I had an information interview with a colleague at a local software company the other day to discuss managing social media channels for technical support. When we first setup the meeting, he wrote me about a ‘channel management problem’:
“We used to put all of our documentation in user guides for each
product. FAQs and troubleshooting guides would be included in these
and updated with each release. If a user had a problem they would
contact us via email for support.”
“Now we have several channels for support and documentation. People can still consult the product documentation, but will often find other useful information (some not covered in the product user guide) in online forums, blog posts, wikis, email lists etc.”
“We’re now finding a lot of people asking for support (indirectly) in
blog posts, blog comments and tweets. This is really hard to manage.”
“For example, we constantly monitor Twitter for @company messages and tweets that mention us or our products. Once or twice a day we’ll find that someone has asked a question about one of our products or complained about it. This can difficult because the answer may be too lengthy for a tweet, or too awkward (e.g. a bug has been found) to respond to publicly. For those cases, we try to direct the tweeter to our product forums or email support.”
When we met, he mentioned that they’ve recently started using a twitter productivity tool that helps them manage tweets from various users at the company. But some challenges remain:
- How do you respond to tweets in other languages?
- How do you use a URL shortener (like bit.ly) to track traffic to a support resource?
- Is it useful to monitor traffic from social media channels separately?
- Is it worthwhile to implement a redditt/digg mechanisim on the support portal to get crowds to identify popular support posts?
- What do analytics reveal about documentation usage on the support site?
I’ve certainly used web analytics software on support sites to get a general sense of what topics/areas of the product are causing issues. And capturing most popular search terms can certainly tell you where users struggle.