The Ultimate Guide to Ticket Analysis for Business Success

Learn how ticket analysis can transform your business. Our ultimate guide covers strategies to optimize performance and success.

Sep 21, 2024

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The Ultimate Guide to Ticket Analysis for Business Success

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Your customer service team is buried under a mountain of tickets. They're struggling to keep their heads above water, and it shows. Customer satisfaction is plummeting, and your team is frustrated. To make matters worse, there needs to be a clear end in sight. This scenario is all too common, especially during peak seasons when customer inquiries skyrocket. Fortunately, Ticket Analysis is an effective way to get your team out of this jam. Through thorough ticket analysis, you can uncover actionable insights that will help your business improve customer support efficiency, enhance customer satisfaction, and drive overall business success. Read on to learn more about ticket analysis, how it works, and how it can help your business.

One valuable tool to help you achieve your goals is AI customer support software, such as ChatBees. Hubspot Help Desk Software can help lighten the load for your customer service team by tackling repetitive inquiries so they can focus on resolving complex issues. In doing so, you'll enhance the customer experience and uncover hidden insights from ticket analysis that will foster better business performance.

What is a Support Ticket System?

A support ticket system is a tool for managing customer inquiries and issues. When a customer seeks help, you can create a ticket. This ticket is a digital note for tracking and resolving the customer’s problem.

The ticket records all the information related to the issue, including conversations between the customer and the support team and any notes, files, or other documentation that may help in the resolution process. Support ticket systems help you stay organized so no customer issue falls through the cracks. They also allow for smoother, faster customer support by providing structure to resolving incoming customer inquiries.

How Does a Support Ticket System Work?

A support ticket system collects and organizes customer inquiries to be tracked and resolved efficiently. Tickets can come from various channels, such as:

Social media

Live chat or messaging

Customer support

Portal you have set up on your company’s website. An omnichannel approach to customer service enables companies to streamline their ticket workflows by organizing requests from all their channels and bringing them to one comprehensive dashboard.

Omnichannel ticketing systems allow queries from any channel, and support ticket systems give visibility into customer conversations across the organization. These systems allow the support team to collaborate to solve queries or extract relevant insights from tickets.

The Importance of Terminology in Customer Support Interactions

Some help desk providers have ditched the term support ticket in favor of more human-sounding terms like conversations or chats. All of these terms reflect the back-and-forth nature of support tickets. They are conversations, and these conversations carry a wealth of data.

This data is relevant to teams across the organization, from marketing support to sales. For example, our service level agreement (SLA) feature will automatically notify management if customer service agents aren’t responding to tickets in the timeframe you promised your clients.

What are the Benefits of Using a Support Ticket System?

Good customer support software allows you to manage multiple conversations at a time, whether new or previously existing. Your ticketing system should also provide a way to establish a knowledge base of common issues your users are experiencing, which can be a great reference for support agents or an external customer-facing resource to deflect common queries.

Once a frequently asked question or request comes in, automation can direct the customer to self-service channels, deflect the query to the appropriate agent, or lead to the creation of an article inside a knowledge base.

Strategies for Effective Ticket Management and Escalation

You could mark open tickets as a certain status so your team knows the issue is common and can be responded to en masse. While some backlog is normal, support leaders can create a queue system that prioritizes tickets so no customer request is left open for too long. A ticket escalation process would be useful for more complex and challenging inquiries.

With a robust ticket escalation process, your team can swiftly and efficiently resolve issues in today’s fast-paced and customer-centric landscape. A support ticket system is the best way to scale your customer service efforts to provide better, more personalized experiences.

What is a Support Ticket Analysis Report and Why is it important?

A support ticket analysis report reveals trends happening with your submitted tickets. This report shows the different types of help desk tickets you submitted. By adhering to a consistent rhythm of reviewing and analyzing your tickets, you can improve your support interactions and experiences.

What Does This Analysis Report Do for You and Why is it Important?

Seeing trends populating behind your hundreds of ticket submissions lets you know how to alleviate your ticket volume. You’ll also be able to diminish some of your team members' redundant workload.

Solving repetitive items that can be clarified with self-help documents will go a long way to clear up time to focus on bigger tasks. This analysis report helps you connect the dots and lets you see what’s happening in your help desk department.

