Generative AI
retail & eCommerce
use cases

Just like a juggler tossing flaming torches and crystal balls into the air, a marketing team in eCommerce and retail has to manage many conflicting elements at once. From creating a general campaign message that appeals to a wide array of shoppers, to ensuring precise timing across multiple channels, marketing to retail audiences requires intense focus, coordination, and control. As the marketing team carefully adjusts the pace and content of their campaigns, the goal is always to deliver a seamless experience that sparks delight with every interaction.

Generative AI lessens the burden on marketing folks by helping them quickly and easily synthesize data and create personalized content and ads that are more effective and engaging.

The key functions of generative AI for retail/eCommerce marketing

Create

Staying ahead of new campaigns and product turnover with fresh, on-brand copy is no easy task. After all, there are only so many ways to say “sale” and “new product arrival.” AI helps retail marketers ‌quickly generate new ideas and create personalized campaigns that resonate with customers through buzz-worthy content.

Other than your people, your proprietary data is your biggest competitive advantage in the ever-shifting retail and eCommerce landscape. Generative AI helps turbocharge your content efforts by autonomously transforming existing data and content into endless variations that embed relevant messaging into every experience.

Analyze

Conducting thorough audience, competitor, and customer research is a crucial step for any successful retail/eCommerce marketing strategy — it’s a must for making sure your strategy is on-point and your message is hitting the mark. Plus, a rewarding retail/eCommerce marketing strategy requires savvy data analysis to make sure you invest every dollar in the right place. Generative AI helps your team answer questions and swiftly discover insights to craft effective campaigns that resonate with target audiences.

Govern

As marketing teams expand their content to more platforms, it becomes increasingly difficult to ensure that brand guidelines are being followed everywhere. Manual proofreading of content can be tedious and time-consuming, taking away from the time needed to create valuable content.

Generative AI can be used to create content that adheres to your brand’s style guide, rules, and regulations and help marketers create content that resonates with their targeted audience. AI can also be used to identify any content that violates your brand’s guidelines or contains offensive language, ensuring that only compliant content is published.

Marketing use case examples

Type	Example
Create	Write three versions of Google ad copy for this product. Write a product description using our voice.  Draft a press release. Write ten ideas for BOGO sale email headlines.
Analyze	What are the most popular channels used by our target customers? What influencers is our social media audience following on TikTok? When do our competitors start launching seasonal campaigns? What are the demographics of the top buyers of this product?
Govern	What legal disclaimers are missing from this promotion copy? Rewrite this outdated web copy to follow our new brand guidelines.

Support professionals and customers alike face significant challenges in a retail setting. High ticket volumes, unhelpful chatbots, and rerouting to try to find the right agent are problems that can ruin anyone’s day, no matter which side of the interaction you’re on. 

Generative AI can make life easier for customer service teams while also providing solutions that serve customers more efficiently and accurately.

The key functions of generative AI for retail/eCommerce customer support

Create

Striking the perfect balance between customer service, product knowledge, and sales can be tricky, but that’s what it takes to deliver the best customer experience. Generative AI helps retail customer teams with content generation by providing automated, personalized content that helps reduce customer service agents’ workload and improve the customer experience.

Retail customer support teams face the challenge of transforming data and content from various sources into meaningful information that’s easy to understand and accessible to customers. To do this successfully, teams must employ creativity and patience to ensure that customers receive the highest quality of support. Generative AI helps customer support teams easily and quickly transform data and content into more personalized experiences, enabling smarter customer service processes.

Analyze

Conducting research for a retail customer support team can be challenging due to the variety of consumer preferences, the limited and often biased sample size, and the difficulty in isolating the specific causes of customer satisfaction or dissatisfaction. Generative AI helps support teams conduct research quickly and accurately, providing data-driven insights to improve customer experience and retail operations.

Managing customer support data is a complex task — it requires the right mix of cutting-edge analytics and common sense to truly understand customer needs and predict future customer behavior. 

Generative AI can help retail customer support teams make sense of large amounts of data and quickly identify trends, enabling you to prioritize and address customer issues quickly. AI can also provide valuable insights into customer sentiment, equipping your team with the data you need to better understand and serve your customers.

Govern

Retail customer support teams face several challenges when it comes to enforcing brand guidelines and compliance. These challenges include inconsistent brand messaging, human error and inconsistency, training and onboarding difficulties, scalability issues, and the complexity of multichannel support. These challenges can impact customer trust, increase legal and reputational risks, and hinder brand consistency.

