Elevate Zendesk Support with Conversational Analytics

Traditionally, customer support data analysis focused on quantitative aspects, such as response times and ticket resolution rates. While those metrics are well established performance indicators, they fail to contextualize customer service ticket data. To that end, conversational support analytics adds a qualitative layer, deciphering the sentiment, intent, and contextual nuances embedded in customer conversations.

If you are looking to contextualize your Zendesk Support conversations and go beyond mere transactional insights, conversational analytics can unravel the intricacies of customer needs, pain points, and satisfaction levels.

What are Conversational Analytics?

Conversational analytics refers to the systematic analysis of interactions between customers and support channels, particularly in written or verbal exchanges such as chat messages, emails, or phone conversations.

By leveraging natural language processing (NLP) and other advanced analytical techniques, conversational analytics enables customer-centric organizations to gain a deeper understanding of the qualitative aspects of customer communication to identify trends, patterns, and opportunities to enhance the customer experience, ultimately leading to more informed decision-making and improved customer satisfaction.

In platforms like Zendesk, conversational analytics plays a pivotal role in decoding customer conversations to provide a holistic view of customer interactions.

Conversational Analytics vs. Feedback Surveys

While customer feedback surveys have long been a staple for gauging satisfaction, conversational analytics emerges as a more dynamic and nuanced solution. Customer feedback surveys often rely on predefined questions, limiting the scope of responses to predetermined options. This structured approach may inadvertently overlook the subtleties of customer sentiment, as customers might find it challenging to express complex feelings within the constraints of a survey.

Conversational analytics, on the other hand, operates in a more flexible and adaptive manner. By analyzing customer interactions, it captures unfiltered and authentic expressions of sentiment and provides a real-time, contextual analysis of customer data.

Furthermore, conversational analysis can help you enhance and validate your understanding of strategic KPIs such as Net Promoter® Score (NPS), Customer Effort Score (CES), Customer Satisfaction (CSAT) you monitor via feedback surveys.

Zendesk’s Current Analytics Capabilities

Zendesk users can use the platform’s analytics solution Zendesk Explore to track and monitor quantitative metrics which can include ticket attributes or agent responses and performance KPIs. Zendesk Explore, however, does not offer built-in text or sentiment analytics capabilities.  These limitations make it challenging to contextualize and understand qualitative support ticket data.

How to Use Surveypal Insights to Analyze your Zendesk Conversations

Here’s what you can do by implementing Surveypal Insights into your Zendesk Instance:

Gauge Customer Sentiment

Implementing conversational analytics within Zendesk enriches customer support with a deeper understanding of customer sentiment, intent, and contextual nuances. This enables you to gain insights beyond surface level-metrics which can be used to craft personalized responses, identify emerging trends, address repetitive issues preemptively, and adapt support strategies dynamically.

Real-time Insights

One of the standout advantages is the real-time nature of conversational analytics. Unlike traditional surveys, which offer a window into customer perceptions post-service, conversational analysis provides you with immediate insights into ongoing customer interactions. This allows you agility in the context of daily support operations and the opportunity to adapt strategies by making data-driven decisions.

Automated Analysis of Large Ticket Volumes

By automating the analysis of large volumes of customer interactions you can uncover patterns, identify common issues, and streamline workflows. This automation not only saves time but also allows you to allocate resources more effectively, reducing response times and optimizing the overall customer support process.

Merge Contextual Topic Analysis with Zendesk Metrics

Surveypal Insights analyzes your Zendesk ticket data to automatically discover topics that emerge from customer conversations. This process enables you to capture insights without the need of manual coding. By merging contextual topic analysis with Zendesk metrics you can:  

1. Uncover process and knowledge gaps

Combining conversational analytics with operational metrics such as ticket reopen rates or ticket resolution rates you can gauge your teams’ ability to address and resolve issues associated with any give topic and assess the efficiency of processes such as ticket routing, support automation, and training agent training programs.

2. Evaluate the financial impact of your support tickets

Surveypal Insights crunches conversational data in conjunction with other operational metrics to derive the average cost per ticket on any topic. This way you can quantify the financial impact of your support operations and evaluate how addressing a product issue or a process inefficiency will lower your customer service costs.

3. Predict support performance

If every customer were to rate the support they received from your team, how would you score? The Predictive Performance Score is a metric designed to help you answer that question. In order to generate your Predictive Performance Score, Surveypal Insights analyzes your support tickets through the prism of more than 10 performance-focused metrics to deliver a more holistic image of your customer service experience.

Conclusion

Gaining qualitative insights from your Zendesk conversations is easier with Surveypal. Combine Zendesk Support with the analytical power of Surveypal to get actionable insights of your customer service data and gain a deeper understand of the customer experience.