Using generative AI in commerce: A comprehensive use case guide

Table of Contents

Using generative AI in commerce: A comprehensive use case guide

Marc Stracuzza
Marc Stracuzza
Director of Portfolio Strategy, commercetools
Manuela Tchoe
Manuela Tchoe
Senior Content Writer, commercetools
Published 06 March 2024
Estimated reading time minutes

The world of commerce is no stranger to artificial intelligence: From predictive analytics to AI-powered chatbots for customer service, businesses have been using AI for some time now. But it’s been the rise of generative AI (GenAI) that has unleashed the full potential of artificial intelligence for all things commerce, empowering businesses not only to craft personalized customer experiences but also to augment productivity and innovation. Here, let’s delve deeper into the key use cases in leveraging generative AI in commerce for B2C and B2B organizations.

Using generative AI in commerce: A comprehensive use case guide

An introduction to GenAI in commerce

If 2023 was the breakout year of generative AI, 2024 is set to maintain the upward momentum of this much-talked-about technology. As a paradigm shift, GenAI is changing the way we work, making it imperative for businesses to leverage this technology or risk falling behind. GenAI is already making inroads in commerce — online, offline or a mix of both. B2B and B2C companies are adopting GenAI to tackle pain points and maximize opportunities, so they can overcome challenges faster and differentiate in the marketplace. 

But AI has been a fixture of commerce for a long time, so what does GenAI bring to the game, exactly? GenAI is capable of generating new data, images or content based on learned patterns, from creating product data in your PIM (product information management) system to crafting marketing emails. It’s all about leveraging and applying data to unlock advanced use cases, such as personalization, guided selling and even the surfacing of insights.  

While many companies are experimenting with GenAI with straightforward use cases like content creation, executives are exploring a diverse range of use cases across four main categories: 

  • Boosting productivity: Improve employee productivity through content creation, code generation and more.  

  • Augmenting customer engagement: Utilize AI-powered chatbots, product search, personalization and so on. 

  • Leveraging data for instant insights: Tap into a wealth of data in real-time to optimize pricing, inventory and more. 

  • Enhancing product development and innovation: Enable designers and innovators to create novel product concepts and optimize designs.   

Here’s an overview of use cases that businesses are already exploring — and some that are still rather unexplored — as a guide to your GenAI journey.

Boosting productivity

“AI is productivity software,” stated a Forrester Research report on AI adoption. “It is designed to improve worker productivity and productivity is good for business.” Indeed, a lot of the opportunities — as well as the threats and myths — surrounding GenAI revolve around if (or how) this technology will replace millions of jobs. Actually, the real impact of GenAI is to make employees more efficient and productive. In addition to helping marketers create marketing copy faster and more efficiently, GenAI assists developers in writing and reviewing code, enabling faster data analysis and more. 

Maximizing productivity in applications like the creation of content, code generation and debugging, simplifying integrations and parsing documentation is all about leveraging extensive and openly available data. Let’s find out how GenAI is already helping businesses enhance organizational productivity.

Content creation

Let’s start with the core building block of GenAI: Creating brand-new content, be it text, images, videos and other multimedia content. Based on predefined criteria, GenAI can help companies generate and refine product descriptions, social media posts and so much more. 

While GenAI frees up human resources for more strategic tasks, the reality is that human oversight is needed to ensure whatever GenAI comes up with is factually correct and created according to brand guidelines. 

Product descriptions 

Every company relies on accurate product information across channels, but generating product information for product listing pages (PLPs) and product detail pages (PDPs) is no easy task. GenAI provides an optimal solution to solve tasks related to product information, such as generating product names and descriptions that can even be automatically optimized for SEO. 

Automating product descriptions can be achieved relatively simply: By giving a set of inputs and training the data, GenAI can create compelling copy according to a specific tone of voice or customer type. With open architecture and APIs powered by composable commerce, enriching product descriptions becomes much more straightforward. 

Because GenAI excels in combining multiple sets of information, personalizing interactions becomes much easier and faster. For example, if you’re looking for a car seat that comfortably fits in a small car for under 100 USD, AI can compare that request to a vast dataset against product descriptions and provide you with a list of recommendations. You can take a step further with product detail pages by A/B testing them, so you can try out what content works best for your audience. 

