Introduction

There are multiple uses for conversational AI in different industries. In this article, we will focus on conversational AI for e-commerce. We share some of the best practices and tips for your AI strategy.
Conversational AI is an automation technology that uses artificial intelligence (AI) to simulate a conversation between a user and a machine or computer program. It can be used in chatbots or virtual assistants, which are computer programs designed to engage in casual conversations with users through text-based interfaces such as instant messaging, emails, and social media posts.
Conversational AI allows businesses to create automated conversations that have personalized responses based on previous interactions with their customers. It can also help make their websites more engaging by having virtual sales associates answer customer service questions and guide them through the process of ordering items from the site.
This article will explain what conversational AI is and why it matters for e-commerce operations today!

What is conversational AI and how does it work?
Want to know the future of AI in e-commerce? Find out what Conversational AI can do for you and how you can use it for your business. Keep reading 😉
Conversational AI is a technology that enables a computer to have a conversation with a human.
It’s a form of artificial intelligence and uses natural language processing and machine learning to analyze the user’s speech and respond in an appropriate way for the context. A chatbot is an example of conversational AI, which uses automation to provide customer service or sales assistance.
In the past, this sort of application was almost exclusively limited to human operators. Chatbots, however, have a number of advantages over humans: they can be programmed to follow complex scripts and interact in specific ways; they can answer questions with a level of specificity that is impossible for people, and they are scalable because they do not need to be trained by an operator.
Chatbot design has evolved significantly over the past few years. The early days saw chatbots simply attempt to mimic human behaviour and conversation (a style known as “chatty”), but now we see more sophisticated techniques being used to create conversational agents that appear more lifelike than ever before. This includes using natural language processing (NLP) technologies, such as sentiment analysis and natural language generation (NLG).
NLG allows bots to generate responses instead of copying them from pre-written templates, providing even greater flexibility when building conversational agents.
The use of NLP has increased dramatically since its introduction in the 1990s. NLG is a subfield of NLP that aims to give computers the power to understand natural human language, enabling them to respond intelligently and naturally, as well as giving them the ability to read and write text.
The field of conversation design has also grown significantly over time. It encompasses all aspects of designing how conversational agents interact with each other, including their intents (what they want), actions (what they do) and outcomes (how they behave). Conversation design involves building conversational agents that achieve specific goals during a conversation.
For example, an agent might be programmed with a script for responding when asked about products or services: “Please send me information about [product name]”. The script could include things like: “Yes” if you have it in stock; “No” if not; “I am sorry but I cannot find this product on my system.”; etc. This type of dialogue may seem simplistic at first glance, but it is a fundamental part of conversation design.
In a future blog, we will be looking at the different techniques available to chatbot builders and how they can be used to create more lifelike conversational agents. Let’s give you a sneak preview first 🙂
To begin with, let’s look at some basic NLP technologies that are widely used in today’s bots: sentiment analysis and natural language generation (NLG).
Sentiment Analysis
The goal behind sentiment analysis is to understand the emotional tone of a text. It does this by analyzing the information contained in it for signs of positive or negative sentiments such as sarcasm, anger, or sadness. This can then be used by a bot to craft an appropriate response based on those emotions that would make it seem more relatable.
The most common way of doing this is by extracting the words from sentences and counting them up across all documents in order to determine if there are any high-frequency words being written about certain topics more than others; these might include swear words or items which have been commonly associated with negative emotions (such as death).
This is a very simple example, but it demonstrates how sentiment analysis can be used to determine the tone of a text. It could also be used to identify times when people are most likely to feel happy or sad and adjust the bot’s responses accordingly.
Natural Language Generation
NLG is a technology that enables bots to generate natural language without having to rely on templates or pre-written scripts. This means that they can respond in an authentic way, using their own knowledge of linguistic structures and probabilities. An NLG engine will use certain top-level grammatical structures such as nouns, adjectives, verbs and adverbs in order to create sentences which appear natural and lifelike. These might include:
“I am sorry but I cannot find this product on my system.”; “It looks like you have not ordered this product recently”; “Can you tell me more about [product name]?”; etc. You will find these sorts of expressions very often in the Aliexpress Livechat with chatbots, for example.
Examples of conversational AI

