Retailers and CPGs face a tough reality today:

  • Evolving customer demands
  • Impending recession and inflation at a record high
  • Increasing cost of goods and services across the entire supply chain
  • Talent retention challenges

The name of the game is creating operational efficiencies while still delivering best-in-class experiences.

It’s no wonder then, that technologies like OpenAI’s ChatGPT and DALL-E have become extremely popular, accumulating more than 1 million users a week after launching.
These technologies are a form of generative artificial intelligence. Generative AI is a type of artificial intelligence system capable of generating text, images, or other media in response to prompts. Content can be delivered in the form of text, images, video, or even music.

Large-scale, generative AI models have a deep understanding of language and code, enabling new reasoning and comprehension capabilities for building cutting-edge applications and game-changing experiences. Applying these models to a variety of use cases opens new possibilities in the types of digital experiences deliverable to customers.

For retailers and CPGs, generative AI can deliver hyper-personalization, innovation, and intelligence across several business areas:

  • Consumer engagement: By automating asset creation for advertising and campaigns, innovating with smart, user-generated content, and managing brand presence and representation across channels.
  • Marketing and store operations: By improving customer experience through more in-depth analysis of customer calls and complaints via automated summaries, and by enhancing employee experience by automating report generation and workforce scheduling for store managers, for example.
  • Back-office management: By improving response time and accuracy of internal communications, IT and HR helpdesk tickets, and/or procurement matters.
  • Automation innovation: Automating everything from product descriptions to marketing emails to onboarding training and enablement of employees.

10 ecommerce use cases for generative AI

Future-looking digital leaders are experimenting with ways to incorporate generative AI in their go-to-market strategies. Generative AI can help create efficiencies for the business and a better, more personalized experience for the shopper, improving your bottom line across the entire supply chain.

Product discovery

1. Streamlined content creation
Automatically create “evergreen” marketing and brand content (product guides, how-to instructions, buyer’s guides, etc.) to publish as needed.

2. Personalized product search and recommendations
Utilize customer intent and preference to deliver dynamic descriptive product content that resonates better with shoppers and delivers the personalized experience they expect ... at scale.

Commerce operations, administration, and analytics

3. Product descriptions for SEO
To avoid product descriptions not optimized for SEO – or without a description all together, generative AI can create persuasive descriptions of products that also support SEO optimization strategies.

4. Crowd-sourced customer feedback at scale
Use AI to search customer reviews for specific products across multiple channels, sources, and marketplaces. Streamline the sourcing of this information and feedback to better control your brand, or to respond to customer feedback faster and improve satisfaction.

5. Product quality analysis
AI can help identify production errors, anomalies, and defects by analyzing images of products in production, enabling analytics to improve product quality across R&D and through the delivery experience.

Supply chain optimization

6. Supply chain disruption predictions
Predictive insights from generative AI can surface impacted orders with proactive identification of external factors, whether it’s weather, finance, or geopolitics – all things that could impact critical supply chain processes.

7. Intelligent inventory forecasting
Automate inventory management by analyzing past orders and customer preferences to forecast demand and suggest inventory levels.

Bridging the online and offline experience

8. Smart(er) store associates
Integrate machine learning and AI across every endpoint – both in stores and behind the scenes. Enable store associates to track, manage, and replenish stock levels in real-time so businesses can be better prepared to respond to unexpected events.

9. Personalized in-person checkout experience
Use generative AI to create and deliver personalized order summaries to store managers at checkout, creating more opportunities for up-sell, cross-sell and improving the customers’ experience.

Post-order experience

10. Chat for “digital humans”
Use ChatGPT to generate content for digital avatars that can personalize and improve customer engagement. Use tools like the Microsoft Whisper API, for example, for human-level accuracy of speech-to-text to add an even more human-like component. Utilize conversational commerce capabilities to better answer order status questions in real-time, or by offering personalized recommendations for individual shoppers.

Conversational commerce with generative AI

Let’s dig deeper into one of the ways generative AI can impact your ability to deliver superior commerce experiences.

Conversational commerce, a common use case for generative AI in commerce, is a topic that has been buzzing for a few years now. Simply put, conversational commerce is about the intersection of messaging technologies and shopping. It’s become relatively commonplace for businesses to offer chat capabilities on their site or app to help guide the shopper through the buying process and answer basic customer service questions.

Generative AI enables brands to take conversational commerce to the next level. It can be integrated into all your digital experiences to drive personalization across channels. Generative AI can learn and remember what your shoppers’ preferences are as they shop, opening opportunities for you in the form of a personal shopper, personalized product descriptions, and the ordering experience.

Personal shopper

Today shoppers’ journeys are very linear and transient.

Let’s say you set out shopping for a new outfit and you search for a shirt in a specific color or style. You then look at pants, and then shoes. Most websites treat these searches as completely distinct interactions – but they weren’t to you.

Some websites try to solve this by simulating a salesperson via chatbot and asking you a series of pre-defined questions — which is a horrible experience and robotic in nature.

A better opportunity is to incorporate generative AI behind your website — integrating sophisticated intelligence and context to an otherwise normal shopping experience online. This would allow you to learn about a shoppers’ preferences as they shop for the shirt so that those preferences can be applied to the experience as they search for pants.

On-demand, personalized product descriptions

Another way generative AI elevates conversational commerce is by understanding the shoppers’ preferences and rewriting product descriptions tailored to that visitor in real time. This creates a personalized product discovery process that mirrors one they would get in-store from a sales associate’s guidance.

Let’s say you’re shopping for a bike online. The website can gather that you are searching for a comfortable ride, something that responds well to gravel and rough terrain, and that you’re based in Minneapolis, MN (according to your IP) where there are many lakes with paths to ride around. Generative AI can use that information to transform the product information and descriptions based on visitor context, site searches, and content clicks, creating an experience that truly speaks to the shopper.

Reorder intelligence for routine purchases

Let’s say a shopper makes regular purchases at Target, roughly three times every week. Your digital experience with Target could remember the types of coffee beans you buy weekly or your shampoo preference at roughly the same time every few weeks you need to replenish.

Add-to-cart suggestions or auto-generated shopping lists for your next store run would make these routine purchases easier and create a level of service that many shoppers now expect. Generative AI can create these advancements in the experience.

Opening new commerce opportunities

Generative AI opens even more ways for brands to take advantage of artificial intelligence and continue to both improve the shopping experience and create efficiencies in the way the business operates.

Future-looking leaders in retail and CPG are moving to modern commerce to bring these efficiencies to life. A modern commerce platform, like Sitecore OrderCloud, will support seamless integration to best-of-breed AI technologies, like Microsoft’s Azure AI.

Kayla Bryant is Director of Enablement Programs at Sitecore. Connect with her on LinkedIn.

Mike Edmonds is Senior Director of Strategy, Worldwide Retail, Consumer Goods & Gaming at Microsoft. Connect with him on LinkedIn.