Generative AI helps retail customer support teams enforce brand guidelines and compliance by ensuring consistent messaging, reducing human error, simplifying training, enabling scalability, and supporting a unified experience across multiple channels. It improves customer satisfaction, brand loyalty, and operational efficiency.

Customer support use case examples

Type	Example
Create	Write a step-by-step how-to on processing a return. Write a troubleshooting guide for call center agents. Write an order status email. Turn this customer support call recording into a troubleshooting playbook.  Create an FAQ based on ‌last week’s chatbot sessions. Turn this order tracking data into a delivery status SMS. Update order confirmation emails to reflect our new refund policy.
Analyze	What are our most common customer support queries? What communication channels do our customers prefer? How do customers feel about the customer service they’ve received?  Summarize this help center article. Which responses are prompting customers to ask for an agent? What service requests represent upselling opportunities? What areas for improvement should we consider based on qualitative customer survey responses? Review this spreadsheet of support tickets. Suggest help center articles which could address the most common topics. Create a bulleted summary of this help center article.
Govern	Make sure support agents are using approved product names and descriptions.

Operations teams have a lot to do, and they need to do it well: forecasting, synthesizing information from many different sources and vendors, and generating informational text for an ever-growing number of SKUs. These challenges can impact profitability, customer satisfaction, and overall operational efficiency. Generative AI can take a huge load off operations teams’ shoulders by automating and simplifying these tasks.

The key functions of generative AI for retail/eCommerce operations

Create

Whether it’s creating product descriptions or handling vendor communications, the operational content demands of a retail business can be overwhelming. 

Generative AI allows retail teams to create and adjust internal and external-facing communications on the fly, freeing up time to focus on other tasks, and streamlining the entire process.

Analyze

Supply chain issues paired with the pace of the industry in the past few years have put pressure on retail and eCommerce operations teams to act fast and communicate issues to employees and customers alike. 

Generative AI can analyze heaps of data and give accurate demand forecasts, helping teams optimize their inventory and avoid costly mistakes like running out of stock or having too much. It can also gather information from different sources and vendors, putting it all together in one place and giving teams actionable insights and recommendations.

This analysis will provide retailers with the knowledge to order and manufacture wisely, optimizing the supply chain and delivery process.

Govern

Retail operations teams need to ensure that their operations align with regulations and standards, which can be a complex and time-consuming task. From monitoring product safety and labeling requirements to managing data privacy and security, compliance issues can arise at multiple stages of the retail process. 

Generative AI can help alleviate these challenges by automating compliance monitoring and flagging any deviations or non-compliance issues. By analyzing data and comparing it against relevant regulations, generative AI can provide real-time insights and recommendations to ensure that operations teams stay on track. This not only saves time and effort but also helps mitigate risks and maintain a trustworthy reputation in the market.

Operations use case examples

Type	Example
Create	Draft a playbook on negotiating with suppliers. Automatically create a product description once a SKU enters our system. Generate a shipping delay announcement. Use this logistics meeting recording to write a fulfillment RFP.  Turn this manufacturer recall update into a company-wide memo.
Analyze	What are the shipping options available for this product? What product category historically runs low at this time of year? Which suppliers meet our ESG standards?   Which products aren’t selling as forecast? Conduct market segmentation analysis to identify opportunities for growth. Analyze store traffic and recommend adjustments to store layouts. Turn this sales data into a quarterly predictions report.
Govern	Update our current collection of transactional emails for compliance. Customize product descriptions and specs for multiple marketplace formats.

Learning and development (L&D) teams have a big job to do: produce quality, highly accurate, and engaging training for employees at every level throughout the organization. Comprehensive training and development materials are an essential part of providing consistent customer experiences, especially in a retail setting. 

Generative AI can help learning and development teams in the retail industry by streamlining and automating training, assessments, knowledge management, and course recommendations. ‌By leveraging generative AI, teams can create personalized learning experiences tailored to the needs of each employee. Additionally, generative AI can generate and supply real-time data to training and development teams, allowing them to quickly and easily identify strengths and weaknesses among their workforce, as well as providing insights into the effectiveness of training programs.

The key functions of generative AI for retail/
eCommerce L&D

Create

Creating content for L&D can be a time-consuming process, often requiring hours of research and development to create materials that are engaging and effective for learners. 

Generative AI is a powerful tool for L&D teams, providing the ability to quickly create content tailored to the specific needs of their learners. With generative AI, teams can produce content quickly and efficiently, allowing them to focus on other aspects of their job.

