How Conversational AI Benefits the Retail Sector

Retailers face the challenge of managing costs while delivering exceptional customer service operating on tight margins. In such a scenario, conversational AI proves invaluable by effective dialog management, providing cost-effective 24/7 customer support, personalizing shopping recommendations and combating shopping cart abandonment. 

And when we talk of retail, e-commerce can’t be far behind. 

Conversational AI’s role and impact on e-commerce are indelible, boosting online sales by 67% by virtue of virtual assistants, chatbots and voice bots.  But before we understand conversational AI in retail, let’s understand what conversational AI is.

What is conversational AI?

Conversational AI is an artificial intelligence technology that mimics human conversation by leveraging AI technologies like natural language processing and machine learning. Serving as automated virtual agents, conversational AI tools like chatbots and voice bots engage with customers, decipher their queries and take brand-configured actions. It also facilitates realistic and relevant customer interactions without human intervention in various domains, notably customer service.

Learn more: How Does Conversational AI Help Customer Service?

6 Benefits of conversational AI in retail industry

The fusion of Artificial Intelligence and retail has led to a paradigm shift, redefining the shopping experience for consumers worldwide. Let's delve into the benefits that highlight the impact of Conversational AI in this bustling sector.

1. Improved revenue per customer

Conversational AI empowers businesses to implement effective sales and conversion strategies that are tailored to each customer’s behavior patterns and preferences.

It allows retailers to craft targeted marketing campaigns, personalize customer experiences, and optimize product offerings. With real-time data updates and interactions, Conversational AI ensures that your marketing strategies and product offerings stay consistently relevant and effective.

AI algorithms identify opportunities for upselling, cross-selling and personalized offers. Targeted interactions not only increase revenue per customer but also cultivate a sense of value and exclusivity, strengthening the customer's affinity for the brand and extending their customer lifetime value (CLV).

Example: An online beauty store uses Conversational AI to understand individual outfit preferences. As a result, the AI tailors product recommendations and curates outfit selections during customer interactions, creating a more engaging and customized experience.

2. Reduced cart abandonment

You can utilize live chat features with proactive prompts to highlight the latest deals, engaging at-risk customers. In fact, you can continue the conversation by employing AI-driven outbound calls to tackle cart abandonment. It drives higher conversion rates while enhancing the overall digital customer experience.

Example: A fashion retailer notices a trend of cart abandonment during the checkout process. Leveraging AI-driven outbound calls, the system automatically contacts customers who left items in their carts. The AI provides personalized incentives, such as limited-time discounts or free shipping, successfully recovering potential lost sales and improving the overall customer experience.

3. Reduced customer churn

With conversational AI, you establish a robust customer support system that operates on preferred communication channels round the clock. You build trust and loyalty over time by showcasing an unwavering commitment to exceptional service.

What else?

Advanced AI tools provide insights through sentiment analysis, enabling tailored support experiences. This fosters long-term customer relationships and customer retention in a hyper-competitive industry like retail.

Example: A customer contacts the company's support chatbot to inquire about a delayed refund. The conversational AI acknowledges the concern, gathers relevant information and initiates an expedited refund process. During the interaction, the AI system explains the steps being taken to resolve the issue promptly, reassuring the customer and reinforcing the commitment to efficient after-sale service.

4. Enhanced efficiency

Imagine a work environment where mundane tasks are seamlessly handled by AI-led conversational AI software. This liberates employees to focus on high-value, meaningful work that drives innovation and growth.

These virtual agents also serve as invaluable support systems, offering real-time guidance on optimal customer service. This dynamic support ensures consistent delivery of exceptional experiences and prevents breaches of Service Level Agreements (SLAs).

Example: Imagine a customer walking into a busy retail store seeking information about ongoing promotions. Instead of waiting in line for a human representative, they engage with a virtual agent through a user-friendly kiosk or mobile app. The virtual agent, equipped with natural language processing, instantly understands the customer's query and provides detailed information about the current promotions, available discounts and associated terms and conditions.

How to implement conversational AI in the retail market

There are incredible benefits conversational AI brings to retail and it will be an integral part of it in the future. Understand how to implement it through this six-step process.

1. Input generation

Begin by capturing verbal or written input from users, which serves as the initial interaction with the conversational AI system.

