Enable unprecedented levels of automation and agility with cloud computing solutions.
6 ways big data can save your help desk
Like it or not, your help desk is the public face of your company. It’s where your customers go to find answers to their most pressing questions.
That’s why finding ways to turn your company's help desk experience into a positive and engaging one is so important—and it’s part of the changes we’ll see big data bring to IT in the years ahead.
Today, most help desks organize and deliver information in a way that's rigid, unnatural, and often frustrating for customers. Frustrated customers are potentially bad news, of course, because they can form strong opinions about your company and share those opinions loudly on social media.
Big data tools let us create applications that engage with customers more naturally and produce results more quickly, with fewer escalations to (and failures in) the call center, and fewer angry Facebook and Twitter posts. These tools will soon make service desk interactions a little more human, and that’s an important development because your customers are humans and they generally prefer to interact with other humans—in strings of text or spoken words.
Big data tools store and interpret “human interaction data,” such as text, video, or voice recordings. These data snippets can be analyzed for such metrics as sentiment, meaning, or common themes. The results boost the ability of the help desk to quickly identify potential solutions.
So the trick for businesses is to find ways to deliver what IT guru Geoffrey Moore calls “systems of engagement” that humans can approach … as humans. Here are six ways big data will soon allow your help desk to deliver a more engaging customer experience.
1. Smarter conversations
As one of your help desk agents chats with a customer, a big data system will interpret the conversation and search for relevant information to display to the agent. This information should help the agent provide swift and informed responses to the customer’s questions.
2. Image recognition
Imagine that an application crashes on your customer's PC. The customer can use a mobile app to take a picture of the error message on their screen and send it to the IT service desk system. Analytics tools would use optical character recognition to understand the image and automatically categorize the incident. This makes case entry much easier for both customers and help desk agents.
3. Search made easy
When your customers are searching for answers to their questions on your website, they will get frustrated if the information is not readily available. But if you feed your customers’ search requests into an analytics tool that leverages big data, it will provide all the keywords your help desk needs to search for. This will give your help desk Google-like search flexibility.
4. Automatic clustering of search topics
Big data analytics tools can automatically cluster topics people search for on your help site. You’ll then see which topics are well served by your help system and which ones need to be augmented. If you’re an insurer, for example, you might see lots of searches related to filing claims while abroad and notice your help topics really don’t serve that topic very well. If that’s the case, you'll know where to make improvements.
5. Identifying problem areas
The IT standard for service management calls for incidents to be grouped into "problems." There may be hundreds of open incidents that relate to a single problem: for example, issues with the company’s VPN system, which can be solved by increasing VPN capacity.
While it’s difficult, costly, and time-consuming for humans to go through hundreds or thousands of incidents, an advanced analytics tool could automatically understand and cluster these incidents. Service desk agents could view each cluster later to decide whether to create a problem. The swift approach of using big data tools to assist in incident-to-problem clustering can be applied to any help desk situation.
6. Monitoring customer sentiment
Big data tools allow you to monitor a whole series of social media sources, including Facebook and Twitter. You can look for clustering of conversations (lots of people are talking about making insurance claims when traveling abroad), or you can monitor sentiment (people are very frustrated about how difficult it is to make these claims, and the frustration is increasing). You can then respond quickly to the customer feedback.
For example, my daughter recently faced a severe delay on her train journey returning home from the university she attends. She tweeted her frustration using the hashtag for the rail operator. To her amazement, she was tweeted by someone from the rail operator who apologized for the delay and suggested an alternative route for her trip. No delay would have been best, of course, but she was impressed that social media was being monitored—and that helpful actions were being taken.
An analytic approach to customer service
The consequence of a poor help desk experience can be a storm of negative publicity as frustrated customers turn to social media to vent their anger. After all, the help desk is not always the first place customers turn to when they want to vent their frustrations—in fact, it’s often the last resort.
That could be changing thanks to the increasing ability of big data analytics tools to understand human interaction, allowing us to make our help desks more customer-friendly and more responsive to the needs of our users—who are increasingly satisfied with nothing less.
Big data and the help desk: Lessons for leaders
- Use big data tools to engage your customers naturally.
- Improve your help desk’s search function to minimize customer frustration.
- Monitor social media and respond quickly to customer feedback.
This article/content was written by the individual writer identified and does not necessarily reflect the view of Hewlett Packard Enterprise Company.