Shopify-based customer segment filters
Use this reference guide to understand the filter names, operators, and values that are used to build customer segments that are based on the default Shopify filters.
On this page
- Abandoned checkout date
- Anniversary
- Amount spent
- Cities
- Companies
- Countries or regions
- Created by app id
- Customer account status
- Customer added date
- Customer email domain
- Customer language
- Customer tags
- Customer within distance
- Email events
- Email subscription status
- First order date
- Last order date
- Number of orders
- Orders placed
- Predicted spend tier
- Product subscription status
- Products purchased
- RFM group
- SMS subscription status
- States or provinces
- Store credit accounts
- Storefront events
Abandoned checkout date
Name: abandoned_checkout_date
Includes customers by the date that they last abandoned their cart.
Operators |
Exactly on date: = Not on date: != On or before date: <= Before date: < On or after date: >= After date: > Between dates: BETWEEN {date1} AND {date2} Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values | |
Format |
Absolute date: YYYY-MM-DD Date offset examples: -4w , -10y Named date:
|
Example |
Include customers who last abandoned their cart within the last week:abandoned_checkout_date >= 7_days_ago Include customers who last abandoned their cart within the last eight months: abandoned_checkout_date > -8m
|
Notes | Date values are based on entire days and depend on which time zone your store is in. |
Anniversary
Name: anniversary
Includes customers by the date of the event associated with the date parameter.
Function parameters |
Specify the event that you want to filter on. For example: 'metafields.facts.birth_date'
|
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Operators |
MATCHES : Parameter is true.NOT_MATCHES : Parameter is false.IS NULL : Parameter doesn't exist.IS NOT NULL : Parameter exists.For dates, the available operators include: Is equal to: = Is not equal to: != Greater than: > Smaller than: < Smaller or equal to: <= Greater or equal to: >= Between: BETWEEN
|
Values |
date
|
Format |
Absolute date: YYYY-MM-DD Date offset examples: +4w , +3m Named dates or ranges:
|
Example |
Include customers with a birthday in the next 30 days:anniversary MATCHES ('metafields.facts.birth_date') BETWEEN today AND +30d
|
Notes |
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Amount spent
Name: amount_spent
Includes customers based on how much money they have spent in your store.
Operators |
Is equal to: = Is not equal to: != Greater than: > Smaller than: < Smaller or equal to: <= Greater or equal to: >= Between: BETWEEN
|
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Values | |
Format |
Number range: # AND # Number: # Decimal number: The decimal point (.) is used as the decimal separator. Thousand separators, such as commas or spaces, aren't accepted. Language-specific formatted numbers aren't accepted. |
Example |
Include customers who have spent 1 to 999.99 in your store:amount_spent BETWEEN 1 AND 999.99
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Notes |
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Cities
Name: customer_cities
Includes customers who have an address in the specified city. Customers who have multiple addresses might be included in more than one customer segment that uses this filter.
Operators |
Contains this exact city: CONTAINS Doesn't contain this exact city: NOT CONTAINS Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values | |
Format |
countryCode-regionCode-cityCode
|
Example |
Include customers who have an address in New York City:customer_cities CONTAINS 'US-NY-NewYorkCity'
|
Notes | To find a city, you can start typing the name of the city, and then select the appropriate value from the list that's displayed. |
Companies
Name: companies
Includes customers from companies that have been configured as B2B customers.
Operators |
Contains this exact company ID: CONTAINS Doesn't contain this exact company ID: NOT CONTAINS Doesn't exist: IS NULL Exists: IS NOT NULL
|
---|---|
Values | Company ID |
Format | |
Example |
Is a B2B customer:companies IS NOT NULL Isn't a B2B customer: companies IS NULL Includes customers who are affiliated with a specific company: companies CONTAINS 3778915041302 |
Notes |
|
Countries or regions
Name: customer_countries
Includes customers who have an address in the specified country or region. Customers who have multiple addresses might be included in more than one customer segment that uses this filter.
Operators |
Contains this exact location: CONTAINS Doesn't contain this exact location: NOT CONTAINS Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values | Use the ISO two-letter country code. |
Format | |
Example |
Include customers who have an address in the United States:customer_countries CONTAINS 'US'
|
Notes | To find a country, you can start typing the name of the country, and then select the appropriate value from the list that's displayed. |
Created by app id
Name: created_by_app_id
Includes customers who have been created by the specified app.
