WE SERVE YOU AROUND the WORLD “The First Rule of Any Technology Used in a Business Is That Automation Applied to an Efficient Operation Will Magnify the Efficiency

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WE SERVE YOU AROUND the WORLD “The First Rule of Any Technology Used in a Business Is That Automation Applied to an Efficient Operation Will Magnify the Efficiency 01 / WE SERVE YOU AROUND THE WORLD “The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.” – Bill Gates Changes in Latitude – Changes in Attitude https ://www.youtube.com/watch?v=QPx4EcanXLg …People are willing to buy more!! GLOBAL ANCILLARY REVENUES 2017 USD 82.2 Billion Expect $100+ BILLION in 2018 Source: The Amadeus Worldwide Estimate of Ancillary Revenue by Ideaworks Ancillary Revenue – Here to Stay Source: The Amadeus Worldwide Estimate of Ancillary Revenue by Ideaworks Ancillary Revenue – Where Does It Come From? Source: The Amadeus Worldwide Estimate of Ancillary Revenue by Ideaworks Traditional Sales Model Innovative Sales Model Airlines Must Adapt their Approach to Sales 01 / WE SERVE YOU AROUND THE WORLD Step 1 Know Your Customers Getting Data is Easy…Understanding Data is Hard • Airlines have a wealth of data available to them yet few know how to access it and even fewer still how to understand it • Data that is easily attainable: Bundled Airport Arrival Schedule Purchase Search History Packages Time O&D Trends Preference History (Hotel/Car) (Early/Late) Frequent Flyer Solo Traveler Checked On Board Travel Social Media Points or w/ Others Baggage Shopping Influencer Connectivity (Earned/Used) • United Airlines uses a predictive analytics system that collects and detects up to 150 different variables to make up a customer persona profile Give the Customer What THEY Want • Are you missing opportunities? Transit Airport Expedited Fare Rule Companies (Taxi, Restaurant Security/Immigra Overrides Uber, ETC.) Discounts tion for fee “Flight of the Lounge Access for Baggage Courier Airport Parking day” Coupon a day Services Redemption • Customer experience was identified by 61% of survey respondents as the top brand promise and the number 1 measure of customer loyalty* • Personalization drives customer loyalty ‒ Think back to our Amazon example ‒ A fully engaged customer will more likely become a loyal customer *Sabre/Forbes Insight Survey – Ascend Magazine, issue 2, 2017 Step 2 - The –IZATION Dilemma Customization versus Personalization …yet generated HALF of Carriers Total Revenue In 2015 a major US carrier reported… ATPCO WORKS AROUND THE WORLD 119 206 111 The ATPCO-powered Fares & Rules system contains 99% Over 99% of intermediated fares and over 87% of all 170m over 170 million airline fares, composed of over 122 fares in the world are filed and distributed with ATPCO million public fares and almost 48 million private fares THE GLOBAL MARKETPLACE IS EVOLVING The airline of 2035 will look much different than those we know today 2035 2016 7.2 billion 3.8 billion passengers passengers • The next generation of travel consumers will have grown up with technology much different than we did • Advanced technologies and process driven changes are a must Same Data Identifying Existing Opportunities Many airlines have valuable Different data already in use within their organization, but it is siloed. Goals Breaking down information silos, sharing data, and setting goals can be a place to start. Same Data, Different Goals • Identify and understand what data is available across various entities • Prioritize sharing this knowledge • Select goals for each department and the data needed to achieve them • What information do I need to have a holistic view of my customers? • Ownership under one entity • Master Data Management (MDM) Same Data, Different Goals Master Data Management (MDM) Data Quality Ensuring Data is Marrying Assigning accurate, up to different pieces ownership of date, and error of structured and data for free unstructured maintenance, data together to accessibility, Data Quality Data create master improvement view and MDM Data Integration Data enhancement of Data Governance Data related Data Data processes Governance Integration Same Data, Different Goals How can shopping data be used by each of the following entities? Distribution Sales and Revenue Customer Pricing and Marketing Management Experience Ecommerce Same Data, Different Goals: Sales • Online Sales/Offline Sales • Who could I be targeting that I am not? • When is the best time for tactical sales promos? • Alternatively, what is not working? • Bundled packages • What is the data telling me about how passengers shop? • Are there opportunities that I am missing to have initiatives that involve bundling? Is there a demand for it? Same Data, Different Goals: Marketing • Shopping data can be used within every day workflow • Can be used to • Identify locations that are popular • Marketing impacts after