Speakers.

The third installment of the highly successful series and another New York Times bestseller, Think Like A Freak is Levitt and Dubner’s latest—and most revolutionary—book. Taking their successful Freakonomics ideas to the next level, Levitt and Dubner offer an engaging and innovative new program sure to inspire and enlighten audiences. Each idea presented by Levitt and Dubner will be illustrated by a story or example, in their ever-popular counterintuitive style, that will provide your audience with illuminating thoughts for profitable thinking. With their trademark blend of captivating storytelling and unconventional analysis, they take us inside their thought process and teach us all to think a bit more productively, more creatively, more rationally—to think, that is, like a Freak.

Salesforce is the global leader in customer relationship management (CRM), helping companies connect with their customers in a whole new way. Founded in 1999, Salesforce enables companies of every size and industry to take advantage of powerful Fourth Industrial Revolution technologies—cloud, mobile, social, internet of things, and artificial intelligence—to get closer to their customers. This revolution promises an incredible wave of innovation and technology that will radically transform our economies, our societies and our daily lives. Of these technologies, Artificial Intelligence (AI) has the potential to be the key component to revolutionize the way we support businesses, including media and communications companies and how they analyze their business to support their customers and guests. AI solutions at Salesforce promise to make companies ever more productive by augmenting the decisions they make with relevant information. But in practice, how can you deliver algorithmic insights at scale for your business at the moment of action? Join this session to see some real-world examples of data and analytics intelligence in action in the media and communications industry and see how you can optimize Sales, Service , Marketing and Operations with Salesforce Analytics.

Create deeper guest experiences, operational excellence, and digital transformation by connecting man and machine.

MicroStrategy 10.11 is here. With the latest release, users can build, deploy and consume transformative analytic content and mobile applications with speed and at scale. See how the latest innovations drive insight by tapping into enhanced mapping capabilities, Artificial Intelligence, Augmented Realty, Natural Language Processing and Generation, new out-ofthe- box visualizations, and governed self-service. Organizations now have more ways to deliver insights to any device, and can accelerate their journey to the Intelligent Enterprise.

Data is being created and streamed faster than ever and consumed by more people (and algorithms) than legacy technology can support. Subsidiaries and partners -like Nielsenhave their own data that could add context to internal data, if combined. The new consumer streaming division adds complexity as content and data from many sources is brought into one division. Attend this session to see a how to create a new analytics circle of life. Hear from Snowflake CEO Bob Muglia as he describes the journey of maturity that data takes from creation to consumption. Hear how to take the noise out of disparate data so you can share data insights in perfect harmony with all the living things in the analytics jungle. You’ll leave with a path forward to no (data) worries for the rest of your days.

Neural networks are machine learning models inspired by the human brain that have been around since the 1960s. But over the past 10 - 15 years they’ve been made “deep” and yielded significant advances in our ability to solve very hard problems. For example, Alpha Go learned to beat the best human players by playing against itself, and deep neural networks can find cancer in radiology images as well as highly trained radiologists. In this talk we’ll do three things: introduce the core concepts of neural networks, deep learning, and an extension called deep reinforcement learning for control problems (Alpha Go is such a system); discuss applications of these methods that are yielding significant value in industrial settings; and show a concrete application to cybersecurity for rides inside theme parks.

Cheri and Jess will be joined by Tableau experts to demonstrate cool new capabilities in the latest release of Tableau and a peek into what’s coming. The Tableau team will show you how to make an impact with your data and explore some best practices and tips & tricks to add to your Tableau arsenal.

Many of your customers are walking around broadcasting who they are and where they are for anyone willing to listen. Come hear how SAS, Cisco and Intel can help you use that data to engage customers and create richer relationships. With the advent of passive location services through Cisco wireless platforms, you can use this data to fill in the gaps and create a complete a 360-degree view of each customer. We’ll explore how to tie together both online and offline data, as well as physical presence and movement data, to feed real-time analytics powered by Intel.

Modern marketing is built on the ability to collect, understand, and thoughtfully act on reliable, in-the-moment customer data—and it’s that data that supports the relevant, personalized experiences that customers crave. Marissa Aydlett (Braze SVP of Marketing) and Jon Hyman (Braze cofounder and CTO) will take a look at the innovative, data-driven approaches being taken by forward-looking organizations, and explore how pairing nuanced customer data and creative thinking with innovative technologies makes it possible to provide powerfully engaging, highly personalized brand experiences that keep customers coming back.

