5 inspirational examples of chatbots in e-commerce

A Custom AI-Powered Chatbot Application For E-Commerce Organization In Dubai USM

ecommerce chatbot case study

Bots can even calculate personal preferences, order history, and social media activities to figure out which item best fits a visitor’s needs. Messaging channels such as Facebook Messenger, WhatsApp, etc have gained popularity amongst today’s digital customers. In fact, 67% of consumers prefer using messaging apps when interacting with a business. Kik is a successful chatbot that helps customers find what they actually want using Artificial Intelligence technology. Reducing support tickets is one of the biggest challenges in online business.

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The COVID-19 pandemic led to an unexpected surge in online shopping, resulting in JioMart experiencing three times the predicted traffic. They identified for automation to supplement their customer service and introduce new communication channels apart from their website to support their customers via an omnichannel platform. For product descriptions, they use fine-tuning, a process to make AI understand their style and language. This helps create accurate and engaging descriptions for their large inventory. AI-generated descriptions were even better than human-written ones in tests.


During this process, consumers’ interaction with the chatbot may be less than in the other two stages. In the postpurchase stage, consumers’ behaviors mainly contain postpurchase engagement or service requests. Tasks that the chatbot needs to address in this process may be more complex than the other two stages. In a traditional business setting, employees are required to be friendly to consumers and convey positive emotions to them (Tsai and Huang, 2002).

ecommerce chatbot case study

KeywordCountry is a Keyword Research tool that uses Artificial Intelligence, Big Data and Machine Learning to sort and sift thru 17+ Data points to generate market intelligence. However, the solution in the actual project will vary a lot in terms of the data we get from each version of the iteration and testing. Upon a successful trial, the user can simply use the toggle to accept or reject the product. The user can easily track the order on the map; in case there is no in-app navigation — a button to navigate it to maps is there.

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Most companies might think of e-commerce chatbots in terms of customer service. However, there are many more use cases for AI chatbots in e-commerce along the entire customer journey. Personalized service through chatbots will not only make your customers happier, it will also increase their spending. In a recent Statista survey, 63% of businesses said that personalization increased their conversion rates, and 31 percent of e-commerce business have noticed an increase in revenue. We measured the variables using existing scales adapted from previous research (see the Appendix).

  • They’re then given a link to a Nivea webpage full of tips and products designed to look after their type of skin.
  • This works for items of clothing, makeup, faces, and even pictures of celebrities wearing the user’s favourite beauty products.
  • A web application that features a chatbot building scripting language with the ability to turn simple spreadsheets into complicated chatbots for lead generation, client followup and more.
  • The chatbot takes the user through the stages of ordering a pizza in a simple and engaging way – from choosing toppings to selecting a time slot for delivery.

Ying Bao is a PhD candidate in the School of Information Technology and Management in the University of International Business and Economics, Beijing, China. Her interests focus on user behaviors and trust in the sharing economy and corporate social responsibility. Her research papers have appeared in Information Processing and Management, Internet Research, Group Decision and Negotiation. Her papers have also been presented in the leading conferences such as Hawaii International Conference of System Science (HICSS) and American Conference on Information System (AMCIS).

Step 7: Track user engagement and behavior

Staples is a great chatbot eCommerce example of how to use this tool to guide customer interactions. The office product retailer created its Easy System to make it easier for customers to order what they needed. Customers could ask the bot simple questions or scan their lists to generate an order. Chatbots for the retail industry can give tips and offers to customers based on previous interactions and their activity on the site. Once a bot gets to know a customer, it can personalize service offerings and suggest products the customer might like. It also gives a customer insight into what product might meet their needs.

ecommerce chatbot case study

Create product descriptions in seconds and get your products in front of shoppers faster than ever. If you’ve been using Siri, smart chatbots are pretty much similar to it. No matter how you pose a question, it’s able to find you a relevant answer. Simple chatbots are the most basic form of chatbots, and come with limited capabilities. They are also called rule-based bots and are extremely task-specific, making them ideal for straightforward dialogues only. They can choose to engage with you on your online store, Facebook, Instagram, or even WhatsApp to get a query answered.

Elkjøp wanted to automate global customer support to enhance service and satisfaction

Sinch Chatlyer, for example, has developed a conversational AI chatbot for e-commerce that you can set up in minutes. At the same time, the AI technology behind it will guarantee your customers the best possible experience. AI bots can answer most frequently asked questions successfully while providing a smooth customer experience. As AI chatbots in e-commerce have smoother interactions with customers and can understand their issues better than regular bots, AI chatbots can also solve more inquiries successfully.

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Naturally, the bot also provides the handoff to the Client Advisor option. Like Sephora, this clothing giant launched an ecommerce chatbot on Kik. H&M’s chatbot sends pictures of outfits and asks users to choose a better match for them. The main goal of an AI chatbot in the e-commerce industry is to convert casual website visitors into potential customers and enhance the purchase decision process. Online business owners should insert their business objectives in the chatbots to help make the customers take action beneficial to the needs of the business and the customers themselves.

A Business-to-Consumer e-commerce business sells products and services directly to consumers. The landing pages of e-commerce B2C sites use AI-powered chatbots to understand the customers’ needs and recommend the correct product for them. AI Chatbots are smart chatbots that answer customer questions instantly. Implementing these advanced chatbots on your websites means you don’t have to rely on the customer support team to answer every question. AI chatbots regularly learn from the interactions with shoppers and make the conversation feel more natural; just like a real-life conversation. Most customers expect businesses to be available 24 hours a day, 7 days a week.

ecommerce chatbot case study

AI-powered eCommerce chatbots will increase the value of your eCommerce store and create brand awareness among your customers. AI chatbots, also known as eCommerce chatbots, will answer customer questions like a real person. AI chatbots also use Natural Language Processing to understand customers’ questions and enhance the sales process. Many online business owners use chatbots to engage with their customers and increase the sales of their businesses.

Imagine that your potential customer wants to buy something from your online store. So, instead of going to your online store and searching for products, the customer sends a message to you through your business page on Facebook. AI bots learn from previous interactions and look back to get smarter to handle more complex conversations.

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ecommerce chatbot case study

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