Entertainment Features. These features include netflix subscriptions. They are returned in the india/feature/entertainment endpoint.Definitions of these features generated by Pngme are:
| Feature | Definition | Use Case | Value Proposition | Response value | |
|---|---|---|---|---|---|
| count_entertainment_and_subscription_events _{t0_days}_{t1_days} | The number of SMS received indicating that the user engaged in spending through entertainment and certain subscriptions. The counts are summed over a period of t0 to t1 days history prior to the prediction date, where the time windows are 0-30, 31-90, or 0-90 days. | • Improve customer satisfaction and loyalty by offering easier payment to subscriptions rewarding their loyalty and encouraging repeat purchases. • Enhance customer engagement and retention by offering tailored product recommendations | • These features may be indicative of an individual’s spending capacity • Understanding a user’s activity related to subscriptions and entertainment can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} | |
| count_netflix_events _{t0_days}_{t1_days} | The number of SMS received indicating that the user engaged in netflix subscriptions. The counts are summed over a period of t0 to t1 days history prior to the prediction date, where the time windows are 0-30, 31-90, or 0-90 days. | • Improve customer satisfaction and loyalty by offering easier payment to netflix. • Enhance customer engagement and retention by offering tailored product recommendations • Improve data quality and reliability by using SMS data as a source of truth. | • This feature may be indicative of an individual’s spending capacity Indicates disposable income and entertainment preferences • Understanding a user’s activity related to entertainment can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} | |
| count_wines_and_spirits_events _{t0_days}_{t1_days} | The number of SMS received indicating that the user engaged in spending through purchasing wines/spirits. The counts are summed over a period of t0 to t1 days history prior to the prediction date, where the time windows are 0-30, 31-90, or 0-90 days. | • Enhance customer engagement and retention by offering tailored product recommendations • Improve data quality and reliability by using SMS data as a source of truth. | • This feature may be indicative of an individual’s spending capacity Might signal high-income or affluent customers for premium banking products On the other hand might also signal risky profiles where there is excessive spending on wines and spirits | {int, null} | |
| sum_of_entertainment_and_subscription_debits _{t0_days}_{t1_days} | The amount of money a customer has spent on entertainment and certain subscriptions. The debits are summed over a period of t0 to t1 days history prior to the prediction date, where the time windows are 0-30, 31-90, or 0-90 days. | • Improve customer satisfaction and loyalty by offering easier payment to subscriptions rewarding their loyalty and encouraging repeat purchases. • Enhance customer engagement and retention by offering tailored product recommendations • Improve data quality and reliability by using SMS data as a source of truth. | • These features may be indicative of an individual’s spending capacity • Understanding a user’s activity related to subscriptions and entertainment can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} | |
| sum_of_netflix_debits _{t0_days}_{t1_days} | The amount of money a customer has spent on netflix subscriptions. The debits are summed over a period of t0 to t1 days history prior to the prediction date, where the time windows are 0-30, 31-90, or 0-90 days. | • Improve customer satisfaction and loyalty by offering easier payment to netflix. • Enhance customer engagement and retention by offering tailored product recommendations • Improve data quality and reliability by using SMS data as a source of truth for verifying ecommerce activities of customers. | • This feature may be indicative of an individual’s spending capacity • Understanding a user’s activity related to entertainment can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} | |
| sum_of_wines_and_spirits_debits _{t0_days}_{t1_days} | The amount of money a customer has spent on purchasing wines/spirits. The counts are summed over a period of t0 to t1 days history prior to the prediction date, where the time windows are 0-30, 31-90, or 0-90 days. | • Enhance customer engagement and retention by offering tailored product recommendations • Improve data quality and reliability by using SMS data as a source of truth. | • This feature may be indicative of an individual’s spending capacity Might signal high-income or affluent customers for premium banking products On the other hand might also signal risky profiles where there is excessive spending on wines and spirits | {int, null} |