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 January 17

  • Action: Doug to review and propose refinements to current SFDC product taxonomy

    • Output: separately from how SKUs shook out, here’s how product managers think and talk about products and hierarchy (this human-readable schema should be applied across user experiences (e.g. Salesforce vs. PowerBI use cases))

    • Is there a distinction between “sub-group” (SFDC) and “sub-category” (NetSuite)?

    • Already in progress because of other contexts

 

  • Action: gather current state of conversions and leads across company

    • Doug email going out 2/2 to collect this info

 

  • Action: Let's create an Analytics portal/table of contents thing (needs an owner) – we have overlapping data being consumed (APIs, databases, data lake, data warehouse, excel, google sheets, punched cards, rope core memory, braille) and presented in multiple output channels (SFDC, PowerBI, NinjaCat, probably others) 

    • There should be some kind of ANALYTICS STOREFRONT thing where you can

      • Find the data thing you need or 

      • Ask for it

    • Includes a list of links to reports about various topics (@aishwarya has a proto-version of this already to share)

    • Should include some kind of "dictionary" (I am 90% sure that "dictionary" is the wrong term but) that describes where the stuff comes from and how it's derived

    • This is a good idea

    • I think I volunteered to own it but I am glancing over at you @Brian Gildea

       

  • Are there "duplicated" datasets between lake & warehouse for product sales data? – Charlotte asked @Martial Fodouop to sort this out because there was some angst somewhere about it

    • Drew’s presentation is intended to be closer to “installed” base vs. “entitled” set from SFDC

    • Ideally Drew would like to be pulling data for Layered App Penetration from…? (Drew can you elaborate?)

      • Right now based on manual data recorded by Drew’s team

    • Drew and Martial to have coffee or something

 February 8

  • Review: Reina/Aishwarya to compare notes on MRR / Core Product KPIs dash

    • Aishwarya: Lance can use the Products KPI dashboard instead of Sales Dashboard created by Reina. Lance has a copy of report based on his requirement. Once that’s approved by him we can discontinue using Reina’s dashboard. Lance Copy of Core Product KPIs | Salesforce – Created by Aishwarya

  • Discussion: Ownership of the complete picture

    • Robert: The owner of the complete picture should be a product person not an engineering person. Given the scope of that complete picture, seems like it should be a product person on the analytics team.

 

  • Review: Doug Chase (Deactivated) to review and propose refinements to current SFDC product taxonomy

    • Output = separately from how SKUs shook out, here’s how product managers think and talk about products and hierarchy (this human readable schema should be applied across user experiences (e.g. Salesforce vs. PowerBI use cases))

    • Is there a distinction between “sub-group” (SFDC) and “sub-category” (NetSuite)?

      • Martial: These are not currently consistent. We have sub-group in NS as well. It is replacing sub-category. And that's where SF is pulling from. So new field "sub-group" in NS and SF are consistent (the same).

  • Discussion: Other inputs to CX assessment and attribution

    • Things like page speed, time on site, customer flows through pages

      • These sorts of metrics ultimately impact conversion rates. They are leading indicators of future conversion impacts.  

    • If we roll out an inventory detail page redesign and conversions are unaffected or even go up currently we say "yay! that's a win!," but if we look at other metrics we might find that conversions on those specific pages went down and leads were redistributed.  

      • Or we might see that the page speed time went up on average 0.1 seconds, or that bounce rate went up 2%, or that we are seeing more rage clicking.  

      • Or we might see a redistribution of leads to other conversion types.  

    • All of this while conversions remain stable. But if you roll out 2, 3, 5, 10 updates with similar impacts you have meaningfully negatively impacted conversions.  Death by a thousand cuts.  

    • It's easier to see the cumulative future negative impact by looking at these other metrics with each release.

 

  • Review: Doug Chase (Deactivated) to compile current state across company

    • Review results and define next steps. How do we get consistent across the whole company?

 

  • Action: (Needs owner) Let's create an Analytics portal/table of contents thing – we have overlapping data being consumed (APIs, databases, data lake, data warehouse, excel, google sheets, punched cards, rope core memory, braille) and presented in multiple output channels (SFDC, PowerBI, NinjaCat, probably others) 

    • There should be some kind of ANALYTICS STOREFRONT concept where you can reliably:

      • Find the data, visualization, or widget you’re looking for  

      • Ask for one to be created

      • Find a list of links to reports about various topics (@aishwarya has a proto-version of this already to share)

      • Learn where the data for a given visualization comes from, and how it's derived

         

  • Review: Are there duplicated datasets between lake & warehouse for product sales data?

    • Charlotte had asked @Martial to sort this out because there was some angst somewhere about it

    • Drew: Charlotte and I had a good conversation this week about our current state. We understand that subsets of some data is copied to the lake, and that it is for different purposes/use cases than the BI that is coming from the enterprise team.

      • In other words, we're not sending data to the lake with intention to duplicate insights that can come directly out of SF or through BI coming from her team.

      • That said, we do want to document definitions for common types of metrics for two reasons:

        • 1) the SF experts can have visibility and input into calculations made using SF data and

        • 2) in a case where the same metric does exist in product and enterprise reporting, we can ensure we're using the same method to calculate them. 

      • Aishwarya Ghumekar and Martial Fodouop, I'm looking forward to working with you two on documenting these definitions. I figured we could use some of our next Power BI meeting to start that discussion.  

    • Drew’s sales data is intended to be closer to “installed” base vs. “entitled” set from SFDC

  • Ideally Drew would like to be pulling data for Layered App Penetration from…

    • We would ideally pull this from historical data stored in the lake. The main thing is to get away from manually recording it since you can't modify the filtering for past data and it requires human entry. That said, there are some challenges to pulling point in time for all the datasets... so I don't have any timeframes around tackling this.