Last but not least, GenAI can assist companies in translating product descriptions across regions to localize experiences more effectively. 

AI-enabled code generation and debugging 

GenAI offering capabilities like code generation and debugging are a game-changer for companies to increase innovation. Similar to content creation, generating code with AI may not be production-ready and requires human oversight, but it does help in reducing development time and effort, as well as accelerating time-to-market for eCommerce implementations. 

For instance, commercetools provides an Auto-GPT plugin and real-time sync capabilities where LLMs (large language models), trained on our data, create a landscape of possibilities in interactive engagement and user prompt responses. Plus, you can get nearly production-ready code on ChatGPT to get started with commercetools.

Try it out! AI-enabled nearly production-ready code

With our extensive, well-documented, standards-compliant APIs and a vast amount of source code in the public domain, GenAI can easily write code that’s nearly production-ready. Pull up ChatGPT today and enter the following prompts in GPT-4:

  • Write a [framework or language of your choice] frontend for commercetools.
  • Write an integration in [framework or language of your choice] to connect commercetools with [any MACH®-based vendor of your choice].
  • Write a data migration script in [framework or language of your choice] to migrate data from Hybris 6.4 to commercetools.

AI-powered developer assistants and documentation 

Open and publicly available documentation empowers users with deep insights and accessibility, so it’s easier to navigate extensive information. This is particularly important as implementing new tools and systems should be accomplished faster and more efficiently, so companies can tap into the power of new technologies without constraints. 

As long as the information is available and datasets are trained, GenAI can provide meaningful information, code suggestions and more.

AI-powered developer assistants by commercetools

Supercharge your commercetools adoption with AI-powered developer onboarding tools, designed to help your engineering team onboard faster. AI-powered Docs Assistant Easily find answers to your commercetools questions: Simply type your question and get a detailed response with the links to all the relevant documentation pages. Plus, with an AI-powered Code Generator, you can create practical demo code for your everyday use cases — such as generating an API client or adding to a cart — in seconds.

As a part of commercetools Foundry, a pre-composed solution that accelerates composable implementations by 30%, you can unlock the benefits of GenAI to implement composable commerce faster and more efficiently.

Automating commerce implementations

GenAI can be used to automate low-level implementations of solutions, such as commercetools, with “Build me a website that…”-style prompts that build MVPs of commerce experiences. We ran an experiment that showed GPT-4 is proficient in enhancing and expanding code patterns, and can introduce commendable programming patterns and syntax over time. While GenAI needs very clear and precise requirements to generate meaningful code, using GenAI to bootstrap a basic application could be used in a potential commercetools implementation. 

Naturally, human oversight is needed throughout the entire process. Plus, combining AI-powered tools for improved results, like GPT-4 for coding, Midjourney to create the design and Figma to adapt the design for the code, can bring surprisingly good results.

Augmenting customer engagement

The use of artificial intelligence in customer engagement isn’t new, with the use of AI-powered chatbots and personalization as the main use cases for a direct interface with customers. According to Forrester Research, chat is GenAI’s most common customer-facing application in B2C commerce solutions due to its ability to significantly improve the reliability of responses. Indeed, modern chatbots increasingly use conversational AI techniques like natural language processing (NLP) to understand the user’s questions and automate responses in real-time. 

But there’s much more than AI-powered chat (aka, conversational AI) that boosts customer engagement. GenAI opened the door to a string of new (or improved) applications, from enhancing product search and personalization to interactive in-store experiences. 

Product search

Traditional keyword-based searches often yield limited results, leading to frustration and suboptimal user experiences. GenAI, however, enables more intuitive and context-aware search functionalities, improving product discovery and relevance as it provides the ability to search by posing questions or querying a description of what consumers intend to purchase. In other words, the paradigm in product search is shifting: Instead of having users trying to figure out the right keywords or sentences for the search engine to provide meaningful results, GenAI enables the search engine to interpret what the user is saying to get results.  

