Leveraging ITS Data for Transit Market Research: A Practitioner's Guidebook (2008)

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61 City of Madison-Metro Transit (Madison Metro) provides fixed route bus service to a metropolitan area of approximately 250,000 residents. The Madison Metro system comprises 56 routes (including four dedicated to the University of Wis- consin campus and one providing capitol area parking shuttle service). Its fleet of 202 buses carried over 12 million boarding riders in 2006. Transit use in the Madison region is quite high in comparison with other metropolitan areas of similar size. Census 2000 data show that over 12% of city residents com- mute by transit, a likely reflection of the presence of a major university enrolling over 41,000 students and a metropolitan economy in which more than 30% of the labor force is em- ployed in the state and local government sectors. Preliminary analysis pointed to the following reasons for selecting Madison Metro as a case study for this Guidebook: • Madison Metro is a moderately sized agency that has de- ployed ITS technologies fairly recently. Deployment of AVL, APC, and magnetic stripe card systems occurred in 2004–2005. Prior to deployment there was little data collection or analysis. • Madison Metro has developed a successful pass program involving the University of Wisconsin, local colleges, the City of Madison, and area hospitals. Data from magnetic stripe cards are used in pass program pricing and service planning. • Madison Metro has drawn on non-transit ITS data in its market research activities. The research team met with Madison Metro staff in March 2007. Organizational Structure Madison Metro’s organizational structure is comparatively flat (see Figure B-1). Market research and service planning/ scheduling are distinct functions on a par with finance and transit services (which includes operations, maintenance, and paratransit). Staff numbers are relatively limited. Planning and scheduling consists of six persons, while fourteen persons (including nine customer service representatives) make up the marketing and customer services unit. A two-person information systems unit is responsible for managing data across the agency. Madison Metro is a department of the City of Madison, which has both advantages and disadvantages. On the plus side, it has been supported by the city’s information services (IS) unit in integrating GIS data with transit ITS and market research data. Also, the agency is overseen by the city’s Park- ing and Transit Commission, which has endorsed downtown parking pricing policies that are very transit supportive (e.g., monthly parking fees in the city’s downtown garages are $133, compared with $47 for a monthly transit pass). On the nega- tive side, Madison Metro is required to conform to the city’s policies that may not be applicable, such as for Web design, and it receives little support from the city’s IS department in maintaining its ITS databases. Experience With AVL, APC, and Magnetic Stripe Cards Madison Metro participated with other transit agencies in the state in a system procurement process coordinated by the Wisconsin DOT (WiDOT). Milwaukee Transit played a lead role in selecting ITS technologies, while the other transit agen- cies could opt in if they desired. Although Madison Metro’s general manager has been in his current position for less than a year, he was directly involved in the WiDOT-coordinated ITS procurement process while serving as the GM for another of the participating transit agencies. The ITS technologies selected by Madison Metro include AVL (with automated voice annunciation) and APCs, de- ployed in 2004, and magnetic stripe cards, deployed in 2005. APCs are installed on 38% of the fleet. All of the systems are A P P E N D I X B City of Madison—Metro Transit Case Study

Figure B-1. Madison Metro organizational structure.

