Nearly every day in the adult classes I run on writing, I talk about the importance of two things. The first is in writing for your audience; and the second is in gaining effective feedback from that audience.

(These days I work for AutoSpeed only part time: my main job is as a trainer, mostly for the Australian Public Service in Canberra.)

When writing, if you cannot get inside your audience’s heads, you’re lost: you’re writing not for the reader but for yourself. So as a writer, you should always be thinking of your audience: will they understand this word, this concept? Will this interest them? Thinking of them, what is the best way to express these ideas? Would the audience prefer that I use an inductive or deductive approach? Would the story work better for the audience if I include this diagram or that photo?

And so on and so on, right down the screen (or page).

But of course, while the writer can think of the audience, they can never be sure that they’ve hit the right spot. Not without feedback, anyway.

Feedback from the audience can be detailed, it can be analytical and it can be highly structured. Alternatively, it can be very simple, very quick and anonymous. At AutoSpeed we chose the latter, giving readers a 1-5 continuum they can use to assess every page of content on the site. Because it’s simple and anonymous, many people choose to provide feedback.

In fact, as this is published, we will have received close to one million page feedbacks! One million! That’s quite extraordinary – and from a writer’s perspective, it provides immense feedback value.

Feedback helps govern AutoSpeed’s direction; it influences the writing style and it allows us to take major risks with content – and then to see if those risks pay off.

For any given article, I analyse the feedback rating in four ways.

1. The total number of feedbacks closely correlates with the page views of the article, so at a glance I can tell whether the article has been well read – or not.

2. The average score shows how much the article was liked by readers – our one million average (ie the average of all the individual article averages) is currently 2.81, so a comparison of individual articles with that number is easy.

3. The diversity of ratings tells me how much impact the article had on readers – how engaged they were with it. What I want to see is polarisation: readers either loved it or hated it. An even spread of scores from 1 – 5 indicates to me that readers did not become much engaged – and that is not what I want!

4. The change of average rating for an individual article alters over time. This is because initially loyal and longstanding readers rate the article; subsequently a greater mass of readers coming to the article via links and search engine results arrive to give their view. Thus I can see how current and new readers rate material differently.

So thanks if you’ve rated any articles over the years. The information you provided with those clicks – all 1,000,000 of them – helps guide and influence our writing.