Partner with HERO2
Rewards that move people out of their cars, with trip-by-trip data behind every estimate.
Bring new customers to your door
List a reward for free. People who walk, bike and ride transit spend their Power at your business, and you see every visit.
- Free to list your business
- Switch rewards on for your slow hours
- Customers redeem on their own phone
- See every visit in your dashboard
Already partnering with HERO2
- University Taqueria
- IB's Hoagies (Southside)
- Top Dog (Downtown)
- Red Tomato Pizza House
- Cali Grill
- Tea Hut
- Wonderful Spa
“We're excited to partner with HERO2, promoting sustainability while bringing new students to try out our products.”
Why choose HERO2
Cities
Reward residents for leaving the car at home, and see how they actually get around, trip by trip.
Big events
Steer visitors to new neighborhoods and local businesses on foot, by bike and by transit, and measure the shift.
Campuses and employers
Scope 3 commute emissions usually come from surveys and averages. HERO2 builds the estimate from real trips, and rewards the ones made without a car.
Developers
Under CEQA, projects that add too many vehicle miles traveled (VMT) must mitigate them, for example through a VMT bank. Every HERO2 trip comes with its mode and distance, so the car miles a program replaces can rest on real trips instead of a default estimate.
Why we start on campus
Students already walk, bike and ride transit. We start there, build momentum, and keep the habit alive when life pulls toward a car.
- 01
Start with students
Campuses are full of people who already get around without a car. That's the habit we build on.
- 02
Learn the baseline
Confirmed trips earn Power whatever the mode, so HERO2 learns how each person really travels, car trips included.
- 03
Win back the car trips
When graduation, a first job or a move pulls someone toward driving, HERO2 sees the shift, and rewards give them a reason to switch back.
How it's calculated
Every estimate starts with a real trip.
- 01
Detect
Phone sensors pick up each trip, and a model splits it into legs: walking, biking, bus, train or car.
- 02
Compare
Each leg is compared with how that person would otherwise travel: their own car (EPA fuel-economy data), their past trips on the same route, or their recent travel. New riders get a regional average car.
- 03
Stay conservative
The estimate is scaled down by the model's confidence in each trip, and only that cautious figure is reported.
Research with UC Berkeley CDSS
Trip segmentation
Turning raw GPS into separate trips with clean start and stop points.
Mode identification
Machine learning that tells walking, biking, transit and driving apart from phone sensors.
Routine prediction
Learning routines to time nudges toward lower-carbon trips.
Working with
- Compete4LA (LA Business Council)
- UC Berkeley CDSS
- UC Office of the President, Sustainability
Get in touch
team@hero2.org
Have car miles to cut, Scope 3 to measure or a crowd to move? Let's talk.
Contact usAlready a partner?
Sign in to the partner portal to publish rewards, see each redemption, and check the travel and estimated CO₂ impact behind them.