integrated, with a single log on for operators. AVL data are radio-transmitted on a one-minute polling cycle, while stop- level data are stored on an on-board computer. The agency is presently developing a real time stop arrival-reporting link on its website using the AVL poll data. Automated internal/ external stop announcements are made at more than half of the 2,100 stops in the system. Beyond the base cash fare, there are a variety of payment/ fare options for riders. Options include a 31-day pass (acti- vated on first use); youth semester and summer passes; adult, youth, and senior-disabled 10-ride cards; and unlimited- ride weekend family passes. In addition, Madison Metro has negotiated pass program agreements with the university, sev- eral area colleges, the City of Madison, and several area hos- pitals. Transfers on the system are free. A breakdown of fare revenue in 2006 shows a substantial share linked to the negotiated pass programs (48.7%), fol- lowed by 10-ride tickets (19.7%), passes (17.8%), and cash fares (13.8%). Over time, the share of revenues from cash and 10-ride tickets has been declining, while the share from 31-day passes has been growing. The introduction of magnetic stripe cards has facilitated recent changes in the pass program. Before cards were deployed, Madison Metro negotiated arrangements with area institutions that guaranteed a base level of funding in ex- change for unlimited rides up to an agreed upon threshold. Beyond the threshold, program participants were charged on a per ride basis. Pass program ridership numbers were recorded by operators pressing designated keys on electronic fareboxes. The introduction of magnetic stripe cards has ef- fectively eliminated any concerns that may have existed about the accuracy of the pass program ridership counts. Beginning fall 2007, pass program agreements will be priced on a straight per ride basis. Some of the new program agreements include clauses that limit increases or decreases in revenues from changes in ridership over previous years levels. Systemwide stop level boarding and alighting data are being recovered by the APCs. Staff noted that passenger load data are not “zeroed out” at the end of each bus trip, and loads thus grow over the course of the day as more people ap- pear to be boarding than alighting. A software fix, such as that described by Furth et al. (2006), will need to be introduced to correct this problem. The accuracy of the boarding and alighting counts also has not yet been systematically verified, as in Kimpel et al. (2003). Staff thus had greater confidence in the ridership counts obtained from fare card and farebox data than from APC data. However, stop level APC data have proved useful to service planners in targeting stop amenity improvements at locations with the greatest passenger volumes. The final element of Madison Metro’s ITS technology package consists of digital cameras, which are installed on 20 buses (10% of the fleet). They are in the process of in- stalling Wi-Fi transmission to enable real time feeds of the camera images to the dispatch center. Concerns about grant- ing external access to the images through the state’s open record laws have factored in the decision not to archive cam- era image data. While the cameras offer a potential means of validating passenger movements recorded by APCs, the two systems are not currently installed on the same buses. Prior to deploying its ITS technologies, Madison Metro collected very little passenger data. Ride checks were done by staff to collect data for NTD reporting and electronic farebox data provided summary totals for routes along with operator keyed counts associated with pass users. Although the new technologies had been in active service for less than two years at the time of the site visit, staff provided a number of exam- ples of ITS data applications in the areas of customer service, market research, service planning, and scheduling. Madison Metro has historically relied on customer tele- phone contacts with service representatives and community meetings as a primary source of customer information. Using the playback feature, they are now able to check vehicle loca- tion status in the AVL data archive to help resolve customer complaints. The agency is engaged in an ongoing stop planning, evalua- tion, and consolidation process in an effort to improve service. As is often the case in the industry, proposals to relocate or eliminate stops encounter active responses from the commu- nity. As illustrated in Figure B-2, Madison Metro used GIS to present APC boarding and alighting data, as well as street and employment data from other city agencies, to communicate information related to a stop closure near the state capitol. In an easy-to-understand map, staff were able to communicate information on stop usage, distance to the nearest alternative stops, the grade that pedestrians would face in walking to other stops, and the number of persons working in the area affected by the proposed stop closure. In another GIS application, staff drew on APC stop level data and adjacent traffic count data (obtained from the Madi- son Area Metropolitan Planning Organization) to portray “exposure” at stops in the system for selling advertising space in stop shelters. Stop level passenger movement data were also analyzed by service planners to identify higher traffic lo- cations for adding stop amenities. The geography of Madison has influenced the design of the transit route network, and consequently places a greater than normal emphasis on on-time performance for effective ser- vice delivery. The network converges on the isthmus between Lakes Mendota, Monona, and Wingra, where state and city government, the University of Wisconsin, commercial activ- ity, and regional health services are concentrated. Residential and retail development spread out from both ends of the isth- mus around and beyond the lakes. Outlying routes feed 63