5 Key Areas to Focus on For Help Desk Ticket Analysis

What should you focus on and ensure is included in your help desk ticket analysis? Take the following five key data points and ensure you know what these typical help desk KPIs are saying and why they may be essential for you to.

1. Help Desk Load

See the number of ongoing tickets, how many are received on a specific basis, and the time your team members are working to respond to tickets. This initial point will give you a good measure of what is happening with your help desk team. From there, the other points below will offer a more granular view of the items impacting your help desk load.

2. Average Resolution Time

Know how long it’s taking your team to bring the submission to a resolution. The longer your team takes to solve the average ticket, the less your team can handle it. If your team has sufficient resources available to users, it may be commonplace for your team to deal with longer resolution times.

This means they are dealing with more intricate tickets and not spending an inordinate amount of time on simple tasks. Dig into the average issues and whether the resolution time matches the average ticket type.

3. Average Response Time

Gauge how long it takes your team to respond to help desk tickets as they come in initially. If you notice any submission taking longer than 24 hours to respond, an issue must be addressed. Whether staffing or efficiency, it’s best to keep the threshold lower than this to maintain your customer experience.

4. Ticket Volume

To find trends to know your biggest pain points, you’ll need to keep a steady eye on ticket volume and what the peaks look like. If you’re seeing significant spikes, it’s probably suggestive that you have something that requires immediate action.

Something may be broken in the system, or you may need more external-facing documentation for your users. If you’re seeing a steady pace of notable volume increases, it may be time to hire more staff.

5. Ticket Volume by Channel

If your organization collects help desk tickets from channels other than a single submission pipeline, understand and visualize which channels populate the most volume. This can tell you two important things.

If you have a particular channel producing more volume than others, it may need to be given more attention by staff or more self-help options. If one channel seems to be lagging in volume more than the others, it could indicate that you’re providing sufficient support or that the channel option may or may not need to be advertised more. It’s up to you and your data to determine which category this falls into and where you should go.

Enhancing Customer Support Efficiency with AI Solutions

ChatBees optimizes RAG with our AI customer support software for internal operations like customer support, employee support, etc.. This software provides the most accurate response and easily integrates into workflows in a low-code, no-code manner. ChatBees' agentic framework automatically chooses the best strategy to improve the quality of responses for these use cases.

This improves predictability and accuracy, enabling these operations teams to handle more queries. No DevOps is required to deploy and maintain the service.

Start for free

Try our AI customer support software to 10x your customer support operations today. Get started for free, with no credit card required. Sign in with Google and get started on your journey with us today!

Ticket Deflection

Reduce Support Tickets

Automate Support

Scaling Customer Support

Ticket Queue Management

10 Help Desk Metrics and KPIs You Should Be Tracking

1. Response Time: Understand This Metric to Improve the Customer Experience

Response time is a critical metric that gauges the efficiency and effectiveness of a support team by measuring the time it takes for customer agents to respond to customer inquiries. This report helps organizations identify how quickly customers receive attention after raising a request or issue, directly correlating to customer satisfaction.

By analyzing variations in response times, help desk managers can pinpoint operational bottlenecks, assess the impact of staffing levels, and implement strategies to enhance responsiveness. Optimizing average response times not only improves the customer experience but also boosts the overall productivity of the help desk team by ensuring resources are appropriately allocated.

2. Resolution Time: The Key to Understanding Help Desk Efficiency

Analyzing resolution times is an essential tool for evaluating the overall effectiveness of a customer support team that focuses on the duration it takes to fully resolve a customer's issue from the moment it is reported. This metric is pivotal for assessing the competency and efficiency of the support process, as shorter average resolution times often lead to higher customer satisfaction.

By tracking and analyzing these times, management can identify trends and inefficiencies in problem-solving. This report also allows organizations to set realistic performance benchmarks, promote continuous improvement, and fine-tune their approach to handling customer issues, ultimately leading to a more streamlined and effective help desk service.

3. Ticket Volume, Tickets Opened, and Tickets Resolved Rate: Keep Your Help Desk Organized

Tracking ticket volume, tickets opened, and tickets resolved rate offers a comprehensive overview of a support team's workload and throughput. This report tracks the number of new help desk tickets created within a specific timeframe alongside the number of tickets successfully resolved, providing a clear snapshot of customer demand and operational efficiency.

