ACI-NA 2014 AIR SERVICE DATA SEMINAR

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1 2014 Mead & Hunt, Inc. ACI-NA 2014 AIR SERVICE DATA SEMINAR Ticketing & Booking Data: Advanced Session January 28, 2014

2 2 TOPICS The Process First Step: Booking Second Step: Ticketing Third Step: Settlement Fourth Step: Flight Now What? Using the Data Summary

3 THE PROCESS

4 4 DATA LIFE CYCLE Time Booked Ticketed Settled Flown MIDT TCN BSP/ASP Gov t Traditional ticketing process flows from the reservation to the actual flight

5 FIRST STEP: BOOKING

6 6 BOOKING Booking data yields Marketing Information Data Transfer/Tapes (MIDT) data No longer on tapes, referred to as Transfer MIDT captures nearly 60% of global bookings % fluctuates throughout the world Declining in the US since the early 2000 s Airline specific Some airlines have as much as 85% of bookings in MIDT Airlines such as Southwest are generally excluded from the data due to lack of participation in the Global Distribution Systems (GDS)

7 7 MIDT = GDS BOOKINGS Includes: Most Internet booking engines (e.g. Orbitz, Travelocity) Does not include: Direct connect relationships with online sites (e.g. AA pursuing Direct Connect with travel agents to reduce GDS costs) Direct connect includes city or airport ticket offices, airline websites, reservation centers Knowing which GDS has dominance can provide more bookings in a data purchase GDS Sabre Amadeus Worldspan Galileo Abacus Travel Sky Many Others Main Region North America Europe North America North America Asia Pacific Asia Pacific

8 8 MIDT BOOKINGS Reservation of a passenger s intent to fly Occurs before a ticket is sold Can be held, changed, or cancelled Available from many vendors Some estimate fare data based on fare classes Some calibrate the data Estimate missing data from direct sales Attempt to reflect the true market size Historical data availability varies by vendor

9 9 MIDT DATA AVAILABLE Data True itineraries: origin, destination, connect points Booking and travel month - future data available Marketing and operating airline Passenger counts Booking class of service Point of origin airport Travel agency postal codes Available a few weeks after the close of each month

10 10 MIDT STRENGTHS/WEAKNESSES Strengths Available from several vendors Near global coverage Published within weeks of the close of each month Available by travel month Some vendors offer future travel data Fare class categories Unrestricted use of international O&D data Weaknesses Costs can be high know what you want before you buy Fare data is not actual, and limited to fare class categories Does not reflect market size Includes phantom passengers whose bookings are never ticketed or flown Direct data sales not included Different vendors source different GDSs

11 SECOND STEP: TICKETING

12 12 TICKETING After purchase, a ticket is issued using an assigned fare and fare basis code Booking and ticketing are often done together, but not always Travel agents/airlines issue tickets Data from this step is generally not available/used

13 THIRD STEP: SETTLEMENT

14 14 SETTLEMENT Clearinghouses Exist to pass funds collected at travel agencies to the airlines Handle refunds and exchanges Yields Billing and Settlement Plan (BSP) data Run by International Air Transport Association (IATA) Yields Area Settlement Plan (ASP) data Run by Airline Reporting Corporation (ARC)

15 15 BSP CLEARINGHOUSE Designed to facilitate and simplify the selling, reporting, and remitting procedures of IATA agents Data and funds flow between travel agents and airlines Agents remit a single payment to BSP, covering sales made on all BSP-participating airlines BSP makes a single payment to each airline, covering sales made by all agents within a country/region Operates in more than 160 countries Over 65,000 travel agencies Almost 400 airlines - IATA membership not required Tickets issued through 30+ reservations systems

16 16 BSP DATA Majority of worldwide airline revenues are ticketed via IATA travel agencies and settled with the BSP system Tickets sold directly through airlines do NOT flow through BSP Airline websites Airline telephone reservations centers City or airport ticket offices Available a few weeks after the close of each month Data available back to January 2005

