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Artificial Intelligence Helps Developing Better Customer Support/ai-insights/artificial-intelligence-helps-developing-better-customer-support
Artificial Intelligence Helps Developing Better Customer Support

Artificial Intelligence Helps Developing Better Customer Support

November 05, 2021

Businesses depend highly on building mobile and web-based applications for customer support since the demand for quick digital services and assistance has seen incredible growth. At least 67% of the people wish to look into or utilize the messaging applications while communicating with the businesses, says Chatbots Magazine. The smooth experience offered by the advanced intelligent technologies and assistance in a span of seconds is the key factor offering the customer support solutions triggered by AI an edge over the competition.

According to the reports from Gartner, about 37.5% of the Customer Support Services (CSS) concentrate on making plans and running pilots to implement the chatbots by 2023. This shows that AI-driven chatbots are grabbing attention and reducing the burden of reaching a wide range of customers, using advanced AI strategies and automated technologies. Realizing the demand for AI in CSS, AI professionals have been polishing their skills with Artificial Intelligence Certification.

AI Trends in Customer Support Service

As per the Zendesk Study, more than 42% of the total B2C customers were keen on purchasing the products or services after experiencing better customer support service. It also says that about 52% of the customers stopped the purchases because of the poor customer interaction leaving them disappointed.

AI technology is considered as an opportunity for businesses to offer real-time customer support solutions 24x7 to the customers leaving zero chances of not attending to their needs.

The following are the two major contributors to the technological advancements in AI.

  1. Machine learning

    With machine learning, massive amounts of data are collected and learned by the machines to implement the major decisions and processes. Facebook messenger, spam folders, and recommendations or friend suggestions are examples of Machine learning applications you use in daily life.

  2. Natural Language Processing

    According to Statista, the market value for NLP has increased from 3 billion USD in 2017 to 43 billion USD in 2025.  NLP can let you trigger everyday interactions with AI technologies, to enable machines that interpret spoken, and text communications. The examples for NLP in your daily life are Alexa, Cortana, Siri, etc

AI-powered payment functionality is also helpful to make payments automatically through APIs such as Stripe, Paypal, etc. Chatbots can make automated transactions with these applications.

Why Organizations should use AI-driven Customer Support Strategies

  • Improved customer satisfaction

    As per the study conducted by IBM and Aberdeen, at least 33% of users build their satisfaction using AI-based personalized solutions.

  • Real-time Insights:

    With customer contact and communication channels, businesses can gain real-time insights and data regarding customer behavior or purchase patterns.

  • Customer acquisition and retention

    AI-based communications make new customers instantly and see improved growth in the number of customers made, along with best retention measures.

  • No waiting time:

    Customers will not end up waiting for the agent’s availability, chatbots are always available to attend to the users on time.

  • Sensitivity-driven escalations:

    As per the seriousness and the niche-specific cases, the chatbots can escalate the issues to the particularly concerned authority with automated processes.

  • Automated workflows and scheduling:

    With CRM data it is easy to set the routing and scheduling techniques, and chatbots can be trained to deliver solutions with automated workflows.

  • Personalized services:

    The deep learning, and inbuilt algorithms the machines can easily respond in a human-friendly way and help in the decision making with relevance to the needs of the customers.

How Organizations use AI to improve Customer Support Services

  1. Chatbots

    Chatbots are great ways to boost engagement in your businesses and let customers be reached on time. About 67% of the consumers made their communications with chatbots over the past year, says Invesp reports.

    The most popular AI-driven chat or software include Intercom, Drift, TechCrunch, Duolingo, etc. Blenderbot is the most versatile open-source chatbot developed by Facebook, this is named so because the chatbot is capable of blending various conversational skills.

  2. Language Analysis

    The NLP tools can collect customer information, extract the necessary data, improve the user experience, etc. The tools can also help agents to detect whether the customer is happy with the conversations and adjust the conversations accordingly.

    Monkeylearn is the best NLP-driven platform that lets you obtain data insights with its sentiment analysis, keyword extraction, and data classification techniques. These APIs are available in every programming language.

    Other NLP-driven tools include Google Cloud NLP, Amazon Comprehend, IBM Watson, etc.

  3. Object Detection

    With the object detection technique, you can easily locate the objects in an audio or video. They help you carry out automated tasks to enhance image recognition. Nowadays, even self-driving cars use embedded AI-object detection systems that can detect objects to avoid accidents and perform real-time monitoring of the vehicles and their distance.

  4. Optical Character Recognition

    OCR is generally utilized to perform automation of document processing. You can train the systems to enable reading the document in sequence, and let the data extraction or automatic field populating techniques. The data retrieval from documents is easier with optical character recognition techniques. Adobe Acrobat Pro DC, AWS Textract, Docsumo are examples of OCR tools.

    The OCR techniques deployed by Adobe Acrobat made it easier to edit the printed documents, export files, extract text from images, etc.

  5. Machine Learning Models

    The machine learning models are used to train the systems and make use of predictive analytics to implement the best business decisions. Risk analysis, prediction of outcomes, recommendations, analyzing demand, and managing the stock, are all various examples where machine learning is used.

    If you have been into Amazon Prime or Netflix, you might have come across the recommended movies or shows, based on what you have watched earlier which is a machine learning application. With the personalized recommendations, Netflix was able to save about $1 billion, says LearnHub.

Conclusion

AI-driven customer services have seen an improvement in customer management operations across various business niches. AI can get valuable business insights with the collection of customer data and to get the customer interactions at a faster pace.

AI can take customer support services to the next level and the demand for AI professionals in the customer support segment is skyrocketing. It is important to keep yourself pace with these changing trends in the CSS segment. To upgrade the skills, and adapt to the latest trends and changes in AI-based customer solutions with the best AI strategies, make sure you are equipped with the best AI certifications from a reliable provider.