Web Analysis

Web Analysis, also known as traffic analysis or Web controlling, serves to improve efficiency and monitor the long-term success of websites. It is a method of recording and evaluating information about the behavior of visitors, as well as calculating it into statistical data (KPIs). From these performance metrics, appropriate measures can then be derived which are meant to generate positive development depending on the objective of a website operator.

Important metrics (KPIs)[edit]

KPIs (Key Performance Indicators) are statistical information which only has any real significance if compared with previous or industry-specific data. It must be considered within a reasonable period of time in order to be able to see change as a trend and not as ordinary, everyday fluctuation. However, a regular analysis is recommended to initiate timely measures based on key statistical data with a negative trend.


Most viewed[edit]

Another important piece of information, which is determined by web analytics, is traffic. Thus, the effect of already implemented advertising campaigns reflects not only in increased sales, but also in increased traffic.

Duration of visit[edit]

Besides the development of number of visits, it is possible to analyze the behavior of users. The duration of the visit on a website, also detected by web analytics, is an indicator of customer satisfaction, and can be used as an incentive to make a site more user-friendly.

Popular user path[edit]

Weaknesses of a website may come to light since the analysis will reveal specific information about respective subpages. Thus, a user’s path and sequence of his clicks can be tracked and in case of successful application can even be influenced and controlled.

To illustrate the data obtained as related to specific topics, various statistics can be generated which provide informative value with clarity.

Page value[edit]

Page value indicates how valuable a page is with respect to the actions taken by visitors following it. In the ideal case this may be a transaction, conversion or lead generation.

Classification of visitors[edit]

For operators of online shops, web analytics provides a breakdown of visitors based on purchase interests. The majority of visitors will leave the site without completing a purchase. The reason is that they are often new customers who are not yet ready to commit to purchasing an unfamiliar product.

Furthermore, one can determine how many users add an item to their cart independent of the final purchase, whereas another group of visitors makes the purchase. If these are regularly interested customers with frequent purchase decisions, it’s called customer base.

Objectives of web analytics[edit]

A lot of key statistics are calculated and observed as part of web analytics in general. Each of these indicators represents an incentive to take action towards improvement. Therefore, it is very important for website operators to focus on their main objectives and set priorities correctly. If this is the case, then a consistent and rapid introduction of targeted measures is possible.

Possible targets of web analytics can be:

  • Boost visitor numbers
  • Customer loyalty
  • Keeping visitors on the website as long as possible
  • Increase conversion
  • Improve customer satisfaction
  • Controlling of advertising success
  • Increase revenue by selling

Important questions[edit]

The following questions can be answered with the help of web analytics:

  • What do visitors want from my site?
  • What wishes remain unfulfilled?
  • What are the reasons leading to leaving the site?
  • What makes users visit my website?
  • Do they use any particular keywords in search engines?
  • Where are the weaknesses, or where is there is a need for improvement?

Web analytics as a tool for SEO[edit]

In the field of search engine optimization, other KPIs are usually measured which are specifically important for SEO measures as the general statistics for web analytics. The focus is increasingly placed on individual factors which are important for search engines such as:

  • Visibility index
  • Google
  • Referrer source analysis
  • Technical KPIs
  • Content KPIs
  • Link KPIs

An example of the analysis of user behavior in the network and the range of websites is the Arbeitsgemeinschaft Online Forschung eV (AGOF) (English: Online Research Working Group eV).