11 Prominent Use Cases for Conversational AI in Retail

The retail industry is undergoing a seismic shift, driven by changing customer behavior and major technology trends. Conversational AI is at the heart of this transformation.

With 87% of retailers already using AI and 60% planning to boost AI investments in the near future, one thing is clear: Conversational AI in retail is now essential for businesses looking to enhance customer experience and streamline operations.

In this article, we’ll dive deep into conversational AI for retail, looking at the different ways it can be used to add value. Read on to explore:

• Major use cases of conversational AI in retail, with real-life examples
• How conversational AI benefits retailers and customers alike
• Key steps for implementing conversational AI in your retail business
• Why it pays to work with an expert technology partner like Intellias

What is conversational AI in retail?

Conversational AI in retail involves using AI-powered software, such as retail AI chatbots and virtual assistants, to interact with customers. Conversational AI models combine technologies such as natural language processing (NLP), machine learning  (ML), generative AI and voice recognition. This enables chatbots to interpret what customers need, provide human-like responses and adapt to individual preferences.

The adoption of conversational AI in retail has been supercharged in recent years by changing customer expectations. Since the COVID-19 pandemic, online shopping has soared in popularity. In 2023, 20% of retail sales were made online, with that figure expected to increase to over 22% by 2027.

At the same time, customers are demanding more from retailers. They expect human-like interactions, personalized recommendations and instant support around the clock. This is where conversational AI in retail can be a game-changer.

Key use cases and applications

Conversational AI’s ability to provide slick, personalized interactions enables it to disrupt a broad range of customer-facing processes. Below, we’ll explore 11 of the most powerful conversational AI use cases for retail.

1. Customer support

Customer support is perhaps the most obvious and widespread application of conversational AI in retail. AI-powered chatbots are now considered standard, with 73% of customers expecting websites to offer them. They’re popular, too — 74% of internet users prefer using them for simple questions.

AI-powered customer support is a win-win for retailers and their customers. The former get to streamline call centers by automating the handling of low-complexity issues and directing more complex ones to human operatives. The latter get instant answers to questions anytime, and on any device. Walmart, for example, has handled millions of customer inquiries by providing chatbots that offer instant answers to questions about order status.

2. Personalized shopping

Conversational AI doesn’t just enhance traditional services. It offers new ones altogether. Now, customers can receive personalized product recommendations based on their purchase history, product searches and market trends. For companies, this means endless opportunities to add value.

Beauty retailer Sephora, for example, allows its customers to take a quick skincare quiz. Based on the answers, the AI creates bespoke product recommendations that fit the person’s skin type and needs. The result is happier customers, greater engagement and higher conversion rates.

3. Order & returns management

Conversational AI ensures that retail customers are always kept in the loop with real-time updates and order tracking. If a product arrives and isn’t right, customers can be quickly guided through the returns process by a chatbot instead of filling out clunky forms.

Source: Ada 

4. Inventory and product availability

If a customer sees the perfect jacket but wants to try it on in person, they need to know whether it’s in stock at their nearest branch. With conversational AI technology, customers can get instant answers to stock queries. They can even reserve items via simple conversational chatbots, or ask questions about sizing and fit.

5. Marketing and promotions

When it comes to retail promotions, personalized offers outperform generic ones every time, leading to an improvement in margins of up to 3%. Customers love personalized marketing communications too, with 71% expecting it and 76% getting frustrated when retailers don’t offer it.

So, how do personalized marketing and promotions work in practice? Imagine an AI-powered chatbot crunching user data and browsing history, combining it with data on stock levels and market trends, and coming up with a tailor-made offer on that pair of sneakers the customer has had their eyes on.

Source: Zendesk 

6. Feedback and sentiment analysis

Making a sale needn’t be the end point of an interaction. With a retail chatbot, you can follow up with customers to ask them about their experience of shopping with you. Your AI can then combine data from countless customers to deliver actionable insights about sentiment and satisfaction. This helps you understand what you are doing well, and where you could improve.

7. In-store assistance

Conversational AI in retail doesn’t have to be limited to eCommerce. Customers who visit physical stores can benefit from virtual assistants accessible via digital kiosks and interactive displays. These virtual assistants answer customer questions, provide product recommendations and help customers locate or order specific products.

8. Appointment scheduling

Conversational AI can help customers book appointments. Instead of outdated web forms, customers can simply converse with the AI to specify their availability and appointment needs. This enables high-end retailers to book customers in for styling sessions, dress fitting or virtual consultations without lifting a finger.

9. Loyalty and reward programs

AI can enhance customer loyalty programs. For example, a conversational AI system can suggest personalized perks in-app or nudge customers when they’ve become eligible for certain rewards. This helps increase customer engagement with loyalty programs, encouraging repeat sales that drive profitability.

