AI-Powered Support Ticket Analysis

SentiSum integrates directly with your help desk to provide accurate, granular analytics on every support conversation.

Know exactly what issues are driving sentiment & friction. And have quantitative evidence to make change happen.

✔ All support channels  ✔ Even speech ✔ And CX feedback

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What is Support Ticket Analysis?

Accurate. Granular. Fast.

Sentisum uses the latest advances in natural language processing to analyze your calls, chats, emails, and survey results.

It doesn't tag tickets like a human. We're slow and make mistakes.

Our AI is the opposite, even at huge scales it understands the nuances of complex speech and text.

You'll have detailed tags and trend analytics on the drivers of sentiment—whatever the support channel.

About our Tech

Truly actionable ticket analysis for help desks

Deeply understand your customers with support ticket sentiment & topic trends

Sentisum analyzes support ticket topics and their sentiment, so you know exactly what's driving customer experience.

You'll also understand the connection between reasons for contact and CSAT and NPS scores—giving you a deep understanding of your customers.

Ask any question you want and get answers based on your support tickets.

Say goodbye to manually digging through data or waiting on ad-hoc reports. Get quick, meaningful answers about your customer experience with SentiSum. It's as easy as asking a question.

With the addition of speech analytics, you'll even be able to search and query your phone calls.

Get 'reasons for contact' trends in your inbox

Build transparency across your organisation with Daily Digests—trending topics, intents and sentiments delivered daily. Stay in-the-know and be alerted to rising issues.

Bring all your feedback channels together

We integrate with all your customer conversation channels—voice, surveys, reviews and social media comments included.

By democratizing these insights in one, easy-to-use place, you make it easy for your organisation to make better, customer-centric decisions.

Why replace your existing tagging system?

Most tagging systems take a lot of manual analysis work to get insights you trust. Usually tags are inaccurate, inconsistent or generic, so customer support insights remain siloed.

Before SentiSum

• Tags are broad and require manual digging.

•Tags become outdated so insight is missed

•Tags are based on 'keywords' = inaccurate

•Tags are applied inconsistently by agents

•Reporting is still time-consuming

After SentiSum

• Tags are granular and get to the heart of the issue.

• Tag taxonomies are continuously up-to-date

• Tagging is machine-learning based = accurate

• Tags are applied consistently to 100% of your tickets

• Reporting is made simple with automation

• Tags can be trusted to guide triggers, automations and company-wide improvements

Don't take our word for it

We're proud to be working with these incredible companies, empowering them with actionable insights from their support channels

"SentiSum is easy to set up and the insights are accurate. Every team has started using customer conversation insights!"

Customer story

Joe Quinlivan

Head of Customer Care

“With SentiSum you go in, you open it up, and you see the stories being told to you. You see an increase in a particular topic and immediately understand why."

Customer story

Nick Moreton

Director of customer support

"We're very impressed by the technology itself, but even more so by the relentless effort the team puts in to support our specific use case."

Customer story

Johannes Ganter

Head of CRM & Digital

View all customer stories

Support Ticket Analysis FAQs

What is Support Ticket Analysis?

Support ticket analysis starts with ticket classification. Ticket classification refers to the process of categorizing customer support requests (tickets) based on their content, purpose, or issue type.

An accurate, useful classification involves sorting tickets into categories based on their topic, for example "refund requested", "delivery issue", or "food arrived mouldy", or their sentiment, for example "positive", "netural" or "negative".

The primary goals of support ticket classification include:

  1. Improving Response Times: By accurately classifying tickets, support teams can route them to the most appropriate department or support agent who is best equipped to handle the specific issue. This helps in reducing the time it takes to respond to and resolve customer issues.
  2. Improving Customer Servicev Outcomes: Classification allows for more personalized and effective responses to customer inquiries, as it ensures that the right expertise is applied to each query.
  3. Resource Allocation: By understanding the types of support requests being received, organizations can better allocate their resources, ensuring that areas with higher demand have adequate support staff.
  4. Identifying CX Trends and Issues: Classification can help in identifying trends and recurring issues, which can inform product improvements, training needs, and customer service strategies.
  5. Automation and Prioritization: Most support ticket systems can sort tickets by tags, which can also help in prioritizing urgent or high-priority issues.

The process of support ticket classification can be manual, with staff members reading and categorizing each ticket, or automated, using natural language processing (NLP) and AI algorithms that analyze the support request and categorize it.

At SentiSum, we put the power of automated support ticket analysis in your hands. Using the latest developments in artificial intelligence, and our easy-to-use platform, you'll have access to high quality tags & insights at your fingertips.

Why is an AI-powered support ticket analysis tool worth it?

Human beings are excellent at two things: (1) Tasks that require creativity and (2) tasks that require empathy.

