If good data is the foundation of customer insight, tagging is the foundation of good data and in our experience, whilst all organisations claim to be data driven/data centric/customer led few organisations actually are as a result of poor analytical tagging
In essence, “tagging” refers to the set-up of a digital analytics platform (most commonly Google Analytics) and includes everything from installation of the tracking script itself through to event tracking and the definition/identification of specific customer segments. As a result, without a robust tagging specification an organisation is not able to create the data necessary to enable effective performance reporting or customer insight. Having a state-of-the-art customer data platform or visualisation suite is irrelevant if you don’t have the right data.
Despite the clear importance of a robust tagging specification, many organisations struggle to get their tagging right. This stems from the lack of an analytical strategy and a lack of technical acumen.
An analytical strategy (also known as a measurement framework) is a detailed plan of what you want to report (metrics) and how you want to report it (dimensions/segments). Without an analytical strategy it is not possible to define a tagging specification (as you don’t know what you want to measure). Most organisations simply want “data” or “insight” without giving any consideration that what, exactly, they need to report.
Given that analytical tagging is a highly technical component of the data analytics and insight process, it is important for an organisation to have a high level of technical understanding of their analytics platforms (e.g. Google Analytics). Some metrics, dimensions and segments are available out of the box and so require no additional tagging whilst others are not out of the box and so should be captured within the tagging specification, furthermore some customer segmentation is defined through combinations of existing metrics and dimensions and so should be considered within the analytical strategy but does not require additional tagging. To make this even more complex, depending on the analytical strategy the same metrics may or may not require custom tagging, for example product add to carts can be identified out of the box (with an enhanced E-Commerce tracking implementation) but often also benefit from custom tagging e.g. to identify the specific CTA the user clicked.
Ultimately, whilst analytical tagging is a complicated process, it is also fundamental to an organisations ability to measure their performance and understand the customer. If an organisation gets it right, they are significantly more empowered to make truly data-driven decisions and ensure that they offer the best possible experience for their customers.