Entertainment industry desires to push their boundaries to deliver indelible seamless experiences to guests in the Experience Era. As enterprises plan for customer experience first, the need for curated data, holistic views of customers, intelligent services, and APIs have become paramount. Join John Mellor, Vice President of Strategy & Business Operations Digital Experience at Adobe, as he shares the art of the possible for the industry overall by activating relevant and compelling experiences in real-time with fast data, AI and Machine Learning.

Join Adam Savage as he shares his tales of adventure exploring the research savannah. Having built everything from Buddhas to futuristic weapons, fine-art sculptures to dancing vegetables, Adam Savage has spent his life gathering information, data and skills to take what’s in his brain and make it real….with sometimes explosive results. Unorthodox, engaging and not to be missed, this presentation is sure to make you roar with excitement as Adam takes you on his journey into obsession.

Can computer vision really deliver operational outcomes? Join us and David Bencs, the head of player analytics for the Orlando Magic, to learn more about it. A panel of AI and ML experts will take you through a 5-D experience on how basketball teams, media, insurance, and retailers are applying vision analytics to deliver operational outcomes such as enhancing customer experience, reducing forecast error, and winning basketball games.

AI and digital technologies enable organizations to interact with customers and offer personalized products and experiences in increasingly sophisticated ways. But such technologies often confront a “last mile problem”: targeting the right product or service to the right customer at the right time does not guarantee adoption or customer satisfaction. A major insight of behavioral economics is that offering people the right choices is not enough. The way choices are arranged, framed, and communicated can also have disproportionate impacts on customers’ perceptions and behaviors. Small tweaks to choice environments – in both the physical and digital worlds – can therefore yield disproportionate benefits. This talk will sketch the core principles of behavioral economics and choice architecture, and give numerous examples of choice architecture in action. Behavioral economics can be viewed as a scientific approach to improved customer engagement and experiences; it is the ‘missing link’ that enables data analytic and digital technologies to live up to their transformative potential for innovation and more profitable customer relationships.

Building muscles takes practice. Practice confidence building. How confident are you that your authentic self is showing up to work everyday? Do you trust your own skills? Can you stand tall in a group of power women or men with your head held high? What is noteworthy about you and adds distinct value to those that work with you? Answering these questions elevates your status in your own mind and leads to a shift in the confidence you project, and the way that others will see you. With over 22 years of professional experience, Tiffani Bova will share her personal journey to find the ultimate in career success and personal fulfillment including exercising your “confidence muscle” and building a “symphony of support,” which will inspire and delight women at every stage in their career.

Data has fundamentally transformed customer experience. The best companies have reinvented their operations by making them data-centric, underpinning physical experience with data enablement to better know, serve, and delight their guests.
Bel, makers of the iconic Babybel and The Laughing Cow cheeses, is on a journey to redefine their product experience with data at the core. bel is setting its sights on learning from and adopting a page from the playbooks of the world’s most magical and datadisciplined brands: how can a company with limited data and an intermediated distribution chain create a direct connection with its customers using data?
Join a fireside chat with Dan Waters, Global CMO of bel brands and Julie Fleischer, VP Marketing at Neustar on how all brands have the opportunity to better leverage customer data in order to win the ever-demanding modern customer. Find out how Neustar and Bel are leveraging consumer information to build a customer data set that will power its analytics and experiences alike.

Digital and the growth of direct to consumer has transformed the ways in which guests experience brands, whether in parks, cruise ships, websites, mobile apps or through streaming content. Guest expectations are higher than ever before and companies may not get a second chance when they fail to meet expectations.
A key to keeping up with and exceeding guest expectations is connecting your data into a complete view of the guest to see not only where they have been, what they have done, what they are doing right now (in real-time) as well as predicting what they will do next.
Joe Colletti, General Manager of Teradata’s Customer Journey practice, will describe how Teradata is enabling the power of analytics through connected data to enhance guest experience. He will share real world examples of applying innovative analytics to drive guest engagement, improve guest experience and increase returning guest visits.

