Web Page tagging: gathering data through code

Data is one of the hottest commodities of the 21^stcentury. American mega-retailer Target was aware of this current trend years ago, when they began to develop a data-driven prognosis model. The aim of this model was to take collected customer data and transform it into useful information, to ultimately increase sales efficiency and customer satisfaction. This tool generated a stir in 2012, when the New York Times discovered how Target was able to correctly predict a teenage girl’s pregnancy before her father could find out.

Having access to credit card information and local supermarket purchasing behavior represents only a small portion of the total amount of data available to companies and store owners nowadays. In addition, customers are leaving increasingly longer and more informative online trails, which companies are of course eager to use for their own gain. The more extensive an online offer is, the greater potential there is that Big Data can be harvested. Here, data is generally collected via so-called web page tagging. But what exactly does this term mean, and how does it work?

Page tagging: definition

Page tagging refers to the implementation of tags in the existing HTML code of a given web presence. These markings help to analyse the behaviour of users when they are moving between two page views. As a client-side method for gathering data, it presents an alternative to server-based log analyses, and it’s often also referred to as a web analysis. It is important that web page tagging be understood as a separate entity to conventional tagging methods: this involves labeling content in social networks, blogs, or websites, in order to structure topics.

Different tools are available for users to help them evaluate their collected data and add tags, like Google Analytics. The information from Google Analytics can reveal how much traffic goes through a site, how long these visitors stay on average, and the respective page or screen size of the devices they’re using.

How page tagging works

Contrary to traditional log analyses, the foundation of page tagging as a cross-server method was laid in the 90s by so-called web bugs, known as tracking pixels or pixel tags. These single pixel graphics, which were added to the HTML code and could initially only be viewed by website visitors, offered a convenient solution for tracking the frequency of page visits. If a user called up the respective page, then the tracking pixel, which was located on an external server, was downloaded. This made it possible for providers to collect, store, and analyse data for their customers.

Around the millennium, page tagging web analytics were optimised, by making the pixel tags invisible and adding JavaScript Code to them. These tags are also added to the HTML documents, revealing information about the requesting client (visitor’s browser). This allows website operators to find out which operating systems visitors are using, where they originally come from, and which keywords brought them to your website. In case the client deactivated JavaScript, then only the tracking pixel is downloaded. This only registers the page visit, so no other user or device details can be followed.

The results of page testing analysis and its applications

Page tagging is relevant for anyone interested in actively maintaining the constant growth of their web project. And there’s no doubt that the gathered data is especially valuable when it comes to sales-oriented marketing; the potential to use this data to attract new users, readers, or customers shouldn’t be underestimated either. Here are a few examples of the valuable insights that can be gained from page tagging results:

The device used: more and more users are accessing the internet via mobile devices. Having mobile pages and a responsive design (i.e. optimising sites for all devices) should always be a priority for any website operator. Page tagging lets you find out more about the user visit distribution of one page to another. Make sure to keep industry-specific developments (e.g. the growing number of purchases completed on mobile devices) in mind when working with this technology.

Popular topics, content, search words: high click rates and longer page views indicate that your published topics and themes have aroused your viewers’ interest. Operators of blogs or news portals are able to gain valuable input this way, which can be used for future planning. Information on the keywords used is especially interesting when it comes to online shops and other web services.

Conversion rate: observing conversion rates, i.e. the value that indicates the positive number of transactions in relationship to the total number of visitors, is an indispensable e-commerce measure. This way, online shop operators are able to find out how many users turned into paying customers. A conversion can even be something as simple as registering for a newsletter, clicking a link, or downloading a specific file.

Bounce rates and internal searches: the moment in which a user leaves your site can just as easily be determined as the last website they accessed. Bounce rates can be indicative of weak content or technical shortcomings. For this reason, it’s crucial to inspect the functionality of individual elements, the general loading time as well as the menu navigation factors. A clue that the latter aspect isn’t functioning as it should be is if users do not frequently use the menu, or internal search function, on your website.

Although web page tagging is often considered to be the same thing as web analysis, the latter aspect encompasses a large spectrum of measures for harvesting data. Here, things like log analyses, cookies, compiling click redirects, tracking AJAX, Java, and flash elements come into play. All of these data gathering methods help deliver valuable information that you can analyse for your own gain.