Food Features. These features include spend on food. They are returned in the nigeria/features/food endpoint.Definitions of these features generated by Pngme are:
| Feature | Definition | Use Case | Value Proposition | Response value |
|---|---|---|---|---|
| count_food_events _{t0_days}_{t1_days} | The number of SMS received indicating that the user engaged in spending through food events, where food events are broken down into general food spending, bar and restaurant, catering, food processor and distributor, food store, wine and spirit 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 customer service and build stronger relationships with customers, thereby increasing customer retention by understanding customers’ spending habits and preferences on food events. • Use data to offer personalized services such as budgeting and financial planning tools that track food events and compare pricing and packages from different catering or food precessing services, helping them make cost-conscious decisions and manage their finances better. • Improve data quality and reliability by using SMS data as a source of truth for verifying food events of customers. | • This feature may be indicative of individuals who frequently dine out, possibly suggesting a personal or professional interest in the food and drink industry. • Understanding a user’s activity related to food events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} |
| sum_of_food_debits _{t0_days}_{t1_days} | Total of food debit transactions across depository accounts. where food events are broken down into general food spending, bar and restaurant, catering, food processor and distributor, food store, wine and spirit events. The transactions 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 service and build stronger relationships with customers, thereby increasing customer retention by understanding customers’ spending habits and preferences on food events. • Use data to offer personalized services such as budgeting and financial planning tools that track food events and compare pricing and packages from different catering or food precessing services, helping them make cost-conscious decisions and manage their finances better. • Improve data quality and reliability by using SMS data as a source of truth for verifying food events of customers. | • This feature may be indicative of individuals who frequently dine out, possibly suggesting a personal or professional interest in the food and drink industry. • Understanding a user’s activity related to food events can help tailor marketing strategies and develop products that cater to this specific customer segment. | {int, null} |