Operators |
Is equal to: = Isn't equal to: !=
|
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Values | The ID of the app to segment on. |
Format | App ID |
Example |
Include customers who have been created in the Shopify admin:created_by_app_id = 1830279
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Notes |
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Customer account status
Name: customer_account_status
Includes the customers who have the specified customer account status.
Operators |
Is equal to: = Is not equal to: !=
|
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Values |
Declined: 'DECLINED' The customer was invited to create an account, but declined.Disabled: 'DISABLED' The customer has not created an account, or your store is using the new customer accounts.Enabled: 'ENABLED' The customer created an account.Invited: 'INVITED' The customer has been invited to create an account, but has not yet accepted or declined.
|
Format | |
Example |
Include customers who have been invited to create an account, but declined:customer_account_status = 'DECLINED'
|
Notes |
Customer added date
Name: customer_added_date
Includes customers based on the date that they were added to your store.
Operators |
Exactly on date: = Not on date: != On or before date: <= Before date: < On or after date: >= After date: > Between dates: BETWEEN {date1} AND {date2}
|
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Values | |
Format |
Absolute date: YYYY-MM-DD Date offset examples: -4w , -10y Named date:
|
Example |
Include customers who were added within the last week:customer_added_date >= 7_days_ago Include customers who were added within the last eight months: customer_added_date > -8m Include customers who were added during a specific date range: customer_added_date BETWEEN 2022-12-01 AND 2022-12-31
|
Notes | Date values are based on entire days and depend on which time zone your store is in. |
Customer email domain
Name: customer_email_domain
Includes customers whose email address belongs to the specified domain. The domain name is the part of the email address after the @
symbol, for example: gmail.com
.
Operators |
Is equal to: = Isn't equal to: != Doesn't exist: IS NULL Exists: IS NOT NULL
|
---|---|
Values |
The following domain names are offered as suggestions. You're not limited to these domain names. You can manually enter any other valid domain names:
|
Format | |
Example |
Include customers whose email domain is shopify.com:customer_email_domain = 'shopify.com'
|
Notes |
Customer language
Name: customer_language
Includes customers based on the language that the customer uses to communicate with your store.
Operators |
Is equal to: = Isn't equal to: != Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values | Use the ISO 639-1 two-letter language code. |
Format |
The following values are examples of some common ISO language codes. Your data isn't limited to these language codes. You can manually enter any other valid language codes, but the values that are offered to you as suggested values in the editor are the only ones that are available in your customer data.
|
Example |
Include customers who communicate with your store in English:customer_language = 'en' Exclude customers who communicate with your store in Canadian English: customer_language != 'en-CA'
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Notes |
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Customer tags
Name: customer_tags
Includes customers based on their tags.
Operators |
Contains this exact tag: CONTAINS Doesn't contain this exact tag: NOT CONTAINS Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values | The name of a customer tag. |
Format | |
Example |
Include customers who have the GoldStatus tag:customer_tags CONTAINS 'GoldStatus'
|
Notes |
Tags are not case sensitive. Learn more about tags and their considerations. |
Customer within distance
Name: customer_within_distance
Includes customers within a specified distance of a saved location.
