Understanding Segment Conditions

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Products


Loyalty

Supported plans

Premium, Enterprise

eCommerce Platform

Shopify, Shopify Plus

Each segment is made up of one or more conditions. These conditions define who should be included and/or excluded from your segment.

You can include and/or exclude people based on the following conditions:

  • Customer behavior
    Segment based on your customer’s purchasing behavior

  • Customer attributes
    Segment based on attributes associated with your customer

  • Loyalty & Referrals
    Segment based on your customer’s loyalty program data

  • SMS (for SMSBump customers only)


    Segment based on your customer’s SMS engagement data

Data types

The options available for your segment conditions will depend on their data type.

The following data types are available:

String

A string is a plain text value. It can contain any finite sequence of characters, i.e., letters, numerals, symbols, and punctuation marks.

You can use any of the following operators for string properties:

  • Equals: Matches the specified text

  • Doesn’t equal: Does not match the specified text

  • Contains: Contains the specified text

  • Doesn’t contain: Does not contain the specified text

  • Starts with: Starts with the specified text

  • Ends with: Ends with the specified text

Date

A date is used for any date-time value. You can use a specific date or a date range:

  • Over all time: Occurred at any point in time

  • In the last: Occurred in the last X days, months, or years. Includes today and the date that is the selected number of days in the past.

  • In the next: Will occur in the next X days, months, or years. Does not include today’s date.

  • Between: Occurs between X and Y dates

  • Before: Occurs on a date prior to a selected date, excluding the date itself

  • After: Occurs after a selected date, excluding the date itself

  • On exact date: Occurs on the exact date specified

Number

A number is a numeric value without a decimal.You can use a specific number or a range of numbers:

  • Equals: Is exactly the number specified

  • Doesn’t equal: Is not exactly the number specified

  • Is less than: Is smaller than the number specified

  • Is greater than: Is greater than the number specified

  • Is at least: Is greater than or equals the number specified

  • Is at most: Is less than or equals the number specified

Boolean

The boolean data type can only represent two values: true or false.

A boolean value can be represented as:

  • Is / is not

  • Has / has not

List

A list is any array of values. It is commonly used for statuses such as store account status, payment status, etc.

Conditions

Choose from a wide range of conditions when building your segments:

Customer behavior

Customer behavior relates specifically to their purchasing behavior. You can segment based on any activity tracked by your e-commerce platform, for example, placing or abandoning an order, spending a certain amount, and the transaction status.

The following conditions and data points are available:

Condition

Description

Data type

Placed an order

The date the customer placed an order on your store

Date

Ordered product/s

The product/s the customer has already purchased

List of products

Abandoned an order

Whether or not the customer abandoned their cart

Boolean (has / has not)

Tip: You can add a filter to specify when the order was abandoned, using a specific date or date range

Number of orders

The number of orders customers made in your store (excludes canceled orders)

Number

Total spend

The amount of money the customer spent on your store in their lifetime

Number

Fulfilled order status

The status of the purchase the customer made on your store

List (fulfilled / partially fulfilled / unfulfilled)

Order payment status

The status of the customer’s payment

List (paid / partially refunded / partially paid / pending / unpaid / refunded / voided)

Customer attributes

Customer attributes is information you collected about your customer from your e-commerce platform and/or Yotpo. This includes whether they have an account with you, their account status, whether they are part of an existing segment or list, and more.

The following conditions and data points are available:

Condition

Description

Data type

Account in store

Whether or not the customer has an account on your store

Boolean (has / has not)

Created account

The date the customer created an account on your store

Date

Store account status

The status of the account in the e-commerce platform

List (enabled / disabled / invited / declined)

Gender

Determined based on the customer's name

List (male / female)

Part of a segment

Whether or not the customer is part of an existing segment

List of existing segments

Part of a list

Whether or not the customer is part of an existing list

List of existing lists

Tagged with

Tags you assigned within the e-commerce platform

String (tag name)

Loyalty & Referrals

Loyalty & Referrals relates to information about your customer’s loyalty account status. This includes whether they opted into your loyalty program and when, their points status, and more.

