Acquia CDP

Dimensions tables

The following is the list of tables for standard dimensions:

Dimension tableDescription
AttributionTrack 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.
CustomerGroup customer-specific attributes, such as demographics, customer IDs, or segments.
CohortsGroup customers or entities based on shared characteristics or behaviors within a specific timeframe. These dimensions are often used for Cohort Analysis.
Machine LearningCategorize or predict behaviors or outcomes based on historical data patterns. These dimensions are generated or influenced by machine learning algorithms.
Market Basket AnalysisGroup the items purchased together in transactions. These dimensions are often used to understand purchasing patterns and recommend related products.
ProductGroup individual products such as product IDs, names, descriptions, or attributes.
Product CategoryCategorize products into groups or hierarchies based on shared characteristics or types.
Sales OrganizationGroup organizational units responsible for sales. For example, sales regions, teams, or territories.
TransactionGroup transactional data such as transaction IDs, dates, amounts, or types of transactions.

Attribution

Sub-GroupDimension nameDescriptionPre-calculated field?
-Campaign ID | NameThe campaign ID and name.No
Campaign Level NamesLevel 1 NameThe name of the level 1 campaign.No
Campaign Level NamesLevel 2 NameThe name of the level 2 campaign.No
Campaign Level NamesLevel 3 NameThe name of the level 3 campaign.No
Campaign Level NamesLevel 4 NameThe name of the level 4 campaign.No
Campaign Level NamesLevel 5 NameThe name of the level 5 campaign.No
-Campaign NameThe name of the campaign.No
Campaign Start DateDateThe date when the campaign started.No
Campaign Start DateDay of MonthThe day of the month when the campaign started.No
Campaign Start DateDay of WeekThe day of the week when the campaign started.No
Campaign Start DateHour of DayThe hour of the day when the campaign started.No
Campaign Start DateMonthThe month when the campaign started.No
Campaign Start DateMonth NameThe name of the month when the campaign started.No
Campaign Start DateQuarterThe quarter when the campaign started.No
Campaign Start DateQuarter of YearThe quarter of the year when the campaign started.No
Campaign Start DateTime of DayThe time of the day when the campaign started.No
Campaign Start DateWeek of YearThe week of the year when the campaign started.No
Campaign Start DateYearThe year when the campaign started.No

Customer

Sub-GroupDimension nameDescriptionPre-calculated field?
AddressCustomer CityThe city from the customer’s primary address.No
AddressCustomer CountryThe country from the customer’s primary address.No
AddressCustomer RBDIThe 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
AddressCustomer StateThe state from the customer’s primary address.No
AddressCustomer Zip CodeThe Zip Code from the customer’s primary address.No
AgeAgeThe age of the customer.No
AgeAge GroupThe age of the customer, grouped into buckets for easier use.No
-Buyer IdentificationThe 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 StatsAOVThe average order value for customers calculated using [Product Revenue] / [Transaction Count].Yes
Buying StatsAverage Annual TransactionsThe annual transaction frequency for customer calculated using [Transaction Count] * 365 / [Days since First Transaction].Yes
Buying StatsAverage Discount RateThe average discount rate for customers to identify promotion driven customers.Yes
Buying StatsFirst Transaction RevenueThe 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 StatsLast Transaction IntervalThe number of months between the last and the second to last transaction of the customer.Yes
Buying StatsRevenue - 13-24 MonthsThe 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 StatsRevenue - Last 12 MonthsThe 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 StatsRevenue - LifetimeThe 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 StatsRevenue 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:

  • 1: Top 10%
  • 10: Bottom 10%
  • 0: The customers that have not purchased in a given time period.
Yes
Buying StatsRevenue 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:

  • 1: Top 10%
  • 10: Bottom 10%
  • 0: The customers that have not purchased in a given time period.
Yes
Buying StatsRevenue 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:

  • 1 - High Value: Top 10% by revenue
  • 2 - Medium Value: 20% to 80% by revenue
  • 3 - Low Value: Bottom 20%

Non Buyer: The customers that have not purchased in the given time

period.

Yes
Buying StatsRevenue 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:

  • 1 - High Value: Top 10% by revenue
  • 2 - Medium Value: 20% to 80% by revenue
  • 3 - Low Value: Bottom 20%

Non Buyer: The customers that have not purchased in the given time

period.

