Customer service leaders often have access to more data than they know what to do with. Dashboards, charts, and metrics are everywhere—but clarity? That’s harder to come by.
Which metrics actually matter? And which reports give you the insight you need to improve service, support your team, and plan ahead?
In this guide, we break down six essential customer service reports that help teams uncover blind spots, reduce response times, and improve customer satisfaction. Whether you’re running a lean support operation or scaling a larger one, these are the reports you can’t afford to ignore.
Table of Contents
- What are customer service reports?
- Why do customer service reports matter?
- 6 customer service reports to track in 2025
- What about Predictive analytics in Customer Service Reporting?
- Reporting With Hiver: Go Beyond the Basics
- Final Thoughts: Reports Aren’t Just for Checking Boxes
- Get Insightful Customer Service Reports in Hiver
What are customer service reports?
Customer service reports provide a structured view of how your team is performing and how your customers are experiencing support. They compile key metrics—such as resolution times, CSAT, and ticket volume—into digestible insights that help you:
– Understand agent workload and efficiency
– Spot trends in customer issues
– Track progress toward support goals
Why do customer service reports matter?
1. Improve Team Performance
Reports help you spot bottlenecks and training gaps. For instance, if a particular channel (like chat) consistently shows slower response times, it may signal the need for more staffing or better workflows.
2. Elevate Customer Experience
When analyzed well, reports highlight friction points in the customer journey—long wait times, missed follow-ups, or repeated complaints. This allows you to refine processes or even update help center content.
3. Inform Strategic Decisions
At a leadership level, reports offer quantifiable insights to justify hiring, tool investments, or workflow changes. For example, a spike in escalation rates for certain issues might prompt more in-depth training or a UX fix.
6 customer service reports to track in 2025
1. Daily Volume of Customer Requests
This report shows how many customer queries your team receives daily—and through which channels (email, chat, phone, etc.).
Why it matters:
- Helps with staffing decisions
- Identifies peak support hours or days
- Reveals which channels may be under/overutilized
? In Hiver: You can use the “New Conversations” report to track all incoming queries by date and channel.
?Pro Tip: If you notice a spike in queries over the weekend, consider adjusting team schedules to avoid backlogs.
2. Requests Closed per Agent
This report tracks how many customer issues each agent resolves.
Why it matters:
- Gauges how effectively agents are managing their workload
- Identifies top performers who may be setting the bar for efficiency
- Surfaces workload imbalances, which—if left unchecked—can lead to burnout or inconsistent quality of services
Looking at closure numbers in isolation can be misleading, though. An agent who closes a large number of tickets might be resolving simpler issues, while others may be handling more complex ones. That’s why this report is best interpreted alongside other metrics like CSAT and Average Handle Time.
? In Hiver: You can view conversations closed per agent over time. For example, the report may show that ‘Abhinav’ closed 52 conversations last week—helping managers understand workload patterns and performance at a glance.
?Pro Tip: If one agent is closing significantly more tickets than the rest, check whether they’re overburdened, using more efficient workflows, or simply taking on less complex issues. This insight can inform fairer task distribution and even surface best practices worth sharing across the team.
3. Average Response Time
Average Response Time is the average time your customer service agents take to respond to customer requests. It is calculated by dividing the total time taken to respond to requests by the total number of requests received.
Why it matters:
- A core driver of customer satisfaction and trust
- High response times can lead to frustration and churn
- Helps managers evaluate team bandwidth and identify slowdowns
If your average response time starts to climb, it may be a sign your team is stretched thin or bottlenecks exist in ticket routing.
? In Hiver: The Response Time Report breaks this down by agent, channel, and time frame. This allows managers to spot which areas need intervention quickly.
?Pro Tip: Combine response time insights with ticket volume trends to understand if delays are due to high demand—or workflow inefficiencies. Automating request routing or adding self-service options can help reduce pressure on agents.
4. Average Handle Time
Average Handle Time (AHT) is the average amount of time a customer service agent spends actively handling a request. This includes the time on the call or chat, any hold time, and post-interaction tasks like documentation.
Why it matters:
- Longer handling times often indicate inefficiencies or knowledge gaps
- It’s closely tied to customer experience—no one likes waiting too long for answers
- Useful for workload planning and setting realistic SLAs
Let’s say a customer contacts a travel agency to change a flight. The agent begins the interaction at 10:00 AM and sends confirmation by 10:15 AM—that’s a 15-minute handle time. If similar requests start taking 30–45 minutes, you’ll want to investigate where delays occur.
?Difference between Average Handle Time and Average Resolution Time
These two metrics may sound similar, but they measure different things:
- Average Resolution Time (ART) is the total time taken to resolve a customer issue—start to finish. This includes all back-and-forths, waiting periods, escalations, and agent hand-offs.