Repurposing existing L&D content can be time-consuming and costly. With tight deadlines and limited resources, teams often find it difficult to meet their goals.

With generative AI, retail and eCommerce learning and development teams can swiftly turn existing resources into high-quality, personalized content. Then your team can focus time on what matters most: delivering impactful learning experiences for your frontline employees. For example, an L&D team could quickly create detailed, store-specific training materials for sales associates by taking existing resources and using generative AI to customize them automatically for different store locations. Or generative AI can automatically generate custom learning paths based on the results of an employee questionnaire.

Analyze

Researching and understanding the data behind employee training is a difficult task for retail learning and development teams, especially when it comes to making decisions quickly and accurately. With ever-evolving customer demands and a competitive landscape, it’s more important than ever to stay ahead of the curve.

Generative AI can save learning and development teams time and energy by quickly and accurately summarizing large amounts of data and providing insights that would otherwise be inaccessible. For example, AI can identify patterns in customer interactions to help create customer service training modules.

Govern

L&D teams have to make sure that all employees receive the right training to follow the rules and regulations. This includes topics such as workplace safety, diversity and inclusion, and customer privacy. It’s not easy to keep track of everything, especially when you have a big and diverse workforce. 

Generative AI can help automate compliance by flagging language that violates legal and regulatory rules, ensuring accurate and compliant training materials. It can ensure factual accuracy by detecting claims that need to be fact-checked. Additionally, generative AI can help maintain brand alignment by ensuring that all work reflects the brand, messaging, and style guidelines, using inclusive and unbiased language. Overall, generative AI can streamline workflows, improve productivity, and help create a compliant and knowledgeable workforce.

L&D use case examples

Type	Example
Create	Generate questions and answers related to corporate policies and procedures to include in online courses. Draft a script for a video training module. Develop a training simulation scenario. Use this source material to give me a 90-minute training agenda formatted into a table.
Analyze	Summarize employee surveys on the effectiveness of different learning programs. Evaluate the impact of emerging technologies and trends on the learning program. Create personalized recommendations for employee training based on individual roles, skills, and development objectives. Based on employee performance data, what skills do specific employees need to function at their peak performance? What’s the optimal path for each employee’s individual learning and development goals? Which training interventions have been successful, and which have not, based on employee performance data post-training?
Govern	Make sure employee onboarding and orientation materials use inclusive language.

Product teams in the retail industry have to come up with new products, manage existing ones, and keep up with what customers want. It involves a lot of research, working with suppliers, and collaborating with different teams. On top of that, they have to make sure their products meet customer expectations, follow the rules, and stay competitive.

But here’s where generative AI can be a game-changer. It can help product teams by automating tasks like researching the market, analyzing trends, and keeping an eye on the competition. With generative AI, product teams can get valuable insights, make smart decisions based on data, and improve their product development process. This means they can launch better products that customers love and stay ahead in the retail game.

The key functions of generative AI for retail/eCommerce product teams

Create

Creating new content every time a product launch is announced can be a huge drain on product teams’ resources and creativity. From creating product descriptions to managing customer reviews, retail product teams face a unique set of challenges when it comes to generating content quickly and accurately.

Generative AI can help solve the challenge of creating consistent, on-brand content for retail and eCommerce product teams, while also saving time and resources. By using natural language processing algorithms to identify relevant content, teams can generate new product descriptions, product titles, and other content in a fraction of the time it would take them to do it manually. 

Repurposing content for the retail space can be time-consuming and complex, often requiring teams to create multiple versions of content to fit the different needs of their customers. With tight deadlines and pressure to deliver, it’s no wonder retail teams are looking for more effective, efficient ways of repurposing content.

Generative AI helps product teams repurpose and transform content quickly and easily. With generative AI, retail product teams can create content that’s both engaging and uniquely tailored to their customer’s needs. For example, AI can quickly generate personalized product descriptions for apparel items across different sizes, colors, and styles. From there, it can automatically produce product descriptions in different languages and categorize items into taxonomies. This ensures that customers have consistent, accurate, and up-to-date information regardless of language or device.

Analyze

Research in a retail context can be time-consuming and tedious, making it difficult for product teams to stay up-to-date with the latest industry trends. Analyzing data can be a huge challenge‌ — ‌from understanding customer buying behavior to optimizing pricing strategies.

Generative AI can help product teams quickly and easily extract valuable insights from research data. For example, AI-driven sentiment analysis can identify the most popular opinions on a product or service, giving product teams a better understanding of customer needs.

