Acquia CDP
Dimensions tables
The following is the list of tables for standard dimensions:
| Dimension table | Description |
|---|---|
| Attribution | Track the way credit for conversions or actions is assigned to different touch-points in a customer's journey, such as first-touch, last-touch, or multi-touch attribution models. |
| Customer | Group customer-specific attributes, such as demographics, customer IDs, or segments. |
| Cohorts | Group customers or entities based on shared characteristics or behaviors within a specific timeframe. These dimensions are often used for Cohort Analysis. |
| Machine Learning | Categorize or predict behaviors or outcomes based on historical data patterns. These dimensions are generated or influenced by machine learning algorithms. |
| Market Basket Analysis | Group the items purchased together in transactions. These dimensions are often used to understand purchasing patterns and recommend related products. |
| Product | Group individual products such as product IDs, names, descriptions, or attributes. |
| Product Category | Categorize products into groups or hierarchies based on shared characteristics or types. |
| Sales Organization | Group organizational units responsible for sales. For example, sales regions, teams, or territories. |
| Transaction | Group transactional data such as transaction IDs, dates, amounts, or types of transactions. |
| Sub-Group | Dimension name | Description | Pre-calculated field? |
|---|---|---|---|
| - | Campaign ID | Name | The campaign ID and name. | No |
| Campaign Level Names | Level 1 Name | The name of the level 1 campaign. | No |
| Campaign Level Names | Level 2 Name | The name of the level 2 campaign. | No |
| Campaign Level Names | Level 3 Name | The name of the level 3 campaign. | No |
| Campaign Level Names | Level 4 Name | The name of the level 4 campaign. | No |
| Campaign Level Names | Level 5 Name | The name of the level 5 campaign. |
| Sub-Group | Dimension name | Description | Pre-calculated field? |
|---|---|---|---|
| Address | Customer City | The city from the customer’s primary address. | No |
| Address | Customer Country | The country from the customer’s primary address. | No |
| Address | Customer RBDI | The Residential or Business Delivery Indicator: A flag to mark whether the customer’s primary address is a business or residential address. Parcel delivery to residential addresses is more expensive than to business addresses (United States only). | No |
| Address | Customer State | The state from the customer’s primary address. | No |
| Address | Customer Zip Code | The Zip Code from the customer’s primary address. | No |
| Age |
| Sub-Group | Dimension name | Description | Pre-calculated field? |
|---|---|---|---|
- | AttrWindow Range in Days | Attribution window is a period of time you set between which transactions by customers included in a cohort / campaign can be credited to that same cohort / campaign. The default attribution window is [0:14], representing a range of 0 to 14 days from the campaign execution date. This period determines when transactions are credited to the campaign or cohort. You can adjust the window using [X] format, where X and Y are the lower and upper bounds in days. For customization, contact your CVM. | Yes |
- | Campaign | Segment Name | The campaign name with the segment name. | Yes |
Campaign Execution Date | Date | The specific date when the campaign or segment was executed. | Yes |
Campaign Execution Date | Day of Month | The day of the month when the campaign or segment was executed. |
| Sub-Group | Dimension name | Description | Pre-calculated field? |
|---|---|---|---|
| Behavior Based Cluster | Behavior Based Cluster - 1 Month Ago | The cluster of customers personas based on their purchase behavior, preferences, and spending patterns a month ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Behavior Based Cluster | Behavior Based Cluster - 2 Months Ago | The cluster of customers personas based on their purchase behavior, preferences, and spending patterns two months ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Behavior Based Cluster | Behavior Based Cluster - This Month | The cluster of customers personas based on their purchase behavior, preferences, and spending patterns this month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Behavior Based Cluster | Behavior Based Cluster - Today |
| Sub-Group | Dimension name | Description | Pre-calculated field? |
|---|---|---|---|
| First Item Details | First Category Name Level 1 | The category name of the level 1 first item. | No |
| First Item Details | First Category Name Level 2 | The category name of the level 2 first item. | No |
| First Item Details | First Category Name Level 3 | The category name of the level 3 first item. | No |
| First Item Details | First Category Name Level 4 | The category name of the level 4 first item. | No |
| First Item Details | First Category Name Level 5 | The category name of the level 5 first item. |
| Dimension name | Description | Pre-calculated field? |
|---|---|---|
| Product Brand | The brand name for product | No |
| Product ID | A Unique identifier for product | No |
| Product Item Status | Availability status for product. ‘Active’ means the product is in stock, available or available for order / preorder. ‘Inactive’ generally means the product is out of stock or no longer available. It’s null for products that we do not have the Availability for. | No |
| Product Name | Name for product | No |
| Dimension name | Description | Pre-calculated field? |
|---|---|---|
| Product Category - Level 1 | Customers purchased from 1 distinct product category. | No |
| Product Category - Level 2 | Customers purchased from 2 distinct product categories. | No |
| Product Category - Level 3 | Customers purchased from 3-5 distinct product categories. | No |
| Product Category - Level 4 | Customers purchased from 6-10 distinct product categories. | No |
| Product Category - Level 5 | Customers purchased from 10+ distinct product categories. | No |
| Sub-Group | Dimension name | Description | Pre-calculated field? |
|---|---|---|---|
| Geography | Sales Org City | The city for sales organization. | No |
| Geography | Sales Org Country | The country for sales organization. | No |
| Geography | Sales Org State | The state for sales organization. | No |
| Geography | Sales Org Zip Code | The Zip Code for sales organization. | No |
| - | Sales Channel | The channel for sales organization. The following are the values:
|
| Sub-Group | Dimension name | Description | Pre-calculated field? |
|---|---|---|---|
| Customer Transaction Sequence | Customer Transaction Sequence | A number to indicate the sequence of transactions for each customer after sorting their transactions by [Transaction Date] in ascending order. ‘1’ denotes the first transaction for a given customer, ‘2’ denotes the second transaction for the same customer. These values are calculated at the transaction header-level. If a customer places more than one transaction on the same day, each of those transactions have a different sequence number depending on the timestamp of the transaction and the unique identifier of the transaction. | Yes |
| Customer Transaction Sequence | Customer Transaction Sequence - New vs Repeat | A flag to indicate if a customer is a new customer or a repeat customer when the transaction was made. Transactions with [Customer Transaction Sequence] = 1 are marked as ‘New’ whereas transactions with [Customer Transaction Sequence] > 1 are marked as ‘Repeat’. Note that this field is calculated at the transaction level, and it does not indicate buyer status as of today. Instead, it indicates buyer status as of when the transaction was made. | Yes |
| Customer Transaction Sequence | Customer Transaction Sequence Group | The Bucketed version of [Customer Transaction Sequence] for transaction | Yes |
| No |
| - | Campaign Name | The name of the campaign. | No |
| Campaign Start Date | Date | The date when the campaign started. | No |
| Campaign Start Date | Day of Month | The day of the month when the campaign started. | No |
| Campaign Start Date | Day of Week | The day of the week when the campaign started. | No |
| Campaign Start Date | Hour of Day | The hour of the day when the campaign started. | No |
| Campaign Start Date | Month | The month when the campaign started. | No |
| Campaign Start Date | Month Name | The name of the month when the campaign started. | No |
| Campaign Start Date | Quarter | The quarter when the campaign started. | No |
| Campaign Start Date | Quarter of Year | The quarter of the year when the campaign started. | No |
| Campaign Start Date | Time of Day | The time of the day when the campaign started. | No |
| Campaign Start Date | Week of Year | The week of the year when the campaign started. | No |
| Campaign Start Date | Year | The year when the campaign started. | No |
| The age of the customer. |
| No |
| Age | Age Group | The age of the customer, grouped into buckets for easier use. | No |
| - | Buyer Identification | The dimension that indicates whether the customer is an identified or unidentified buyer. All transactions that have a blank or null Customer get attributed to a generic Unidentified customer. This is primarily used with Sales Organization dimensions to view a distribution of revenue attributed to unidentified individuals for POS sales. | Yes |
| Buying Stats | AOV | The average order value for customers calculated using [Product Revenue] / [Transaction Count]. | Yes |
| Buying Stats | Average Annual Transactions | The annual transaction frequency for customer calculated using [Transaction Count] * 365 / [Days since First Transaction]. | Yes |
| Buying Stats | Average Discount Rate | The average discount rate for customers to identify promotion driven customers. | Yes |
| Buying Stats | First Transaction Revenue | The revenue from the customer’s first transaction. Note that ranges are inclusive at the higher bound. For example, ‘0-25’ includes up to 25, ‘25-50’ starts at 25.01. | Yes |
| Buying Stats | Last Transaction Interval | The number of months between the last and the second to last transaction of the customer. | Yes |
| Buying Stats | Revenue - 13-24 Months | The total revenue for customer’s purchases in the previous 13-24 month duration. Note that ranges are inclusive at the higher bound. For example, ‘0-100’ includes up to 100, ‘100-200’ starts at 100.01. | Yes |
| Buying Stats | Revenue - Last 12 Months | The total revenue for customer’s purchases in the last 12 month duration. Note that ranges are inclusive at the higher bound. For example: ‘0-100’ includes up to 100, ‘100-200’ starts at 100.01. | Yes |
| Buying Stats | Revenue - Lifetime | The total revenue for all purchases in the customer’s lifetime. Note that ranges are inclusive at the higher bound. For example: ‘0-100’ includes up to 100, ‘100-200’ starts at 100.01. | Yes |
| Buying Stats | Revenue Decile - 13-24 Months | The revenue decile for customers based on total revenue for all purchases in the previous 13-24 month duration. The following are the values:
| Yes |
| Buying Stats | Revenue Decile - Last 12 Months | The revenue decile for customers based on total revenue for all purchases in the last 12 month duration. The following are the values:
