Support tickets are the foundation for customer support in the sense that for for almost everything within the confines of support, tickets become the structural basis on which customers and support agents communicate. The process of ‘raising tickets’ is practiced by every company that offers a service or product, with a lot of them relying on tools like Zendesk and Freshdesk to manage and control these tickets that are raised by customers and automatically assigned to the right agent. Tickets are also the basis for determining or understanding the efficaciousness of support, on in other words, measuring certain KPIs like First Response Time, Average Handling Time, Resolution Time, etc.
But ticket volume can be overwhelming and for various reasons as well - you might have alot of customers, a new feature just went out that people don’t understand, your product is complex, the customer support team is small hence each have more tickets to solve, etc. Whatever the reason might be, higher ticket volume can lead to friction and deteriorating customer support performance through late resolutions, more back-and-forth, and of course, one of the most pressing concerns in customer support, employee burnout.
As we mentioned already, higher ticket volumes can result in lower customer satisfaction and higher employee attrition. Both absolutely unfavourable conditions for a company. Adding on to this is the factor of repeat tickets. What are these? Repeat tickets are concerns raised by customers that have been raised before. And this is quite obvious because multiple customers or users can have the same concern. This isn’t their problem. But it is a major problem for your team because the amount of time spent on resolving the same queries again and again is not only an inefficient way of working but also adds on to the frustration of already burnt out employees.
You don’t want your support team to spend their significant time answering basic questions like "How do I reset my password?" or "Where can I find the x tab?". Self-serve is becoming prominent with AI and so is the expectation of customers to reduce human touchpoints. Support chatbots have become the go-to solution for most support teams and chatbots really do prove to be sufficient when it comes to solving queries that are most likely to be repeated. A chatbot can instantly pull up relevant answers from your help center or self-service portal to resolve customer inquiries.
Furthermore, these self-service bots can be programmed or automated to route queries to a support agent if the bot isn’t able to answer or in the case if the customer wants specifically to speak to an agent.
Customers usually don’t prefer having to speak to support agents unless it’s absolutely necessary. Which is why they would always prefer self-help options before anything else. If you have a discoverable knowledge base which is easy to navigate and find specific answers, you can see a huge decrease in repeat tickets and as a result more time for agents to focus on important tickets.
A great way to create an extensive FAQ section is by paying attention to these repeat queries - what are some of the most commonly asked questions? What’s equally important is to focus on how these questions are being asked. You can use that to answer the questions how they’ve been asked which improves the discoverability factor for customers and they don’t have to spend a lot of time trying to find the answers.
Usually one of the biggest reasons for larger ticket volume and, even more so, larger repeat ticket volume is unfamiliarity with the product or new features of the product. From a customer support standpoint, you should be deliberate in providing feature updates or even host workshops if necessary to help customers understand how the product works. Make it as obvious as you can and leave nothing to assumptions when it comes to explaining features. If your customers understand the product inside out, there are very few chances of trivial tickets being raised, which will in turn reduce repeat ticket volume.
Analyzing ticket trends is an indirect way of speaking to customers. You can monitor patterns or trends to see what are customers talking about or raising tickets for recently. Learnings from here can help you prioritize which areas of the product or feature need improvement. A part of reducing repeat ticket volume is to also change features that might be leading to repeat tickets.
Factors that we discussed already like providing self-service options, creating an extensive knowledge base, and monitoring or analyzing ticket trends can be solved with Threado AI. How Threado AI makes any of this possible is by getting trained on your knowledge bases and it can be installed within the product or as an embed where customers can ask questions.
Once you’ve signed up for Threado AI, you can train the bot on multiple data sources including URLs, PDFs, tabular data through CSVs, customer conversations, support tickets, and more.
After you’ve trained Threado AI, you can first test it yourself, and then install it across channels where your customers can use it as part of a self-serve option.
You can install the bot as a web chat on your website, within the product, or on Slack. Your customers will be able to access the bot wherever it’s installed and ask questions. Depending on how well your knowledge base has been maintained or how detailed it is, Threado AI can answer most concerns without needing customers to have to speak to agents.
You can analyze Threado AI’s performance and see which queries was it not able to answer. Unanswered queries mean those questions were not resolved and that can be identified as a gap in the knowledge base. The same can be said for answers that were downvoted which means that the answer was either incorrect or incomplete.
Threado AI also gives you the questions that the bot wasn’t able to answer and are flagged as ‘Open’ conversations. You can directly navigate to these conversations and keep a close eye on these questions. From here, you can also see the answers that have been downvoted and understand what might be wrong with the answer.
Once you’ve identified these gaps, you can upgrade the knowledge base to become with FAQs and answer these questions, not just from the perspective that the bot will be able to answer these but also from a discoverability standpoint so your customers are able to find these answers directly from the help center.
Your support side-kick
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