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Late Deliveries and Ratings: Propensity Score Matching Approach
- Late delivery impacts customer satisfaction, an important metric for e-commerce platforms like Olist which connects small businesses across Brazil to channels for product delivery. Late deliveries are inevitable at times, fortunately, with causal inference and Propensity Score Matching (PSM), businesses can conduct observational studies to see the impact of late deliveries on customer ratings.
- PSM is used to reduce estimation bias when conducting evaluations with observational data. Propensity scores are the likelihood of an observation being exposed to treatment; late delivery status in this case.
- The likelihood of an order being late is based on a logistic regression analysis of certain order characteristics, giving it a propensity score. Late and on-time deliveries are matched by their similarity in propensity scores to create balanced groups.
- The objective of matching late deliveries to on-time deliveries is to measure the causal effect of late delivery on customer rating. Based on the resulting -1.97 average treatment effect of late delivery on the matched sample, we can conclude that late deliveries decrease customer satisfaction significantly.
- This analysis shows that customer satisfaction is reduced significantly due to late delivery. Platform developers should critically investigate better solutions and logistics models to ensure prompt order delivery in order to maximize customer satisfaction.
- A waiting time minimization model could be developed, which minimizes the wait time for each order, taking into consideration parameter like order size, time window in which the order was placed, and distance to customer’s delivery address.
- Another option would be to invest in real-time route optimization software, which would optimize delivery routes for each logistics partner with many supporting features. This would increase the number of deliveries a single logistics partner could handle in a day while ensuring timely delivery of orders.
- In conclusion, businesses must look beyond product quality and focus on ensuring timely delivery of customer orders. Delays in delivery are detrimental to customer satisfaction. The use of causal inference and PSM makes observational studies possible for businesses to identify factors that hinder customer satisfaction and to develop strategies that reduce them, including logistics improvements.
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