As of 2018, there were 2.5 quintillion (a million raised to the power of 5) bytes of data generated daily. While this number continues to grow exponentially, its efficacy reduces (if not confuses) our ability to make meaningful inferences without proper analysis.
In the realm of digital marketing, there are a plethora of analytical tools, statistical packages, and BI dashboards one can used to discern online activity. One that we’ve found as an agency that is almost universally adopted by our clients, is Google Analytics. This post will briefly explore how this platform can be leveraged, and more particularly how to (correctly)attribute positive online user behavior.
In Analytics, conversions are – by default - credited to the last campaign, search, or ad that referred a user when he or she converted. BUT… what role did prior website referrals,searches, and ads play in that conversion? How much time passed between the user's initial interest and his or her on-site action? These are important questions, and an unclear or ignorant understanding of what the data is telling you can result in sub-optimal decision-making.
The commercial real estate sector is one that experiences(among others) extended user journeys, multiple website referral channels, and extensive site-map structure. To overcome blurring these into the same picture, to better understand the interplay of acquisition channels, and to optimize channel marketing spend requires a holistic, multi-channel funnel overview.
Distilled down to its core, multi-channel funnels have to do with attribution – understanding what action/s caused an outcome. Optimal attribution has to do with casual inferences, not those that are superfluous. The below cartoon powerfully captures this.
It follows, that determining the magnitude, direction, and relationship of brand interventions on audience actions, is central to driving evidence-based decisions, and consequently, optimal budget allocation.
As a platform Google Analytics is highly malleable and effective, but as the saying goes: garbage in, garbage out. Correctly configuring and understanding the various components to a multi-channel report is central to being able to truly trust what the data tells you. Three of these aspects include:
1. The look back window: the period to which a conversion can be retraced to its initial interaction.
2. The conversion point being tracked: these could be on a micro or macro basis (contact form submission, a property’s marketing package download, a user’s online session duration… etc).
3. The attribution model being used: the rule, or set of rules, that determine how to credit a conversion to touch points in the conversion’s path. An example can be seen below.
While we hope the above has shed some light on the value of analytical reporting, and harnessing data-driven insights for effective decision-making, there is another side to the equation. Google Analytics reports on historical data generated. It does not account for that which has not occurred or could occur in the future. Valuing that which can be measured, over that which cannot, is a bias in and of itself, and can also lead to sub-optimal decision making. But that’s for another blog...