How to make AI shopping assistants your brand ambassadors

It is predicted that 95% of all purchases will be made online by 2040. To stay ahead of this curve, retail and eCommerce brands should welcome their new brand ambassador – AI shopping assistants.  

When you think of a shopping assistant, you probably associate them with luxury brands; a perk of buying expensive clothes, bags, shoes, or even furniture. But with the rise of online shopping, personal shopping assistants aren’t so exclusive anymore. 

Retail and eCommerce customers expect convenient experiences when they shop online. Using AI personal shopping assistant is the perfect way to make their shopping journey smoother and more personalized. 

What is an AI shopping assistant? 

An AI personal shopper is available 24/7, capable of handling many customer requests at once while offering personalized online shopping experiences through intelligent recommendations. 

Even better, AI agents constantly learn from interactions, using purchasing history and preferences to improve their responses over time. 

Which AI is best for shopping? (+ AI shopping assistants use cases) 

The mix of personalization and real-time data is transforming how retailers connect with customers. Acting like a digital personal stylist, AI shopping assistants make every interaction more relevant, helpful, and engaging at every stage of the journey.  

By handling tasks behind the scenes, virtual assistants eliminate the need to switch between apps or wait on hold, making the entire shopping experience faster, more convenient, and more enjoyable. While the goal is to simplify online shopping, these AI assistants do far more than just suggest the perfect outfit, they serve as always-on, intelligent support systems. 

To make this possible, personal shopping services integrate various types of AI that work together to better understand and assist customers: 

Conversational AI: Natural conversations, instant support 

Conversational chatbots use AI, machine learning (ML), and natural language processing (NLP) to understand what users want and reply naturally. They continuously learn from interactions, adapt to user behavior, and improve over time, offering 24/7 customer support across channels like WhatsApp, Instagram, and websites. 

Use cases: 

• Instantly answer FAQs about payments, shipping, or product details 
• Share real-time updates about your orders 
• Send back-in-stock alerts or cart reminders to help you complete your purchase 

Agentic AI: Autonomous assistance with a human touch 

Agentic AI takes shopping assistants a step further. It enables shopping assistants to act independently. It handles multi-step tasks like processing returns or guiding users through complex queries, only involving human agents when needed. This makes customer service faster and more efficient. 

Use cases: 

• Smoothly guide customers through the return process 
• Assist with detailed product comparisons or multi-part queries 
• Confirm orders instantly after purchase 

Agentic RAG: Accurate answers, backed by real-time data  

Agentic RAG combines generative AI with an external knowledge base, like product catalogs, policies, manuals, and past purchases. This enables large language models (LLMs) to retrieve accurate information from multiple sources and handle more complex tasks and workflows. As a result, assistants can instantly gather relevant data, manage detailed queries, and deliver precise responses across channels. 

Use cases: 

• Provide fast, accurate responses to customer questions 
• Deliver special offers based on your profile and shopping activity 
• Ensure up-to-date product and policy info, no matter where you’re chatting 

Benefits of an AI shopping assistants 

Using AI technologies in retail and eCommerce can boost performance, save time, and reduce costs. Here’s how: 

1. Increased ROI 

AI powered shopping assistants offer smooth, personalized shopping journeys across messaging channels. By reducing friction and offering relevant support, they increase the chances of repeat purchases, customer retention, and long-term loyalty. 

2. Improved customer engagement 

By learning from behavior and purchasing history, AI assistants can deliver interactive, personalized conversations that engage users and make shopping more enjoyable. 

3. Cross-selling and upselling 

It can recommend products or upgrades that align with customer needs. This boosts average order values through smart product discovery. 

4. Smarter inventory management 

AI helps analyze trends, predict demand, and optimize inventory levels. This reduces stockouts and overstocking by ensuring you always have the right products available. 

5. Increased conversion rates 

As they offer real-time assistance, personalized product recommendations, and consistent support throughout the shopping journey, AI assistants help eliminate obstacles and lead shoppers to complete their purchases. 

Tips to train and optimize your AI shopping assistant 

Like any great brand ambassador, your AI assistant needs to learn your voice, understand your customers, and stay updated with your offerings. 

Here’s how to make sure your assistant evolves with your business: 

1. Provide it with the right data 

Your AI is only as good as the data it learns from. Integrate it with your product catalog, inventory system, FAQ documents, and customer data platform. Every conversation is also an opportunity for AI chatbots to gather zero-party data that shoppers willingly share. Use this data to build rich customer profiles within your customer data platforms (CDPs) and improve your AI assistant to deliver even more personalized, high-impact customer experiences. 

2. Align tone and brand voice 

Customers should feel like they’re speaking with your brand, not just a robot. Make sure your assistant uses a tone that matches your brand personality; friendly and playful, or polished and professional. Also, consider developing a chatbot persona or identity so it feels like customers are interacting with a real person. This helps build trust and strengthens your brand connection. 

3. Regularly review interactions 

Use analytics to track how your assistant is performing. Are users completing purchases? Where are they dropping off? What questions are getting repeated? This helps you identify gaps and refine your assistant’s scripts and capabilities. 

4. Run A/B tests for messaging 

Test different conversation flows, greetings, and promotional messages to find what resonates most with your audience and drives engagement or conversions. 

5. Involve your human agents 

AI works best alongside humans. When the AI agent is no longer able to help, escalate seamlessly to a live agent who can continue the conversation with full context. This hybrid model ensures a smooth, high-quality experience for your customers. 

The journey ahead: Navigating the future of retail 

AI and cloud-based omnichannel solutions are shaping the future of retail, especially in digitally advanced markets. To succeed, retailers must embrace AI technologies, continuous learning, and combining physical and digital touchpoints. 

While we’ve explored the power of various AI agents, their full potential depends on integrating them with customer data platforms (CDPs) and automation tools. A Conversational Experience Orchestration Platform (CXOP) provides a single, unified interface where retailers can build and deploy intelligent chatbots, store and utilize customer data across the entire journey, and automate routine tasks. 

Simply put, CXOP brings together all the necessary components to orchestrate a flawless customer experience, including the strategic deployment of AI assistants at the right time. 

Ultimately, the goal is to improve human connections and create a customer-centric shopping experience through conversational engagements. 

These AI assistants serve as brand ambassadors, delivering tailored recommendations, quick answers, and smart guidance. They reshape customer journeys while increasing ROI, reducing complexity, improving customer satisfaction, and building customer loyalty.