How can AI make customer service better? 5 types of AI-powered customer service software to know about

Sara Yonker

May 2, 2023

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From the voice assistants in our phones to the smart thermostats in our homes, we interact with artificial intelligence on a daily basis. 

That’s especially true when it comes to customer service. If you’re considering implementing AI into your customer service operations, it can be overwhelming to understand what AI can do - and all the different software platforms that provide one or more of the solutions. Here’s a breakdown for anyone considering upgrading their AI game. 

5 ways AI is used in customer service

1. Chat conversations 

AI-powered chatbots can provide immediate assistance to customers on your website 24/7. When you implement a chatbot, you’ll likely need to select a software vendor that specializes in conversational AI. This type of artificial intelligence software allows you to create lifelike conversations with your customers and respond to a myriad of situations and prompts. 

2. Self-service

Although chatbots are a form of self-service, there are also opportunities for other AI-powered self-service applications that empower your customers to handle issues themselves. 

For example, AI can help automate customer service processes, such as ticket creation, routing, and resolution, improving efficiency and reducing manual work. You can use AI image recognition software to intake information from your customers without manual oversight. 

3. Predictive analysis

AI-powered sentiment analysis can help companies analyze customer feedback and sentiment, and take actions to address issues.

Once you understand that, you can also use AI to predict customer behavior, such as likelihood to churn or make purchases.

4. Voice recognition

AI-powered voice recognition can be used to automatically route calls to the right department or representative, verify identities, and provide customers with personalized service.

5. Personalization

Customers respond to offers, emails, and solutions that fit their specific needs.  You can use AI to automatically personalize customer interactions, by analyzing customer data and providing recommendations or customized solutions based on customer preferences and behavior.

What’s the difference between conversation intelligence and speech analytics?

Conversation Intelligence and speech analytics are two related but distinct technologies that are used to analyze customer interactions with businesses.

Conversation Intelligence refers to the use of AI and machine learning to analyze spoken and written interactions between customers and businesses. It typically involves the use of tools like natural language processing, sentiment analysis, and speech recognition to extract insights from conversations and identify trends and patterns.

Speech Analytics, on the other hand, is a more specific form of conversation intelligence that focuses on analyzing spoken interactions only. It involves using speech recognition technology to transcribe audio recordings of customer interactions into text, which can then be analyzed using natural language processing and other techniques.

So while both conversation intelligence and speech analytics are used to analyze customer interactions and gain insights into customer behavior and sentiment, speech analytics is a more specialized form of conversation intelligence that specifically focuses on spoken interactions. Conversation intelligence can include a broader range of data sources, such as customer chat logs and email transcripts, while speech analytics is limited to analyzing voice recordings.

What’s the difference between conversational AI and conversation intelligence?

Conversational AI refers to the use of AI and machine learning to create conversational interfaces, such as chatbots and voice assistants. The goal of conversational AI is to create a natural, human-like interaction between humans and machines. Conversational AI is typically used in customer service and support, as well as in other applications where there is a need for automated, conversational interactions.

Conversation intelligence, on the other hand, refers to the use of AI and machine learning to analyze human-to-human conversations, typically in a business context. The goal of conversation intelligence is to extract insights from conversations and identify trends and patterns that can be used to improve business operations and customer interactions. Conversation Intelligence is typically used in sales, customer service, and support, as well as in other applications where there is a need to analyze and understand human-to-human interactions.

While both conversational AI and conversation intelligence involve the use of AI and machine learning to analyze human conversations, conversational AI focuses on creating automated, conversational interfaces between humans and machines, while conversation intelligence focuses on analyzing human-to-human conversations.

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