Campaign Level Names

Level 1 Name

The name of the level 1 campaign.

No

Campaign Level Names

Level 3 Name

The name of the level 3 campaign.

No

Campaign Level Names

Level 5 Name

The name of the level 5 campaign.

No

Campaign Start Date

Date

The date when the campaign started.

No

Campaign Start Date

Day of Week

The day of the week when the campaign started.

No

Campaign Start Date

Month

The month when the campaign started.

No

Campaign Start Date

Quarter

The quarter when the campaign started.

No

Campaign Start Date

Time of Day

The time of the day when the campaign started.

No

Campaign Start Date

Year

The year when the campaign started.

No

Address

Customer Country

The country from the customer’s primary address.

No

Address

Customer State

The state from the customer’s primary address.

No

Age

Age

The age of the customer.

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

Average Annual Transactions

The annual transaction frequency for customer calculated using [Transaction Count] * 365 / [Days since First Transaction].

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

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 - 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 - 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 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:

• 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 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 - Lifetime

The total number of transactions made in a customer’s 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

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 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

Email Last Click Date

Date

The date 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 Name

The name of the month when the customer last clicked one of the email 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

Year

The year when the customer last clicked 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

Month

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

Week of Year

The week of 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 Week

The day of the week 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 of Year

The quarter 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

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

Month

The month when the first transaction was made by a 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

Week of Year

The week of 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 Week

The day of the week of the first transaction made by a 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 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

Year

The year when the first transaction was made by a customer in the physical format.

Yes

First Transaction Date

Day of Month

The day of the month 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

Quarter

The quarter 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 - 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 Quarter of Year

The fiscal quarter 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 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 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 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 3

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

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

Month

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

Week of Year

The week of 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 Week

The day of the week of the last transaction 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 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

Year

The year when the last transaction was made by the customer in the physical format.

Yes

Last Transaction Date

Day of Month

The day of the month 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

Quarter

The quarter 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 - 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 Quarter of Year

The fiscal quarter 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 2

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

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

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 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

Email Domain

The domain of the customer’s email address.

No

-

Primary Brand

The product brands that customers made most transactions during their lifetime.

Yes

Sales Organizations

Closest Store

The closest store for customers.

Yes

Sales Organizations

First 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 Organizations

Primary Physical Store

The physical Store that customer made most transactions in during their lifetime

Yes

Sales Organizations

Sales Channel Count

Number of sales channels customers have purchased from in their lifetime.

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

Month

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

Week of Year

The week of 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 Week

The day of the week 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 of Year

The quarter 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

Day of Month

The day of the month 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

Quarter

The quarter 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

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 - Today

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

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 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 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 - 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 - 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 - 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 - 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- 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 - 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- 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 - 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

Second Best Channel

The second next best channel that the customer is most likely to engage with.

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 - Weekday

The optimum time during weekdays 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 - 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

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 4

The category name of the level 4 first item.

No

First Item Details

First Item Brand

The brand of the first item.

No

First Item Details

First Item Size

The size of the first item.

No

First Item Details

First Product Name

The name of the first product.

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 3

The category name of the level 3 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 Color

The color of the second item.

No

Second Item Details

Second Product ID

The ID 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

Product ID

A Unique identifier for product

No

Product Name

Name for product

No

Product Category - Level 2

Customers purchased from 2 distinct product categories.

No

Product Category - Level 4

Customers purchased from 6-10 distinct product categories.

No

Geography

Sales Org Country

The country for sales organization.

No

Geography

Sales Org Zip Code

The Zip Code for sales organization.

No

-

Sales Org ID

A unique identifier 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

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

Days since Customer First Transaction

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

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 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 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

Day of Month

The day of the month of the transaction made by the customer.

No

Transaction Date

Month

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

Week of Year

The week of 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 Quarter of Year

The fiscal quarter 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

Day of Month

The day of the month 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

Quarter

The quarter 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 - 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 Quarter of Year

The fiscal quarter 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 Type

The type of transaction line, default value is ‘Purchase’. Contact your CDP CVM for descriptions if you have custom transaction linetypes.

No