| Yes |
| Buying Stats | Revenue Segment - 13-24 Months | The revenue segment for customers based on total revenue for all purchases in the previous 13-24 month duration. The following are the values:
| Yes |
| Buying Stats | Revenue Segment - Last 12 Months | The revenue segment for customers based on total revenue for all purchases in the last 12 month duration. The following are the values:
| Yes |
| Buying Stats | Revenue Trend Segment | The revenue trend segment for customers derived by comparing revenue decile in the previous 13-24 months as compared to the last 12 months. It characterizes whether they spent less (‘Downward’), the same (‘Stable’), or more (‘Upward’) in the previous 13-24 months period as compared to the last 12 months. The following are the values:
| Yes |
| Buying Stats | Transaction Count - 13-24 Months | The total number of transactions made by customers in the previous 13-24 month duration. | Yes |
| Buying Stats | Transaction Count - Last 12 Months | The total number of transactions made by customers in the last 12 month duration. | Yes |
| Buying Stats | Transaction Count - Lifetime | The total number of transactions made in a customer’s lifetime. | Yes |
| - | Category Count | The number of distinct product categories that customers purchased from in their lifetime. | Yes |
| - | Customer Gender | The gender of the customer as determined by the genderization algorithm of Customer Data Platform (CDP). Values are Female, Male, Neutral and Unknown. Neutral refers to names that are either male or female. If the gender can not be determined, CDP displays Unknown. | No |
| - | Customer Status | The buying status of the customer. Possible values include Buyer, Non Buyer, Unidentified. | Yes |
| Days since First Transaction | Days since First Transaction | The number of days since the customer’s first transaction, that is, the tenure of the customer in days. | Yes |
| Days since First Transaction | Days since First Transaction Group | The bucketed version of [Days since First Transaction] represented in months. | Yes |
| Days since Last Transaction | Days since Last Transaction | The number of days since the customer’s last transaction, that is, the recency of the customer in days. | Yes |
| Days since Last Transaction | Days since Last Transaction Group | The bucketed version of [Days since Last Transaction] represented in months. | Yes |
| Email Last Click Date | Date | The date when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Day of Month | The day of the month when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Day of Week | The day of the week when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Month | The month when the customer last clicked one of the email campaigns | Yes |
| Email Last Click Date | Month Name | The name of the month when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Quarter | The quarter when the customer last clicked one of the campaigns. | Yes |
| Email Last Click Date | Quarter of Year | The quarter of the year when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Week of Year | The week of the year when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Year | The year when the customer last clicked one of the email campaigns. | Yes |
| Email Last Open Date | Date | The date when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Day of Month | The day of the month when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Day of Week | The day of the week when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Month | The month when the customer last opened one of the email campaigns | Yes |
| Email Last Open Date | Month Name | The name of the month when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Quarter | The quarter when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Quarter of Year | The quarter of the year when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Week of Year | The week of the year when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Year | The year when the customer last opened one of the email campaigns. | Yes |
| Email Last Send Date | Date | The date when the customer was last sent an email. | Yes |
| Email Last Send Date | Day of Month | The day of the month when the customer was last sent an email. | Yes |
| Email Last Send Date | Day of Week | The day of the week when the customer was last sent an email. | Yes |
| Email Last Send Date | Month | The month when the customer was last sent an email. | Yes |
| Email Last Send Date | Month Name | The name of the month when the customer was last sent an email. | Yes |
| Email Last Send Date | Quarter | The quarter when the customer was last sent an email. | Yes |
| Email Last Send Date | Quarter of Year | The quarter of the year when the customer was last sent an email. | Yes |
| Email Last Send Date | Week of Year | The week of the year when the customer was last sent an email. | Yes |
| Email Last Send Date | Year | The year when the customer was last sent an email. | Yes |
| First Transaction (Digital) Date | Date | The date of the first transaction made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Day of Month | The day of the month of the first transaction made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Day of Week | The day of the week of the first transaction made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Month | The month when the first transaction was made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Month Name | The name of the month when the first transaction was made by the customer in the digital format. | Yes |
| First Transaction (Digital) Date | Quarter | The quarter when the first transaction was made by the customer in the digital format. | Yes |
| First Transaction (Digital) Date | Quarter of Year | The quarter of the year when the first transaction was made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Week of Year | The week of the year when the first transaction was made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Year | The year when the first transaction was made by a customer in the digital format. | Yes |
| First Transaction (Physical) Date | Date | The date of the first transaction made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Day of Month | The day of the month of the first transaction made by a customer in the physical format. | Yes |
| First Transaction (Physical) Date | Day of Week | The day of the week of the first transaction made by a customer in the physical format. | Yes |
| First Transaction (Physical) Date | Month | The month when the first transaction was made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Month Name | The name of the month when the first transaction was made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Quarter | The quarter when the first transaction was made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Quarter of Year | The quarter of the year when the first transaction was made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Week of Year | The week of the year when the first transaction was made by a customer in the physical format. | Yes |
| First Transaction (Physical) Date | Year | The year when the first transaction was made by a customer in the physical format. | Yes |
| First Transaction Date | Date | The date of the first transaction made by a customer. | Yes |
| First Transaction Date | Day of Month | The day of the month of the first transaction made by a customer. | Yes |
| First Transaction Date | Day of Week | The day of the week of the first transaction made by a customer. | Yes |
| First Transaction Date | Month | The month when the first transaction was made by a customer. | Yes |
| First Transaction Date | Month Name | The name of the month when the first transaction was made by a customer. | Yes |
| First Transaction Date | Quarter | The quarter when the first transaction was made by a customer. | Yes |
| First Transaction Date | Quarter of Year | The quarter of the year when the first transaction was made by a customer. | Yes |
| First Transaction Date | Week of Year | The week of the year when the first transaction was made by a customer. | Yes |
| First Transaction Date | Year | The year when the first transaction was made by a customer. | Yes |
| - | First Transaction Date - Is Before YTD (Yes / No) | A flag to indicate whether the day of year from customer’s [First Transaction Date] is before today’s day of year. This flag is typically used for Year over Year (YoY) reporting. You can create a report with [First Transaction Date - Month Name] dimension, pivot on [First Transaction Date - Year] dimension, and add [First Transaction Date - Is Before YTD] as a filter with ‘Yes’ value. Such a report accurately compares measures sliced by [First Transaction Date] in a YoY fashion. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Month Num | The fiscal month number of the customer’s first transaction date. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Quarter of Year | The fiscal quarter of the year of the customer’s first transaction date. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Week of Year | The fiscal week of the year of the customer’s first transaction date. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Year | The fiscal year of the customer’s first transaction date. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 1 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics, or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 2 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 3 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 4 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 5 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 1 | The product categories for products bought in a customer’s first transaction. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 2 | The product categories for products bought in a customer’s first transaction. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 3 | The product categories for products bought in a customer’s first transaction. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 4 | The product categories for products bought in a customer’s first transaction. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 5 | The product categories for products bought in a customer’s first transaction. | Yes |
| Last Transaction (Digital) Date | Date | The date of the last transaction made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Day of Month | The day of the month of the last transaction made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Day of Week | The day of the week of the last transaction made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Month | The month when the last transaction was made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Month Name | The name of the month when the last transaction was made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Quarter | The quarter when the last transaction was made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Quarter of Year | The quarter of the year when the last transaction was made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Week of Year | The week of the year when the last transaction was made by a customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Year | The year when the last transaction was made by a customer in the digital format. | Yes |
