END TO END AIRPORT PASSENGER ANALYTICS November 9, 2015
HOW IT WORKS Ingest Existing Data Hardware Passive Detection End to End Analytics Cisco MSE Aruba ALE CUTE Agent Log-on AODB Flight Data Other On-Site Sentiment Data If there Sentiment is no difference Scraping from the previous Wi-Fi 60 second wait time the same number is reflected on the new refresh Weather Data Flight Delay Base Station Bridge back to servers BLE Sensors DC Voltage BT 2.0 & BLE 4.0 Wi-Fi Sensors Camera Image Capture Also acts as beacons 2 Queue Analyzer Confidential SITA 2015
PERCEPTION vs REALITY 2013 installation in Empire State Building Concierge service misinforming visitors on time to top (Said 2 hours) Critical visitor decision point is 45 minutes ESB set out to improve this perception to increase traffic If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh Using our passive sensors reality is 37 Minutes Perception 2 Hours API feed on website will improved visits by 8-10% Reality 37 Minutes 15mm ROI on year 1
DATA AGNOSTIC Bluetooth 2.0 & 4.0 Beacon Database Application Analytics SITA Registry Close Proximity Analytics Wi-FI Aggregated Cisco/Aruba Wi-Fi Data Ticket Scan PAX Traveler Metrics Ingest Compile Deliver Meaningful Analytics Camera Data Proxy for Density & Positioning FLIFO - AODB Proxy for Asset Density Retail Engagement & Positioning 4 Presentation Title Confidential SITA 2015
END TO END IMPACT ANALYSIS WAIT FLOW VISIT ENGAGE RECLAIM Queuing Wait Times Passenger Flow Analytics Passenger Visit & Dwell Retail Food & Beverage Carousel Wait Times Predictive Queuing Historical Queuing Lane Open Detection Recommendations First Location Visited Referring locations Last location visited Transfer Gate to Gate First Location Visited Most Visited Location Location Dwell Times Rank of Visits & Density Retail Draw Rate Retail Traffic By Hour Missed Opportunity Airline Wait Times Historical Wait Times Historical By Airline Impact to Travelers 5 General Confidential SITA 2015
PASSENGER WAIT TIMES KEY FACT Increasing passenger satisfaction by 2% will result in $0.8 increased spend per head Epinion Study May 2015 6 Presentation Title Confidential SITA 2015
SECURITY CHECKPOINT Our Q-view product allows an airport to view the current predictive wait times and also see the line at a glance refreshed every 60 seconds If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh
SECURITY CHECKPOINT Leverage mix views for cross functional views If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh
SECURITY CHECKPOINT For airports with multiple queues we provide a mix view that allows the airport to view a snapshot across the entire airport If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh
SECURITY CHECKPOINT A single click interface enables zoom view for more detail of the selected checkpoint Security F 16-20Min Current Wait Time 14:23Min If there is no difference from the previous 60 second Daily Average wait time Wait Time the same number is reflected on the new refresh Lanes Open
SECURITY CHECKPOINT We ingest sentiment data for correlation analysis including: Feedback now Happy or not Social Scraping If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh
SECURITY CHECKPOINT Our solution also enables lane detection for correlation with wait times. We utilize one of three technologies for detection including: Bluetooth Sensors If there Motion is no Sensors difference from the previous 60 second wait time the same number is reflected on the new refresh Accelerometers Lanes open
SECURITY CHECKPOINT Lane detection allows for lane open forecasting and recommendations by day and hour. We leverage historical information, thresholds, If and there AODB is no flight difference data to from recommend the previous 60 second wait time the same number is reflected on the new refresh lanes open to handle the departing passengers within threshold levels.