And, we're also not good at two things: repetitive, boring tasks and tasks that require speed of processing.

But lucky us, AI is the complete opposite.

AI can categorize 100,000 support tickets in minutes and make sure those categories apply exactly the same way to each ticket. Amazing, right? That would take us forever.

Here's three parts of support ticket analysis that AI excels at:

  1. Handling High Volumes: AI excels at processing vast numbers of support tickets efficiently. This capability allows your system to manage an increasing volume of inquiries without overwhelming your team. The need for additional staffing is reduced, even as customer interactions grow.
  2. Uniform Application: AI operates without fatigue or personal biases, ensuring a level of consistency in analysis that manual processing can't guarantee. Human error or variability in performance, often seen with manual reviews, is significantly minimized, ensuring every ticket is treated with uniform attention and accuracy.
  3. Immediate Processing: Leveraging its rapid processing capabilities, AI ensures that support tickets are promptly assigned to the appropriate agents. This swift action facilitates near-instantaneous responses, regardless of the volume of incoming tickets or the time they are received, greatly enhancing customer satisfaction through timely support.

And an added bonus? Nobody on your team gets bored out of their mind tagging support tickets all day.

How to do a support ticket analysis yourself?

We wrote about how to manually analyze support tickets in detail in our guide on Support Driven Growth.

There are four key steps:

1/ Collate your feedback data

Collect it in our free template here.

2/ Decide on your taxonomy

Categorising feedback isn’t always easy. Choose topics that are granular enough to be insightful but high level enough that you can draw out similarities. When dealing with high volumes of unstructured free text (such as customer support ticket logs) you’ll want to create both high-level themes and more granular sub-categories.

We have a complete guide to creating help desk ticket categories here.

3/ Start tagging your tickets

Add your tickets and categories to the spreadsheet. We suggest one person tags all the tickets to ensure objectivity—two people may interpret the same piece of text differently, categorising it differently.

4/ Look for patterns and share insights

Apply filters to your spreadsheet to reveal which topics are mentioned in the highest volumes, and send the data off to the relevant team. The popularity of the theme and category can be a clear indicator of what needs prioritisation.

It's worth noting that we'd only recommend doing a manual support ticket analysis if you have a handful of tickets each month. Otherwise your insights will quickly become biased and non-useful.

What does a ticket analysis report look like?

We built our ticket analysis reporting to be simple and sharable. The more eyeballs the better for encouraging teams across your company to improve customer experience.

In this FAQ, I'll show you several examples of our analysis reports at SentiSum.

1. Our ticket analysis reporting dashboard for voice calls:

SentiSum's call center voice analytics software highlights

2. Our customer support ticket analysis dashboard:

3. Our daily summary email that highlights key trends in your support conversation topics

Do you also analyze support voice calls?

Yes, we do. Alongside granular CX insights, our voice call analysis feature also analyzes agent performance and summarizes feedback for the agent on every single call. Our customers love using it to accelerate and improve quality assurance.

All your channels under one roof

SentiSum is a single source of truth. In one simple-to-use dashboard, you'll understand the topic and sentiment of every customer conversation, survey and review.

Explore integrations

What you can do with SentiSum

Automated tagging engine

Extract granular, actionable insight from customer conversations.

Learn more

Auto-prioritisation and triage

Route and prioritise tickets based on their topic and sentiment.

Learn more

Monitor reviews & social comments

Automatically turn angry reviews or social comments into tickets.

Learn more

Survey data analysis

Understand the topic and sentiment of 100% of CSAT & NPS surveys.

Learn more

Try SentiSum today

Democratise voice of the customer insights across your company

Free 2-week trial

Better, faster CX decisions. All thanks to support ticket analytics.

SentiSum's AI categorises your conversations with detailed topic, intent and sentiment tags.

Accelerate your decision-making with readily available root cause support insights for every meeting, CX project, or training session.

Customer support ticket analytics and insights using AI automation

SentiSum tags tickets with unparalleled accuracy and granularity

Democratise actionable insights from every conversation channel

A daily email full of customer insights

Get 'reasons for contact' trends in your inbox

Build transparency across your organisation with Daily Digests—trending topics, intents and sentiments delivered daily. Stay in-the-know and be alerted to rising issues.

Make support tickets searchable

Like Google for your support data, you'll be able to answer queries from other departments by simply searching any keyword or topic.

With the addition of our voice analytics technology, you'll even be able to search for terms within phone calls.

Search bar image for showing how support tickets become searchable
Customer insights single source of truth

Bring all your feedback channels together

We integrate with all your customer conversation channels—voice included—as well as surveys, reviews and social media comments.

By democratising these insights in one, easy-to-use place, you make it easy for your organisation to make better, customer-centric decisions.