Chatbot Development for E-commerce with Combined Machine Learning and AI Technologies

September 3, 2020
Chatbot Development for E-commerce with Combined Machine Learning and AI Technologies

These days, there are a lot of expectations placed on the digital customer experience. Customers demand and businesses must deliver seamless communication and interactions. Customer service can make or break a business: every extra minute of waiting on the phone and every time a company is unable to answer questions motivates the customer to leave and never come back. Customer service is the first line of defense, the first interaction point. With the advent of artificial intelligence, e-commerce has reaped the benefits of chatbots and their multi-purposefulness.

Chatbot Market by 2024

According to Small Biz Genius data, 85% of customer interaction will be handled by algorithms by 2021. The global chatbot market is expected to reach $1.3 billion by 2024, with AI-based chatbots increasing 53% annually (Global Market Insights). Customers around the world enjoy their experiences with chatbots: chatbots can respond to their questions in a matter of seconds and walk a shopper through their journey.

Online Shopping Bots: Definition and Advantages

Let’s start with a shopping bot definition.

Bots for online shopping are computer programs that are meant to simulate human conversation based on predefined patterns, triggers, conditions, etc. They are a form of intelligent assistant—like Siri or Alexa. Traditionally, chatbots have fulfilled specific, narrow tasks. But as they get more sophisticated, their presence has expanded.

Bots for Online Shopping are Computer Programs
“We’re seeing businesses large and small drive tangible results using messaging as a marketing channel—from acquiring new customers to driving repeat sales. Businesses are turning to Messenger to help their customers find the perfect gift, book appointments, get personalized deals, receive shipping updates and so much more. Messaging helps businesses and their customers connect in a personal and productive way—all at scale.”

— Andrew Kritzer, Product Manager, Messenger Platform

Today, there are two kinds of chatbots: ordinary chatbots and intelligent chatbots. Intelligent chatbots are powered by artificial intelligence and machine learning. The progress of AI and natural language processing has made it possible for businesses to provide deeply personalized services 24/7 and drive positive business results.

The advantages of chatbots include, but are not limited to:

  • an immediate reaction to customer queries
  • being reactive or proactive
  • consistency of conversation
  • data collection 
  • constant learning and contextualization
  • applied via various mediums: messenger apps, social media, SMS, live chats, etc.

During the last decade, the use of messenger apps has surpassed social networks. Furthermore, chatbot funnels have had a considerable impact on customer acquisition, retention, and customer loyalty.

Messenger Marketing vs Websites & Emails

Weaving chatbots into an e-commerce business influences customer relationships in a number of ways:

  • drives acquisition 
  • provides sales incentives in the form of coupons 
  • personalization via quizzes
  • boosts conversion rate via purchase suggestions, AR, help guides, etc.
  • increases engagement and retention
“All of the big trends in commerce over the past couple of decades have been in moving to where your customers are. Rather than forcing your customers to come to you, you go to where they are. The next generation of that is conversational commerce. It is inevitable that everyone is going to have to incorporate conversations inside of Messenger, and into social media platforms, in order to sell things more effectively.”

— Phil Libin, Founder of All Turtles and Evernote

Successful E-commerce Chatbots: Why Use Them?

The best way to get the idea of chatbots and their value for a business is to see them in action.


A Philippines-based e-commerce store specializing in selling consumer goods. The self-titled chatbot provides exhaustive information on the store and delivery options, and acts as a support agent. Argomall introduced their chatbots to streamline sales and enhance the customer support experience. Ultimately, chatbot became the key support tool and boosted ROI 23x.

Bot Burger

Bot Burger chatbots started as an experiment for serving customers at nighttime on Fridays and Saturdays. Customers could start a conversation with a bot via an ad, Messenger, or Facebook post. Bot Burger doubled its sales in December and January, and after interacting with a bot, 20% of customers said they would like to buy again, becoming repeat customers.


Finding a perfect present for loved ones is hard. The Lego chatbot helps with decision-making. Ralf, the gift chatbot, provides customers with personalized gift offers in the Messenger app. As a result, Lego reduced the cost per conversion by 30%. In some areas, Lego boosted return per ad 6x.


