A practical introduction to Web analytics for technical communicators

What analytics parameters do you rely on to track the performance of your technical content?

At the STC India Conference earlier this month; my colleague, Vikrant Rai, and I presented a session that discussed some key content-related parameters. Here is the slidedeck:

Localizing Images: Cultural Aspects and Visual Metaphors

In May 2011, I had the opportunity to deliver a session titled Localizing Images: Cultural Aspects and Visual Metaphors at the STC Technical Communication Summit in Sacramento, California. It was a great experience speaking on this topic to a predominantly American audience, since there was cultural exchange happening right from the word Go.

A variation of the session was also accepted on the program for the 2011 STC India Conference. I was looking forward to traveling to Chennai to present the session on December 3. Unfortunately, a middle ear infection played spoilsport and the doctor forbade me from flying for at least a couple of weeks. My colleague, Nandini Gupta, then graciously agreed to present the session on my behalf.

A slide deck for the session is embedded below:

Localizing Images: Cultural Aspects and Visual Metaphors

You can download an audio recording of my session at the STC Summit from this link (~9 MB). The recording should be used in conjunction with the slide deck.
There’s more! The paper (accompanying this session) published in the Proceedings of the conference is embedded below. Happy reading!

Localizing Images: Cultural Aspects and Visual Metaphors

Join me at STC Summit 2011

I’m excited to share that I’ll be part of STC Summit 2011, presenting the following two sessions:

A session summary for the second session is available from the STC Learning Center. If you want to read it right away, download the PDF from this URL.

I look forward to meeting you at the Summit!

RoboHelp Server: An introduction

As technical communicators, one of our key responsibilities is to optimize the value of the user-assistance content that we deliver. What defines the value of content? I focus on the following key indicators:

  • The topics should be search-optimized and populated with the right keywords. Users should be able to reach the right topics when they search using the relevant keywords (if not close to relevant keywords!).
  • Once users reach a topic, they should be able to quickly find answers to the most pertinent questions that they have in that product area.
  • Based on the Web traffic details for a topic, key documentation areas must be identified and optimized.

For optimizing content in alignment with these indicators, we need specific information about our users’ content access patterns. This is where RoboHelp Server proves valuable as a powerful application for hosting, tracking, and managing RoboHelp output in multiple formats.

The many reports that RoboHelp Server provides help identify how users navigate user-assistance content and the product areas where this content needs to be strengthened:

  • Search Terms with No Results: Search terms that returned no results and the number of times users searched for them
  • Frequently Searched Terms: Frequently-searched keywords and how many times users searched for them
  • Frequently Accessed CSH: Frequently-accessed context-sensitive Help topics and how many times they are accessed. The report is arranged by the context IDs of the CSH topics.
  • Frequently Viewed Topics: Report on Topics that end users view most often
  • Usage Statistics: Chronological graphical report of the number of hits to the Help system as a whole. Pages searched for and not opened reflect in this list. The usage statistics report has three additional tabs:
  • Page Views: Number of pages viewed over a given window of time. The window of time is determined by the labels along the X axis.
  • Pages Per Visit: Number of pages viewed per visit. Every instance when a user opens the project is considered as a separate visit. Visits from different Web browsers are counted separately.
    • Browser: Comparative data about the Web browsers in which users viewed the Help content
    • OS: Comparative data about the operating systems on which users viewed the Help content
  • Search Trends: The percentage of search terms that returned no results. The detailed view of this report gives the total number of search terms and how many of them returned results/no results.
  • Help System Errors: Error messages encountered by the current logged-in user

Ankur Jain, Adobe’s product manager for RoboHelp, shares his perspective of the business relevance of these reports in an excellent blog post titled, Create What They Want to Read.

For the while, I’ll leave you with some other insightful community content for RoboHelp Server:

Explore these links and do come back later for more information and tips. Happy reading!