With the advent of ChatGPT technology, the landscape for eCommerce product discovery is changing, but the core problem remains the same: how can retailers fix a fragmented search and recommendation system that leaves shoppers confused and frustrated? In our Ultimate Guide for eCommerce product discovery, we explore the ins and outs of a changing landscape.More
In this article, we’ll go over how to fix it–by looking at two common user journeys in eCommerce discovery, and using AI to create a frictionless shopping experience for each.
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Retailers are beginning to re-imagine visual search for eCommerce to include non text-based searches, such as search by image. We explore the nuances.
As growing businesses, two Shopify SMBs wanted to move away from manually tagging their products and dedicate their time and resources to other aspects of their business. They were tired of spending precious days tagging product attributes and learned that fashion AI could be a great solution for them.
There’s a problem with the current state of eCommerce discovery: siloed apps that don't work together to deliver a consistent product discovery experience, leaving shoppers frustrated and unable to find the products they want. From mismatched search results to repetitive discovery loops, shoppers aren’t getting the most out of product discovery when they’re on retailers' websites. We figure out how to solve the problem with holistic eCommerce discovery.
Freshly launched, the Virtual Mannequin Filter for earrings provides shoppers with another product category they can intuitively search for, and find perfectly tailored products to their needs. We’re excited to add a new product category to the Virtual Mannequin Filter, to better help shoppers discover new products seamlessly.
Personalization is the art of delivering the right content to the right person at the right time. It’s a mix of data and “art,” but most of all, personalization is at the core of delivering a superior shopping experience. But, how can we achieve a great personalization experience for eCommerce? We'll walk you through examples and take a look at the necessary components to achieve it.
Dynamic filters separate a good eCommerce product discovery experience from a bad one. With shopper expectations at an all-time high, dynamic filtering’s benefits are clear: increased conversions and more intuitive experiences. But, creating dynamic filters can be a complex and laborious process. We explain how they can improve your eCommerce product discovery and how to implement them.
The majority of e-commerce sites struggle with product list and filtering user experience (UX), with 57% of sites presenting a mediocre or worse experience. Despite being resolvable, UX issues lead to potential customers abandoning suitable products. We provide a product filtering checklist for UX best practices, based on Baymard's 2023 report.
Feature extraction for eCommerce is the foundation for building personalization like search, recommendations, and filters. But, depending on how features are extracted, the quality of structured data can vary. In this article, we go behind the scenes and discover how YesPlz tags product attributes uniquely.
Despite new technology developments in 2023, eCommerce recommendations are still lagging behind. In this article, we’ll go over the state of eCommerce recommendations in 2023, including the difference between traditional and non-traditional recommendations and the latest updates.
Creating the ideal eCommerce recommendation requires a mix of technology and creativity. YesPlz used technical expertise and creative ideas to create AI recommendations for two fashion retailers, W Concept and The Handsome. Here's how we did it.