Designing a Mobile Security Wait-Times Feature for Pre-Arrival Awareness
Research Design
Generative Research into how uncertainty around security shapes traveler emotions, behaviors, and perceptions of fairness
Concept Testing to test whether wait-time information could credibly reduce that uncertainty
Content Testing to refine language, scales, and presentation for trust
Live Evaluation to assess real-world impact of mobile security wait-times feature on satisfaction and behavior
Problem Space
Travelers’ experiences of airport security—and the terminal experience leading up to it—are poised to shift significantly over the next decade. Rising passenger volumes and structural constraints at major hubs are reshaping how security and pre-security spaces operate. As major carriers exert greater influence over airport expansion and how security operations are integrated into the terminal, airlines increasingly shape how travelers prepare for screening, including before they arrive at the airport.
From the customer perspective, security poses a distinct challenge for airline experience design. Alongside delays, it is one of the strongest drivers of day-of-travel satisfaction, largely because it shapes when travelers decide to leave for the airport and how they experience arrival. Yet security screening is the one stage of the journey airlines do not control directly. It sits between parts of the experience the airline does influence, such as check-in, bag drop, and boarding. However, travelers do not separate these boundaries when evaluating their experience. Stress at security produces a halo effect that the airline ultimately absorbs.
Rising passenger volumes make this tension more acute. Higher throughput increases congestion in and around security, driving the need for airport expansion, reconfiguration, and tighter integration between security and the surrounding terminal. As these spaces are redesigned, decisions about layout, circulation, and capacity become increasingly sensitive to arrival patterns.
Together, these conditions established a clear research and design challenge. If airlines are to increase customer confidence and improve operational performance without relying solely on infrastructural change, they need ways to influence customer behavior upstream, before airport arrival. That requires understanding how travelers plan around security, and whether providing credible security wait-time information before arrival could change that behavior.
This work examined whether pre-arrival security information, delivered through a security wait-times feature in the airline mobile app, could reduce uncertainty at the point of planning—encouraging later, more distributed arrivals while helping airlines reduce precaution-driven congestion and make the security experience more predictable.
The Psychology of Security Wait Times and its Applications
Phase 1: Generative Research
First, we had to understanding how travelers experience airport security, and how their experience shapes behavior before, during, and after screening. The research drew on traveler interviews, in-airport intercept conversations, journey walkthroughs, an attitudinal survey, and on academic and industry research on the psychology of waiting, and the associated concepts of perceived wait-times, perceived fairness/unfairness, and perceived justice/injustice.
What emerged was a behavioral cycle that exist due to wait-time and procedural unpredictability. At the center of this pattern is a self-reinforcing cycle driven by perceived wait time, uncertainty, and fairness:
When travelers lacked credible expectations, they compensated by arriving early. Earlier arrival increased dwell time and sensitivity to delay. As waiting stretched without explanation, frustration escalated and was interpreted as unfairness or neglect. That experience only reinforces precautionary behavior and restarted the cycle.
The research also showed a clear pattern around confidence and planning. Travelers who did not feel confident about what to expect in terms of their security experience arrived earlier and rated the security experience more negatively, even when their reported wait times were similar to travelers who felt knowledgable about what to expect at security and were not concerned. Secondary research helped explain this pattern. Predictability and explanation often matter more for perceived control than absolute duration. When travelers can see how the situation is unfolding and understand why it looks the way it does, they can judge risk, time their actions, and decide what to do next. When they cannot, even short waits feel threatening, because there is no stable basis for planning.
The practical insight was straightforward. Travelers don’t need certainty—they need their expectations set and updated in n ways that let them act with confidence.
Phases 2-3: Concept Validation and Refinement
With the behavioral model established, research shifted from explaining uncertainty to testing whether wait-time information could actually reduce it. The central question was whether those estimates could earn trust across different planning styles and moments in the journey.
The generative research indicated that travelers wanted to understand what the wait-time estimate represented, how it was generated, and how current it was. Our prototype combined historical and real-time inputs into a single ‘Expected Wait Time’, supported by visible timestamps to signal recency and integrity.
The design focused on presenting one intelligible reference point whose reliability could be assessed at a glance. Content testing showed strong preference for concrete, procedural language (“Lines” rather than “Crowds”) and for time ranges rather than point estimates. Ranges helped travelers interpret variability without feeling misled when conditions changed, and frequent travelers were especially sensitive to implied precision.
The result was a set of portable content and presentation standards designed to preserve trust as conditions changed.
Phase 4: Live Evaluation
Live evaluation focused on travelers flying on selected pilot flights where the Security Wait Time feature was available in the mobile app. Post-security SMS surveys and intercept interviews were paired with geofencing-based arrival timing to assess both reported behavior and observed arrival patterns.
Survey results indicated clear awareness and behavioral impact. 71% of respondents noticed the feature, and among those, a majority reported using it to help decide when to go to the airport or approach security. Geofencing analysis provided early behavioral corroboration: during the 21-day pilot, arrival times for customers on pilot flights shifted later on average compared to travelers on comparable flights at the same terminal and departure windows where the feature was not available.
While the pilot duration and sample size limit definitive conclusions, the direction of the shift aligned with both survey responses and the underlying behavioral model. Together, these measures established a baseline for continued evaluation as the feature scales.
Strategic Implications
From a customer-facing perspective, the research showed that addressing security concerns does not require eliminating variability at the checkpoint, but making that variability intelligible early enough for travelers to plan around it. When customers can form and revise expectations with confidence, they rely less on precautionary early arrival and more on information.
Operationally, this creates leverage without infrastructure change. Reducing precaution-driven arrivals helps smooth demand across security-adjacent spaces, improve circulation, and ease peak congestion even when screening throughput remains constant. Over time, it also supports more informed decisions about terminal layout, staffing, and capacity as hubs expand.
This research complemented a broader study of day-of-travel app engagement conducted for the development of a new travel mode in the app that activates in the 24 hours before departure.
That work showed that, alongside delays, security is one of the two primary concerns shaping how travelers plan and time their arrival at the airport. When security information is missing or unreliable, travelers compensate by arriving early and by juggling between their airline’s app and other sources, esp. Google Maps, airport websites, the TSA app, or third-party security wait-time sites . The broader patterns of mobile engagement and pre-arrival coordination explored in that work are detailed further in the related case study, linked at the end of this page.
Case Study
Day-of-Travel Mobile Engagement
A diary study of how travelers actually used—and worked around—airline apps across the full travel day, informing “travel mode” experiences that prioritize what matters when time is tight.
→ View case study