Transport Features. These features include spend at a gas/petrol station, spend at a hotel, general transportation events etc. They are returned in the srilanka/features/transport endpoint.Definitions of these features generated by Pngme are:
| Feature | Feature Definition | Use Case | Value Proposition | Return Value |
|---|---|---|---|---|
| count_transportation_and_ travel_events_{t0_days}_{t1_days} | The number of SMS received indicating that the user engaged in spending through transportation and travel events, where transportation and travel events are broken down into general transportation and travel spending, hotel, parking 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. | • Increase customer loyalty and retention by offering incentives on transportation and travel events services, such as discounts, or redeemable purchase points on airfare, hotel etc. • Offer personalized services such as airfare events comparison across different airlines & dates or offer lodging options to customers who frequently engage in travel for smoother commute. • Improve data quality and reliability by using SMS data as a source of truth for verifying transportation and travel events of customers | • This feature may be indicative of individuals who travel, commute, or vacation regularly, as well as those owning vehicles, suggesting a certain lifestyle or mobility requirement. • Understanding a user’s activity related to transportation and travel events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} |
| count_hotel_events_{t0_days}_{t1_days} | The number of SMS received indicating that the user engaged in spending through hotel 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. | • Increase customer loyalty and retention by offering incentives on transportation and travel events services, such as discounts, or redeemable purchase points on hotel. • Offer lodging options to customers who frequently engage in travel for smoother commute. • Improve data quality and reliability by using SMS data as a source of truth for verifying transportation and travel events of customers | • This feature may be indicative of individuals who travel or vacation regularly • This feature may also be indicative of an individual’s spending capacity • Understanding a user’s activity related to transportation and travel events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} |
| count_parking_events_{t0_days}_{t1_days} | The number of SMS received indicating that the user engaged in spending through parking 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. | • Improve data quality and reliability by using SMS data as a source of truth for verifying transportation and travel events of customers | • This feature may be indicative of individuals who own vehicles, suggesting a certain mobility requirement. • Understanding a user’s activity related to transportation and travel events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} |
| sum_of_transportation_and_ travel_debits_{t0_days}_{t1_days} | The sum of SMS received indicating that the user engaged in spending through transportation and travel, where transportation and travel spends are broken down into general transportation and travel spending, hotel, parking 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. | • Increase customer loyalty and retention by offering incentives on transportation and travel services, such as discounts, or redeemable purchase points on airfare, hotel etc. • Offer personalized services such as airfare events comparison across different airlines & dates or offer lodging options to customers who frequently engage in travel for smoother commute. • Improve data quality and reliability by using SMS data as a source of truth for verifying transportation and travel spends of customers | • This feature may be indicative of individuals who travel, commute, or vacation regularly, as well as those owning vehicles, suggesting a certain lifestyle or mobility requirement. • Understanding a user’s activity related to transportation and travel events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {float, null} |
| sum_of_hotel _debits_{t0_days}_{t1_days} | The sum of debits indicating that the user engaged in spending through hotel. 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. | • Increase customer loyalty and retention by offering incentives on transportation and travel events services, such as discounts, or redeemable purchase points on hotel. • Offer lodging options to customers who frequently engage in travel for smoother commute. • Improve data quality and reliability by using SMS data as a source of truth for verifying transportation and travel events of customers | • This feature may be indicative of individuals who travel or vacation regularly • This feature may also be indicative of an individual’s spending capacity • Understanding a user’s activity related to transportation and travel events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {float, null} |
| sum_of_parking _debits_{t0_days}_{t1_days} | The sum of debits indicating that the user engaged in spending through parking. 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 data quality and reliability by using SMS data as a source of truth for verifying transportation and travel events of customers | • This feature may be indicative of individuals who own vehicles, suggesting a certain mobility requirement. • Understanding a user’s activity related to transportation and travel events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {float, null} |