Yes
Buying StatsRevenue 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:

  • Non Buyer: The customers that have not purchased in the given time period.
  • Unidentified: Indicates invalid data.
  • 2 Period Inactive: The customers are buyers who did not make a purchase in the last 24 months but made a purchase before 24 months ago.
  • Lapsed: The customers who made a purchase in the last 13-24 months but did not make a purchase in the last 12 months.
Yes
Buying StatsTransaction Count - 13-24 MonthsThe total number of transactions made by customers in the previous 13-24 month duration.Yes
Buying StatsTransaction Count - Last 12 MonthsThe total number of transactions made by customers in the last 12 month duration.Yes
Buying StatsTransaction Count - LifetimeThe total number of transactions made in a customer’s lifetime.Yes
-Category CountThe number of distinct product categories that customers purchased from in their lifetime.Yes
-Customer GenderThe 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 StatusThe buying status of the customer. Possible values include Buyer, Non Buyer, Unidentified.Yes
Days since First TransactionDays since First TransactionThe number of days since the customer’s first transaction, that is, the tenure of the customer in days.Yes
Days since First TransactionDays since First Transaction GroupThe bucketed version of [Days since First Transaction] represented in months.Yes
Days since Last TransactionDays since Last TransactionThe number of days since the customer’s last transaction, that is, the recency of the customer in days.Yes
Days since Last TransactionDays since Last Transaction GroupThe bucketed version of [Days since Last Transaction] represented in months.Yes
Email Last Click DateDateThe date when the customer last clicked one of the email campaigns.Yes
Email Last Click DateDay of MonthThe day of the month when the customer last clicked one of the email campaigns.Yes
Email Last Click DateDay of WeekThe day of the week when the customer last clicked one of the email campaigns.Yes
Email Last Click DateMonthThe month when the customer last clicked one of the email campaignsYes
Email Last Click DateMonth NameThe name of the month when the customer last clicked one of the email campaigns.Yes
Email Last Click DateQuarterThe quarter when the customer last clicked one of the campaigns.Yes
Email Last Click DateQuarter of YearThe quarter of the year when the customer last clicked one of the email campaigns.Yes
Email Last Click DateWeek of YearThe week of the year when the customer last clicked one of the email campaigns.Yes
Email Last Click DateYearThe year when the customer last clicked one of the email campaigns.Yes
Email Last Open DateDateThe date when the customer last opened one of the email campaigns.Yes
Email Last Open DateDay of MonthThe day of the month when the customer last opened one of the email campaigns.Yes
Email Last Open DateDay of WeekThe day of the week when the customer last opened one of the email campaigns.Yes
Email Last Open DateMonthThe month when the customer last opened one of the email campaignsYes
Email Last Open DateMonth NameThe name of the month when the customer last opened one of the email campaigns.Yes
Email Last Open DateQuarterThe quarter when the customer last opened one of the email campaigns.Yes
Email Last Open DateQuarter of YearThe quarter of the year when the customer last opened one of the email campaigns.Yes
Email Last Open DateWeek of YearThe week of the year when the customer last opened one of the email campaigns.Yes
Email Last Open DateYearThe year when the customer last opened one of the email campaigns.Yes
Email Last Send DateDateThe date when the customer was last sent an email.Yes
Email Last Send DateDay of MonthThe day of the month when the customer was last sent an email.Yes
Email Last Send DateDay of WeekThe day of the week when the customer was last sent an email.Yes
Email Last Send DateMonthThe month when the customer was last sent an email.Yes
Email Last Send DateMonth NameThe name of the month when the customer was last sent an email.Yes
Email Last Send DateQuarterThe quarter when the customer was last sent an email.Yes
Email Last Send DateQuarter of YearThe quarter of the year when the customer was last sent an email.Yes
Email Last Send DateWeek of YearThe week of the year when the customer was last sent an email.Yes
Email Last Send DateYearThe year when the customer was last sent an email.Yes
First Transaction (Digital) DateDateThe date of the first transaction made by a customer in the digital format.Yes
First Transaction (Digital) DateDay of MonthThe day of the month of the first transaction made by a customer in the digital format.Yes
First Transaction (Digital) DateDay of WeekThe day of the week of the first transaction made by a customer in the digital format.Yes
First Transaction (Digital) DateMonthThe month when the first transaction was made by a customer in the digital format.Yes