Function parameters |
You can use only one distance parameter for each filter.coordinates (required): Use this parameter to specify the pin location you want to use to create your segment. distance_km (required): Use this parameter to specify the distance radius you want to search within for customers.distance_mi (required): Use this parameter to specify the distance radius you want to search within for customers. |
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Operators |
MATCHES : Parameter is true.NOT_MATCHES : Parameter is false.IS NULL : Parameter doesn't exist.IS NOT NULL : Parameter exists. |
Value | |
Format |
Supported format for coordinates :
Supported format for coordinates (latitude, longitude): #
Supported format for distance_mi , distance_km :
#
|
Example |
This filter requires coordinates and one distance parameter to be valid. Filter customers who have an address within 10 miles of coordinates (45.419190, -75.696727): customer_within_distance MATCHES (coordinates = (45.419190, -75.696727), distance_mi = 10 ) Filter can be used in conjunction with other filters to narrow your customer list down even further. For example: Filter customers who have address within 20 kilometers of coordinates (43.634,-79.412) and have placed at least one order: customer_within_distance MATCHES (coordinates = (43.634,-79.412), distance_km = 20 ) AND number_of_orders > 0
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Notes |
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Email events
Name: shopify_email.EVENT
Includes customers based on selected email events. Supported events (EVENT
) include the following:
- Bounced:
bounced
- Clicked:
clicked
- Delivered:
delivered
- Marked as spam:
marked_as_spam
- Opened:
opened
- Unsubscribed:
unsubscribed
Function parameters |
activity_id (optional): Use this parameter to select the marketing activity ID that you want to filter.count (optional): Use this parameter to specify the number of times an email event occurred.date (optional): Use this parameter to specify the date of the event. |
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Operators |
MATCHES : Used when the event has happened.NOT_MATCHES : Used when the event didn't happen.IS NULL : Parameter doesn't exist.IS NOT NULL : Parameter exists.For dates, the available operators include: Is equal to: = Isn't equal to: != Greater than: > Smaller than: < Smaller or equal to: <= Greater or equal to: >= Between: BETWEEN
|
Value | |
Format | Supported formats for activity_id :
= (single value)IN : A set of comma-separated values with implicit "OR", wrapped in parentheses. For example: (activity_id IN 1, 2, 3) . There is a limit of 500 activity IDs in a set.Supported date formats for date :YYYY-MM-DD
The named dates are default values and can't be changed. For custom dates, use a date offset. Email events are available for the last 26 months, with data starting on March 2022. Supported formats for count :#
|
Example |
Specify whether an email event happened using a MATCHES or NOT MATCHES operator:shopify_email.opened MATCHES (activity_id = 135195754518) shopify_email.opened NOT MATCHES (activity_id = 135195754518) Use the parameter activity_id to specify the marketing activity ID that you want to filter on:shopify_email.delivered MATCHES (activity_id = 135195754518) Use the parameter date and the operator >= to specify a start date for an email event:shopify_email.delivered NOT_MATCHES (activity_id = 135195754518, date >= 2022-01-01) Use the parameter date and the operator <= to specify an end date for an email event:shopify_email.delivered MATCHES (activity_id = 135195754518, date <= 2022-01-01) Use the parameter date and the operator BETWEEN to specify both a start and end date for an email event:shopify_email.bounced NOT_MATCHES (activity_id = 135195754518, BETWEEN -12m AND today)
|
Notes |
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Email subscription status
Name: email_subscription_status
Includes customers based on whether they're subscribed to your marketing email.
Operators |
Is equal to: = Isn't equal to: != Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values |
Not subscribed: 'NOT_SUBSCRIBED' The customer hasn't subscribed to your marketing email.Subscribed: 'SUBSCRIBED' The customer is subscribed to your marketing email.Pending: 'PENDING' The customer is in the process of subscribing to your marketing email.Invalid: 'INVALID' The customer’s email address marketing state is invalid.Unsubscribed: 'UNSUBSCRIBED' The customer has unsubscribed from your marketing emails.Redacted: 'REDACTED' The customer’s email address has been redacted.
|
Format | |
Example |
Include customers who have subscribed to your email marketing:email_subscription_status = 'SUBSCRIBED'
|
Notes |
First order date
Name: first_order_date
Includes customers who placed their first order on the date specified.
Operators |
Exactly on date: = Not on date: != On or before date: <= Before date: < On or after date: >= After date: > Between dates: BETWEEN {date1} AND {date2} Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values | |
Format |
Absolute date: YYYY-MM-DD Date offset examples: -4w , -10y Named date:
|
Example |
Include customers whose first order was placed since last week:first_order_date >= 7_days_ago Include customers whose first order was placed since eight months ago: first_order_date > -8m
|
Notes | Date values are based on entire days and depend on which time zone your store is in. |
Last order date
Name: last_order_date
Includes customers who placed their last order on the date specified.
Operators |
Exactly on date: = Not on date: != On or before date: <= Before date: < On or after date: >= After date: > Between dates: BETWEEN {date1} AND {date2} Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values | |
Format |
Absolute date: YYYY-MM-DD Date offset examples: -4w , -10y Named date:
|
Example |
Include customers whose last order was placed since last week:last_order_date >= 7_days_ago Include customers whose last order was placed since eight months ago: last_order_date > -8m
|
Notes | Date values are based on entire days and depend on which time zone your store is in. |
Number of orders
Name: number_of_orders
Includes customers based on the number of orders that they have placed in your store.