Analyzing these key metrics allows management to assess the balance between incoming support requests and the team's capacity to address them. High volumes of unresolved tickets might indicate:

Understaffing

Insufficient training

Inefficiencies in the support process

A high-resolution rate suggests that the team is managing its workload effectively. This report helps ensure that the help desk is adequately staffed and equipped to maintain high levels of customer service.

4. Customer Satisfaction: The Most Important Metric for Help Desk Success

Customer satisfaction (CSAT) is a vital indicator of how well a support team meets customer needs and expectations. This report gathers data from post-interaction surveys, feedback forms, and direct customer ratings to quantify satisfaction levels. This type of analysis is crucial for maintaining high customer service standards and shaping future customer engagement and retention strategies.

By closely monitoring CSAT, businesses can assess the impact of their customer service efforts and identify specific areas needing improvement. For example, high satisfaction rates are often linked to customer loyalty and positive word-of-mouth, while lower scores can signal the need for immediate corrective actions.

5. Net Promoter Score: Measure Customer Loyalty With This Simple Help Desk Metric

Net promoter score (NPS) is a powerful metric that gauges customer loyalty and the likelihood of customers recommending a company to others. NPS is calculated based on responses to the following question: How likely are you to recommend our service to a friend or colleague? Responses are graded on a scale from 0 (not at all likely) to 10 (extremely likely).

NPS categorizes respondents as promoters, passives, or detractors and subtracts the percentage of detractors from the percentage of promoters to determine the overall score. Regularly reviewing NPS enables companies to measure customer sentiment and satisfaction over time, identify trends, and initiate targeted improvements in areas that significantly impact customer loyalty and advocacy.

6. Average Handle Time: Watch This Metric to Ensure Quality Customer Service

Average handle time (AHT) is a metric used to assess the efficiency of customer support interactions. It measures the average duration agents take to resolve a customer issue from start to finish. This includes all the time spent talking to the customer and any time spent on related tasks.

Thoroughly analyzing AHT helps businesses gauge the effectiveness of their training programs, the adequacy of their resource allocations, and the complexity of issues handled. Remember that it’s not all about speed; a lower AHT may indicate a more efficient resolution process, but balancing AHT with quality of service is essential.

7. Customer Effort Score: Measure How Easy It Is for Customers to Get Support

Customer effort score (CES) is an insightful metric that evaluates how customers can resolve their issues with a support team. This score is derived from customer responses to a specific question, such as, How easy was it to resolve your issue?

By analyzing CES, businesses can pinpoint aspects of customer interactions that are most problematic or cumbersome and initiate targeted improvements to streamline processes. This focus on minimizing customer effort is crucial for increasing satisfaction and loyalty, as more accessible interactions encourage loyalty and positive recommendations.

8. Escalation Rate: Identify Complex Customer Issues That Need Additional Support

The escalation rate measures the percentage of customer issues that require escalation from the initial point of contact to higher levels of support or management to achieve resolution. This rate is an essential indicator of the complexity and severity of issues being reported and the capability of the first-tier support team to handle them.

Monitoring and managing escalation rates helps businesses optimize their resource allocation and improve the efficiency and effectiveness of their customer service operations. This ultimately increases customer satisfaction and reduces operational costs.

9. First Contact Resolution Rate: Improve This Metric to Boost Customer Satisfaction

The first contact resolution rate (FCR) indicates the proportion of customer issues resolved during the initial interaction with the support team without further follow-ups or escalations. A high FCR rate is generally associated with higher customer satisfaction, reflecting the support team's ability to address problems quickly and effectively.

FCR also helps:

Identify training needs

Improve communication tools

Refine problem-solving techniques

By improving FCR, businesses can:

Significantly reduce operational costs

Decrease the volume of repeat calls

Improve overall customer loyalty

10. Ticket Distribution: Understand Your Help Desk’s Ticket Data

Analyzing ticket distribution provides crucial insights into the volume and types of issues reported across various categories and departments. This enables businesses to visualize workload distribution and identify patterns in customer inquiries. This report breaks down ticket data by category, such as:

Technical support

Billing issues

Product Inquiries

Understanding ticket distribution helps management allocate resources more effectively, ensuring staffing levels and expertise match demand. It also highlights trends in customer needs or recurrent issues, guiding process improvements, targeted training initiatives, and the development of proactive measures to reduce incoming ticket volume in specific categories.

