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Web Analytics

Web analytics is a process of measuring, gathering, analyzing and preparing online data for the purpose of understanding user behavior, optimizing websites and using online advertising campaigns to the greatest extent possible.

Two categories of web analytics

With web analytics we measure number of visits of a certain site and see what visitors are interested in and what they are not. With such knowledge and insights we can improve a certain webpage and make it more user- (and conversion-) friendly.

Two categories of web analytics

1. Off-site web analytics mostly deals with measuring the behavior of potential buyers, web recognition of your company and links to your website.

2. On-site web analytics mostly measures the behaviour of those users that are already on your page. We can see what they were doing on the page and how long they were visiting it. By using this information we can improve your website or a certain campaign.

We must be aware of the fact that no website or advertising campaign is perfect, thus there is always room for improvement. Web analytics provides basic tools for the analysis of the current state and for the determination of direction of corrections.

As our basic analytical tool we use Google Analytics, but we also use MOZ in Clicktale, for example. With the help of these tools we can precisely analyze website visits and set further strategies.

Google Analytics

Five fundamental pillars of web analytics

1 Setting targets

This is the most important step in analytics implementation. If we do not know what our goals and targets are, we will not know when they are reached.

2 Key success factor (KSF)

These are the indicators that help us measure the progress on the way to realizing our goals. With measuring those indicators we get a more detailed insight in the operation of a certain campaign or website.

We know different types of KSF:

  • repayment on investment (ROI)
  • further sales
  • social interaction
  • traffic sources
  • the price of advertising on the obtained contact/sales
  • conversion measurements
  • visualization of the purchase channel
  • position of keywords on search engines.

We do not use all the indicators at once – we determine the ones that are essential for a certain company or marketing campaign.

3 Gathering data

We need to be careful to collect the right and accurate data and also that we don’t miss out any data we would need. Collecting incorrect information and/or selection of insufficient amount of them can lead to false interpretation and consequently to incorrect strategy placement.

4 Data analysis

When we have already gathered the information and we wish to analyze it, we have to be careful about the following:

  • no website can be compared to any other website
  • “bounce rate” (represents the percentage of visitors who enter the site and then leave, rather than viewing any other pages within the same site) measures quality of users who enter the site
  • keywords used by those users that are on the site tell us a lot about why they are visiting a certain site
  • search engine at a certain web site tells us what exactly users are looking for.

Analyzing data helps us to improve a certain webpage because we know what users want and search for, it also helps us find the mistakes and make the page more user-friendly.

5 Testing and implementation of alternatives

When analysis is finished, we can set the hypothesis about which corrections are going to improve the situation. Before implementing those corrections we need to test the hypothesis, since we don’t know if something that seems right to us is right for the user. This stage is followed by implementation.

Web Analytics: A B test

We need to understand that web analytics is a circular process that actually never ends. When we correct and improve certain page, we have to start the analysis all over again.

Pillars of Web Analytics