9 Powerful Use Cases of Conversational AI for Retail

Conversational artificial intelligence (AI) is transforming the future of retail. With capabilities like personalization at scale, seamless integrations, and human-like interactions, conversational AI enables retailers to deliver exceptional customer experiences while optimizing critical operations.

In this comprehensive guide, we’ll explore 9 of the most impactful applications of conversational AI across the retail sector. For each use case, we’ll share real-world examples and data that showcase the technology‘s benefits. Read on to learn how leading retailers are leveraging conversational AI to drive growth and stand out from the competition.

The 9 Use Cases Covered:

1. Customer Support
2. Customer Feedback Analysis
3. Dynamic Customer Segmentation
4. Online In-Store Experience
5. Order Tracking
6. Personalized Shopping Assistance
7. Targeted Promotions
8. Detailed Product Information
9. Payments and Refunds

Conversational AI is Transforming Retail

Before diving into the use cases, let‘s quickly look at how conversational AI is transforming retail more broadly.

Conversational AI refers to technology that enables naturally flowing dialogues between humans and machines, including chatbots, virtual assistants, and more. Some of its key capabilities include:

• Natural language processing to understand nuanced customer questions and requests
• Seamless integrations with backend systems to access live data
• Contextual awareness to continue conversations seamlessly across devices
• Sentiment analysis to understand how customers feel from language
• Hyper-personalization at scale to tailor interactions and offers

According to research from Juniper:

• 80% of large retailers are currently piloting or planning to implement AI over the next 1-2 years. [1]
• Adoption of conversational AI in retail is projected to grow over 15X between now and 2025. [2]
• 73% of retailers believe AI-enabled chatbots improve customer satisfaction and loyalty. [3]

It’s clear conversational AI is rapidly becoming a mandatory retail capability rather than a nice-to-have. Now let’s explore some of its most valuable applications.

1. Customer Support

Exceptional 24/7 customer support is crucial for any retailer today. However, managing high ticket volumes across channels like phone, email, chat, social media, and in-store can be challenging without the right tools.

This is where conversational AI-powered chatbots and virtual assistants come in. By implementing these technologies, retailers can cost-effectively scale support and enable instant self-service for customers.

According to research from IBM, chatbots can handle 70-90% of routine support requests – freeing up agents for more complex issues. [4]

Key capabilities enabled by conversational AI include:

FAQ Bots

• Instantly answer common questions 24/7 without customers waiting on hold
• Reduce simple, repetitive inquiries to lower customer support costs

For example, Sephora‘s chatbot provides immediate assistance with store locations, gift cards, returns, and more.

Multilingual Support

• Serve global audiences by allowing customers to interact in their native languages
• Help retailers expand into new geographical markets

Pizza Hut‘s chatbot seamlessly handles orders in languages including English, Spanish, Brazilian Portuguese, German, Arabic, and Turkish.

Authentication

• Securely verify customer identities before providing account information or processing transactions
• Builds trust by protecting sensitive user data

For example, Lowe‘s chatbot Ask Lowe‘s requests account credentials before assisting with order issues to prevent unauthorized access.

Troubleshooting

• Guide customers step-by-step to quickly resolve issues on their own
• Provides an automated self-service alternative to waiting for agent assistance

Staples‘ Webby-winning chatbot Staples Easy System engages in conversational dialogues to fix problems with orders, deliveries, payments, and more.

By scaling support and deflecting routine inquiries, conversational AI enables retailers to deliver 5-star service levels cost-efficiently.

2. Customer Feedback Analysis

Understanding customer sentiment is crucial for retailers to identify issues proactively and improve experiences. However, compiling insights from surveys, reviews, support tickets, social media, and other unstructured data sources is challenging to do manually or with basic analytics.

Conversational AI solutions are purpose-built to ingest these myriad customer feedback channels and extract meaningful insights using natural language processing, text analysis, and machine learning algorithms.

Key capabilities include:

• Analyze customer feedback data from any source – calls, chats, emails, social posts, reviews, etc.
• Automatically categorize and tag comments based on topics, sentiment, keywords, etc.
• Generate visual sentiment dashboards and reports to spot trends
• Enable drill-down analysis into underlying root causes

For example, the below dashboard from Yellow.ai provides a real-time pulse on customer satisfaction levels across support channels:

A conversational AI sentiment dashboard. Image source: Yellow.ai

With an always-on feedback analysis solution, retailers can rapidly identify pain points, monitor campaigns, and take timely action to optimize experiences.

3. Dynamic Customer Segmentation

Dividing customers into segments allows retailers to tailor messaging, product assortments, promotions, and experiences to different audience groups. However, traditional segmentation based on basic attributes like demographics, purchase history, etc. provides limited insight into changing needs.

Here, conversational AI comes in – by analyzing full conversational history across channels, advanced solutions can uncover deeper insights and cluster customers into dynamic segments in real-time.

For example, Servion‘s EngagementCX solution builds psychographic profiles based on interaction analytics to group customers with similar attitudes, emotions, interests, and needs.

Benefits of real-time conversational AI segmentation include:

• Micro-targeting campaigns to be hyper-relevant
• Personalizing recommendations and offers
• Right-sizing product assortments based on demand
• Optimizing store layouts and merchandise based on local preferences

As an example, if conversational AI detects a rise in fitness-focused conversations among a customer group, a retailer could respond with targeted athleisure wear offers. This level of real-time personalization was impossible before AI.

4. Online In-Store Experience

For ecommerce retailers especially, recreating the immersive, high-touch in-store experience online is crucial. Conversational AI enables digital experiences that mirror the personal, intuitive nature of brick-and-mortar stores.

