Omni-channel is not a new hype, it's the norm. We have access to omni-channel analytics, omni-channel communication and automation tools. Now we connect that and visualize this connection. Segmentation is needed, not only for people, but for marketing automation.

Marketing attribution is a buzzword that has everyone the paid advertising community talking. But what does it mean for you? Is it really a magic bullet, or is attribution just a bunch of bullshit? This talk goes through the need for attribution, shares practical applications and technologies, and ends with a framework for you to get started.

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.

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.

With BigQuery business and organisations have a unique chance of taking there analytics data and start the transformation towards a data lake. By combining customer, analytics, marketing and CRM data here we not only get a repository where can have room to add or work with data as we see fit, we also open up for the opportunity to use machine learning to actually sift through our data to help determine the causality and relationship between the individual data points. This way we use the full power of data to define our segments and profiles based on their actual behavior and not our prejudice.

All attribution models are wrong, but some are useful. Except for Data Driven Attribution models of course which just might be right. Correct? Or not? Peter wants to reframe the discussion so it is not about attribution models but about techniques for optimising your marketing spend. He will talk about why the technique of attribution is wrong and where to invest your time/resources instead.

The increasing complexity of digital landscape on one side and huge business expectations on the other side are the driving force of change in e-commerce. Fueled by tons of data machine learning and artificial intelligence are slowly becoming the norm. But algorithms themselves won't be able to change the companies and deliver success. Entire companies need to change as well. How to embrace this change? Where to start and what to expect? How to organize yourselves? We'll deep-dive into data-driven digital marketing framework, followed by insights and case studies from clients and finish up with a stack of tools and takeaways you can use to produce some quick wins.

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.

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.

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?