👩💻 At a Glance
A transaction report contains sponsorship, donation, ticket and purchase data. You can download a transaction report via the Reports area in the Data Centre.
To get a better understanding of just your ticket data, you can filter by Product Type = Ticket. Each row in the table is a separate ticket. If one person buys three tickets, each ticket will appear as its own row in the table.
Creating a pivot table is a great way to help you summarise large datasets without complex formulas. For example, a pivot table would be helpful to see the total number of tickets a supporter has bought broken down by ticket name.
For a more in detailed breakdown of the each column in a transaction report, please take a look at Transactions Export v3.0.
How to download a transaction report
To create a transaction report:
Go to the Data Centre – Access the Data Centre via the blue navigation panel on the left of the page.
Click on the Reports tab – In the grey panel on the left of the screen, click Reports.
Select Transactions – In the Reports Builder section select Transactions.
Select report builder version – Choose V3 (latest version) of the report builder.
Select date range – Manually select the date range or click a predetermined date range offered by Social Sync.
Add campaign filter (optional) – When using report builder V3, you have the option to apply a campaign filter to help refine your data.
Download the report via the Report History table – In the Report History table at the bottom of the page, click on the three vertical dots next to the transaction report you would like to download. Click Download from the context menu.
How to filter a transaction report by ticket purchases
Once you've downloaded and opened the transaction report, you'll need to:
Filter Product Type (column P) by Ticket – All ticket purchases will display as "Ticket" in the Product Type column.
Once filtered by Product Type, helpful columns to look at include:
Platform ID (column K) – The ID unique to each transaction. If multiple tickets were purchased within the same transaction, they will have the same Platform ID.
Product ID (column O) – The ID unique to each ticket type. For example, if you offer three different ticket types for an event, there will be three Product IDs.
Product Name (column Q) – The name of the ticket purchased.
Supporter ID (column AL) – The Supporter ID of the person who purchased the ticket.
First Name (column AO) – The first name of the person who purchased the ticket.
Email (column AQ) – Email address of the person who purchased the ticket.
Using pivot tables to summarise data
Once you've filtered Product Type (column P) by Ticket, it may be easier to create a pivot table to help summarise the data.
To create a pivot table in Excel:
Select any cell in the Transactions report spreadsheet
Click Insert > Pivot Table
Choose if you want the Pivot Table to be created in a new or existing worksheet
Drag the fields you want to include in the pivot table to the relevant areas of the report (filters, columns, rows, values)
To see how many tickets each supporter has purchased, broken down by type, you would drag:
Product Type (column P) to Filters – make sure Product Type = Ticket
Product Name (column Q) to Columns
Supporter ID (column AL) OR Email (column AQ) to Rows
Product Name (column Q) to Values
To see how many tickets were purchased within the same transactions, broken down by type you would drag:
Product Type (column P) to Filters – make sure Product Type = Ticket
Product Name (column Q) to Columns
Platform ID (column K) to Rows
Product Name (column Q) to Values