Operators |
Is equal to: = Isn't equal to: != Greater than: > Smaller than: < Smaller or equal to: <= Greater or equal to: >= Between: BETWEEN
|
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Values | The value that you enter must be a whole number. |
Format |
Number range: # AND # Number: #
|
Example |
Include customers who have placed more than 10 orders:number_of_orders > 10
|
Notes |
BETWEEN includes both the start and the end values. For example, number_of_orders BETWEEN 1 AND 100 includes customers who have placed at least 1 order and as many as 100 orders. |
Orders placed
Name: orders_placed
Includes customers who placed orders or spent a certain amount during a specified date range.
Function parameters |
app_id (optional): Use this parameter to specify which app created the order.location_id (optional): Use this parameter to specify which location the order was placed from.count (optional): Use this parameter to specify the exact number of times an order was placed.amount (optional): Use this parameter to specify the exact amount spent on an order.sum_amount (optional): Use this parameter to specify the amount spent on all orders.date (optional): Use this parameter to specify a date for the event. |
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Operators |
MATCHES : Parameter is true.NOT_MATCHES : Parameter is false.IS NULL : Parameter doesn't exist.IS NOT NULL : Parameter exists.For dates, the available operators include: Is equal to: = Isn't equal to: != Greater than: > Smaller than: < Smaller or equal to: <= Greater or equal to: >= Between: BETWEEN
|
Values | |
Format |
Supported formats for count , amount , and sum_amount :Number: # Supported formats for date :Absolute date: YYYY-MM-DD Date offset examples:
|
Example |
Specify whether an order has been placed using a MATCHES or NOT_MATCHES operator:orders_placed MATCHES () orders_placed NOT_MATCHES () Filter customers that placed more than 3 orders (inclusive) in the last 6 months: orders_placed MATCHES (count >= 3, date >= -6m) Filter customers that spent more than $1000 (inclusive) in the last 90 days: orders_placed MATCHES (sum_amount >= 1000, date >= -90d) Filter customers that spent less than $100 (inclusive) in the last 7 days: orders_placed MATCHES (sum_amount <= 100, date >= -7d) Filter customers that spent more than $1000 (inclusive) and placed more than 3 orders (inclusive) since January 1, 2023: orders_placed MATCHES (sum_amount >= 1000, count >= 3, date >= 2023-01-01) Use the parameter date and the operator BETWEEN to specify a specific date range. You can express between January 1, 2023 and June 1, 2023 (inclusive) in the following way:orders_placed MATCHES (count >= 3, BETWEEN 2023-01-01 AND 2023-06-01)
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Notes |
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Predicted spend tier
NAME: predicted_spend_tier
Includes customers who are within the specified predicted spend tier. Learn more about predicted spend tier.
Operators |
Is equal to: = Isn't equal to: != Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values |
'HIGH' 'MEDIUM' 'LOW' |
Format | |
Example |
Include customers who are in the HIGH tier:predicted_spend_tier = 'HIGH'
|
Notes |
Product subscription status
Name: product_subscription_status
Includes customers who have the specified product subscription status.
Operators |
Is equal to: = Isn't equal to: != Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values |
Active: 'SUBSCRIBED' The customer has an active product subscription.Cancelled: 'CANCELLED' The customer has canceled their product subscription.Expired: 'EXPIRED' The customer's product subscription has expired.Failed: 'FAILED' The customer has a failed payment.Never subscribed: 'NEVER_SUBSCRIBED' The customer never subscribed.Paused: 'PAUSED' The customer has paused their product subscription.
|
Format | |
Example |
Include customers who have an active product subscription:product_subscription_status = 'SUBSCRIBED'
|
Notes |
Products purchased
Name: products_purchased
Includes customers who purchased the specified product. In addition, you can include customers who bought the product during a specified date range.