- Average Handle Time (AHT), on the other hand, refers to the total time an agent spends on a customer interaction. This includes the time spent talking or replying to the customer, plus any after-call or follow-up work. It’s useful for evaluating agent productivity.
5. First Contact Resolution
First Contact Resolution (FCR) measures the percentage of customer queries that are resolved in the very first reply—without any need for follow-ups or escalations.
Why it matters:
- It’s one of the strongest indicators of efficient and effective support
- High FCR rates often correlate with higher customer satisfaction and lower operational costs
- Reduces agent workload and shortens resolution cycles
Improving FCR starts with empowering your agents to deliver complete answers upfront. That includes giving them access to past conversations, contextual customer data, and clear internal documentation.
Strategies to improve FCR:
- Build a well-maintained internal knowledge base
- Use AI-powered tools like Hiver’s Copilot to instantly surface relevant customer information
- Train agents to anticipate likely follow-up questions and address them proactively in the first reply
Sample report showing First Contact Resolution on a daily basis
?Case in point: Vacasa, a vacation rental company, used Hiver to automate email assignments and streamline internal collaboration. Instead of manually forwarding emails or sending side messages, agents simply tagged teammates and added notes. This allowed them to reduce turnaround time and resolve queries 80% faster.
6. Customer satisfaction score
CSAT (Customer Satisfaction Score) measures how satisfied a customer is with a particular support interaction. Usually gathered via post-interaction surveys, it’s one of the clearest indicators of service quality.
Why this matters:
- Provides real-time feedback on agent performance and service quality
- According to Hiver’s latest benchmark report, 41% of support teams consider CSAT their most important KPI.
- Trends in CSAT can uncover deeper issues in processes, tools, or communication
? In Hiver: You can automatically send CSAT surveys after conversations and filter results by agent, team, tag, or channel. This lets you drill down to the root causes behind rising or falling scores.
?Pro Tip: Don’t just collect CSAT scores—review the open-ended feedback alongside the numbers. Then, work cross-functionally with product and operations teams to fix the most common root causes. This creates a tighter feedback loop and improves both the customer journey and internal processes.
What about Predictive analytics in Customer Service Reporting?
Customer service reporting isn’t just about what has happened—it’s also about anticipating what will happen. Predictive analytics uses historical data and machine learning to forecast customer issues, volume spikes, or even churn risks.
For example, if your data shows a recurring spike in tickets after a new product update, your team can prep ahead of time with FAQs or staffing support.
In fact, Verizon uses generative AI to determine the reason behind 80% of its customer calls. This strategy has helped the company retain up to 100,000 customers annually.
Reporting With Hiver: Go Beyond the Basics
In order to rigorously track such reports, you need a customer service platform. That’s where Hiver can help.
It’s a customer service platform designed to feel as intuitive as your everyday inbox. It combines familiar email-like usability with powerful collaboration, automation, and reporting features tailored for support teams.
Here’s a breakdown of reporting capabilities in Hiver:
1. Conversation Reports
Conversation Reports in Hiver help you understand how effectively your team is managing customer conversations. With the help of these reports, you can understand the number of conversations that have taken place, how quickly your team responds to queries, and the average time they take to resolve these queries.
2. User Reports
Keep track of every support agent’s performance and workload. Find out their average response and resolution times, Customer Satisfaction (CSAT) ratings, and much more. With the help of Hiver’s User Reports, you can identify top performers and the ones who might need training or assistance.
3. Tag Reports
Tag Reports in Hiver help you identify trends and recurring issues across customer conversations. For instance, you can track the number of open or pending conversations tagged as ‘high priority’—making it easier to spot bottlenecks, escalate issues early, and allocate resources where they’re most needed.
4. Custom Reports
Custom Reports in Hiver give you the flexibility to go beyond default metrics. You can build tailored dashboards by applying filters across tags, statuses, time periods, or team members—so you’re always looking at the data that matters most.
Below is a custom report showing the number of new conversations assigned to a support team from March 16th to April 14th, tagged as ‘L1-Chat.’ This level of granularity can help you understand conversation trends at a much deeper level. For instance, if there’s a sudden spike in L1-Chat tickets during a specific week, you can investigate what triggered it—be it a product bug, a marketing campaign, or a seasonal surge.
Final Thoughts: Reports Aren’t Just for Checking Boxes
Customer service reports aren’t just internal dashboards—they’re your best tool for uncovering blind spots, making smarter decisions, and building a team that’s prepared for what’s next.
But data only becomes valuable when it’s used correctly. Whether you’re tracking CSAT trends or resolving tickets faster, the goal should always be to improve—not just measure.
Start with these six reports, dig into the insights, and use them to shape a smarter, more responsive support experience.
Get Insightful Customer Service Reports in Hiver
- See how your team is performing at a glance
- Track key metrics like response time and resolution rates
- Use insights to make smarter support decisions