Chatbots are not a common practice in the automotive industry. However, Toyota went off the beaten track and introduced a quiz bot to collect customer data and assign a relevant sales team. Over 50% of customers who completed the quiz were willing to book an offline test drive. The campaign resulted in a 10% click-through rate, an impressive result in Hong Kong.

“Today, consumers don’t make the distinction anymore between online and offline. Consumers want to shop whenever they want it and how they like it. They expect personalization and relevant suggestions. Today, we can offer this via videos, 360 views, trying sunglasses with AI, chatbots to create conversations with the brands and much more, all to create a real feeling of shopping.”

— Frederik Van Lierde, Founder & CEO,

AI Chatbot for E-commerce: the Value for Customer Service

A major advantage of an AI chatbot is that it can be used through all stages of the sales funnel. Chatbots enhance the Customer experience in the following ways:

  • initiating a conversation with potential customers, greeting them and asking whether the visitor has any questions
  • sending reminders about abandoned carts
  • boosting engagement by causing customers to stay longer on the page
  • accumulating data on prospects
  • personalized content delivery according to individual customer preferences
  • 24/7 customer service
  • sending notifications on offers, discounts, and coupons

Customer support and chatbots have huge potential together:

  • AI can predict the future needs of a customer. This can be accomplished by ML capabilities used in combination with purchase history.
  • The audience around the world uses messaging apps more than anything. Chatbots give businesses a chance to address their customers right in the place where they spend most of their time.
  • Chatbots are cost-effective. Traditionally, high-quality customer service demanded significant investments in lengthy and expensive training. By automating customer service, a business can cut costs. Also, a chatbot can be built on low-cost or free tools and platforms.
  • Conversational APIs are steadily growing.

Chatbot E-commerce: Examples of Application

These are the following use cases where a chatbot can come in handy:

  • Recommendation of products: Online retailers are empowered to learn buyer patterns, boost engagement and upsells.
  • Search result personalization: A customer journey becomes seamless, smooth, and short, and conversion rates are increased by several times.
  • Automation of orders: Customers like to place orders through chatbots because it saves time and their preferred products are saved and can be reordered at any time.

The implementation of chatbots depends on the needs of your business. At the moment there are several types of chatbots e-commerce businesses can use:

Script bots

They are deemed the simplest kind which operate on the basis of predefined scripts. By recognizing specific words and phrases, bots deal with simple tasks and basic questions. Despite being the most popular type of chatbots, script bots cannot brag about their flexibility. A number of e-commerce businesses integrate chatbots with NLP in order to make the chat look as natural as possible.

AI bots

Built upon artificial intelligence, these types of bots are more advanced. However, their work can only be partly automated, so consider some human participation in order to recognize particular requests.

AI+ML bots

These are considered the most intelligent bots. The combination of artificial intelligence and machine learning makes them self-sufficient as they do not require human input or participation to provide accurate information. Alexa and Siri belong to this type of intelligent assistant.

There is a clear difference between AI chatbots and rule-based chatbots. Before considering implementing one in your business, you have to be aware of the major distinctions.

Rule-based chatbots are also known as decision-tree chatbots; they operate on the basis of defined rules and are used to map the conversation. Rule-based chatbots are cheaper and faster, can contain interactive elements, and integrate quite well with legacy systems.

AI chatbots use ML to understand the intent and context, and NLP to generate relevant answers. Their sophistication increases with the amount of time and effort you spend using and training them. Because AI bots learn from collected information, they literally become better with each infusion of data. Decision making becomes more skillful, and they are not limited in terms of languages.

“Chatbots add value to a business when they perform as well as human beings. Chatbots can go far beyond mere software, becoming devoted assistants who know us better than ourselves; they know our likes, dislikes, and their purpose is to not disappoint us. From a business perspective, chatbots give omnipresence and customer-centricity.”

— Vlad Medvedovsky, Founder and Chief Executive Officer at Proxet, a custom software development services company.

Proxet has been engaged in the development of self-learning solutions for numerous verticals. Our AI engineering team has vast experience in natural language processing, chatbots, voice recognition, and far beyond in other technical areas. We combine knowledge with expertise and leverage them for our clients to be successful.

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