In less than a decade the analytics industry has radically changed. Up until 2012, the DAA was actually called the WAA (Web Analytics Association). The name change was made in large part to reflect the full gamut of data that analysts deal with in marketing and optimization. The contemporary analyst has become a storyteller of sorts, gathering and interpreting data from multiple platforms in order to understand the totality of a user’s journey. Platform Experience vs User Journey
The proliferation of new platforms, like mobile applications and IoT devices, led to an influx of new data sources. Yet, until recently, web analytics remained distinct from analytics collected on other platforms. Dimensions and metrics simply did not match up across all platforms. Users’ habits changed by device, so it was important to look at how customers used each platform and not assume that marketing and optimization strategies applied across devices.
For instance, consider your typical eCommerce product catalog. A desktop user browses products with an always-visible navigation and product filters. A high number of searches on a website meant that users were having difficulty finding something. However, that same catalog on a mobile app may show only one or two products at a time. Hence, on mobile devices, searching for a product may be the first thing that a user does, and a high number of searches was normal. Different platform experience meant different benchmarks for each device.
Digital analysts, however, spend most of their time studying conversion rates and the impact of marketing efforts. They attempt to quantify each step of the conversion process, inferring what worked well and what didn’t. And while dimensions and metrics are unique to each platform, the conversion goals are largely the same across devices – a purchase, a sign up, a download, or any defined objective. Simply put, analysts can gain much more by combining data on user actions and conversions for insights on how marketing efforts work together on different platforms.
Up until recently, integrating data meant trying to identify commonalities between platforms and attempting to create coherent data sources. While this process may result in some rolled up metrics and an executive dashboard, it will not provide actionable insights on how interactions on different devices collectively led to the conversions. In such limited comparisons the user’s journey is lost. Tell the Story of Your Customers
At the outset I mentioned that the contemporary digital analyst serves as a storyteller. The story he or she tells is that of the user’s journey. Any successful story should have the following components: the challenge (a business need or problem), the characters (your customers), the tragedy (associated costs or risk), and the heroic triumph (conversions). By way of our analogy, the plot of the story, or the events that mark the progression of time, serves as the analysis. As such, the analysis must include the following:
- An introduction (the acquisition channel)
- A rising action (micro-conversions throughout the user’s path)
- The climax (the start of the checkout funnel)
- Failing action and resolution (conversion or dropoff)
In other words, the analyst must consider and tell the entirety of the story about the user’s journey. As analysts, we don’t only focus on what occurred when the user first visited the website and browsed products for several minutes. Nor do we solely look at what his or her actions were during the final minutes spent on the mobile app to complete the transaction and buy products. Rather, we focus on the process at both the micro and macro levels along the path to the conversion (Figure 1).
For instance, analysts must consider the following types of questions. Did the user see a promotion on Facebook? Did he or she subscribe to a mailing list to receive a 10% off coupon? Was the coupon viewed on a mobile device? Did the conversion occur on the mobile device during the initial session? Or did the signup occur through a retargeting advertisement? By approaching the journey from this perspective, the basic unit of measurement becomes the user. We examine the user and the actions he or she took along the way, regardless of the platform.
Event Based Models
Analytics platforms are increasingly adopting user-centric reporting in lieu of session-based reporting. A user-centric focus means user actions must follow the same architecture regardless of platform or device. Many analytics platforms were badly in need of upgrades to support cross-device insights, as many of the tracking models were focused solely on measuring analytics for a specific device type, web analytics or app analytics, not both.
There have been many user-centric innovations of late. Both Google and Adobe have introduced the concept of data streams, with Google’s App+Web and Adobe’s Experience Platform, collecting and integrating data from different platforms into one unified system. Mixpanel and Amplitude employ event-based, user-centric models that track the specific actions which individual users take within your product. This is similar to what Google’s App+Web event-based measurement model does by reusing the data schema of Google Analytics for Firebase (Google’s standard for tracking mobile app analytics over the past three years).
For the first time in a while we are starting to see the same terminology being used across different analytics platforms – “Events” and “User Properties” (with the exception of Mixpanel which uses “Profile Properties”). The standardization of data on the way in facilitates quality results on the way out. It also allows organizations to expand integrations of digital analytics data with other data sources, such as CRM, POS (Point of Sale), VoC (Voice of Customer) and more, the sky's the limit when we have unified tracking models. Consequently, organizations can leverage artificial intelligence and machine learning to make predictions and provide insights that help them personalize customer experiences.
Plan of Action
Many organizations will go through this practice very soon as analytics platforms are evolving towards user-centric and journey insights. An important part of this transition is enabling action by removing barriers and being proactive about this change. Some organizations may see this as an opportunity to re-engineer their tracking and sync platforms together. Analytics leaders have long envisioned cross-device insights, and now that the technology is ready, it’s time for them to define transformation goals, build a guiding coalition and establish a sense of urgency to execute on this transformation.
As analysts, we know that an effective analytics strategy starts with the business objectives and trickles down to measuring the micro and macro conversions related to the business goals. In other words, we track the actions, or events, regardless of the platform. This does not mean that you should ignore metrics and actions specific to the platform experience. Rather, find those platform specific metrics and track them, as they are valuable when optimizing the user experience for each device. These data points will serve as subsets that will not impact the overall merger of event data across platforms and devices.
The shift to event-based data models and data streams is already happening. Start preparing by thinking of the user’s journey. When drawing analytics strategies, consider each action across platforms and ensure that the data tells the entire story, rather than an isolated occurrence or performance metric. While switching the data sets will be happening soon, switching the mindsets is what needs to happen first.
"Journey management and valuable personalization depend on identifying and serving the individual, in real-time and at any scale. These are the superpowers of marketing, but they are hamstrung without easy access to a robust customer data profile." Adobe 2020 Digital Trends Report.