Measurement and attribution are critically important for marketers today. The road to marketing relevance and exceptional guest experience demands that brands unify their marketing ecosystem and break down data barriers for closed-loop, incremental measurement. However, the fragmentation of technologies and platforms introduces a variety of measurement complexities.
A successful omnichannel marketing strategy requires the ability to measure media impact on driving cross channel interactions - only achievable by leveraging both digital and offline data. In this session you will learn how to:
- Establish the foundation of a unified marketing ecosystem through Ingestion & Validation of Data, Identity Resolution, Anonymization, and Privacy & Security Regulations
- Overcome obstacles with fragmented and incomplete data across online and offline using analytics
- Translate cross channel campaign insights into actionable results with example use cases

Change in the retail industry has been accelerated by new competitors and the massive global digital transformation of the last few years. The use of technology to understand the rapidly shifting attitudes and sentiments of highly informed buyers, whose changing preferences for web and mobile reverberate across the industry. The success of technology-savvy, aggressive and ‘think-big’ start-ups and especially Amazon is also putting pressure on more traditional retailers to come up with new answers. The pressure traditional retailers face is how to utilize their own data to increase conversion rates and revenue by understanding behavior to find new ways to increase foot traffic or identify innovative new channels via mobile, web, social media and using ad tech. Big Data Analytics and now increasingly Machine and Deep Learning are all being used in understanding the consumer in order to get more goods ‘into the basket’ and to the consumer quicker.

The MarTech landscape is changing, its constant. We are seeing the emergence of CDPs, a more dominant positioning of AI and decision management, and platforms that enable connectivity across the entire consumer experience. These capabilities are being deployed in cloud based environments that promote marketing agility through high velocity adaption. Organizations must come to terms with the role of these capabilities and rationalize these into their suite of MarTech capabilities. They must also understand the implications to the organization.

Brand advertisers know: it’s no small task to hone in on highly-individualized and nuanced consumer desires. Tougher still: finding and connecting with those individuals in the right moments and environments with the right message. And yet in the digital era of dwindling attention spans, relevance and context have never been more critical for brand advertisers to nail.
Further complicating things: today’s rapidly-evolving digital advertising ecosystem — marked by campaign automation, programmatic buying and a vastly broadened breadth of channels where content is published and consumed. For brands, a convoluted landscape has made controlling the where, when and how of messaging feel all the more tenuous at a time when where ads run matters just as much as where they don’t. How can you remain on the cutting edge (leveraging data and programmatic efficiencies) while ensuring the health and protection of your brand?
During this session, Oracle Data Cloud SVP and Co-founder of Moat, Jonah Goodhart, investigates effective, brand-safe reach for today’s marketers. He’ll explore leveraging measurement to inform creative decisioning and media buying, underscoring what data can do for your brand in the age of the consumer.

This presentation offers a brief glimpse into the insights that are derived from consumer research that adopts a cultural lens. The session will briefly summarize how culturally based qualitative consumer research differs from traditional quantitative research and will then detail some of the insights that have been learned from this type of research. For example, I will discuss why we don’t really choose which university we go to, even though we think we do; why how people plan when they have their first child is more important than what they actually plan to do; and what impact our consumption choices have, ranging from the mundane (e.g., signing a kid up for soccer) to the less common (e.g., outsourcing teaching your child to ride a bike), on purchase behavior and consumer well-being.

Insights that can help make better business decisions can come from anywhere. ESPN recognized the opportunity that public social data provided to enhance their current portfolio of research methods and dove in. Last year ESPN set out on a journey to build a social intelligence strategy and acquire capabilities to provide timely and holistic insights for the business from social data. Join Kevin and Ian as they share details around the creation of this team, who and how they support their business partners, current projects and where they’re heading. They’ll outline use cases across key business partners including Marketing, Ad Sales, Affiliate Strategy, Communications, and Content. There’s no lack of conversation around the Worldwide Leader in Sports and separating the signal from the noise has enabled ESPN to understand their fans reaction in a more timely and actionable way allowing them to better serve the fan anytime, anywhere.

In this session, Steve will provide an overview of AI and how it relates to the analytics frameworks used in business. He will provide real world case studies on how businesses in different industries are using supervised, unsupervised, and reinforcement learning today. He will highlight key challenges in the field and dispel some common myths.

