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318 Points

Fri, Jul 12, 2019 7:01 PM

Prepping for Partner/Customer QBR's with GPX Data

I'm super excited to share this use case I worked on today, because it pulls from several different part of the data side of GPX.

Context: One of our Strategic Partnership Managers (this role is similar to an Account Manager type for a large, high-touch customer) was prepping for the QBR with one of her accounts this morning. We worked together to find some GPX data to facilitate the conversation.

I took the approach of having my colleague ask me the questions she was trying to answer, then we explored GPX to answer those questions.

Questions:

  • 1: The last 2 quarters, what paths did this partner's users take in our product?

    • PX Feature: Path Analyzer

    • Filters:

      • Account Filter > Integration Type is [partner name] (this is a custom attibrute in GPX for us, could be filtered to account name)

    • Date Range for the Path Analyzer:

      • 1 report set to 1/1/19-3/31/19

      • 1 report set to 4/1/19-6/30/19

      • Sidenote: It would be nice to be able to see Path Analyzer data for more than 3ish months at a time.

    • Scope = User

  • 2: What about the partner's users who are new to our product?

    • PX Feature: Path Analyzer

    • Filters:

      • Account Filter > Integration Type is [partner name] (this is a custom attibrute in GPX for us)

      • Users Filter > Signed Up:

        • Between 1/1/19 - 3/31/19

        • Between 4/1/19-6/30/19

    • Date Range for the Path Analyzer:

      • 1 report set to 1/1/19-3/31/19

      • 1 report set to 4/1/19-6/30/19

    • Scope = User

    • Note: My colleague was a bit confused about the difference between the date ranges at the tope of the Path Analyzer and the date ranges you can apply to user signups in the filters. Here's how I explained it:

      • Date range at the top of the Path Analyzer = time filter for the activity displayed in the report

      • Date range within the user signup filter = time filter for the users who signed up during that timeframe

      • Therefore, by applying a signup time filter with the same activity time filter, I am asking the question:

        • For users who signed up this quarter, what are the paths they took in our product this quarter?

      • If I applied a signup filter for users who signed up in Q1 2019 with an activity filter for Q2 2019, I am asking the question:

        • For users who signed up last quarter, what are the paths they took after being in our product for a few months?

  • 3: How many new users has this partner had in the last 6 months?

    • PX Feature: Custom Dashboards (you could do this without a custom dashboard, but I took the opportunity to create a CDB since she would likely be referring to it in the future)

    • Widget: New Users

    • Filters: Monthly / Last 6 Months

    • Settings: Added a preset Public Filter for this partner, but this could easily be an account name or something like that

  • 4: How many monthly active users has this partner had for the last 6 months?

    • PX Feature: Custom Dashboards

    • Widget: Active Users

    • Filters: Monthly / Last 6 Months

  • 5: What is the overall level of activity of this partner's users in the last 6 months?

    • PX Feature: Custom Dashboards

    • Widget: Events Recorded

    • Filters: Monthly / Last 6 Months

    • Note: The way I've explained "events" to my colleagues is that they are page views / button clicks (I know it goes beyond this, but that's the best way I have to describe our current view), and a report of total events over time is a good way to see levels of overall activity. For example, we found that our events recorded for the last 6 months for this partner increased 31.6% compared to the preceding 6 months, which is a good indicator of increasing activity levels. Anyone have better ideas on how to explain that?

Here is the partner-customized dashboard for questions 3, 4, and 5. I'm sure we will add more to this dashboard later!

  • 6: What do the most frequent users do when they are in our product?

    • PX Feature: Audience Explorer + Analytics > Features > Adoption

    • Audience Explorer:

      • Filter:

        • Account Filter > Integration Type = [partner name] (this is a custom attibrute in GPX for us, could be filtered to account name)

      • Sort by: Number of visits Z>A

      • I saw that for this partner, the top 13 visitors had been into our product more than 100 times. So I used that as my parameter to define a frequent user. I'm sure this could be defined in more nuanced ways, but that's what I did for now.

      • I kept this view open, then opened a new window on my other monitor.

    • Analytics > Features > Adoption:

      • Filters:

        • Account Filter > Integration Type = [partner name]

        • Users Filter (set to OR) > User Identifier is:

          • Here I copied and pasted the user identifiers for the top 13 users from the view in Audience Explorer.

      • Date Range: Monthly / Last 6 months

      • Measured by Events Grouped by Features

      • Note: it would be nice to be able to filter by a user's number of visits. I noticed that you can do this in Segments, but not on the reports. This could be very useful in reporting so I can filter by those thresholds.

    • Here is the final result:

All that to say, we were able to put together some valuable data very quickly for this partner QBR. The custom dashboards are already a lifesaver when it comes to helping my colleauges use the product. It helps lessen the initial learning curve by giving them somewhere to look that I can customize for them while they get their feet wet with GPX.

Hope this is helpful to others!