First Transaction (Digital) DateMonth NameThe name of the month when the first transaction was made by the customer in the digital format.Yes
First Transaction (Digital) DateQuarterThe quarter when the first transaction was made by the customer in the digital format.Yes
First Transaction (Digital) DateQuarter of YearThe quarter of the year when the first transaction was made by a customer in the digital format.Yes
First Transaction (Digital) DateWeek of YearThe week of the year when the first transaction was made by a customer in the digital format.Yes
First Transaction (Digital) DateYearThe year when the first transaction was made by a customer in the digital format.Yes
First Transaction (Physical) DateDateThe date of the first transaction made by the customer in the physical format.Yes
First Transaction (Physical) DateDay of MonthThe day of the month of the first transaction made by a customer in the physical format.Yes
First Transaction (Physical) DateDay of WeekThe day of the week of the first transaction made by a customer in the physical format.Yes
First Transaction (Physical) DateMonthThe month when the first transaction was made by the customer in the physical format.Yes
First Transaction (Physical) DateMonth NameThe name of the month when the first transaction was made by the customer in the physical format.Yes
First Transaction (Physical) DateQuarterThe quarter when the first transaction was made by the customer in the physical format.Yes
First Transaction (Physical) DateQuarter of YearThe quarter of the year when the first transaction was made by the customer in the physical format.Yes
First Transaction (Physical) DateWeek of YearThe week of the year when the first transaction was made by a customer in the physical format.Yes
First Transaction (Physical) DateYearThe year when the first transaction was made by a customer in the physical format.Yes
First Transaction DateDateThe date of the first transaction made by a customer.Yes
First Transaction DateDay of MonthThe day of the month of the first transaction made by a customer.Yes
First Transaction DateDay of WeekThe day of the week of the first transaction made by a customer.Yes
First Transaction DateMonthThe month when the first transaction was made by a customer.Yes
First Transaction DateMonth NameThe name of the month when the first transaction was made by a customer.Yes
First Transaction DateQuarterThe quarter when the first transaction was made by a customer.Yes
First Transaction DateQuarter of YearThe quarter of the year when the first transaction was made by a customer.Yes
First Transaction DateWeek of YearThe week of the year when the first transaction was made by a customer.Yes
First Transaction DateYearThe 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 DateFirst Transaction Fiscal Month NumThe fiscal month number of the customer’s first transaction date.Yes
First Transaction Fiscal DateFirst Transaction Fiscal Quarter of YearThe fiscal quarter of the year of the customer’s first transaction date.Yes
First Transaction Fiscal DateFirst Transaction Fiscal Week of YearThe fiscal week of the year of the customer’s first transaction date.Yes
First Transaction Fiscal DateFirst Transaction Fiscal YearThe fiscal year of the customer’s first transaction date.Yes
First Transaction Last Marketing Touch - OnlineFirst Transaction Last Marketing Touch - Online 1The 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 - OnlineFirst Transaction Last Marketing Touch - Online 2The 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 - OnlineFirst Transaction Last Marketing Touch - Online 3The 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 - OnlineFirst Transaction Last Marketing Touch - Online 4The 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 - OnlineFirst Transaction Last Marketing Touch - Online 5The 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 CategoryFirst Transaction Product Category - Level 1The product categories for products bought in a customer’s first transaction.Yes
First Transaction Product CategoryFirst Transaction Product Category - Level 2The product categories for products bought in a customer’s first transaction.Yes
First Transaction Product CategoryFirst Transaction Product Category - Level 3The product categories for products bought in a customer’s first transaction.Yes
First Transaction Product CategoryFirst Transaction Product Category - Level 4The product categories for products bought in a customer’s first transaction.Yes
First Transaction Product CategoryFirst Transaction Product Category - Level 5The product categories for products bought in a customer’s first transaction.Yes
Last Transaction (Digital) DateDateThe date of the last transaction made by the customer in the digital format.Yes
Last Transaction (Digital) DateDay of MonthThe day of the month of the last transaction made by the customer in the digital format.Yes
