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Hourly Usage Patterns Using Patron Counts
Hourly Usage Patterns Using Patron Counts

Using Excel functions you can easily view your typical patron usage throughout a given day after exporting patron counts from DigiQuatics.

Josh avatar
Written by Josh
Updated over 3 years ago

To start, select your desired Location and date range to export your Patron Counts from DigiQuatics:

Next you will need to copy ALL of the data from the exported spreadsheet. Click in the upper-left corner of the first cell A1 to select all data in the sheet:

Open the DigiQuatics Patron Counts Analytics Template file. You can download that here. View the PASTE YOUR PATRON COUNTS HERE sheet if it is not selected already. Again select all of the data in the sheet by clicking to the upper-left of cell A1. Paste all of your copied data to this sheet:

View the PivotTable sheet. This is where all of the number-crunching is done on your Patron Counts data. Select any cell inside the table of data. Activate the PivotTable Analyze (or similar) tab in Excel, then click the Refresh button to update the table values.

These values by default show all exported Zones from DigiQuatics. If you would like to drill down in the data to view Patron Count Analytics by zone, click on the All filter dropdown arrow to the right of Zone. You can select or deselect any zones here:

Once you select any filters, the PivotTable values should automatically update.

If you select the Chart sheet in the Excel workbook, you will see a histogram of the Patron Count data by hour of the day (in 24-hour format since Excel works best with this). You can see the total sum of patron counts, the average patron counts, minimum, and maximum patron counts from your data:

This is particularly helpful for identifying usage patterns through the day in your exported date range. For example, we could conclude that given maximum counts, we typically only need two lifeguards scheduled before 11am, but between 11am and 4pm, we likely need three lifeguards scheduled given the lifeguard ratio at our pool.

If you drill down into specific "zones" of data by program, you may be able to conclude something like removing a program from a certain time of day given that no one shows up for water walking between 11am and 2pm if your pool space is better utilized for a more popular program.

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