10. Payment processing support

AI chatbots can guide customers through the payment process, helping them to choose the right options and troubleshoot failed transactions. AI-powered chatbots reduce the time it takes to complete an order by up to 70% compared to traditional apps.

Starbucks, for example, introduced an AI-powered chatbot to help streamline customer orders. Customers can talk to the chatbot and tell it what they want, without needing to type anything. The chatbot then routes the order to the barista team to process.

11. Omnichannel customer engagement

The beauty of conversational AI is that it can be deployed across multiple channels simultaneously. So, whether customers visit a retailer’s website, app, or social media channels, they have the same flawless interactions.

How to implement conversational AI in retail

Implementing conversational AI isn’t something you can do overnight. Realizing the chatbot use cases we outlined above requires a combination of careful planning and technical expertise. Here are some key steps to follow for a successful implementation.

Define clear objectives

Any successful conversational AI strategy starts by defining clear objectives. These act as a guiding star, ensuring that every decision you make is in service to an overarching goal. To help you define clear objectives, start by asking some important questions:

• What are our current challenges or inefficiencies?
• How can conversational AI help us overcome those challenges?
• What exactly are we hoping to achieve through AI adoption — e.g. greater efficiency, increased sales, reduced costs, or happier customers
• How exactly will we measure success? What metrics and benchmarks will we use?
• What are our competitors doing well? Where can we offer something different or better?

The answers to these questions will help you define use cases. Moreover, it will help you define an effective conversational AI strategy that’s aligned with your broader organizational goals.

Select suitable tools and vendors

With your strategy set, you can turn your mind to acquiring the right tools for the job. There are plenty of ready-made, enterprise-grade solutions available, including offerings from OpenAI, Meta, Microsoft, and Zendesk. Below is an example of a simple conversational AI builder from LivePerson.

When weighing up different AI applications, it’s important to consider their UX, scope, and the risks associated with each. Risks can differ depending on the level to which an application is exposed to external stakeholders, as well as the sensitivity of content it handles. It’s also important to understand the general risks that are inherent to conversational AI products, and what guardrails different vendors offer to mitigate them.

You’ll also need to identify and prioritize specific requirements for your conversational AI tool, including language support, privacy, security, and integration with back-end systems. Scalability is another major consideration, both in terms of a solution’s ability to handle increased demand but also its ability to handle additional use cases. For example, if you choose a conversational AI tool for customer support, will it be flexible enough to use in HR as well? Does the application offer additional competencies, such as voice biometrics, content generation, or intelligent document processing?

Alternatively, you can build a conversational AI system from scratch, tailoring it to your specific needs and use cases. Both off-the-shelf and custom-built solutions come with some trade-offs, so it’s important to know the pros and cons before making a decision. Below, we’ll break down how both options compare across different factors.

The best choice will depend largely on the size of your business, your budget and your long-term vision. If in doubt, working with an external technology partner like Intellias can help you make the right decisions and build AI systems that drive powerful ROI for the long term.

Integrate with existing systems

Conversational AI tools need to work alongside your existing systems. This means integrating with the following platforms to enable a joined-up ecosystem and seamless data sharing:

• Customer relationship management (CRM) system
• Point of sale (POS) system
• Enterprise resource management (ERP) system
• eCommerce platform
• Inventory management system
• Marketing and customer support platforms

Integrating conversational AI into your existing tech stack can be challenging, especially if you are using legacy systems. We recommend planning the integration process carefully and conducting a thorough audit of your existing systems to understand the complexities involved.

Again, Intellias can help here by providing expert technical guidance and, if necessary, modernizing your existing tech architecture.

Train and continuously improve AI

To realize the benefits of conversational AI for retailers, AI models must be trained on relevant data relating to customers, products, prices and broader market trends. The more data an AI can consume, the better it will understand your business and its customers, resulting in more accurate and relevant outputs.

In addition to giving your AI the information it needs to do its job, you’ll also need to fine-tune how it communicates. Just like a human customer service operative is trained to represent your business and speak its language, so is your AI. Ensure that your AI is trained to:

• Master your company’s tone of voice
• Use industry-specific lingo
• Understand customer needs and challenges

Benefits of conversational AI for retailers

Conversational AI isn’t just fancy tech. It offers a more effective way of engaging customers that drives efficiency, scalability and profitability. Below, we’ll look at some of the key benefits of conversational AI for retail businesses.

