Everything you need to know about Conversational AI

Conversational AI
Dec 17, 2021
Mégane Gateau
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Everything you need to know about Conversational AI

Table of contents

1. What is Conversational AI?

2. How does Conversational AI work?

3. What is the difference between Conversational AI and Chatbots?

4. Benefits of Conversational AI

5. Conversational AI by Industry

6. Conversational AI Testimonials

7. How to build Conversational AI?

8. What is the best Conversational AI?

Find out everything you wanted to know about conversational AI and how it helps companies provide a better customer experience.1. What is Conversational AI?


Conversational AI is artificial intelligence made up of a combination of:

  • natural language processing (NLP): part of machine learning that focuses on modeling and interpreting language so that software can interact with humans.
  • machine learning (ML):  a field of artificial intelligence, consisting of a set of algorithms, features, and datasets that continually improve with experience.
  • speech recognition, and other language technologies. 

Conversational AI processes the spoken or written word and figures out the best way to respond to all users’ requests.


2. How does Conversational AI work?

At its simplest, conversational AI processes words into action. The system of components allows it to understand, respond, and adapt to each interaction.

There are several components that enable conversational AI to have human-like conversations through voice or text:

  • Automatic Speech Recognition (ASR)
  • Natural Language Understanding (NLU)
  • Dialog Management 
  • Natural Language Generation (NLG)
  • Text to Speech (TTS)

While Conversational AI solutions allow applications to make quick decisions based on incoming data, this process involves several steps. 

  1. Input generation: First, a user gives input to the machine via written text or voice.
  1. Input analysis: Then, if the input is text-based, natural language understanding (NLU) is applied to extract the meaning of words. In case it is spoken text, automatic speech recognition (ASR) is applied to translate words into a machine-readable format.
  1. Dialogue management: During this step, Natural Language Generation (NLG), formulates a response to the user’s query.
  1. Reinforcement learning: Last, but not least, user inputs are analyzed by machine learning algorithms to refine answers over time. This ensures the best accuracy possible.


Conversational AI flow



3. What is the difference between Conversational AI and Chatbots?

There are several differences between conversational AI chatbots and traditional chatbots. The main one is that traditional chatbots understand via keywords, where AI chatbots have more powerful understanding mechanisms.These answers are associated with keywords that trigger an automatic response whenever a customer's question contains one of them.

Whereas an AI chatbot does not need a script, but rather learns gradually by reinforcement learning.

Differences between conversational AI and chatbots


4. Benefits of Conversational AI

Why use Conversational AI? Conversational AI is a cost-effective solution from medium businesses to large enterprises. Here are just a few examples of the many benefits you can gain from using it.

Better customer experience

First and foremost, conversational AI allows businesses to provide quick and accurate responses to customers. Customers want immediate answers - giving them quick responses is the easiest way to improve their experience with your brand on many channels.

With the omnipresence of mobile devices, businesses need to be ready to provide real-time information to customers. Because conversational AI chatbots are accessible on many channels and faster than human agents, customers can engage with brands faster and more frequently. This immediate assistance leads to a significant improvement in the overall customer experience. As customer satisfaction increases, this will translate into greater loyalty and additional revenue from referrals.

Reduced costs and increased revenue

A conversational AI platform gives businesses the ability to serve more customers without having to hire additional customer service agents. 

In addition, businesses can also generate revenue by using AI virtual assistants to upsell or cross-sell products. Conversational AI can automatically provide personalized offers or make product recommendations to increase revenue, and also convert abandoned carts.

After the purchase, conversational AI applications can also play a key role in managing customer service requests. At Mindsay, we have seen AI chatbots deflect 50% of incoming requests.This helped make their agents free to focus on complex requests.


Empower customer service agents to deliver higher-value work

The performance and happiness of customer service agents improve when they are helped by AI-powered chatbots. Indeed, they have more cases resolved and fewer mundane requests to handle.

Freeing up human agents from time-consuming requests enables companies to make them focus on complex work that delivers higher value.


Curious to see if conversational AI could benefit your team? Try our free chatbot ROI calculator to get the answer right away!


5. Conversational AI by Industry

According to Allied Market Research 2021 report, the global conversational AI industry generated $5.78 billion in 2020, and is anticipated to generate over $32.62 billion by 2030.

The COVID-19 pandemic has boosted the growth of conversational AI-based technology in 2020 and is expected to grow by the end of 2022.

