Whether you regularly receive thousands or only just a handful of daily customer support tickets, how you handle ticket management can be one of the most consequential things your business does.
You have to process them fast, of course. But just closing them out isn’t sufficient, if you’re not completely solving your customers’ issues. Or, even if you’re solving your customers’ issues, but they don’t leave the interaction significantly happier than they entered it, you can still have problems.
You need to make sure your customer support team is proactively solving issues – preemptively uncovering problems before they ever hit their inbox, properly onboarding new customers, and pacifying agitated ones, all while tickets stack up behind them.
But how can you understand overall ticket management and the minute details, without having to manually read through every support ticket? Implementing a ticket management system with AI software might just be the answer you’re looking for.
Not only can it help expedite and improve your customer service, but ticket data analysis augmented with machine learning tools can extract other powerful insights from customer data, to improve your products and services and grow your overall business.
A ticket management system is software and/or a network of processes used to organize and route customer service tickets, facilitate customer support, and extract and analyze customer feedback data to improve products and services.
A ticket management system is an integrated help desk that streamlines processes and draws customer feedback and customer support communications into a single channel, to better improve internal and external communication.
While ticket management systems still require mainly manual processes – tagging, routing, etc. – they can be huge time savers by consolidating information and collecting and storing data for future use.
Ticket management systems make handling customer issues easier by:
At their core, ticket management systems are interactive tools that organize information, alert employees of work that needs to be done, and provide real-time status updates regarding completed actions.
While every business that handles more than just a handful of customer tickets a day should consider a ticket management system to save time and money, when you integrate AI tools with your ticket management system, you’ll be able automate processes even more and analyze your ticket data for actionable insights to improve your products and your business.
When you leverage AI tools, like MonkeyLearn, to work in concert with your ticket management system, you’ll be able to:
Integrating machine learning AI tools can improve and streamline internal processes, so urgent issues get handled first, and you can always be sure that your customers are getting the best service possible.
SaaS text analysis tools, like MonkeyLearn, can do this automatically to save time and money and perform much more accurately than human analysis.
Take a look at this pre-trained survey feedback classifier, for example. It’s designed to automatically sort and tag survey responses into the categories, Features, Pricing, Ease of Use, and Customer Support:
The above is an example of topic analysis, a technique that can automatically tag tickets according to predetermined subjects or aspects. Topic classifiers can be trained to classify customer service tickets and automatically route them to the correct department or employee, like in the below:
Urgency detection is another example of machine learning that uses sentiment analysis to automatically tag incoming tickets as Urgent or Not Urgent:
Once your AI text analysis tools are integrated with your ticket management system, you’ll not only improve processes, but you’ll be collecting a constant stream of data that you can analyze for powerful insights. Ticket data analysis allows you to uncover recurring issues, so you can quickly implement changes.
There might be a simple bug to fix, but it was never called to your attention because you have dozens of customer service agents each only receiving a handful of complaints on the issue. Implementing a ticket management system with AI will even allow you to collect data on customers and customize their individual experiences.
Furthermore, when you collect and analyze customer support feedback, you can combine this data with customer feedback results from NPS survey analysis, social listening techniques, and more. Ticket management system analysis is a holistic approach to improving your overall customer support and using the resulting data to improve your business and your bottom line.
Let’s take a look at what machine learning can do to set up your ticket management system and automate your ticket data analysis.
It used to be that you’d have to analyze your support tickets manually to know what department to route them to, understand how well your staff was handling them, calculate response times, etc. It’s a tedious and repetitive task that often leads to mistakes from boredom or inherent human bias.
Much of the useful data in your customer tickets is qualitative, meaning it has more information to offer. This is data that can unlock the opinions and feelings of your customers – to really dig into the customer experience. However, qualitative data is unstructured data, so it’s much harder to analyze.
And that’s where artificial intelligence comes in. MonkeyLearn is a SaaS machine learning text analysis platform that makes it easy to set up your own ticket management system and constantly analyze your support tickets for actionable insights, 24/7 and in real time.
Take a look at this pre-trained sentiment analysis model put to work on our comment from above. It automatically analyzes tickets for opinion polarity (positive, neutral, negative, and beyond):
Now, when we join sentiment analysis with topic/aspect analysis, we get aspect-based sentiment analysis:
The aspect or category “Ease of Use” is “Negative.” This can be put to work on your customer tickets to route the most urgent directly to the correct department and follow which aspects of your business or customer support are particularly positive and which are negative.
MonkeyLearn’s suite of text analysis tools can be specifically trained to the language and criteria of your industry and your business, so you end up with a custom-built ticket management system and analysis designed just for your needs.
MonkeyLearn’s direct integrations with Zendesk, Freshdesk, and other customer support ticket systems allow you to funnel your tickets and data through MonkeyLearn to run your analyses 24/7– and automate processes, so you save even more time. Take a look at this post to learn how to integrate Zendesk and MonkeyLearn in just four steps.
Ticket data analysis is clearly a useful tool for any business, to automate processes, decrease response times, and extract valuable customer insights.
With MonkeyLearn you can custom-train dozens of text analysis tools, usually in just a few steps, and have them work in concert for super fine-grained results. Furthermore, integrations with tools you already use, like Zapier, Zendesk, SurveyMonkey, Google, Excel, and more, mean you’ll spend less time moving from application to application to get the analysis you need.
February 19th, 2021