Just get on the plane and let us bring you into a week of pure digital analytics. We will shuttle you straight from the airport to the conference venue where your days will be filled with seminars and events that SUPERWEEK has become synonymous with.
Matt Gershoff / Conductrics - New York, USA
Machine learning can be thought of as sitting at the intersection of computer science and statistics. "Computer Science has focused primarily on how to manually program computers, Machine Learning focuses on the question of how to get computers to program themselves ..." – Tom Mitchel
For many tasks, it makes relatively little difference if these programs are opaque to human introspection. We are almost exclusively concerned with performance for some task ("is this a cat?"; Donkey Kong, etc.). Here, high capacity models, like deep learning, suffer little penalty for marginal increases in representational complexity.
However, for several reasons, marketers tend to be wary about ceding control of their customers’ experiences to black box methods. Firstly, they need assurances that they can trust automation to make reasonable decisions over a large space of possible environments. Secondly, companies often have internal and legal regulatory requirements around the how, and which, data may be used for making marketing decisions. With the EU’s GDPR coming into effect in May 2018, this will be even more of a concern.
We will cover, at a conceptual level, simple linear models, decision trees, and deep learning. I will argue, that while lacking the expressiveness, or capacity, of more complex representations, linear models and decision trees have many appealing properties for the marketing use cases:
Human readable: for any given input, a human can easily determine the output.
Auditable: for regulatory review and approval before use.
Loggable: because each decision node in each decision tree can be uniquely identified, it is possible to register, and retain a history of what policy, or rule, was used for every decision event. This is particularly useful for significant decisions as defined by Article 22 of the GDPR.
Krista Seiden / Google Analytics - San Francisco, USA
Tim Wilson / Analytics Demystified - Dublin (OH), USA
The data available to marketers -- literally at their fingertips by way of a few mouse clicks -- has exploded over the last decade. Yet, while there is more data -- and it is more accessible -- than it has ever been, the way we think about and use data has hardly evolved at all. With the recent advances in cloud computing and processing power, the industry is abuzz with talk of machine learning and artificial intelligence. How, then, will we get from the world of Microsoft Excel (or Tableau) to a world where "the machines" are automatically and dynamically optimizing all aspects of our marketing?
In this presentation, Tim will make the case that simply "waiting for the magical black box to arrive" is a risky strategy and that, rather, marketers and analysts should dive into (the shallow end of) the data mining and statistical analysis pool to not only get greater value from their data now, but to set themselves up for the machine-driving marketing of future.
Jim Sterne / Digital Analytics Association - Santa Barbara, USA
AI and Machine Learning will become an integral part of your marketing analytics life so before Matt Gershoff explains how it works, Jim walks you through what it is and how it is being used. From natural language processing and computer vision to chatbots and robots, you'll see how AI is applied to customer interaction. Then, Jim dives into machine learning so you can determine which software services are worth your time, communicate better with the data scientists in your company, decide to become one yourself, and figure out how and where to bring AI and ML into your marketing tool suite.
Daniel Waisberg / Google - London, UK
In this presentation, Daniel will talk about data visualization techniques to effectively uncover and communicate insights. We will discuss advanced concepts on how to tell a data story and make more informed business decisions.
Julien Coquet / Hub'Scan - Montélimar, France
Join renowned expert Julien Coquet around the fireplace as he takes the role an a digital analytics Gordon Ramsey.
Like most digital marketing projects, digital analytics projects suffer from a lack of vision and planning. This leads to poorly executed projects that yield poor results. Sometimes, analytics become a concern after a new manager arrives, only to discover how bad things turned out! Julien will share stories about the worse analytics situations he ever encountered - along with simple yet effective solutions to these problems.
EVENING BONFIRES, MULLED WINE
Caleb Whitmore / Analytics Pros - Seattle, USA
Tahir Fayyaz / Google Cloud - London, UK
Sam Briesemeister / Samsung Digital Services Research - Seattle, USA
Cloud computing has rapidly become a priority for many organizations, as their software lifecycle accelerates and needs for scalability and reliability increase. Many enterprises choose Kubernetes, an open-source software service platform with major investment from Google, Microsoft, and others, to support resilient cloud-agnostic applications. As firms invest in more behind-the-scenes automation, integrating offline business process data into analytics becomes increasingly valuable.