Function parameters |
id (optional): Use this parameter to specify the product a customer has purchased that you want to filter. quantity (optional): Use this parameter to specify the quantity of products purchased per order.sum_quantity (optional): Use this parameter to specify the quantity of products purchased across all orders.date (optional): Use this parameter to specify a date for the event.tag (optional): Use this parameter to specify a product tag for purchased products that you want to filter.
|
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Operators |
MATCHES : Parameter is true.NOT_MATCHES : Parameter is false.IS NULL : Parameter doesn't exist.IS NOT NULL : Parameter exists.For dates, the available operators include: Is equal to: = Isn't equal to: != Greater than: > Smaller than: < Smaller or equal to: <= Greater or equal to: >= Between: BETWEEN
|
Value | |
Format |
Supported formats for tag :string (single value)Supported formats for id :
= (single value)IN : A set of comma-separated values with implicit "OR", wrapped in parentheses. For example: (id IN 1012132033639, 2012162031638, 32421429314657) . There is a limit of 500 product IDs in a set.Supported date formats:Absolute date: YYYY-MM-DD Date offset examples:
Supported formats for quantity and sum_quantity :Number: #
|
Example |
Specify whether a product has been purchased using a MATCHES or NOT_MATCHES operator:products_purchased MATCHES (id = 2012162031638) products_purchased NOT_MATCHES (id IN 2012162031638, 1012132033639)
products_purchased MATCHES (tag = 'red') Filter customers that purchased a specific product since January 1, 2022 until today: products_purchased MATCHES (id = 1012132033639, BETWEEN 2022-01-01 AND today) Filter customers that purchased a product with the tag 'red' since January 1, 2022 until today:products_purchased MATCHES (tag = 'red', BETWEEN 2022-01-01 AND today) Within the last 30 days: products_purchased MATCHES (date >= -30d) Until January 1, 2022: products_purchased MATCHES (date <= 2022-01-01) Use the parameter date and the operator BETWEEN to specify a specific date range. You can express between January 1, 2022 and June 1, 2022 (inclusive) in the following way:products_purchased MATCHES (id = 1012132033639, BETWEEN 2022-01-01 AND 2022-06-01) Filter customers that have recently purchased a lot of products with a specific tag: products_purchased MATCHES (tag = 'product_tag', sum_quantity >= 3, date >= -90d)
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Notes |
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RFM group
Name: rfm_group
Includes customers based on which RFM group they're categorized into. Learn more about RFM customer analysis.
Operators |
Is equal to: = Isn't equal to: != Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values |
Dormant: 'DORMANT' At risk: 'AT_RISK' Previously loyal: 'PREVIOUSLY_LOYAL' Needs attention: 'NEEDS_ATTENTION' Almost lost: 'ALMOST_LOST' Loyal: 'LOYAL' Promising: 'PROMISING' Active: 'ACTIVE' New: 'NEW' Champions: 'CHAMPIONS' Prospects: 'PROSPECTS'
|
Format | |
Example |
Include customers in the RFM group Needs Attention:rfm_group = 'NEEDS_ATTENTION'
|
Notes |
SMS subscription status
Name: sms_subscription_status
Includes customers based on whether they're subscribed to your marketing SMS text messages. Learn more about collecting customer contact information.
Operators |
Is equal to: = Isn't equal to: != Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values |
Subscribed: 'SUBSCRIBED' The customer is subscribed to your marketing SMS text messages.Pending: 'PENDING' The customer is in the process of subscribing to your marketing SMS text messages.Redacted: 'REDACTED' The customer has pending redaction because of a GDPR erasure request.Unsubscribed: 'UNSUBSCRIBED' The customer has unsubscribed from your marketing SMS text messages.Not subscribed: 'NOT_SUBSCRIBED' The customer never subscribed to your marketing SMS text messages.
|
Format | |
Example |
Include customers who have subscribed to your marketing SMS text messages:sms_subscription_status = 'SUBSCRIBED'
|
Notes |
States or provinces
Name: customer_regions
Includes customers who have an address in the specified region within a country. Customers who have multiple addresses might be included in more than one customer segment that uses this filter.
Operators |
Contains this exact location: CONTAINS Doesn't contain this exact location: NOT CONTAINS Doesn't exist: IS NULL Exists: IS NOT NULL
|
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Values | Use the ISO country code with the ISO 3166-2 subdivision code. |
Format | |
Example |
Include customers who have an address in New York State:customer_regions CONTAINS 'US-NY'
|
Notes | To find a region, you can start typing the name of the region, and then select the appropriate value from the list that's displayed. |
Store credit accounts
Name: store_credit_accounts
Includes customers who have a store credit balance on your store.
