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Seat Map Report/Analysis Help Needed

Jennifer Hubbartt
$organization

Hello! I'm looking to analyze the instances that each individual seat is sold and it's average ticket price sold throughout the run of a production. For instance, I'd like to know for all performances of Production A, how many times Section 1, Row B, Seat 5 was sold, and the average ticket price sold among those instances. Ideally I would set this up in Analytics so I can then filter by constituent and get to know who is purchasing specific seats and the constituent(s) demographics. My feeble attempt has resulted in incorrect data.

Has anyone pulled this information with success, and could please lend your advice? I'm hoping to use this information to make informed decisions on scale of hall and optimized inventory management.

Thank you!

  • $organization

    I am in the process of doing something similar for the Santa Barbara Symphony. I haven't yet created a map in Analytics, but I was able to create a pivot table to see how each seat was selling.

    For the venue we use, Zone, then the seat row and number were enough for the Row information for a Pivot: (you may or may not also need Section?)

    Rows
    Zone
    Seat Row
    Seat Num

    For what you're looking for, these could be your values.

    Values
    Times Sold* — COUNT([Perf Seat Key])
    Average** — [Total Ticket Paid Amount]/[# of Unique Performance ID]

    * This is actually how many times the seat was filled so comps count. You could redo this to filter comps out.
    ** This is an average of the total paid divided by all performances regardless of whether they sold.

    Using the Jump to Dashboard for _Constituents should work to see who is in these seats.

    In addition to what you're looking for, I also exported the total Ticket Paid Amount and the total Seat Home Base Value. This shows the total revenue on each seat vs. the potential revenue if each seat sold at full price (for us that means even subscription tickets are "lost" income since they are less than full price).

    At this point I exported to Excel (although I could have kept going in Analytics) to see % of revenue on each seat vs. its potential and used Excel's color scales to see how "red" our lowest-earning seats were last season. Mid-way through this season we will see if these seats are still a problem and potentially re-price/re-zone.

    -- Mike