Traffic isn't caused by cars, it's caused by the people driving them.
Through the application of behavioral economics, computer science becomes commuter science.
Behavior Modification Engine
The advent of new technologies in the transportation sector have rapidly changed the industry’s understanding and management of traffic, but for all those innovations have done to analyze traffic patterns and measure corridor reliability, they’ve done little to address the core cause of traffic: human behavior. INDUCE was designed to change that.
The INDUCE behavior modification product is where computer programming meets commuter programming. INDUCE’s artificial intelligence pairs extensive data on user travel patterns and behaviors with demographic and psychographic insights to create rich user personas. This deep understanding of user motivations, wants, and needs allows agencies to dynamically micro-targe pre-qualified audiences with contextually-relevant information and solutions, increasing response rates and behavior change while preserving resources.
Traffic is fluid and dynamic, and achieving operational goals during rush hour requires different management strategies than doing so at noon. Through the INDUCE product, agencies can run campaigns triggered by any number of real-time events and predetermined parameters. For example, when rush hour traffic exceeds a predetermined travel time index threshold along a particular corridor, single-occupancy drivers could be targeted with a campaign to convert them to take transit, leave at a later time when congestion has reduced, or carpool with another driver. As to which travelers are targeted for which mode or behavior shift, INDUCE’s artificial intelligence does all of the work once again.
For many campaigns, there is an array of potential commuter actions which can contribute to a successful outcome. Whereas one commuter might be inclined to carpool, another might have greater flexibility in what time they arrive at their destination. The key to motivating behavior change is to first understand a commuter’s personal goals and objectives then deliver the compelling, personally-relevant information which can help achieve them.
Based on data that has been captured from our JOURNEY platform (e.g., observed travel behaviors, information captured from in-app microsurveys and inferred activity type from destinations and time of day such as picking up kids from school, dining habits, etc.), INDUCE will micro-target a specific set of users.
By using sophisticated AI-based mathematical algorithms, campaign parameters are then matched to user characteristics to compute a likelihood of change coefficient; users with high coefficients are more likely to try a suggested alternative such as changing mode of transportation or altering their route or time of departure. The attractiveness of alternate modes is evaluated for the upcoming trip (Is the nearest transit station convenient and do transit arrival times synch with the user’s normal schedule? Are there other commuters nearby with similar destinations and departure times who would be ideal carpooling companions?). By combining high-change coefficient users with rank-ordered attractiveness of options, INDUCE populates JOURNEY with personalized information/suggestion tiles promoting the highly-relevant commute options.
Graduated Baby-Steps Progression
Taking the bus, sharing a ride with a neighbor, leaving a little earlier than normal -- if the clear advantages of these options were as clear as assumed, commuters would already be utilizing them. The truth is that few commuters are ready to toss their keys and dive into the deep end of alternative commutes. For this reason, INDUCE employs a graduated strategy which begins with presenting strong selling-points to the user: ”Taking transit will eliminate your parking costs!”, “Use transit’s free wi-fi and check off some to-dos on the way to the office!”, “Did you know you could pay for your ride directly through your smartphone?”
These information tiles are used selectively and serve to inform the user as well as raise the attractiveness of alternative modes. After 2-3 information tiles have been delivered to the user (each with a Learn More option) and the user has dipped their toes in the water, INDUCE then displays a tailored time-appropriate suggestion tile proposing a new mode or departure time with a “Try It” option.
Option to Incentivize with Points/Rewards
Not all users are ‘good’ targets for mode or departure time change. It could be that their travel behaviors are unpredictable or perceived to be too rigid (e.g., very little flexibility in their schedule, too many stops en route to their final destination), or that the commuter is simply too rooted in their routine to consider other options.
To further increase user engagement and behavior conversion, optional incentives can be integrated into JOURNEY to achieve campaign and system goals. The value of the incentives and how they are administered are facilitated by INDUCE to nudge a user through the progression of adopting alternative modes. For example, tapping “Learn More” on an information tile could earn 25 points, while actually trying transit or joining a carpool could earn 100 points (upon verification via integrated measures). The reward points accrued by a user can be spent on transit and transportation services or redeemed in-app for gift cards to national stores and restaurants. The conversion value of these points, the frequency of the offers and how they are administered (changing mode, time of departure, etc.) are all configurable by the agency. The challenge in incentive administration is to use them judiciously, only ‘reward’ changed behavior and taper them down once the change has been sustained -- these critical components all are managed by INDUCE’s artificial intelligence-backed algorithms.