K-Fashion Site Eases Workload with No-Code Personalization, Hits 51% Sales Increase

Codibook is a Korean fashion ecommerce multi-brand website known for its shopping community of over 800000 “coordinators,” who create their favorite outfits from over 70 different online retailers — and share their creations with other online shoppers. So traffic wasn’t a problem for Codibook, but ROI on personalized marketing conversions was.

problem

Too much time and money spent on product page personalization

solution

Find an easy-to-start personalization solution with less hands-on maintenance and better customer support

Results

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optimized workflow

59%

Conversion Rate increase

38%

Average Order Value increase

51x

Revenue increase

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“Personalized recommendations help a lot to boost product page order value and overall revenue but the time and money spent setting it up and maintaining the system began cutting into the returns we were expecting.”

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Rosetta.ai case study

Codibook

Female shoppers from all over the world including the US, Canada, Japan, Taiwan, China and a number of other Southeast Asian countries comprise Codibook’s active user base. Service is provided in 5 languages and 12 currencies, but every brand is shoppable (browsing, coordinating, purchasing, shipping) from the Codibook site.

Since its beginning in 2011, the number of coordinators has exploded and capitalizing on it has been a challenge. Personalization helped and when it burst onto the ecommerce scene Codibook was an early adopter — but they soon realized that it’s a lot of work!
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The Problem

Personalization is high priority but time consuming and costly to manage

The effort Codibook had to put into their personalized marketing eventually became unfeasible. With a small ecommerce team the jobs to be done for the initial set up and daily maintenance interfered with other mission critical tasks.

But personalization is more important than ever now, especially in the highly competitive fashion ecommerce niche where young shoppers expect offers to be personalized.

In order to find a solution, Codibook CTO, Lee Yoo-Seok, travelled to Taiwan where he went to the Appworks demo day and saw a pitch by Daniel Huang, CEO of Rosetta.ai.
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The Solution

A SaaS product page solution tailored for today’s fashion ecommerce pros

The Rosetta.ai solution has some big advantages for ecommerce engineers and marketers alike:
  • Simplified onboarding process is quick and easy with one-click setup
  • Daily maintenance takes less time on the backend and doesn’t require ML experience
  • Preference profiles with actionable consumer insights for merchandising and product development are compiled automatically


These profiles are powered by the company’s Aesthetics AI, a personalized recommendation system that uses computer vision trained by fashion industry experts to recognize exactly which aesthetic attributes matter most to individual online shoppers.

Apparel and beauty websites with this advanced personalization system on their product pages are, on average, doubling their conversion rates and tripling their order value.

So instead of just recommending products previously viewed by the visitor, or a segment to which the visitor belongs (which lesser recommendation systems still do to this day), the Rosetta.ai solution recommends new unseen items that feature precise fashion industry tags from individual shopper’s preference profiles.
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Product tags and individualized recommendations on the Codibook product page..

This automation on the back end drives more cross-sells on the front end, especially to knowledgeable fashion shoppers who appreciate seeing an accurate recommendation on the product page.
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Results

59%

Conversion Rate increase

38%

Average Order Value increase

51x

Revenue increase

Since going live with Rosetta.ai on their product page, Codibook has improved the efficiency of their workflow, and gained valuable consumer insights about their legions of website visitors.

Their daily workload has become easier with automated customer data management and individualized consumer insights. And at the bottom line, fashion-focused, personalized recommendations have delivered impressive increases to conversions, average order value and overall revenue.

Enabling merchants to understand the language of fashion.

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