Conversational artificial intelligence (AI) is transforming retail by enabling natural dialogues between customers and machines. According to Salesforce, AI-driven conversational interfaces will power 85% of customer service interactions by 2025.
As consumers increasingly embrace conversational AI, retailers have huge opportunities to optimize customer engagement while automating operations. In this comprehensive guide, we explore the top 9 use cases of conversational AI across the retail customer journey – from browsing to purchase and beyond.
The Rise of Conversational AI in Retail
Leading retailers like Walmart, Sephora, and Home Depot have already adopted conversational AI in various forms like chatbots and virtual assistants.
According to IBM estimates, 80% of retailers plan to implement AI-powered conversational platforms by 2020. Key drivers of this growth include:
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Demand for personalized experiences: Over 62% of customers expect tailored engagement from retailers.
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Need for instant, accurate answers: 67% of consumers prefer chatbots for quick questions while shopping.
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Increasing use of voice assistants: 50% of shoppers have used voice technology when browsing online.
Source: IBM
As adoption surges, conversational AI is empowering retailers to provide individualized assistance, operational efficiency, and tailored recommendations – ultimately driving revenue growth.
9 Key Use Cases of Conversational AI in Retail
Let‘s explore the top 9 retail use cases where conversational AI delivers proven value.
1. Customer Support
Conversational AI is extremely useful for automating customer support and delivering quick, accurate answers. According to Salesforce research, 67% of consumers prefer chatbots for quick inquiries and 50% have used a chatbot when shopping online.
AI-powered chatbots can handle common retail customer service tasks like:
- Answering frequently asked questions
- Account management
- Order status checks
- Troubleshooting issues
- Returns and exchanges
This allows human agents to focus on complex issues and building customer relationships. According to IBM, retail chatbots can resolve up to 80% of routine customer service queries, leading to 20% higher customer satisfaction.
Leading retailers using AI for customer service include:
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H&M: The fashion retailer implemented an AI chatbot that handles ~1.5 million conversations per year.
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Home Depot: Their conversational bot helps customers locate products, get order status, find stores, and more.
2. Customer Feedback Analysis
Analyzing customer sentiments and feedback is critical for retailers. However, manually reviewing surveys, social media, reviews and other unstructured data is time-consuming.
Conversational AI solutions from vendors like Clarabridge can quickly parse large volumes of customer data to identify:
- Pain points in the customer journey
- Product quality feedback
- User experience issues
- Marketing campaign resonance
<img src="https://miro.medium.com/max/1400/1*DV3lsd-vSSG4RG>
These insights allow retailers to continuously improve while responding faster to customer needs. According to Forrester, 57% of firms affirm that AI has helped them identify insights they would have otherwise missed.
3. Dynamic Customer Segmentation
Retailers can leverage conversational AI to develop detailed customer profiles and segment consumers based on their behaviors and preferences.
By analyzing customer data from various touchpoints, conversational AI tools can identify patterns and categorize customers into dynamic groups. This allows highly targeted, relevant marketing and experiences.
Source: IBM
Key benefits of conversational AI-driven segmentation include:
- Personalized recommendations: Provide suggestions tailored to the user.
- Tailored incentives: Customized promotions and offers.
- Optimized product assortments: Match inventory to customer needs.
- Improved conversion rates: Segment-targeted experiences convert at 5-15% higher rates according to Evergage.
4. Online In-Store Experience
Recreating the intimacy of brick-and-mortar stores online improves customer satisfaction. Conversational AI enables retailers to incorporate interactive elements into their digital experience.
For example, Sephora‘s chatbot allows customers to:
- Get personalized skincare recommendations
- Book in-store services
- Find nearby stores
- Schedule curbside pickup
This provides a more engaging, consultative online shopping experience.
Conversational platforms drive 2X more conversions compared to traditional retail sites by recreating personal connections.
5. Order Tracking
Order tracking is a key part of the post-purchase experience. Conversational AI gives retailers an automated way to provide shipment status and delivery updates.
Chatbots integrated with order management systems can inform customers about:
- Order confirmation
- Shipping status
- Carrier information
- Estimated delivery date
- Returns process
This level of transparency improves customer satisfaction and loyalty. According to Statista, 76% of customers want real-time order tracking from retailers.
6. Personalized Shopping Assistance
Conversational AI allows retailers to provide tailored guidance and recommendations to each customer. Virtual assistants can access individual purchase history and profile data to personalize the experience.
For example, a fashion retailer‘s chatbot could:
- Suggest items based on previous purchases
- Recommend sizes or styles that typically fit the customer well
- Show complementary pieces to consider adding to the cart
- Provide styling advice for special occasions
Source: IBM
The result is a convenient, personalized concierge service that boosts sales. For instance, The North Face saw a 60% increase in order value from conversational AI recommendations.
7. Targeted Promotions
Conversational AI enables retailers to serve up promotions tailored to each user based on their unique interests and behaviors.
For example, chatbots can identify:
- Product categories the user frequently browses
- Lapses since the user‘s last order
- Complementary items not in the user‘s purchase history
- Appropriate discounts based on order value
Source: Smaply
This level of personalization establishes trust and increases purchase frequency. Stats show personalized offers have 10x higher click-through rates and conversion rates 5-15x higher than generic promotions.
Leading retailers effectively using AI to personalize offers include Starbucks, Nike, Sephora, and Target.
8. Detailed Product Information
Conversational AI makes it easy for customers to get in-depth product details on demand.
Integrations with product databases allow retail chatbots to instantly answer common questions about:
- Technical specifications
- Materials
- Sizing or fit
- Compatibility with other products
- Ingredients
- Comparison between product variations
Source: CubeChat
This saves customers time and provides confidence during the purchasing process. According to eMarketer, 73% of customers want quick access to detailed product information from retailers.
9. Payments and Refunds
Conversational platforms offer new opportunities to facilitate payments and refunds. Retailers can implement AI chatbots and voice assistants to:
- Process payments and capture key details
- Enable voice-activated purchases
- Generate digital receipts and invoices
- Assist with refund requests and returns
- Detect fraudulent transactions
However, proper security measures must be in place to protect sensitive financial information. According to Business Insider, over 50% of millennials are open to purchasing through conversational platforms.
This article covered 9 diverse use cases where conversational AI can optimize the retail shopping journey and enable more tailored, engaging customer experiences:
- Automated customer support
- Customer feedback analysis
- Dynamic customer segmentation
- Recreating the in-store feel online
- Order tracking and updates
- Personalized shopping guidance
- Targeted promotions and offers
- On-demand product information
- Streamlined payments and refunds
As consumers increasingly embrace conversational interfaces, retailers implementing the right AI-powered use cases will gain data-driven insights, operational efficiencies, and higher sales through contextual engagement.
Early adopters of conversational AI like Walmart, H&M, Sephora, and The North Face are already seeing double-digit improvements in metrics like customer satisfaction, average order value, and conversions. The possibilities for next-level retail experiences through AI are truly exciting!