17 17 BSP DATA DIFFERENCES TO MIDT Included in BSP but not included in MIDT Average fares (subject to IATA masking rules due to no market competition) Point of sale data down to city name/zip code (not just travel agency zip code) Not included in BSP but is in MIDT Booking month Operating airline

18 18 BSP STRENGTHS/WEAKNESSES Strengths Includes tickets SOLD, not just booked Accounts for refunds and exchanges Contains ACTUAL fare information Different fare class categories Publishes data within weeks of close of month Available by travel month Unrestricted use of international O&D data Weaknesses Only available from IATA and its partners Does not reflect market size Direct data sales not included Biggest hole is world s largest market: U.S. IATA offers adjusted data IATA and ARC work together to combine data

19 19 ASP CLEARINGHOUSE Similar to IATA s BSP, but ARC handles the U.S. Began as part of the Air Transport Association (now Airlines for America) Since deregulation, U.S. carriers have owned ARC Every major U.S. carrier and railroad processes tickets through ASP Almost 200 participating carriers Nearly 16,000 travel agencies including online travel agencies Over 150 corporate travel departments

20 20 ASP DATA Tickets sold directly by airlines do NOT flow through ASP Airline websites Airline telephone reservations centers City or airport ticket offices ASP processes over 50% of airline tickets in the U.S., which is 20% of tickets worldwide Available Data Similar to BSP but also includes booking month and future data Updated daily - some products provide data in 5 business days Data available back to January 2008

21 21 ASP STRENGTHS/WEAKNESSES Strengths Publishes data quickly, within a week Includes tickets SOLD Available by travel DAY Contains ACTUAL fare data Fare class categories Unrestricted use of international O&D data Offers standard file specification for merging with BSP data Market Locator shows where travelers live Weaknesses Only available from ARC and its partners Partnership deals exist with IATA and Diio Only includes data sold in the U.S. ARC and IATA work together to combine data Does not reflect market size Direct data sales not included

22 FOURTH STEP: FLOWN

23 23 FOURTH STEP: FLIGHT Airlines collect flight coupons from travelers Process is becoming more electronic Airports and governments often require airlines to submit their flown ticket data Represents airline data used in origin and destination and onboard reports

24 NOW WHAT? USING THE DATA

25 25 TYPES OF ANALYSES Market monitoring Market shares Itinerary shares Seasonality Premium traffic splits Point of sale splits Diversion/Leakage Uses and potential issues Case Study: Fort Wayne

26 26 EXAMPLE: MARKET SHARE ANALYSIS 100% 90% 80% 70% 60% 50% 40% 30% ANALYSIS OF MARKET SHARE ONT-ORD Passenger trends help airports follow competition among airlines on a route. 20% 10% 0% AA DL UA US Source: ARC Market Locator CY 2012

27 27 EXAMPLE: ITINERARY SHARE ANALYSIS ITINERARY SHARE: ONT-ORD UA-Direct, OTHER-, 1.8% 6.7% UA-DEN, 6.4% UA-SFO, 8.5% DL-SLC, 9.6% UA-IAH, 10.5% AA-DFW, 17.9% US-PHX, 38.5% Current passenger routings can determine if your airport should target a new airline. US-PHX AA-DFW UA-IAH DL-SLC UA-SFO UA-DEN UA-Direct OTHER- Source: Diio Mi, CY 2012

28 28 EXAMPLE: SEASONALITY SEASONALITY OF MARKET ONT-ORD 12.0% 10.0% 8.0% 6.0% Looking at traffic figures by month shows market seasonality. 4.0% 2.0% 0.0% Source: ARC Market Locator CY 2012

29 29 EXAMPLE: PREMIUM TRAFFIC Business Class PDEW, San Diego to Tokyo Narita Nov 2010 to Nov %YOY! New JL Service Premium traffic makes airlines happy. New service can lead to increases in premium traffic Note: Source: Diio Mi FM internet-based aviation data portal

