This document outlines the 8 core drivers of gamification according to Octalysis framework: 1) Epic Meaning and Purpose, 2) Development and Accomplishment, 3) Empowerment of Creativity and Feedback, 4) Ownership and Possession, 5) Social Influence and Relatedness, 6) Scarcity and Impatience, 7) Unpredictability and Curiosity, 8) Loss and Avoidance. Each driver is then broken down into specific techniques that can be used when designing gamified systems. The document concludes by recommending some foundational books on game design.
The document discusses the history and development of the global distribution system (GDS) for airline travel reservations. It describes how in the past, making a single reservation across multiple airlines required 20 separate communications, which led to the creation of the first computerized reservation system called SABRE. SABRE and competing systems like Apollo automated reservations and helped airlines and travel agents distribute inventory and book flights more efficiently. This helped establish the oligopoly of major GDS providers that still exist today.
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This document outlines the 8 core drivers of gamification according to Octalysis framework: 1) Epic Meaning and Purpose, 2) Development and Accomplishment, 3) Empowerment of Creativity and Feedback, 4) Ownership and Possession, 5) Social Influence and Relatedness, 6) Scarcity and Impatience, 7) Unpredictability and Curiosity, 8) Loss and Avoidance. Each driver is then broken down into specific techniques that can be used when designing gamified systems. The document concludes by recommending some foundational books on game design.
The document discusses the history and development of the global distribution system (GDS) for airline travel reservations. It describes how in the past, making a single reservation across multiple airlines required 20 separate communications, which led to the creation of the first computerized reservation system called SABRE. SABRE and competing systems like Apollo automated reservations and helped airlines and travel agents distribute inventory and book flights more efficiently. This helped establish the oligopoly of major GDS providers that still exist today.
This document provides an introduction to travel technology, discussing key concepts like passenger name records (PNR), central reservation systems, codesharing versus interlining, married versus passive segments, and stopovers. It also covers the differences between direct bookings with airlines versus bookings through global distribution systems (GDS) like Sabre, and the rise of new distribution capability (NDC) standards. The goal is to explain fundamental industry terminology and technologies to understand how flights are booked and scheduled.
This document addresses frequently asked questions about subscriptions. It discusses trials versus paid subscriptions, the onboarding process, different billing plans and pricing, handling billing issues, cancellation reasons, and the importance of retention and patience for revenue growth from subscriptions over time. The key topics covered are trials, transactional versus subscription models, onboarding timing, comparing monthly and yearly plans based on conversion and renewal rates, addressing billing issues, learning from customer exits, and understanding the revenue dynamics of subscription businesses.
The document discusses various theories of innovation including Kondratiev's economic cycle theory and Schumpeter's theories on creative destruction, entrepreneurs vs capitalists. It then discusses Gartner's Hype Cycle and issues with mathematical proofs. The rest of the document covers theories around consumers, competitors, and value networks as drivers of innovation. It suggests incumbents protect profitable customers, competitors' strengths can also be weaknesses, and disruptors should build new value networks. Signals of change include customer groups like non-consumers who lack access/ability and overshot customers who stop paying for improvements. The document also defines resources, processes, values, and value networks in the context of analyzing competitors. It considers when integration or modularization is
The document contains lessons learned from Bayram Annakov's experience as an entrepreneur and CEO. It discusses the importance of teams over solitude, taking a systems view with feedback loops rather than isolated challenges, and questioning assumptions rather than just reading business books. Key recommendations include reading works by Drucker, Meadows, Christensen, and Horowitz to gain strategic insights about management, systems thinking, disruption, and leading change. Feedback and changing motivations over time are also highlighted as important lessons.
This document discusses theories of innovation and signals of change in industries. It summarizes that consumers may be overshooting their device needs or may lack access to certain services. Incumbents tend to protect profitable customers while competitors assess strengths, processes, and values. Disruptors should build new value networks rather than compete directly. The document identifies customer groups, and defines resources, processes, and values that competitors analyze for signals of change. Modularization may be best when performance exceeds needs, while integration maximizes technology.
US Airlines History outlines the development of the commercial airline industry in the United States over several parts:
Part 1 discusses the early history including the Wright brothers' first flight in 1903, the growth of air mail services in the 1920s-1930s which led to the establishment of the first major airlines like United, Eastern, and Pan Am.
Part 2 covers the introduction of government regulation of the industry through the establishment of the Civil Aeronautics Board (CAB) to regulate fares and entry/exit to routes.
Part 3 notes the transition to jet aircraft in the 1950s with planes like the Boeing 707 and the start of non-stop transcontinental flights, but also the issue of half
This document provides 7 lessons for life in a startup. The lessons are: 1) Go fullstack and learn all aspects of the business, 2) Build a minimum viable product and iterate quickly, 3) Establish clear boundaries for responsibilities and work-life balance, 4) Ask "why" to understand motivations and goals, 5) Focus on key processes that move the business forward, 6) Promote transparency in operations and decision making, 7) Gather feedback frequently to support ongoing improvement. The overall message is that startups require flexibility, constant learning, and an MVP mindset to succeed.
