Last night I watched a short video on a site called Inside Adsense. The title of the article was Speeding Up: The Basics And Analytics, which was kind of a goofy title because, if you ask me, the video had nothing to do with the title.
Anyway, in the video, which is about 4 minutes, the presenter talks about ways to check the type of traffic you’re getting based on looking at a few specific areas. One of those, the one I’m going to talk about here, is Visitor Loyalty. This basically states how often someone decides to come back to your website, or in this case, to my blog. It doesn’t tell how it knows who they are, and it doesn’t tell you who they are, but it knows.
I decided to look at some statistics, and of course I wanted to share with all of you. I’ve also looked at visitors before, but never at this stat, I don’t believe. I’m also doing two different time periods, one current, and one from last November, when this blog was humming.
For now, I’m choosing June 1st to June 30th. First I look at just general visitors information. During this period, I had 1,301 visitors, 883 absolute unique visitors, which means never been here before. People stayed an average of 2 minutes and 18 seconds, which means enough actually stayed around to read what I had to say. And it said I had 64% of absolutely new visitors. That percentage different from the number of visitors and absolute unique visitors, which comes in around 68%, and my thought is that the 64% represents people who have never been here before, whereas the other group has been here before, but hadn’t been by in a very long time.
Next I looked at Visitor Loyalty. It starts with that figure of 64% of new visitors, which are also one and done; thanks for coming, sorry you had to leave so soon. The rest of the figures are intriguing, though. They’ll tell you how many people came twice, three times, up to 8 times, then you get divisions such as 9-14 times, 15-25 times, 26-50 times, 51-100 times, 101-200 times, and finally 201+ times. All of these comprise my remaining 36%. My highest is people who’ve come back more than 200 times, at 11.61%; wow! There’s true loyalty, I must say. Next is twice at 6.15%, followed by 101-200 times at 3.77%, and 9-14 times at 3.54%. That’s a total of 326 visitors.
One other interesting statistic is looking at what they term Visitor Recency. This shows the percentages of how quickly visitors come to see your content. My figure is at 88% within 24 hours of posting; nice! I’m wondering if a lot of that is the Twitter factor or the subscriber factor, since all my posts show up on Twitter immediately, and of course if one subscribes to a feed they’ll know about it pretty quickly also.
Now to compare this period to November. In that month I had 1,602 visitors, 867 of them absolute unique visitors. They stayed on the site an average of 5 minutes and 59 seconds; nice. And my absolutely new visitors was around 52%.
More comparing, out of that 52%, my highest group of people coming back to the blog was from 101-200 at 12%, 2 times at 7.7%, 51-100 times at 7%, and 15-25 at 3.9%, totaling 491 visitors. And, the final statistic, my Visitor Recency figure was 92.5% within 24 hours.
This points out some interesting things. One, some of my readers have stuck with me through a lot, and I thank you for it. There’s also a lot of new readers who visit, which is great, but I’m not capturing all of their attention since their bouncing quicker than in the past. Probably many new people who visit this blog take a look at one other post, since that’s the second highest number, and then decide it’s not for them; gotta keep ’em coming. What’s a great figure for visitor loyalty? I’m not really sure, but I’m not necessarily mad at either of the figures I have.
One final thing to throw in here, since I’m talking about visitors. Out of my top 10 visited articles in the month, only 4 of 19 were written in June. My fouth highest was written last November, third highest written in January. That’s probably not a bad thing, having older posts that still bring visitors to the blog.
So, there you go. More information you probably didn’t need, but information that, if you’re on Analytics, you might think about looking at to figure out something about your visitors.