Leverage AI to Improve Your Customer Service Experience

Leverage AI to Improve Your Customer Service Experience

Thanks to digitization, the relationship between brands and customers has been continuously changing. With the rise in customer expectations, brands need to find new ways of interaction to improve the efficiency and quality of their services. And this is why many brands have already started leveraging AI to enhance customer experiences with process automation.

Artificial intelligence (AI) can help brands accelerate their application development while allowing end-users to interact with the applications easily. The IT conferences and events have already discussed the impact of AI on businesses.

Let's talk about some common use cases of AI in enhancing the customer experience while delivering modern and engaging applications.

1. Chatbots

Chatbots are among the most common use cases of AI and an excellent way to offer carefree engagement to your customers that fits into their busy schedules. With chatbots, you can:

● Scale the first line of support, and reduce traffic to other support channels,

● engage with your customers in a direct yet conversational style

● Support your employees by storing the information in knowledge bases or Q&A formats

Some of the most popular chatbot Softwares are Intercom and Drift, but today, modern application development platforms provide you with the tools to build your own chatbot services customized to your business needs.

2. Object detection

Object detection is another use case of AI that enables you to automate taste related to image recognition. For instance, if you are a banking institution looking to improve your new customers' onboarding experience, object detection can be an excellent way to provide just what your customers need. With this tool, they have to upload a picture of their ID and click a selfie. The object detection will automatically match their face in the ID with the selfie and validate their identity, thereby eliminating the whole in-person process.

3. Machine-learning models

 You can also train machine learning modes and merge them into your applications to create and evolve predict analysis to make better-informed business decisions. Some of the most common use cases to machine learning are:

● Automation of an approval decision

● Classify tickets for recommending a solution

● Predict product demand, sales discount, etc.

4. Language analysis

Language analysis is another great use case of AI that allows the collaborators to extract critical information from customer feedback and adapt to their communication needs. It is an excellent tool to improve the overall call center experience. With this tool, your agents can easily detect if the customer is happy or not and then adjust their tone and actions accordingly.

5. Optical character recognition

Optical character recognition can enable your systems to read a document like an invoice, extract relevant information and populate the right fields accordingly. As a result, you can quickly process accurate information from documents in an efficient way.

Final note

Your customers expect smooth and effortless experiences from your business, and artificial intelligence can play a crucial role in giving them just what they need. Given the importance of this subject, the Internet 2.0 conference in the USA will be discussing various aspects of AI and how it can transform the customer relationship with businesses.



A premier technology event, the Internet 2.0 Conference will walk you through recent innovations and tech tools that can empower businesses in this increasingly digital world. Having C-level executives, renowned technologists, app developers, AI scientists, and robotics experts in attendance, the conference aspires to be the ground zero of new ideas which will shape the tech arena in the years to come.


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