personal taste or a specific event you might be shopping for. How exactly might a Web 3.0 service tackle a problem like this?

SM: The entire expert system needs to have a data structure against which the merchandise gets categorized and a rules engine that does the matchmaking based on that characterization. In other words, all the parameters — user, mood, size, event, location, time — need to be clustered, categorised and tied to a rules engine that is the personal shopper.

BoF: But in a trend-based industry like fashion, the rules are always changing!

SM: Every season, the merchandise will need to be entered into the inventory database according to the categorisation. Am I talking too much computer science? This is a complex system to build and to my knowledge, it hasn’t been built yet. At Uuma, this is what we had started to build. This was the central vision driving Uuma’s personalised store and personal shopper service.

BoF: With the coming of personal shopping agents, will Web 3.0 fundamentally democratise the delivery of personalised services that were once considered a luxury? What opportunities are there for luxury brands to differentiate their 3.0 offerings?

SM: There are degrees of personalised experiences. A basic level of personalisation can be achieved by mass brands using technology, especially intelligent agents. But luxury brands could layer in additional levels of personalization, including human personal shoppers who use technology to track your closet and your preferences and then offer additional judgment to augment the user experience and put together custom collections. My point is, the entire user experience can be massively enhanced to reach degrees of customization and personalization that we haven’t seen yet.

Finally, if you mine the data collecting in these online stores and pass some of that back to the designers, they can create custom collections based on specific types and styles of customers and be able to sell them effectively, knowing exactly what retail interfaces the customers are hanging out at. These are incredibly exciting possibilities for the business of fashion to become more personalised on the one hand — and also more scientific on the other. The fashion industry could become more financially successful by utilising personal data: analysing it and designing and merchandising accordingly.

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