Boost Customer Experience with AI-Driven Customer Sentiment Analysis

    Boost Customer Experience with AI-Driven Customer Sentiment Analysis

    Customer sentiment analysis has a number of advantages – it can help businesses in determining how their customers feel about their product, allowing them to improve their offering. They can also examine public perceptions of their competitors in order to replicate their success and avoid making the same mistakes.

    To keep a steady flow of profit, it’s critical to hear what customers have to say about the business. Brands can now readily undertake sentiment analysis with the help of Artificial Intelligence (AI), thanks to remarkable technological advancements. When they analyse reviews, comments, feedback, and so on, they can get a sense of how customers are feeling, whether positively or negatively.

    Sentiment research enables a company to determine what it should continue to do and what it should cease doing right now. This process can be used to make improvements to a product or service, introduce a new offering, or make any other strategic changes.

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    However, it is not restricted to analyzing customer reviews and feedback; if properly implemented, it can automatically detect emotional tone in diverse reviews and acquire real-time insights from massive amounts of customer data. Furthermore, the information gathered can be used to improve a company’s product or services.

    Customer experience AI Sentiment Analysis

    The first step in establishing a compelling customer experience is to understand the value of a business and its customers participating in a transparent and continuous discussion. Chat, voice, social media, digital self-service, and chatbots are all examples of interaction silos that should be unified into a single paradigm. It will help infer the genuine nature of customer feelings and opinions via AI-powered sentiment analysis, allowing contact center leaders to have complete transparency of the end-to-end customer experience.

    Customer and live agent interactions can be subjected to AI-driven sentiment analysis in real time, ensuring that automation and agent experiences are sensitive to negative and positive customer communications.

    Here are a few areas where sophisticated AI sentiment analysis technologies can improve the customer experience.

    Frustration detection in automation

    Self-service channels are now supported by AI-driven sentiment analysis in addition to automated response capabilities. This data can be used to determine when a self-service interaction isn’t as enjoyable or useful as an agent-assisted interaction. If a live representative is required, sentiment analysis can identify the level of urgency and route the consumer appropriately. If the automated workflow does not result in a satisfactory resolution, the objective is to give the consumer a way out.

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    Intelligent routing

    Contact centres can not only identify a customer’s emotional makeup, but also route that consumer to an agent who is emotionally equipped to provide excellent customer service. With AI sentiment analysis, it’s quite simple to figure out which agent is best suited to assist the customer, as well as providing the complete context of the interactions, minimizing the frustration of repeated information and allowing for a faster resolution time.

    Real-time feedback

    Customer feedback has the power to make or break a company, so businesses must leverage those opportunities. Conversations that match the requirements for a good customer interaction can be flagged using sentiment analysis. Businesses should use a survey to capitalize on favorable sentiment in real time, while their customers are still in the moment. The company’s brand reputation will benefit from it.

    Identifying the root cause

    In the contact center, AI is more than just a sentiment detector. It can extract valuable information, such as the core causes of customer dissatisfaction. Customer frustration, which is distinct from negative sentiment, may be the most accurate indicator of customer satisfaction and any underlying service issues. Determining the source of a customer’s annoyance can not only help in resolving the issue at hand, but also in identifying a contact center’s flaws in the future.

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    Prangya Pandab
    Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.