2. Automatic speech recognition (ASR)

Utilize Automatic Speech Recognition (ASR) to translate the received verbal input into machine-interpretable data, setting the stage for further analysis.

3. Analyzing input with NLP

Employ Natural Language Processing (NLP) to decipher and analyze the translated text. This step enhances the system's understanding of the user's input, capturing nuances and context.

4. Dialog management

Craft human-understandable responses using Dialogue Management, a process fueled by natural language generation (NLG). This step ensures coherent and contextually appropriate interactions.

5. Reinforcing learning

Implement machine learning (ML) techniques for reinforced learning. Over time, the conversational AI application or model learns from user interactions, evolving and fine-tuning its responses for heightened accuracy.

With the implementation sorted, let’s discuss the wide and varied use cases of conversational AI for retail in the next section.

Use cases of conversational AI for the retail sector

From personalized shopping experiences to streamlined customer support, the retail industry is undergoing a transformative journey where every interaction becomes an opportunity for engagement. Brands understand this, and they are leveraging conversational AI to enhance the customer journey using conversational AI.

🔎Journey stage: Product Discovery

A virtual shopping assistant can help a new visitor navigate your e-commerce website, collect contact information and understand preferences and needs by following the visitor around the website. This way, conversational AI removes friction from the discovery stage and leaves a lasting impression on prospective customers.

📊Journey stage: Consideration

A product information chatbot can be used to furnish quick information about the products that the visitor browses. It can answer questions about product features, pricing, models, availability and technical specs. The visitor needn’t dig into dense product pages and can even get their hands on similar products for quick comparison of features, prices and ratings/reviews.

🛒Journey stage: Purchase

An order processing chatbot removes friction at the point of sale by delivering information on refund/exchange policies, shipping time and other frequently asked shopper questions. By keeping customers focused on the impending purchase, conversational AI prevents card abandonment and other churn issues.

🎧Journey stage: After-sales support

A common grouse of customers is lousy post-sales support, which acts as a deterrent to repeat purchases. To avoid this, you can establish an after-sales conversational AI solution that troubleshoots product usage issues and delivers personalized demos to improve product adoption.  

🤝Journey stage: Loyalty

Conversational AI can also field questions about customer loyalty programs and related issues like points redemption and exclusive deals. In addition, it can collect authentic reviews in exchange for brand-approved discounts and use this user-generated content as social proof.

Still looking for inspiration?

Look no more. Take a leaf from Prada’s conversational AI journey here:

Renowned for housing some of the world's foremost luxury brands, the Prada Group remains dedicated to elevating its value through strategies that enhance both visibility and allure. This commitment to evolution led the Group to forge a strategic alliance with Sprinklr, aiming to seamlessly transpose the innovative ethos that has fueled the brand's success since its inception in 1913.

Challenge: Recognizing the need for a high-quality, comprehensive digital sales experience, the Prada Group sought to empower sales agents to connect with customers on popular social platforms such as Facebook and Instagram.

Solution: The Prada Group expanded its partnership with Sprinklr, adding Sprinklr Service to enable sales agents to provide unparalleled digital sales experiences. Leveraging conversational commerce capabilities, agents could now communicate, support and complete sales transactions directly within social channels like Facebook and Instagram. 

What did Prada get with Sprinklr’s conversational AI in retail? 

1. Global social selling operations: The Unified-CXM platform empowers the Prada Group to conduct social selling on a global scale, streamlining sales, service, and customer retention through a unified and integrated solution. 
2. AI-driven consumer insights: Leveraging cutting-edge AI-driven analytics, the Prada Group obtains in-depth insights into brand health and relevant events. By tracking millions of mentions across diverse topics, the Sprinklr platform provides a comprehensive understanding of consumer sentiments, aiding targeted social selling strategies. 
3. Comprehensive campaign management: With the Unified-CXM platform, the Prada Group gains full visibility into the entire lifecycle of social selling campaigns, from creation to publishing and performance analysis across modern channels. This comprehensive oversight enables precise targeting, ensuring effective reach to relevant audiences, while also offering valuable insights into the performance and resonance of marketing content. 

Impressive, right?

If you, too, are a retail leader keen to increase your brand share, click below to see how Sprinklr is helping more than 200 retailers redefine their shopping experience.

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