Function parameters |
balance (optional): Use this parameter to specify the customer's current store credit account balance.currency (optional): Use this parameter to specify the currency of the customer's store credit balance.next_expiry_date (optional): Use this parameter to specify the date of the soonest expiring unspent store credit.last_credit_date (optional): Use this parameter to specify the date when the customer last received store credit.
|
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Operators |
MATCHES : Parameter is true.NOT_MATCHES : Parameter is false.IS NULL : Parameter doesn't exist.IS NOT NULL : Parameter exists.For dates, the available operators include: Is equal to: = Isn't equal to: != Greater than: > Smaller than: < Smaller or equal to: <= Greater or equal to: >= Between: BETWEEN
|
Values | |
Format |
Supported formats for currency :Currency code: For example USD Supported formats for balance :Number: # Supported formats for next_expiry_date and last_credit_date :Absolute dates: YYY-MM-DD Date offset examples: 7 days ago: -7d 4 weeks ago: -4w 3 months ago: -3m 1 year ago: -1y Named dates: today
yesterday
|
Example |
Filter customers who have a store credit account balance greater than or equal to 1 in any currency:store_credit_accounts MATCHES (balance >= 1) Filter customers who have a store credit account balance greater than or equal to $1 USD: store_credit_accounts MATCHES (balance >= 1, currency: 'USD') Filter customers with store credit expiring in the next 7 days: store_credit_accounts MATCHES (next_expiry_date <= +7d) Filter customers who last received store credit more than 1 month ago but still have a balance available to spend: store_credit_accounts MATCHES (last_credit_date <= -1m, balance >= 1)
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Notes |
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Storefront events
Name: storefront.EVENT
Includes customers based on storefront events. Supported events (EVENT
) include the following:
- Product viewed:
product_viewed
- Collection viewed:
collection_viewed
Function parameters |
id (optional): Use this parameter to specify the products or collections that you want to filter on. date (optional): Use this parameter to specify a date for the event.count (optional): Use this parameter to specify the exact number of times a product or collection was viewed.Product event-specific parameters: tag (optional): Use this parameter to specify the product tag you want to filter on. This behaves the same as filtering for every product ID with that tag. |
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Operators |
MATCHES : Parameter is true.NOT_MATCHES : Parameter is false.IS NULL : Parameter doesn't exist.IS NOT NULL : Parameter exists.For dates, the available operators include: Is equal to: = Isn't equal to: != Greater than: > Smaller than: < Smaller or equal to: <= Greater or equal to: >= Between: BETWEEN
|
Value | |
Format |
Supported formats for id :
= (single value)IN : A set of comma-separated values with implicit "OR", wrapped in parentheses. For example: (id IN 1012132033639, 2012162031638, 32421429314657) . There is a limit of 500 product or collection IDs in a set.Supported formats for tag :
string (single value)Supported date formats:
Absolute date: YYYY-MM-DD Date offset examples:
The named dates are default values and can't be changed. For custom dates, use a date offset. |
Example |
Specify whether a storefront event happened using a MATCHES or NOT_MATCHES operator:
storefront.product_viewed MATCHES() storefront.collection_viewed NOT_MATCHES () Use the parameter id to specify the products that you want to filter on:storefront.product_viewed MATCHES (id = 2012162031638) storefront.collection_viewed MATCHES (id IN 2012162031638, 456, 789) Use the parameter tag to the product tags you want to filter on: storefront.product_viewed MATCHES (tag = 'jeans') Use the parameter date and the operator >= to specify a start date for a storefront event:storefront.product_viewed MATCHES (id = 2012162031638, date >= 2023-04-03) storefront.collection_viewed MATCHES (id = 2012162031638, date >= -30d) Use the parameter date and the operator <= to specify an end date for a storefront event:storefront.product_viewed MATCHES (id = 2012162031638, date <= 2023-04-30) storefront.collection_viewed MATCHES (id = 2012162031638, date <= -7d) Use the parameter date and the operator BETWEEN to specify both a start and end date for a storefront event:storefront.product_viewed MATCHES (id = 2012162031638, BETWEEN 2023-04-03 AND 2023-04-30) storefront.collection_viewed MATCHES (id = 2012162031638, BETWEEN -90d AND -30d) Filter customers that viewed a specific product in the last 30 days: storefront.product_viewed MATCHES (id = 2012162031638, date >= -30d) Filter customers that viewed a specific collection since January 1, 2023 until today: storefront.collection_viewed MATCHES (id = 2012162031638, BETWEEN 2023-01-01 AND today)
|
Notes |
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