The Visualizations
How can our visualizations provide meaningful information about customer trends to the Uber Company?
Distribution of Rides Over Time
September 1st 2015 - August 31st 2015
This visualization aims to serve as a comprehensive interpretation of the usage of Uber services in the Washington D.C. area over the span of a 12-month period. Scanning from left to right, it is evident that the line graph surges and dips during certain nationally observed holidays. The graph seems to have a relatively stable progression until right before the end of October 2014 when it reaches 100k trips per day, possibly due to the increased demand for Uber rides during Halloween, when people might travel to surrounding neighborhoods to partake in activities such as trick-or-treating. In addition, there is an uptick in rides on November 1st, the day before the DC marathon and possibly might represent runners or the public taking Ubers to attend the event. Conversely, the end of November shows a dip in Uber rides, as the majority of those who celebrate the holiday of Thanksgiving might choose to spend the day with family and friends rather than commute for work. Similarly, the end of December appears to reach an all-time low of about 30k trips per day, potentially as a result of people staying at home or a relatives’ place during the holiday season and around New Years Eve.
Experienced Leadership
How Time Affects Demand
Average speed
by hour
Fortunately, the Washington D.C. Uber Dataset provided information on the distance and duration of each trip allowing for the calculation of average speed in order to compare the demand of trips during rush hours and the respective traffic flow during those particular time intervals. As expected, the times from 7am-9am and 4pm-6pm on Weekdays seem to have the lowest average speed or the worst traffic flow compared to other times throughout the day, most likely due to the rush of vehicles commuting to and from places of work.
Average COUNT
by hour
The above graph demonstrates a relationship between the average number of rides depending on the hour of the day, and follows a normal pattern of peaking at the busiest traffic periods from 8am to 10am and 6pm to 8pm and usually curve down towards the early hours of the morning as well as the middle of the day from 11am to 4pm.
MEDIAN distance
by HOUR
The above graphs compare the distribution of the median distance of trips through the day in an effort to better represent any distinct patterns on weekdays or weekends. As shown visually, there is a clear peak in median distance of rides around 5am -7am during both weekdays and weekends, raising the question of could it be due to picking up customers who would otherwise use public transportation to travel to the other boroughs? In addition, the time interval is so early in the morning and although the subway runs 24/7, bus services don’t operate throughout all hours in the day, so the dip in rides represents those who need to travel outside the downtown area for various reasons early in the day.
Average count
by hour
Taking it one step further, we can also analyze the average speed of Uber rides throughout the day to extract more information about the distribution of rides taken within suburbs and cities separately. According to the above graph, it is obvious that a much greater amount of Uber rides have an average speed between 5 miles per hour to 15 miles per hour, which is quite low for traveling when traveling within suburbs, so it seems that most customers use Uber when traveling to a location that requires going on a highway which is a lot more prone to congested traffic during rush hour that would significantly lower the average speed and can therefore explain the huge peak around this specific speed interval.
Total Trips between Sept. 1st - Aug. 31st 2015
Estimated Revenue between Sept. 1st - Aug. 31st
Although Figure 1 reflects a drop in rides for the months of May, June, July, and August of 2015, the estimated monthly base revenue from September 2014 to August 2015, shown in Figure 2, follows a positive linear trend, and doesn’t exhibit a sharp decrease beginning in the month of May. For these reasons, it’s safe to assume that the discrepancy in the 2 visualizations reflects an issue within the dataset itself, as the overall revenue and usage over the same time frame should, but do not follow the same trends. In the possibility that the Uber company experiences a similar drop in usage around the same time every year, datasets published in previous years were also analyzed and can be referenced below. However, surrounding years do not demonstrate the same seasonal trend, and the graph to the bottom right shows a steady, linear growth of daily rides through a 4 year period. Due to the lack of other data sources that provide information about the status of Uber rides in Washington D.C. specifically, it is difficult to define the cause of the dip in the visualization to a particular occurrence, but we can rather suggest the possibility of an error in the method of data collection.