| Last Transaction (Physical) Date | Date | The date of the last transaction made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Day of Month | The day of the month of the last transaction made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Day of Week | The day of the week of the last transaction made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Month | The month when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Month Name | The name of the month when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Quarter | The quarter when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Quarter of Year | The quarter of the year when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Week of Year | The week of the year when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Year | The year when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction Date | Date | The date of the last transaction made by the customer. | Yes |
| Last Transaction Date | Day of Month | The day of the month of the last transaction made by the customer. | Yes |
| Last Transaction Date | Day of Week | The day of the week of the last transaction made by the customer. | Yes |
| Last Transaction Date | Month | The month when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Month Name | The name of the month when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Quarter | The quarter when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Quarter of Year | The quarter of the year when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Week of Year | The week of the year when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Year | The year when the last transaction was made by a customer. | Yes |
| - | Last Transaction Date - Is Before YTD (Yes / No) | A flag to indicate whether the day of year from customer’s [Last Transaction Date] is before today’s day of year. CDP uses this flag for Year over Year (YoY) reporting. You can create a report with [Last Transaction Date - Month Name] dimension, pivot on [Last Transaction Date - Year] dimension, and add [Last Transaction Date - Is Before YTD] as a filter with ‘Yes’ value. Such a report accurately compares measures sliced by [Last Transaction Date] in a YoY fashion. | Yes |
| Last Transaction Fiscal Date | Last Transaction Fiscal Month Num | The fiscal month number of the customer’s last transaction date. | Yes |
| Last Transaction Fiscal Date | Last Transaction Fiscal Quarter of Year | The fiscal quarter of the year of the customer’s last transaction date. | Yes |
| Last Transaction Fiscal Date | Last Transaction Fiscal Week of Year | The fiscal week of the year of the customer’s last transaction date. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Year | The fiscal year of the customer’s last transaction date. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 1 | The product categories for products bought in the customer’s last transaction. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 2 | The product categories for products bought in the customer’s last transaction. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 3 | The product categories for products bought in the customer’s last transaction. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 4 | The product categories for products bought in the customer’s last transaction. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 5 | The product categories for products bought in the customer’s last transaction. | Yes |
| Marketing Status & Preferences | Address Certified | A Flag to indicate whether the customer’s primary address has been certified by the CDP Data Quality Engine (using USPS CASS certification): ‘True’ means that the address is CASS certified, ‘False’ means the address is not CASS certified (and likely invalid), ‘Unknown’ means that there is either no address, or that the address is not in the US / Canada (those are the only countries we can certify right now). | No |
| Marketing Status & Preferences | Address DPV Confirmed | A flag to indicate whether the customer’s primary address has been Delivery Point Validation confirmed. DPV is the process of verifying that an address is actually deliverable, meaning that mail can be sent to that address. A single street address may have multiple delivery points, such as individual units in an apartment building. ‘Y’ means the address is DPV confirmed whereas ‘N’ means the address is not DPV confirmed. Typically, all DPV confirmed addresses are also Certified but all Certified addresses may not be DPV confirmed. | No |
| Marketing Status & Preferences | Do Not Call | A flag to indicate whether the customer has opted-in or opted-out of the Call campaigns. ‘Y’ means customer has opted-out whereas ‘N’ means customer has opted-in. | No |
| Marketing Status & Preferences | Do Not Email | A flag to indicate whether the customer has opted-in or opted-out of the Email campaigns. ‘Y’ means customer has opted-out whereas ‘N’ means customer has opted-in. | No |
| Marketing Status & Preferences | Do Not Mail | A flag to indicate whether the customer has opted-in or opted-out of the Direct Mail campaigns. ‘Y’ means customer has opted-out whereas ‘N’ means customer has opted-in. | No |
| Marketing Status & Preferences | Do Not Text | A flag to indicate whether the customer has opted-in or opted-out of the SMS or Text campaigns. ‘Y’ means customer has opted-out whereas ‘N’ means customer has opted-in. | No |
| Marketing Status & Preferences | Email Domain | The domain of the customer’s email address. | No |
| Marketing Status & Preferences | Email Status | A flag to indicate the validity of the customer’s email address. The following are the values:
-‘X’: ‘Invalid’, the email address syntax is invalid. | No |
| - | Primary Brand | The product brands that customers made most transactions during their lifetime. | Yes |
| - | Product Count | Number of distinct products purchased by customers during their lifetime. | Yes |
| Sales Organizations | Closest Store | The closest store for customers. | Yes |
| Sales Organizations | Distance to Closest Store | The distance, in miles, between customer and the closest store. This dimension works only for US, Canada and UK addresses (for both stores and customers). | Yes |
| Sales Organizations | First Transaction Sales Channel | The sales channel of the customer’s first transaction. The following are the values:
| Yes |
| Sales Organizations | Last Transaction Sales Channel | The sales channel of the customer’s last transaction. The following are the values:
| Yes |
| Sales Organizations | Primary Physical Store | The physical Store that customer made most transactions in during their lifetime | Yes |
| Sales Organizations | Primary Sales Channel | The sales Channel that the customer made most transactions in during their lifetime. The following are the values:
| Yes |
| Sales Organizations | Sales Channel Count | Number of sales channels customers have purchased from in their lifetime. | Yes |
| Second to Last Transaction Date | Date | The date of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Day of Month | The day of the month of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Day of Week | The day of week of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Month | The month of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Month Name | The name of the month of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Quarter | The quarter of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Quarter of Year | The quarter of the year of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Week of Year | The week of the year of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Year | The year of the second to last transaction made by the customer. | Yes |
| Web First Visit Date | Date | The date when a customer first visited the website. | Yes |
| Web First Visit Date | Day of Month | The day of the month when a customer first visited the website. | Yes |
| Web First Visit Date | Day of Week | The day of the week when a customer first visited the website. | Yes |
| Web First Visit Date | Month | The month when a customer first visited the website. | Yes |
| Web First Visit Date | Month Name | The name of the month when a customer first visited the website. | Yes |
| Web First Visit Date | Quarter | The quarter when a customer first visited the website. | Yes |
| Web First Visit Date | Quarter of Year | The quarter of the year when a customer first visited the website. | Yes |
| Web First Visit Date | Week of Year | The week of the year when a customer first visited the website. | Yes |
| Web First Visit Date | Year | The year when a customer first visited the website. | Yes |
| Web Last Visit Date | Date | The date when a customer last visited the website. | Yes |
| Web Last Visit Date | Day of Month | The day of the month when the customer last visited the website. | Yes |
| Web Last Visit Date | Day of Week | The day of the week when the customer last visited the website. | Yes |
| Web Last Visit Date | Month | The month when the customer last visited the website. | Yes |
| Web Last Visit Date | Month Name | The name of the month when the customer last visited the website. | Yes |
| Web Last Visit Date | Quarter | The quarter when the customer last visited the website. | Yes |
| Web Last Visit Date | Quarter of Year | The quarter of the year when the customer last visited the website. | Yes |
| Web Last Visit Date | Week of Year | The week of the year when the customer last visited the website. | Yes |
| Web Last Visit Date | Year | The year when the customer last visited the website. | Yes |
Yes |
Campaign Execution Date | Day of Week | The day of the week when the campaign or segment was executed. For example, Monday, Tuesday, and so on. | Yes |
Campaign Execution Date | Month | The numeric representation of the month when the campaign or segment was executed. For example, 1 for January, 2 for February, and so on. | Yes |
Campaign Execution Date | Month Name | The name of the month when the campaign or segment was executed. For example, January, February, and so on. | Yes |
Campaign Execution Date | Quarter | The quarter of the year when the campaign or segment was executed. For example, Q1, Q2, Q3, and Q4. | Yes |
Campaign Execution Date | Quarter of Year | The numeric representation of the quarter when the campaign or segment was executed. For example, 1, 2, 3, and 4. | Yes |
Campaign Execution Date | Time | The timestamp indicating the time when the campaign or segment was executed. | Yes |
Campaign Execution Date | Time of Day | The specific time of day when the campaign or segment was executed. For example, morning, afternoon, evening, and so on. | Yes |
Campaign Execution Date | Week of Year | The week number within the year when the campaign or segment was executed. | Yes |
Campaign Execution Date | Year | The year when the campaign or segment was executed. | Yes |
