Understanding Segment Conditions
Understanding Segment Conditions
Article Summary
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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 true 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.
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.
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