Segment Conditions
Combine these attributes with KPI’s to create specific segments that fit into your store’s needs!
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Subscriber Account
Cellphone
Email
Store View
Submitted entry in Form
Subscribed from Form
+ all Extra Fields
Customer Searches
Searched for…
Searched for… recently
Searched for… frequently
Frequency & Recency
Green Flying Panda allows you to decide what you consider to be frequent and recent by defining those values in the extensions configurations.
Define the number of days back you consider recent and the percentage you consider frequent!
Customer Account Attributes
Created in
Date of birth
Email
First name
Group
Last name
Middle name/initial
Name prefix
Name suffix
Panda – Customer Price Expression
Panda – Disable Customer Prices
Tax/VAT number
Attribute Prediction
When we are obligued to fill form entries related to age or gender, we might sometimes give random or false responses because we don’t see the relevance of giving that information…
With this attribute prediction feature, you are able to set those entries as optional, which reduces the amount of false answers and still gives you an idea of each customer’s gender and age!
Customer Store Activity
Account
Account registration date
Days since registration
Activity
Days since last activity
Last activity date
Number of visits
Age & Gender
Customer age
Customer date of birth
Days to anniversary
Customer gender
Current Shopping Cart
Number of days with an abandoned cart
Number of products in shopping cart
Product quantity in shopping cart
Shopping cart total
Equity Equations
{global_orders_number}
{number_completed_orders}
{order_average}
{retention_rate}
+ up to 10 custom equations!
Reviews
Days since last review
Last review date
Number of reviews
Order Stats
Number of completed orders
Number of completed orders with discount
Number of orders
Order amount for the last year
Order amount previous to the last year
Order average for the last year
Order average previous to the last year
Percentage orders with discount
Percentage of completed orders
Percentage of global average order amount
Order Dates
Average days between orders
Days since first complete order
Days since last complete order
Days with a pending payment for an order
Date of first complete order
Date of last complete order
Lifetime Sales
Lifetime sales amount
Lifetime sales average
Lifetime sales cost
Lifetime sales discount
Lifetime sales profit
Lifetime sales refunded
Lifetime sales shipping
Lifetime sales subtotal
Lifetime sales taxes
Why use segments?
Imagine you have a stock of large sized men’s clothes to sell – you can filter all men who have previously bought L sizes and create a campaign that will only be sent to them!
Previous Orders
Billing Country
Billing Postcode
Billing Region
Billing State/Province
Payment Method
Purchase Date
Shipping Method
Subtotal
Total Items Quantity
Total Weight
Product SKU
Customer Default Billing Address
Country
Postcode
Region
State/Province
Formulas
Green Flying Panda’s list of available variables – use them to define your own formulas!
Customer Variables
Days since last completed order
Days since first completed order
Days since registration
Number of reviews
Number of orders
Number of completed orders
Percentage of completed orders
Total order amount
Order average
Percentage order amount compared with global average
Order average in the past year
Orders total in the past year
Order average before the past year
Orders total before the past year
Average of days between orders
Total shipping amount
Total taxes amount
Total subtotal amount
Total discount amount
Total profit amount
Total refunded amount
Total cost amount
Global Variables
Customer retention rate
Rate of discount
Customer lifespan
Global number of orders
Global orders average
Average global number of orders
Global number of completed orders
Global orders amount
Global costs amount
Global refunded amount
Global shipping amount
Global taxes amount
Global profit amount
Periods Variables
Combined orders amount from all orders
Combined orders amount from current period
(year or month)
Combined orders amount from previous period
(year or month)
Combined orders amount from previous periods before current minus X years or months
Combined orders amount from previous after the specified year or month
Combined orders amount from the specified year
Combined orders amount from years greater than the specified year
Combined orders amount from years less than the specified year
Combined orders amount from the last X days