- | Campaign ID | The unique identifier associated with the campaign. | Yes |
- | Campaign Name | The name or title of the campaign. | Yes |
- | Segment ID | The unique identifier associated with the segment. | Yes |
- | Segment Name | The name or title of the segment. | Yes |
- | Variant Name | The specific variant or version of a campaign or segment, if applicable. | Yes |
| The cluster of customers personas based on their purchase behavior, preferences, and spending patterns today. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. |
| Yes |
CC Studio | Custom Calculation Dimension | The custom calculation dimension created within CC Studio for specific analytic needs. | Yes |
| Fuzzy Clustering | Most Likely Cluster Probability | The probability of a customer belonging to a cluster with the best match. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Most Likely Cluster Value | The cluster where the customer belongs to with the highest probability. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Second Most Likely Cluster Probability | The probability of a customer belonging to a cluster with the second best match. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Second Most Likely Cluster Value | The cluster where the customer belongs to with the second highest probability. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Third Most Likely Cluster Probability | The probability of a customer belonging to a cluster with the third best match. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Third Most Likely Cluster Value | The cluster where the customer belongs to with the third highest probability. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Likelihood to Buy | Likelihood to Buy - 1 Month Ago | The likelihood or probability that an existing customer makes a purchase in the near future based on behaviors a month ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Buy | Likelihood to Buy - 2 Months Ago | The likelihood or probability that an existing customer makes a purchase in the near future based on behaviors two months ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Buy | Likelihood to Buy - This Month | The likelihood or probability that an existing customer makes a purchase in the near future based on behaviors this month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Buy | Likelihood to Buy - Today | The likelihood or probability that an existing customer makes a purchase in the near future based on today’s behaviors. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Convert | Likelihood to Convert - 1 Month Ago | The likelihood or probability that a non-buyer makes a purchase in the near future learning from the past one month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Convert | Likelihood to Convert - 2 Months Ago | The likelihood or probability that a non-buyer makes a purchase in the near future learning from the past two months. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Convert | Likelihood to Convert - This Month | The likelihood or probability that a non-buyer makes a purchase in the near future learning from the past month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Convert | Likelihood to Convert - Today | The likelihood or probability that a non-buyer makes a purchase in the near future learning from today’s behavior. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Engage on Email | Likelihood to Engage on Email - 1 Month Ago | The likelihood or probability that someone opens an email in the near future learning from email events from a month ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Engage on Email | Likelihood to Engage on Email- 2 Months Ago | The likelihood or probability that someone opens an email in the near future learning from email events from two months ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Engage on Email | Likelihood to Engage on Email - This Month | The likelihood or probability that someone opens an email in the near future learning from email events from this month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Engage on Email | Likelihood to Engage on Email - Today | The likelihood or probability that someone opens an email in the near future learning from today’s email events. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Pay Full Price | Likelihood to Pay Full Price - 1 Month Ago | The likelihood or probability that someone pays full price in the near future learning from a month ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Pay Full Price | Likelihood to Pay Full Price- 2 Months Ago | The likelihood or probability that someone pays full price in the near future learning from two months ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Pay Full Price | Likelihood to Pay Full Price - This Month | The likelihood or probability that someone pays full price in the near future learning from this month. Likelihood to Pay Full Price- 2 Months Ago To set up the model, contact your CVM. | Yes |
| Likelihood to Pay Full Price | Likelihood to Pay Full Price - Today | The likelihood or probability that someone pays full price in the near future learning from today. Likelihood to Pay Full Price- 2 Months Ago To set up the model, contact your CVM. | Yes |
| Next Best Action | Next Best Channel | The next best channel that the customer is most likely to engage with. | Yes |
| Next Best Action | Second Best Channel | The second next best channel that the customer is most likely to engage with. | Yes |
| Predictive Lifetime Value | Predictive Lifetime Value - Decile - Today | The buckets the predictive lifetime value from a customer into groups. | Yes |
| Predictive Lifetime Value | Predictive Lifetime Value - Revenue Group - Today | The buckets the predictive lifetime revenue from a customer into groups. | Yes |
| Predictive Sends | Optimal Email Send Time - Overall | The optimum time when emails can be sent to a customer. | Yes |
| Predictive Sends | Optimal Email Send Time - Weekday | The optimum time during weekdays when emails can be sent to a customer. | Yes |
| Predictive Sends | Optimal Email Send Time - Weekend | The optimum time during the weekends when emails can be sent to a customer. | Yes |
| Product based Cluster | Product based Cluster - 1 Month Ago | The customer personas based on the products or product categories they purchased from a month ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Product based Cluster | Product based Cluster - 2 Months Ago | The customer personas based on the products or product categories they purchased from two months ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Product based Cluster | Product based Cluster - This Month | The customer personas based on the products or product categories they purchased from this month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your . | Yes |
| Product based Cluster | Product based Cluster - Today | The customer personas based on the products or product categories they purchased from. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| First Item Details | First Item Brand | The brand of the first item. | No |
| First Item Details | First Item Color | The color of the first item. | No |
| First Item Details | First Item Size | The size of the first item. | No |
| First Item Details | First Product ID | The ID of the first product. | No |
| First Item Details | First Product Name | The name of the first product. | No |
| First Item Details | Selected Dimension First Item | The first item of the selected dimension. The value of this field is determined by the value set in the Analysis By Dimension filter. | No |
| Second Item Details | Second Category Name Level 1 | The category name of the level 1 second item. | No |
| Second Item Details | Second Category Name Level 2 | The category name of the level 2 second item. | No |
| Second Item Details | Second Category Name Level 3 | The category name of the level 3 second item. | No |
| Second Item Details | Second Category Name Level 4 | The category name of the level 4 second item. | No |
| Second Item Details | Second Category Name Level 5 | The category name of the level 5 second item. | No |
| Second Item Details | Second Item Brand | The brand of the second item. | No |
| Second Item Details | Second Item Color | The color of the second item. | No |
| Second Item Details | Second Item Size | The size of the second item. | No |
| Second Item Details | Second Product ID | The ID of the second product. | No |
| Second Item Details | Second Product Name | The name of the second product. | No |
| Second Item Details | Selected Dimension Second Item | The second item of the selected dimension. The value of this field is determined by the value set in the Analysis By Dimension filter. | No |
Physical:Offline storesWarehouse: Warehousing locations, if anyOther: The channels that do not fall into earlier categories such as call centers.| No |
| - | Sales Org ID | A unique identifier for sales organization | No |
| - | Sales Org Name | The name for sales organization | No |
| - | Sales Org Type | The type of sales organization, an optional level of categorization after the sales channel. For example, Physical sales organizations may have types such as ‘Retail’ or ‘Outlet’ whereas Digital sales organizations may have a type such as ‘eCommerce’. The possible values for your environment depend on data provided during implementation. | No |
| Days since Customer First Transaction |
| The number of days between a given transaction and the customer’s first transaction. Note that this field is calculated at the transaction level, and it does not indicate customer tenure as of today. Instead, it indicates customer tenure as of when the transaction was made. |
| Yes |
| Days since Customer First Transaction | Days since Customer First Transaction Group | The bucketed version of [Days since Customer First Transaction] for transaction. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 1 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics, or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 2 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 3 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 4 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 5 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Transaction Date | Date | The date of the transaction made by the customer. | No |
| Transaction Date | Day of Month | The day of the month of the transaction made by the customer. | No |
| Transaction Date | Day of Week | The day of the week of the transaction made by the customer. | No |
| Transaction Date | Month | The month when the transaction was made by the customer. | No |
| Transaction Date | Month Name | The name of the month when the transaction was made by the customer. | No |
| Transaction Date | Quarter | The quarter when the transaction was made by the customer. | No |
| Transaction Date | Quarter of Year | The quarter of the year when the transaction was made by the customer. | No |
| Transaction Date | Week of Year | The week of the year when the transaction was made by the customer. | No |
| Transaction Date | Year | The year when the transaction was made by the customer. | No |
