Personalized recommendations are becoming more and more common but did you know that most of the ones you may be seeing on ecommerce marketplace platforms actually underperform?
The “Recommended Just For You” items they’re showing to shoppers are liked by pre-determined customer segments and aren’t that tempting to most shoppers nowadays, especially the younger ones who expect 1–to-1, real time personalized recommendations.
On the other hand…
A true 1-to-1 Personalization Platform on your own site can tell you what attributes individual shoppers see in the products they desire. Is it the neckline? The sleave? The material? This data is the difference between an accurate recommendation and a generic one.
The biggest brands use these systems. They go to great expense to set up their own ecommerce recommendation systems with AI visual recognition to break down what’s being seen by each shopper and then create the onsite tools to recommend products that share similar visual aesthetics.
But nowadays, this technology is also available to SMBs with website traffic yielding first-party data.
Making your first-party data more valuable
No-code SaaS solutions are available to help merchants of all sizes personalize their branded websites for individual shoppers. And the platforms are easy to manage, even for marketing professionals without machine learning experience.
Taking true ownership of your first-party data
For starters the Platform lets you analyze key shopping metrics, shopper preferences, and top performing recommenders, all at a glance.
How do you recognize shopper preferences?
The Platform uses AI-powered visual recognition that’s trained by fashion industry experts to break down what shoppers like about what they’re looking at.
With this aesthetic sensitivity to your website visitors, you can see what they see on the attribute level, analyze their preferences, and then use the Platform’s recommender apps to cross sell items that are much more likely to be bought.
The AI generated tags that are being looked at most, are the ones that shoppers prefer.
You can analyze product performance…
And even check out individual shopper data…
Data privacy is a non-issue because shoppers are only ever identified by a Customer ID Number.
How do you show shoppers what they want?
Your shoppers’ preferred aesthetics are compiled into Individual Shopper Preference Profiles that you can use to create 1-to-1 personalized recommenders on any page of your site.
Our most successful clients have found that recommendations on product details pages have doubled their AOV!
You can select handy pre-made recommenders (in-page carousels or exit-intent popups)…
And you can customize them however you want to fit your site’s look and feel…
What the apps looks like on a website
Korean multi-brand fashion site, Codibook, is a long time Rosetta AI client. They’ve found the Platform’s recommender apps useful for converting more traffic and simplifying their daily workload.
They use the Recommender plugin to put personalized recommenders on their product details page where they increase AOV.
L’Oréal Luxe Division brand, Shu Uemura, uses another the Promotion plugin on their home page to show banners offering discounts. These popup banners feature Rosetta AI's hesitant customer detection which shows the banner at the optimal time to reduce bounce rate.
Connecting the platform to your site: fast and easy
The best way to begin is to schedule a call with us and connect with Sales Director, Hermione Tsai. Just sign up below for the 30-day free trial and she'll get in contact with you.
It’s an extremely easy process and she’ll walk you through connecting your product feed and your Google Tag Manager.
From there, you’ll have the Rosetta AI Personalization Platform at your fingertips to begin creating your first recommender.
We look forward to hearing from you and helping you grow business. We’ve made great connections so far with brands that adopt new things early on — and we will continue to do so!
A final word from CEO Daniel Huang: “Presently, we’re adapting what we’ve learned about ecommerce in Asia and expanding. We’re looking forward to making new connections with growth-focused ecommerce brands, worldwide.”