Uber Rides in 2014
Uber Rides from Q4 2014 to Q4 2018
Analyzing Discrepancies
How Location Affects Demand
Across 11 Taxi Zones in Washington D.C.
REFERENCE MAP
VISUALIZATION
WHERE ARE THE BUSIEST AREAS?
2a
The zone 2A is home to Washington D.C.’s most populated neighborhood: Georgetown- a magnet for highly educated professionals with great salaries as well as a large student population with about two-thirds of the Georgetown University undergraduates living in dorms on the 100-acre campus on the west side of the neighborhood. The population is primarily white, younger, and mostly single. Usually, ride-hailing use is strongly concentrated among urban residents, with 39% of urban college graduates and 35% of urbanites who earn more than $75,000 per year using ride-hailing services. With the population mostly consisting of 18-to- 29-year-olds, the majority of 2A residents seem likely to not own a personal vehicle and rely only on ride-hailing users, as frequent ride-hailing users are less likely than other American to own a car. In addition, an extremely busy area located north of M Street and west of Wisconsin Ave is near Georgetown University, resulting in a high demand from college students heading home from the bars during the late night hours.To not much surprise, taxi zone 2A seems to hold the highest demand for services such as Uber and this trend is reflected in the visualization above.
1
Taxi Zone 1 encompasses Washington D.C.’s central business district- home to federal instructions such as the White House, U.S. Capitol Building, Federal Bureau of Investigation Office, and The Ronald Reagan Building and International Trade Center, as well as popular public attractions such as the 3 Smithsonian National Museums, National Museum of Women in the Arts, and multiple chains of dining and shopping establishments. Although the visitors in the downtown area have access to the Metro and Taxi Cabs, ride-hailing services seem to be comparatively the cheapest option for traveling short distances, making Uber a popular choice among tourists hopping from one attraction to another within the region. Ever since the new program Uber For Business opened in 2020, it has provided exclusive services for federal employees commuting to and from places of work, and could further explain the demand of Uber rides in the downtown district of D.C.
4C
Located in Taxi Zone 4C, the suburban city of Silver Spring is home to of plenty neighborhoods and employment centers, and is situated only 6.2 miles from the heart of Washington D.C., making the city feel like an extension of the nation’s capital. Many Silver Spring residents use Uber’s ride-hailing services for easy commuting into and out of offices located in Washington D.C. Aside from places of work, downtown Silver Spring hosts several entertainment, musical, and ethic festivals, as well as a multitude of options for dining and shopping for visitors. Unlike zones 2A and 1, the residents of zone 4C have access to many public transportation services such as the MARC Train, Metrorail Red Line, and the Silver Spring Rail Station- the busiest bus terminal in the entire Washington D.C. Therefore, instead of targeting customers during working hours, Uber drivers could expect to see a higher demand for rides around centers of nightlife entertainment in a cultural hub.
How Location Affects Traffic Flow
Across 11 Taxi Zones in Washington D.C.
Created using Tableau, the Sankey diagram to the left displays the flow of rides into and out of the 11 taxi zones of Washington D.C, in an effort to visually map the most popular Uber routes within the city. Sankey Maps are interpreted left to right, and are a type of flow diagram in which the width of the arrows is proportional to the flow rate. According to the magnitude of pickups and drop-offs for each taxi zone, we can make conclusions about what percentage of rides originating from a particular zone travel to another zone, or study the distribution of all 11 taxi zones within each destination zone. For example, it is evident that a large percentage of the total rides consist of people traveling within zone 2A as represented by the thickest arrow, and the second busiest route turns out to be the customers traveling from zone 2A to zone 1. As mentioned in the previous section, the zones 1 and 2A comprise of Washington D.C.’s central business district and most populous suburban area, respectively, which provides a reasonable explanation for the heavy traffic flow between these two regions.
