Predicted transactions

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

Each prediction is represented by a percentage, where a lower percentage represents a lower likelihood that a customer will return to make another purchase during the next 365 days: a “0.10” score is a 10% likelihood of return, a “0.26: score is a 26% likelihood of return, and a “0.63” score is a 63% likelihood of return.

About predicted CLV attributes

AmpIQ 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. For example, in the Segment Editor, select the Predicted Probability Of Transactions Next 365 D attribute, select the is condition, and then enter “50” into the field to return an audience of customers with a 50% probability of returning 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. For example, in the Segment Editor, select the Predicted Order Frequency Next 365 D attribute, select the is between condition, and then enter “1” in the minimum field and “20” in the maximum field to return an audience of customers who are predicted to make a purchase up to 20 times in 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. For example, in the Segment Editor, select the Predicted Average Order Revenue Next 365 D attribute, select the is greater than or equal to condition, and then enter “100” in the field to return an audience who are predicted to spend 100 dollars or more in 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 order frequency to identify which of those customers are more likely to order multiple times.

3. Add predicted average order value to identify customers who are most likely to spend, on average, at least $100 per order.

Use in segments

To find predicted probability of transactions, start with the Predicted Probability of Transaction Next 365 attribute in the Predicted CLV Attributes table, and then select a condition. After the attribute appears in your segment, specify the probability of transaction that you want to use in your segment.

After the attribute appears in your segment, specify a frequency for predicted probability of transaction that aligns to the condition you selected. For example, to find customers whose likelihood to purchase is greater than or equal to 35%:

Note

Predicted transactions are available to users of AmpIQ 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 probability of transaction, such as “1.2”, “40.6”, or “50.0”. Tip Use the following conditions to return a range of probabilities instead of a specific probability: 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 probabilities that are between the specified predicted probability.
is greater than	More useful Returns probabilities that are greater than the specified predicted probability.
is greater than or equal to	More useful Returns probabilities that are greater than or equal to the specified probability.
is in list	Less useful Avoid using the is in list condition; individual probabilities are not typically made available in a list.
is less than	More useful Returns probabilities that are less than the specified predicted probability.
is less than or equal to	More useful Returns probabilities that are less than or equal to the specified predicted probability.
is not	Less useful Avoid using the is not condition. For example, if you specified “50.0” then any probability that is less than or equal to “49.99” and any probability that is greater than or equal to “50.01” would be returned.
is not between	Less useful Discovers outlier probabilities. For example, if most of your probabilities are between “30.0” and “40.0”, use “30.0” and “40.0” to return probabilities that were less than and greater than those values.
is not in list	Less useful Avoid using the is not in list condition when individual probabilities are not made available as a list.
is not NULL	Returns customer records that have a value, such as “.50”, “59.99”, and “100.0”, 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.