Jonatan Lundin's blog
In pursuit of the ultimate techCom information architecture
Are personas an effective tool when developing end user assistance?
As a technical communicator, you often start by categorize users into user groups where each user groups is given a name, for example Network engineer, System administrator, Operator etc. To make the user group come alive, you develop personas to represent each user group. But how do you, as a technical communicator, actually develop user groups and personas? And how do you determine what type of information to write and how to classify and organize information in deliverables based on a set of personas?
How do you design for findability, part 2?
Today, users are searching for an answer when stuck in product usage. Nobody is reading the manual methodically. If your users are having trouble in finding information in your manuals, your business may be facing a risk of losing its customers. This risk is increasing since the time users have to spend on searching is limited or even decreasing and the amount of information to search in is constantly increasing.
How do you design for findability?
SeSAM is a design framework for technical communicators. Check out SeSAM (now on YouTube) if you are lacking an information modelling strategy on how to determine what type of information end users need and how to organize and classify content for findability; in practice how to design end user deliverables. SeSAM can complement your DITA strategy.
SeSAM is now unlocked on YouTube. For more info see: http://www.youtube.com/user/jonatanlundin
Are you creating and managing content nobody reads?
Of course you say “no”. But, how do you know if your documentation is read and used (and helps the user)? My experience is that a lot of companies create and manage content that nobody reads. Nobody reads due to two reasons: users can’t find it (even if it is relevant) or because the content is judged to be irrelevant, when skimming the text.
How is a topic signaling its content?
The first thing a user does when viewing a topic found in a search system, is not to read it, but evaluate if it contains the answers the user is looking for. How can we help our users determine if the found topic contains the answers? Let’s explore the how, but let’s first take a look at the search process in detail.