Case Study • Apparel
K-Fashion Site Eases Workload with No-Code Personalization, Increases Sales 51%
Problem
Too much time and money spent on product page personalizationSolution
Find an automated personalization solution with better customer supportResults
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 e-commerce scene Codibook was an early adopter — but they soon realized that it’s a lot of work!
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 e-commerce 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 e-commerce 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.
Solution
A SaaS product page solution tailored for today’s fashion e-commerce pros
The Rosetta AI Platform has some big advantages for e-commerce 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 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 platform recommends new unseen items that feature precise fashion industry tags from individual shopper’s preference profiles.
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.
Results
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.