If you use Activity Stream, chances are you saw the Customer Tags graph on the Customer Overview dashboard:
Where do Customer Tags come from?
The customer tags are derived from an algorithm that analyzes purchases, customer records, partner databases, and also data from external databases, such as a gender categorization we set based on a customer's first name.
Each tag is associated with a customer when a certain criterion is met, and it is updated in real-time.
You may find some are more intuitive than others, so here's a simple explanation of each of them:
(you can also reach out to us to get a more specific rule for the tags)
- Classification Category Tags: eg. Likes Comedy
Customer who has attended more than a few events labeled with a certain category
- Ticket Variants: (e.g. student, retiree, or family)
Customer who has bought most of their tickets with a matching variant
- Prefers Part Of Week:
The two categories are weekdays (Monday, Tuesday, Wednesday, and Thursday) and weekends (Friday, Saturday, and Sunday)
Customers who have attended a handful of events and the majority of them are happening at one of the categories mentioned above.
- Repeat Traveller:
Customer who has attended at least a few events, where all trips have been out of town and the average distance needs to also be a considerable amount from the venue.
Customer who has at least one purchase within the last months.Customer who has not bought a ticket for a few years before the newest purchase
Customer who is within a year of going inactive
If a customer has no purchases within 3 years of today
Customer who has purchased within the last few months
Second Time Buyer:
Customer who has exactly two purchases
First Time Buyer:
Customer who has exactly one purchase
Customer who has attended at least a few eventsThe spending average is a certain percentage below the average of all tickets being sold on your platform.
Customer who has attended at least a few events and has bought products.The spending average must be a certain % below the spending average of your customers
- High-Value Customer:
If a customer's total event purchases are above the vast majority of customer spending
Customer who has attended a handful of events in the pastCustomer who has never bought a ticket within a few months of the show date
Customer who has attended at least a few eventsCustomer who has attended most of their events where tickets were bought within the last few weeks of the show date
Customer who has made several purchases per year for the last three years
Single Item Buyer:
Customer who has bought a single ticket (non-zero price) to more than a few events
Invitee: (in other words free ticket holder)
Customer who has at least a handful of purchases in the last year and zero spending for the whole period
Customer who has more than a handful of purchases with the required amount of tickets
We have three different volume categories, based on the number of tickets:
Volume buyer 6+: More than 6 tickets
Volume buyer 10+: More than 10 tickets
Volume buyer 20+: More than 20 tickets
If the number of non-zero purchases is greater than 3
Very loyal customer:
If the number of non-zero purchases is greater than 6
Lapsed High-Value Donor:
Customer who has donated more than the vast majority of customers, but have not made a donation in the last year
Customer who has donated more than the vast majority of customers and the donated amount is more than 100, within the last year
Lapsed Repeat Donor:
Customer who has more than one donation but none made in the last year
Customer who has more than one donation and at least one made in the last year
Lapsed One Time Donor:
Customer who has have exactly one donation but it was made over a year ago
First Time Donor:
Customer who has have exactly one donation and it is made in the last year
Long Term Loyalty:
Customer who has at least one purchase or donation per year for the last 3/5/10 years
Because every client is different, using customer tags will allow you to filter your clients through a smaller lens, to identify their interest groups and how they buy tickets. If you'd like a few ideas on how to use them check out our articles on Buying Patterns or on Targeting Clients from 2+ Years Ago.