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Introduction

The customers are the biggest resale marketplaces in the Americas. They are at the forefront of a $24B secondhand market.

One of them has

They also focus on providing online, and in-store services for buying and selling second hand apparel for retailers and brands.

1:1 Personalization
"It happens seamlessly when the machine is trained. We train our neural networks to understand what the outfit even means. And how outfits are put together. We are understanding customers behavior and from that we are creating style profiles which is individualized. Recommendations are not based on what a thousand people have done, it is all about you the individual shopper. And then we create recommendations of individual products and outfits because we know that…the more a shopper interacts with the system and the more feedback we get, the more we learn"
Julia Dietmar

Julia Dietmar
CPO, Vue.ai

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The challenge

The resale industry’s exercise with personalization is pairing customer data with content with an added challenge personalizing when inventory = 1. The number of unique items in the inventory posed a challenge when it came to providing recommendations. Surfacing recommendations through the shoppers journey with products similar to the shoppers visual style preferences and intent was also a hurdle.

Shoppers had to be kept engaged

  1. With relevant recommendations across various pages on the site,
  2. By showing them items that were similar to their Style Profiles and intent.
  3. With recommendations similar to items that are out-of-stock or unavailable.
Execution

Visual Intelligence across shopper journey

Solution:

  1. Vue.ai’s ‘Recommended for You’ solution uses shopper browsing history—short-term and long-term intent—to surface recommendations that are the most relevant for that shopper in that particular moment.
  2. Visually similar product recommendations are deployed on the product page. Shoppers are always shown the most relevant products in spite of the limitations of inventory. With Amazon Simple Queue Service powering real-time synchronization of catalog updates, Vue.ai is able to ensure that only the most recent version of product data is used.
  3. Emails with compelling content helps improve click rates, increase engagement and conversion. With shopper behavior tracking powered by proprietary technology as well as Amazon CloudFront, Vue.ai’s algorithms are able to pick up on shopper signals across the retail site and serve them the most compelling experiences. This ensures that the most relevant email content is surfaced for each shopper, at the time of opening the email.
The Vue.ai Advantage

For Retailers

Curate individual wardrobes based on user browsing historyEnable retailers to establish one-to-one relationship and a competitive advantage
Cross-selling and up-selling products through recommendations Recommendations based on shopper preferences and past purchase data helps better engagement

For Shoppers

Product recommendations generated from visual & non-visual cuesProvides users with a seamless shopping journey
Navigation paths leading to better catalog visibilityInformed shopping decisions
Solution

Personalization on the Home Page

Vue.ai’s Personalization Suite uses shopper data to gain insights into shopper preferences. This includes visual style-based attributes like color, pattern, shape, for fashion retail, and brand, category, etc.

Ensures

Personalization for the Category Page

Shoppers often turn to category listing pages to discover products. Listing pages are said to generate as much as 60% of a site’s traffic. The process of clicking through filters, product, and pages can be time-consuming and frustrating. By personalizing this page, retailers decreased the time it takes for the shopper to find products of interest, and decrease the time to purchase.

This ensured

Personalization for the Product Page

Vue.ai’s Visually Similar Product Recommendations: Visually relevant styles for each shopper, taking into account attributes such as color, pattern, shape and more.

  1. Products with Increased relevance are served to the shoppers. When shoppers reflect affinity to certain attributes, Vue.ai algorithms recognizes these affinities and displays products based on these.
  2. These recommendations are used to manage out-of-stock products on pages, so shoppers can continue their journey even if a product they like is unavailable.

Personalization for the Cart Page

Vue.ai’s Visually Similar Product Recommendations: Visually relevant styles for each shopper, taking into account attributes such as color, pattern, shape and more.

  1. Once a shopper is well into the purchase funnel, there is limited opportunity to surface additional products. Recommendations on this page are useful in driving upsell. Cross product recommendations ensure the shopper is given insight into as many products, across as many brands as possible.
  2. The Complete the Look solution is implemented for the customer on the cart page to provide greater product visibility for shoppers.
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Key Takeaways

Vue.ai’s personalization solution ensures that

  • Every shopper has their journey tailored for them from the minute they come into the site.
  • User attributes are mapped meticulously to product preferences based on various signals.
  • Every shopper has access to products and styles that are unique to their on-site journey and their preferences
  • Products with increased relevance are served to the shoppers. When shoppers reflected affinity to certain attributes, Vue.ai algorithms recognizes these affinities and displays relevant products.
  • These recommendations are also used to manage out-of-stock products on pages, so that shoppers can continue their journey even if a product they like is unavailable.
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