Govern

Product teams in the retail industry have to make sure their products meet all the rules and regulations. From ensuring product safety and accurate labeling to managing data privacy and security, there’s a lot to keep track of.

But here’s where generative AI can lend a helping hand. It can automate compliance monitoring, flag any issues, and provide real-time insights and recommendations. With generative AI, product teams can save time, reduce risks, and maintain a trustworthy reputation in the market. So, they can focus on what they do best — creating awesome products that customers love, without worrying about compliance headaches.

Product use case examples

Type	Example
Create	Create custom product descriptions that accurately reflect the features and benefits of a given product. Generate a product launch communication plan. Generate product titles that are catchy and descriptive, while also on-brand.
Analyze	Identify customer opinions on a product or service. Turn product features list into competitor comparison charts. Develop market research insights to inform product design decisions. Looking at historical sales data, what is the best shopping day to launch this new product? What does this customer loyalty data tell us about repeat purchase and cross-selling opportunities? Which customers are more profitable for a particular product or line of products?
Govern	Make in-line suggestions for inclusive language, voice; tone, and correct terminology in all content. Automatically classify retail products into specific categories, based on product descriptions and other text data. Standardize retail product data across different geographical markets, formats, and currencies, for global retail operations.

Functional requirements

With the right tools in place, all of these‌ business-transforming use cases are possible. Here are the capabilities your generative AI software should have:

• Knows your products
• Adheres to your legal and regulatory rules
• Speaks in your voice
• Writes in your style
• Integrates easily into existing workflows
• Understands relevant data formats
• Detects claims and checks facts
• Protects everyone’s data (yours and your customers’)
• Meets the compliance needs of secure organizations

Case study

OPERATIONS

How Adore Me uses Writer to save 35 hours per writer per month

Adore Me is a digitally-native intimates brand that Victoria’s Secret & Co. recently acquired. They offer a wide range of lingerie and apparel for women of all sizes and budgets. Adore Me stands out for its innovative Home Try-On commerce service, which allows customers to try on products before making a purchase. They’re also committed to sustainability and have become the first Certified B Corporation intimate apparel brand in the US. Adore Me’s inclusive product assortment and strong brand authenticity resonate with Gen Z and Millennials, making them a valuable addition to Victoria’s Secret & Co.

Ranjan Roy, Adore Me’s SVP of Strategy, had a years-long interest in AI. He was eager to use it in his work, but according to him, “I’ve watched this space closely, but things were never really prime time-ready.” That is, until he found Writer.

Before Writer: Struggling to keep up in a fast-paced world

Anyone who’s ever worked in a startup setting knows it’s fast-paced, to say the least. Before Writer, Ranjan and his team were feeling the pressure of having to do it all on their own. 

Ranjan wanted an AI tool that would take care of “a lot of your day-to-day, more monotonous work — or at least [make it] much, much faster.” He knew that if he found a tool that did this well, he’d free up time for his whole team to work on more strategic, creative endeavors.

A well-tailored solution that scales

In his search for the right AI tool, Ranjan was impressed with how well-tailored Writer was to “actually solving real business problems for us.” Immediately, he could see how he and his team could use Writer to write copy, streamline processes, and make people more efficient in their daily work.

According to Ranjan, the “lightbulb moment” arrived when using Writer to build a press release, something he historically hated doing. After feeding eight bullet points into an AI app, Ranjan received a press release — along with a quote from the company’s CEO that he hadn’t even provided. And the quote was factual, related to an upcoming partnership they were announcing. In other words, Writer had taken the quote from an internal source, knowing it was relevant. “That was the moment it clicked,” says Ranjan.

Today, Ranjan and his team use Writer to:

• Write product descriptions automatically, saving every writer hours of repetitive work
• Automatically enforce environmental, social, and governance (ESG) compliance
• Free up resources so team members can work on more high-impact projects

Sailing into a strategy-focused future

For Ranjan, the biggest benefit of using Writer is that it allows his team to “automate the boring stuff,” allowing him and his team to work on more creative efforts. With all the time and effort saved, his team has been able to focus on the bigger creative picture. 

His advice to anyone wondering if Writer will work for their team? “Everyone wants to communicate better. There are so many people across your organization that have so many small things [to write],” and giving them the tools to do so can make everyone more strategic.

Try out Writer today

Ready to see what generative AI can do for your retail and eCommerce business?

Try Writer out today and see how it transforms the lives of your employees and your customers.