A retail chatbot is an AI-driven tool designed to engage with customers just like a human would, helping them find the perfect product, track their orders, and even manage returns. Studies show that using chatbots in retail can cut customer service costs by up to 30%, all while making customers happier.

The growing popularity of retail chatbots is part of a larger trend towards AI in customer service. By 2025, nearly all customer interactions—around 95%—are expected to be managed by AI.

If you’re ready to create a retail chatbot for your business, you’ve come to the right place. This step-by-step guide will walk you through building an AI-powered retail chatbot that can save you both time and money.

How Does a Retail Chatbot Work? 

A retail chatbot operates using a combination of advanced AI technologies to interact with customers and provide personalized assistance. Here’s a breakdown:

• Large Language Models (LLMs): LLMs, such as GPT-4, are trained on vast amounts of text data to understand and generate human-like language. In retail chatbots, LLMs  can generate appropriate responses and engage in natural conversations, closely mimicking a human assistant.
• Retrieval Augmented Generation (RAG): RAG combines AI-driven retrieval methods with generative models to enhance the accuracy of responses. The chatbot first retrieves relevant information from a predefined knowledge base (e.g., product details, policies) and then uses an LLM to generate a coherent and contextually appropriate reply, ensuring responses are both accurate and conversational.
• Knowledge Base (KB): This is a structured database that stores information relevant to the retail business, such as product catalogs, FAQs, and company policies. The chatbot, powered by AI, accesses this knowledge base to provide customers with up-to-date and precise information. 
• Natural Language Processing (NLP): NLP is a branch of AI that enables the chatbot to understand, interpret, and respond to human language. It involves techniques like tokenization, entity recognition, and sentiment analysis to process customer input and determine the intent behind queries.

Retail Chatbot Use Cases: Top 3 Examples

At a minimum, a basic retail chatbot should be able to help customers with:

1. Shopping experience: Offering product recommendations to guide their purchases.
2. Orders and purchases: Assisting with tasks like tracking order status, canceling orders, and requesting refunds.
3. Returns and exchanges: Explaining return policies and facilitating exchanges.

Keep reading to learn how you can use Voiceflow’s template to build an AI chatbot that includes all these features.

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Enhanced Shopping Experience

Typically, e-commerce lacks the in-person shopping assistants found in brick-and-mortar stores, who guide customers through products and offer personalized recommendations. According to a McKinsey report, 70% of consumers expect personalization in their online shopping experience, yet only 40% feel they receive it. 

A retail chatbot can help create a more human-like interaction, leading to a more personal and intuitive shopping experience. For example, buttons, carousels, and product cards can offer customers personalized recommendations. 

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Using Voiceflow’s template, you can easily customize your product recommendation menu. What’s more exciting is that you can create a dynamic carousel, one that doesn’t require you to manually upload each product simply by uploading your product information into our knowledge base.

Orders and Purchases

65% of customers expect their issues to be resolved in one interaction, but this can be tricky if you are running an e-commerce business. Chatbots can meet this demand by providing quick, precise responses, 24/7. 

Voiceflow’s template allows you to build a chatbot that can efficiently handle routine inquiries like checking order status or canceling orders, while seamlessly transferring more complex questions to a real-life agent. 

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This hybrid approach combines the efficiency of automation with the empathy of human support. According to a McKinsey report, businesses that blend AI with human interaction can reduce customer service costs by up to 30% while improving customer satisfaction by up to 20%. 

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Returns and Exchanges

Human customer support agents often find themselves inundated with tickets that involve handling repetitive tasks, such as explaining return policies. This can lead to burnout and reduce their availability to address more complex, nuanced customer issues. 

An AI-powered agent with a custom knowledge base can alleviate this burden using a custom Knowledge Base (KB) and Retrieval Augmented Generation (RAG). RAG enables the AI agent to retrieve accurate information from a vast database, such as company policies, and then use advanced language models like GPT to convey that information in a natural, human-like manner. Leveraging AI in this way can enhance customer satisfaction while significantly reducing operational costs, as it allows human agents to focus on resolving more intricate, high-value inquiries.

Voiceflow’s template lets you easily build a knowledge base that your AI agent can use to find answers. Plus, it allows the AI to transfer the ticket to a real agent when needed. All it takes is adding a block—no coding required.

Build and Launch Your Retail Chatbot In 30 Minutes

Voiceflow makes it easy for anyone to design, prototype, and launch AI-powered, human-like retail assistants in no time. 

With Voiceflow’s platform, you don’t need to be a tech expert to get started. Start with our templates, and you’ll have your retail chatbot up and running in minutes—plus, it’s free!