A Thought Piece
YesPlz.AI, October 2023
After speaking to hundreds of retailers of all different sizes, we noticed commonalities: retailers want AI in eCommerce but don’t know which type is best for them.
We’ve noticed that retailers are now understanding the value add of AI in eCommerce, but still looking for a better, easier way to integrate the technology–and still debating where the most impactful use cases are.
In this article, we’ll explore real use cases for AI in eCommerce, and how retailers can harness AI to improve their most pressing needs.
What could the future of AI and shopping look like in 2024 and beyond?
As online retail continues to exponentially become more mature, sophisticated retailers are exploring product discovery solutions as a competitive advantage–a way to stand out against the fierce, numerous competition, and optimize their day-to-day business as product catalogs continue to grow.
Shoppers want a more delightful shopping experience, instead of browsing through irrelevant products. Ideally, with just a few words, a shopping website can immediately understand a shopper's prompt, finding the exact products they’re looking for, or are inspired by.
Shoppers are tired of doing all of the work–they want the eCommerce to do the work for them.
In 2023, most shoppers have been exposed to AI and have higher than ever expectations for search technology.
As a result, the modern shopper wants to be able to easily put together complex searches, with multiple product attributes, details, and vibes.
Based on YesPlz in-depth research analyzing over 3,000 unique prompts from shoppers, the future of shopping looks like shopping by:
Occasion: Shoppers want to filter products by occasion such as night out, workout, or wear-to-work.
Personal attributes: Our research shows that shoppers, when given the opportunity, want to filter by specific attributes that matter most to them such as a flattering waistline for their body type or the right length for their height.
Aspirational styles: YesPlz data shows that shopper prompts also ask for styles that make them appear their preferred styles such as luxurious, romantic, or powerful.
Moreover, we know that the modern shopper wants more than keyword-based text search.
The modern shopper wants to be able to quickly build complex searches through using visual cues, and conversational commerce, and not be limited to repeated, one-sided text searches.
Unfortunately, there aren’t search and recommendation solutions that accommodate these shopper needs.
Online retailers aren’t effective at converting product discovery solutions, which creates a huge inefficiency in their product catalogs.
Most retailers lack:
-good metadata to build good product discovery solutions
-the resources to build and maintain strong discovery solutions
-budget to effectively outsource all of their discovery solutions
The result: Today’s online retailers plug into 3 to 5 different discovery apps, and still can’t help shoppers discover what they want. And, they’re stuck with duplicated costs and high spending of internal resources to manage multiple vendors.
Clearly, the current way of doing product discovery is broken.
But, with advanced AI in eCommerce, we can fix broken product discovery. Shoppers can easily navigate and command websites to recommend style suggestions for special occasions, find the exact items they want, and even suggest what to style together
Before we dive into more advanced AI, we want to break down the current state of fashion AI.
When we discuss AI in eCommerce, we’re not just talking about ChatGPT-style chatbots, but instead:
Natural language understanding: AI can help retailers understand text search queries better to figure out the best product matches. NLP can also be used for conversational commerce.
AI Tagging: AI models can be trained to discern product attributes from retailer product catalogs, and automatically tag them, so retailers can plug into more advanced filtering and recommendations.
Computer vision: The ability for machines to interpret and understand detailed product attributes from product images
Generative technology: When AI can create new content that didn’t exist before, such as ChatGPT or DALL-E images.
While these AI concepts alone are quite exciting, when combined, they can be used to create an entirely new product discovery experience.
As AI continues to become more advanced, solutions providers like YesPlz AI are combining them to solve the toughest customer problems, like mismatched search results because of a lack of understanding intention.
We’ll explain more below.
Advanced, combined AI technologies can change the way that fashion brands are approaching product discovery.
Here are 3 key capabilities AI can do differently:
Capability 1: AI in eCommerce can understand a shopper's intention
When a shopper types in “black silk dress for wedding,” they have a very specific occasion and intention in mind. However, current eCommerce discovery apps aren’t sophisticated enough to identify occasions, leaving shoppers with a range of search results that are outside of their intention.
Capability 2: AI can build creative solutions that weren’t possible before without AI.
Before, discovery apps were overwhelming for shoppers who were stuck navigating complex text-based filters. But, with advanced AI, we can build visually-focused search (like the YesPlz Virtual Mannequin Filter) that not only makes search more accurate, but is an entirely new way for shoppers to navigate search.
Capability 3: AI can provide immediate personalization, leading to accurate and delightful product matching
Shoppers don’t want to see generalized recommendations. YesPlz AI simplifies personalizing product discovery for eCommerce sites.
AI for eCommerce can improve product filters to make it easier for shoppers to narrow down products by visual, design, and silhouette attributes.
In addition, it can improve search quality through laser-accurate search, even creating new ways to search for products.
AI tagging can be used to accurately and quickly tag product attributes, even the most granular details, that would be nearly impossible for humans to tag. With streamlined tagging, retailers can build advanced recommendations and search filters that provide the most accurate discovery experience.
We help fashion eCommerce have the most personalized discovery solution, removing inefficiency from their sites.
The 3 ways that we remove inefficiencies for retailers are:
1. Automating deep product tagging to get rich metadata.
Our AI thoroughly analyzes each product, and can extract rich metadata in milliseconds, such as color, sleeve type, occasion, silhouette, and details like lace. By automating deep product tagging, we save retailers from the inefficiency of manual tagging.
2. Training AI for personalization to scale out styling and shopping assistant services.
Previously, without AI in eCommerce, retailers relied on human stylists or inaccurate software for styling services, which is extremely costly and time-consuming. Now, with YesPlz AI, we offer personalization that makes it easy for retailers to offer styling services such as Complete the Look and GPT AI Stylist
3. Simplifying the integration process. With a single integration, retailers can access multiple product discovery solutions in 2 to 4 weeks
Our AI has been trained on a million fashion data points working with from top global fashion retailers to innovative fashion startups. And, it has been successfully integrated with different eCommerce platforms.
Lastly, it has already been validated by the successful product discovery conversion rates of our clients.
Our clients have seen results such as an increase of 15% of additional sales generated, and a 1.7x increase in the average cart size by using YesPlz’s AI in eCommerce.
We offer the best and simplest AI product discovery solution across all verticals, removing any inefficiencies for eCommerce sites.
Curious to learn how our AI can work for your eCommerce?
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