Interpreting Web Analytics Data

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Interpreting Web Analytics Data

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Interpreting Web Analytics Data

At some point in time, most Web site owners will ask the question

“Who’s coming to my site, anyway?” It’s an important question and one that an entire industry has been built around.

Web analytics is a tool used to examine traffic occurring on a Web site; an analytics program reports this traffic and depending on the level of analytics sophistication can segment this report into precise, individual elements.

Where Does Pentera Come In?

Pentera provides automated reports delivered directly to the client.

These in-depth reports present valuable insights as to site traffic patterns and directed interests.

Our analytics reporting provides a window into your site’s traffic: who is visiting, why, for how long, and what they found to be of interest.

Annual Web site reviews are offered by Pentera as part of a premier support service and can include careful review and analysis of the site’s analytics data. Pentera’s experience will help guide you along the path to improving site performance and capitalizing on existing site traffic.

Types of Analytics Tools

The many tools for use in collecting and reporting this information may for the most part be broken down into the following types:

Raw data

Tools of this nature (such as Urchin) tend to collect data without regard to who or what is browsing the site. These tools generally are server-side and will report every hit and every visit regardless of the nature, type, or reason for the visit. Raw Data tools will usually report significantly higher numbers than tools designed with more refined filters.

Google Analytics is the most widely used analytics service, currently in use by about 40% of the 10,000 most popular Web sites.

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Filtered analytics

Filtered analytics tools (such as basic Google Analytics reporting) provide a basic method of sorting data and removing unwanted information—search engine indexing and developer’s time on site, for example. These tools present lower numbers than their raw data counterpart and thus may be used to examine a more real-world view of Web site traffic than is possible with raw data. Often these tools will provide valuable information such as the average time spent on site, pages viewed per visit, and percentage of unique visitors. Useful filtered analytics tend not to be a reliable index of actual traffic and should be used only as a general metric—comparing findings only to previous data generated by the same tool.

Intelligent analytics

Intelligent analytics tools (such as advanced Google Analytics reporting) provide a more robust and reliable method of collecting and filtering Web site traffic data. These tools are designed to gather and filter data in such a way as to create a more accurate view of traffic that is actually occurring on the Web site. These tools provide the services offered by filtered analytics tools and include the ability to segment traffic across users, browsers, geographic areas, marketing segments, and

much more.

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Filtering and Segmentation

While raw data is useful information to a given approach, the ability to filter and segment data can make the numbers much more meaningful.

Below are explanations of a few common filters and segmentations:

Filters

Search engine filters

These filters remove traffic generated by search engines indexing the site, an action that occurs on a regular basis and rarely involves human interaction.

Site developer filters

Custom instruction to the filtered and intelligent analytics tools allows for traffic generated by specific IPs and/or domains to be removed. This removes visits that would otherwise be scored by those maintaining the site.

Segments

Visits

Typically this is a measure of the overall number of individuals committing what the analytics tool considers to be a review of one or more site pages. This number should not be confused with hits, as a visit will typically generate a number of hits. A visit is a primary element and many of the following segments will reference this number.

Pages per visit

This is a number generated by dividing the number of pages viewed for all visits by the number of visits. A higher number indicates that more pages are being viewed during each visit; typically, higher numbers are desired.

Average time on site

Typically this number is created by dividing the total time spent by all visits by the number of visits. This number indicates how long an average visitor spent on the site, and normally a higher number is desired.

Percentage of new visits

This is a value determined by the server’s ability to recognize a visitor from one visitation to another. This is tricky to determine, and often intelligent analytics can perform a more accurate analysis here. This number tends to indicate generally what percent of new visitors a site has seen in the period being analyzed.

Filters and segments help organize the raw analytics numbers into metrics that you can use to evaluate the traffic on your site.

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What to Look For

Determining “good analytics” for a Web site is an individual process;

some sites want very high traffic numbers, while others are more concerned with the time spent on site or the number of pages viewed.

Generally, for specialty sites such as planned giving Web sites where emphasis is maintained on a more focused population segment, more attention should be directed to time spent on the site and the number of pages being viewed than on the number of hits or visits generated.

Reasons for this are fairly straightforward: These Web sites are of interest to a smaller segment of the general population and are informational in nature. Typically, results from such sites are generated not by pumping large numbers of visitors through the site but by targeting specific audiences and providing the information they want and need while they are on the site.

So for such sites, special focus should be placed on:

• Pages per visit—Look for higher numbers for this metric.

• Average time on site per visit—A higher number here is also desirable.

Contrasting these two metrics may provide an idea of how interested the target audience is in information imparted by the Web site—in other words, how well the message is getting out.

New visits

Fresh viewing is always nice but a planned giving site may generate more results from return visits. Typically this number will vary considerably, but it should not stay very high or low for a protracted period of time.

Pentera’s periodic Web site reviews can help you make the most of your site’s analytics data.

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What Not to Look For

Hits vs. Visits

It is common to confuse the value of “hits” with that of “visits.” A hit is essentially any request to the Web server; this includes both internal and external requests, mail requests, image loads, authentications, server uptime checks, and effectively any action that takes place on the Web server. If the request can be associated to a particular Web site, it will count as a hit. The result is that any site will generate a very large number of hits very quickly. A visit, on the other hand, is a much more careful measurement of traffic. Typically visits will filter out non-human traffic (image loading, internal requests, authentications, uptime checks, mail requests) and will focus on external page access. Further, a visit will keep track of each visitor and track that visitor across a number of pages.

This results in a visit being comprised of dozens or even hundreds of hits

—and provides much more intelligible analytics to the client.

Bounce rates

Simply put, a “bounce” is a visit that enters and leaves on the same page, or one that stays on the same page for an extended period of time (usually between 10-20 minutes). Bounce rates will tend to be higher on many planned giving sites, as the analytics is monitoring only a single section of the site and pass-through traffic will be recorded as bounces. For this reason it is advised to view bounce rate as a relative measure—in other words, rather than focusing on the actual number, watch for changes in that number from month to month. Fluctuations will occur as part of normal Web site ebb and tide, but radical changes may indicate a change of viewer focus or even a problem with the site.

Less important metrics:

 Hits

 Bounce rates

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Where Do I Go from Here?

As you can see, interpreting Web analytics is not an exact science—the metrics used to evaluate one type of site may not be appropriate for your planned giving Web site, for instance—but the use of services like Google Analytics coupled with the appropriate filtering and segmenting can give you a much clearer picture of who is visiting your site and what they’re doing while they are there.

To help you make sense of your analytics data, Pentera offers an annual Web site review in which we’ll analyze the analytics and make recommendations based on our findings. If you’re not seeing the results you desire, improvements and solutions may be in order. Whether these adjustments would best occur on your actual Web site or rather in the marketing of your Web site—Pentera can help!

Contact Us Today

8650 Commerce Park Place, Suite G Indianapolis, Indiana 46268

phone: (317) 875-0910 e-mail: [email protected] www.pentera.com