| - | Transaction Date - Is Before YTD (Yes / No) | A flag to indicate whether the day of year from [Transaction Date] is before today’s day of year. This flag is typically used for Year over Year (YoY) reporting. You can create a report with [Transaction Date - Month Name] dimension, pivot on [Transaction Date - Year] dimension, and add [Transaction Date - Is Before YTD] as a filter with ‘Yes’ value. Such a report accurately compares measures sliced by [Transaction Date] in a YoY fashion. | No |
| Transaction Fiscal Date | Transaction Fiscal Month Num | The fiscal month number of the customer’s transaction date. | No |
| Transaction Fiscal Date | Transaction Fiscal Quarter of Year | The fiscal quarter of the year of the customer’s transaction date. | No |
| Transaction Fiscal Date | Transaction Fiscal Week of Year | The fiscal week of the year of the customer’s transaction date. | No |
| Transaction Fiscal Date | Transaction Fiscal Year | The fiscal calendar year of the customer’s transaction date. | No |
| Transaction Line Date | Date | The date of the transaction made by the customer at the line level. | No |
| Transaction Line Date | Day of Month | The day of the month of the transaction made by the customer at the line level. | No |
| Transaction Line Date | Day of Week | The day of the week of the transaction made by the customer at the line level. | No |
| Transaction Line Date | Month | The month when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Month Name | The name of the month when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Quarter | The quarter when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Quarter of Year | The quarter of the year when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Week of Year | The week of the year when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Year | The year when the transaction was made by the customer at the line level. | No |
| - | Transaction Line Date - Is Before YTD (Yes / No) | A flag to indicate whether the day of year from [Transaction Line Date] is before today’s day of year. This flag is typically used for Year over Year (YoY) reporting. You create a report with [Transaction Line Date - Month Name] dimension, pivot on [Transaction Line Date - Year] dimension, and add [Transaction Line Date - Is Before YTD] as a filter with ‘Yes’ value. Such a report accurately compares measures sliced by [Transaction Line Date] in a YoY fashion. | No |
| Transaction Line Fiscal Date | Transaction Line Fiscal Month Num | The fiscal month number of the customer’s transaction line date. | No |
| Transaction Line Fiscal Date | Transaction Line Fiscal Quarter of Year | The fiscal quarter of the year of the customer’s transaction line date. | No |
| Transaction Line Fiscal Date | Transaction Line Fiscal Week of Year | The fiscal week of the year of the customer’s transaction line date. | No |
| Transaction Line Fiscal Date | Transaction Line Fiscal Year | The fiscal calendar year of the customer’s transaction line date. | No |
| - | Transaction Line SubType | The subtype of transaction line, possible values are ‘Demand’, ‘Canceled’, ‘Shipped’, and ‘Returned’. | No |
| - | Transaction Line Type | The type of transaction line, default value is ‘Purchase’. Contact your CDP CVM for descriptions if you have custom transaction linetypes. | No |
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| No |
| - | Campaign Name | The name of the campaign. | No |
| Campaign Start Date | Date | The date when the campaign started. | No |
| Campaign Start Date | Day of Month | The day of the month when the campaign started. | No |
| Campaign Start Date | Day of Week | The day of the week when the campaign started. | No |
| Campaign Start Date | Hour of Day | The hour of the day when the campaign started. | No |
| Campaign Start Date | Month | The month when the campaign started. | No |
| Campaign Start Date | Month Name | The name of the month when the campaign started. | No |
| Campaign Start Date | Quarter | The quarter when the campaign started. | No |
| Campaign Start Date | Quarter of Year | The quarter of the year when the campaign started. | No |
| Campaign Start Date | Time of Day | The time of the day when the campaign started. | No |
| Campaign Start Date | Week of Year | The week of the year when the campaign started. | No |
| Campaign Start Date | Year | The year when the campaign started. | No |
| The age of the customer. |
| No |
| Age | Age Group | The age of the customer, grouped into buckets for easier use. | No |
| - | Buyer Identification | The dimension that indicates whether the customer is an identified or unidentified buyer. All transactions that have a blank or null Customer get attributed to a generic Unidentified customer. This is primarily used with Sales Organization dimensions to view a distribution of revenue attributed to unidentified individuals for POS sales. | Yes |
| Buying Stats | AOV | The average order value for customers calculated using [Product Revenue] / [Transaction Count]. | Yes |
| Buying Stats | Average Annual Transactions | The annual transaction frequency for customer calculated using [Transaction Count] * 365 / [Days since First Transaction]. | Yes |
| Buying Stats | Average Discount Rate | The average discount rate for customers to identify promotion driven customers. | Yes |
| Buying Stats | First Transaction Revenue | The revenue from the customer’s first transaction. Note that ranges are inclusive at the higher bound. For example, ‘0-25’ includes up to 25, ‘25-50’ starts at 25.01. | Yes |
| Buying Stats | Last Transaction Interval | The number of months between the last and the second to last transaction of the customer. | Yes |
| Buying Stats | Revenue - 13-24 Months | The total revenue for customer’s purchases in the previous 13-24 month duration. Note that ranges are inclusive at the higher bound. For example, ‘0-100’ includes up to 100, ‘100-200’ starts at 100.01. | Yes |
| Buying Stats | Revenue - Last 12 Months | The total revenue for customer’s purchases in the last 12 month duration. Note that ranges are inclusive at the higher bound. For example: ‘0-100’ includes up to 100, ‘100-200’ starts at 100.01. | Yes |
| Buying Stats | Revenue - Lifetime | The total revenue for all purchases in the customer’s lifetime. Note that ranges are inclusive at the higher bound. For example: ‘0-100’ includes up to 100, ‘100-200’ starts at 100.01. | Yes |
| Buying Stats | Revenue Decile - 13-24 Months | The revenue decile for customers based on total revenue for all purchases in the previous 13-24 month duration. The following are the values:
| Yes |
| Buying Stats | Revenue Decile - Last 12 Months | The revenue decile for customers based on total revenue for all purchases in the last 12 month duration. The following are the values:
| Yes |
| Buying Stats | Revenue Segment - 13-24 Months | The revenue segment for customers based on total revenue for all purchases in the previous 13-24 month duration. The following are the values:
| Yes |
| Buying Stats | Revenue Segment - Last 12 Months | The revenue segment for customers based on total revenue for all purchases in the last 12 month duration. The following are the values:
| Yes |
| Buying Stats | Revenue Trend Segment | The revenue trend segment for customers derived by comparing revenue decile in the previous 13-24 months as compared to the last 12 months. It characterizes whether they spent less (‘Downward’), the same (‘Stable’), or more (‘Upward’) in the previous 13-24 months period as compared to the last 12 months. The following are the values:
| Yes |
| Buying Stats | Transaction Count - 13-24 Months | The total number of transactions made by customers in the previous 13-24 month duration. | Yes |
| Buying Stats | Transaction Count - Last 12 Months | The total number of transactions made by customers in the last 12 month duration. | Yes |
| Buying Stats | Transaction Count - Lifetime | The total number of transactions made in a customer’s lifetime. | Yes |
| - | Category Count | The number of distinct product categories that customers purchased from in their lifetime. | Yes |
| - | Customer Gender | The gender of the customer as determined by the genderization algorithm of Customer Data Platform (CDP). Values are Female, Male, Neutral and Unknown. Neutral refers to names that are either male or female. If the gender can not be determined, CDP displays Unknown. | No |
| - | Customer Status | The buying status of the customer. Possible values include Buyer, Non Buyer, Unidentified. | Yes |
| Days since First Transaction | Days since First Transaction | The number of days since the customer’s first transaction, that is, the tenure of the customer in days. | Yes |
| Days since First Transaction | Days since First Transaction Group | The bucketed version of [Days since First Transaction] represented in months. | Yes |
| Days since Last Transaction | Days since Last Transaction | The number of days since the customer’s last transaction, that is, the recency of the customer in days. | Yes |
| Days since Last Transaction | Days since Last Transaction Group | The bucketed version of [Days since Last Transaction] represented in months. | Yes |
| Email Last Click Date | Date | The date when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Day of Month | The day of the month when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Day of Week | The day of the week when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Month | The month when the customer last clicked one of the email campaigns | Yes |
| Email Last Click Date | Month Name | The name of the month when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Quarter | The quarter when the customer last clicked one of the campaigns. | Yes |
| Email Last Click Date | Quarter of Year | The quarter of the year when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Week of Year | The week of the year when the customer last clicked one of the email campaigns. | Yes |
| Email Last Click Date | Year | The year when the customer last clicked one of the email campaigns. | Yes |
| Email Last Open Date | Date | The date when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Day of Month | The day of the month when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Day of Week | The day of the week when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Month | The month when the customer last opened one of the email campaigns | Yes |
| Email Last Open Date | Month Name | The name of the month when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Quarter | The quarter when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Quarter of Year | The quarter of the year when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Week of Year | The week of the year when the customer last opened one of the email campaigns. | Yes |
| Email Last Open Date | Year | The year when the customer last opened one of the email campaigns. | Yes |
| Email Last Send Date | Date | The date when the customer was last sent an email. | Yes |
| Email Last Send Date | Day of Month | The day of the month when the customer was last sent an email. | Yes |
| Email Last Send Date | Day of Week | The day of the week when the customer was last sent an email. | Yes |
