Web metrics, web analytics and website statistics

Summarized overview

In this article you will find discussion and definitions of:

• metrics and E-metrics
• Analytics
• Statistics
• Statistics Opentracker measures

You will also find information about:

• The function of statistics
• How statistics can help improve web performance
• What statistics can & should tell you
• How to apply this information
• Comparing stats programs;
• Different types of measurement
• Translating raw data: from server-browser dialogue to interface
• Fine-tuning statistical measurement
• Tracking and statistical accuracy
• Human agency: how statistics are created

What are they, and why measure them?

There are various terms used to describe the science of recording and interpreting website statistics. Web metrics, web analytics, web stats and site stats, to name a few. ‘E-metrics’ refers to analysis of electronic businesses.

Metrics

The ‘metrics’ of web metrics refers to measurement, the science of measuring websites. Specifically, measuring website events, and extracting trends. In this case, those events are human clicks.

Analytics

Analytics is the act of distinguishing categories within recorded stats, and analyzing for any patterns. The process of analytics means, literally, taking apart the whole of something in order to study its component parts.

Statistics

Statistics are a scientific application. The goal is to form actions, for example website content management, based on the data which are recorded.

With an application of statistics there is less guesswork. Simple questions can be answered, for example, something very basic; are there more or less people coming to your site this week than there were last week? Is your site doing better or worse this week?

What should your stats tell you? They will inform you about numerous aspects of your traffic; the number of (returning) visitors to your site, and how visitors surf through your pages. This information tells you about the content of your site and how visitors use it. Your traffic statistics are an indicator of website performance. When applied in this sense, site stats can be used very effectively to make updates.

Comparing different types of measurement

When comparing different types of measurement, the classic scenario of ‘the difference between apples and oranges’ often arises. In the same way, different website statistics programmes have unique ways of measuring important variables such as pageviews, unique visitors, and visits.

Therefore it is not always easy to compare the results generated by two statistics programmes to track one site. The process itself can be very useful, in terms of thinking through the differences in results and determining what is actually being measured. We encourage the use of numerous programmes, for example, combining a tracking service with log analysis.

If the method of measurement stays the same through time, then the results will be very useful for purposes of comparison. Therefore, choosing the method of measurement is important. Scientifically speaking, changing the method of measurement during an experiment invalidates the process.

If you compare results from two types of measurement you will find differences in numbers. For example, measuring pageviews versus unique visitors, or the whole site versus specific pages. If you compare the same statistics over time, you are not changing the method of measurement. This is the most accurate way of recording statistics. This will allow you to find patterns and definitive answers, for instance if traffic is growing or diminishing. Is your campaign in America working, are visitors returning over time? Do your efforts to bring targeted traffic through a PPC campaign lead to conversions? Do returning visitors generate more revenue than the first-time visitors?

Statistics and determining what to measure

In any statistical endeavour, the first step is to define what is being measured. In this case, the common denominator is human events, clicks on a website, which are defined as pageviews.

Specifically, the statistics discussed here are a translation from raw data, clicks, and server-browser dialogues, into a user interface from which patterns can be discerned. The goal of web metrics is to extract patterns which tell you what is happening. The next step is to create actions, i.e. what to do about your traffic patterns.

Web metrics and analytics is an exciting field at this moment, because there are not many patterns being sought. An example might be comparing ‘bounce rate for first time visitors’ with ‘bounce rate for returning visitors’, which has not become a standard of analysis (aggregate bounce rate stats tell you how far into your site visitors are clicking).

fine-tuning statistical measurement is an ongoing process

One key point to bear in mind is that nothing can be measured with 100% accuracy - don’t believe it if that’s what you’re being told. The skill lies in trying to keep measurements useful, despite the inability to reach 100% accuracy. An acceptable margin of inaccuracy within the scientific discipline of statistics is 5%. That does not make the world an uncertain place - it means that you have to be specific in knowing what is important. For example, trends, are trends rising or declining over time?

The process of determining what to measure involves the creation of numerous definitions. There are always elements that are being under or over-measured. That is why the system requires constant calibration, in terms of what people really want to know, which in turn determines what should be measured. An example would be the question ‘what constitutes a search engine?’ Should the Yellow Pages and White Pages be included? There are new search engines & portals appearing every day. What criteria should be used to classify search engines? Our list of officially recognised search engine list, located on our forum, requires constant calibration.

With reference to improving the marketing strategy of your website, it is important to focus on the the most important variables for you, and locate an application that provides these measurements in a clear format. For example, measuring the performance of specific keywords that you purchase for your Pay-Per-Click campaigns (PPCs).

Statistical needs vary depending on site size. Therefore it is up to statistics programmes to present the statistics in a way that is useful for webmasters of different sized sites.

Large sites, for example, are more interested in trends. Larger sites generate higher volumes of data, in which clickstreams won’t be very interesting. As there are too many clickstreams (e.g. sites which receive several thousand visitors a day), only the aggregates are interesting. Larger sites are interested in aggregate data, while smaller sites are interested in discreet data.

Trends are aggregate statistics. For example, a site’s bounce rate is an aggregate statistic. Bounce rate are stats designed for the purpose of identifying patterns which are hidden within the stats.

Discreet stats such as clickstreams, will tell you what individual people are doing on your site. Discreet stats are not aggregates, as you are actually seeing what the data is “built” of.

This type of information (clickstream analysis) is very useful for development purposes and understanding user reaction. If you are designing a new site, knowing how first-time visitors navigate will help to determine how successful the site is, and what changes need to be made.

Opentracker and statistical accuracy

Opentracker is a best-of-breed solution. We offer a high degree of statistical accuracy because we use cookies to measure unique visitors. Human events, in the form of page views, are used to generate the statistics we present. One click is equal to one page view. There is no translation, just one-to-one correlation.

We do not extrapolate, we count visitors

To illustrate some of the difficulties associated with counting and measuring, consider a statistic that tells you how many people voted in an election. Counting votes is a difficult process and re-counts are often undertaken and it’s not unusual to reach different totals every time.

Take American presidential elections as an example. Re-counts are often undertaken, however, they invariably come up with different totals every time.

When polls are released, the number presented is an extrapolation, based on a percentage of people contacted by phone, or asked at the door for whom they voted.

Opentracker does not extrapolate, but presents trends derived from actual clicks. This is how we try to narrow the margin of error. We use optimization techniques based on cookies and visitors to improve our accuracy.

When the trends presented are derived from actual clicks, the margin of error will be narrowed. Traffic measurement techniques based on cookies improve accuracy.

Our point is that data, (i.e. statistics) are numbers created by people. Therefore it is important to understand how these numbers are defined and generated.

The data collected with cookies gives insight into site visitors over time, the traffic is deduced from unique visitors and there is minimal 'double-counting' of visitors. We often asked why Opentracker’s traffic numbers are often lower than those recorded by log files – and this is why.

We believe Opentracker to be at least 30% (and probably much higher) more accurate than standard web tracking and statistics solutions currently available.

Article written by Eddie Moojen and Cralan Deutsch. August 2003. Updated February 2005.

Related reading:

• Clickstream analysis
• The difference between hits, visitors, and page views
• How does user tracking work?

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