"Once the computers got control, we might never get it back.... If we’re lucky, they might decide to keep us as pets.” --Life Magazine
The latest buzz words in data science are artificial intelligence. This is mostly due to the remarkable success of machine learning methods collectively known as “deep learning.” With deep learning, cars can recognize pedestrians and motorists, Alexa can interpret your speech, and Google can create translations in 100 different languages. But with almost all “hot” technologies, there is a risk that hype and expectations can outpace capabilities. To help parse the hype from the reality, this presentation will describe what deep learning is, where it works, and where it doesn’t, so you’ll know when the AI apocalypse will arrive at your doorstep. (Spoiler alert: not in your lifetime.)

Competitive advantage in business today requires maximizing the value of a firm’s data. Leaders from a variety of technical and non-technical backgrounds today are held accountable for decisions in everything from data infrastructure and cybersecurity to machine algorithms and artificial intelligence. Driving value with data requires connecting a technical understanding of how data can be utilized to a business strategy resulting in a decision making culture capable of successfully putting data to work. We will discuss data from the leadership perspective, from the principles of talent management and org design, to culture, data literacy and ascending the analytics curve.

Understanding dynamics of pedestrian movement is essential for planning and operating publically accessible spaces such as building interiors or parks. Psychologically, pedestrian movement can be addressed as spatial decision making. A key challenge is the scarcity of data about individual behaviors and emergent crowd phenomena. We employ a combination of methods: real world- experiments with individual volunteers in densely populated spaces such as airports and shopping malls, using mobile physiological trackers and eye-tracking to capture decision making, path choice, emotions and visual attention. Our Zurich lab allows for 36 individuals to engage in desktop Virtual Reality experiments simultaneously, in evacuation scenarios and collaborative vs. competitive treasure hunt games. We currently move to real-time online multi-player interaction with larger humancontrolled crowds and agent-based simulations. This is integrated into a model of patron decision making in a virtual theme park, tackling individual and crowd level dynamics, with real-world, VR and synthetic data.

In today’s technology-first and media-driven marketplace, marketers frequently pivot between feeling excited about burgeoning possibilities and overwhelmed by increasing complexity. Asked to build power brands, engaging experiences and personalized messaging, the modern-day marketer needs a robust and holistic view of consumers to understand what they do, why they do it, and how to efficiently reach them. You’ll see how research is enriched with category, media and digital behavior to sharpen targeting and to fuel movie purchasing for Marvel and Star Wars.

How do you scale a scheduling improvement for a small set of stores to all merchandise deliveries at Disney World? The answer lies in optimization! To borrow a tune from the Notorious B.I.G.:

Disney, Disney, Disney, can't you see? Delivery's in need of optimizing Constraints are set, limit the days Prevent excess OT from being paid.

We will walk you through an application of optimization modeling principles to Disney's merchandise warehouse deliveries. This example will follow the progress of the project from proof-of-concept heuristics to a cost-based model that accounts for warehouse labor rules. We will discuss the business reasons behind the development of the input data set, objective function, and constraints, as well as how those parameters evolved over time. Come for the story of a project all about working smarter, not harder, but stay for the broadly applicable lessons on how to apply optimization to real-world problems!

There is a lot of fairy dust swirling about a new technological innovation called blockchain that has many companies and industries racing to understand how it might improve the way they do business. But this disruptive digital innovation comes with a lot of complexities, hype, and misinformation. So what exactly is a blockchain? And how is it disrupting industries all across the globe? And what is going on with all of the cryptocurrencies that are the forefront of the media coverage of blockchain? Are there real world applications for this new technology? How does it affect marketing and analytics? These are just some of the many questions surrounding blockchain and its current state. This presentation aims to demystify what blockchain is, how companies and industries are currently using and innovating on the blockchain, and what the future might hold for this break-through technology in marketing, analytics, and beyond.

15 years ago, Blockbuster attempted a hostile takeover of its main brick-and-mortar competitor, Hollywood Video. Now, neither of these companies exist. We instead choose to receive our media from innovators like Netflix and Redbox. History is filled with victors who, instead of playing the game, changed the rules of the game by utilizing innovation. What is the common thread among these disruptive innovations? How can we utilize disruptive innovations to improve our work? In this talk, we will examine the stories of Blockbuster and Netflix, explore the common themes of innovation, and extract strategies for adapting and benefiting from a changing landscape both in life and in the workplace.