Why AI Sentiment Analysis has Become a Critical Part of the Customer Experience

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Staying on top of what customers are saying about your brand through voice and digital channels is a complex task that’s made simpler by artificial intelligence (AI) powered sentiment analysis. The power of AI sentiment analysis is that brands can have a pulse on how their customers are feeling, positively or negatively, and know when to intervene as needed.

Many companies already use sentiment to address indirect communications, such as addressing reviews online or better understanding how their products can be improved. These are clear indicators for brands to take action.

But sentiment analysis goes far beyond simply analyzing customer reviews and feedback. The real power of AI sentiment analysis is its ability to provide complete transparency of the interactions your customers have through digital channels and with live agents. This level of analysis enables brands to more quickly detect customer frustration and improve these direct interactions moving forward.

AI Sentiment Analysis in the Contact Center

In addition to monitoring a brand’s online reputation, sentiment analysis has powerful applications in contact centers. It can be used to assess the nature of customer comments in phone calls, social media, text messages, emails, and chatbot sessions. These contacts can be routed based on customer sentiment to, for example, agents that are good at soothing angry customers. Additionally, sentiment scores can be applied to help identify both best practices and coaching opportunities. When paired with other customer experience measures, such as Net Promoter Scores (NPS), sentiment analysis results can also help provide a more holistic view of what customers think and feel.

Powering the customer experience AI Sentiment Analysis

Understanding the value of a business and its customers engaging in a transparent and persistent conversation is the first step to providing a powerful customer experience. We believe that interaction silos — voice, chat, social media, digital self-service, IVR and chatbots — should be consolidated into a single, elegant paradigm. By applying AI-powered sentiment analysis, it will help derive the true nature of customer opinions and feelings, which enables contact center leaders to have complete transparency of the end-to-end customer experience.

AI-driven sentiment analysis can be applied in real-time to customer and live agent interactions ensuring automation and agent experiences are sensitive to the positive and negative communications of customers.

Powerful ways to use AI sentiment analysis

  • Automation: Enable dynamic AI driven decisions in realtime to provide the best path given customer satisfaction and frustration levels.
  • Routing: Agent selection and interaction management that empowers agents to positively and productively interact with customers in digital and voice channels.
  • Workforce Optimization: Inspire self-improvement and amplify quality management efforts to enhance the customer experience by assessing every interaction.
  • Analytics: Turn insights into results by making data relevant and actionable to drive measurable improvements and understand the end-to-end customer experience.

Sentiment analysis goes far beyond just words. It can also uncover frustrations your customers have as they traverse various customer service channels. Below are four contact center use cases where powerful AI sentiment analysis tools can deliver a more meaningful customer experience.

  1. Detecting frustration in automation – Beyond automated-response capabilities, self-service channels are now also aided by AI-driven sentiment analysis. This information can diagnose when a self-service experience is not as satisfying or as useful as an agent-assisted interaction would be. If a live agent is needed, sentiment analysis can recognize the urgency and route the customer accordingly. The key is to provide your customer an out if the automated workflow isn’t leading to a successful resolution.
  2. Intelligent routing – Contact centers can not only determine the emotional makeup of a customer, but also route that customer to an agent emotionally equipped to supply exceptional customer service. With AI sentiment analysis, it is fairly easy to determine who the most suitable agent is to help the customer, as well as provide the full context of the interactions, removing the frustration of repeated information and faster time to resolution.
  3. Determining root cause – AI in the contact center is more than just a feelings detector. It can extract powerful insights such as root cause sources of customer frustration. Separate from negative sentiment, customer frustration may be the most accurate detector of customer satisfaction and any underlying service issues. Determining the origins of a customer’s frustration will not only help resolve the issue at hand but also a contact center’s shortcomings going forward.
  4. Real-time feedback – Customer feedback can make or break a company, so it is critical for brands to take advantage of those moments. Sentiment analysis can flag conversations that meet the criteria of a successful customer interaction. Take advantage of the positive sentiment, in real-time, when your customer is still in the moment, by sending out a survey. It will pay dividends for your company’s brand reputation.

Delivering a powerful customer experience

As customer expectations continue to evolve, it is vital to understand every aspect of the customer journey – what is working and what is problematic. With advances in AI and Natural Language Processing (NLP), brands have a way to scale and identify what triggers positive or negative brand perception, giving us a glimpse into what was otherwise undetectable.

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