Tracking and Collecting Data in Web Analytics and Conversion Optimization

Currently, there are two main technology approaches for collecting web analytics data: log file analysis and page tagging.

Log file analysis software reads the records, called log files, on the web server, which record all clicks that take place on the server. Web servers have always stored all the clicks which take place in a log file, so the software interprets data which has always been available. A new line is written in a log file with each new request. For example, clicking on a link, an Ajax call or submitting a form will each result in a new line being written.
 
Page tagging, on the other hand, sends information to a third party server, where statistics can be generated. The browser executes JavaScript code which communicates with the tracking software.

Pixel tracking can be used to track email campaigns. Here, a tiny transparent 1 pixel by 1 pixel is placed in the email. When you load the images in the email, you will also load the tiny image that tracks your activity. 
 
What you should know:Log file analysis

• Log files are normally produced by web servers, so the raw data is readily available. Page tagging, however, requires changes to the web site.
• Log files are very accurate – they record every click. Page tagging can be less accurate. If a user’s browser does not support JavaScript, for example, no information will be captured.
• Log files are in a standard format, so it is possible to switch vendors and still be able to analyse historical data. Page tagging is proprietary to each vendor, so switching can mean losing historical data.
• Log files record visits from search engine spiders – useful for search engine optimisation.
• Log files record failed requests, whereas page tagging only shows successful requests.

Page tagging

• JavaScript makes it easier to capture more information (for example: products purchased, or screen size of a user’s browser). You can use log file analysis to capture this information, but it will involve modifying the URLs.
• Page tagging can report on events, such as interactions with a Flash movie, that log file analysis cannot.
• Page tagging can be used by companies that do not run their own web servers.
• Page tagging service providers usually offer a greater level of support. This is because it is a third party service, whereas log file analysis software is often managed in-house.

Because of the different methods of collecting data, the raw figures produced by the two services will differ. Sometimes, both are used to analyse a web site. However, raw figures not matching up should not be a problem. It is through interpreting these figures that you will be able to understand how effective your Digital Marketing efforts are.

Web site analytics packages can be used to measure most, if not all, Digital Marketing campaigns. Web site analysis should always account for the various campaigns being run. For example, generating high traffic volumes by employing various Digital Marketing tactics like SEO, PPC and email marketing can prove to be a pointless and costly exercise if the visitors are leaving your site without achieving one (or more) of your web site’s goals. Conversion optimisation aims to convert as many of a web site’s visitors as possible into active customers.

What information is captured
There are three types of web analytics metrics:

• Count – these are the raw figures captured that will be used for analysis
• Ratio – this is an interpretation of the data that is counted
• KPI – either a count or a ratio, these are the figures which help you to determine your success in reaching your goals

In analysis, metrics can be applied to three different universes:

• Aggregate – all traffic to the web site for a defined period of time
• Segmented – a subset of all traffic according to a specific filter, such as by campaign (PPC) or visitor type (new visitor vs returning visitor)
• Individual – the activity of a single visitor for a defined period of time

Here are some of the key metrics you will need to get started on web site analytics.
 
Building block terms: 

• Hit – a request to the server (and a fairly meaningless number on its own)
• Page – unit of content (so downloads and Flash files can be defined as a page)
• Page views – the number of times a page was successfully requested
• Visit or session – an interaction by an individual with a web site consisting of one or more page views within a specified period of time
• Unique visitors – the number of individual people visiting the web site one or more times within a period of time. Each individual is only counted once.

1. new visitor – a unique visitor who visits the web site for the first time ever in the period of time being analysed
2. repeat visitor – a unique visitor with two or more visits within the time period being analysed
3. return visitor – a unique visitor who is not a new visitor

These are the most basic web metrics. They tell you how much traffic your web site is receiving. Looking at repeat and returning visitors can tell you about how your web site creates loyalty. As well as growing overall visitor numbers, a web site needs to grow the number of visitors who come back. An exception might be a support web site – repeat visitors could indicate that the web site has not been successful in solving the visitor’s problem. Each web site needs to be analysed based on its purpose.
 
Visit characterisation:

• Entry page – the first page of a visit
• Landing page – the page intended to identify the beginning of the user experience resulting from a defined marketing effort
• Exit page – the last page of a visit
• Visit duration – the length of time in a session
• Referrer – the URL that originally generated the request for the current page

1. internal referrer – a URL that is part of the same web site
2. external referrer – a URL that is outside of the web site
3. search referrer – the URL has been generated by a search function
4. visit referrer – the URL that originated a particular visit
5. original  referrer – the URL that sent a new visitor to the web site 

• Click-through – the number of times a link was clicked by a visitor
• Click-through rate – the number of times a link was clicked divided by the number of times it was seen (impressions)
• Page views per visit – the number of page views in a reporting period divided by the number of visits in that same period

These are the terms that tell you how visitors reach your web site, and how they move through the web site. The way that a visitor navigates a web site is called a click path. Looking at the referrers, both internal and internal, allows you to gauge a click path that visitors take.
 
Content characterization:

• Page exit ratio – number of exits from a page divided by total number of page views of that page
• Single page visits – visits that consist of one page, even if that page was viewed a number of times
• Bounces (single page view visits) – visits consisting of a single page view
• Bounce rate – single page view visits divided by entry pages

When a visitor views a page, they have two options: leave the web site, or view another page on the web site. These metrics tell you how visitors react to your content. Bounce rate can be one of the most important metrics that you measure! There are a few exceptions, but a high bounce rate usually means high dissatisfaction with a web page.
 
Conversion metrics:

• Event – a recorded action that has a specific time assigned to it by the browser or the server
• Conversion – a visitor completing a target action

Other metrics which apply to Digital Marketing tactics include:

• Impression – each time an advert or a page is served
• Open – each email that is deemed open. Usually if the images are loaded, an email is considered open

In order to test the success of your web site, you need to remember the TAO of conversion optimisation:

• Track
• Analyse
• Optimise

Using your goals and KPIs, you’ll know what metrics you will be tracking. You will then need to analyse these results, and then take appropriate actions. And the testing begins again!