Docs by Design

In my previous post, Measuring your technical content – Part 1, I described some content goals and how those might be defined and measured for an introduction topic. In this post, I look at Getting Started topics.

Getting Started topics

If Introduction topics bring people in by telling them how your product can help them, Getting Started topics are where you show them how that works. Readers who come here from the Introduction topic will want to see some credible evidence that backs up the claims made in the Introduction topic and these topics are where you can demonstrate that.

Technical readers will also use this as the entry point into the technology, so there are at least two customer journey paths intersecting here.

• One path will come to a conclusion here, moving from the Introduction page to see the value and then the Getting Started topic to see how it works
• Another path starts from the Getting Started page (already understanding the value proposition of the product) and moving deeper into the technology to apply it to their specific case.

Because at least one of the customer journeys through the Getting Started topics are less funnel-shaped than for the Introduction topics (some are almost inverted funnels), it’s important to start with the goals and required instrumentation before writing so that you can design your page to provide the information that the customer needs for their goals as well as the data you’ll need to evaluate the page (your goal).

So, in that case, what how might you measure such a topic’s success?

Continue reading “Measuring your technical content – Part 2”

This started out as a single post, but grew, and grew, and… Well, here’s the first installment.

After the last few posts, it would be easy to get the impression that I don’t like Google Analytics.

Not true.

I just don’t like when it’s treated like it’s the only tool that can collect data about a web site—especially a non-funnel (informational) web site.

In this collection of posts, I’ll look at my favorite topic, API documentation, and how you might analyze it in the context of the customers’ (readers’) journeys. This analysis doesn’t have to apply only to API documentation, because it’s based on customers’ goals, which are more universal and, if you look carefully, you might see a customer goal that matches some of your content.

So let’s start with the basic questions…

Continue reading “Measuring your technical content – Part 1”

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” ^[1] lists these ways to measure value:

1. Outcome measures
2. Ratings of customer satisfaction
3. Projections (estimates) of value added
4. 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”