Google Analytics and Google Tag Manager are used by around 30 to 50 million companies worldwide. The tools are great for basic web analytics but restrict the user to aggregated data unless a substantial fee is paid (reported to be £90K per annum). This presents a large obstacle for small to medium sized businesses who want to develop a data-driven strategy. Let’s imagine a small retailer wants to implement a recommendation engine. Not a bad idea given that Amazon estimates that around 35% of sales are generated through their recommendation engine! To do so, the retailer needs access to the ‘raw’ data, but they won’t want to pay a fee of £90K for what is often a research project and won’t want to abandon GA because of the time invested in developing accurate tracking through GTM.
Ultimately, Google’s binary (either free or very expensive) payment plans do not encourage companies to experiment with data. While this may be tolerable today, in the long term, small and medium sized companies are going to be left behind in the race to develop data-driven solutions.
An affordable solution.
An ideal solution would allow a company to continue using GA and GTM whilst somehow allowing the extraction of ‘raw’ hit-level data at an affordable price.
One solution we have been working on here at Measurelab is to implement research by Simo Ahava. This solution uses GTM to ‘trick’ Google into reporting hit-level data as a custom dimension, along with the essential client and session identifiers. Once implemented you can pull unaggregated data from Google’s internal databases and begin to really understand how customers interact with your website.
However, it can be tricky to get all of the data out of Google’s internal databases. It can be done using a Google Analytics’ API but this requires some serious engineering. To this end, we have developed a user-friendly web application which can handle large backdates of data in one fell swoop.
Bang! Hit level data at just a fraction of the cost of a GA 360 subscription. One word of caution, you will still have a wait until enough data has been collected before you can perform a meaningful analysis!