How to Implement Support Ticket Analysis in Your Business

Support ticket analysis helps businesses improve customer service by analyzing the data generated from support tickets. To get started, support ticket analysis requires setting up a system that effectively captures and organizes relevant customer data.

This typically involves using a support ticket management platform that centralizes all communication, categorizes tickets, and tracks performance metrics.

Setting Up a System for Ticket Analysis

When setting up a support ticket analysis system, it is essential to ensure that all customer interactions are logged and categorized correctly. This ensures that no valuable data slips through the cracks and enables robust analysis and reporting. In addition to categorizing tickets, businesses should consider implementing automated workflows and tagging systems. These features can:

Streamline the ticket management process

Prioritize critical issues

Facilitate better collaboration within the support team

Training Your Team for Effective Analysis

To maximize the benefits of support ticket analysis, it is crucial to equip your team with the necessary skills and knowledge. Training your support staff on how to collect, interpret, and analyze support ticket data can make a world of difference in the effectiveness of your initiatives. Fostering a culture of continuous learning and improvement will ensure that your team stays up-to-date with the latest support ticket analysis techniques and best practices. Regular training sessions, workshops, and knowledge sharing can help your team refine their analysis skills and gain a deeper understanding of your customers' needs.

Interpreting the Data from Support Tickets

Once your support ticket analysis system is up and running, it's time to dive into the data and extract valuable insights that can guide your customer success efforts.

Identifying Common Customer Issues

Analyzing support tickets allows businesses to identify the most prevalent issues customers face. This knowledge serves as a roadmap for resolving recurring customer problems, streamlining processes, and enhancing overall customer satisfaction. By addressing these common pain points, organizations can demonstrate their commitment to customer success and build stronger relationships with their clientele.

Recognizing Trends and Patterns

Support ticket analysis helps uncover emerging trends and patterns that might go unnoticed otherwise. By examining patterns in support tickets, businesses can gain a better understanding of the evolving needs of their customers.

This insight empowers organizations to anticipate future challenges, adapt their strategies, and stay ahead of the competition. It also presents an opportunity to develop proactive solutions and preemptively address customer concerns before they escalate.

Hubspot Ticketing System

Ticketing Tools

Service Hub Hubspot

Hubspot Operations Hub

Hubspot Notion Integration

Hubspot Help Desk

Hubspot Tickets

Call Center Ticketing System

Best Ticketing Apps

Leveraging Support Ticket Analysis for Customer Success

Businesses can leverage insights from support ticket analysis to enhance customer success. By analyzing ticket data, organizations can better understand customer issues and improve their responses to support inquiries. This process helps address customer problems proactively, improving customer relationships and driving retention.

Get Ready to Analyze Your Help Desk Data

Now that you know what you should have included and focus on with your help desk ticket analysis, now what? Do you understand what to look for within those groups of data and what it might be telling you? Consider these points to interpret your reports and start improving your team’s efficiency.

Find Ticket Trends

Identifying ticket trends will probably be your top priority and the answer you receive from your help desk ticket analysis reports. At the end of the day, the best solution ticket trends may point to may be that you need to bring on a couple of new members to your team.

Maybe it’ll tell you that your team is doing an amazing job and deserves further recognition. Either way, you won’t know if you’re not looking and analyzing your help desk ticket analysis properly.

Improve Customer Support Strategies

By analyzing support tickets, businesses can identify areas of improvement in their customer support strategies. This might involve:

Identifying gaps in knowledge

Enhancing response times

Implementing self-service solutions

Improving communication channels

Taking proactive measures to address these issues can increase:

Customer satisfaction

Loyalty

Retention rates

Create Self-Help Documentation

Identifying and creating self-help documentation should be your next action step. While this may take additional effort from your team, it will be an upfront investment that will save your team plenty of time and effort almost immediately after. This could also be a great opportunity for you to collaborate with your marketing department to help put together insightful and effective documentation.

Automate Ticket Assignment

Automatic ticket assignment can be the next beast you tackle to help improve the flow of tickets and ensure everyone knows what they own. If you see natural groupings of ticket types coming in with team members who really shine with those, give them ownership.

Look at what you’re getting in and the strengths of those on your team. From there, figuring out an automated ticket assignment system may come naturally to roll out.

