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

Growth marketing has been all the rage, but what is it? Is it new age optimizers looking for a fancy title? Marketers spinning their services in a new way? A buzzword for a game of bingo? User lifecycle marketing? In this session, Krista walks you through what Growth Marketing is, why it's important, how it's different, how we can all do it, and most importantly, how measurement works for growth.

Digital channels offer organisations the ability to recognise customers and personalise experiences. What are the opportunities in personalisation? What are the risks associated with failing to deliver personalisation?

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.

The European digital marketing industry is inevitably shifting towards programmatic advertising, which poses difficult challenges for all involved parties – publishers, marketeers and analysts alike. As the technical infrastructure is getting more complex, it is increasingly difficult to properly collect, integrate and analyse the appropriate customer behavioral data sets, while those players who succeed first get a strong competitive advantage on the market. Luckily, it is not required anymore to employ a swarm of data engineers and data scientists to get started, as many of the critical business questions can be answered with relatively little effort using off-the-shelf tools.

Several companies see the need to be data-competent, however, there is a struggle in the implementation of analytics strategy due to various factors, including bureaucracy and the lack of organizational agility.

"In the midst of chaos, there is also opportunity". GDPR is coming and being prepared is not an option, it’s a requirement. Prolet will walk through the challenges presented by the new regulation for all of us, from in-company struggles to winning the battle with, and for the user.

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?

Can your mobile apps help you learn about yourself?

In this presentation, Daniel will talk about data visualization techniques to effectively uncover insights and communicate data. He will talk about charts best practices, types of visualization for different purposes, and some design principles.

Websites come in many types, styles, and budgets. Each website, be it a news site, an online store or a personal blog, has its own performance indicators. These may include the number of unique visitors, average order value, conversion rate etc. Web analytics systems are aimed to help track those indicators, analyze them and make decisions. But how you can trust them if the data collection process is screwed and data is scattered. During this speech, you'll get a checklist for your project that covers all the main mistakes in the project settings and analysis. Save your time and learn from the mistakes other teams have already made.

ROI isn’t a static line in the sand. Analytics guides our constant strive for improvements. How can we change the conversation about the ROI of analytics for it to become a foundation for decision making.

There are typically two issues that analysts (especially beginner and intermediate level) are faced with, when trying to extract actionable and useful insights out of their data. The first one - data is irrelevant. The second one - data is wrong.

If you work with a media agency (or are one) the first question to ask them is how many data scientists do you have? Do you prefer Amazon Web Services, Microsoft Azure, or the Google Cloud Platform? Come see examples from one of Canada's largest retailers of advertising spending that is wasted from poor targeting, access issues, and lack of big data understanding. We will also dive into examples of broken implementations of Analytics that cause even more issues. If you are not in-sourcing the core components of your Media and Analytics you are almost certainly at risk or already suffering from many of these problems. In this session, Martin and Charles Farina will show you what you need to find the right partner, but more importantly what you also have to provide.

With the abundance of data available in analytics we are no longer competing on the volume of data we have access to, but the quality of the questions we ask. The challenge is that we have never been taught to ask or taught other people to ask the right questions from analytics. So we spend our lives answering questions like "what is our bounce rate?" or "how much did the last campaign convert?" when we could be asking important and business critical question. This means that we in analytics have to consider putting the KPQ (Key Performance Question) before the KPI (Key Performance Indication) to start asking better questions.