Content Comparison

• Review: Reina/Aishwarya

  • Sync on https://leadventure1.lightning.force.com/lightning/r/Report/00O8b000009I8fOEAS  (Reina apparently has a similar report going that we haven't seen.)

• Does Krissy have an existing separate dataset related to churn/attrition? – Yes, cancellation dashboard in PowerBI – is this the right version @Martial Fodouop?

  • https://app.powerbi.com/links/9Rj02wXv4e?ctid=515fce4f-ec7a-46f5-be34-13c81256a7d0&pbi_source=linkShare

  • Lance shared output from Product/Ops meetings where this set of reasons is used

     

• New Sales report for SEO (SFDC): https://leadventure1.lightning.force.com/lightning/r/Report/00O8b000009I9LtEAK/view?queryScope=userFolders

   

• We enumerated states of product/customer relationship.

  • As product or ops, the diffs between these sets are interesting (client needs fulfillment or needs support):

    • 1. No relationship

    • 2. Entitled

    • 3. Fulfilled

    • 4. Functioning

    • 5. Cancelled (reason)

    • 6. It's Complicated

• 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))

• 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

• “the complete picture” of event tracking / customer journey / funnel

  • After survey results are returned we’ll break out on this in DigMS

  • 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.

  • CMS dashboards, other products have differently-implemented and sometimes double-tracked

  • Scope includes not just the overall tracked events and data points, but the crafting of the story around this

  • Scope includes process around standardizing method of documenting events etc.

    • “Do you need reporting on this?”

    • How does your product/feature intersect with the customer purchase journey?

    • To include on LC or something upstream

  • Need to be able to assess impact of changes that are made to our conversions approach

  • To be discussed/decided by DigMS product

• Discussion: Agreeing about how to evaluate churn

  • Krissy currently uses https://app.powerbi.com/links/9Rj02wXv4e?ctid=515fce4f-ec7a-46f5-be34-13c81256a7d0&pbi_source=linkShare

    • But it looks like the definition used here is going to change soon

    • New report for this is currently being tested

    • Maybe review next week?

  • Aishwarya: There are few cancels reports created by Reina which will eventually be replaced by the cancellation report we are creating (Martial Fodouop and Abbey Middleton from Internal Systems team).

• • How do we get to a consistent set of cancellation reasons?

    • Lance shared output from Product/Ops meetings where this set of reasons is used

  • New Sales report for SEO (SFDC): https://leadventure1.lightning.force.com/lightning/r/Report/00O8b000009I9LtEAK/view?queryScope=userFolders

     

• Discussion: Customer/Product Relationship States

  • Is there anything to be done here; should we try to make sure that products are enabled to make all of these distinctions?

  • As product or ops, the diffs between these sets are interesting (client needs fulfillment or needs support):

    • 1. No relationship

    • 2. Entitled

    • 3. Fulfilled

    • 4. Functioning

    • 5. Cancelled (reason)

    • 6. It's Complicated

• 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).

SFDC-Product Groups and Sub-Groups 2024.xls.xlsx

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[Link to Product Hierarchy here]

Goal: come up with a set of site perf (just perf?) parameters that can be assessed for impact by incoming products and features

• Dependent on ongoing research into site performance analysis tools

• What’s the impact of this product or feature on these measurements?

  • What’s the impact of that impact on conversions?

• 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.

• 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)

• • Current list includes all SFDC and PowerBI reports by all authors, requester, modified by

    • But probably not the Product-based PowerBI reports

  • There should be some kind of

• •  report library? 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

• Question: As someone sending data to the Lake, how do I monitor and assess the quality of my data there?

  • Team gets alerts if data types don’t agree and stuff like that; will reach out to product manager

  • Product teams should maybe get access to the Lake

• 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.