GenAI also allows users to search for products using images rather than text by analyzing visual features and patterns to identify similar products. NLP models can also take advantage of GenAI, allowing conversational interactions with search engines, making it easier for users to express their preferences and find relevant products.

Personalization, recommendations and guided selling

By leveraging advanced algorithms to understand and anticipate individual preferences, behaviors and needs through a combination of data analysis, machine learning and NLP, GenAI can tailor recommendations to match a customer’s specific interests and preferences. Unlike traditional recommendation engines that rely on static rules or segmentation, GenAI dynamically adapts recommendations in real time based on user behavior and feedback. 

Moreover, GenAI can generate recommendations that enable guided selling across multiple modalities, including text, images, audio and video. This allows businesses to engage users through diverse content formats and channels, enhancing the overall user experience and driving engagement and conversion. 

Another area GenAI excels is in personalizing PDP information, like text, images and even sounds, per user persona based on demographics, source of traffic and other data. Today, most shoppers will click directly through PDPs from social media, so there’s an opportunity to create a personalized experience: For instance, a boomer coming from a Facebook group and a Gen-Z user coming from TikTok should get targeted, personalized experiences, which are more likely to resonate with each of them instead of a generic product landing page. 

Customer reviews summary 

Customer reviews are crucial for companies to turn interest into conversion. However, the sheer amount of reviews for specific products and services can seem overwhelming to customers. GenAI can help by summarizing reviews, making them more easily digestible. Amazon, for instance, launched an AI-generated customer review to highlight the good, the bad and everything in between. 

But you don’t have to be a retail giant to achieve this: Adorama, a camera, electronics and film equipment retailer, leverages GenAI to fine-tune useful content from user reviews, FAQs and other sources, bringing them all in one place. The goal is to keep the customer on their website instead of straying away to Google or Amazon for more product and customer review information. 

Interactive in-store experiences 

GenAI enables businesses to implement AR (augmented reality) and virtual try-on experiences in-store, allowing customers to visualize products in real-world environments before making a purchase. By leveraging AI-powered image recognition, businesses can offer immersive try-before-you-buy experiences for products such as clothing, cosmetics and furniture. As AR devices evolve, like Apple Vision Pro headsets, such immersive experiences are steadily moving toward mainstream adoption in the years to come. 

Smart mirrors and interactive displays powered by GenAI can provide personalized product recommendations, style suggestions and virtual fitting sessions in-store. By analyzing customer preferences, body measurements and style profiles, these AI-driven interfaces offer tailored recommendations, transforming the in-store shopping experience and driving sales.

For example, the discount store chain Five Below uses generative AI to help customers find what they’re looking for in its incredibly large assortment. GenAI assists in going through a tremendous amount of data to give indicators in minutes instead of weeks. By surfacing insights with astonishing speed, Five Below is able to unlock the power of data in real-time to make in-store experiences meaningful and seamless for customers. 

Customer-generated features 

Providing useful — and sometimes, fun — ways of giving customers a taste of GenAI is a clever way of boosting loyalty and even virality. B2C companies have been particularly successful in integrating GenAI features into advertising campaigns, promotions and more. 

One such example is Moonpig, a Britain-based greeting card retailer. The company launched a feature powered by GenAI to help customers come up with the right words for their greeting cards. The online home store for furniture, Wayfair, launched a GenAI-based tool to create shoppable “photorealistic images to enable consumers to envision their own homes in new styles by simply uploading a picture of their space.”

Leveraging data for instant insights

As an internal enabler, data is at the heart of every interaction and being able to tap into a wealth of information instantly is critical for personalization strategies, product search and so many more use cases that directly impact the shopper. 

By surfacing insights from various data sources and helping untangle unstructured data effectively, GenAI enables companies to generate insights at lightning speed, so they can adapt strategies and tactics according to what the data is telling them. 

For instance, a vast amount of commerce data and insights are scattered across disparate systems, posing challenges for business users to locate and utilize them effectively. Through prompt engineering and advanced search engines, GenAI can uncover signals and patterns, facilitating various use cases such as customer segmentation and customer reviews to improve product recommendations.

