Predictive Attributes - Customer LTV

Understanding Lexer's predictive attributes

A customer's lifetime value (LTV) is predicted based on the future profits or salesĀ attributed from a customer. Within a customer profile, the two main attributes measuring LTV are:

1. Predicted Spend
2. Predicted Order Value

We call them, Predictive Attributes.

The attributes are trained to consider these model inputs to predict customer LTV. To understand the predictive attributes, these are the key factors which you can consider and remember easily using the acronym "RFM-IT":

  1. Recency - When was the last time the customer transacted
  2. Frequency - How many times have they transacted
  3. Monetary value - How much have they spent
  4. Inter-transaction time - How many days on average between transactions
  5. Tenure - How long have they been a customer for (I.e. From the first time the customer transacted)
  6. Churn Risk - How likely are they to churn based on their history purchases

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