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The big-data-powered Social Help Desk : because humans don’t interact in structured records


Sadly, we are not judged on our performance during normal operations. It’s when something goes wrong that our customers form their strongest opinions of us—and switch to our competition, and condemn us loudly via social media. Interactions with a help desk, whether it’s an IT service desk, a tax agency’s, or an insurance company’s, are vital to success. That’s why finding ways to turn the help desk experience into a positive, and engaging, one is so important.


A key challenge is that the help desk is approached by humans, who like to interact like humans—in strings of text or spoken words. Yet our help desks organize and deliver information in structured records, creating a rigid, unnatural, and often frustrating experience for the user. No one wants to conform to an artificial system of record. Businesses will have to find ways to deliver what IT guru Geoffrey Moore calls “systems of engagement,” which humans can approach … as humans.

 help desk.png

Moving forward, augment our help desks with the Big Data analytics tools that understand speech, text, and pictures, allowing us to create applications that engage with people more naturally, and produce results more quickly, with fewer escalations to the call center (and fewer failures there), and fewer angry Facebook posts.


Let’s look at the ways your analytics evolution will let your help desk deliver a more engaging experience.


How Big Data can turn your help desk into a "social help desk"


1. Auto-augmenting a conversation with relevant information

As your help desk agent chats with a customer, the Big Data system will interpret the conversation, understanding what you are talking about. It will then search for relevant information and display it to the help desk agent. 




2. Automatic analysis of help desk interactions

Voice analysis technology is now at the point where it can not just automatically recognize speech, but also, understand what is talked about. Is the customer happy? Is the customer ready to quit (“churn” as it’s often known). We can automatically churn thru hours of customer interaction looking for the good, the bad, and the ugly.


3. Easy, forgiving searches

It is frustrating for customers that they have to know exactly how you have arranged the information in your help desk—the knowledge articles, known problems and the like.




 So, give customers’ search strings to a smarter analytics tool and it will give back all the different keywords your help desk needs to search for.


For example, you may have knowledge articles on making claims abroad. These could match “sorting problems on holiday” or “money stolen when travelling”.


4. Automatic clustering of search topics

Big Data analytics tools can automatically cluster the topics people search for on your help system. You’ll then see which topics are well served by your help system, and which need to be augmented. You might determine that there are lots of searches of your insurance help system regarding making claims while abroad, but that your help topics really don’t serve that topic very well.


In other words, “auto-clustering” of search topics allows you to produce a better help system.




5. Automatic clustering of calls into problem areas

The IT standard for service management, ITIL, calls for incidents to be grouped into problems. For example, there may be hundreds of open incidents that relate to issues with the company’s VPN. These would then result in a problem being raised, perhaps calling for an increase in the capacity of the VPN system. While it’s difficult, or slow and costly, for humans to go through hundreds or thousands of incidents, an advanced analytics tool can automatically understand and cluster the incidents. Service desk agents can then view each cluster to decide whether to create a problem.


The use of Big Data tools to assist in incident-to-problem clustering is not unique to IT service desks—it can be applied to any help desk situation. Once problem clusters have been identified, business processes can be adjusted and/or user documentation and help can be upgraded.


Not only is this “incident to common problem” clustering important for help desks, it’s also very important for product management too. If they see a common problem, or opportunity, then they can create new products and product bundles or enhance existing products. [Example for insurance help desk → lots of incidents with claims from abroad → this is a generic problem]


6. Clustering and sentiment analysis of community activity “out there"

The prevalence of social media means that your help desk is just the tip of the iceberg when it comes to customer dissatisfaction. My daughter recently faced a severe delay on her train journey returning home from university. She tweeted her frustration, including the name of the rail operator in her tweet. To her amazement, she was immediately tweeted by someone from the rail operator apologizing and offering an alternative routing for her trip. A lack of delay would have been best, but she was impressed that social media was being monitored—and helpful information was given.



(Image : Silcon Prairie News)


Big Data tools allow you to monitor a whole series of social media sources, including, of course, Twitter. You can look for clustering of conversations (“Lots of people are talking about making insurance claims when travelling abroad.”). You can then monitor sentiment (“People are very frustrated at how difficult it is to make these claims, and the frustration is increasing.”).



Humans interact in spoken word, in text strings and with pictures. And it’s not always the help desk that they turn to when they want to vent their frustrations—in fact, the help desk is typically a last resort.


The increasing ability of Big Data analytics tools to understand human interaction allows us to make our help desks more customer-friendly and more proactive to the needs of our users—who are increasingly satisfied with nothing less.


And, our ability to monitor social media interactions allows us to be more proactive – we don’t wait until someone contacts our help desk before starting to address a problem. After all, common issues with our product or service can very quickly spiral out of control in the world of social media.


Want more ?

For more information on HP Big Data, please go to and/or look at my Big Data page.

Mike Shaw
Director Strategic Marketing

linkedin.gifMike Shaw

About the Author


Mike has been with HPE for 30 years. Half of that time was in research and development, mainly as an architect. The other 15 years has been spent in product management, product marketing, and now, strategic marketing. .


 A great post to help highlight how Big Data can transform the Help Desk.

Philip Randles

Despite all the technologies in use across all the service desks I have ever contacted, it is always the human ability to locate seperate pieces of disparate information and form a logical conclusion as to root cause or it being part of a larger problem.

Software like the above will allo greater maturity of any service desk using such products, in that a lot of the work and evaluation is done for them. This is especially useful in the example of above, where self help can be rapdidly delivered to the enduser by the support of such systems.

Robert Kern

I like the concept of clustering actual incidents - showing you areas where you could turn your attention on, in case of problem creation. Like to see that in action, its sounds to be most helpful. Getting this actual picture without some intelligent analytics currently is kind of difficult - so thumbs up!

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