Sam will demonstrate (and share code!) for deploying in-house analytics services into Kubernetes, and integrating Kubernetes back-end application logs into Google Analytics, BigQuery, and other analytics solutions.
Mariia Bocheva / OWOX - Kiev, Ukraine
Mark Edmondson & Tor Christensen / IIH Nordic - Copenhagen, Denmark
Aurélie Pols / Mind Your Privacy - Madrid, Spain
Moe Kiss, Michael Helbling, Tim Wilson + guests
EVENING BONFIRES AND WHISKY TASTINGS
Viktor Tarnavsky / Yandex Metrica - Moscow, Russia
Martijn Scheybeler / Postmates - San Francisco, USA
Moe Kiss / The Iconic - Sydney, Australia
Moe shares the most valuable analytical technique she learned from her time in government – ACH. Often, confirmation bias (the tendency to interpret new evidence as confirmation of one’s existing beliefs) railroads an analyst’s findings. ACH draws on scientific methodology, cognitive psychology and decision analysis to avoid this analytical trap. The strength of ACH is that it is difficult for an analyst’s natural biases to influence the outcome of their analysis. Moe teaches how to build your own hypotheses matrix and set up to disprove hypotheses using a case study. And yes, she’s applying ACH to her work at THE ICONIC, Australia & New Zealand’s largest online retailer.
Jeff Sauer / Jeffalytics - Planet Earth
Steen Rasmussen / IIH Nordic - Copenhagen, Denmark
Demonstrate any digital analytics solution or method of your own that is way beyond the defaults. Who decides who's gonna win? The audience. Send your nomination to firstname.lastname@example.org!
Doug Hall / ConversionWorks - London, UK
EVENING BONFIRES AND WHISKY TASTINGS
Damion Brown / Data Runs Deep - Melbourne, Australia
From Plato to Alain De Boton, philosophers have been the people tasked with finding truth, and bringing it to the masses. To a web analyst, that pursuit of truth should sound familiar: it's the job of web analytics to shine a light in the corners that reveal truth about human behaviour. In this fun and informative talk, Damion looks at how the history of philosophy has parallels with analytics best practice, and along the way ponders on whether the Digital Analytics industry might just have found an incredibly rare thing that nobody thought existed: an actual use for a philosophy graduate.
Charles Farina / Analytics Pros - Seattle, USA
Rob McLaughlin / SKY - London, UK
Kristoffer Ewald / MetaPeople Group - Switzerland
PANEL DISCUSSIONS on everything hot
Superweek is held on a beautiful moutaintop, in the highest-lying 4-star hotel in Hungary, the Hunguest Grandhotel Galya. You can take the conference’s shuttle bus service available several times a day from the airport and downtown Budapest to the mountaintop at a return price of €80 (+ VAT).
Need assistance or completing via standard wire / bank transfer / Transferwise? Let us help you at email@example.com!
Not sure yet about the attendee names or dates to visit? No problem - you can just book a room or daily tickets contingent to be specified later (e.g.: some 6 nights and 6 days contingent may be used for 2 people, each staying for 3 days and nights or for 5 people, 4 staying for a single day with someone staying for 2 and so on).
Door-to-door airport shuttle is a full, round trip service to and from the conference venue with a minimized waiting time taking your flight schedule into account.
Prices displayed at the Eventbee checkout process below will include all fees and taxes (27% VAT for tickets and transfers, 18% VAT for accommodations) which are subject to refund by your domestic Tax Office inside the EU.
Nights of 27th / 28th January (Saturday, Sunday) and 2nd / 3rd February (Friday, Saturday) are also available.
Please find options for accommodation in shared double room (€100 + €18 VAT), single room upgrade (€80 + €14.4 VAT / night), door-to-door airport or Budapest downtown return transfer (€80 + €21.6 VAT), special food or late check-out (€40 + €7.2 VAT) also before checking out.
Prices are valid by Tuesday, 3rd October.