Last Transaction (Digital) DateDay of WeekThe day of the week of the last transaction made by the customer in the digital format.Yes
Last Transaction (Digital) DateMonthThe month when the last transaction was made by the customer in the digital format.Yes
Last Transaction (Digital) DateMonth NameThe name of the month when the last transaction was made by the customer in the digital format.Yes
Last Transaction (Digital) DateQuarterThe quarter when the last transaction was made by the customer in the digital format.Yes
Last Transaction (Digital) DateQuarter of YearThe quarter of the year when the last transaction was made by the customer in the digital format.Yes
Last Transaction (Digital) DateWeek of YearThe week of the year when the last transaction was made by a customer in the digital format.Yes
Last Transaction (Digital) DateYearThe year when the last transaction was made by a customer in the digital format.Yes
Last Transaction (Physical) DateDateThe date of the last transaction made by the customer in the physical format.Yes
Last Transaction (Physical) DateDay of MonthThe day of the month of the last transaction made by the customer in the physical format.Yes
Last Transaction (Physical) DateDay of WeekThe day of the week of the last transaction made by the customer in the physical format.Yes
Last Transaction (Physical) DateMonthThe month when the last transaction was made by the customer in the physical format.Yes
Last Transaction (Physical) DateMonth NameThe name of the month when the last transaction was made by the customer in the physical format.Yes
Last Transaction (Physical) DateQuarterThe quarter when the last transaction was made by the customer in the physical format.Yes
Last Transaction (Physical) DateQuarter of YearThe quarter of the year when the last transaction was made by the customer in the physical format.Yes
Last Transaction (Physical) DateWeek of YearThe week of the year when the last transaction was made by the customer in the physical format.Yes
Last Transaction (Physical) DateYearThe year when the last transaction was made by the customer in the physical format.Yes
Last Transaction DateDateThe date of the last transaction made by the customer.Yes
Last Transaction DateDay of MonthThe day of the month of the last transaction made by the customer.Yes
Last Transaction DateDay of WeekThe day of the week of the last transaction made by the customer.Yes
Last Transaction DateMonthThe month when the last transaction was made by the customer.Yes
Last Transaction DateMonth NameThe name of the month when the last transaction was made by the customer.Yes
Last Transaction DateQuarterThe quarter when the last transaction was made by the customer.Yes
Last Transaction DateQuarter of YearThe quarter of the year when the last transaction was made by the customer.Yes
Last Transaction DateWeek of YearThe week of the year when the last transaction was made by the customer.Yes
Last Transaction DateYearThe 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 DateLast Transaction Fiscal Month NumThe fiscal month number of the customer’s last transaction date.Yes
Last Transaction Fiscal DateLast Transaction Fiscal Quarter of YearThe fiscal quarter of the year of the customer’s last transaction date.Yes
Last Transaction Fiscal DateLast Transaction Fiscal Week of YearThe fiscal week of the year of the customer’s last transaction date.Yes
First Transaction Fiscal DateFirst Transaction Fiscal YearThe fiscal year of the customer’s last transaction date.Yes
Last Transaction Product CategoryLast Transaction Product Category - Level 1The product categories for products bought in the customer’s last transaction.Yes
Last Transaction Product CategoryLast Transaction Product Category - Level 2The product categories for products bought in the customer’s last transaction.Yes
Last Transaction Product CategoryLast Transaction Product Category - Level 3The product categories for products bought in the customer’s last transaction.Yes
Last Transaction Product CategoryLast Transaction Product Category - Level 4The product categories for products bought in the customer’s last transaction.Yes
Last Transaction Product CategoryLast Transaction Product Category - Level 5The product categories for products bought in the customer’s last transaction.Yes
Marketing Status & PreferencesAddress CertifiedA 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 & PreferencesAddress DPV ConfirmedA 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 & PreferencesDo Not CallA 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 & PreferencesDo Not EmailA 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 & PreferencesDo Not MailA 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 & PreferencesDo Not TextA 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 & PreferencesEmail DomainThe domain of the customer’s email address.No
Marketing Status & PreferencesEmail Status

