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Counting unique individuals for which tickets are purchased at a multi-venue General Admission destination

Bob Oliver
$organization

Hello:

We are a multi venue general admission destination as the questions hints. I'm trying to find a way in analytics to determine (approximately) the number of unique ticketed individuals an order or collection of orders represent. For example,an individual order could include:

  • 3 tickets for the castle
  • 2 for the tower
  • 2 for one of the galleries.

Whilst this could represent tickets for anything from 3 to 7 separate individuals, a reasonably safe assumption is that it is 3 individuals, but one of them has decided not to go tower and has no interest in art. I'm struggling to find a way in analytics to aggregate ticket counts per line to return just the maximum number of tickets on any 1 line in the order (which then I could sum per month, etc) so that I can then use my assumption. As anyone with the same issue solved this?

We do offer packages that are easier to work out, but many tickets sales are still individual tickets. We also don't yet have NSCAN - so stuck trying to solve it as above.

Thanks,

Bob.

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  • $organization
    Hello,
     
    Actually think I’ve got it. Didn’t realise MAX had two modes of operation, including one whereby you can pass in a group by criteria.
     
    So
     
    max([Performance Date and Code],sum([Ticket Count])) seems to work as below, first showing the group by and then without. Will need to test behaviour in additional aggregations. Coming back the next day and looking again often seems the best way with Analytics.
     
     
    This I hope the business will agree is a fair approximation of total individuals buying tickets.
     
    Thanks all!
     
    Bob.
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  • $organization
    Hello,
     
    Actually think I’ve got it. Didn’t realise MAX had two modes of operation, including one whereby you can pass in a group by criteria.
     
    So
     
    max([Performance Date and Code],sum([Ticket Count])) seems to work as below, first showing the group by and then without. Will need to test behaviour in additional aggregations. Coming back the next day and looking again often seems the best way with Analytics.
     
     
    This I hope the business will agree is a fair approximation of total individuals buying tickets.
     
    Thanks all!
     
    Bob.
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