It’s all about data and being able to test something quickly to see if it will work, and potentially moving on if it doesn’t. At the end of the day, having the data and evaluating it and understanding it, and using AI to help you do that faster, can really help you get there, because it gives you indicators that could take so many usually weeks to get to you and it can get it to you in minutes. So I think that's really exciting.
Paul Johnson

Vice President of Engineering, Five Below

Enabling an unrestrained data flow is crucial for a successful GenAI implementation. Businesses must orchestrate insights from diverse, unstructured data sources, and align them with key customer and user journey information. This is precisely where composable commerce emerges as a game-changer: The combination of unlimited data access and a composable tech stack empowers businesses to fully harness the potential of GenAI.

Pricing optimization strategies 

Companies can leverage GenAI to implement dynamic pricing that maximizes revenue while meeting customer demand and market conditions. GenAI can analyze historical sales data, market trends, competitor pricing, etc. to forecast demand and identify pricing opportunities. 

In addition, companies can also tap into GenAI to segment customers based on their preferences, purchasing behavior and willingness to pay. A/B testing and experimentation can also help create alternative pricing scenarios and analyze their impact on key performance metrics to refine their pricing strategies. Finally, companies can implement sophisticated pricing rules and algorithms that automate pricing decisions based on predefined criteria. 

Inventory management 

By leveraging advanced algorithms and data-driven insights, GenAI models trained on historical sales, seasonality and trends data can provide demand patterns with greater accuracy and efficiency. 

Such analysis also applies to demand forecasting for specific products as well as customer behavior. GenAI integrates seamlessly with existing supply chain management systems, ERP systems and inventory management software to streamline forecasting processes and facilitate data sharing via APIs.

Enhancing product development and innovation

Unleashing the power of GenAI, designers and innovators can create novel product concepts, optimize designs and personalize offerings based on customer preferences and market trends. 

Design new products and concepts 

By analyzing data, such as customer feedback, competitor offerings and industry trends, GenAI generates innovative concepts that inspire creativity and drive innovation. While not commerce-specific, it’s a use case that certainly impacts brand positioning, customer engagement and productivity. 

More than creating new stuff, GenAI also helps companies optimize existing products by automatically generating alternative design iterations and variations. 


GenAI facilitates rapid prototyping and visualization of product concepts through virtual simulations, 3D modeling and rendering techniques. By generating photorealistic prototypes and visualizations, GenAI helps designers and engineers validate concepts, communicate ideas and iterate designs more effectively, reducing time-to-market and development costs.

Experimenting with GenAI: Be intentional about your use cases and goals

Experts anticipate substantial growth in GenAI implementations, especially as more companies tackle data hygiene and leverage personalization strategies to increase conversions and revenue. Productivity applications are also growing at lightning speed, as businesses need to ramp up the use of cutting-edge tools and systems to boost commerce experiences. 

That said, what use cases are the most important for your company? What are the pain points your business is currently facing that GenAI could potentially help with? At this stage, it’s crucial to set a plan on realistic use cases that bring business value faster, instead of complex applications that resemble a science fiction movie. 

Undoubtedly, GenAI is a new tech that needs time and effort to mature, but you can already unlock the benefits of it starting now by leveraging composable commerce. The combination of unlimited data access and a composable tech stack empowers businesses to fully harness the potential of generative AI. 

As Smita Katawar, Senior Vice President of Data and Technology at the American supermarket chain Wegman’s, said: “For AI to be smart and meaningful, it has to connect data from various aspects of a customer’s journey. When you have composable and easy communication pathways within your architecture, it just makes the foundation for the futuristic AI experiences very simple.”

If you’re ready to experiment with generative AI on commercetools, use our comprehensive API documentation to get started.

Marc Stracuzza
Marc Stracuzza
Director of Portfolio Strategy, commercetools

Manuela Tchoe
Manuela Tchoe
Senior Content Writer, commercetools

Manuela Marques Tchoe is a Content Writer at commercetools. She was a Content and Product Marketing Director at conversational commerce provider tyntec. She has written content in partnership with Facebook, Rakuten Viber and other social media platforms.

Related Blog Posts