30 30 EXAMPLE: POINT OF SALE SPLIT Point of Sale Country Splits, BOS to NRT YE Nov 2013 US, 36% Other, 2% Ticketing data can show where people are buying tickets for a particular flight and can be vital for marketing purposes. Japan, 62% Source: Diio Mi FM internet-based aviation data portal

31 31 DIVERSION/LEAKAGE ANALYSES Virtually all airports experience diversion (i.e. leakage) Diversion to surrounding airports occurs for many reasons Pricing Schedule (frequency, nonstop destinations) Designed to estimate an airport s total market including diverting traffic from their catchment area Basis for identifying new opportunities and creating route forecasts Airlines do not typically analyze markets at this level

32 32 USES FOR LEAKAGE STUDIES Basis for pitching new airline service Most small hub and non-hub airports are too small to support new service with passengers currently flying out of the airport Assist in outreach to local travel agencies Targeting marketing & sales to specific areas

33 33 RISKS OF LEAKAGE ANALYSES Leakage studies are snapshots in time Can be done consecutively but trends are difficult to differentiate from noise Major markets with large sample sizes as well as macro-level should be primary focus Know the catchment area and potential hazards MIDT and travel agency data can be skewed by large national travel agencies Can lead to problems with the data

34 34 LEAKAGE STUDY: CATCHMENT AREA Geographic area, all things being equal, the population would use local airport for their air service needs Catchment area size can dramatically affect leakage Too large an area, leakage will be over-represented and overall market will appear larger than reality Too small an area, leakage will be under-represented and overall market will appear smaller than reality WHEN IN DOUBT, A SMALLER CATCHMENT AREA IS BETTER Do not give an airline a reason to reject the leakage data

35 35 LEAKAGE STUDY: TIME FRAME Every market is different Most markets should use the most recent data available ARC/MIDT data is available within weeks of previous month US DOT DB1B data is 4-6 months behind (3Q13 available) Seasonal markets (ski, beach, etc.) may have separate seasonal studies to demonstrate peak passenger demand Changes in service at local or competing airports can greatly impact leakage and should be taken into account

36 36 LEAKAGE STUDY: DETERMINING WHERE PEOPLE GO Multi-step process Booking/ticketing data used to calculate the % of passengers that fly out of the local airport (retention) Adjustments are made throughout the process for abnormal bookings, airlines not participating in MIDT/ARC, etc. Retention rates applied to the flown DOT DB1B data to calculate overall True Market Estimate Retention rates established and applied on a market-bymarket basis for domestic and international

37 37 CASE STUDY: FORT WAYNE, INDIANA Fort Wayne, Indiana (FWA) Small hub with approx. 280,000 enplanements Service to 5 major hubs on legacy carriers; 5 destinations on Allegiant Air Performed leakage study for calendar year 2012 ARC data with OTAs and Traditional Travel Agencies Approx. 100,000 records from the catchment area

38 SUMMARY

39 39 SUMMARY MIDT BSP ASP Contents Bookings Ticket Settlement Ticket Settlement GDS Coverage By Vendor 35 GDSs U.S. GDSs Direct Sales? No No No Coverage Worldwide All but USA USA Only Data Delay 3 Weeks 5 Weeks 1 Week Point of Sale? Yes Yes Yes Base Traffic? Yes Yes Yes Estimated True Market Size By Vendor By Vendor By Vendor Full Routing Detail Yes Yes Yes, with Rules Fare Categories? Yes Yes Yes Fare Detail Estimated by Fare Category Yes, with Masking Rules Yes, with Masking Rules

40 40 SUMMARY ASP, BSP, and MIDT all come with limitations Direct data sales not included ARC and IATA alone exclude the other s region Widely accepted and used by airlines Valuable in helping to analyze trends Data allows airports to build strong business cases to persuade airlines to act, using the same data sources as the airlines themselves

41 Thank You 2014 Mead & Hunt, Inc. Mead & Hunt, Inc.: Jeffrey Hartz Senior Consultant 959 Redcedar Way Coppell, Texas Phone:

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