passengers to four timed-transfer locations, which connect to trunk service that runs through the dense central corridor. Schedules must be written to ensure that the outlying trans- fers are made and that interlined trunk service departs from the core on time. Schedule writers’ jobs have been greatly fa- cilitated by having access to running time data between route time points. Dwell times at stops are also being examined in relation to passenger movements to identify instances where operators have to kill time to maintain the schedule. Overall, schedules have been fine-tuned to reflect actual operating conditions represented in the AVL and APC data. Staff noted that after the revision of schedules fewer complaints were being logged from customers and operators. Generally, Madison Metro has not been very heavily en- gaged in comprehensive customer or population surveys. Its last system rider census was completed in the 1990s, and it has recently hired a contractor to undertake a rider/non-rider perceptions survey. The survey work undertaken by staff has focused on specific customer groups or locations. Staff recently completed a Web-based survey targeting persons with disabilities to assess preferences for lifts versus ramps to board vehicles. In areas where the agency is assessing oppor- tunities for improving service, market research staff has used the city’s GIS to obtain addresses of residents within 1/4 mile for a mail survey of service preferences. With less than two years experience working with ITS data, Madison Metro staff have not fully tapped the potential that they see in its applications to market research, planning and scheduling issues. One of the attributes characterizing transit use in Madison is the seasonality in ridership patterns. In 2006, for example, July boardings were just 55% of the November totals. Such seasonal differences largely reflect the travel activities of area university and college students and faculty. Staff would like to gain a better understanding of the travel patterns of this important segment of their market. Examination of APC boarding and alighting data by month would provide insights into the stops and routes that are most affected by this group’s travel. Examination of the sequence of their card transactions, following the procedure developed by Rahbee and Czerwinski (2002), would also provide a better understanding of their travel paths through the system. The insights gained from such analysis would allow staff to better adapt service levels and schedules to seasonal travel demands. There is also an interest among market research and plan- ning staff in making greater use of GIS in analyzing census 64 Figure B-2. Presentation of information on a proposed stop closure in Madison.

data. Applications were identified in two contexts. First, staff are interested in developing customer profiles along corridors where service is already provided. Second, there is an interest in identifying the areas that are currently not served or under- served where the demographics suggest the existence of latent demand for transit. Performance Indicators Madison Metro’s management meets monthly with the Parking and Transit Commission. A variety of fixed route operating performance indicators are reported to the commis- sion, covering service supplied and consumed (vehicle miles/hours; boardings/transfers), service quality (lift usage; vehicle/passenger accidents), customer service (complaints; compliments; suggestions), and maintenance (road calls; vehi- cle inspections). Detailed boarding statistics are also reported by time period and by route, along with corresponding productivity measures (boardings per revenue hour). Routes with boardings per revenue hour below 60% of the systemwide average are flagged for evaluation. Performance indicators also cover revenues (by source) and operating expenses. Associated productivity measures— farebox recovery, passenger revenue per trip, and operating cost per revenue hour and passenger trip—are reported. Madison Metro has identified a dozen peer properties and compares its revenue and productivity indicators to the com- posite peer averages. Data for peer properties are taken from the NTD. Presently, the performance indicators reported to the commission do not draw on ITS data, with the exception of boardings, which are based on fare card and farebox data. Fare policy discussions would be facilitated by regular reporting of activity across alternative fare media. Properties with AVL sys- tems are now commonly reporting on-time performance. This would likely be a useful performance indicator for Madison Metro, given the importance of timed transfers in its system. Issues, Observations, and Challenges Management Madison Metro Transit is beginning to make full use of the benefits of leveraging market research with data from ITS technologies. Among the three case study properties, ITS technology deployment has occurred most recently at Madi- son Metro. Also, even after accounting for is relatively smaller size, the level of staff resources available is more limited than those available at the other case study properties. For exam- ple, data from the 2005 National Transit Database shows that while Madison Metro ranks 52nd overall in vehicles operated in maximum service (VOMS), it ranks 70th overall in total administrative employees. While an institution-level em- ployment measure does not necessarily reflect IT and market research staff levels, it does highlight the challenges facing the