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NextGen Platform Segmentation Glossary

Glossary of terms and definitions for filter criteria and operators.

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Written by Support
Updated this week

Creating cross-channel filters will be easy once you have the basic understanding of the logic behind the types of data available in Listrak's NextGen Platform.

Common Terminology

  • Segment: A subset of the total contacts based on common characteristics regardless of channel or opt-in status. A segment can be saved for reuse.

  • Filter Criteria: Individual criteria that a contact would have to meet to be included in a segment. Multiple filtered criteria can be used to define a segment.

  • Rule: A single piece of criteria configured by applying values such as date parameters, numeric values, text values, and other attributes. 💡Configurations will vary depending on the type of criteria selected and data available in your account.

  • Operators: A logical conjunction (AND/OR) that is used to connect two or more filters within a single group or, used to connect two or more groups within a filter together.

  • Refinement Criteria: Additional filtering options that can be added to refine the criteria based on 'something specific', frequency of messages sent and over a period of time. Some or all refinement options are only applicable to criteria types noted with this icon ↪️.

    • Something Specific

      • Message (subject line) name > can multi-select

      • Channel

    • Frequency

      • How many times > numeric

        • Exactly

        • Over

        • Under

    • Time

      • Over how long > days

        • 1 day = in the past 24 hours, 2 days = in the past 48 hours, etc.

        • Do NOT use 0 days as that will not pull any data, it means 'has done nothing'



Criteria Types

💡 Helpful Tip: All date-based criteria are based on UTC timezone.

Contact Profile

💡 Any date data type in this group gives the option to include the year when calculating the date. Use this in scenarios where the exact year needs to be referenced (e.g. birthdates or anniversaries) when pulling in contacts.

  • Buyer Preference: Buyer preferences are calculated by determining which variable (e.g. color, gender, size, style) of an item a contact purchases most frequently and only accounts for items they keep. Preference is determined at the category level (e.g. if you are using size - large shirt, medium pants). If a contact has not purchased a category or they have purchased an equal number of products across sizes no preference will be available.

    • Color

    • Gender

    • Product Tags (Shopify only)

    • Size

    • Style

  • Common: Personal data that is commonly acquired for a contact. Data can be collected by list imports, API connections, JavaScript, data management steps in a Journey, or other custom methods of adding data into the platform. Note, these fields are automatically created by Listrak and can not deleted.

    • Address & Location

      • City: text

      • Country: text

      • Postal Code: text

      • State | Region | Province: text

      • Time Zone: text

    • Personal Information

      • Area Code (North America): numeric (e.g. 717, 652, 319)

      • Birthday: date (MM/DD/YYYY) or (MM/DD)

      • Currency: numeric

      • Customer Tags: text (Shopify only)

      • Email Domain: text (e.g. gmail.com, aol.com)

      • First Name: text

      • Job Title: text

      • Last Name: text

      • Organization: text

      • Registration Language: text

      • Wedding Anniversary: date (MM/DD/YYYY) or (MM/DD)

  • Custom: Custom fields allow you to create unique profile groups and fields for collecting additional data about a contact. Data can be collected by list imports, API connections, JavaScript, data management steps in a Journey, or other custom methods of adding data into the platform.

  • Devices & Services: Data that pertains to the type of device and service provider used by a contact. This data is based on whatever the integrated systems pass to the Listrak system.

    • Device OS*: This is the operating system that runs your device; some examples are Microsoft Windows, (Apple's) macOS and (Google's) Android OS.

    • Device OS Version*: The particular form of the operating system, for example Windows 10 and Windows XP are different versions of the Microsoft Windows OS.

    • Device Type*: This is the type of device use, such as a desktop, mobile phone, etc.

    • Mobile App Version*: The particular form of your App's operating system.

    • SMS Carrier: The wireless service provider a client uses to send/receive text messages.

      *Only available for App Push Channel


Contact Behavior

Data derived from contacts' actions and behaviors ranging from subscribing, message and site engagement.

💡 Activity is not channel specific.

  • Browse

    • Browse URL ↪️: The last URL browsed.

    • Last Site Visit: The date and time of the last on-site activity by the contact, as captured by the Listrak JavaScript framework.

  • Messages

    • Clicked ↪️: A check to see if a contact has or has not opened a specific message(s).

      • Refine by specific message or channel.

    • Last Click Date: The date a contact last clicked a message.

    • Last Open Date: The date a contact last clicked an email.

