Booking churn Subscribers in Analytics?

Hi, 

We are looking into the booking churn for our subscribers at Malmo Opera.

Parameters we want to look into on a seasonal level:

  • How many are returning subscribers season after season?

             In what packages? Other patterns?

  • How many are new subsribers per season?

             In what packages? Other patterns?

  • How many drop offs per season?

             In what packages? Other patterns for drop offs?

Anyone got any tips and tricks on how get started with this in Analytics, reports or in List Manager/ Extraction Manager?

We dont know if Analytics is the right place for this since there is no Data set for Subscribers?

 

Thanks a lot for your help!

Josefin

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  • Hi Josefin,

    This is such a big, interesting topic. The variations in what define new, returning, lapsed, and churned (or drop offs) varies widely, as does the scope of the patrons to be considered in those buckets (everyone, or only subscribers, or any buyer within a certain season type).

    I'm going to see if I can scratch the surface a bit from the Analytics side to start, where we can pull together the overall numbers. This NewReturnLapseandChurn.dash dashboard is an exercise I've drafted in calculating these values in Analytics in such a way as to respect any dashboard filters you may apply in order to impact the scope of the buckets (e.g. only subscribers). The dashboard outlines some assumptions around the calculations for who is new verses lapsed, etc., which is logic you can alter once you've been through the exercises and translate this into your own business rules.

    This dashboard is part of a greater whole, and hard codes the fiscal years into the value formulas, whereas typically I would use relative fiscal year values so that each year's change over would not require editing all the formulas in the dashboard.

    I'm also attaching NewReturnLapseandChurnChart.dash shown below as an example of what you can do with these numbers. The dashboard has default filters for

    • Is Package Flag, to limit the results to just package buyers, non-package buyers, or everyone.
    • Season Type, to limit to only certain types of yearly seasons.

    One could add any other applicable filter, and the new, return, lapsed, and churn values will respect it.

    Best,
    Chris

  • Hi again Chris,

    Thanks again for this dashboard.

    It is really helpful in this case!


    Just so that I am clear on what I am looking at here. What is the difference between lapsed and churned in your dashboard?

    Thanks a lot för your help,

    Josefin

  • Hi Josefin,

    Thank you for asking. In the context of THIS sample, the logic is defined as follows:

    • New = constituents who attended in the current year, and not in the prior 2 years
    • Returning = constituents who attended in current year, and (at any point) in the prior 2 years
    • Lapsed = constituents who have not attended in the current year, and did attend in the season 1 year prior
    • Churned = constituents who have not attended in the current or prior 1 year, and did attend in the season 2 years prior

    Said another way, using FY 2020 as the current FY:

    • New = attended in 2020 and not 2019 nor 2018
    • Returning = attended in 2020 and in 2019 or 2018
    • Lapsed = attended in 2019 and not in 2020
    • Churned = attended in 2018 and not in 2019 nor 2020

    I tried to document in the dashboard itself along with the Venn Math used to calculate the buckets so that it can be extended for other versions of these buckets based on different business rules. 

Reply
  • Hi Josefin,

    Thank you for asking. In the context of THIS sample, the logic is defined as follows:

    • New = constituents who attended in the current year, and not in the prior 2 years
    • Returning = constituents who attended in current year, and (at any point) in the prior 2 years
    • Lapsed = constituents who have not attended in the current year, and did attend in the season 1 year prior
    • Churned = constituents who have not attended in the current or prior 1 year, and did attend in the season 2 years prior

    Said another way, using FY 2020 as the current FY:

    • New = attended in 2020 and not 2019 nor 2018
    • Returning = attended in 2020 and in 2019 or 2018
    • Lapsed = attended in 2019 and not in 2020
    • Churned = attended in 2018 and not in 2019 nor 2020

    I tried to document in the dashboard itself along with the Venn Math used to calculate the buckets so that it can be extended for other versions of these buckets based on different business rules. 

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