Wouldn’t it be great if you were able to automatically analyze all your Zendesk tickets to gain actionable insights?
Customer service interactions produce a goldmine of data that can be used in many ways to improve support performance and the customer experience. Most of us, however, do not have enough time or resources to comb through this data and make sense out of it manually. The good news is that AI has come very far and technologies such as text analytics enable you to examine your customer experience data on a deeper, more insightful level.
If you are thinking of leveraging AI to power up your Zendesk with text analysis, then you are on the right track. Unfortunately, the limitations of Zendesk’s analytics capabilities leaves you with three options.
- You could take the manual approach, open excel, and try to extract meaning from your textual data by yourself. This could actually work if you have an extremely low volume of customer service inquiries. In any other case, this approach is time and resource consuming.
- Ask your data scientists to write scripts to extract insights from your support conversations. If you are lucky enough to have a data scientist in your company, chances are you will have to compete with other departments in your organization for their time. Additionally, the analysis of your Zendesk interactions will not happen in real-time leading you to miss out on valuable insights.
- You can perform automatic text analysis by using a tool built specifically for Zendesk.
Keep on reading to find out what are the benefits of text analytics tools for customer service teams and how to enhance Zendesk with an automated text analysis solution.
What is Text Analytics?
Text analytics, in the context of customer service, refers to the process of extracting deeper insights and meaning from unstructured textual data, such as customer feedback, emails, chat*, ticket content, etc. In its essence, it transforms the wealth of unstructured customer data into actionable intelligence, driving informed decision-making and delivering more efficient and effective customer service experiences.
Text analytics harnesses natural language processing (NLP) and machine learning techniques to systematically analyze and understand the sentiments, preferences, and concerns expressed by your customers in written form therefore, enabling your team to identify patterns, trends, and emerging issues, facilitate proactive responses, personalize support, and enhance overall customer satisfaction.
Making the Case for Automated Text Analytics in Zendesk
Here are some of the main reasons why you need a text analytics solution in Zendesk.
Improved Customer Understanding:
Gain deep insights into customer sentiment, needs, and pain points. By analyzing customer tickets and messages, you can identify recurring issues and understand preferences, to tailor your support efforts more effectively.
Enhanced Issue Prioritization:
With text analytics, you can automatically categorize and prioritize tickets based on urgency and severity. As a result, you can quickly address critical issues and allocate resources efficiently, leading to faster response times and improved customer satisfaction.
Automated Ticket Routing:
Automatically route tickets to the most suitable agents or departments based on the content and context of the customer’s request. This ensures that customers receive assistance from the right experts, reducing resolution times and minimizing frustration.
Proactive Issue Resolution:
Text analytics empowers you to identify emerging trends and potential problems before they escalate. This proactive approach allows you to address issues early, preventing negative feedback and customer churn.
Personalized Customer Support:
By analyzing historical interactions and customer profiles, text analytics apps can provide agents with valuable context during conversations. This personalization enhances the customer experience by making interactions more relevant and empathetic.
Efficient Knowledge Management:
Index and categorize a vast amount of textual information, making it easier for agents to access relevant knowledge articles and resources when handling tickets thus streamlining issue resolution and reducing agent research time.
Text analytics can assist in monitoring and evaluating the quality of customer service interactions. It can flag issues like compliance violations, inconsistencies, or missed opportunities for upselling, ensuring that the service provided aligns with company standards and Service Level Agreements (SLAs).
By automating ticket categorization, routing, and initial responses, text analytics can help you optimizing resource allocation to reduce operational costs while maintaining or even improving support quality.
Training and Coaching:
Text analytics tools can help you systematically evaluate agent performance by examining an array of data such as response time, accuracy, and ability to resolve issues at first contact. By analyzing big volumes of customer care interactions, you can identify recurring issues or common challenges your agents may face and design targeted training modules or coaching sessions to address them.
Leveraging text analytics in customer service can set your businesses apart from competitors. It demonstrates a commitment to understanding and meeting customer needs, which can result in customer loyalty and positive word-of-mouth recommendations.
Surveypal’s Text Analysis Solution for Zendesk
When it comes to text analysis tools for Zendesk Support, Surveypal offers one of the most well-rounded solutions in the market. Here’s the main reasons why:
Contextual Topic Analysis
Analyze customer interactions, such as emails, chat logs, support tickets, and social media conversations, to understand not just the keywords or topics being discussed, but also the context in which they are mentioned. As a result, Surveypal generates granular, root-cause-level insights that can be used to improve productivity, CX, and sales.
Integrate Contextual Topic Analysis with Zendesk Metrics
Make your data work harder by combining contextual topic analysis insights with your Zendesk KPIs to gain a comprehensive view of customer outreach, pinpoint areas of friction, and a deeper understanding on how customer perceptions and sentiments impact your core perfrormance metrics.
Predictive Performance Score
If every single customer that reached out to you with an issue were to rate the level support they received, what would that score be? If this score existed, it would give you a much more accurate overview of the state of your customer service experience. Surveypal is able to generate a Predictive Performance Score based on your existing customer care data – including text analytics data- and get you a step closer to making decisions based on data that is not limited to small subset of interactions but represents the perceptions of your broader customer base
Multilanguage and Multichannel Coverage
You customers might speak many different languages and choose to contact you through a variety of channels – such as email, chat, messaging apps, etc. Surveypal’s text analytics solution automatically covers multiple languages and channels to ensure that every customer’s voice is heard.
Open – ended Feedback Analysis:
Aggregate and analyze customer feedback to identify common themes and areas for improvement. Combine unstructured customer feedback data analysis with KPIs and structured metrics to shape product development and service enhancements.
Here are the most important takeaways from this article:
- Automated text analysis enhances your ability to better understand your customers, offer superior support, and make data-driven decisions that impact your bottom line and improve the customer experience
- Zendesk does not offer built-in text analytics capabilities but fear not, text analytics solutions such as Surveypal Insights can be easily integrated into Zendesk and deliver real-time insights
- Find Surveypal Insights in Zendesk Marketplace to make the most ofthe textual data in your support environment