A flag to indicate the validity of the customer’s email address. The following are the values:

  • ‘V’: ‘Verified’, the email address syntax is valid, the domain is good or known and the email address is not a known spam trap.

‘U’: ‘Unverified’, the email address syntax is valid but the domain is

unknown or bad.

-‘X’: ‘Invalid’, the email address syntax is invalid.

No
-Primary BrandThe product brands that customers made most transactions during their lifetime.Yes
-Product CountNumber of distinct products purchased by customers during their lifetime.Yes
Sales OrganizationsClosest StoreThe closest store for customers.Yes
Sales OrganizationsDistance to Closest StoreThe 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 OrganizationsFirst Transaction Sales Channel

The sales channel of the customer’s first transaction. The following are the values:

  • Digital: Online stores
  • Physical:Offline stores
  • Warehouse: Warehousing locations, if any
  • Other: The channels that do not fall into earlier categories such as call centers.
Yes
Sales OrganizationsLast Transaction Sales Channel

The sales channel of the customer’s last transaction. The following are the values:

  • Digital: Online stores
  • Physical:Offline stores
  • Warehouse: Warehousing locations, if any
  • Other: The channels that do not fall into earlier categories such as call centers.
Yes
Sales OrganizationsPrimary Physical StoreThe physical Store that customer made most transactions in during their lifetimeYes
Sales OrganizationsPrimary Sales Channel

The sales Channel that the customer made most transactions in during their lifetime. The following are the values:

  • Digital: Online stores
  • Physical:Offline stores
  • Warehouse: Warehousing locations, if any
  • Other: The channels that do not fall into earlier categories such as call centers.
Yes
Sales OrganizationsSales Channel CountNumber of sales channels customers have purchased from in their lifetime.Yes
Second to Last Transaction DateDateThe date of the second to last transaction made by the customer.Yes
Second to Last Transaction DateDay of MonthThe day of the month of the second to last transaction made by the customer.Yes
Second to Last Transaction DateDay of WeekThe day of week of the second to last transaction made by the customer.Yes
Second to Last Transaction DateMonthThe month of the second to last transaction made by the customer.Yes
Second to Last Transaction DateMonth NameThe name of the month of the second to last transaction made by the customer.Yes
Second to Last Transaction DateQuarterThe quarter of the second to last transaction made by the customer.Yes
Second to Last Transaction DateQuarter of YearThe quarter of the year of the second to last transaction made by the customer.Yes
Second to Last Transaction DateWeek of YearThe week of the year of the second to last transaction made by the customer.Yes
Second to Last Transaction DateYearThe year of the second to last transaction made by the customer.Yes
Web First Visit DateDateThe date when a customer first visited the website.Yes
Web First Visit DateDay of MonthThe day of the month when a customer first visited the website.Yes
Web First Visit DateDay of WeekThe day of the week when a customer first visited the website.Yes
Web First Visit DateMonthThe month when a customer first visited the website.Yes
Web First Visit DateMonth NameThe name of the month when a customer first visited the website.Yes
Web First Visit DateQuarterThe quarter when a customer first visited the website.Yes
Web First Visit DateQuarter of YearThe quarter of the year when a customer first visited the website.Yes
Web First Visit DateWeek of YearThe week of the year when a customer first visited the website.Yes
Web First Visit DateYearThe year when a customer first visited the website.Yes
Web Last Visit DateDateThe date when a customer last visited the website.Yes
Web Last Visit DateDay of MonthThe day of the month when the customer last visited the website.Yes
Web Last Visit DateDay of WeekThe day of the week when the customer last visited the website.Yes
Web Last Visit DateMonthThe month when the customer last visited the website.Yes
Web Last Visit DateMonth NameThe name of the month when the customer last visited the website.Yes
Web Last Visit DateQuarterThe quarter when the customer last visited the website.Yes
Web Last Visit DateQuarter of YearThe quarter of the year when the customer last visited the website.Yes
Web Last Visit DateWeek of YearThe week of the year when the customer last visited the website.Yes
Web Last Visit DateYearThe year when the customer last visited the website.Yes

Cohorts

Sub-GroupDimension nameDescriptionPre-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.

