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In attempting to design a system that is capable of tracking subways and the number of people that are on each train car, we needed to determine what group of people we are targeting. After careful consideration, people of the upper-middle class with smartphones that commute and that want to use their wisely is the customer segment that we are pursuing. In general, people that are a part of the middle class make between $25,000 and $100,000 per year, however this definition needs to be adjusted for cities like New York City and San Francisco because of the high cost of living. Since our idea targets one of these cities, an adjusted income for our customer is needed and comes out to be between $54,000 and $120,000. This will apply to people that live both inside and outside of the city, as people from both areas are the commuters whom we are targeting. Furthermore, the ideal way to deliver information to this group is through their phone, so the end goal is create an app that will display the location and occupancy for the subway cars. This leads to how we plan on determining the location of the cars. Today, the common practice for tracking vehicles is through GPS, whether it is with smartphones or devices that have a built in sensor. Effective examples of this tracking is MTA Bus Time Technology, which allows the MTA to track all of its buses throughout New York City and accurately determine when they will make it to their stops. Amtrak also offers users the ability track trains, where the sensors are placed on the tracks and as the train passes by it sends a signal relaying its location. Now this effective because these buses and trains stay above ground, allowing the sensors to remain in contact with GPS and determine their locations. Since the subway is underground a different kind of locator is needed, and the alternative is a device that relies on preloaded maps, timing, and accelerometers to determine its location. Generally, accelerometers are used in tracking movement for people, so this is a new concept as applied to vehicles. The second part of our idea requires the counting of people on the subway cars. While people is not a new idea as seen with companies like SenSource, Inc. or Traf-Sys, Inc. that specialize in developing technology for this purpose. However, these systems are designed for retail environments, so that businesses can measure the foot traffic in their stores and they tend to be expensive. Simpler devices exist but they may not provide accurate data as they use infra-red sensors that can be easily triggered. For this reason a heat sensitive camera would probably work best as it would allow us to see the number of people on a given car, while keeping their identity secure. The technology we need exists, which makes the hardest part of our idea, collecting the data and making it available to our users. While we plan on using low energy Bluetooth beacons or attempting to use wifi as means of gathering data, we would still have to set up a server that could process the information of how many people are actually in the train and where the train is in real time. Then another issue becomes developing an app that updates to have the most recent data. This issue would have to be resolved through further research into data processing and software development as I believe no one currently has a strong enough skill set to handle such complicated programming. We could also seek out the advice of experienced app developers and people that deal with information technology regularly.

Customer Segment: 18-45 year old business-oriented New York City subway commuters who have flexible, but valuable time

Value Proposition: A train tracking app that solves the problems of time waste during a commute by telling the user exactly when a train will arrive at the station, and crowded trains by notifying the user of the number of people on the train at a time.

Customer Research: I called different relatives and friends including Tracey Dwyer (Electrical Engineer, Checkpoint Systems), Jim Dwyer (CPA, AIG), Dr. Jennifer Hartstein (PsyD), and Vannessa Drossman (Marketing, Martha Stewart) who fit the customer segment and asked them the following questions: What annoys you the most about commuting on the subway? What subway apps do you have downloaded on your phone? Would you be interested in an app that helps you avoid crowds and save time on a subway? Conclusively, they were most bothered by the people on the trains. After a long day of work, it’s bothersome to be surrounded by large crowds. When asked if they would stay at work longer to avoid the crowds, they responded that they would. Some of them often do just that. Based on their past experience, they will leave the office at the time of day that they believe will help them avoid rush hour. However, they noted it is not a very accurate system. Depending on holidays, weather, etc. commuting patterns change; it is often unpredictable. All of them had HopStop downloaded onto their phones. However, they infrequently use the app. The will only use it if they are traveling to a place they have never been, which is rare. They responded that they would definitely download an app that does those things if it is easy-to-use and accurate. User-interface was very important. Some of them also suggested adding the trip-planning aspect of the commute, which HopStop offers, would improve the product.

Competitors: Current New York City subway app competitors include HopStop, Embark NYC, and MTA SubwayTime. Neither HopStop nor Embark NYC offer train tracking or crowd control. However, MTA SubwayTime offers train tracking features. The app only tracks the trains on 8 of the 24 NYC Subway lines. Ultimately, none of the apps do what our train tracking app would offer. Although members of our customer segment have these apps downloaded to their phones, they use them infrequently. Our customer segment wants to be informed about crowds and train timing daily, and would get more use out of an app that does just that. Incorporating the mapping attributes of Embark NYC and HopStop would expand our market and supplant the need for either of those apps as a whole. Apple recently purchased HopStop and the application is shutting down in October.

Future Research: Calling competitors and posing as a customer, interviewing subway riders

Customer Segment: Business Commuters Age 18-45 who are upper middle class and have time that is valuable, but flexible.

Our current value prop is an app and sensor combination that tracks the amount of people on various trains and recommends the routes depending on user preferences such as personal space or efficient travel, Current apps on the market such as Roadify, Embark NYC, or Exit Strategy do not track the real-time location of trains or the amount or kinds of people on trains,so their use is limited. However, exit strategy does tell you which part of the train to get on if one wants to exit as close as possible to one’s desired exit or destination, which is a very useful feature and could be implemented in our product. The other two apps that were mentioned also display delays and other crowdsourced information about one's route. However, all of these apps seem to be incomplete versions of an app that could address a lot more pains that our customer segment has. We still need to go out and do more interviews or contact the makers of apps for the NYC subway system to try and gain a deep and insightful understanding of what jobs our customers have to do, what their pains are, and what gains they would like to see in their lives. As of now we are still not sure exactly what technology we could use for our product, but technologies such as CO2 sensors, cameras, or infrared sensors combined with low energy bluetooth or wifi could be used to make our value proposition a reality.