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

1. From the Customer 360 page, under All Databases, select the menu for the customer 360 database, and then click Edit.

2. From the Database Editor, click Add Table.

3. 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
   

4. Hide the table from the Visual Segment Editor by verifying that Show in VSE? is unselected.

5. 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

1. From the Customer 360 page, under All Databases, select the menu for a database, and then click Edit.

2. Click Add Table.

3. Set Build Mode to “Passthrough”, and then select the Predicted CLV Attributes table from the drop-down menu.

4. Hide the table from the Visual Segment Editor by verifying that Show in VSE? is unselected.

5. 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: Active (likelihood to purchase is greater than 60%) Cooling down (likelihood to purchase is between than 50% and 60%) At risk (likelihood to purchase is between than 35% and 50%) Highly at risk (likelihood to purchase is between than 20% and 35%) Lost (likelihood to purchase is less than 20%) For one-time buyers, groupings include the following tiers: Active (purchased within 60 days) Cooling down (purchased 60-120 days ago) At risk (purchased 120-180 days ago) Highly at risk (purchased 180-240 days ago) Lost (purchased 240+ days ago)
Predicted Customer Lifetime Value Tier	String	A percentile grouping of customers by predicted CLV. Groupings include: Platinum: top 1% of customers Gold: top 1%-5% of customers Silver: top 5%-10% of customers Bronze: top 10%-25% of customers Medium: top 25%-50% of customers Low: bottom 50% of customers 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.