Case Studies

Case Study: Pairing Transit OOH with Transit-Mobile for Lyft

Lyft Rideshare


Lyft wanted to boost app installs and activations from Chicago’s suburban rail riders, by focusing on the ‘First’ and ‘Last Mile’ of their commute. Additionally, they wanted to tie this mobile campaign into one of their largest out-of-home campaigns ever.

Mobile Creative

Lyft Mobile Banner
Lyft Mobile Banner


CommuteStream provided the expertise and technology necessary to target the desired riders at the right time, as well as analytics and data to improve the campaign over time. Additionally, CommuteStream’s rich reporting helped Lyft better understand how and which riders were responding.



CommuteStream’s expertise in public transit advertising helped Lyft identify and target suburban commuters at a time and place when they are thinking about getting to and from the train. Resulting click, installation, and activation data were collected throughout the campaign and fed back into the system to provide a better understanding about which riders were responding.


Strategic, train-station-based, day-parted targeting was used to reach the desired audience. In addition, approximately 20% of impressions were used for broader regional “polling”. This less selective targeting allowed CommuteStream to maintain a broader understanding of response trends across all of Chicago’s public transit.

Lyft Out-of-Home Ads
Out-of-Home Creative

CommuteStream allowed us to reach the exact segment we were going after, measurably — no better way to synchronize mobile ads with traditional transit OOH.

~Jean-Paul Biondi, Head of Marketing, Chicago

0.27% CTR Increase.


After analyzing the first month of rider engagement we optimized targeting, immediately increasing CTR by an additional 0.27% for the remainder of the campaign. This modest gain in CTR led to a substantial 94% increase in daily app installs and an 88% boost in overall conversions. Subsequent phases of the campaign built on the success and data from this initial phase. Reports and data visualizations were provided back to Lyft, helping them to better understand riders and inform broader marketing decisions.

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