Predicted_CLV_Attributes Table¶
The Predicted_CLV_Attributes table contains information, for each individual Amperity ID, about predicted future spend and the probability of churn.
Note
The size of the Predicted_CLV_Attributes table in your tenant is based on the number of Amperity IDs.
Add table¶
Add the Predicted_CLV_Attributes table to the customer 360 database.
as a SQL table¶
A SQL table adds a table to the customer 360 database using Spark SQL and a SELECT
statement to define the table’s schema.
The days_since_last_order
and historical_order_frequency_lifetime
columns in the Predicted_CLV_Attributes table are not recommended for use with segmentation or for downstream workflows. Use SQL to build a predicted attributes table for use in the customer 360 database that omits these columns.
To add the Predicted_CLV_Attributes table as a SQL table
From the Customer 360 tab, under All Databases, select the menu for the customer 360 database, and then click Edit.
From the Database Editor, click Add Table.
Set Build Mode to “SQL”, and then use a
SELECT
statement similar to the following to define the schema:SELECT amperity_id AS `amperity_id` ,predicted_average_order_revenue_next_365d AS `average_revenue_365` ,predicted_clv_next_365d AS `clv_365` ,predicted_customer_lifecycle_status AS `purchase_likelihood` ,predicted_customer_lifetime_value_tier AS `value_tier` ,predicted_order_frequency_next_365d AS `predicted_orders_365` ,predicted_probability_of_transaction_next_365d AS `purchase_probability` FROM Predicted_CLV_Attributes
Hide the table from the Visual Segment Editor by verifying that Show in VSE? is unselected.
Click Activate to update the customer 360 database with your changes.
as a passthrough table¶
A passthrough table adds a table to the customer 360 database using an existing table without making any changes to its schema.
To add the Predicted_CLV_Attributes table as a passthrough table
From the Customer 360 tab, under All Databases, select the menu for a database, and then click Edit.
Click Add Table.
Set Build Mode to “passthrough”, and then select the Predicted_CLV_Attributes table from the drop-down menu.
Hide the table from the Visual Segment Editor by verifying that Show in VSE? is unselected.
Click Activate to update the customer 360 database with your changes.
Column reference¶
The Predicted_CLV_Attributes table contains the following columns:
Column Name |
Data type |
Description |
---|---|---|
amperity_id |
String |
The unique identifier that is assigned to clusters of customer records that all represent the same individual. The Amperity ID does not replace primary and foreign keys, but exists alongside them within unified profiles. Note The Amperity ID is a universally unique identifier (UUID) that is represented by 36 characters spread across five groups separated by hyphens: 8-4-4-4-12. For example: 123e4567-e89b-12d3-a456-426614174000
|
predicted_average_order_revenue_next_365d |
Decimal |
The predicted average order revenue over the next 365 days. |
predicted_clv_next_365d |
Decimal |
The total predicted customer spend over the next 365 days. |
predicted_customer_lifecycle_status |
String |
A probabilistic grouping of a customer’s likelihood to purchase again. For repeat customers, groupings include the following tiers:
For one-time buyers, groupings include the following tiers:
|
predicted_customer_lifetime_value_tier |
String |
A percentile grouping of customers by predicted CLV. Groupings include:
Note This attribute returns only the customers who belong to the selected value tier. For example, to return all of your top 10% customers, you must choose platinum, gold, and silver. Silver by itself will return 5% of your customers, specifically those are in your 5-10%. |
predicted_order_frequency_next_365d |
Decimal |
The predicted number of orders over the next 365 days. |
predicted_probability_of_transaction_next_365d |
Decimal |
The probability a customer will purchase again in the next 365 days. |