Predicting customer lifetime value is a way of identifying those customers who potentially generate the majority of your sales revenue.
With this model, you can tailor advertisements to individuals or groups of similar users and target your most valuable customer segments.
Quick start on GCP with a ready-to-use model
Automatized model retraining and deployment
Own the model+data
Automatic deployment, training and operation - only lightweight configuration needed
A minority of customers will most likely generate the majority of profit. Identifying and focusing on this particular group is essential for accurately targeting campaigns.
By predicting the lifetime value you can easily target customers in region of interest, track their activity and identify their impact. You can also use this information to take action and plan how to move customers from one segment to another.
By measuring CLTV in correlation with other metrics you can retrieve information on how long it takes to recoup the investment in a campaign. In other words, you can get more accurate predictions of optimal Customer Acquisition Cost (CAC).
The CLTV blueprint provides automated predictive modeling pipelines. This means there is no need to build your own ML pipelines – they’ve already been built for you.
By using SQL you can tailor the model to your needs, while still retaining the highly predictive model performance of AutoML.