agency in integrating AVL, magnetic stripe card, and APC data for market research and planning. The transit ITS literature emphasizes the importance of man- agement support, particularly in the post-deployment period where data archiving and development of analysis tools are oftentimes starved for funding. Having been directly involved in the statewide transit ITS procurement process, Madison Metro’s general manager showed a depth of insight and com- mitment that was uncharacteristic of his peers. He stressed that the technologies represented a direct investment in customer satisfaction (by providing stop annunciation and vehicle arrival information) and an indirect investment in developing new markets (by recovering data that would improve understand- ing of existing customers and help in identifying and reaching out to new customers). He suggested that the systems and the information they provided represent “the wave of the future” for the transit industry, deserving more funding. Market Research The market research function at Madison Metro is not as fully developed as it is at CTA and TriMet. As is the case at most smaller agencies, market research is not used in an on- going and strategic capacity; rather, it is used tactically, with studies being implemented on an ad hoc basis when a need for specific information is identified. Although systematic collection of market data is not present, staff is aware of the existence and benefits of ITS data and have been creative in applying such data in selected circumstances. An example of creative use of ITS data was the combination of traffic count and passenger data at stops to represent advertising exposure. With the emergence of ITS data at Madison Metro, there is an opportunity to develop the agency’s market research func- tion through analysis of customer data from fare cards and APCs, and service delivery data from AVL. To capitalize on the opportunity, the two marketing specialists currently ded- icated to core activities could be supplemented by a market research analyst dedicated to drawing ITS data into Madison Metro’s market research program. ITS and IS Madison Metro is transitioning from an environment in which there was no consistent data collection to one where ITS operating and passenger data streams pose several chal- lenges. The data support staffing that was embedded in the market research and planning units at CTA and within the scheduling and planning functions at TriMet, which proved 65

important in their efforts to leverage ITS data, does not presently exist at Madison Metro. The agency has been fortu- nate in dealing with this limitation by virtue of the fact that its IS manager is a former service planner and operator who brings an understanding of market research and operations practice that is not normally found in that position. While there is adequate IS staffing to manage ITS data, there is a need for additional staff to develop applications and cus- tomized reports. The vendor-provided reporting software (Ridecheck Plus) was not considered very useful without cus- tomization. Additional IS staff would also open up an oppor- tunity to tap the intellectual resources of the university through internships, which has not been pursued to date because of the limited time staff have to take on management of this activity. Moreover, the University of Wisconsin administers a U.S. DOT-sponsored regional University Transportation Center (UTC) whose theme (optimization of transportation invest- ment and operations) appears to be compatible with Madison Metro’s need for developing new applications that leverage ITS data. University faculty and graduate students could poten- tially be engaged in UTC-supported research or technology transfer activities that would help to meet this need. While the coordinated statewide ITS procurement program eased the burden that each property faced in the process, the “one size fits all” approach meant that the systems acquired may not have been best suited to each property. Among the alternative fare payment technologies, smart cards were dropped from consideration fairly early in the process, and there was a concern that the magnetic stripe card technology selected represented a second best choice for Madison Metro. There were several observations on the technology deploy- ment and procurement processes. First, it was necessary to re-geocode the stops in the system to achieve the accuracy re- quired for AVL operation. Second, staff emphasized that it was important to obtain full documentation of the systems. Third, staff thought that the procurement and deployment processes would have been improved by collecting more in- formation from other transit properties that had already gone through the processes. References Furth, P.G., Hemily, B., Muller, T.H.J., and Strathman, J.G. TCRP Report 113: Using Archived AVL-APC Data to Improve Transit Performance and Management. Transportation Research Board of the National Academies, Washington, D.C., 2006. Kimpel, T.J., Strathman, J.G., Callas, S., Griffin, D., and Gerhart, R. L. Automatic Passenger Counter Evaluation: Implications for National Transit Database Reporting. In Transportation Research Record: Journal of the Transportation Research Board, No. 1835, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 93–100. Rahbee, A., and Czerwinski, D. Using Entry-Only Automatic Fare Col- lection Data to Estimate Rail Transit Passenger Flows at CTA. Proc., 2002 Transit Chicago Conference, Chicago, IL, 2002. Madison Metro Staff Interviewed David Eveland, Coordinator, Information Systems Charles Kamp, General Manager Julie Maryott-Walsh, Manager, Marketing and Customer Service Sharon Persich, Manager, Service Planning and Scheduling 66