Understanding Segment Conditions

      Understanding Segment Conditions


        Products


        Loyalty
        Supported plans

        Platinum, 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:

        ConditionDescriptionData type
        Placed an orderThe date the customer placed an order on your storeDate
        Ordered product/sThe product/s the customer has already purchasedList of products
        Abandoned an orderWhether or not the customer abandoned their cartBoolean (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 ordersThe number of orders customers made in your store (excludes canceled orders)Number
        Total spendThe amount of money the customer spent on your store in their lifetimeNumber
        Fulfilled order statusThe status of the purchase the customer made on your storeList (fulfilled / partially fulfilled / unfulfilled)
        Order payment statusThe status of the customer’s paymentList (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:

        ConditionDescriptionData type
        Account in storeWhether or not the customer has an account on your storeBoolean (has / has not)
        Created accountThe date the customer created an account on your storeDate
        Store account statusThe status of the account in the e-commerce platformList (enabled / disabled / invited / declined)
        GenderDetermined based on the customer's nameList (male / female)
        Part of a segmentWhether or not the customer is part of an existing segmentList of existing segments
        Part of a listWhether or not the customer is part of an existing listList of existing lists
        Tagged withTags you assigned within the e-commerce platformString (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:

        ConditionDescriptionData type
        Loyalty memberWhether or not the customer opted into your loyalty programBoolean (is / is not)
        Opted inThe date the customer opted into your loyalty programDate
        Opted outThe date the customer opted out of your loyalty programDate
        Points earnedThe total number of points the customer earned from your loyalty programNumber
        Points balanceThe customer’s current points balanceNumber
        Points expiration dateThe date the customer’s points will expireDate
        Total number of point redemptionsThe number of times the customer has redeemed points in their lifetimeNumber
        Total redeemed pointsThe number of points the customer has redeemed for rewards in their lifetimeNumber
        Redeemed pointsThe most recent date that the customer redeemed pointsDate
        Current VIP tierThe customer’s current VIP tier statusString
        Entered current VIP tierThe date the customer entered their current VIP tierDate
        VIP tier expiration dateThe expiration date for the current VIP tierDate
        Total number of successful referralsThe number of successful referrals made by the customer in their lifetime, as defined in your Referral Program settingsNumber
        Referred by customerWhether or not the customer was referred by someone elseBoolean

        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:

        ConditionDescriptionData type
        SMS subscriberWhether or not the customer is subscribed to SMSBoolean (is / is not)
        Subscribed from a specific sourceWhether or not the customer subscribed from a specific sourceList of existing subscription sources
        Part of an SMS listWhether or not the customer is part of an existing SMS listList of existing SMS lists
        Clicked an SMS linkThe date the customer clicked a link in an SMS sent via SMSBumpDate
        Converted via SMSThe date the customer made a purchase via a link sent in an SMS via SMSBumpDate
        Clicked or purchased from a past marketing campaignWhether or not the customer clicked or purchased upon receiving a campaign messageList 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:

        ConditionDescriptionData type
        Submitted a reviewWhether or not the customer submitted a review within a timeframeDate
        Tip: You can add the following filters to specify the review that was submitted:- Product reviewed- Star rating- Sentiment- Channel- Review source
        Number of reviewsThe number of reviews submitted by the customerNumber
        Tip: You can add the following filters to specify the type of reviews:- Product reviews- Site reviews- Positive reviews- Negative reviews
        Average reviews sentimentThe average sentiment of reviews submitted by the customerList
        Tip: You can add the following filters to specify the type of reviews:- Product reviews- Site reviews
        Average reviews star ratingThe average star rating of reviews submitted by the customerNumber
        Tip: You can add the following filters to specify the type of reviews:- Product reviews- Site reviews
        Topics mentioned in reviewsThe topics mentioned in reviews submitted by the customerList
        Number of uploaded mediaThe number of uploaded media by the customerNumber
        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:

        ConditionDescriptionData type
        Likely to purchase againThe 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 riskThe 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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