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

Machine Learning

Sub-GroupDimension nameDescriptionPre-calculated field?
Behavior Based ClusterBehavior Based Cluster - 1 Month AgoThe 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 ClusterBehavior Based Cluster - 2 Months AgoThe 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 ClusterBehavior Based Cluster - This MonthThe 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 ClusterBehavior Based Cluster - TodayThe 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 ClusteringMost Likely Cluster ProbabilityThe 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 ClusteringMost Likely Cluster ValueThe 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 ClusteringSecond Most Likely Cluster ProbabilityThe 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 ClusteringSecond Most Likely Cluster ValueThe 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 ClusteringThird Most Likely Cluster ProbabilityThe 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 ClusteringThird Most Likely Cluster ValueThe 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 BuyLikelihood to Buy - 1 Month AgoThe 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 BuyLikelihood to Buy - 2 Months AgoThe 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 BuyLikelihood to Buy - This MonthThe 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 BuyLikelihood to Buy - TodayThe 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 ConvertLikelihood to Convert - 1 Month AgoThe 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 ConvertLikelihood to Convert - 2 Months AgoThe 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 ConvertLikelihood to Convert - This MonthThe 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 ConvertLikelihood to Convert - TodayThe 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 EmailLikelihood to Engage on Email - 1 Month AgoThe 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 EmailLikelihood to Engage on Email- 2 Months AgoThe 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 EmailLikelihood to Engage on Email - This MonthThe 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 EmailLikelihood to Engage on Email - TodayThe 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 PriceLikelihood to Pay Full Price - 1 Month AgoThe 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 PriceLikelihood to Pay Full Price- 2 Months AgoThe 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 PriceLikelihood to Pay Full Price - This MonthThe 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 PriceLikelihood to Pay Full Price - TodayThe 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 ActionNext Best ChannelThe next best channel that the customer is most likely to engage with.Yes
Next Best ActionSecond Best ChannelThe second next best channel that the customer is most likely to engage with.Yes
Predictive Lifetime ValuePredictive Lifetime Value - Decile - TodayThe buckets the predictive lifetime value from a customer into groups.Yes
Predictive Lifetime ValuePredictive Lifetime Value - Revenue Group - TodayThe buckets the predictive lifetime revenue from a customer into groups.Yes
Predictive SendsOptimal Email Send Time - OverallThe optimum time when emails can be sent to a customer.Yes
Predictive SendsOptimal Email Send Time - WeekdayThe optimum time during weekdays when emails can be sent to a customer.Yes
Predictive SendsOptimal Email Send Time - WeekendThe optimum time during the weekends when emails can be sent to a customer.Yes
Product based ClusterProduct based Cluster - 1 Month AgoThe 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 ClusterProduct based Cluster - 2 Months AgoThe 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 ClusterProduct based Cluster - This MonthThe 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 ClusterProduct based Cluster - TodayThe 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

Market Basket Analysis

Sub-GroupDimension nameDescriptionPre-calculated field?
First Item DetailsFirst Category Name Level 1The category name of the level 1 first item.No
First Item DetailsFirst Category Name Level 2The category name of the level 2 first item.No
First Item DetailsFirst Category Name Level 3The category name of the level 3 first item.No
First Item DetailsFirst Category Name Level 4The category name of the level 4 first item.No
First Item DetailsFirst Category Name Level 5The category name of the level 5 first item.No
First Item DetailsFirst Item BrandThe brand of the first item.No
First Item DetailsFirst Item ColorThe color of the first item.No
First Item DetailsFirst Item SizeThe size of the first item.No
First Item DetailsFirst Product IDThe ID of the first product.No
First Item DetailsFirst Product NameThe name of the first product.No
First Item DetailsSelected Dimension First ItemThe 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 DetailsSecond Category Name Level 1The category name of the level 1 second item.No
Second Item DetailsSecond Category Name Level 2The category name of the level 2 second item.No
Second Item DetailsSecond Category Name Level 3The category name of the level 3 second item.No
Second Item DetailsSecond Category Name Level 4The category name of the level 4 second item.No
Second Item DetailsSecond Category Name Level 5The category name of the level 5 second item.No
Second Item DetailsSecond Item BrandThe brand of the second item.No
Second Item DetailsSecond Item ColorThe color of the second item.No
Second Item DetailsSecond Item SizeThe size of the second item.No
Second Item DetailsSecond Product IDThe ID of the second product.No
Second Item DetailsSecond Product NameThe name of the second product.No
Second Item DetailsSelected Dimension Second ItemThe second item of the selected dimension. The value of this field is determined by the value set in the Analysis By Dimension filter.No

Product

Dimension nameDescriptionPre-calculated field?
Product BrandThe brand name for productNo
Product IDA Unique identifier for productNo
Product Item StatusAvailability 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 NameName for productNo