seeing where are they booking vs shopping • How in advance are they booking • Look to Book Ratio Same Data, Different Goals: Revenue Management • Shopping data can be incorporated into every day workflow • Dates that are in high demand • What people shop for and what they actually book • Last minute changes in demand Same Data, Different Goals: Pricing • Setting pricing strategy and using supporting data to leverage coding in ATPCO • Understand what is coded in ATPCO vs what actually sells • Fares put into ATPCO do not always sell • On average only about 5% of fares put into the marketplace actually sell • IE using shopping data to adjust advance purchase dates Same Data, Different Goals: Customer Experience • What customers look at vs what they actually book • Identifying customer purchasing behavior and finding patterns • INSERT Graphic from DJ email on African Passenger Behavior • Look for opportunities for personalization for customers • IE Business passengers receiving discount for baggage inefficient Schedules/Logistics ATPCO TYPES OF DATA Social Media Shopping And MORE! Types of Data • What data is available within Search Schedule the organization? History/Purchase O&D Trends Performance History • What data is not available? • Identify opportunities to acquire data from outside sources when Bundled needed Baggage Influencers Packages • How do I aggregate social (Hotel/Car) media data? Customer Frequent Flyer Social Media Behavior Trends Program Stats (IE Arrival Time) Types of Data • Structured Vs Unstructured Data Unstructured Structured Data Data Database Table Social Media • Data that resides in fixed • Blogs, tweets, comments, field within a record or file likes, followers, hashtags • IE FF Program Data such as videos, images name, address, FF number Types of Data: Historical Data • What are past trends and patterns in market behavior; commercial level • Routes • Markets • Cabin purchased • Opportunities for “Bundling” Types of Data: Ancillaries • Baggage • Food • Seat Selection • Legroom • Branded Fares Types of Data: Shopping Data • What do customers shop for vs what do they actually book? • When do they shop for it? • What kind of passengers make the purchase? Business? Leisure? • Look to book • Web Analytics Systems and Applications capture this data Types of Data: Sales Data • What sells? • What does not sell? • What is changing in the marketplace? • Are my competitors doing better or worse? • Traditionally this data resides within Sales, Revenue Management, Revenue Accounting Types of Data: Schedules/Routes • What sells based on schedule? • What does not? • Does something need to change based on data received? Types of Data: Social Media • What are my customers saying about me? • Are there videos, images that I can use? • Where can I get this data? • How do I analyze this data? Who can do this for me? Types of Data: Customer Data • What are past trends and patterns in customer behavior? • Connecting customer total spending data with the customers profile for personalization to identify predictive analytics opportunities • Segmenting by location demographics, past purchase behavior, and market behavior • Identifying similar customer profiles and capturing trends • Differences between personal travel or business for the same passenger • Frequent Flyer program data • Option to gather customer data and create profile Market Analysis ENTEBBE - BUJUMBURA Fares Filed Vs Sold Sold Fares Filed Fares Workflow Optimization How to optimize workflows to reduce time to market 03 / ATPCO NDC/NDC Exchange INNOVATION. Change is an opportunity as much as it is a challenge. At ATPCO, we get excited about reimagining the future of flight and the way people travel. DYNAMIC PRICING Routehappy by ATPCO We innovate through a deep understanding of the airline industry and the business needs of the ecosystem. NDC Exchange A community platform where Airlines and Sellers exchange Offers/Orders Real time Translations of different message formats Delivering reduced integration and maintenance costs Enabling faster speed-to-market NDC Use Cases ROUTEHAPPY BY ATPCO Offers That People Want To Buy FARES AND OPTIONAL RICH CONTENT HAPPY FLYER RULES SERVICES How they shop How they customize How they see it RICHER SHOPPING EXPERIENCES FOR CONSUMERS Dynamic Pricing What is Dynamic Pricing? Offer Management – Ability to dynamically control offers to customers based on current real-time market variables Five Defined Methods of Dynamic Pricing 1. More Frequent Fare Updates 2. Dynamic Availability 3. Dual RBD 4. Dynamic Pricing Engines 5. Dynamic Fare Generation • Will require substantial process changes and development of new industry standards driving much higher costs and extended timelines Dynamic Pricing Example: POINT 2 – Dynamic Availability Changes the RM availability of fare products based on characteristics
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