    • Last Send Date: The date a contact was last sent a message.

    • Opened ↪️: A check to see if a contact has or has not opened a specific message(s).

      • Refine by specific message or channel.

    • Sent ↪️: A check to see if a message has or has not been sent a specific message(s).

      • Refine by specific message or channel.

  • Subscriptions

    • Most Recent Subscription: The date a contact last subscribed across all channels, will be refined when applied to an audience within a channel.

    • Original Subscription: The date a contact first subscribed across all channels, will be refined when applied to an audience within a channel.

    • SMS Subscription Keyword: The first keyword the contact used to subscribe to the SMS channel.

    • Subscription Status: The status of a contact's identifier (e.g. email address) in a specific channel that can be limited by timeframe.


Product Behavior

Data derived from contacts' purchase history, browse behavior related specifically to products and cart abandonment behaviors.

  • Browse

    • Browse Count ↪️: The number of times a contact has browsed the site.

    • Browsed Brand ↪️: The brand of the last product browsed by the contact.

    • Browsed Category ↪️: The category of the last product browsed by the contact.

    • Browsed Subcategory ↪️: The subcategory of the last product browsed by the contact.

    • Most Browsed Brand: The brand, determined by products previously browsed, that a contact has viewed the most.

    • Most Browsed Category: The category, determined by products previously browsed, that a contact has viewed the most.

    • Most Browsed Subcategory: The subcategory, determined by products previously browsed, that a contact has viewed the most.

  • Cart: Data is available for an extended period of time after the contact completes the behavior.

    • Cart Has Brand ↪️: Any product in the abandoned cart that had a brand associated with it.

    • Cart Has Category ↪️: Any product in the abandoned cart that had a category associated with it.

    • Cart Has SKU ↪️: Any product in the abandoned cart that had a SKU associated to it.

    • Cart Has Subcategory ↪️: Any product in the abandoned cart that had a subcategory associated with it.

    • Cart Item Count: The number of products in the abandoned cart.

    • Cart Item Total: The total value of all products in the abandoned cart.

    • Cart Items On Sale: Identifies if any of the products in the abandoned cart are on sale.

    • Last Cleared Cart: The last date the cart was cleared, which means the cart no longer has products in it.

    • Last Updated Cart: The last date a saved cart was updated, this includes the initial created a cart and and change following that action.

  • Purchase: This data comes from several sources such as from an overall order (the Orders file), product specific details (the Order Items file and Products file) and calculations to determine values such as Average Order Value, Sum of all Orders and more. Note, this will also incorporate any historical order data you have uploaded into Listrak.

    • All Orders

      • First Order Date: The first date a contact made a purchase.

      • Last Order Date: The last date a contact made a purchase.

      • Order - Item Quantity: The quantity of a line item in an order.

      • Order Date: Any date a contact made a purchase.

      • Order Item Brand: The brand of a product in an order.

      • Order Item Category: The category of a product in an order.

      • Order Item SKU: The 'Stock Keeping Unit' assigned to a product.

      • Order Ship Date: The date the order was shipped.

      • Order Source: The source of the order based on the order channel provided, e.g. Online, Instore.

      • Order Status: The provided status of an order.

      • Order Store Number: The specific value designated to the merchant used to identify different stores.

      • Order Tags: Shopify Order Tags

      • Sum of all Order Item Quantities: The total piece count of all line items across all orders.

      • Sum of all Order Item Totals: The total dollar amount of all line items in all orders (excludes tax, surcharges, shipping, etc.).

      • Sum of all Order Totals: (excludes tax, surcharges, shipping, etc.).

      • Total Number of Orders: The total number of orders placed during a time period by a contact (includes tax, surcharges, shipping, etc.) and (excludes returns, back-orders, etc.).

    • Average Order

      • Average Length Between Orders: The average number of days between any order.

      • Average Order Item Quantity: The average number of products (line items) purchased by a contact.

      • Average Order Item Total: The average dollar amount spent based on the number of products in an order (excludes tax, surcharges, shipping, etc.).

      • Average Order Line Item Count: The average number of times a product (line item) was purchased by a contact.

      • Average Order Value: The average dollar amount spent in an order (includes tax, surcharges, shipping, etc.).

    • Largest Order

      • Largest Order Item Total: The single item purchased with the largest dollar value during the lifetime of the contact (excludes tax, surcharges, shipping, etc.).