| Email Last Send Date | Month | The month when the customer was last sent an email. | Yes |
| Email Last Send Date | Month Name | The name of the month when the customer was last sent an email. | Yes |
| Email Last Send Date | Quarter | The quarter when the customer was last sent an email. | Yes |
| Email Last Send Date | Quarter of Year | The quarter of the year when the customer was last sent an email. | Yes |
| Email Last Send Date | Week of Year | The week of the year when the customer was last sent an email. | Yes |
| Email Last Send Date | Year | The year when the customer was last sent an email. | Yes |
| First Transaction (Digital) Date | Date | The date of the first transaction made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Day of Month | The day of the month of the first transaction made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Day of Week | The day of the week of the first transaction made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Month | The month when the first transaction was made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Month Name | The name of the month when the first transaction was made by the customer in the digital format. | Yes |
| First Transaction (Digital) Date | Quarter | The quarter when the first transaction was made by the customer in the digital format. | Yes |
| First Transaction (Digital) Date | Quarter of Year | The quarter of the year when the first transaction was made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Week of Year | The week of the year when the first transaction was made by a customer in the digital format. | Yes |
| First Transaction (Digital) Date | Year | The year when the first transaction was made by a customer in the digital format. | Yes |
| First Transaction (Physical) Date | Date | The date of the first transaction made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Day of Month | The day of the month of the first transaction made by a customer in the physical format. | Yes |
| First Transaction (Physical) Date | Day of Week | The day of the week of the first transaction made by a customer in the physical format. | Yes |
| First Transaction (Physical) Date | Month | The month when the first transaction was made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Month Name | The name of the month when the first transaction was made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Quarter | The quarter when the first transaction was made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Quarter of Year | The quarter of the year when the first transaction was made by the customer in the physical format. | Yes |
| First Transaction (Physical) Date | Week of Year | The week of the year when the first transaction was made by a customer in the physical format. | Yes |
| First Transaction (Physical) Date | Year | The year when the first transaction was made by a customer in the physical format. | Yes |
| First Transaction Date | Date | The date of the first transaction made by a customer. | Yes |
| First Transaction Date | Day of Month | The day of the month of the first transaction made by a customer. | Yes |
| First Transaction Date | Day of Week | The day of the week of the first transaction made by a customer. | Yes |
| First Transaction Date | Month | The month when the first transaction was made by a customer. | Yes |
| First Transaction Date | Month Name | The name of the month when the first transaction was made by a customer. | Yes |
| First Transaction Date | Quarter | The quarter when the first transaction was made by a customer. | Yes |
| First Transaction Date | Quarter of Year | The quarter of the year when the first transaction was made by a customer. | Yes |
| First Transaction Date | Week of Year | The week of the year when the first transaction was made by a customer. | Yes |
| First Transaction Date | Year | The year when the first transaction was made by a customer. | Yes |
| - | First Transaction Date - Is Before YTD (Yes / No) | A flag to indicate whether the day of year from customer’s [First Transaction Date] is before today’s day of year. This flag is typically used for Year over Year (YoY) reporting. You can create a report with [First Transaction Date - Month Name] dimension, pivot on [First Transaction Date - Year] dimension, and add [First Transaction Date - Is Before YTD] as a filter with ‘Yes’ value. Such a report accurately compares measures sliced by [First Transaction Date] in a YoY fashion. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Month Num | The fiscal month number of the customer’s first transaction date. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Quarter of Year | The fiscal quarter of the year of the customer’s first transaction date. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Week of Year | The fiscal week of the year of the customer’s first transaction date. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Year | The fiscal year of the customer’s first transaction date. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 1 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics, or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 2 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 3 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 4 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Last Marketing Touch - Online | First Transaction Last Marketing Touch - Online 5 | The last of all online marketing touches, which are responsible for the customer’s first transaction. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 1 | The product categories for products bought in a customer’s first transaction. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 2 | The product categories for products bought in a customer’s first transaction. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 3 | The product categories for products bought in a customer’s first transaction. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 4 | The product categories for products bought in a customer’s first transaction. | Yes |
| First Transaction Product Category | First Transaction Product Category - Level 5 | The product categories for products bought in a customer’s first transaction. | Yes |
| Last Transaction (Digital) Date | Date | The date of the last transaction made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Day of Month | The day of the month of the last transaction made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Day of Week | The day of the week of the last transaction made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Month | The month when the last transaction was made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Month Name | The name of the month when the last transaction was made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Quarter | The quarter when the last transaction was made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Quarter of Year | The quarter of the year when the last transaction was made by the customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Week of Year | The week of the year when the last transaction was made by a customer in the digital format. | Yes |
| Last Transaction (Digital) Date | Year | The year when the last transaction was made by a customer in the digital format. | Yes |
| Last Transaction (Physical) Date | Date | The date of the last transaction made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Day of Month | The day of the month of the last transaction made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Day of Week | The day of the week of the last transaction made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Month | The month when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Month Name | The name of the month when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Quarter | The quarter when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Quarter of Year | The quarter of the year when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Week of Year | The week of the year when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction (Physical) Date | Year | The year when the last transaction was made by the customer in the physical format. | Yes |
| Last Transaction Date | Date | The date of the last transaction made by the customer. | Yes |
| Last Transaction Date | Day of Month | The day of the month of the last transaction made by the customer. | Yes |
| Last Transaction Date | Day of Week | The day of the week of the last transaction made by the customer. | Yes |
| Last Transaction Date | Month | The month when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Month Name | The name of the month when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Quarter | The quarter when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Quarter of Year | The quarter of the year when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Week of Year | The week of the year when the last transaction was made by the customer. | Yes |
| Last Transaction Date | Year | The year when the last transaction was made by a customer. | Yes |
| - | Last Transaction Date - Is Before YTD (Yes / No) | A flag to indicate whether the day of year from customer’s [Last Transaction Date] is before today’s day of year. CDP uses this flag for Year over Year (YoY) reporting. You can create a report with [Last Transaction Date - Month Name] dimension, pivot on [Last Transaction Date - Year] dimension, and add [Last Transaction Date - Is Before YTD] as a filter with ‘Yes’ value. Such a report accurately compares measures sliced by [Last Transaction Date] in a YoY fashion. | Yes |
| Last Transaction Fiscal Date | Last Transaction Fiscal Month Num | The fiscal month number of the customer’s last transaction date. | Yes |
| Last Transaction Fiscal Date | Last Transaction Fiscal Quarter of Year | The fiscal quarter of the year of the customer’s last transaction date. | Yes |
| Last Transaction Fiscal Date | Last Transaction Fiscal Week of Year | The fiscal week of the year of the customer’s last transaction date. | Yes |
| First Transaction Fiscal Date | First Transaction Fiscal Year | The fiscal year of the customer’s last transaction date. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 1 | The product categories for products bought in the customer’s last transaction. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 2 | The product categories for products bought in the customer’s last transaction. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 3 | The product categories for products bought in the customer’s last transaction. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 4 | The product categories for products bought in the customer’s last transaction. | Yes |
| Last Transaction Product Category | Last Transaction Product Category - Level 5 | The product categories for products bought in the customer’s last transaction. | Yes |
| Marketing Status & Preferences | Address Certified | A Flag to indicate whether the customer’s primary address has been certified by the CDP Data Quality Engine (using USPS CASS certification): ‘True’ means that the address is CASS certified, ‘False’ means the address is not CASS certified (and likely invalid), ‘Unknown’ means that there is either no address, or that the address is not in the US / Canada (those are the only countries we can certify right now). | No |
