Predicted CLV

Predicted customer lifetime value represents the total value of all orders a customer is predicted to make if they return to make another purchase during the next 365 days.

Each prediction is represented by an amount, where a higher amount represents an increase in the amount of money a customer will spend (in total) during the next 365 days: a 25.75 score is a likelihood that a customer will spend $25.75, a 140.45 score is a likelihood that a customer will spend $140.45, and a 295.25 score is a likelihood that a customer will spend $295.25.

About predicted CLV attributes

Amperity provides a set of attributes that predict customer lifetime value (CLV) during the next 365 days.

Each of these attributes provides a score that is independent of other predicted CLV attributes:

1. Predicted CLV represents the total value of all orders a customer is predicted to make if they return to make another purchase during the next 365 days.

   Note

   Predicted CLV is the multiplication of three columns: 1) predicted probability of return, 2) predicted order frequency, and 3) predicted average order value.

   Each component of predicted CLV is also available as an individual score:

   1. Predicted probability of transaction represents the likelihood that a customer will return to make another purchase during the next 365 days.

   2. Predicted order frequency represents the number of orders a customer is predicted to make if they return to make another purchase during the next 365 days.

   3. Predicted average order revenue represents the average value of each order a customer is predicted to make if they return to make another purchase during the next 365 days.

2. Predicted value tiers group customers by pCLV: Platinum (top 1%), Gold (top 1%-5%), Silver (top 5%-10%), Bronze (top 10%-25%), Medium (top 25%-50%), and Low (bottom 50%).

Use a combination of predicted CLV attributes to identify high-value audiences for use with campaigns that focus on winning repeat customers, such as churn prevention, winback, and one-time buyer campaigns.

For example:

1. Start with predicted probability of transaction to identify customers with a higher likelihood of return.

2. Add predicted CLV to identify which of these customers would be high-value customers if they were to become a repeat customer, regardless of the number of purchases or average order amount.

Examples

The following topics contain examples of using predicted CLV:

• Lapsing customers

Use in segments

To apply predicted CLV to your segment, start with the Predicted CLV Next 365 in the Predicted CLV Attributes table, and then set its condition to is greater than or equal to.

After the attribute appears in your segment, specify an amount for predicted customer lifetime value that aligns to the condition you selected. For example, to find customers for whom customer lifetime value is predicted to be greater than or equal to $2000:

Note

Predicted CLV is available when predictive modeling is enabled for your tenant.

Available conditions

The following table lists the conditions that are available to this attribute.

Note

This attribute has a Decimal data type. All Decimal data types share the same set of conditions. Recommended conditions for this attribute are identified with “ More useful” and conditions with more limited use cases are identified with “ Less useful”.

Condition	Description
is	Less useful Returns a specific amount of predicted customer lifetime value, such as “117.99”, “129.99”, or “179.99”. Tip Use the following conditions to return a range of predicted customer lifetime values instead of a specific predicted customer lifetime value: is between, is greater than, is greater than or equal to, is less than, and is less than or equal to.
is between	More useful Returns a range of predicted customer lifetime values that are between the specified predicted customer lifetime values.
is greater than	More useful Returns predicted customer lifetime values that are greater than the specified predicted customer lifetime value.
is greater than or equal to	More useful Returns predicted customer lifetime values that are greater than or equal to the specified predicted customer lifetime value.
is in list	Less useful Avoid using the is in list condition; individual predicted customer lifetime values are not typically made available in a list.
is less than	More useful Returns predicted customer lifetime values that are less than the specified predicted customer lifetime value.
is less than or equal to	More useful Returns predicted customer lifetime values that are less than or equal to the specified predicted customer lifetime value.
is not	Less useful Avoid using the is not condition. For example, if you specified “111.99” then any predicted customer lifetime values less than or equal to “111.98” and any predicted customer lifetime values greater than or equal to “112.00” would be returned.
is not between	Less useful Discovers outlier revenue. For example, if most of your predicted customer lifetime values are between “111.99” and “182.99”, use “111.99” and “182.99” to return predicted customer lifetime values that were less than and greater than those values.
is not in list	Less useful Avoid using the is not in list condition when predicted customer lifetime values are not made available as a list.
is not NULL	Returns customer records that have a value, such as “14.99”, “59.99”, and “127.22”, but also “ “ (a space) and “0” (zero). If the record has any value it will be returned.
is NULL	Returns customer records that do not have a value.