      • Largest Order Total: The single order with the highest dollar total during the purchase lifetime of the contact (includes tax, surcharges, shipping, etc.).

    • Smallest Order

      • Smallest Order Item Total: The single item purchased with the smallest dollar value during the lifetime of the contact (excludes tax, surcharges, shipping, etc.).

      • Smallest Order Total: The single order with the smallest dollar total during the purchase lifetime of the contact (includes tax, surcharges, shipping, etc.).

    • Most Common Order

      • Most Common Order Day

      • Most Common Order Hour

      • Most Common Order Item Category

      • Most Common Order Item Master SKU

      • Most Common Order Item SKU

      • Most Common Order Item Subcategory

      • Most Common Order Source

    • Order Items (Product attributes)

      • Order Item Brand

      • Order Item Category

      • Order Item Clearance

      • Order Item Color

      • Order Item Discontinued

      • Order Item Gender

      • Order Item Master SKU

      • Order Item On Sale

      • Order Item Price

      • Order Item Quantity

      • Order Item Ship Date

      • Order Item Tag

      • Order Item Size

      • Order Item SKU

      • Order Item Status

      • Order Item Style

      • Order Item Subcategory

      • Order Item Title


Predictive

Predictive Analytics* uses Listrak's AI to take information about contact's past interactions on your site to identify patterns of behavior to help identify what contacts are likely to do in the future. Listrak tracks over 80 different data points to learn about your contact base and predict their future actions. The models constantly update to account for new trends and behavior across your contact base.

  • Engagement

    • Product Affinity: Groups contacts together based on the strength of their relationship with a specific brand, category, or subcategory.

      • Brand Affinity

      • Category Affinity

      • Subcategory Affinity

    • AI Channel Affinity: Groups contacts together based on their preferred messaging channel (determined after 7 days from subscription date) for each domain they are subscribed to. A contact's preferred channel will change based on their engagement with each subscribed domain.

      • Note that all available Listrak channels will appear in the dropdown.

    • Lifecycle Stage: A measure of a contact's position in their purchase life cycle:

      • Active: Identifies contacts who have made a recent purchase or recently engaged with the brand and are in the first half of their life cycle.

      • At Risk: Identifies contacts who have not made a recent purchase or not recently engaged with your brand and are in the second half of their life cycle.

      • Churned: Identifies contacts who have not purchased within their expected life cycle.

    • Likelihood to Click an Email: A measure of the likelihood that a contact has to click through a link in an email.

    • Likelihood to Open an Email: A measure of the likelihood that a contact has to open an email.

    • Likelihood to Purchase: A measure of the likelihood that a contact has of making a purchase.

    • Likelihood to Unsubscribe from Email: A measure of the likelihood that a contact has of unsubscribing from your email list.

      💡 Helpful Tips

      • All likelihood models measure the chance that a given behavior will occur in the next 14 days.

      • Most Likely: Identifies contacts who are two times or more likely to complete a specific action.

      • More Likely: Identifies contacts who are more likely than the average contact and less than two times more likely to complete a specific action.

      • Less Likely: Identifies contacts who have between a 0.5 - 1x likelihood to complete a specific action.

      • Least Likely: Identifies contacts who have less than a 0.5x likelihood to complete a specific action.

  • Purchase

    • Coupon Affinity: Groups contacts by the chance that they will use a coupon when making a purchase. Passing coupon information in the orders file is required to identify a buyer's coupon affinity.

    • Discount Affinity: Groups contacts by the chance that they will purchase an item using a discount. Passing discount information in the orders file is required to identify a buyer's discount affinity.

      💡 Helpful Tips

      • Coupon/Discount Buyer: 100% of purchases made using a coupon or discount.

      • Coupon/Discount Preferred: 50-100% of purchases made using a coupon or discount.

      • No Preference: 25-50% of purchases made using a coupon or discount.

      • Full-Price Buyer: Less than 25% of purchases made at a discount.

      • Non-Coupon Buyer: Less than 25% of purchases made using a coupon.

    • Predicted Future Spend (Percentile): A calculation using a percentile breakdown representing the amount a contact is likely to spend with your brand in the next 365 days.

    • Predicted Future Spend (Value): A calculation using the dollar value representing the amount a contact is likely to spend with your brand in the next 365 days.

    • Project Order Date: The last order date plus the average reorder days is the expected next order date.

*Predictive Analytics is an additional solution offered by Listrak. If you are interested in purchasing Predictive Analytics, please contact your Account Manager.

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