It's common to receive complaints from customers, but when your team also starts complaining, it can become overwhelming.
Have you ever calculated the amount of manual work your customer support agents have to do alongside handling customer interactions on calls, emails, or chat?
If you receive around 3000 tickets per month, your team could spend approximately 3.5 weeks solely on ticket tagging, review analysis, reporting, and performance checks.
Ticket Tagging consumes 82 hours
On average, it takes about 1 minute and 38 seconds to tag a ticket, which includes reviewing the customer support interaction and tagging the conversation.
To put it simply, if an agent spends approximately 1 minute and 38 seconds on support tags, that adds up to around 81.67 hours per month on average, which is equivalent to 2.04 working weeks.
Yes, you heard it right; that's over 2 weeks spent on ticket tags.
Tagging customer's complaints include:
- Reviewing customer conversations
- Choosing appropriate tags to categorize feedback
- Ensuring tag accuracy
AI ticket tagging tools that help you boost your customer feedback analysis, just like ClientZen, can reduce your ticket tagging by up to 95% since it uses artificial intelligence to apply smart semantic tagging automatically to every customer feedback.
Review analysis takes around 50 hours
Customer feedback analysis takes a bit of time from your team; the feedback analysis process can vary depending on a few factors, like the volume of customer reviews and data points, the complexity of the data analysis process, and, of course, the tools being used for feedback analysis.
Various customer feedback analysis methods, including manual analysis, automated tools, and AI-powered methods, can transform qualitative data from surveys and reviews into quantifiable insights.
Here are some general estimates for monthly data analysis and reporting:
- Small-scale analysis (simple metrics and trends): Reviewing basic metrics (such as NPS, CSAT, or number of support tickets) may take around 8-12 hours per month.
- Moderate analysis (trends, deeper insights): Deeper analysis involving multiple KPIs, trends, and detailed reports could take around 15-25 hours per month.
- Comprehensive analysis (segmentation, advanced insights): Advanced reporting, including segmentation, cross-referencing feedback with behavior, sentiment analysis, and recommendations, might take 30-50 hours or more per month.
If you would choose to automate customer feedback analysis, that would reduce this time with at least by 50% or even 80%.
Checking performance on your customer feedback data consumes 8 hours
Another 8 hour of work is spent on checking how customer feedback has evolved over a short manner of time, identifying trends, and discussions on how to improve customer satisfaction by utilizing both quantitative data and qualitative data in the analysis process.
These are shorter, weekly meetings that typically focus on operational performance and identifying immediate improvements. Here’s a breakdown for you:
- Performance Review (~30-45 minutes per meeting):
- Discuss overall ticket handling, SLAs, response times, and individual performance metrics.
- Compare metrics to previous weeks and address any underperformance.
- Trend Analysis (~15-20 minutes per meeting):
- Review recurring customer issues and common themes in tickets.
- Identify emerging customer trends (new issues, new product feature inquiries, etc.).
- Customer Feedback & Satisfaction (~10-15 minutes per meeting):
- Quick review of CSAT, NPS, and other feedback scores to monitor trends in customer sentiment.
- Immediate Process Adjustments (~10-15 minutes per meeting):
- Discuss potential quick improvements to workflows, tools, or ticket handling processes.
- Assign action items or tasks to team members based on the discussion.
- Open Feedback & Future Priorities (~5-10 minutes per meeting):
- Team members share any challenges or suggestions for improvement.
- Agree on short-term goals or tasks for the upcoming week (e.g., improve response time, focus on a particular issue).
By using ClientZen, you can significantly reduce this time by adding custom alerts for your segments, topics, or categories. This way, you’ll be notified automatically and instantly to know about every customer shift right away.
Mantra AI co-pilot can help you get personalized insights for each team member who would like to delve deeper into understanding their customer experience, thereby boosting customer loyalty and retention.
Strategic meetings can add up to 2.5 extra hours
Monthly meetings are held to focus on long-term performance, company goals, and larger improvements that require coordination across teams. The agenda for these meetings typically includes the following:
Using modern tools and technologies, such as AI and visualization software, can effectively analyze and understand customer feedback, transforming complex customer sentiments into actionable insights that enhance product and service improvements.
1. Long-Term Performance Review (30-45 minutes):
- A detailed review of performance metrics such as ticket volumes, CSAT, NPS, and response times over the last month.
- Identification of long-term trends, such as consistent low CSAT in specific product areas or ticket types.
