In my last post, I talk about how Google Analytics isn’t very helpful in providing meaningful data about technical or help content. It can’t answer questions like: Did it help the reader? Did they find it interesting? Could they accomplish their task/goal thanks to my content? What do readers really want? You know, simple questions like those.
While a little disappointing, that’s not what makes me sad.
What’s sad is that the charts on the dashboard have all the makings of dysfunctional communication. For example, the dashboard seems to tell me, “You’re not retaining readers over time.” But, it can’t, or it won’t, tell you why.
Awww, come on, gimme a hint?!
Continue reading “Google Analytics just makes me sad”
Lately, I’ve seen a collection of blog posts about using Google Analytics for technical or, more generally, informational content that seem to use a formative research method, that goes something like, here’s the data you can collect, now let’s imagine the questions that it might answer. It’s not that this method is not valid, just that it’s one that is usually done at the beginning of a project and it doesn’t scale particularly well. What many technical communicators could use on a daily basis is summative data on how their content is doing on a day-to-day basis.
Can Google Analytics provide useful summative metrics? Sure, but very few that monitor what matters to the reader. Most of them fall into the vanity metrics category for informational content. The reason is that people don’t come to informational sites to read web pages or click links (which is what Google Analytics tracks). They come to accomplish a goal—a goal that is likely not found in your informational web site. Your site, if it is doing its job, is a means to another goal.
So, how can you measure whether a reader accomplished their goal? And, by measure, I mean observe directly and not infer (or imagine) reader behavior.
Continue reading “The answer is Google Analytics—what was the question?”
This topic has been discussed in technical writing circles for decades. It’s not so much as a discussion as it is folklore in the form of good advice that’s difficult to apply in practice and it’s been around for a long time—this 1995 article by Ginny Redish, “Adding value as a professional technical communicator”  lists these ways to measure value:
- Outcome measures
- Ratings of customer satisfaction
- Projections (estimates) of value added
- General perceptions of the value of technical communicators’ work
I like how she starts with measuring the value added, because if you can’t measure it, then how do you know you have actually delivered it? Further, if you can’t measure it, how can you show improvement in that—(a) whatever it is, it’s now better and (b) it’s better because of a decision you implemented. That’s a trick question. You can’t. So, how can you measure this? Continue reading “Measuring the value of technical writing”