All you need to know about attribution models

It was august 2009 and I was invited to a meeting with Marketing managers of a multinational company. End of year was coming and all of them where working on their budgets for the next year. Each director was supposed to present their proposal and then distribute the marketing budget based on the potential revenue each area could generate for the company (paid search, SEO, TV, email marketing, etc). Each director made his presentation trying to convince all the rest that his/her area had the best potential and, hopefully, get the biggest budget. It was really interesting that each of

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Multi dimension customer segmentation and what can you expect from each data type

What’s better for clustering your audience/users, using Behavioral or Demographic variables?  This is a hot topic since the first websites came along. Since I remember companies use to segment their clients and potencial clients mostly using a Demographic criteria, which means grouping people into groups based on age, sex, income, occupation, religion, race, etc. Historically those variables are classified into Hard, Soft and moment referred ones. 1- Hard Variables: The Hard Variables are the ones that normally never change like the birthdate or name. 2- Soft Variables: The Soft Variables are those that can change from time to time, like level of education or income. 3-

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What are Flow Scorecards and why are way better than regular ones

Scorecards are a semi-standard structured type of report, supported by proven design methods and automation tools, that can be used by managers to keep track of the execution of activities by the staff within their control and to monitor the consequences arising from these actions (by Wikipedia), and looks like this: The problem I find in that type of scorecard is that there is no relation between the company strategy and the performed tactic activities, which are (if the scorecard is properly design) each one of the measured metrics. On the other hand, it’s not impossible to see either the cause and consequence relationship between the actions or how

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How do you know you are dealing with Data Driven organization?

Most companies we know today born in a time where information was scarce which explains perfectly why they haven’t developed a Data Driven component into their cultural DNA. To have a good feeling on what I mean when I say lack of information let’s take a look at some figures. 90% of the data on the internet has been created since 2016 (IBM Marketing Cloud Study) Around 200 million wearable devices where sold in 2019, increasing around 600% in just 3 years. The internet users came from 16 million in 1995 to 4.5 billion in 2019. There are 83% more

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Dealing with overpromising vendors in an hyperbolic digital marketing world

We are living in a quite particular digital industry. Technology had invaded humanity so almost everyone today knows “something” about technology. In any case the “levels of knowledge” do actually make a big difference. The partial knowledge of technology produced a surprising effect. Right now, people believe that technology can solve everything. That’s why it is normal that when you talk about a technological advance with random people, those with lower knowledge are less surprised than those with higher knowledge. It seems like there is a inversely proportional relationship among tech knowledge and surprising capacity that is getting worse and

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A unique opportunity to create stories and experiences that really matters to our audience 

Yesterday I was thinking on how digital advertising had changed since my first steps in the internet. I still remember the first floater or Layer banner that really shocked me, It was from Nike. You was navigating a publisher’s website and a Shark’s Fin started swimming around the screen like in the movie, like trying to frighten you, this really kept my attention and finally the Nike logo was displayed with a very catchy phrase that I can’t even remember right now. That was 1999. Simple, creative, catchy. This days is not that simple to take user’s attentions. In 1999,

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How to create storytelling dashboards like a boss

So the Analytics people has to be the ones that simplify the decision making process. They have to be the ones that help people consume the information in a way that is simple, it is not time consuming, it is not confusing and as univocal as possible. Analyzing and reporting are two completely different things, like I mentioned in “How to make self explaining reports“. But making the long story short, the person that analyzes the data goes through a process of questions and answers that generates the layers of information that will give context to the reported data (What

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Vision is the key factor for a Data Driven Culture

In my book Meta Analytics I presented two sides of the analytics synapsis. The object that we analyze (companies) and the subject that make the analysis (the people). Between those two things there are a lot of things to deal with to convert the result of the synapsis in an insight that can be taken into action. In this post I’d like to talk about the object, the company. A company is a system, a set of parts that interact together with the common objective of adding value (in the present and in the future). So basically the information system

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Life before and after Magic Leap, are you prepared?

I remember that during the first wave of internet we tried to replicated the physical world but inside the browser. So buying cloths online was supposed to be like being in the store, which at that time was just impossible. It wasn’t until the second internet wave (after the crash of the first bubble) that we realized that internet won’t be or supposed to be like the real world. Actually it was able to be better but in a different way. During this second wave was where companies like Amazon came to make a revolution in the way we shop,

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