• Happier customers. With 24/7 support and personalized interactions, conversational AI ups the CX game for retailers, ensuring customers are looked after every step of the way.
• Increased sales. Happier customers tend to stick around and spend more. AI provides personalized product recommendations and upselling/cross-selling opportunities that boost the bottom line.
• Operational efficiency. AI automates the repetitive manual processes that take up so much time and resources. This allows retailers to get more done with less, freeing up human agents for more complex tasks.
• Data-driven insights. Conversational AI captures valuable customer data from multiple sources in an instant, turning them into insights that shape better decisions.
• Unbeatable scalability. Unlike human support teams, AI can scale up or down in real time. Peak times and spikes in demand are no issue, and quality and consistency are never impacted.
• Competitive edge. Conversational AI is a highly adaptable technology, providing retailers with ample opportunity to differentiate themselves from competitors with unique applications that customers love.

As the chart below shows, adopting AI-powered virtual agents has a tangible impact on retail businesses, resulting in happier customers and more efficient support services.

Source: IBM

Major challenges and considerations

To realize the benefits we’ve outlined above, retailers have to navigate all sorts of challenges. Below, we’ll outline some of the major hurdles to successful AI adoption.

• Data privacy and compliance. Ensuring that AI-driven conversational interfaces align with GDPR and other data protection regulations is a major consideration for retailers.
• Maintaining a human touch. It can be tempting to see conversational AI as a silver bullet to all retail processes. This can lead to an over-reliance on AI at the expense of human interactions. The key is to find the right balance between automation and emotional intelligence.
• Technical issues. AI chatbots aren’t standalone tools. To work effectively, they must integrate with your existing technology. Seamlessly integrating AI with legacy systems can be challenging without the right expertise.
• Differing attitudes to AI. Not all customers are the same. While your average Gen-Z customer might not think twice about interacting with an AI chatbot, older generations might prefer traditional customer service channels, despite their flaws. This generational divide can impact retailers with a predominantly older customer base.
• Ongoing maintenance. Conversational AI needs regular updates to keep pace with customer expectations and new use cases. This requires ongoing investment in both tech infrastructure and expertise.
• A lack of in-house expertise. AI is a new technological frontier, and many businesses don’t have the expertise or experience in-house to maximize the potential it offers. This can lead to poor implementation or ineffective use cases that do more harm than good.

Of course, you can overcome all of these challenges by working with an expert technology partner, like Intellias.

Intellias — your partner for conversational AI in retail

Intellias is at the forefront of AI adoption. Our expert team helps retailers maximize the opportunity that AI offers, enabling them to drive engagement, grow their business and provide slick, personalized interactions at scale.

We can help you at every stage of your conversational AI journey, including:

• Identifying real-world use cases and creating actionable roadmaps
• Building, implementing and customizing conversational AI to meet your specific needs
• Integrating conversational AI tools with your existing systems
• Providing ongoing technical support and optimization
• Complying with AI governance and security best practices

For example, we helped a global Fortune 500 retailer launch a powerful AI chatbot. The chatbot was designed to train sales representatives on how to sell a new line of premium products. It also doubled as a customer engagement tool, helping customers find out more about the new products.

We built the solution from scratch, combining NLP and ML algorithms. Once ready, we integrated the chatbot into the business’s social media channels and web apps, enabling users to access it anywhere. We later scaled its capabilities to span multiple languages. The results have been impressive, enabling our client to:

• Deliver faster, more engaging training for sales staff
• Cut operational costs while increasing efficiency
• Increase customer loyalty and brand exposure
• Offer detailed product explanations and personalized recommendations
• Access powerful retail analytics and data-driven insights

Future trends in conversational AI for retail

However groundbreaking conversational AI may seem right now, these are still early days in terms of adoption and potential. So, what can we expect in the coming years, and how will it impact the retail industry? Here are some examples of conversational AI trends to watch out for:

• Advanced NLP. Smarter conversational AI models will grasp context, emotion and nuance at human-like levels.
• Voice commerce. Customers will be able to shop for products simply by talking, thanks to voice-activated virtual assistants.
• Visual AI. AI chatbots will not only be able to interpret human speech but also images, helping customers find similar products faster.
• AR Integration. AI and augmented reality will provide truly immersive shopping experiences, enabling customers to try on clothes or position new furniture virtually.

The bottom line

Conversational AI is reshaping the retail industry, transforming how retailers engage customers. From endlessly scalable customer support to personalized marketing, chatbot use cases in retail are driving new levels of efficiency and customer satisfaction.

For retailers looking to stay ahead of the curve, conversational AI now forms a central part of a modern retail strategy. But success with AI isn’t a given. It requires careful planning, consideration and access to deep technical expertise.

If you’re looking to maximize the potential that conversational AI offers, Intellias can help. With a team of AI experts, we can help you design, develop and deploy AI tools that achieve your retail goals.