How to make AI shopping assistants your brand ambassadors

Learn how AI shopping assistants are transforming the retail landscape, driven by the need for exceptional customer experiences in an era where every interaction matters. 

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 online shopping experiences, and an AI shopping assistant is the perfect way to make their journey smoother and more personalized than ever before.

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

What is an AI shopping assistant?

AI shopping assistants use artificial intelligence to help customers with their shopping activities. A shopping assistant is available around the clock, capable of simultaneously handling a wide range of customer queries and providing tailored, personalized recommendations.

What’s more, thanks to AI, this assistant continually learns from each interaction, constantly refining its performance to deliver even better outcomes. 

Types of shopping assistants

There are two main ways you can build and launch a shopping assistant using chatbots:

Rule-based chatbots

These chatbots are fantastic for fast deployment and simple use cases. They are trained on specific information and can navigate the user based on key words. Rule-based chatbots are ideal for quickly addressing high-volume queries using predefined flows or sending product recommendations.

Conversational AI chatbots

These chatbots offer a human-like conversation and are designed to carry out more complicated use cases. They don’t follow specific rules or restrictions, and can naturally analyze the users input to provide the best response. AI chatbots require training on customer intents and phrases to enable natural conversations.

What can AI shopping assistants do?

The goal of an AI shopping assistant is to elevate the overall shopping experience, not just help you pick the perfect outfit. There are a wide range of use cases that AI assistants can carry out:

  • Providing personalized recommendations
  • Answering FAQs
  • Back-in-stock messages
  • Cart abandonment reminders
  • Order confirmations
  • Send special offers and discounts
  • Order confirmation
  • Delivery information
  • Return processing

Carrying out these use cases with a virtual assistant makes the entire shopping experience smoother, with no need to switch between apps or waiting on a call for an agent to pick up your query.  

AI shopping assistants offer a personalized and catered experience, although majority of the customer journey consists of actions completed by the customer through self-service.

Benefits of an AI shopping assistant

Integrating AI shopping assistants has emerged as a transformative strategy for businesses looking to enhance customer experiences and streamline operations. Companies can leverage these assistants for strategic purposes like optimizing inventory, cross-selling and upselling, and reducing costs. 

1. Reduce costs and save time

Automating routine tasks with AI shopping assistants can significantly reduce operational costs and save time. This includes automating customer queries, order tracking, and basic problem resolution. Businesses can optimize resources and allocate human staff to more strategic and complex tasks.

2. Greater engagement

By understanding customer preferences and behavior, AI assistants can engage users in meaningful conversations, provide a more interactive and personalized experience, and make shopping more enjoyable and memorable.

3. Cross-selling

An AI shopping assistant can easily suggest complementary products or upgrades based on customer selections. This can help your business increase average transaction value by promoting additional items that align with the customer’s needs and wants.

4. Inventory management

AI can help your business optimize inventory levels by analyzing historical data, predicting demand, and identifying trends. This ensures you maintain optimal stock levels and reduces the likelihood of overstocking or stockouts.

This combination of personalized interactions and data-driven insights creates a more competitive and customer-centric environment for your business.

Example of an AI shopping assistant

Hong Kong is a city known as a dynamic global shopping destination. There, the retail and e-commerce sectors are undergoing a significant transformation—all thanks to artificial intelligence and cloud-based omnichannel solutions. 

Let’s take Zalora, Southeast Asia’s fashion leader, as an example. Using generative AI in their business has helped them streamline processes and enhance customer experience by automating responses and ensuring customers have a more personalized experience. 

These innovations are not merely reshaping customer experiences but are also driving business performance to new heights. Engaging customers through the proper digital channels is crucial to thrive in this shifting retail landscape.

What goes into building an AI shopping assistant?

Machine learning algorithms

Machine learning algorithms help AI identify patterns, collect and analyze data, make predictions, and perform certain tasks without being specifically programmed for it. Machine learning helps your shopping assistant analyze interactions between customers and provides relevent outputs based on the users responses. 

Natural language processing 

Your AI shopping assistant needs to offer a smooth and human-like conversational experience. That means the chatbot needs to understand human language and generate natural responses. Natural language processing (NLP) makes this possible by enabling your AI chatbot with sentiment analysis, natural language generation, machine translation, and much more.  

Real-time data collection and analysis 

Your customers can offer up a lot of data about themselves through conversations with an AI shopping assistant. Brands should take advantage of zero party data by collecting this information to build out detailed customer profiles on a customer data platform. This information can be used to help improve experiences with your AI assistant and offer more personalized offers and experiences to your end users.  


This all comes together through a chatbot. You can use a chatbot building platform to create an AI assistant from scratch and make it as simple or complex as you like. Chatbots for retail brands bring your virtual assistants to life and can be improved upon continuously based on the data you collect from your users.

If this all sounds a bit overwhelming or complex, not to worry, you don’t need to design, implement, and deploy an AI assistant on your own. Infobip CX and AI experts can work with you to help create the perfect shopping assistant and can take care of the heavy technical side of things, so you can focus on offering customers the best experiences. 

Talk to an expert 

How to implement an AI shopping assistant


of organizations in Hong Kong use CPaaS and SaaS within their operations


of the surveyed organizations have intentions to increase their communications platform expenditure between 2023 and 2024

Source: Infobip

To stay competitive, businesses in the retail sector need more than just customer support. They require a comprehensive platform to automate and orchestrate customer journeys across multiple channels.

By integrating chatbot services into popular social media platforms like WhatsApp, Facebook, and Instagram—Hong Kong’s top three platforms—businesses can enhance customer service, offering convenience and a conversational experience.

The strategic combination of AI chatbots and an omnichannel approach creates personalized interactions and 24/7 customer support through familiar channels, driving customer satisfaction and loyalty.

Moreover, this strategy also brings about a unified view of the customer. It enables businesses to deliver targeted marketing campaigns across various touchpoints. This could substantially reduce operational costs through automation and a simplified sales process while increasing employee productivity.

Picture being an online shopper looking for an item from the comfort of your home computer or smartphone. You discover an eCommerce website that leverages an AI-powered shopping assistant on their live chat service. This chatbot delivers immediate responses while remembering all your preferences, predicting your needs, and offering personalized product recommendations.

With integration across popular social media platforms, this chatbot experience can be brought to your WhatsApp and other social media platforms. This showcases that the business has embraced a seamless and personalized experience via an AI and omnichannel strategy, fostering customer loyalty and anticipation for future offerings.

The journey ahead: Navigating the future of retail

AI and cloud-based omnichannel solutions have immense potential to revolutionize retail due to high digital adoption rates.

To stay ahead in a competitive market, businesses must embrace these technologies and recognize the merging of digital and physical retail landscapes. This requires a shift in mindset, with continuous learning and adaptation.

The future of retail is not about replacing human interaction with AI or going fully digital but rather using technology to enhance human connections and create a customer-centric shopping experience through conversational engagements.

AI-powered shopping assistants, acting as brand ambassadors, improve customer experience by providing personalized recommendations, prompt responses to inquiries, and valuable guidance throughout the customer journey. This not only enhances the customer experience but also transforms business models, maximizes marketing ROI, and simplifies processes for businesses and consumers.

The future of retail is here, and it is digital, immersive, and customer-centric.

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