More on Tracking Visitors for Multiple Blogs
I've written a fair number of posts on the importance of tracking your daily visitors as a whole over multiple blogs. What I may not have mentioned is the importance of also tracking your individual blogs. Some of this falls into the domain of the geeky, but it's a necessity if you are or are planning to blog professionally. (Note: some of the content here is a revist of previous topics.)
What I've noticed for my multiple blogs collectively is that, on average, my daily pageviews is increasing steadily. However, when you run multiple blogs like I do, and barely have enough time for everything that needs to be done, it's not hard to forget to check the stats of your blogs individually. It's possible that while your over-all visits are up, that some of your more important (to you) blogs are down.
I use a technique called "moving averages" (aka "sliding averages"), which I've written about several times here. Essentially, you choose a window of time, typically a multiple of 28 days (4 wks x 7 days/wk). The longer your window, the better. So if you choose, say, a 6-month window (6 x 28 = 168 days), then you apply a sliding average of 168 days.
Starting with day 1 of your pageviews data, you calculate the average of days 1-168, then the average of days 2-169. Keep "sliding" until you no longer have enough days for a full 168-day window. This group of averages is the moving average for the given window.
The moving average graph (aka trend line) tells you what has happened, not what will happen. The longer the window, the smoother the trendline. Stock market statisticians choose several windows, short- and long-term, and plot these MMAs (Multiple Moving Averages) to see what is going on in different industries. They apply the MMA as a whole to one market index, as well as to individual stocks.
If you do the same with your blogs as a collection and individually, it's easier to see what's going on. Of course, this is extra work if you don't have yourself some sort of stats package. However, a relatively simple way to do a moving averages analysis is to download your Google AdSense pageview statistics (by date and by channel) in CSV (Comma-Separated Value file) format. This format is compatible with Microsoft Excel spreadsheet format. In fact, if you use the Open-Source OpenOffice package, CSV will work there, or pretty much with any spreadsheet package.
Now you can set up your spreadsheet to calculate the sliding average. What I'll do is eventually post a prepared Excel spreadsheet for readers to download. You simply replace the "raw pageviews" column with your data, and the MMAs are calculated automatically. There'll even be a graph of the various trendlines. (If possible, I'll also offer an OpenOffice file). And if I can ever get a wee bit of time in the new year, I'll set up a service on one of my domains where you can calculate and see your trendlines in a browser.
One thing to keep in mind is that short-term fluctuations do occur. Another thing to consider is that if you move a blog to a new domain (but keep the old one alive and just post new entries to the new blog), you may have to rebuild your traffic. As an example, the old BlogSpinner blog enjoyed reasonable traffic, getting as high as #28 in the "BlogTopSites" computer/internet category. It's dropped to something like 78 at the time of this writing for two important reasons:
(1) New entries are not being posted. That means that the SERPs (Search Engine Results Pages) rankings are dropping for blog-related directories.
(2) Competition from other blogs under the same category.
Some people don't like installing this hit-counter type of graphic. But at a glance, I can compare my old BlogSpinner to my new version. Unfortunately because the newer blog has fewer entries posted, it tends to get much less traffic from search engines. This kind of statistic is an important consideration if you are planning to move blogs around.
(c) Copyright: 2005-present, Raj Kumar Dash, http://blogspinner.countwordula.com/
What I've noticed for my multiple blogs collectively is that, on average, my daily pageviews is increasing steadily. However, when you run multiple blogs like I do, and barely have enough time for everything that needs to be done, it's not hard to forget to check the stats of your blogs individually. It's possible that while your over-all visits are up, that some of your more important (to you) blogs are down.
I use a technique called "moving averages" (aka "sliding averages"), which I've written about several times here. Essentially, you choose a window of time, typically a multiple of 28 days (4 wks x 7 days/wk). The longer your window, the better. So if you choose, say, a 6-month window (6 x 28 = 168 days), then you apply a sliding average of 168 days.
Starting with day 1 of your pageviews data, you calculate the average of days 1-168, then the average of days 2-169. Keep "sliding" until you no longer have enough days for a full 168-day window. This group of averages is the moving average for the given window.
The moving average graph (aka trend line) tells you what has happened, not what will happen. The longer the window, the smoother the trendline. Stock market statisticians choose several windows, short- and long-term, and plot these MMAs (Multiple Moving Averages) to see what is going on in different industries. They apply the MMA as a whole to one market index, as well as to individual stocks.
If you do the same with your blogs as a collection and individually, it's easier to see what's going on. Of course, this is extra work if you don't have yourself some sort of stats package. However, a relatively simple way to do a moving averages analysis is to download your Google AdSense pageview statistics (by date and by channel) in CSV (Comma-Separated Value file) format. This format is compatible with Microsoft Excel spreadsheet format. In fact, if you use the Open-Source OpenOffice package, CSV will work there, or pretty much with any spreadsheet package.
Now you can set up your spreadsheet to calculate the sliding average. What I'll do is eventually post a prepared Excel spreadsheet for readers to download. You simply replace the "raw pageviews" column with your data, and the MMAs are calculated automatically. There'll even be a graph of the various trendlines. (If possible, I'll also offer an OpenOffice file). And if I can ever get a wee bit of time in the new year, I'll set up a service on one of my domains where you can calculate and see your trendlines in a browser.
One thing to keep in mind is that short-term fluctuations do occur. Another thing to consider is that if you move a blog to a new domain (but keep the old one alive and just post new entries to the new blog), you may have to rebuild your traffic. As an example, the old BlogSpinner blog enjoyed reasonable traffic, getting as high as #28 in the "BlogTopSites" computer/internet category. It's dropped to something like 78 at the time of this writing for two important reasons:
(1) New entries are not being posted. That means that the SERPs (Search Engine Results Pages) rankings are dropping for blog-related directories.
(2) Competition from other blogs under the same category.
Some people don't like installing this hit-counter type of graphic. But at a glance, I can compare my old BlogSpinner to my new version. Unfortunately because the newer blog has fewer entries posted, it tends to get much less traffic from search engines. This kind of statistic is an important consideration if you are planning to move blogs around.
(c) Copyright: 2005-present, Raj Kumar Dash, http://blogspinner.countwordula.com/