Moreover, the rise in adoption of AI chatbot solutions in various industries: from retail and e-commerce, to fintech and insurtech, as well as the huge benefits seen by the travel industry, is is proof of the power and efficiency that conversational AI brings to businesses.


Conversational AI for the travel industry

COVID-19 has impacted the tourism industry like never before. Companies have had to adapt to this sudden and prolonged loss of business coupled with a high demand of questions from customers who need help and guidance more than ever. The travel industry needed to turn to innovative solutions in order to serve a huge surge in customer request volumes without scaling their support team.

Many airline companies, including French Bee, decided to implement a conversational AI solution to best weather the storm brought on by COVID. One of the main benefits they realized was that the robot helped them reduce call volumes by 50%. With fewer calls making it through to the call center, French Bee has been able to reduce their customer service costs.

Their conversational AI strategy helped them to:

  • Decrease by 50% the number of calls to the call center
  • Increase in the on-site baggage conversion rate
  • Reduce call center costs

Conversational AI for retail & eCommerce

eCommerce is booming. By 2024, Insider Intelligence predicts that consumer retail spending via chatbots worldwide will reach $142 billion.

With online shopping as popular and competitive as it is today, eCommerce chatbots play a crucial role in a brand's success when it comes to serving and retaining customers. Thus, AI chatbots should be at the very heart of customer support strategies, providing personalized shopping experiences at every step of the process.

This is what espaceplaisir did when they decided to implement Mindsay’s Conversational AI right before Black Friday to handle the huge increase in customer requests.

In just one week, their AI chatbot helped them to:

  • Automatically answer customer inquiries about payments, delivery, returns, and order tracking. 
  • Connect to their Zendesk live chat and ticketing system, so that agents can enter the chat when necessary.
  • Be able to effortlessly manage a huge surge in customer demands 

Conversational AI for mobility & logistics 

According to  several reports, by 2035, the urban mobility platform market will reach $12.4 billion in Europe, and $5.2 billion in the United States. 

These new users will need help quickly during their first use, but also on a daily basis in case of traffic interruption or equipment problems. Conversational AI bots can really help mobility and logistics companies because they can serve the user quickly and efficiently, at any time of day.

Here are some of the key benefits:

  • Improve agents’ response time up to 99%
  • Deflect up to 50% of customers’ tickets
  • Answer to users and provide live information 24/7 on every channel 

To improve their CSAT and customer loyalty, logistics and mobility companies are now turning to AI to be able to quickly answer customers in need while eliminating repetitive tasks for agents.

Conversational AI for banking and insurance

In the coming years, it's the quality of the user experience that will make the difference when it comes to brand loyalty.. And this is especially true for fintech and insurtech companies, as their products manage people’s money. Correctly implementing AI chatbots will be crucial to these brands to provide the right customer experience. 

Here are some chatbot use cases that could benefit banking and insurance businesses:

  • Educate and sell financial products
  • Personalized financial advice
  • 24/7 support, very important in case of stolen or blocked cards


AI per indutry


6. Conversational AI testimonials 

Our customers are realizing the huge potential of Conversational AI chatbots and they’re happy to share their experiences.

“Mindsay’s innovative conversational AI platform ensures we’re staying on the cutting edge of customer service improvements and going the extra mile for our customers.”

Paula Aduana-So, Operations Manager at Cleeng

“Thanks to Mindsay chatbot, Kiwi.com customers can now quickly and easily get answers to their questions without the need to connect to the customer service agents.”

David Mička, Product Manager at Kiwi.com

“We want to be there to help our customers at any time, and the bot helps us do that. The bot is now automatically handling a lot of customer requests, so the customer gets immediate answers and no longer needs to wait for an agent.”

Isabel Rodriguez, Head of Analytics, Digital Marketing & e-commerce at Iberia Express


Not convinced yet? Take a look at all of our conversational AI reviews!

7. How to build Conversational AI?

Using a no-code conversational AI platform has never been easier. In addition, our team is always here to help you build your chatbot. But first, to ensure you build the right AI chatbot for your business, we created a quick checklist:

1- Define your goals 

2- Select the channels where you want to deploy your bot

3- Choose use cases 

4- Design conversation flows 

5- Train the AI

6- Test the AI as a customer

7- Deploy it on each channel

8- Analyze and optimize it so you can provide the best customer experience.

If you’re ready to start your AI chatbot journey, let’s talk


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