2. Customer Experience & Business Alignment (45 minutes):
- Alignment of customer support goals with broader business objectives, such as launching a new product or enhancing an existing feature based on feedback.
- Prioritization of customer issues that require deeper business or product changes.
3. Process Optimization and Strategy Adjustments (30-45 minutes):
- Review of existing workflows to identify inefficiencies, such as manual tagging taking too long or redundant steps in ticket handling.
- Discussion and planning of automation opportunities, for example, implementing AI for auto-tagging or using self-service tools for customers.
4. Cross-Team Collaboration (15-30 minutes):
- Collaboration with other teams like product development, marketing, or engineering to discuss feedback that requires their input, such as product bugs, feature requests, or marketing miscommunication.
- Planning of cross-functional initiatives or changes that impact multiple departments.
5. Strategic Goal Setting & Planning (30 minutes):
- Setting high-level goals for the next quarter or month, for example, reducing ticket volume by improving product documentation or launching new support channels.
- Assignment of key stakeholders to drive these initiatives and creation of timelines.
ClientZen users have noticed a significant reduction in the time spent on strategic meetings ever since every team member gained access to their specific reports. With Mantra AI, each team member receives the specific insights they need without having to spend time on these tasks during their strategic meetings.
Spending 3.5 business weeks on manual analysis is ridiculous
Spending three and a half weeks on manual work is as absurd as stating, “Your call is important to us,” while your employees are stuck sorting through spreadsheets instead of assisting customers.
A feedback analysis tool can significantly reduce the time spent on manual analysis by enabling users to collect, analyze, and visualize customer feedback effectively. These tools often feature customizable surveys and advanced analytics capabilities, allowing businesses to gain valuable insights into customer preferences and sentiments without requiring technical expertise.
Real-World Examples of Customer Feedback Analysis Enhancement
Real-world examples of customer feedback analysis demonstrate its impact on business success. For instance, a SaaS company might use feedback analysis to identify areas for product improvement, leading to enhanced customer satisfaction. An e-commerce retailer could analyze customer feedback to optimize the shopping experience and boost their online reputation. Similarly, a restaurant might use feedback analysis to refine their menu and service, resulting in increased customer loyalty. By analyzing customer feedback, businesses can gain actionable insights that drive improvements in their products, services, and overall customer experience.
By automating customer feedback analysis, businesses can experience immediate benefits in just a few months.
Managing Support Volumes at Scale
As businesses grow, customer support teams often struggle to keep up with the increasing volume of customer requests. Customer feedback analytics can help by automating much of the analysis, enabling teams to efficiently manage large-scale feedback.
For example, Plannable reduced their feedback analysis workload by 15-20% by implementing ClientZen, allowing them to maintain high customer satisfaction despite the growing volume of support tickets. Similarly, PrestaShop, which receives over 150,000 pieces of feedback annually, was able to handle a workload that would typically require a larger team by using ClientZen.
Freeing Up Time for Customer Service Agent
Customer feedback analytics reduces manual workloads for customer service agents, allowing them to focus on solving customer problems more effectively. This led to a 30% increase in positive feedback related to feature requests within six months for Plannable. At PrestaShop, enhanced efficiency enabled their VoC team to focus on strategic tasks, reducing support tickets related to registration problems.
Automating Data Analysis and Detecting Negative Sentiment Drivers
CXA automates data analysis to detect negative sentiment and pain points without manual effort. ClientZen's platform identifies negative sentiment drivers in real-time, enabling instant access to key insights. This functionality helped PrestaShop detect registration issues and improve the customer experience. Additionally, ClientZen's automation tools track conversation trends, allowing businesses to address emerging issues and improve customer satisfaction proactively.
Improving Retention and Reducing Churn
By using ClientZen, PrestaShop reduced negative sentiment by 15% during onboarding and cut support interactions by 9%. This not only improved customer satisfaction but also reduced churn. Additionally, negative sentiment decreased by 4% and the average number of conversations per customer dropped by 1%. These changes show how CXA helps businesses identify issues early and make data-driven improvements to enhance customer loyalty.
Would you like to convert that 3.5 business weeks into a single click?
We recommend ClientZen. If you're looking to streamline your work, consider booking a demo. There's no commitment, and you'll discover how ClientZen can optimize your overall customer experience.
Customer feedback made easy
Customer feedback tagged automatically
Real-time customer sentiment scores
Pain-points evolution over time