Let the Data Speak

Your data is ready to tell you something, you just have to be willing and know how to listen. Keep these five help desk KPIs in mind when building your help desk ticket analysis to start enhancing your team’s efficiency.

Streamlining Internal Operations with ChatBees

ChatBees optimizes RAG for internal operations like customer support, employee support, etc., with our AI customer support software. This software provides the most accurate response and easily integrates into workflows in a low-code, no-code manner. ChatBees' agentic framework automatically chooses the best strategy to improve the quality of responses for these use cases.

This improves predictability and accuracy, enabling these operations teams to handle more queries. No DevOps is required to deploy and maintain the service.

Start for free

Try our AI customer support software today to 10x your customer support operations. Get started for free, with no credit card required. Sign in with Google and get started on your journey with us today!

How Do You Do Support Ticket Analysis With AI?

AI tools take ticket analysis to the next level by automating the process, speeding up response times, and making support teams more efficient. Machine learning can analyze historical ticket data to identify trends that help organizations improve their support operations.

You may notice that a particular product is generating a lot of tickets. With this knowledge, you can investigate and resolve the issue before more customers become frustrated.

Classifying Support Tickets with AI

Ticket classification with AI relies on natural language processing (NLP) techniques to understand the raw text of a set of tickets. In the industry, this is called text analytics, and it’s what we specialize in at Keatext. By leveraging text analytics, it’s much smoother to sort tickets properly and get the right person to respond to them as quickly as possible.

That’s because you automatically access a few key things in each support ticket:

Topics (shipping, returns, technical support)

Sentiment (positive, neutral, negative, mixed)

Language (English, French, Spanish)

Urgency (low, moderate, or urgent priority)

Channel (social media, email, live chat)

For example, AI can detect when a customer needs technical support, signaling you to forward the ticket to the IT department. Likewise, it can pick up on negative sentiment to detect how urgent the complaint is, helping you prioritize which cases to attend to first.

The Benefits of Machine Learning for Ticket Analysis

Machine learning is an invaluable foundation for customer support ticket analysis thanks to its unparalleled capabilities: Scalability: Machines are much faster at processing hundreds or even thousands of support tickets, resulting in a significantly more scalable system than manually handling everything. You don’t have to bog down your team with tedious tasks even when the number of tickets goes up.

Consistency: Algorithms never tire and are impervious to bias. While manual sorting can introduce mistakes or inconsistent analyses, machine learning ensures a consistent performance at all times.

Real-time operation: Building on the scalability and speed aspects, machine learning is fast enough to forward support tickets to the right agents almost immediately, no matter the time of day, ensuring prompt responses to boost customer satisfaction.

Getting Started with AI Ticket Analysis Software

Thanks to third-party vendors of help desk data analysis services, implementing these cutting-edge technologies into your workflow is actually quite easy. Most providers will walk you through the process:

Upload sample data of various support tickets.

Define the categories you intend to use.

Train the AI by specifying the categories for each sample ticket.

Test the program by giving it brand new tickets and checking its performance.

Once ready, implement the system through API and other integration tools.

The Operational Benefits of AI Ticket Analysis

From an operational standpoint, ticket analysis with AI helps customer support teams better respond to customers quickly to prevent churn. But there’s more to the story: good ticket analysis goes beyond its functional role as an enablement tool and provides powerful insights about agent performance and customer experience.

Use Cases for Support Ticket Analysis

Support ticket analysis doesn't stop once customer complaints have been resolved. The information involved can still help support agents with their jobs in the future and improve the products and services offered by the company. When it comes to agent performance, businesses can leverage ticket analysis to:

Sort and analyze individual agents’ responses.

Monitor overall sentiment in agents’ responses to customers.

Analyze customers' sentiments to determine their satisfaction level when the ticket is closed.

Assess which topics agents are good at responding to, leading to a high customer satisfaction rate.

Support ticket analysis combines qualitative and quantitative data in a really useful way.

In the examples above, we can combine qualitative data from the text analysis, such as topics and sentiment, with quantitative data, such as customer satisfaction rates and ticket resolution.

