Generative AI’s Impact on E-Commerce

Generative AI is the latest form of applied artificial intelligence that enables businesses and consumers to automate, simplify, and otherwise improve various operations in their day-to-day lives. In the world of e-commerce and e-tail, vendors are implementing generative AI solutions to support employees in their daily work and give customers a new and improved buying experience.
In this guide, we’ll cover some of the most common use cases of generative AI in e-commerce today and we’ll touch on how today’s benefits may lead to further AI growth in this industry.
Table of Contents: Generative AI and E-Commerce

Generative AI Use Cases in E-Commerce
Leading Generative AI Solutions in the E-Commerce Space
Bottom Line: The Benefits of Generative AI in E-Commerce

Generative AI Use Cases in E-Commerce
Generative AI can be used to supplement or even supplant various components of a company’s e-commerce workflow.
Across the e-commerce sector, artificial intelligence benefits both the vendor and its employees as well as customers and prospective buyers. Learn more about generative AI’s use cases in e-commerce below:
AI-Driven Analytics
E-commerce of course involves less face-to-face interaction with customers than traditional commerce, so it can be particularly challenging to gauge customer satisfaction across different parameters and data points.
Online businesses have used data analytics tools for many years now to better understand how customers engage with their brands. But these tools have been limited in the quantity and quality of data they collect as well as the speed with which data is updated.
In contrast, generative-AI-driven data analytics tools give business leaders and data scientists more contextual customer data, updated in real time and across different shopping, channel, and demographic data points.
These generative AI tools can collect data in various unstructured formats, including customer service queries, social media posts and comments, ad clicks and engagements, and other data that has historically been difficult to capture.
Additionally, these tools often go beyond predictive analytics, offering insights into what’s happening now and making prescriptive recommendations for what vendors can do to achieve better results, products, and services in the future.
Other ways users can combine generative AI and data analytics for better e-commerce outcomes include the following:

Quickly assess products, websites, and other customer-facing assets to determine if they are meeting quality requirements.
Make more accurate and timely supply chain predictions.
More effectively manage inventory and demand forecasting needs.

Customer Service Chatbots, Agents, and Coaches
This generative-AI-supported customer service platform monitors conversations and then scores service agents across a variety of important performance factors. Source: Cresta
With generative AI chatbots and virtual agents, businesses can handle chat conversations 24 hours a day that are designed to feel like a real human is engaging with the customer.
Many brands have had 24/7 operational chatbots in the past. But without the content generation and predictive capabilities of generative AI, these previous chatbots have relied heavily on human-built workflows and prebuilt responses that don’t always meet customer needs. Their limited training on limited amounts of data severely impacted their ability to interact with customers. They can’t solve problems in the face of unique customer experience scenarios.
When a customer service problem needs to be escalated, generative AI agents can also be used to triage more complex communications to human customer service reps, giving them all of the contextual information they need to follow up with the customer effectively.
Additionally, these AIs can be used to coach human customer service reps on how to have better customer interactions that match the tone and needs of that individual.
AI Search for Customers
Generative AI tools have made it possible for businesses to quickly scale up their online knowledge bases in a way that answers a variety of customer questions that may not have previously been considered or adequately covered in early versions of online resources.
This database of knowledge can then be embedded in brand websites and apps, and in some cases, may also be connected to the internet for real-time search capabilities and more targeted ads.
AI-driven search not only gives customers the best search results for their queries but also frequently offers contextual information, suggested next searches, and other information that may assist them in their buying experience.
Product Descriptions and Content Writing
Businesses of all backgrounds are experimenting with generative AI for content creation, and the e-commerce world is filled with opportunities where AI can fill the gaps. For example, generative AI tools can be used to quickly write product descriptions, product guides and white papers, marketing and sales blogs, emails and marketing campaigns, chatbot responses, and targeted ad content.
Because of the speed and scale at which generative AI content writing tools can work, businesses can quickly create and rework content while also using these tools to detect customer sentiment in queries and respond accordingly.
Especially in marketing and communications campaigns, many of these content generation tools can also be trained and set up to automatically reply and follow up with customers when appropriate.
Back-Office Operational Support
Shopify Magic’s latest assistant, Sidekick, is currently available to early-access users. Source: Shopify.
A growing number of AI tools focus on creating a one-stop shop for e-commerce back-office operational tasks, including content generation, task management, storefront management, and ad management needs.
An example is Shopify Magic, a set of generative AI capabilities that is built directly into the Shopify commerce platform. Its latest feature is Sidekick, a Shopify assistant that helps vendors manage their task lists while answering specific questions about everything from customer interactions to what’s needed to prepare for an upcoming sale.
Virtual Customer Experiences
Though this area is still fairly early in its development, virtual customer experiences like virtual try-on for clothing e-tailers are quickly growing and gaining a loyal customer base.
Clothing retailers are primarily benefiting from this new innovation, but other VR/AR experiences are also in the works that allow users to have remote shopping experiences that “feel” real. Additionally, a growing number of customer-facing apps now exist that combine different generative AI elements, such as AI assistants, chatbots, guided search, and catered product recommendations, to create a smoother shopping experience for users.
For more on a similar topic, read AI in Retail: What You Need to Know.
Leading Generative AI Solutions in the E-Commerce Space
A number of generative AI solutions have popped up to solve for different e-commerce use cases, including ad and product content creation, communication and customer service, and more.
Below, we’ve gathered information about some of today’s leading e-commerce-focused generative AI solutions:

OpenAI’s ChatGPT and GPT-4: OpenAI’s ChatGPT and GPT-4 are being used by many other generative AI vendors as a foundation for embeddable chatbots, virtual assistants, and other tools that improve the customer experience on e-commerce websites and virtual storefronts.
Jasper: Jasper’s library of tools covers a range of e-commerce needs, including generative AI chatbots, image generation, brand-driven content generation, and automated marketing campaigns.
Gridspace: A contact center tool that supports e-commerce needs like virtual agents to take calls and detailed conversational analytics to coach and improve future conversation outcomes.
Veesual: VR/AR-driven customer experiences for clothing shopping and virtual try-ons.
Shopify Magic: A back-office assistant that can help vendors with task management and content generation types of tasks.
SolidGrids: Product image and content generation, including banner generation and SEO optimization features.
Describely: Product descriptions, catalog content, and other types of product-driven content generation.
Cresta: A contact center solution for virtual contact automation, rep coaching, and real-time call analytics.
AdCreative.ai: Creative ad content generation platform.
Shulex VOC: A ChatGPT-driven AI assistant that makes suggestions, answers questions, and automates various e-commerce tasks.
Phrasee: A content generation platform that works across email, SMS, web, app, and social channels and focuses on customer loyalty outcomes.
Kore.ai: A platform with both employee experience and customer experience tools for conversational AI, AI-driven assistance, and smart search.

For more information on these solutions and others from emerging generative AI startups, read about the 50 Generative AI Startups to Watch in 2023.
Bottom Line: The Benefits of Generative AI in E-Commerce
The generative AI and e-commerce market is ripe with new tools and features emerging on a near-daily basis to address the different wants and needs of e-commerce vendors, business stakeholders, employees, and customers.
While certainly not everyone is open to artificial intelligence taking over tasks that have traditionally involved human-driven customer service, more and more people are growing comfortable with this development. It provides new conveniences, particularly to retailers that are struggling with worker shortages.
With generative AI in a supporting role, e-commerce companies can confidently move forward and grow their businesses in a way that feels sustainable and innovative.
Read next: Top 9 Generative AI Applications and Tools
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