- Retail: Online retail can be tedious and tiresome. Sometimes you just want to pick something up and go, but the process of buying something online is often inefficient, time-consuming and frustrating. Conversational AI has been used in a variety of ways to make retail faster, easier, and more enjoyable.
- Healthcare: Medical consultations are often long and drawn out because they take place over the phone or through a video call rather than in person. The use of conversational AI means that doctors can interact with patients more effectively by reducing the amount of time needed for each consultation while also making it easier for patients with chronic conditions to self-manage their health without having to leave their homes or offices regularly.
- Banking: Banks want customers who will stay loyal for life; this is why many banks are using conversational AI technology as part of their customer relationship management strategies: so they can better engage with clients across channels on an ongoing basis; provide personalized recommendations based on behaviour patterns; answer common questions quickly without requiring someone else from within the organization (i.e., “How much did my last transaction cost me?”); etcetera).
Why is conversational AI important?

Conversational AI is the future of e-commerce. As a business owner, you need to be able to engage with your customers and provide them with an experience that makes them happy. That’s why conversational AI is so important for e-commerce businesses: it helps you increase sales, build customer loyalty and improve efficiency.
What are the benefits of using Conversational AI in e-commerce?

The benefits of using Conversational AI in e-commerce are clear. You will be able to:
- Increase sales by understanding your customers better and helping them achieve their goals.
- Save time by automating repetitive tasks, freeing up your employees for more valuable work.
- Improve customer service by using conversational artificial intelligence to help solve customer issues faster with less effort from you or your team members.
- Understand your customers better than ever before, so that you can serve them better and increase their loyalty towards you as a result of this knowledge.
How to implement Conversational AI in your online store?

You’ve probably heard of conversational AI, but do you know how it works and why it matters?
Conversational AI is the use of natural language processing (NLP) to have a human-like interaction with a bot. The bot can be built as an app or a website chatbot. For example, you could use Conversational AI for FAQs in your online store.
As another example, when someone asks for pricing information via email or phone call, the platform will automatically respond with the requested information without having to manually search through your website for the answer every single time. This saves time both for you and your customer!
Discover the advantages of using A.I. for e-commerce, and learn what you need to know about conversational A.I.

Conversational AI is a new type of artificial intelligence (AI) that enables you to interact with your customers in ways that were previously impossible. It’s an opportunity for e-commerce businesses to differentiate themselves from their competitors by adopting this new technology and giving consumers experiences they’ve never had before.
Conversational AI is a form of AI where dialogue between two or more parties takes place via voice, text, or graphical interfaces. The way these conversations are conducted makes them seem more human-like, which can be very beneficial for businesses because it can lead to better engagement with customers and an increase in sales opportunities as well as customer loyalty.
Conversational AIs are able to recognize patterns in data much faster than humans can, so they’re capable of doing things like detecting fraud or making predictions about what someone needs based on context clues alone without needing any additional information such as past purchases or browsing history (although those could still be helpful).
Conversational AI market

The conversational AI market is forecasted to reach over $8 billion by 2024, with a compound annual growth rate (CAGR) of 23%, according to MarketsandMarkets. As these systems become easier and more accessible, they’re being used for a wide range of applications beyond chatbots. For example, many companies are now using conversational AI for customer service purposes as well as sales.
Conversational AI VS. chatbot