Understanding the Voice of the Customer

Support ticket conversations obviously contain a wealth of information coming from customers. And with support tickets, it’s expected that this is all about issues that customers are facing. Analyzing this data at scale with AI allows you to see topics and trends that individual support agents may have noticed on their own but your company may not have realized the full scope of. For customer experience, businesses can leverage ticket analysis to:

Identify key issues mentioned by customers across the board.

Sort tickets by product to assess sentiment for individual products.

Prioritize urgent issues mentioned by customers.

See customer suggestions to improve products.

Support ticket analysis has immense potential to improve customer experience.

All it takes is full-scale analysis with AI to ensure that your business is not missing what customers are telling you as directly as possible in their attempts to resolve issues through your help desk.

22 Best Ticket Analysis Tools in 2024

1. ChatBees: Streamline Your Workflows with Chatbees and HubSpot

ChatBees optimizes RAG for internal operations like customer support, employee support, etc., with our AI customer support software, which has the most accurate response and easily integrates into their workflows in a low-code, no-code manner. ChatBees' agentic framework automatically chooses the best strategy to improve the quality of responses for these use cases.

This improves predictability and accuracy, enabling these operations teams to handle more queries. No DevOps is required to deploy and maintain the service.

Start for free

2. SentiSum: AI-Powered Support Ticket Analysis

SentiSum is a ticket analysis tool that uses AI to consume, understand, and deliver insights into your customer support conversations. We built the platform to be as easy-to-use as possible, so you can access detailed information into what customers without technical training.

How it works

Natural language processing analyzes every conversation. We apply granular tags on topics, subtopics, sentiment, and more. Our insights dashboard makes real-time root cause analyses simple. We use technologies like generative AI to summarize insights and answer questions you have.

3. Monkeylearn: Flexible AI Tool for Customer Support Analysis

MonkeyLearn is an AI tool built for sentiment analysis and text analytics in general. You can feed any text into the tool, including support tickets from any channel, and the software will analyze it. Given its wide range of potential applications, MonkeyLearn is a highly flexible tool (although, since it was acquired by Medallia, its focus has been on customer support analysis).

But to benefit from this flexibility, you’ll need to be prepared to commit the time to shape the tool to your use case. Unlike SentiSum, MonkeyLearn’s AI needs to be trained. You don’t need to be a software engineer to do this, as MonkeyLearn is proudly no-code for users. You must set custom tags and qualifiers, import your dataset, and more before you start.

4. Playvox Customer AI: Analyze Support Tickets to Improve Products

The workforce management company Playvox acquired Prodsight in 2022. What was previously a ticket analysis tool for product improvement insights is now known as Playvox Customer AI. While it aspires to be a comprehensive support analytics tool, its strengths remain in helping teams improve their products.

As such, Playvox focuses on what customers are saying about your products, whether they’re requesting new features or highlighting usability issues. Playvox will highlight these and deliver them to your product team, so they can make improvements.

5. Idiomatic: Easy-to-Use Customer Sentiment Analysis Tool

Idiomatic is designed to be incredibly easy to use. Like SentiSum, it doesn’t require you to train its AI or configure any settings before use. Instead, with the help of extensive natural language processing, it helps to make customer sentiment analysis as smooth as possible.

6. SupportLogic: Ticket Analysis Built for B2B Teams

SupportLogic is a customer support ticket analysis tool that’s built specifically for B2B teams. Like other tools in this list, SupportLogic will analyze your tickets from across multiple channels. But it won’t be able to handle B2C conversations.

That’s because SupportLogic’s AI was trained on B2B conversations, meaning it’s equipped only for these interactions. The tool’s system has features built largely for B2B teams, such as churn risk and escalation risk analysis.

Brandwatch is a well-known suite of tools for managing and analyzing social media. With Brandwatch, you can consolidate all your social media messages into one mailbox, manage influencers, and understand what people are saying about you.

If you just want to analyze your support tickets, though, you need Listen, the suite’s sentiment analysis tool. You can track brand mentions, analyze topics across customer messages, and track sentiment trends. The downside is that Brandwatch is only built to help you manage your social media. If your support team is also handling voice calls and emails, you’ll need another tool.

8. HubSpot Help Desk: A Customer-Focused Ticketing System

I love HubSpot because it unifies all of your customer data so that you can provide a 360-degree customer experience. When I use HubSpot, I have complete visibility into a customer’s history, past tickets, and which representative they have worked with before. Armed with a full customer timeline, I can provide personalized, empathetic support and fully understand the customer’s needs and challenges.