| Marketing Status & Preferences | Address DPV Confirmed | A flag to indicate whether the customer’s primary address has been Delivery Point Validation confirmed. DPV is the process of verifying that an address is actually deliverable, meaning that mail can be sent to that address. A single street address may have multiple delivery points, such as individual units in an apartment building. ‘Y’ means the address is DPV confirmed whereas ‘N’ means the address is not DPV confirmed. Typically, all DPV confirmed addresses are also Certified but all Certified addresses may not be DPV confirmed. | No |
| Marketing Status & Preferences | Do Not Call | A flag to indicate whether the customer has opted-in or opted-out of the Call campaigns. ‘Y’ means customer has opted-out whereas ‘N’ means customer has opted-in. | No |
| Marketing Status & Preferences | Do Not Email | A flag to indicate whether the customer has opted-in or opted-out of the Email campaigns. ‘Y’ means customer has opted-out whereas ‘N’ means customer has opted-in. | No |
| Marketing Status & Preferences | Do Not Mail | A flag to indicate whether the customer has opted-in or opted-out of the Direct Mail campaigns. ‘Y’ means customer has opted-out whereas ‘N’ means customer has opted-in. | No |
| Marketing Status & Preferences | Do Not Text | A flag to indicate whether the customer has opted-in or opted-out of the SMS or Text campaigns. ‘Y’ means customer has opted-out whereas ‘N’ means customer has opted-in. | No |
| Marketing Status & Preferences | Email Domain | The domain of the customer’s email address. | No |
| Marketing Status & Preferences | Email Status | A flag to indicate the validity of the customer’s email address. The following are the values:
-‘X’: ‘Invalid’, the email address syntax is invalid. | No |
| - | Primary Brand | The product brands that customers made most transactions during their lifetime. | Yes |
| - | Product Count | Number of distinct products purchased by customers during their lifetime. | Yes |
| Sales Organizations | Closest Store | The closest store for customers. | Yes |
| Sales Organizations | Distance to Closest Store | The distance, in miles, between customer and the closest store. This dimension works only for US, Canada and UK addresses (for both stores and customers). | Yes |
| Sales Organizations | First Transaction Sales Channel | The sales channel of the customer’s first transaction. The following are the values:
| Yes |
| Sales Organizations | Last Transaction Sales Channel | The sales channel of the customer’s last transaction. The following are the values:
| Yes |
| Sales Organizations | Primary Physical Store | The physical Store that customer made most transactions in during their lifetime | Yes |
| Sales Organizations | Primary Sales Channel | The sales Channel that the customer made most transactions in during their lifetime. The following are the values:
| Yes |
| Sales Organizations | Sales Channel Count | Number of sales channels customers have purchased from in their lifetime. | Yes |
| Second to Last Transaction Date | Date | The date of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Day of Month | The day of the month of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Day of Week | The day of week of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Month | The month of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Month Name | The name of the month of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Quarter | The quarter of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Quarter of Year | The quarter of the year of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Week of Year | The week of the year of the second to last transaction made by the customer. | Yes |
| Second to Last Transaction Date | Year | The year of the second to last transaction made by the customer. | Yes |
| Web First Visit Date | Date | The date when a customer first visited the website. | Yes |
| Web First Visit Date | Day of Month | The day of the month when a customer first visited the website. | Yes |
| Web First Visit Date | Day of Week | The day of the week when a customer first visited the website. | Yes |
| Web First Visit Date | Month | The month when a customer first visited the website. | Yes |
| Web First Visit Date | Month Name | The name of the month when a customer first visited the website. | Yes |
| Web First Visit Date | Quarter | The quarter when a customer first visited the website. | Yes |
| Web First Visit Date | Quarter of Year | The quarter of the year when a customer first visited the website. | Yes |
| Web First Visit Date | Week of Year | The week of the year when a customer first visited the website. | Yes |
| Web First Visit Date | Year | The year when a customer first visited the website. | Yes |
| Web Last Visit Date | Date | The date when a customer last visited the website. | Yes |
| Web Last Visit Date | Day of Month | The day of the month when the customer last visited the website. | Yes |
| Web Last Visit Date | Day of Week | The day of the week when the customer last visited the website. | Yes |
| Web Last Visit Date | Month | The month when the customer last visited the website. | Yes |
| Web Last Visit Date | Month Name | The name of the month when the customer last visited the website. | Yes |
| Web Last Visit Date | Quarter | The quarter when the customer last visited the website. | Yes |
| Web Last Visit Date | Quarter of Year | The quarter of the year when the customer last visited the website. | Yes |
| Web Last Visit Date | Week of Year | The week of the year when the customer last visited the website. | Yes |
| Web Last Visit Date | Year | The year when the customer last visited the website. | Yes |
Yes |
Campaign Execution Date | Day of Week | The day of the week when the campaign or segment was executed. For example, Monday, Tuesday, and so on. | Yes |
Campaign Execution Date | Month | The numeric representation of the month when the campaign or segment was executed. For example, 1 for January, 2 for February, and so on. | Yes |
Campaign Execution Date | Month Name | The name of the month when the campaign or segment was executed. For example, January, February, and so on. | Yes |
Campaign Execution Date | Quarter | The quarter of the year when the campaign or segment was executed. For example, Q1, Q2, Q3, and Q4. | Yes |
Campaign Execution Date | Quarter of Year | The numeric representation of the quarter when the campaign or segment was executed. For example, 1, 2, 3, and 4. | Yes |
Campaign Execution Date | Time | The timestamp indicating the time when the campaign or segment was executed. | Yes |
Campaign Execution Date | Time of Day | The specific time of day when the campaign or segment was executed. For example, morning, afternoon, evening, and so on. | Yes |
Campaign Execution Date | Week of Year | The week number within the year when the campaign or segment was executed. | Yes |
Campaign Execution Date | Year | The year when the campaign or segment was executed. | Yes |
- | Campaign ID | The unique identifier associated with the campaign. | Yes |
- | Campaign Name | The name or title of the campaign. | Yes |
- | Segment ID | The unique identifier associated with the segment. | Yes |
- | Segment Name | The name or title of the segment. | Yes |
- | Variant Name | The specific variant or version of a campaign or segment, if applicable. | Yes |
| The cluster of customers personas based on their purchase behavior, preferences, and spending patterns today. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. |
| Yes |
CC Studio | Custom Calculation Dimension | The custom calculation dimension created within CC Studio for specific analytic needs. | Yes |
| Fuzzy Clustering | Most Likely Cluster Probability | The probability of a customer belonging to a cluster with the best match. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Most Likely Cluster Value | The cluster where the customer belongs to with the highest probability. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Second Most Likely Cluster Probability | The probability of a customer belonging to a cluster with the second best match. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Second Most Likely Cluster Value | The cluster where the customer belongs to with the second highest probability. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Third Most Likely Cluster Probability | The probability of a customer belonging to a cluster with the third best match. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Fuzzy Clustering | Third Most Likely Cluster Value | The cluster where the customer belongs to with the third highest probability. Customers are matched to clusters based on purchase behavior, preferences, and spending patterns. | Yes |
| Likelihood to Buy | Likelihood to Buy - 1 Month Ago | The likelihood or probability that an existing customer makes a purchase in the near future based on behaviors a month ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Buy | Likelihood to Buy - 2 Months Ago | The likelihood or probability that an existing customer makes a purchase in the near future based on behaviors two months ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Buy | Likelihood to Buy - This Month | The likelihood or probability that an existing customer makes a purchase in the near future based on behaviors this month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Buy | Likelihood to Buy - Today | The likelihood or probability that an existing customer makes a purchase in the near future based on today’s behaviors. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Convert | Likelihood to Convert - 1 Month Ago | The likelihood or probability that a non-buyer makes a purchase in the near future learning from the past one month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Convert | Likelihood to Convert - 2 Months Ago | The likelihood or probability that a non-buyer makes a purchase in the near future learning from the past two months. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Convert | Likelihood to Convert - This Month | The likelihood or probability that a non-buyer makes a purchase in the near future learning from the past month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Convert | Likelihood to Convert - Today | The likelihood or probability that a non-buyer makes a purchase in the near future learning from today’s behavior. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Engage on Email | Likelihood to Engage on Email - 1 Month Ago | The likelihood or probability that someone opens an email in the near future learning from email events from a month ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Engage on Email | Likelihood to Engage on Email- 2 Months Ago | The likelihood or probability that someone opens an email in the near future learning from email events from two months ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Engage on Email | Likelihood to Engage on Email - This Month | The likelihood or probability that someone opens an email in the near future learning from email events from this month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Engage on Email | Likelihood to Engage on Email - Today | The likelihood or probability that someone opens an email in the near future learning from today’s email events. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Pay Full Price | Likelihood to Pay Full Price - 1 Month Ago | The likelihood or probability that someone pays full price in the near future learning from a month ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Pay Full Price | Likelihood to Pay Full Price- 2 Months Ago | The likelihood or probability that someone pays full price in the near future learning from two months ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Likelihood to Pay Full Price | Likelihood to Pay Full Price - This Month | The likelihood or probability that someone pays full price in the near future learning from this month. Likelihood to Pay Full Price- 2 Months Ago To set up the model, contact your CVM. | Yes |
