Designing a Mobile Security Wait-Times Feature for Pre-Arrival Awareness
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.
Across concept testing, one pattern was consistent: trust depended less on precision than on legibility. Travelers wanted to understand what the estimate represented and how current it was. Some relied on historical patterns to plan earlier in the day; others depended on live signals closer to arrival. What undermined confidence was opacity—unclear sourcing, unclear freshness, or signals that felt guessed.
These findings shaped the feature’s core structure. Historical and real-time inputs were combined into a single Expected Wait Time, supported by visible timestamps to signal recency and integrity. Early signals also pointed toward behavior-aware presentation rather than a single static display.
Attention then shifted to language and scale. Testing showed a strong preference for concrete, procedural terms (e.g., “Lines” over “Crowds”) and for time ranges rather than point estimates. Ranges helped travelers interpret variability without feeling misled when conditions changed. Frequent travelers were especially sensitive to implied precision and quick to notice mismatches.
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.
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
The Psychology of Security Wait Times
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 restarting the cycle.
Survey data reflected the same dynamic. Travelers who felt less confident about what to expect arrived earlier and rated the security experience more negatively, even when reported wait times were similar. Secondary research reinforced this finding: predictability and explanation often matter more for perceived control than absolute duration.
The practical insight was straightforward. Travelers do not need certainty. They need something intelligible to plan around.
Phase 2-3: Concept Validation and Refinement
With the behavioral model established, research focused on whether wait-time information could earn trust across different planning styles—and how it needed to be presented to do so.
The outcome was a set of portable content standards designed to scale with the feature: consistent terminology, range-based estimates, and clear expectation-setting that preserved credibility over time.
Phase 4: Live Evaluation
Live evaluation paired in-line surveys and interviews with behavioral signals such as arrival timing and dwell patterns.
This phase examined whether pre-arrival wait-time information influenced:
when travelers arrived and how they distributed time in the terminal
satisfaction and trust under real operational variability
It also established baseline measures for ongoing evaluation as the feature expanded across locations.
Strategic Implications
This work clarified that predictability is something a product can create—by shaping how travelers interpret variability before it becomes stress.
Airlines can’t control security throughput, but they can influence the conditions under which travelers arrive at security: how early, how tense, and how prepared. That matters because pre-arrival behavior drives downstream outcomes the business does care about—lobby congestion, spillover queues, staffing pressure, and the emotional tone travelers carry into the rest of the journey.
The strategic opportunity is upstream leverage: giving travelers credible, usable information early enough to change what they do. When that happens, the airport works differently. People arrive closer to departure, space pressure eases, and the day-of-travel experience becomes more orderly even without operational changes at the checkpoint.
Longer-term, this also connects directly to hub expansion planning. If the airline has increasing influence over security-adjacent design, then wait-time information becomes part of infrastructure strategy—not just a UI element. Digital guidance can reduce peak crowding and help the physical system stay within its intended footprint.
In that sense, the feature is a model for how digital experience absorbs volatility elsewhere in the journey: not by promising stability, but by making variability interpretable and actionable—early enough to change behavior.