Why tagging customer support tickets is important?

Tags play a crucial role in all aspects of the customer support process. They represent the taxonomy that covers the problem space. As teams use them to describe objects, categories, situations, and emotions, they are the main available feature to sort, categorize, and route incoming tickets to the right agent. Besides, tagging customer support tickets is a fundamental ingredient to map a clear view of the customers as well as of the support team.

Tagging is very useful.

Support teams harness tags in uncountable ways: ticket search, trend analysis, and customer understanding are amongst the most frequent use cases. Team managers, on the other hand, consider tagging as the main piece of data for analytics and reporting. Very common use cases include identifying superstars and analyzing tag distribution among tickets as a means to balance the support team load. For instance, if 50% of the tickets are tagged as “shipping issues” while only 20% of the team are dealing with shipping related tickets, the support manager can rethink the team partition to make it more fair and efficient.

More in-depth analysis of the support tags should inevitably encompass customer understanding: What are the most frequent issues? What are the most formulated requests? What are the most buggy products or services? Such a tag-based analysis has the potential to give a ton of insights that any support team needs all the time to improve the overall customer experience.

Manual tagging is time-consuming

While the value of tags is indisputable, tagging is a tough task that can consume agents valuable time, and could even be a full-time job for some teams. And since a support team’s priority is to deal with customer requests, they generally turn a blind eye to adding the right tags to tickets or, at best, do it poorly.

Zendesk Support automates ticket tagging

That’s why the majority of CRMs and Support management systems integrate one or another form of automatic tagging. Zendesk implements keyword-based automatic tagging that works by identifying one or some keywords to add a tag. This automation offers great help in many situations, especially when the tickets deal with technical issues and the existence of technical key terms can make the job and relieve the team from manual work.

Keyword-based tagging works by processing the ticket and comparing the words in the text with the chosen keywords. The top found matches are added to the ticket as tags. For example, if you receive the ticket “I didn’t get my TV, I think there is a shipping issue with my order”, Zendesk will identify the word “shipping” so the tag “shipping” will be applied. By using simple business rules, the ticket can be routed accordingly.

Keyword-based tagging is insufficient

Let’s assume we’ve got a new message “I’m in a black mood waiting for my order, the delivery is so far behind schedule”. The content is different from the first one, but obviously, it has the same meaning. It will be hard for the automatic tagger to identify the “shipping” tag and thus to understand the customer request, simply because it scans only the words that have the same form as the tag you predefined. But it can’t guess any other combinations of words having the same meaning. It seems evident here that keyword-based automatic tagging hits its limits. But, it remains perfectly suitable for identifying technical-related words, though. Advanced AI can be leveraged to go beyond using keywords for tagging customer support tickets.