Redesigning the Rental Funnel: Increasing Add-On Sales by 18% with Geospatial Foot Traffic Analysis

Our client, a leading car rental provider, faced a classic paradox. Their airport locations were among their most profitable, yet also the source of their worst customer satisfaction scores. For years, they struggled with a persistent issue: despite ever-increasing passenger volumes, their revenue from high-margin ancillary products—like GPS upgrades, child seats, and premium insurance—had remained stubbornly flat. They had a strong suspicion that the physical layout of their rental facilities was to blame, but they lacked the concrete data to justify a multi-million-dollar, nationwide redesign initiative. Their core question was simple yet profound: how could they prove that moving a counter or a display rack would generate a tangible return on investment?

The challenge was to understand the invisible forces shaping the customer experience: customer flow . They needed to see their rental counters not just as a point of sale, but as a dynamic environment with traffic jams, fast lanes, and dead zones. This is where our team at Iceberg Data came in. We proposed a multi-layered data collection and analysis strategy to build a comprehensive picture of how customers navigated these high-stress spaces.

Our first step was to build the foundation. We systematically scraped the publicly available terminal maps from the websites of their top 50 airport locations across North America. This gave us the architectural blueprint for each unique space. Next, we integrated with real-time flight arrival APIs for those same airports. By correlating flight capacities and arrival times, we could accurately predict when large waves of potential customers would be deplaning and heading toward the rental car areas. This moved their staffing model from reactive to predictive.

The most innovative layer of our solution was modeling the foot traffic itself. We tapped into aggregated and fully anonymized data from public Wi-Fi access points within the airport terminals. By analyzing connection density patterns, we created detailed heatmaps that visualized where people congregated, how long they lingered, and the paths they took to get to the rental counters. This entire process was built on public, aggregated data, ensuring that individual privacy was never compromised. To add a qualitative dimension, we scraped thousands of public customer reviews from major travel and aggregator sites, using Natural Language Processing (NLP) to isolate and analyze comments containing keywords like 'wait time,' 'long queue,' 'confusing layout,' and 'slow service.' This allowed us to quantify the negative sentiment directly tied to physical store design.

When we layered these disparate datasets, the bottlenecks and missed opportunities became glaringly obvious. Our analysis revealed two critical zone types. First were the 'high-velocity corridors' —the direct paths travelers took from baggage claim to the rental counter. Customers in these corridors were mission-oriented and moved quickly; marketing displays placed here were almost completely ignored. In stark contrast were the 'involuntary dwell zones' —the long, snaking queues in front of the counters. Our data showed that the average customer spent 8.5 minutes waiting in these lines. This was a captive audience, yet the displays for high-margin add-ons were often located on a far wall, completely out of sight. Furthermore, we discovered that nearly 30% of the people in the main queue were loyalty program members who were eligible for a self-service kiosk, but these kiosks were poorly signed and often hidden behind structural pillars, creating unnecessary congestion for everyone.

Armed with our data visualizations and predictive flow models, the client's operations team finally had the irrefutable business case they needed. They launched a pilot redesign program at three major airports based on our specific recommendations. They moved the self-service kiosks to a prominent, up-front location with clear, bright signage, which immediately diverted a significant portion of traffic and shortened the main queue. Most importantly, they redesigned the queueing areas to guide customers directly past new, interactive displays for insurance packages, satellite radio, and car seats, effectively transforming 'wasted waiting time' into 'active consideration time.' The results were transformative. The average time a customer spent in the facility dropped by over three minutes. Ancillary sales at these pilot locations surged by an incredible 18% , and customer satisfaction scores related to the pickup experience improved by over 30% . The project was a resounding success, and our data is now the blueprint for a nationwide rollout, optimizing each location for efficiency and profit.