The core problem:
Web analytics solutions are built on a premise that is no longer true: that users have a single touchpoint and access sites on a single device. Access is rooted in cookies stored on a single machine that stores data about how that specific web browser visits the site. Now that we can reach websites via our desktops, mobile devices and apps, game consoles and TVs, we, digital marketers, need to find a solution that will help us understand consumer behavior more holistically. More specifically, we can get a better understanding of how visitors interact with businesses at every stage – advertising, sales, product usage, support and retention.
Google recently introduced a solution, Universal Analytics (UA) that will help marketers track people across devices with a single ID so that all data are aligned, across all platforms, by users, not by sessions! UA will help us tailor Google Analytics (GA) to our needs, integrate our own datasets (yes, finally) and ultimately get a more complete vision of the entire marketing funnel.
Because of the purpose of this post, I don’t want to get into the technical details of how Google is be able to do this; I’d rather talk about specific examples of how we can use UA to make more informed decisions.
We did some analysis for a client to understand the differences in site traffic and usage for different devices (i.e., desktop, mobile and tablet). As seen in the heatmaps below (desktop, tablet, phone, respectively) we noticed that phone and tablet traffic were both spread throughout the day, while desktop traffic was concentrated during typical work hours. Given the existing capabilities of GA, we couldn’t tell whether some of the afterhours visits actually spilled over – i.e., the visitor checked the website during the day on their work desktop and returned to the site with their tablet or phone in the evening, to understand what the business/product was offering in more detail.
Until Google’s recent UA announcement, we couldn’t have had access to this kind of data unless visitors were required to login to a site. With the advent of UA, we won’t be limited by these types of challenges, because UA will enable us to track users rather than sessions. We will be able to identify return visitors from different devices and customize content, such as personalizing a specific marketing message for them by, say, not showing a video they had already seen in the morning, regardless or not they were logged in!
We can then compare the performance (goal completions, average time on site, pageviews, etc) of those visitors who were exposed to “personalized” content and put them in different segments in order to develop better strategies and optimize our tactics accordingly: Do we need a mobile strategy? Do we need different CTAs (calls-to-action) for different device types? Should we change where the content is located for phones/tablets so that they are easier to find for returned visitors? The opportunities are almost endless.
Although this is not the ultimate solution for measurement, our analytics group is very excited to be able to do more sophisticated and holistic analyses to get an even deeper understanding of consumer behavior. I am planning to write another post once we start using the tool. I think offline data integration deserves a post by itself.