HubSpot’s Help Desk and Ticketing software are just pieces of the puzzle. You can also use its all-in-one customer service software to streamline all your service efforts from the same place. For example, you can gauge your team’s performance by monitoring metrics like average response times and close times. You can also deploy and manage feedback surveys and more.

Zoho Desk offers a widget tool that you can embed on your website. When loaded in a browser, the widget turns into a support form that customers can fill out to request assistance. They can describe their problem in detail and request a preferred communication channel. This makes it simple for customers to access your support team.

It also allows reps to easily analyze and find solutions for incoming requests, significantly improving first-call resolution rates and customer satisfaction. I also like their time-tracking feature, which records how much time you spend doing different things on each ticket. This gives you more insight into the hurdles a rep has to overcome to solve a specific issue.

10. Freshdesk: AI-Powered Ticketing Solution

Freshdesk is AI-powered help desk software from Freshworks designed for ticketing, ease of use, and rapid resolution of customer complaints. It improves customer support operations through seamless ticketing experiences and self-service options across various channels.

Freshdesk's AI-driven automation routes tickets intelligently, ensuring smooth collaboration among team members for swift and precise resolutions. With Freshworks' built-in AI engine, Freddy AI, Freshdesk enables agents to deliver outstanding service consistently, delighting customers every time.

11. Freshworks Customer Service Suite: Comprehensive Support Software

Freshworks Customer Service Suite is an AI-powered ticketing software known for its comprehensive and intuitive approach to managing customer interactions across multiple channels. It caters to businesses of all sizes, offering scalability and flexibility to grow with your company.

It simplifies the customer support process by centralizing emails, social media messages, live chat, and phone calls into a single, easy-to-manage platform. With its user-friendly interface and extensive customization options, Customer Service Suite makes it easy for businesses to set up a sophisticated customer support center without extensive technical expertise.

12. Help Scout: A Customer-Centric Approach to Support

Help Scout is a customer support platform that offers a shared inbox, help center, and live chat software to help manage customer communications efficiently.

13. Kayako: Customer Service Software for Agent Productivity

Kayako is a customer service software that enhances agent productivity and builds customer loyalty. By offering custom views, tags, and conversation assignments, support teams can better track open requests and assign conversations to the right reps.

14. HappyFox: Help Desk Software with Strong Multi-Channel Capabilities

HappyFox is a help desk software emphasizing multi-channel support for tickets arriving via:

Phone

Social media

It’s integrated with various business applications for accounting, feedback, CRM, commerce, and more.

15. Front: Customer Operations Software for Seamless Collaboration

Front is a customer operations platform that combines support and sales efforts to deliver sufficient service at scale. It optimizes customer communication by merging help desk and email capabilities with automated workflows and real-time collaboration for support agents.

16. ProProfs Help Desk: Cloud-Based Support Software

ProProfs Help Desk is a cloud-based support platform designed to help businesses build relationships with users. It provides a centralized dashboard, helping companies handle both internal and external requests more efficiently.

17. LiveAgent: Full-Featured Help Desk Software

LiveAgent is a full-featured help desk and live chat software designed to personalize customer interactions. It offers a capable chat widget while also providing an omnichannel universal inbox, built-in call center, and robust customer service portal.

18. Klipofolio: Ticket Analysis Visualization

The Ticket Analysis visualization summarizes the ticket types submitted to your help desk. Ticket categories may include ticket type, priority level, assigned agency, and ticket source. This analysis is designed to uncover trends behind ticket submissions. For example, if many tickets submitted are marked Questions, it may indicate the need to write an FAQ for your customers.

19. InvGate Service Desk: IT Support Software with a Friendly Interface

InvGate Service Desk is the all-in-one solution to streamline your IT operations. It's a centralized platform suitable for companies of all sizes and offers on-premise and cloud implementations. Its user-friendly interface not only improves end-user adoption rates but also helps reduce implementation time by allowing your agents to start working with it in no time and with very little training required.

20. ManageEngine: A Consistent Solution for IT Ticketing

ManageEngine provides a consistent solution for IT Service Management with key features such as:

Incident

Problem

Change

Asset

SLA management

Self-service features include a CMDB to manage configuration items, IT project management, and reporting.