SECURITY CHECKPOINT We have a new product that enables visual views of the queue for historical wait times by hovering over the line 9/5/2015 9/5/2015 Sept 5, 10:40AM If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh
SECURITY CHECKPOINT Wait time distribution shows the percent of travelers impacted by wait time windows If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh
SECURITY CHECKPOINT By having our sensors at each retailer, we can also correlate wait time impact to retail visit. This helps set benchmarks to reduce impact on retail visits If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh
WHERE PAX WALK KEY FACT Targeted advertising generates 2.7 times more revenue than non-targeted advertising Epinion Study May 2015 17 Presentation Title Confidential SITA 2015
CONCOURSE Using existing Wi-Fi and or our sensors, we can show the first locations visited by passengers. This often correlates with intent to purchase If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh Beginning Location 18 Queue Analyzer Confidential SITA 2015
CONCOURSE Using existing Wi-Fi and or our sensors, we can show cross shopping. Simply select the retail location and see the top locations where passengers come from and then where If they there go is from no difference the retailer from the previous 60 second wait time the same number is reflected on the new refresh Mid Location 19 Queue Analyzer Confidential SITA 2015
CONCOURSE Using existing Wi-Fi and or our sensors, we can show the last visit prior to departure If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh End Location 20 Queue Analyzer Confidential SITA 2015
CONCOURSE Departures Arrivals - Transfers Using existing Wi-Fi and or our sensors, we can show the top patterns for departures, arrivals, and transfers. We can also show patterns by airline using the AODB and ours sensors at If gates there is no difference from the previous 60 second wait time the same number is reflected on the new refresh 21 Queue Analyzer Confidential SITA 2015 End to End Location
CONCOURSE Deliver gate to gate transfer times to airline and airport applications to inform passengers who have connecting flights. Concourse Flow Traffic Visit Metrics Referral Metrics First Visited Gate to Gate Concourse Retail If there is no difference from the previous Cross Traffic 60 second wait time the same number is reflected on the new refresh Last Visited Gate to Gate Gate to Gate Times B Concourse Departure 22 Queue Analyzer Confidential SITA 2015
SYDNEY AUSTRALIA CISCO MSE INGESTION Example of Passenger Flow 44 Million Records over 28 days Departure Transfer If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh Arrival Total Airport
WHERE PAX VISIT KEY FACT The more you know about your footfall, the more income you can generate from your advertising space Epinion Study May 2015 24 Presentation Title Confidential SITA 2015
CONCOURSE First location visited most visited average dwell Using existing Wi-Fi and or our sensors, we also provide density and rank heatmaps by first visit, most visit, and average dwell. As well as our traffic patterns, we show by airline with our sensor at gates and mashups with If the there AODB is no difference from the previous 60 second wait time the same number is reflected on the new refresh 25 Queue Analyzer Confidential SITA 2015
CONCOURSE First location visited most visited average dwell We provide rankings by category for first visited, most visited, and average dwell by key categories If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh 26 Queue Analyzer Confidential SITA 2015
CONCOURSE Our footprint Heatmap shows saturation by airport and concourse providing empirical data for adjustable lease rates in advertising and retail rents. If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh 27 Queue Analyzer Confidential SITA 2015
28 Queue Analyzer Confidential SITA 2015 WHERE PASSENGERS ENGAGE
RETAIL The airport and the retailers have access to store draw rates enabling retailers to measure impact of marketing strategies and front of store promotions If along there with is no multi difference channel from the previous 60 second wait time the same number is reflected on the new refresh promotions. 29 Queue Analyzer Confidential SITA 2015
RETAIL Stores can plan peak staffing hours based on customer visits along with seeing the missed opportunities. The peak concourse traffic can often miss If align there with is no store difference visits and from this the previous 60 second wait time the same number is reflected on the new refresh informs the retailer when to leverage front of store promotions 30 Queue Analyzer Confidential SITA 2015
RETAIL Airport sublicense model to retailers Access to All Retailers If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh 31 Queue Analyzer Confidential SITA 2015
32 Queue Analyzer Confidential SITA 2015 BAGGAGE WAIT TIMES
BAGGAGE Leveraging AODB flight data, we can segment baggage wait times by airline leading to better ground crew efficiencies Baggage Carousel Average Wait Time If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh 33 Queue Analyzer Confidential SITA 2015
BAGGAGE Wait time distribution by airline provides impact to passengers by day and week If there is no difference from the previous 60 second wait time the same number is reflected on the new refresh 34 Queue Analyzer Confidential SITA 2015