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The term Sliding Average has the same meaning as Rolling Average and Moving Average, or MA for short. I've talked about MAs and MMAs (Multiple Moving Averages) at length over many posts. I like to use MMAs as a reverse crystal ball to find patterns in my web traffic and ad revenue, as well as a means to making an educated guess at future trends.

A moving average is essentially an average value based on a window, usually of time in days, weeks, months, or years. For my blog traffic analysis, I use windows of 28 days (4 exact calendar weeks). The longer the window period, the smoother the trend graph is. However, because I only have less than a year's worth of blog statistics, I'm using 28 days. The window has to be fixed. You can't use 28, 30, 31 days in rotation, depending on the calendar month. You could use a window of 7d, but I feel that this is too small and obscures the real trends. As you've likely read, professional blogging requires a long-term strategy. Hence the reason why I use a 28 d window.

That said, I also use several other windows of 56 d, 84 d, etc., increasing by 28 d each time. These multiple windows give me Multiple Moving Averages (MMAs), and show me both short- and long-term trends simultaneously. If you've ever followed a stock's performance, you may have seen these trend charts. However, they are typically daily charts, with large fluctuations, which obscure long-term performance.

All this may sound scary to those of you that are math-fearing, but it really is pretty easy. For whatever value you are tracking trends for, say daily pageviews, you decide on a window, say 28d, and add up that many consecutive values. So, if your first day of data starts on Oct 1, 2005, your first average is calculated by adding up all your pageviews for Oct 1-28, then dividing by the window size, 28d. This is your first average for your 28d MA. Now repeat for Oct 2-29, etc., until you no longer have 28 days to sum up. Plot the resulting averages over time, against the daily values. Repeat the process for a larger window, say 56 d.

Keep repeating for further larger windows, and you will have an MMA graph. The largest window will show the smoothest curve because the fluctuations have been averaged out. Ideally, your longer-term MA graphs will start to resemble an exponentially increasing curve.

I made promise to post a spreadsheet in which you can plugin in your data, and I haven't forgotten. I'll still do it, hopefully after I've converted this blog over to WordPress. Or Drupal. I haven't decided.

(c) Copyright, 2006-present, Raj Kumar Dash, http://blogspinner.countwordula.com/

Technorati Tags: blogspinner, blogging, pro blogging, multi blogs, web analytics, moving average, sliding average, rolling average, web metrics

A few visitors to this blog were looking for "tips to increase pagerank". The problem with any advice for this result is that it's mostly conjecture. Why? Because unless you work on a search engine team, you probably don't know all the necessary factors.

I was once a search engine webmaster, but this was over a decade ago, when ranking in the SERPs (Search Engine Results Pages) could be bought. You heard me, bought. The rules have change drastically, and they keep changing, mostly for the better.

Some of the factors that go into the making of pagerank, at least for the Google engine, are as follows:

• A domain name that is at least older than a year, or registered for 2 years or longer.
  
• Topic focus. If your blog talks about food and politics about equally, it's unlikely you'll rank high for either subject. On the other hand, if you talk about the food tastes of famous politicians, and if there's an interest such information via the search engines, that may make a difference.
  
• A large body of articles focus on related topics, and with some age on at least some of them. In other words, if you've been writing for a couple of years about, say, health-related matters, you'll likely have lots of articles and rank higher than the website of someone who just started writing about health. However, the body of articles has to be built organically. That is, you can't suddenly post 50 articles on cancer in just a few days. That's not humanly possible, not organic.
  
• Maintaining your popularity. Once you start ranking high in the SERPs, you maintain and even increase your ranking by having your pages clicked on more often than others ranking nearby for the same terms and phrases.
• Backlinks, organically grown. The more sites with related content that link to you, the better. Again, you cannot suddenly have dozens of backlinks appear overnight with the same link text. Even if you suddenly have a popular article with a short title, some of the backlink will differ.
  
• This is conjecture, but some people think that if you have the Google toolbar installed for either the Microsoft IE or Firefox browsers, that Google tracks pages being bookmarked and assigns extra fractions of pagerank if your pages are relatively popular.
  

These are only some of the "organic" pagerank criteria I've gleaned from a variety of blogs (sorry, no specific page links) over the past 6 months: ProBlogger, SEOBook, Jim Boykin, ThreadWatch, Search Engine Journal, and others. There are other factors, but many of them are considered "inorganic" and thus bad.

(c) Copyright: 2006-present, Raj Kumar Dash, http://blogspinner.countwordula.com/

Technorati Tags: blogspinner, writing, blogging, pro blogging, multi blogging, pagerank, web traffic