Toronto Parking Authority (TPA), the company that manages the bike sharing service in Toronto, sells digital ad space at bike share stations across the city. Bike share users rent a bike from a bike share station at a location in the city and can return it to a station at another location within 90 minutes. Toronto’s bike share network operator (Shift Transit) manages marketing and advertising for the bike share service itself (eg. campaigns to gain new riders, build awareness when the footprint of the network is expanded into new neighborhoods of the city, etc.) by advertising the service on the bikes, faces of the bike share stations and bike docks at the stations.
In order to further help partially offset capital and operating expenses for the bike share network, TPA generates advertising revenue by selling the digital ad space at bike share stations by the hour. Some examples of adds displayed on Toronto’s bike share stations include Heineken, Nespresso (1, 2, 3), Meridian Credit Union and Vizzy Hard Seltzer. TPA has recently partnered with Mega Marketers LLC in order to manage ad space on the bike share stations. Mega Marketers LLC’s offerings includes strategically located faces for Out-of-Home (OOH) advertising in the form of billboards, posters and other types of displays to help businesses reach their customers across a wide footprint includes the city of Toronto. In this way, they help businesses optimize customer acquisition and conversion. So, partnering with TPA was a seamless fit for Mega Marketers LLC to compliment its street furniture portfolio.
One of Mega Marketers LLC’s clients is the School of Continuing Education (SCE) at Mega City University (MCU), which is located in Downtown Toronto. Since September of 2022, MCU, a university that is also located in Toronto, has added several practical Artificial Intelligence (AI) certifications to their list of professional development programs. They are looking to launch a marketing campaign in 2023 to grow enrollment in their AI program. The target audience for the campaign is working professionals due to the flexible nature of the scheduling offered by the program (eg. weekend and evening classes, short lecture duration, two sessions per week, etc.). In order to accomplish this, they have decided to include OOH advertising in their media planning strategy. They are now looking to make use of bike share advertising through a digital billboard ad campaign that partly uses the digital ad space for sale on the faces of bike share stations. The aim of the campaign is to build awareness for and increase enrollment in the program by reaching working professionals at key locations across the city.
Bike share systems, including Toronto’s, offer a sustainable first-and last-mile option to compliment various modes of public transit (bus, train, etc.). It is not surprising that the service has reported seeing strong uptake by commuters who use bike share bicycles as commuter devices to/from office locations across the city, with total bike share usage seeing strong year-over-year growth and annual ridership expected to cross the 5M trips mark in 2023. This is a pattern seen in many other bike share programs as well. There were approximately 465,000 users in 2020, which was nearly double the previous year. Data for the number of unique bike share users in Toronto is not available publicly so it is not possible to track this on a yearly basis. Nonetheless, with the strong year-over-growth, MCU feels these bike share users match with their target audience for this ad campaign. They represent future candidates for enrollment in multiple courses offered by the AI program. So, they want to target digital ads to the users of Toronto’s bike share service.
The bike share service footprint is spread out across the city of Toronto and covers nearly 800 bike share stations with plans announced in August of 2022 to reach 1,000 stations by 2025. So, while the same service is available across the entire network, usage patterns are not consistent from station to station. Further seasonal variances can also be expected. Capturing these differences in the content shown in ads will be crucial to effectively reach the target audience. It will also be necessary to use these insights to select the top-performing stations at which to buy ad space in order to reach the largest possible audience of bike share users as cost-effectively as possible.
The marketing team at Mega Marketers LLC has agreed to work with MCU to launch a digital billboard ad campaign to target these bike share users. The campaign will display billboards advertising MCU’s AI program on the face of bike share stations. Mega Marketers LLC will run the campaign at times and locations that are chosen in order to maximize its effectiveness. In order to maximize exposure while also minimizing costs, stations across the network that capture the largest possible share of bike share ridership should be chosen to display ads. The marketing team will use insights about the users of the bike share service to design content for display in the ads.
The business user is a marketing team manager at Mega Marketers LLC.
The marketing team is looking for insights into the usage patterns of bike share stations that would help them efficiently reach their target audience (bike share users). Due to constraints on ad spending, the marketing team wants to target ads that capture the largest possible share of bike share users across the network. As a member of the Data Science team at Mega Marketers LLC, the goal is to extract insights into how, when and where bike share is being used. If the marketing team understands these attributes, then they can tailor the content that is shown on the digital displays at the stations accordingly in order to help MCU maximize their exposure to the target audience while also minimizing costs.
In order to address the client’s requirements, this project performs the following tasks
Extract trends regarding usage of the bike share program in order to understand the behavior of the target audience.
Provide recommendations for
in order to build maximum awareness while minimizing advertising costs.