For example, Burberry partnered with Google to build an innovative conversational app experience. Shoppers can ask for tailored product ideas from store assistants digitally and make video appointment bookings.

Additional ways conversational AI builds online in-store experiences:

• Virtual beauty advisors provide personalized product and regimen recommendations through chat
• Smart fitting rooms with AI-powered mirrors allow customers to request different sizes, styles, colors, etc. while trying items
• AR bots that allow customers to visually overlay products in their actual home setting
• In-store pickup enables reserving items online and conversational bots guiding shoppers to exact shelf locations

Blending digital convenience with an in-store flavor is key for retaining customers. Over 50% of shoppers will abandon purchases if they can‘t replicate physical store experiences online. [5] Conversational AI enables delivering consistent, personalized service across both worlds.

5. Order Tracking

The ability to track delivery status in real-time provides much-needed transparency and helps retailers exceed expectations. However, manually providing shipping updates at scale is difficult.

With conversational AI, retailers can integrate virtual assistants and chatbots directly with order management systems and shipping carriers to enable self-service tracking.

Key capabilities include:

• Real-time ETAs – "Your order is expected to arrive today between 2-4pm."
• Shipping confirmations – "Your order has shipped and is now en route."
• Exceptions handling – Proactively notify customers of unforeseen delays
• Self-service tracking without agent assistance

Order tracking conversational experience. Image source: Yellow.ai

Providing this level of visibility builds trust and heads off many common post-purchase support inquiries. In fact, Yellow.ai found adding order tracking conversations reduced associated support contacts by 45% for a leading retailer.

6. Personalized Shopping Assistance

Today‘s consumers expect personalized assistance and recommendations while shopping – whether online or in physical stores. However, manually scaling personalized service is impossible.

With conversational AI, retailers can deliver tailored shopping guidance, product suggestions, style advice, and other bespoke assistance to each customer.

For example, Stitch Fix leverages an AI stylist called "Alison" to capture style and fit preferences, lifestyle needs, past purchase info, and other data to curate unique boxes for every client.

Other personalized shopping assistance capabilities include:

• Product recommendations based on individual style patterns
• Custom outfit and accessory pairings tailored to the customer
• Complementary item suggestions to help complete a look
• Personalized sizing and fit recommendations based on brand/style preferences
• Curated wish lists and gift ideas based on occasion

83% of shoppers are more likely to purchase again from a retailer that provides personalized recommendations. [6] Conversational AI enables delivering this level of personalization at scale.

7. Targeted Promotions

Generic promotions aligned poorly to customer needs waste budget and annoy shoppers. With data and conversational interfaces, AI can generate tailored offers and recommendations suited to each individual.

For example, Starbucks sends members personalized product suggestions and exclusive deals through its mobile app. These contextually relevant offers see 3X higher redemption rates.

Key capabilities for personalized promotions with conversational AI:

• Individualized discounts, coupons, and exclusive perks based on preferences and history
• Recommend new or complementary products likely of interest
• Early access to sales or new arrivals for top customers
• Adding personalized promotions during conversations with shopping bots

According to research from Epsilon, 80% of customers are more likely to make a purchase when brands provide personalized experiences. [7] With conversational AI, delivering relevant promotions at scale is achievable for any retailer.

8. Detailed Product Information

Immersive product experiences with all the necessary details are required for customers to make informed purchases online. Answering questions on the fly requires significant staff time if not automated.

With conversational AI virtual assistants integrated with product databases, retailers can serve up specifications, materials, care instructions, ingredients, and other information on-demand 24/7.

For example, Whole Foods customers can ask Alexa smart speakers questions about any product in the aisles and get tailored audio responses back instantly.

Key types of product information conversational AI can provide:

• Specifications – dimensions, materials, configurations, etc.
• Usage details – dosage, application methods, recipes, etc.
• Comparisons – how products differ in terms of features, fits, textures, etc.
• Sustainability and sourcing information
• Compatibility with other products

According to research from NewVoiceMedia, 51% of customers want access to more self-service product information. [8] Conversational AI delivers this easily across any channel.

9. Payments and Refunds

Processing payments and handling returns are critical moments of truth where conversational AI can optimize experiences as well.

For payments, conversational capabilities might include:

• Securely saving payment methods for expedited future checkouts
• Voice-activated reordering of favorited products
• Processing payment for purchases directly within a conversational flow
• Generating digital receipts and invoices

And for refunds/exchanges, AI assistants can help by:

• Making it easy to initiate return requests via conversation
• Confirming when refunds have been successfully issued
• Answering policy-related questions if items are past the return window
• Rerouting requests automatically to human agents for complex cases

According to Juniper Research, global retail spend via voice assistants will grow from $2 billion in 2018 to over $40 billion by 2022. [9] Adopting conversational payments now is key to tap into this growth.

Of course, proper security precautions and integrations with payment systems are a must when managing transactions via conversational interfaces.

These 9 use cases only scratch the surface of how conversational AI can transform retail for the better. From automated marketing to warehouse robots you can talk to, the possibilities are truly endless.

With solutions tailored specifically to retail from vendors like Yellow.ai, Servion, and creative.ai, forward-thinking retailers of all sizes are leaping into conversational AI today.

Although an investment is required, the long-term payoff in the form of happier customers, lower costs, and sustained growth makes conversational AI a mandatory retail capability of the future. The data already shows clear ROI – Forrester found automation solutions deliver $8-$12 back for every $1 invested on average.

The bottom line? Shoppers are demanding ever-more sophisticated digital engagement. With conversational AI, retailers can deliver personalization at scale to stand out. The time to implement these technologies is now to get a head start on the competition. Conversational AI marks the future of retail.