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Article 4 min read

The end of the survey era (as we know it) is nigh

While surveys are useful tools for gathering customer feedback, AI-driven customer service analytics can provide deeper customer insights and streamline your support operations.

By Keti Limani, Marketing Manager at Surveypal

Last updated November 30, 2023

Long gone are the days when customer service was just a department and customer experience (CX) just a strategy. As more and more companies fight it out on the CX battlefield, customer service has evolved into an engine for growth. Organisations are continually looking for better ways to evaluate, predict, and improve the customer experience—and, as a result, their bottom line.

For years, surveys and customer feedback were considered a one-way street to capturing CX insights, and rightfully so, as there was no other reliable alternative. However, the rapid advancement of AI technology has created new avenues worth exploring—not necessarily to eliminate CX surveys but rather to enhance our understanding of customer needs, expectations, and emotions.

Surveys provide valuable data but don’t offer the depth, speed, and context that AI-powered insights solutions can deliver. The potential benefits in terms of customer satisfaction, operational efficiency, and brand loyalty make AI a strategic investment for customer-centric organisations committed to delivering exceptional experiences and driving sustainable growth.

The power of AI-driven CX insights

AI-driven customer service analytics come with many advantages that can help revolutionise support and simplify operations:

  • Real-time insights

  • Insights at scale

  • Comprehensive data analysis

  • Sentiment analysis

  • Predictive analytics

  • Personalisation opportunities

Real-time insights

Unlike surveys, which capture feedback after customer interactions, customer service AI analytics provide real-time insights by immediately analysing incoming support tickets. This allows you to spot issues and trends as they occur, so you can proactively address concerns and enhance the customer experience promptly.

Insights at scale

AI-driven customer service analytics can offer CX insights at scale by examining data across all tickets, not just at the individual ticket level. This approach provides a holistic view of customer interactions and trends, empowering you to identify process inefficiencies and take corrective action to optimise customer service performance at scale based on aggregated data.

Comprehensive data analysis

While surveys offer valuable insights, they often lack the depth and context required to fully understand customer sentiments. AI analytics can process vast amounts of unstructured qualitative data—including text from support interactions, emails, and social media—so you gain a deeper understanding of customer conversations. This richer dataset also helps you uncover hidden insights, such as emerging product issues, recurring customer pain points, or unmet expectations.

Sentiment analysis

AI-powered analytics can perform sentiment analysis to gauge the emotional tone of customer interactions. This allows you to understand not only what customers are saying but also why they’re saying it and how they feel about their experiences. You can leverage this information to make adjustments. For example, if you identify a surge in negative sentiment related to a particular product feature, you can prioritise product improvements to mitigate customer frustration.

Predictive analytics

AI can predict future customer behaviour based on historical data and patterns. This capability enables you to anticipate customer needs and proactively offer solutions, reducing the likelihood of issues escalating and increasing customer satisfaction and loyalty.

Personalisation opportunities

According to the Zendesk Customer Experience Trends Report, 76 percent of customers expect personalised customer service, and AI helps you deliver on this expectation. It can personalise responses and recommendations based on customer preferences and past experiences, resulting in more positive and engaging interactions.

The benefits of AI analytics in customer service

AI analytics solutions may incur higher initial costs compared to survey tools. However, the long-term benefits far outweigh the upfront investment. Here are a few advantages:

  • Reduced customer churn: Customer-driven organisational decision-making can yield up to 700 percent ROI over 12 years. By utilising AI to obtain customer intelligence, identify and resolve issues more efficiently, and offer better customer service than your competitors, you can reduce customer attrition rates and increase customer lifetime value.
  • Preemptive customer service: The predictive capabilities of AI data analytics are a game changer because they help you anticipate future customer issues so you can take steps to prevent them from ever arising. As a result, you can save your customers the frustration and your business the costs that come with churn.
  • Improved operational efficiency: AI can automate the analysis of support tickets, saving your agents countless hours and allowing them to focus on higher-value tasks.

  • Competitive advantage: Brands that harness AI for customer insights gain a competitive edge by rapidly addressing customer needs and staying ahead of their competitors.
  • Enhanced brand reputation: A proactive approach to customer service and continuous improvement based on AI insights can lead to a stronger brand reputation and increased customer trust.

Use AI to enhance CX

Surveys come with shortcomings and biases, but they are still effective for capturing customer feedback. On the other hand, AI analytics is a great way to mitigate the limitations of surveys and turn your vast warehouse of customer data into opportunities to identify customer friction, drive growth, and elevate your overall CX.

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