A Guide to Using AI Chatbots in eCommerce A Guide to Using AI Chatbots in eCommerce
AI chatbots have established a strong place in every industry and eCommerce is no different. In fact, chatbots have emerged as... A Guide to Using AI Chatbots in eCommerce

AI chatbots have established a strong place in every industry and eCommerce is no different.

In fact, chatbots have emerged as an eCommerce favorite. Because online retail has a 34% acceptance rate for chatbots by customers — higher than any other industry.

For a long time, eCommerce companies have looked for ways to connect with customers in real-time. Connect in a manner that facilitates a two-way engagement just like a brick-and-mortar store. And now they can via chatbots.

The use-cases of AI chatbots are different for every industry. In eCommerce, they are increasingly used for ‘conversational commerce’  — a term coined by Uber’s Chris Messina which basically implies the collaboration of messaging apps and shopping.

While talking about AI and getting started sounds really exciting, online stores often find it overwhelming to implement AI into their websites and other channels.

Now, since conversational commerce is a relatively unexplored avenue, you need a comprehensive outlook of its functions and how the AI chatbots specifically aid with each step of the buyer’s journey in eCommerce.

Let’s get started. 

Ways you can use AI in eCommerce 

#1 Provide Product Recommendation

Consider the current buying experience of your shopper: They visit the website and browse your website and product pages to search for the product they’re looking for. Depending on the extent to which they narrow down their search, they may find it or not. The process is lengthy and time-consuming.

Now consider the buying experience of your shopper with the help of an AI Chatbot: They visit the website, and they’re greeted with a bubble with a friendly message that directs them to converse with the chatbot. The chatbot asks a series of questions to understand what the customer needs and shows their desired product on the chatbot itself.

Not just this, the next time the shopper visits the website, the bot recognizes the user and recommends products based on their previous purchases.

Which buying experience seems more personal?

That’s what I thought. 


An Accenture study claims that 91% of the shoppers are more likely to shop with brands that provide personally relevant recommendations. Hence, product recommendation is one of the most sought-after use-cases of an eCommerce chatbot. For example, H&M uses the product recommendation chatbot to start a conversation with the user, gets to know their gender, and style preference, and recommend products based on their profile. 

AI Chatbots example

An AI chatbot might sound very complex to build. But in reality, you can build a product recommendation chatbot on a no-code bot-builder.

What is a must for a product recommendation bot is a Google Sheet or an Airtable integration. You can import all your product data into Airtable. Then categorize them based on their sizes, type, colors, availability, etc. Once the sheet is integrated with your chatbot platform, you can display your catalog using Image Carousels. 

#2 Track Customer Orders 

Order tracking is a non-negotiable function to have. While numerous of your marketing notifications may go unread, your order tracking messages are opened with a lot of enthusiasm. In fact, order tracking has the highest open rate at 70%, as compared to the rest of the emails.

Many eCommerce businesses are plagued with a high volume of inquiries on their orders. While the customer has every right to know the status of their order, it’s difficult to address them when there are thousands of orders across regions. Think of an eCommerce store with thousands of orders every day. The influx of order tracking queries is often overwhelming and makes it difficult for agents to cater to every customer.

This is where you can use an AI chatbot. It completely automates the customer queries relating to order tracking and allows your agents to take a breather. Any customer that wants to track their orders can simply converse with the chatbot, input their order details and get a roadmap of where the order is and when it will be delivered to the customer.

To build an AI chatbot that facilitates order tracking, you’ll just need to integrate it with external systems from where the bot can source the information about the packages.

#3 Reduce Cart Abandonment

Statistics show at 69% of shopping carts are abandoned. For an online store, cart abandonment is as frustrating as it can get. Because you work so hard towards creating the perfect buyer journey only for the shopper to discontinue their purchase at the last step. And what adds to the annoyance is that you’ll never know why the prospect abandoned their cart.

So a chatbot offers a simple solution — just ask them.

You can send automated triggers whenever the prospect is about to abandon their cart. This will give you an opportunity to not persuade them to complete the purchase but also to understand the reason why they don’t want to proceed with the purchase at the time. They can also provide real-time assistance to customers during their payment process.

For example, a customer might want to need answers to what are shipping policies, return policies, and offers on their current order. An AI chatbot at the checkout page can answer all these questions and provide real-time assistance to the shopper which makes the experience more personalized.

You can build a FAQ chatbot for the checkout page. You can list down the common questions and determine the intents. You can add responses and deploy them on the checkout page to assist customers during checkout and help you close more sales. 

#4 Send Offers

Who doesn’t love discounts? For an eCommerce business launching a new product or service, sending discount codes can help you attract new customers and make your premium products more affordable to them.

The audience who are new to the website receives these personalized coupons as an incentive. This turns new visitors into loyal customers and retains returning customers. Since chatbots are at the forefront of customer engagement, you can leverage them to urge your buyers to make a purchase with a discount.

You can integrate your messenger app with a loyalty card chatbot API. This loyalty card creates discount codes in a sequence that is unique to each user. Chatbots can also share limited-time offers and send notifications when the deals are about to expire. This ultimately helps in building brand loyalty and boosting sales.

#5 Customer Service

From a customer service standpoint, time, speed, and availability are its three crucial pillars. You need to be available to your customers, at all times and provide quick resolution. As you scale your online store, this combination becomes more challenging to achieve.

Your agents are overworked and don’t find the time to respond to every customer. They also encounter with rude and angry customers often harm their morale. You also have to either hire a 24*7 team or leave queries unaddressed during those times.

An AI chatbot helps you save ample time and money. Some most common customer service use-cases of eCommerce chatbots are:

24*7 service: AI Chatbots are online 24*7 which handles the availability challenge in customer service. Regardless of whether the chatbot addresses the query or not, they can at least record it so the agents can take over when they’re online.

Repeated Queries Automation: Chatbot handles first-level support and provides quick responses to customer queries. This caters to the challenge of speed.

Agent Productivity:  Since your agents don’t have to answer repetitive queries, they are just left with queries that actually require their attention. It frees up their time and boosts their productivity.

For example, most queries often range from return policies, delivery time, shipping costs, and pricing information. And answers to all these questions are more or less the same.

To automate these, you can build an AI chatbot using NLP engines like Dialogflow and IBM Watson. You can categorize your customer queries into different intents. These intents help the AI chatbot understand what and how to respond. The chatbots can accurately respond if different queries are correctly grouped into intents.

You then add different responses to each intent. Machine learning is a prominent characteristic of an AI chatbot. Your bot will learn as it answers your customers and will get more accurate with each conversation. 


Since eCommerce is evolving at an alarming rate, they need tactics to keep up with the trends that elevate the online shopping experience. AI chatbots are a part of this trend. Because doing the bare minimum like adding an email support doesn’t work anymore. You need a mechanism to provide quick answers that keeps the shopping experience intact.

Conversational marketing makes it possible for customers to express what they’re feeling. They prompt eCommerce stores to empathize and take action based on consumer preferences and feedback.

While AI chatbots may seem very futuristic and complex, they’re very much in the present and doing a splendid job of assisting online stores with automation and marketing. They also don’t require high technical knowledge to build. You can learn and deploy bots by yourself with minimal assistance from developers.

Gaurav Belani

Gaurav Belani is a senior SEO and content marketing analyst at Growfusely, a content marketing agency that specializes in data-driven SEO. He has more than seven years of experience in digital marketing and loves to read and write about education technology, AI, machine learning, data science, and other emerging technologies. In his spare time, he enjoys watching movies and listening to music. Website: https://growfusely.com/