This document provides an overview of machine learning concepts and processes. It discusses types of machine learning including supervised learning (classification and regression), unsupervised learning (clustering), and reinforcement learning. It also outlines the typical machine learning process of data collection/preparation, modeling, training models, evaluating results, and improving models. Specific examples discussed include using machine learning for email marketing conversion prediction, rhythmic gymnastics image classification, and recommendation systems.
Neural networks are machine learning models inspired by the human brain. The document discusses neural network architectures like perceptrons and multi-layered deep neural networks. It also covers common neural network techniques for images like convolution and pooling layers used in convolutional neural networks (CNNs). Finally, it provides code examples for using neural networks in Python with the Keras library on image datasets like MNIST and examples of loading pre-trained models like ResNet50 and VGG16 to classify images.
This document introduces machine learning concepts including supervised and unsupervised learning. It discusses preparing data for machine learning by techniques like one-hot encoding, scaling, principal component analysis (PCA), and bag-of-words representations. Code examples are provided to classify cancer data using k-nearest neighbors, cluster data with k-means, reduce dimensions with PCA, and vectorize text with bag-of-words. Finally, potential machine learning exercises are outlined like predicting user purchases, finding user clusters, and regression problems.
Flight to 1000000 users - Lviv IT Arena 2016Empatika
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1) The document discusses the growth of an app from its initial launch to reaching 1,000,000 users. It tracks key metrics like active users and downloads over time.
2) Several lessons are presented on factors that are important for an app's growth, such as focusing on retention of existing users, cultivating relationships with influencers, having a strong team, understanding the relevant industry, and implementing feedback loops to continuously improve the app.
3) The final lesson encourages thinking big about an app's potential by considering frequency of use, retention, partnerships, team strengths, industry opportunities, and implementing a long term vision.
Artificial intelligence has progressed from early attempts at pattern recognition to applications that can solve practical problems. The history of AI includes periods of inflated expectations followed by disillusionment as capabilities fell short of hype. Current key players developing AI include Google, Microsoft, Amazon, and IBM, though capabilities are still limited compared to human intuition. The document recommends books on AI topics and requests donations to AI research funds.
This document discusses travel inequality and why some travel startups fail. It notes that according to research, most people only travel 1-2 times per year, while a small percentage of frequent travelers are responsible for a large portion of airline revenue. The document advocates that for startups to be successful, their business models and retention tactics need to target different types of travelers based on frequency, from one-time users to frequent travelers who subscribe. It provides a framework for matching business models and retention strategies to types of travelers based on their trip frequency.
App in the Air Travel Hack Moscow - Fall, 2015Empatika
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This document provides information about the App in the Air platform for creating travel-related widgets and apps. Key points:
- Widgets must be contextual and trip-based, and can be monetized through PayPal, in-app purchases, or billing. Native SDKs are available for iOS, Android, and Windows.
- The company has won awards including an Amadeus hackathon and PayPal WorldHack and placed in Yandex and Salesforce hackathons.
- It provides guidelines, technical support, and SDKs through GitHub for building travel apps and widgets using partner APIs during a hackathon. Criteria for submissions include the app working, having travel value, and including a demo
This document discusses the key responsibilities of a product manager including determining what features to include in a product, prioritizing features, and deciding when to release the product. It provides two brief stories as examples and includes quotes emphasizing the importance of avoiding premature optimization and gaining development experience. The document concludes by mentioning performing feature audits.
This document provides an overview of several topics related to exponential technologies including exponentials, disruptive innovation processes, solar energy, bioinformatics, artificial intelligence, and their potential impacts. It discusses concepts like digitization, disruption, demonetization, and democratization. It summarizes emerging technologies like DNA sequencing with MinION, synthetic biology, biohacking, and their implications. It also outlines what artificial intelligence is, some of its applications and implications, and recommendations around utilizing publicly available AI tools and platforms.
Singularity University Executive Program - Day 1Empatika
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This document provides summaries of presentations from Day 1 of the SingularityU Executive Program covering various topics:
1. Networks, computing, and sensors were discussed including exponential growth in computing power and connectivity through technologies like Google Loon and Facebook Drones.
2. Software and hardware trends were examined along with emerging devices like smart contact lenses and augmented reality headsets. Ambient intelligence through cheaper sensors and networks was also covered.
3. Applications of artificial intelligence included pattern recognition, deep learning models, and the current capabilities and limitations of AI. Key areas like verification, validation, security and control were identified.
4. Other talks explored forecasting methodology, digital biology advances in DNA sequencing and editing technologies,