3 Ways Text Analytics Support Customer Interaction Management

    Knowledge is power, especially when it comes to customer experience. The more you know about your customers, what they want, what they need, and how you can help them, the better every interaction will be. The result? Happier customers, more confident agents, and an improved bottom line.

    Text analytics is essential for customer interaction management at your contact center. It’s how you analyze text interactions with customers to extract insight into sentiment, emotion, problems, trends, language, and key phrases. From there, you can gain a holistic view of the customer experience and build a model for successful contact center operations.

    How Does Text Analytics Benefit the Customer?

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    Research estimates that around 80% of today’s enterprise data is unstructured. This disorganized data typically includes customer interactions — such as emails, instant messages, live chats, social media, etc. Extracting high-value insights from this unstructured text requires AI and real-time analysis to understand the meaning of human language.

    With text analytics and natural language processing, you can detect and study important information about every customer interaction. This means that your contact center agents can:

    • Better understand how, why, and when your customers contact you.
    • Garner insight from live conversations, including details about sentiment, behavior, product mentions, intent, emotional evolution, and more.
    • Optimize workflows by organizing customer interactions by keyword, topic, emotion, and volume.
    • Gain authentic customer feedback to adjust future interactions and increase customer satisfaction.
    • Save time by directing customers to appropriate self-service channels for automatic troubleshooting.

    And for your customers, this means greater satisfaction with every agent interaction. With the help of text analytics, they should realize:

    • Less time waiting in the queue for the right agent to help them.
    • Decreased frustration with customer support from agent transfers or hold times, resulting in a lower risk of abandonment.
    • Quicker problem and question resolution and a greater likelihood of resolving their complaint upon first contact with your business.
    • Increased customer satisfaction as underlying issues are addressed appropriately and consistently.

    Text analytics is all about reducing frustration for both agents and customers. It does this by giving your contact center agents the knowledge and assistance they need to handle anything that comes their way.

    3 Ways Text Analytics Contribute to Customer Interaction Management

    So, what exactly does this look like in action? How does text analytics contribute to customer interaction management —the process your contact center follows to handle all customer interactions?

    1. More Efficient Customer Journey

    When customers contact your company, they don’t want to deal with transfers or long delays while waiting for support or management interference. Text analytics provide real-time guidance to help agents navigate each customer interaction efficiently.

    Here’s how it works:

    • The customer creates a new service request, live chat question, or email.
    • Text analytics automatically extracts the topic, sentiment, and trends from the customer’s description.
    • Prior customer interactions about the same topic are gathered for additional insight.
    • The customer is routed to the best-suited agent to provide a solution.
    • Then, during the interaction, agents leverage real-time analysis for early detection of issues that may affect the quality of the experience.

    2. Real-Time Conversational Guidance

    If you only analyze your text conversations after the fact, you're leaving significant insights on the table. The most successful contact centers understand that proper customer care is about taking care of your customers while they’re interacting with your brand. And to do this well, you need real-time conversational guidance focused on your customers’ emotional needs. After all, a positive emotional experience directly translates to brand loyalty.

    Text analytics' real-time monitoring uses AI to understand language patterns and intent. It does this by:

    • Using text conversations to automatically route customers to the agent and department best suited to their needs.
    • Tracking every detail of the conversation to spot when brands, products, features, and issues are mentioned and how frequently.
    • Tagging tickets and conversations based on what the customer means rather than their exact words to trigger rules in your help desk.
    • Setting off early detection alerts and warnings when the conversation appears to be trending in a negative direction. For example, a “lack of empathy” alert if politeness isn’t detected in a specific timeframe.
    • Displaying a conversational checklist guide to improve each conversation's efficiency.

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    3. Root-Cause Analysis

    Understanding why your customers contact you and what is most important to them is key to customer interaction management. By getting to the root cause of your customer's problems and the negative behaviors of your contact center agents, you can begin to take steps toward improvement. The key is using text analytics to gain high-quality data about agent performance, repeat callers, and deeper issues.

    Here’s how text analytics helps:

    • It automatically reviews every text interaction to extract information and uncover trends around underlying issues.
    • It identifies text conversations that seem abnormally long to evaluate problems or high degrees of customer dissatisfaction.
    • It uses AI and machine learning to explore the situational context of customer interactions and provide a greater understanding of what’s happening in every conversation.
    • It categorizes customer problems into groups by volume so that management can dig down into the most relevant concerns.

    Better Customer Interactions Improve Your Contact Center's Bottom Line

    Text analytics is a vital component of the customer experience. The AI automates much of the analysis process, which means no matter how busy your support team gets, they can keep up with customer demands and prioritize interactions before things get out of hand. It is essential for customer interaction management and ensuring that every conversation goes well. And customer care plays a vital role in the bigger picture of your company’s success.

    It’s only by understanding your customers’ needs that you can then implement the necessary adjustments to your contact center to make the most out of every conversation. And since high-quality customer service is critical to making the sale, it’s essential to your bottom line.

    Looking for more ways to develop a customer-centric contact center?

    The eBook, Actionable Ways to Improve Call Center Customer Experience & Customer Service, highlights the most common customer experience (CX) challenges for contact centers and provides best practices to help you create a successful CX strategy.

    Using data to improve customer satisfaction webinar


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