Easter Holiday: Analysis of Ride Activity and Earnings in Regional Ride-Hailing Apps
- mkt0814
- Apr 25
- 4 min read
Follow the analysis of ride activity and revenue from regional ride-hailing apps during the 2025 Easter holiday.
Introduction
The Easter period brings significant changes to the dynamics of cities. With an increase in travel, especially to tourist destinations and family gatherings, there is a direct impact on the demand and revenue of urban mobility services, reflecting new transportation needs typical of this time of year.
A total of 6,613,649 rides requested through regional urban mobility apps powered by the Machine platform were analyzed, covering the period from April 1 to April 21, 2025.
By examining key indicators such as the total number of rides requested, rides completed, and the revenue generated, this study aims to explore how Easter impacts the demand for these services and the resulting earnings, drawing comparisons with figures observed in the preceding weeks.
Glossary
Ride Requested: A ride request made by a passenger, which a driver may accept or decline.
Ride Completed: A ride request that was successfully completed, meaning the passenger reached their destination, concluding the operation.
Revenue Generated: Refers to the total amount of money earned from completed rides.
Cancellation Rate: The proportion of ride requests that were not completed.
Results
Rides Requested
The chart below compares the number of rides requested on each day of the Easter holiday with the average number of rides requested on the other days of April.
The day with the highest number of ride requests during the holiday was Saturday, with 285,592 rides requested. Among the other days, Friday recorded the highest average number of requests, with 386,112.
The day with the lowest number of ride requests during the holiday was Monday, with 178,533 rides requested. Among the other days, Sunday had the lowest average, with 251,704.5 requests.
Throughout Easter, demand was lower on all days compared to regular days, with decreases of 44.77% on Friday, 22% on Saturday, 8.86% on Sunday, and 45% on Monday.
Rides Completed
The chart below compares the number of rides completed on each day of the Easter holiday with the average number of rides completed on the other days of April.
The day with the highest number of completed rides during the holiday was Saturday, with 258,857 rides completed. Among the other days, Friday recorded the highest average number of completions, with 352,276.
The day with the lowest number of completed rides during the holiday was Monday, with 160,778 rides completed. Among the other days, Sunday had the lowest average, with 223,035.5 completions.
Throughout Easter, the number of rides completed was lower on all days compared to regular days, with decreases of 46.07% on Friday, 21.85% on Saturday, 9.20% on Sunday, and 45.57% on Monday.
It is important to highlight that cancellation rates experienced changes considered statistically insignificant.
Revenue Generated from Rides
The chart below compares the revenue generated on each day of the Easter holiday with the average revenue generated on the other days of April.
The day with the highest revenue generated during the holiday was Sunday, with R$8,209,839. Among the other days, Friday recorded the highest average revenue, with R$5,735,248.
The day with the lowest revenue generated during the holiday was Monday, with R$3,602,575. Among the other days, Sunday had the lowest average revenue, with R$3,862,805.
During Easter, demand was mostly lower compared to regular days, with decreases of 33.83% on Friday, 28.09% on Saturday, and 16.53% on Monday. However, Sunday saw an increase of 112.54%.
Rides Completed by Region
The map below shows the variation in the number of rides completed across Brazilian states during the Easter period.
The states with the largest variations were Minas Gerais, with an average daily decrease of 18,695 rides; Rio Grande do Sul, with a decrease of 17,294 rides; and São Paulo, with a decrease of 11,467 rides.
No Brazilian state recorded an increase in the number of rides completed during the Easter period.
From a regional perspective, all regions of the country experienced a decline in the number of rides during the analyzed period. The Southeast recorded the highest average daily decrease, with 31,451 fewer rides, followed by the South (-26,234), the Central-West (-18,559), the North (-18,451), and the Northeast (-8,334).
Rides Completed by Region
The map below shows the variation in revenue generated across Brazilian states during the Easter period.
The states with the greatest variations were Tocantins, with an average daily increase of R$680,393; Amazonas, with an increase of R$368,614; and Alagoas, with an increase of R$168,973.
Most Brazilian states experienced a decrease in revenue generated during the Easter period.
From a regional perspective, the Central-West showed the largest average daily decrease, with R$268,568 less in revenue, followed by the Southeast (-R$225,353) and the South (-R$207,707). The North stood out with the highest increase, generating R$818,256 more, followed by the Northeast with R$154,033.
Conclusion
This study analyzed the impact of Easter on urban mobility services. The research provided both a general overview and a state-by-state analysis, aiming to highlight regional variations in the data.
Overall, a 28.5% drop in the number of rides requested was observed during the Easter period compared to previous weeks. Despite the predominantly negative trend, some states performed above average—most notably Tocantins, Amazonas, and Alagoas, which recorded increases in revenue. On the other hand, the most affected states in terms of revenue loss were Rio Grande do Sul, Minas Gerais, and Mato Grosso.
At the regional level, the Southeast was the most impacted, showing the largest reduction in the number of completed rides and the second-largest decline in total revenue. In contrast, the North region stood out positively, with the highest revenue growth among all regions analyzed.
In summary, Easter’s impact on urban mobility varied significantly across states and regions. While some areas reported positive outcomes, the overall effect was predominantly negative. These findings offer valuable insights for more effective planning of future events, enabling mobility companies to better prepare by allocating resources wisely and adjusting operations to optimize performance and user experience.
