February 27, 2024

AI-Powered Fashion Advice: How AI Personal Shoppers Boost Fashion Decision-Making

Explore the capabilities of AI shopping assistants, the best examples of these solutions, and how they’re changing the business landscape in e-commerce and retail.

Written by
Anna Shults

Artificial intelligence had a significant impact on retail and ecommerce. Visual search tools, chatbots, and logistics management systems are becoming more popular by the day. Combined, the use of AI in online shopping helps companies streamline daily operations, reduce costs, and improve customer loyalty.

Personal shopping assistants play a key role in this process, helping retailers and e-commerce enterprises match available products with the right customers. Businesses are quickly catching up to the promises of this technology, as the latest trends show that 95% of customers will shop online by 2040. Our guide covers all aspects of these solutions, how companies use them, and what the results of their implementation are.

Table Of Contents:

The Impact Of AI Shopping Assistants On Retail and E-Commerce

In 2022, the global market for virtual shopping assistants was valued at $516,44 million. Between 2023 and 2032, the CAGR for this market is expected at 29,6%. Walmart, Amazon, eBay, Sephora, and ASOS already offer such helpers to their customers. The latest research provided by Gartners shows the scale of the impact these solutions had on the industry:

  • Virtual shopping assistants cut the number of emails, chats, and calls organizations receive by 70%.
  • Almost 40% of customers use chatbots during online shopping.
  • AI chatbots and assistants allow businesses to improve sales by 67%.
  • Integration of this solution increases profits by 20-40% on average.

The Components Of ​​Virtual Shopping Assistance

Modern solutions help customers select the right products thanks to machine learning, natural language processing, computer vision, and voice recognition. Their combination allows AI assistants to serve just as well, if not better, than human staff, offering a tailored experience to customers of apparel, footwear, and cosmetics stores.

Cloud computing

AI-based shopping assistants use this technology to increase their computational power and scalability. Cloud platforms have the infrastructure to analyze large data volumes and train machine learning models.

Computer vision

This component of virtual assistants helps analyze and assess visual data. It lets solutions identify products, their dimensions, colors, and other traits. Advanced helpers even allow customers to try on things using smart device cameras. 

Data integration

Modern assistants gain access to product catalogs and customer and inventory databases. This connection helps assistants stay informed about prices, customer preferences, and product availability.

Machine learning

AI-powered virtual helpers are trained with vast information about all aspects of enterprises. ML algorithms help identify connections, patterns, and preferences, leading to a more personalized customer experience.

Natural language processing

Virtual assistants understand and interpret human language thanks to NLP. The technology allows them to comprehend intent and client requests, recognize entities such as product names, and conduct sentiment analysis.

Voice recognition

These platforms also work with speech input. Voice recognition turns spoken words into text, allowing solutions to process voice commands. Advanced products even talk to users, clarifying requests or confirming them.

Personal AI Shoppers Applications

  • Customer Behavior Analysis

Virtual assistants use machine learning to gain access to vast amounts of historical client data. This information helps them understand what people shop for during different times of the year, how much they spend on average, and which brands they favor. These insights allow assistants to offer items at an appropriate time.

  • Trend And Preference Tracking

Advanced chatbots and virtual assistants work with more than individual customer data. They conduct in-depth analyses of social media, market trends, and customer reviews to identify trends and patterns in the fashion industry. This information is later used to offer goods that are more likely to sell.

  • Understanding Buyer Intent

The natural language processing technology combined with voice input support allows solutions to understand buyer intent when providing virtual shopping assistance via text or speech. Advanced solutions that use AR and VR also recognize facial expressions if they’re equipped with the right technology, monitoring how customers react to different items.

  • Personalization

One of the main perks of AI assistants is their ability to introduce custom recommendations. They combine machine learning and data integration to retrieve information about product prices, availability, and customer information, recommending the right items to the right customers.

  • Assessment Of Individual Styles

Personalized assistants help clients of e-commerce and retail businesses discover different styles by offering clothes, cosmetics, and accessories options. AI personal shoppers work much like wardrobe consultants but with easier and faster access to the latest trends. This approach makes 56% of customers return for a personal experience. 

Real-Life Examples Of AI In Online Shopping

  1. Amazon’s Rufus

Amazon’s solutions are the youngest on this list, as it was introduced in February of 2024. The Rufus shopping assistant helps clients find the right items in Amazon’s endless catalog. It provides guided help, recommendations, and product comparisons. Users find specific items based on size, color, material, and budget. The solution also answers questions about products. Rufus is currently in beta and is only available for US customers.

  1. ASOS’s Style Match

The UK-based online trailer provides a Style Match application for Android and iOS devices. This solution helps clients find the most suitable outfits. They get access to the company’s vast catalog, holding about 85,000 products. Customers can look for less expensive alternatives to items found on Instagram using visual search.

