As blogs make it easier to publish more information, the process of finding information becomes more difficult. This makes keeping up with the Blogs harder than keeping up with the Jones!

Consider one of two options to keeping up with the feeds:

1. Check and read every blog/web site of interest to you all the time (daily), wasting all of your time and energy doing so.
2. Ignore the blogs and use a search engine when ever you need information – but now you don’t keep up with things as they happen.

Neither of these are good things. The early developers of blogs knew this, so they create a way to let people automatically know about new postings. This is done through Really Simple Syndication, often referred to as RSS. RSS is a special file format that can be read by RSS Readers to alert users of updates.

RSS readers come in several forms. They can be a like a normal desktop application, built into most modern browsers, or web based services.

What they do is periodically check RSS feeds that you “subscribe” to, and alert the user when changes occur. If the Blog post a full feed, you don’t even have to leave your reader to view the post. Partial feeds give you a summary of the posting, or the first few paragraphs and require you to go to the site to see the full article.

You will find that different RSS reader applications provide different levels of usage. I used the built in feature to the Firefox browser at first. I was able to track 10 – 12 blogs that way. Unfortunately, it didn’t show me which posts I’d already seen, and it only lets you see titles, no summaries or full postings. This created a lot of wasted time.

Then I switched to Google Reader. Now I track over 120 blogs, and can even share items with others, because it lets me operate more efficiently. I track things that help me to do my job better, (Web technologies, database feeds, web analytics, search engine information) as well as news, cartoons, historical notes, and Feakenomics. Like most reader software, it allows me to mark items as being read (so I don’t continue to see them) star them for importance, and share favorite postings.

Because RSS can be used for many different purposes, I’ve been able to track regular postings, as well as meeting announcements, on-line classes, and more.

May 1^st is RSS Awareness day. While a week and a half away, it is a good time to learn about how it can help simplify your life.

photo credit: Chesi – Fotos CC

Popularity: 24% [?]

Web Analytics is often used by marketing staff members to determine their effectiveness. This is a real-life example of how I recently helped a company measure the effectiveness of their internally driven e-mail campaign.

A company I work provides training to their clients on the products they have purchased, as part of their on-going support.

Before I started working with this company, only basic analytics from the website was tracked. Not even all of the pages were being actively tracked. So I have been slowly working on adding a complete view of the website usage based upon analytics.

It recently started sending out targeted e-mail newsletters showcasing their latest course offerings based upon what classes the user has previously attended. However, the first e-mails required that the user manually enter the web address, and search for the class. While enrollments improved, it wasn’t as much as had been hopped.

To make things easier, I developed a method to allow the user to directly access the class. Given that a software vendor was used for the site, which has limited customization abilities, this was not as simple as one would think. However, with my web development background it was possible. By using a special link and modifying our analytics package, we were able to start tracking how many people followed the link from the e-mails that went out.

While it was always intuitive that they received more enrollments based upon the e-mails, they had no way to determine how many people were accessed the site based upon the e-mails. They could see that on a given day, enrollments went up – but how about the following days.

Often e-mail isn’t opened or acted upon in the first day due to people being out the office, having to get approval for the expenditure, etc. We can now prove this by seeing web hits from our clients 3 or 4 days after the initial e-mail goes out.

By tracking the information a little more closely, we can see the return on investment (ROI) of the internal e-mailing system and validate its continued use. This has the staff excited about continuing to use this new marketing system, as well as bringing in additional clients for the training.

Popularity: 18% [?]

It’s one thing to look at your reports, its another to start to draw conclusions from your data. Different people will look at the data in different ways. Most often, the reports are looked at by the marketing department/person to see how to better market the site, what Search Engine optimization needs to occur, and measure the effectiveness of their pay-per-click ads. All of these are important uses of the web analytics, but they are not the only uses.

I want to look at a specific example of how I, as a web developer, recently went about making a site faster based upon the results of some analytics reports.

The 80/20 rule of the web

We’ve all heard of the 80/20 rule. On the web it would 80% of people only use 20% of your web site. In reality however, depending upon your site, it could be more like 90/10. A novice web developer will try to optimize all of the pages. An experienced web developer doesn’t bother with those pages that receive only the smallest amount of visitors.

On an Intranet web site I maintain, which tracks the employees’ internal education process, I was looking at the internal search feature. The search results are loaded into the same page. When you count the results from the searches, this page accounted for 24% of all of the page views, making it the second most visited page on the site. (The #1 page is mostly static text, so no real improvements could come from there.)

This means for every 2 people to visit the site, approximately 3 searches were performed in addition to the normal page load. So almost 1 out of every 4 page views was to this internal search engine, and some people were searching multiple times.

This became an area to consider improving. As a little improvement here, would have more effect than a large improvement on a page that is only viewed 1% or less of the time.

Too combat this, I decided to load the results in with AJAX instead of reloading the whole page. This process would improve search response in 3 ways.

Network Connections

Each time a file is downloaded over the Internet, the web browser checks to see if there is a newer version on the server, or if it can use a local file it has already downloaded (cached). Each time it checks to use a local version or downloads a new copy, the server is using up resources, and your end-user has to wait for the files to finish checking/downloading. Because the number of network connections has been reduced, other people can be accessing the site at a faster rate, and the end-user appears to be faster as they don’t have to have their computer do as much work.

The search page referenced 15 external files, plus itself. Of those 12 wouldn’t have to be called anymore. So I was able to reduce the number network connections by 80% for the search results. This was our biggest savings. The number of network connections on a web server is limited by both number and bandwidth speed, therefore the more connections, the slower each connection appears.

Processing of Files

Knowing in advance that it was going to be a popular page, I had tried to make the page as efficient as possible initially. However, with some of the features, like remembering the previous search criteria, because you never left the page, no longer needed, I was able to simplify the page.

The initial page load took about the same amount of time, however when the search results displayed, it appeared to be less than 1 hundredth of a second faster to process the file, about 4.45% faster. While individually it does not yield much savings, when applied as many times as it is with the popularity of the page, the savings adds up, especially during peak times.

Size of Results File Download

I knew I would save a lot in this area. The search interface, consisting of 6 controls, and a variety of other HTML sections, would no longer have to be duplicated in loading the results. This would mean faster downloads, and improved “perception” of the speed of the web page/server. Based on the same sample set of data, there was an 11K reduction in the overhead of the search results, or approximately 14% smaller download. This was for a search with over 100 results. However, many times fewer results (20-50) are returned. So the savings in bandwidth, while still approximately 11K, would be a much higher percentage (30-75%).

Final Thoughts

Because I could determine from our analytics package which files were being processed more, I was able to get the most bang for my buck. This update will take some load off the server, and allow all the pages to benefit from this enhancement. Likewise, almost every visitor will notice a performance improvement in the site because of how often this page is viewed.

This is how a web developer can effectively use web analytics to improve the performance of the web site.

Popularity: 22% [?]

The day after I post a simple overview explaining what a bounce rate is, I find an article where someone who specializes in web analytics has posted a survey to find out what different people’s bounce rate is for their site.

I can tell you that the different sites I manage range from about 8-12% (Corporate Intranet)  to 55-60% (this blog) – blogs generally run higher, because they have several articles on a page, so you don’t have to follow pages to get content. I give a range only because they do vary from day to day.

Interesting…that’s all I have to say. What about any one else out there.  Do you know what the bounce rate for your sites are? Leave a comment if you wish.

Popularity: 27% [?]