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As unlikely as it seemed at many times throughout the year, 2020 actually IS finally drawing to a close, and that means it's time for our annual look back on the year: what happened with the podcast, what happened with the industry, and what happened as the entire world caught fire by way of wood-fuelled, climate-assisted combustion and by virus-induced fevers. In hindsight, there were faint hints of what the rest of the year would bring when our co-hosts and producer were together in person at Superweek in late January, but exactly how upside-down the world went still took them by surprise. One thing stayed constant, though: Tim and Moe continue to be able to talk past each other and violently argue about something about which they, basically, agree. On this episode: cover letters! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Our industry is based on data. But without context, data is meaningless. In our world, data and context should be used to improve the business. Otherwise we are useless.

With the proliferation of event based analytics and sophisticated real time data science and the parallel maturing of token based economice there's a cross roads where they meet worth a fireside chat. Often we get stuck in privacy debate or broad statements of data as the new oil, but it deserves a much more nuanced discussion and look ahead at where we can go...

Stéphane is a veteran of Superweek and each year he brings a forward-looking topic which challenges the way we do our work - he brought us his famous digital analytics maturity model and the radical analytics manifesto, and last year he scared the sh*t out of us by demonstrating how machine learning could be leading us closer to an impeding doomsday. This year, Stéphane will continue where he left last year and dig into real-life examples of questionable ethics and malpractice which will hopefully make you think about your limits and where the red line is for you, as an analyst and as a consumer.

How do you measure the impact of creativity? This is one of the major issues facing analytics in LEGO, since the majority of products are not being sold directly to consumers. Today, LEGO’s internal creative agency is providing thousands of creative communication and marketing assets to hubs all around the world in hundreds of different cultures, but the question remains how can you measure creative work’s productivity and efficiency and how do you determine the return on a creative marketing asset in a complex world?

In this talk Kris Ewald, a 15y veteran of the Analytics industry will share his views and experiments at the crossroads of event based real time data, data science and token based economics.

Marketers and analysts not only want to know which channels & campaigns drive sales and what is their ROI. They want to know how to optimize digital marketing performance starting from strategy and up to keywords bids adjustment. As advertising tools evolve, campaign optimization inside a particular ad service is being constantly improved. The main decision for a marketing professional to make is how to choose the perfect budget allocation across the channels and how to know in advance what results one can expect from each channel in the future.

In this talk we take a look on the most important issues, according to you.

Every report, analysis, statistical method, and amazing technical innovation eventually winds up in the hands of a human person who must incorporate what has been produced into their decision making process. Sounds simple, right? Successful transmission and uptake of the results of analysis is crucial not just for leveraging data effectively but the long term success of the analyst and the programs they cherish. Let's dig into this a bit and see if we can identify some opportunities. And yes, this will include talking about emotions. How does that make you feel?

In this presentation Peter will give you a panoramic view of how A/B testing is done at Nordea, the largest financial services group in the Nordic region and one of the biggest banks in Europe.

MDE calculations: real data example how to know if you could run experiments on a specific location. Data quality: real data examples to show what it means to have 20% more users in your experiment. Prioritization: how to optimize your chance of success by prioritizing your experimentation roadmap based on data? Test results: what are valid results in the data and what not? When is the experiment done? Business case calculations: how much money is your experimentation program really making?

The majority of nowadays attributions are very biased. Some of them do not reflect the whole customer journey, while others are based on some algorithms defined by people (heuristics), while the reality is usually much more complex.

There are too many things Peter wants to discuss about Digital Analytics and yet, he only gets to speak once. So in this talk, he will be musing on a wide range of topics around the nature of Digital Analytics, the work we do and life in general. This session will include what & who is inspiring Peter, what he wants to be working on and learning in the future, his frustrations within the world of Digital Analytics, his thoughts on what companies should be focusing on and of course, Peter’s latest point of view on attribution. The intention is to spark a bit of inspiration and ideas for all attending in return for the inspiration Peter has received from others.

It's here! The Digital Analytics dream of all your digital data and offline data in one platform! Or is it just another buzzword? This presentation will dive into real use cases implemented on Customer Data Platforms across CPG, Automotive, and Gaming industries. Bringing to light how Analysts can utilize this emerging technology to enable capabilities around customer journey analytics, content optimization, personalization, and more.