In part two of our quickstart guide, we delve deeper into the laguage of Adobe’s Customer Journey Analytics.
As we continue our journey through the transition from Adobe Analytics to Adobe's Customer Journey Analytics (CJA), we will dive deeper into a new set of terms that interlock and layer upon each other. This time, our focus is on diving deeper into familiar concepts and introducing you to new terminology that comes along with it. We'll progress from the overarching idea of 'Segment' versus 'Filter,' and move into the distinction between 'Visitor' and 'Person,' navigate through the finer differentiations of 'Visits' versus 'Sessions,' and ultimately, reach the most granular level of 'Hits' versus 'Events.' Along this path, we aim not only to introduce these essential terms that define Adobe's analytics landscape within the CJA framework but also help facilitate a smooth transition in understanding the changes this framework brings.
“Visitor” containers versus “Person” containers
When considering the transition from 'Visitor' to 'Person,' it's crucial to recognize that 'Person' containers will now encompass every interaction and page view made by individuals within a specified timeframe. In contrast, 'Visitor' is limited to counting the number of unique users visiting your website. The adoption of 'Person' containers acknowledges a broader spectrum of customer journeys beyond website traffic. It involves the use of unique identifiers and the linking of common identifiers between data sources. This approach enables us to gain insights into the comprehensive journey points that constitute interactions and purchases within our brands. As a result, we achieve a more comprehensive understanding of customer interactions and journeys, which are now visible across channels, whereas they were separate unique visitors in Adobe Analytics journeys.
“Visit” containers versus “Session” containers
The next layer of CJA terminology introduces us to 'Session' containers, which correspond to what was previously referred to as a 'Visit' in Adobe Analytics' segments. These 'Sessions' provide us with a deeper understanding of individual page interactions, campaigns, or conversions within a specific session, capturing behaviors throughout the entire session, which can span different platforms and experiences. In contrast, 'Visits' in Adobe Analytics limited us to tracking only a sequence of website page views within a given session, restricting the data funnel to what we could track solely with web or app data. For instance, with 'Sessions' in CJA, our insights may extend to scenarios where individuals interact with paid social data sources and subsequently make in-store purchases within the same timeframe.
“Hit” containers versus “Event” containers
In the realm of CJA, 'Event' represents the finest level of granularity in filtering, similar to Segment's 'Hits' containers. Both 'Event' and 'Hits' containers serve the purpose of isolating specific behaviors, tracking codes, or even individual pages within a customer journey. However, a crucial distinction for 'Event' is the necessity to recognize that all data sources could potentially map to the same common dimensions. This mapping ensures the seamless synchronization of all our data sources with each other.
For example, when capturing 'clicks,' this could encompass all clicks occurring on our website and paid search ads. With the ability to connect visitors across devices and platforms, we are no longer confined to a single data source. We now have the capability to include data from multiple sources. Therefore, additional refinement becomes essential to isolate data from a specific source.
In navigating the transition from Adobe Analytics to Customer Journey Analytics, we've explored a landscape of evolving terminology. From the broader concepts of 'Visitor' to 'Person,' the finer differentiations of 'Visits' and 'Sessions,' and the most granular 'Hits' versus 'Events,' we've uncovered a new language that unlocks deeper insights across the entire user experience with your brand. As the field of analytics continues to evolve, connecting data across different platforms and data sources will become more essential to understanding how users interact with your organization and how it impacts your bottom line.