| Likelihood to Pay Full Price | Likelihood to Pay Full Price - Today | The likelihood or probability that someone pays full price in the near future learning from today. Likelihood to Pay Full Price- 2 Months Ago To set up the model, contact your CVM. | Yes |
| Next Best Action | Next Best Channel | The next best channel that the customer is most likely to engage with. | Yes |
| Next Best Action | Second Best Channel | The second next best channel that the customer is most likely to engage with. | Yes |
| Predictive Lifetime Value | Predictive Lifetime Value - Decile - Today | The buckets the predictive lifetime value from a customer into groups. | Yes |
| Predictive Lifetime Value | Predictive Lifetime Value - Revenue Group - Today | The buckets the predictive lifetime revenue from a customer into groups. | Yes |
| Predictive Sends | Optimal Email Send Time - Overall | The optimum time when emails can be sent to a customer. | Yes |
| Predictive Sends | Optimal Email Send Time - Weekday | The optimum time during weekdays when emails can be sent to a customer. | Yes |
| Predictive Sends | Optimal Email Send Time - Weekend | The optimum time during the weekends when emails can be sent to a customer. | Yes |
| Product based Cluster | Product based Cluster - 1 Month Ago | The customer personas based on the products or product categories they purchased from a month ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Product based Cluster | Product based Cluster - 2 Months Ago | The customer personas based on the products or product categories they purchased from two months ago. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| Product based Cluster | Product based Cluster - This Month | The customer personas based on the products or product categories they purchased from this month. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your . | Yes |
| Product based Cluster | Product based Cluster - Today | The customer personas based on the products or product categories they purchased from. You can turn off the ML dimension or the ML dimension may not have data in your environment, if the ML models are not trained. To set up the model, contact your CVM. | Yes |
| First Item Details | First Item Brand | The brand of the first item. | No |
| First Item Details | First Item Color | The color of the first item. | No |
| First Item Details | First Item Size | The size of the first item. | No |
| First Item Details | First Product ID | The ID of the first product. | No |
| First Item Details | First Product Name | The name of the first product. | No |
| First Item Details | Selected Dimension First Item | The first item of the selected dimension. The value of this field is determined by the value set in the Analysis By Dimension filter. | No |
| Second Item Details | Second Category Name Level 1 | The category name of the level 1 second item. | No |
| Second Item Details | Second Category Name Level 2 | The category name of the level 2 second item. | No |
| Second Item Details | Second Category Name Level 3 | The category name of the level 3 second item. | No |
| Second Item Details | Second Category Name Level 4 | The category name of the level 4 second item. | No |
| Second Item Details | Second Category Name Level 5 | The category name of the level 5 second item. | No |
| Second Item Details | Second Item Brand | The brand of the second item. | No |
| Second Item Details | Second Item Color | The color of the second item. | No |
| Second Item Details | Second Item Size | The size of the second item. | No |
| Second Item Details | Second Product ID | The ID of the second product. | No |
| Second Item Details | Second Product Name | The name of the second product. | No |
| Second Item Details | Selected Dimension Second Item | The second item of the selected dimension. The value of this field is determined by the value set in the Analysis By Dimension filter. | No |
Physical:Offline storesWarehouse: Warehousing locations, if anyOther: The channels that do not fall into earlier categories such as call centers.| No |
| - | Sales Org ID | A unique identifier for sales organization | No |
| - | Sales Org Name | The name for sales organization | No |
| - | Sales Org Type | The type of sales organization, an optional level of categorization after the sales channel. For example, Physical sales organizations may have types such as ‘Retail’ or ‘Outlet’ whereas Digital sales organizations may have a type such as ‘eCommerce’. The possible values for your environment depend on data provided during implementation. | No |
| Days since Customer First Transaction |
| The number of days between a given transaction and the customer’s first transaction. Note that this field is calculated at the transaction level, and it does not indicate customer tenure as of today. Instead, it indicates customer tenure as of when the transaction was made. |
| Yes |
| Days since Customer First Transaction | Days since Customer First Transaction Group | The bucketed version of [Days since Customer First Transaction] for transaction. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 1 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics, or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 2 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 3 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 4 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Last Marketing Touch - Online | Last Marketing Touch - Online 5 | The last of all online marketing touches, which are responsible for transactions. This data typically comes from web analytics providers such as Google Analytics, Adobe Analytics or IBM Coremetrics. Represented with the following levels: Source, Medium, Campaign, Adgroup, Keyword. | Yes |
| Transaction Date | Date | The date of the transaction made by the customer. | No |
| Transaction Date | Day of Month | The day of the month of the transaction made by the customer. | No |
| Transaction Date | Day of Week | The day of the week of the transaction made by the customer. | No |
| Transaction Date | Month | The month when the transaction was made by the customer. | No |
| Transaction Date | Month Name | The name of the month when the transaction was made by the customer. | No |
| Transaction Date | Quarter | The quarter when the transaction was made by the customer. | No |
| Transaction Date | Quarter of Year | The quarter of the year when the transaction was made by the customer. | No |
| Transaction Date | Week of Year | The week of the year when the transaction was made by the customer. | No |
| Transaction Date | Year | The year when the transaction was made by the customer. | No |
| - | Transaction Date - Is Before YTD (Yes / No) | A flag to indicate whether the day of year from [Transaction Date] is before today’s day of year. This flag is typically used for Year over Year (YoY) reporting. You can create a report with [Transaction Date - Month Name] dimension, pivot on [Transaction Date - Year] dimension, and add [Transaction Date - Is Before YTD] as a filter with ‘Yes’ value. Such a report accurately compares measures sliced by [Transaction Date] in a YoY fashion. | No |
| Transaction Fiscal Date | Transaction Fiscal Month Num | The fiscal month number of the customer’s transaction date. | No |
| Transaction Fiscal Date | Transaction Fiscal Quarter of Year | The fiscal quarter of the year of the customer’s transaction date. | No |
| Transaction Fiscal Date | Transaction Fiscal Week of Year | The fiscal week of the year of the customer’s transaction date. | No |
| Transaction Fiscal Date | Transaction Fiscal Year | The fiscal calendar year of the customer’s transaction date. | No |
| Transaction Line Date | Date | The date of the transaction made by the customer at the line level. | No |
| Transaction Line Date | Day of Month | The day of the month of the transaction made by the customer at the line level. | No |
| Transaction Line Date | Day of Week | The day of the week of the transaction made by the customer at the line level. | No |
| Transaction Line Date | Month | The month when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Month Name | The name of the month when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Quarter | The quarter when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Quarter of Year | The quarter of the year when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Week of Year | The week of the year when the transaction was made by the customer at the line level. | No |
| Transaction Line Date | Year | The year when the transaction was made by the customer at the line level. | No |
| - | Transaction Line Date - Is Before YTD (Yes / No) | A flag to indicate whether the day of year from [Transaction Line Date] is before today’s day of year. This flag is typically used for Year over Year (YoY) reporting. You create a report with [Transaction Line Date - Month Name] dimension, pivot on [Transaction Line Date - Year] dimension, and add [Transaction Line Date - Is Before YTD] as a filter with ‘Yes’ value. Such a report accurately compares measures sliced by [Transaction Line Date] in a YoY fashion. | No |
| Transaction Line Fiscal Date | Transaction Line Fiscal Month Num | The fiscal month number of the customer’s transaction line date. | No |
| Transaction Line Fiscal Date | Transaction Line Fiscal Quarter of Year | The fiscal quarter of the year of the customer’s transaction line date. | No |
| Transaction Line Fiscal Date | Transaction Line Fiscal Week of Year | The fiscal week of the year of the customer’s transaction line date. | No |
| Transaction Line Fiscal Date | Transaction Line Fiscal Year | The fiscal calendar year of the customer’s transaction line date. | No |
| - | Transaction Line SubType | The subtype of transaction line, possible values are ‘Demand’, ‘Canceled’, ‘Shipped’, and ‘Returned’. | No |
| - | Transaction Line Type | The type of transaction line, default value is ‘Purchase’. Contact your CDP CVM for descriptions if you have custom transaction linetypes. | No |
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Acquia CDP