Day in the Life of an Adobe Analytics Admin in Customer Journey Analytics
As your organisation evolves to use Customer Journey Analytics (CJA), this is existing news and opens up use cases such as: call centre deflection and cross-channel attribution. Whilst your users will be happy that their Adobe Analytics (AA) Workspace skills are transferable to CJA, there are several changes to common implementation tasks and BAU admin activities.
This post is aimed at an administrator audience.
No more props and eVars
As a native Adobe Experience Platform (AEP) application, CJA uses XDM and its schema structure. What does it mean?
- Unlimited dimensions – no need to consider prop vs eVar differences, no limits in managing the variable allocations as strictly.
- Structure – the data types supported are modernised e.g. nested objects and attributes.
Free listvars
listVars were probably the most prized item in AA but since CJA uses XDM, it supports unlimited string arrays which can be used similarly to listVars.
More Control
There is more control on what is the primary key whereas in AA it was always the ECID or AAID before that. Now as an admin, you can create different Connections to bring together multiple data sources.
Flexible (Data) Views
Data Views on the surface look similar to Virtual Report Suites in AA. Whilst it can accomplish that utility, it unlocks even more flexibility without altering data collection.
Marketing Channels
If you remember the last time that you had to edit the Marketing Channel Processing Rules, these rules were normally set during the implementation. This concept is different in CJA, it can be implemented with Derived Fields.
Customer Attributes Enhancement
Breaking down data with fields such as CRM, demographic or NPS scores is native as part of the XDM model.
Classifications to Lookups
Classifications are implemented via Lookup Datasets, these structures can also be used with AEP Audiences.
Classification Rule Builder
The comparable feature is Substring which is configured at the Data View level.
Low Traffic, Less Likely
Although uncommon in the first place, there are fewer chances to encounter low traffic bucketing.
Data Warehouse
The comparable feature is full table exports or alternatively you can consume a custom view using the Query Service.
Data Validation
In AA, the validation would stop at client-side data collection checks. With the variety of data ingested for analysis in CJA, the added functionality of using the flexibility of SQL queries via Query Service to access the raw data is better as a self-serve option.
Conclusion
On the journey to switch from long-standing processes and workflows, there are more and more tools and resources that facilitate the transition to higher maturity use cases.