  1. Sephora’s Virtual Artists

This cosmetic brand offers a virtual makeover experience using the power of facial recognition technology. Clients get access to a library of lipstick colors, eyeshadows, and false lashes. With the help of the virtual assistant, it's possible to find the right combinations and order products without ever setting foot in physical locations.

  1. Walmart’s Virtual Try-On

Like ASOS, this American store chain allows its customers to browse and digitally try on different clothing items and accessories. This service is available for over 270,000 retail items. Customers download the iOS app and take their measurements using device cameras. The solution then recommends products based on this information and allows users to add items to the cart without leaving the app.

How Personalized Shoppers Influence Consumer Behavior

The effective use of AI in online shopping significantly influences client behavior. This technology makes it easier for clients to search for, try on, and purchase items. This streamlined approach to shopping improves the customer experience in several ways.

Offering complementary products

AI-based helpers offer products that will fit well with selected fashion pieces. According to a McKinsey study, this approach can boost sales anywhere from 20% to 30%. Having such assistants saves clients time and effort gathering their wardrobes. 

Tailoring a personal experience

Shoppers enjoy being treated as individuals, which modern AI assistants are more than capable of. They offer laser-focused recommendations that appeal to a person’s taste and previous purchases.

Using tactical promotions

Everybody enjoys a discount on an item they’ve been wanting to buy for a long time. AI-powered constantly monitor the prices for different products, offering them whenever they fit the budget preferences of specific customers.

Providing styling advice

AI assistants use information such as clothing sizes, pricing preferences, and body measurements to offer products in real time. This makes individuals stay longer on websites, explore more options, and reduce returns.

The Results Of This Practice

In addition to being great drivers of revenue, these solutions provide benefits for customers of retail and e-commerce stores. Here’s what they can expect from using AI-based products.

  • Reduced decision-making time. Using solutions with the power of artificial intelligence helps e-commerce and retail clients find better items faster. These tools drastically narrow down search options based on set filters, making it easier to pinpoint the right products and proceed to the checkout.
  • Better customer engagement. AI-based solutions allow clients to immerse themselves fully in the shopping experience. They shop whenever they like, for as much as they like. Virtual helpers never tire and help customers until they find the right items and place their orders.
  • More favorable buying outcomes. The use of visualization and tailored advice allows customers to be happier with their buying decisions. They better know what to expect from the quality of the materials and if the items will fit them. In turn, this leads to fewer returns and associated expenses.
  • Higher loyalty. By providing customers with the best offers and tailored experiences through its AI assistants, businesses build an emotional connection. These ties will increase the likelihood of clients returning for more and building a relationship with the enterprise.

Challenges and Considerations Of Using Personal Helpers

While the benefits and the capabilities of these solutions are apparent, their implementation brings along a series of challenges specific to AI-based solutions. Here are the most pressing issues businesses can face when introducing shopping helpers to customers.

  • Acceptance. Not all clients are eager to interact with AI assistants. Some of them can have second thoughts about working with this tech, while others prefer talking to human experts.
  • Compatibility. Adding new pieces of technology can clash with existing systems. They might need a complete overhaul to become compatible, which adds time and resources to the business expenses.
  • Costs. Investing in AI assistant development and implementation can take a lot of the enterprise budget. Businesses interested in this technology should look for providers that offer services aligned with strategic and budget goals.
  • Data privacy. Another area of concern is that AI shopping assistants are working with vast amounts of customer data. Without robust privacy and security measures, this information can be stolen or leaked, leading to reputational damages.
  • Language nuances. AI assistants don’t always handle multiple languages, dialects, and accents. They also fail to understand the cultural nuances when talking to clients from different regions.
  • Scalability. Retail and e-commerce companies can run into trouble if the assistant developers don’t offer regular updates. These solutions must scale alongside the business needs and improve based on user feedback.

AI In Online Shopping: The Latest Trends

AI shopping assistants are slowly but surely becoming a common sight in e-commerce and retail stores. In 2024 and beyond, the market for these solutions will see the development of several trends. Enterprises will continue to invest in augmented reality tech to provide customers with interactive displays and virtual try-ones.

Another type of helper that will show rapid adoption is voice-enabled assistants. According to statistics provided by Demand Sage, 51% of US shoppers use speech to research products. Currently, only 3% of consumers use voice to purchase clothing items, but another 22% consider doing so in the future.

In the coming years, AI-based assistants will also become a big part of physical stores, blurring the line between online and offline shopping. This process will allow enterprises to manage their online and offline inventory better and offer personalized in-store assistance through AI solutions.


These advancements show a future with higher convenience for shoppers and increased revenues for retailers and e-commerce enterprises. As AI technology becomes more affordable and easy to implement, personalized shopping assistants will become a common tool in this segment. If you wish to join the early adopters, give us a call, and we’ll talk about the best ways to introduce these solutions to your business.

Customer retention is the key

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What are the most relevant factors to consider?

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Don’t overspend on growth marketing without good retention rates

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What’s the ideal customer retention rate?

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Next steps to increase your customer retention

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