21. Hornbill: Comprehensive Service Management Software

Hornbill is a comprehensive service management solution that streamlines IT and business processes.

22. TOPdesk: IT Service Management Software for Business Continuity

TOPdesk provides organizations with tools to manage their IT services effectively and ensure business continuity. TOPdesk software features:

Incident and Problem Management Change Management

Self-Service Portal

Reporting and analytics Integrations

7 Support Ticket Analysis & Reporting Best Practices

1. Define Goals for Your Support Ticket Analysis

Every help desk report uses different datasets and interprets the underlying data in various ways. Pulling reports for every metric and applying random filters will lead to more chaos than obtaining accurate information. To avoid this scenario, be sure of your report’s goals and know what questions you want to be answered with a specific help desk report.

Let’s say you want to look at the overall SLA performance of agents across different time zones. You can pull up the agent performance report and add a filter to group by time zones rather than individual agents. Being specific about your goal will help you select the right dataset and filters for your help desk report.

2. Identify Key Metrics for Ticket Analysis

This is another potential pitfall with having access to a wealth of rich data. Not all of the metrics and data you have will be relevant to your business at a given time, and trying to manage it all detracts from achieving your department’s goals. Is one of your goals to reduce ticket resolution time for high-priority tickets? Looking at the same data for low or medium-priority tickets isn’t relevant to that goal.

Applying the right filters within your report helps build more detailed reports by narrowing down the dataset most relevant to your helpdesk reporting use case. As a rule of thumb, if you can’t immediately identify how a performance indicator can be translated into action, it’s irrelevant to your current goals.

3. Remove Outliers from Your Help Desk Reports

Datasets, especially larger datasets, are prone to outliers. Outliers are data points that far exceed the normal distribution of the set, either as extremely high or low values. Outliers that appear consistently over a long period of time can indicate a problem, but if they’re new events, you should investigate the circumstances behind them before forming a plan of action to fix things.

Events that are unlikely to repeat themselves, such as multiple managers being off-site, are outliers. Isolate tickets that arise from outlier events from your reports as points of concern, but hold off on acting on them until you understand the situation behind them.

Encourage your agents to take ownership of the customer experience by giving them everything they need to thrive, including emotional support, a healthy work-life balance, and open communication about the department and team's goals. This means, among other things, not hiding your reports from your agents.

Give them the information they need to be actionable, and encourage a little healthy competition by showing them the benchmarks for your top agents. Consider incorporating a little gamification into the process. Not only does gamification break up the monotony of the day, but it may also be the key to successfully transforming operations practices.

5. Summarize Help Desk Reports for Executives

While your agents should have a transparent culture of communication, your executive, cross-departmental colleagues don’t need the nitty-gritty details. When you’re going over reports with other executives, focus on what’s imperative to the business at large. After all, what one metric means for you is vastly different from what it means to other departments.

Just like your own reports shouldn’t be overwhelming with unimportant metrics, the reports you compile for your top-level executives should be brief and to the point. Data that drives a point home does its job well; data that gets everyone lost in the weeds is best left off. A helpdesk suite with robust reporting abilities distills data into its simplest form using the art of good data visualization.

6. Set a Schedule for Pulling Help Desk Reports

Unless your business makes use of your help desk daily reports, it’s not necessary to pull them every day. In fact, viewing your reports daily may actually impede your progress rather than optimize it. Try to configure your regular reports on a schedule that’s both actionable and manageable.

Generating reports once a week is a good start. With Freshdesk, you can schedule reports on a recurring basis and email them to yourself or any of your team members at periodic intervals. You get real-time results and the ability to iterate on them quickly, but you don’t spend your day trying to tease out trends that may not be relevant in the long run.

7. Don’t Ignore Qualitative Data in Help Desk Reports

Numbers are impactful, reliable, and quantitative, and they allow you to highlight statistically significant trends. But they’re also incomplete without context and ‘softer’ data points. Customer experience isn’t limited to the time it takes to resolve a ticket or the average first response time; it’s about the whole interaction with your brand.

To improve their customer journey, you need to understand how customers feel. After all, what are customers more likely to remember, that their ticket was resolved in 7.2 hours or that the agent who resolved their ticket was friendly, patient, and went above and beyond? Both are important metrics, even if only one can be quantified.

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