The following conditions and data points are available:

Condition

Description

Data type

Loyalty member

Whether or not the customer opted into your loyalty program

Boolean (is / is not)

Opted in

The date the customer opted into your loyalty program

Date

Opted out

The date the customer opted out of your loyalty program

Date

Points earned

The total number of points the customer earned from your loyalty program

Number

Points balance

The customer’s current points balance

Number

Points expiration date

The date the customer’s points will expire

Date

Total number of point redemptions

The number of times the customer has redeemed points in their lifetime

Number

Total redeemed points

The number of points the customer has redeemed for rewards in their lifetime

Number

Redeemed points

The most recent date that the customer redeemed points

Date

Current VIP tier

The customer’s current VIP tier status

String

Entered current VIP tier

The date the customer entered their current VIP tier

Date

VIP tier expiration date

The expiration date for the current VIP tier

Date

Total number of successful referrals

The number of successful referrals made by the customer in their lifetime, as defined in your Referral Program settings

Number

Referred by customer

Whether or not the customer was referred by someone else

Boolean

SMS

SMS relates to information about your customer’s SMS marketing data from SMSBump. This includes whether they’re subscribed to SMS, their conversion status, and more.

The following conditions and data points are available:

Condition

Description

Data type

SMS subscriber

Whether or not the customer is subscribed to SMS

Boolean (is / is not)

Subscribed from a specific source

Whether or not the customer subscribed from a specific source

List of existing subscription sources

Part of an SMS list

Whether or not the customer is part of an existing SMS list

List of existing SMS lists

Clicked an SMS link

The date the customer clicked a link in an SMS sent via SMSBump

Date

Converted via SMS

The date the customer made a purchase via a link sent in an SMS via SMSBump

Date

Clicked or purchased from a past marketing campaign

Whether or not the customer clicked or purchased upon receiving a campaign message

List of campaignsBoolean (campaign clicked - yes / no)Boolean (campaign converted - yes / no)

Reviews

Reviews relates to information about your customers' Reviews data. This includes data about the reviews they've submitted, including the number of reviews, the average star rating, and more.

The following conditions and data points are available:

Condition

Description

Data type

Submitted a review

Whether or not the customer submitted a review within a timeframe

Date
Tip: You can add the following filters to specify the review that was submitted:- Product reviewed- Star rating- Sentiment- Channel- Review source

Number of reviews

The number of reviews submitted by the customer

Number
Tip: You can add the following filters to specify the type of reviews:- Product reviews- Site reviews- Positive reviews- Negative reviews

Average reviews sentiment

The average sentiment of reviews submitted by the customer

List
Tip: You can add the following filters to specify the type of reviews:- Product reviews- Site reviews

Average reviews star rating

The average star rating of reviews submitted by the customer

Number
Tip: You can add the following filters to specify the type of reviews:- Product reviews- Site reviews

Topics mentioned in reviews

The topics mentioned in reviews submitted by the customer

List

Number of uploaded media

The number of uploaded media by the customer

Number
Tip: You can add the following filters to specify the type of media:- Video- Image

Predictive data

We use predictive analytics to predict the future behavior of your customers based on their historical purchases and activity. Learn more about Predictive data points

Use the data points below in your segmentation to expose valuable engagement opportunities.

To benefit from predictive data, you’ll need the following:

  • An ecommerce integration with Shopify, BigCommerce, or Magento OR an integration that syncs orders via our Core API

  • At least 6 months of order history

  • At least 500 customers who made a purchase more than 3 months ago

The following conditions and data points are available:

Condition

Description

Data type

Likely to purchase again

The likelihood of a customer making a future purchase within the next 90 days based on predictive analytics.
The score ranges between 0 and 3:- 0 Insufficient data- 1 Low- 2 Medium- 3 High

List (Insufficient Data, Low, Medium, High)

Churn risk

The likelihood of a customer churning within the next 90 days based on predictive analytics.
The score ranges between 0 and 4:- 0 Insufficient Data- 1 Low- 2 Medium- 3 High- 4 Churned (customers who have not made a purchase in over a year)

List (Insufficient Data, Low, Medium, High, Churned)

AND/OR connectors

AND connector

Use the AND connector between your conditions to make your segment more exclusive. When you use an AND connector, each condition must be met in order for the person to be included. If someone meets one condition but does not meet the other, they will be excluded from your segment.

Example:

In the example segment below, the customer must have placed at least 2 orders AND placed an order within the last 30 days. If someone has done only one of these actions, they will not be included in your segment. Only those who have done both actions will appear within this segment.

Segment conditions - AND example

OR connector

Use the OR connector between your conditions to make your segment more inclusive. When you use an OR connector, the person must meet one of the joined conditions in order to be included. If someone meets one condition but does not meet the other, they will still be included in your segment.

Example:

In the example below, the customer must have opted into your loyalty program OR ordered a product at least once over all time. If someone has done neither or only one of these actions, they will not be included in your segment. However, anyone who has done at least one of the actions will appear in this segment.

Segment conditions - OR example