Product Category

Dimension nameDescriptionPre-calculated field?
Product Category - Level 1Customers purchased from 1 distinct product category.No
Product Category - Level 2Customers purchased from 2 distinct product categories.No
Product Category - Level 3Customers purchased from 3-5 distinct product categories.No
Product Category - Level 4Customers purchased from 6-10 distinct product categories.No
Product Category - Level 5Customers purchased from 10+ distinct product categories.No

Sales Organization

Sub-GroupDimension nameDescriptionPre-calculated field?
GeographySales Org CityThe city for sales organization.No
GeographySales Org CountryThe country for sales organization.No
GeographySales Org StateThe state for sales organization.No
GeographySales Org Zip CodeThe Zip Code for sales organization.No
-Sales Channel

The channel for sales organization. The following are the values:

  • Digital: Online stores
  • Physical:Offline stores
  • Warehouse: Warehousing locations, if any
  • Other: The channels that do not fall into earlier categories such as call centers.
No
-Sales Org IDA unique identifier for sales organizationNo
-Sales Org NameThe name for sales organizationNo
-Sales Org TypeThe 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

Transaction

Sub-GroupDimension nameDescriptionPre-calculated field?
Customer Transaction SequenceCustomer Transaction SequenceA 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 SequenceCustomer Transaction Sequence - New vs RepeatA 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 SequenceCustomer Transaction Sequence GroupThe Bucketed version of [Customer Transaction Sequence] for transactionYes
Days since Customer First TransactionDays since Customer First TransactionThe 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 TransactionDays since Customer First Transaction GroupThe bucketed version of [Days since Customer First Transaction] for transaction.Yes
Last Marketing Touch - OnlineLast Marketing Touch - Online 1The 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 - OnlineLast Marketing Touch - Online 2The 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 - OnlineLast Marketing Touch - Online 3The 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 - OnlineLast Marketing Touch - Online 4The 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 - OnlineLast Marketing Touch - Online 5The 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 DateDateThe date of the transaction made by the customer.No
Transaction DateDay of MonthThe day of the month of the transaction made by the customer.No
Transaction DateDay of WeekThe day of the week of the transaction made by the customer.No
Transaction DateMonthThe month when the transaction was made by the customer.No
Transaction DateMonth NameThe name of the month when the transaction was made by the customer.No
Transaction DateQuarterThe quarter when the transaction was made by the customer.No
Transaction DateQuarter of YearThe quarter of the year when the transaction was made by the customer.No
Transaction DateWeek of YearThe week of the year when the transaction was made by the customer.No
Transaction DateYearThe 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 DateTransaction Fiscal Month NumThe fiscal month number of the customer’s transaction date.No
Transaction Fiscal DateTransaction Fiscal Quarter of YearThe fiscal quarter of the year of the customer’s transaction date.No
Transaction Fiscal DateTransaction Fiscal Week of YearThe fiscal week of the year of the customer’s transaction date.No
Transaction Fiscal DateTransaction Fiscal YearThe fiscal calendar year of the customer’s transaction date.No
Transaction Line DateDateThe date of the transaction made by the customer at the line level.No
Transaction Line DateDay of MonthThe day of the month of the transaction made by the customer at the line level.No
Transaction Line DateDay of WeekThe day of the week of the transaction made by the customer at the line level.No
Transaction Line DateMonthThe month when the transaction was made by the customer at the line level.No
Transaction Line DateMonth NameThe name of the month when the transaction was made by the customer at the line level.No
Transaction Line DateQuarterThe quarter when the transaction was made by the customer at the line level.No
Transaction Line DateQuarter of YearThe quarter of the year when the transaction was made by the customer at the line level.No
Transaction Line DateWeek of YearThe week of the year when the transaction was made by the customer at the line level.No
Transaction Line DateYearThe 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 DateTransaction Line Fiscal Month NumThe fiscal month number of the customer’s transaction line date.No
Transaction Line Fiscal DateTransaction Line Fiscal Quarter of YearThe fiscal quarter of the year of the customer’s transaction line date.No
Transaction Line Fiscal DateTransaction Line Fiscal Week of YearThe fiscal week of the year of the customer’s transaction line date.No
Transaction Line Fiscal DateTransaction Line Fiscal YearThe fiscal calendar year of the customer’s transaction line date.No
-Transaction Line SubTypeThe subtype of transaction line, possible values are ‘Demand’, ‘Canceled’, ‘Shipped’, and ‘Returned’.No
-Transaction Line TypeThe 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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