The story of the typical support team
We’ve gathered a huge amount of data in recent times from our customers and it seems there’s a big problem in the support world. You have a huge challenge to tackle to deliver top quality support and we have found that the typical support team could save themselves 237 working days of reading a year.
But this sounds crazy, right? How could you be doing that much extra work a year? You’re definitely not trying to create more work for you and your team and it sure would be nice to get this time back. So let’s go through our findings and show you just what’s happening and what you can do about it.
200,000 Support Inquiries a Year
Based on our findings and the supporting data we’ve analysed from our customers the typical company has around 200,00 support inquiries a year from email, message and chat. That’s a lot of customer issues, comments and questions that you and your team need to field every year!
74 words long
Looking at support ticket length, we have found that the average support ticket that comes to your Helpdesk is 74 words long. This number looks only at the body of inquiries from customers, subtracting any auto messages, subject lines and signatures. It doesn’t sound like a lot but to put it into context for you, this paragraph doesn’t even make the cut at 66 words long.
What Makes Up Your Support Data
This all means that your support team gets 14.8 million words a year to read. All of those customer complaints and queries that you have to read, categorize and deal with. It’s what makes up your support data, all in the form of unstructured text that you have as tickets in your Helpdesk. Today the only way you have of helping customers is to read all of these tickets. And the only way to analyse this data is to manually tag it based on what you think the customer issue was.
Harry Potter 716 times!
To put this into more context for you, it takes 7.7 minutes to read 1000 words. Let’s assume you are able to do this and don’t have to open each 74-word ticket as you go, that would take you and your support team 113,960 minutes or 237.4 working days just to read them all! Never mind answering back and solving the issues. All this time could be much better spent watching Harry Potter and the Philosophers Stone 716 times in a row.
That is crazy! And there is no real way to get around this until you start implementing some form of artificial intelligence into your support. With natural language processing and AI, you can start leaving this work to machines.
8 tags for millions of customer issues
On top of all this, despite the millions of possible customer issues your team could have within all those tickets you field, we have found that the average support team uses just 8 tags to categorize all of these tickets. That means the totality of your ability to analyse your support data is reduced to just 8 categories of customer issues. That’s mad! How can you make any decisions based on actionable data to improve your customer’s experience and support, when you don’t yet have any data to base it off?
The catch 22
We have found in our data the reasons for low tag use comes down to a few key things, which we often call the catch 22. If you have lots of predefined tags in your Helpdesk, your agents will end up using their favourites or the ones that are at the top of the list. If you have too few, you have very little granularity on what your customers are calling about.
Artificial Intelligence to Save you 237 days
So what can you do about all this? How do you regain all this time spent reading support tickets? Today artificial intelligence has reached a point a pivotal point. It can understand unstructured text data with natural language processing and machine learning techniques. Our AI is able to read your support tickets. It understands customer intent and categorizes accordingly, no matter how they say it.
This means you are no longer left with 8 categories of customer issues for you to base your decisions off. The AI will automatically tag and categorize hundreds of issues in your support data.
It doesn’t stop there either. AI can automate a number of workflows for your team. With artificial intelligence, you can route tickets to the right team based on the customer’s issue in the support ticket. That means tickets talking about “refunds” “getting my cash back” “reimbursement” can all be automatically routed. Now they are correctly sent to the agent group in charge of processing refunds.
AI can also help in automating responses to common queries like order updates and password reset advice. You can remove unnecessary steps in the support process by asking customers for more information on their issues like order numbers before passing it on to a live agent. You can even prioritize tickets based on certain customer issues in times of stress.
For example, for ticket backlogs it allows you to get the most pressing customer issues answered first.
Improve Customer Satisfaction 29%
All of this decreases your support teams workload and gets your customers’ issues answered faster. But with AI you now also have a real support data set to answer your companies most burning questions. We have found the average support team improves overall customer satisfaction by 29%. Just by acting directly from insights found in their support data. You now know why your customers are calling in great detail. Now you can start to solve some of their recurring issues to make their customer experience even better.
By properly taking advantage of your support data using artificial intelligence, you save your team 237.4 days of reading. We could all use the extra time in work to get things done. Your customers’ needs are also better met now that you have data on why they are calling your support. You can start solving and fixing common customer issues based on hard numbers. It’s time to start utilizing this technology and harnessing the power of your support data.