Utilities Features. These include features on utility bills mostly electricity etc. They are returned in the srilanka/features/utilities endpoint.Definitions of these features generated by Pngme are:
| Feature | Feature Definition | Use Case | Value Proposition | Return Value |
|---|---|---|---|---|
| count_utilities_events _{t0_days}_{t1_days} | The number of SMS received indicating that the user engaged in spending through utilities, where utilities are broken down into general utilities spending, housing events. 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 enabling customers to track their spend and usage patterns across different utility events in order to manage consumption. • Improve customer satisfaction by recommending platforms that provide ease of payment for utility bills • Improve data quality and reliability by using SMS data as a source of truth for verifying utility events of customers. | This feature may be indicative of individuals who earn regularly and possess sufficient resources to cover short-term bills monthly or weekly. Such individuals are likely to be relatively stable financially, as evidenced by their consistent bill payments. • Understanding a user’s activity related to utilities events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} |
| count_housing_events _{t0_days}_{t1_days} | The number of SMS received indicating that the user engaged in spending through housing/rent. 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 enabling customers to track their spend on rent. • Improve customer satisfaction by recommending platforms that provide ease of payment for electricity bills • Improve data quality and reliability by using SMS data as a source of truth for verifying utility events of customers. | This feature may be indicative of individuals who earn regularly and possess sufficient resources to cover short-term bills monthly or weekly. Such individuals are likely to be relatively stable financially, as evidenced by their consistent bill payments. • Understanding a user’s activity related to utilities events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} |
| sum_of_utilities_debits _{t0_days}_{t1_days} | The sum of debits indicating that the user engaged in spending through utilities, where utilities are broken down into general utilities spending, housing bill spends. 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. | • Enhance customer engagement and retention by enabling customers to track their spend and usage patterns across different utility events inorder to manage consumption. • Improve customer satisfaction by recommending platform that provide ease of payment for utility bills • Improve data quality and reliability by using SMS data as a source of truth for verifying utility events of customers. | This feature may be indicative of individuals who earn regularly and possess sufficient resources to cover short-term bills monthly or weekly. Such individuals are likely to be relatively stable financially, as evidenced by their consistent bill payments. • Understanding a user’s activity related to utilities events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {float, null} |
| sum_of_housing_debits _{t0_days}_{t1_days} | The sum of debits indicating that the user engaged in spending through housing/rent spends. 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. | • Enhance customer engagement and retention by enabling customers to track their spend on rent/housing. • Improve customer satisfaction by recommending platforms that provide ease of payment for electricity bills • Improve data quality and reliability by using SMS data as a source of truth for verifying utility events of customers. | This feature may be indicative of individuals who earn regularly and possess sufficient resources to cover short-term bills monthly or weekly. Such individuals are likely to be relatively stable financially, as evidenced by their consistent bill payments. • Understanding a user’s activity related to utilities events can help tailor marketing strategies and develop products that cater to this specific customer | {float, null} |