I'm trying to get a project setup with Adoption Explorer tool but have some questions/confusion on the process.
First, if we already have usage data from our platform stored in the MDA, what does adoption explorer offer? Is it a more powerful reporting tool with better insights? Reading throught the overview article, it doesn't seem to be much different than reports I've already built out.
Secondly, regarding the creation of the project - we have an S3 connection to our platform usage, which is stored in custom MDA tables. Should I be using the S3 bucket as the source or the MDA tables? The biggest issue it seems for this setup is that an 'Account ID' is not provided in the usage datafeed and I have to load that from Salesforce into the MDA which is required by the project setup.
Can I get some tips/tricks or recommendations on how to best set up Adoption Explorer? Thanks!
Best answer by skalleView original
@dan_ahrens Can you share the date and registration details once they're firmed up since I'm OOO next week? Thank you!
Looking forward to this webinar.
But Thanks for the above post , I will take this to reach out to broader audience --
Today GS platform already can help store the Usage data via Custom objects,Rules for metrics, Reports for Dashboards etc, but its not the most ideal way to solve that usecase or turn the data to insights is our premise and that there was a need to standardize this most important "Customer Dataset".
As Manmeet pointed, the inights we can get from AE is very powerful and the fact that the insights/metrics/data can then be turned actionable as they are availablein Rules/Reports is definitely a plus.
With AE - we can bring data from multiple sources to the system and then very quickly using various powerful functions and Layouts(Usage Dashboards in AE) get insights reflected faster and better. We were able to add the concept of Person journey from usage data perspective via AE for the first time in GS.
The various data models to manage Usage data in opens up lot of possibilities around the insights we can get too. Just to name a few data model constructs we have attempted to standardize -
1. Company model
2. Company Person model ( Usage data captured at Person/user level aggregated to the Company/Account level,
3. Introducing the concept of "Instance" model to the above to manage say data at Instance - Location/BU/Product/ Multi-Field also can become that unique identifier for instance - Ex Customer A wants to manage Usage data at Location+Product+Version to make a business decision
4. Company - Entitlement(Use Limits)