On the first tab of your criteria, narrow down your database by the events bookers attended. The options are;

• Performance Date Range  - Narrow down when bookers had to attend. This can be in the past or future. They could have been to any event but it must have been in this date range.
• Classification Codes - Your events are likely to be coded within your ticketing system. For example, by touring company or genre. These are all sorted under the Classification Codes filter. You can filter bookers by events they attended using these codes.
• Event Bands - If you don't have classifications in your ticketing system you can create them in Vital Statistics using event bands.
• Events - Select bookers by specific events attended. They can be in the past or future. If you select more than one event, the booker must have attended at least one of them. They can potentially have attended all of them too!
• Location - If your venue has more than one organisation, such as a cinema and a theatre space you can select bookers by just the location. This is also useful is you sell for another space and want to select those bookers.
• Location Bands - Similar to event bands you can create location bands in Vital Statistics. This is useful is you have data feeding into Vital Statistics from your new and old ticketing system.
• Performance Day of Week - Narrow down when bookers had to attend. You could compare week bookers by weekend bookers.
• Performance Time of Day - Narrow down when bookers had to attend. You could specify matinee bookers.
• Performances - Narrow down when bookers attended to a specific performance rather than the full event run.

On the second tab of your criteria, narrow down your database by the behaviour of the bookers. The options are;

• Transaction Date Range - Narrow down when bookers booked tickets. This can be in the past of future. They could have booked to any event but the booking must have been in this date range.
• Booking days before Performance - Specify how far in advance a booker booked their tickets. It is important to reward early bookers and so you can mail these bookers separately.
• Discount Bands - Similar to Location bands and event bands. You may have a lot of concession codes that you want to group. For example, mailing everyone who has used a discount code that has been active in the last year.
• Discount Types - Narrow down your bookers by specific discount codes they used when purchasing their tickets. Such as Over 60's discount.
• First Time Attenders - Narrow down your bookers by those who are first timers to the venue.
• Group Size - Narrow down your bookers by the number of tickets they purchased.
• Membership at Time of Booking - If we pull through your memberships you can specify those bookers who are members.
• Price Bands - Narrow down your bookers by where they sat within the venue.
• Sales Channel - Narrow down your bookers by specific sales channel they used when purchasing their tickets. Such as online.
• Sales Channel Band - You can group sales channels into bands.
• Spend - In conjunction with the events they attended that you specified in the first tab
• Visits - In conjunction with the events they attended that you specified in the first tab

On the third tab of your criteria, narrow down your selection further by the bookers attributes. The options are;

• Address Valid - When creating a mailing list you can narrow down to those bookers who have filled in the address fields. This is not a Postal address validation.
• Classified Customers - Your customers are likely to be coded within your ticketing system. For example, by genre preferences. These are all sorted under the Classied Customers filter. You can filter bookers using these codes.
• Country - Filter customers by their address, specifically the Country field.
• Current Membership - If we pull through your memberships you can specify those bookers who are current members.
• Data Capture - Narrow down your bookers by those who have provided you data at the point of transaction.
• Data Protection - Narrow down your bookers by their data protection status
• Email Valid - When creating a mailing list you can narrow down to those bookers who have filled in the email adress field. This is not a verified email.
• Mailing Frequency - When using Vital Statistics for Campaigns you can then create segments in which you remove bookers who have regularly received communication in the recent past.
• Mailings - When using Vital Statistics for Campaigns you can then create segments in which you remove bookers who have received specific communication in the recent past.
• Postal Groups - Create postal groups and narrow down your bookers by their postcode.