Chatbots are but one application of conversational AI. As we mentioned earlier, conversational AI is a technology that includes chatbots, but it’s not limited to them. This broader term covers a range of technologies that enable computers to have more human-like conversations with people through speech and text, including virtual assistants like Siri and Cortana, as well as smart speakers like Amazon Echo or Google Home.
To further clarify the distinction between a chatbot and conversational AI:
- A chatbot is a software that uses natural language processing (NLP) to simulate conversation with users via an interface such as Facebook Messenger or Slack.
- Conversational AI encompasses all these types of software, plus other technologies such as machine learning (ML) and deep learning (DL).
Conversational AI for sales

If you’re considering using conversational AI for your e-commerce business, there are many benefits to consider. Here are just a few:
- Conversational AI can be used to generate leads, engage customers, and increase conversions.
- It can be used to boost sales by making it easier for customers to find products they want and make purchases without having to go through complicated processes like checkout pages or phone calls with customer service agents.
- It can also be used in customer retention efforts by helping companies respond quickly when customers have questions about orders or returns — even if those requests come in after hours or on weekends!
Conversational AI in retail

Conversational AI in retail is the use of artificial intelligence (AI) and machine learning to create automated customer service chatbots. The ultimate goal is to eliminate the need for humans to perform certain tasks, such as providing product recommendations or answering simple questions, so they can focus on more complicated issues that require a human touch.
Conversational AI has been around since the 1950s, but it’s only recently become possible thanks to advances in technology like cloud computing, which allows companies to process data without having any physical infrastructure of their own.
In short, Conversational AI is revolutionizing the retail industry by providing a more personalized shopping experience for customers. By engaging in natural conversations with customers, conversational AI can provide recommendations, answer questions, and help customers find the products they need. This technology is also helping to improve customer satisfaction and loyalty by providing a more convenient and efficient shopping experience. In addition, conversational AI can also help to increase sales and improve customer retention rates by providing personalized recommendations and discounts.
Types of conversational AI – AI for e-commerce companies!

This technology is becoming more popular every day, and we are excited to share all of the details on this important topic! If you are interested in learning more about conversational AI, then we highly recommend that you continue reading!
Artificial intelligence is built into our everyday lives, from the moment we turn on a light switch to when we use our smartphones. It’s becoming more pervasive in the business world and can help you create an e-commerce website that customers love and come back to again and again. And with so much data available to analyze customer behaviour, it will only become easier for businesses to leverage artificial intelligence technology to improve their service processes.
There are many different types of conversational AI, each with its own unique capabilities and features. Here are a few examples:
- Chatbots: These are perhaps the most common type of conversational AI. They are used in a variety of settings, from customer service to online shopping.
- Virtual assistants: Another type of conversational AI that is becoming increasingly popular. They are used to help with a variety of tasks, from scheduling appointments to ordering groceries.
- Voice assistants: A type of conversational AI that is becoming more and more popular. They are used to help with a variety of tasks, from setting alarms to playing music.
- Text-to-speech systems: A type of conversational AI that can be used to help with a variety of tasks, from reading books to translating text.
- Natural language processing systems: Natural language processing systems are a type of conversational AI that can be used to help with a variety of tasks, from understanding speech to translating text.
As you can see, there are many different types of conversational AI. While some, like chatbots and voice assistants, can be used to give you information or complete basic tasks, others, like virtual agents and conversational commerce, are designed to facilitate more complex conversations. The features and capabilities of these different types of conversational AI often overlap, but it is important to understand what makes them different.
Where do you see conversational AI being used in the future? Let us know in the comments!
Conclusion
This blog post has highlighted some of the many different types of conversational AI available to help you get a better understanding of what’s out there on the market today. From chatbots that make online shopping more convenient to virtual assistants that help you complete everyday tasks, conversational AI has made its way into more and more of our daily activities as technology improves.
We hope you found this post interesting and informative, and we would love to hear about some of the conversational AI experiences you have had. Please don’t hesitate to contact us via our contact form.
In conclusion, conversational AI is becoming a hot topic in the e-commerce industry. It has many benefits, and it’s important to know how to utilize this technology in your business.
If you are looking for an innovative approach that will help drive sales, then Conversational AI could be the solution for your business!