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Like me, I'm sure you are working on complex challenges when it comes to data. Multi-petabyte data warehouses. Multi-touch, cross-channel attribution analysis. Media mix modeling. Predictive analytics. Human-centric analysis. Oh, and let's not forget the application of machine learning to every facet of your work. It is genuinely fun to work on these opportunities.
Today, a simple lesson that so many of us miss at great peril. In fact in your role, at this very moment, your company is making a mistake in terms of how it values your impact on the business. The lesson is about the limitation of optimizing for a local maxima, usually in a silo. We are going to internalize this lesson by learning from Microsoft.
The rapid pace of innovation and the constantly exploding collection of possibilities is a major contributor to the fun we all have in digital jobs. There is never a boring moment, there is never time when you can’t do something faster or smarter. The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-dr ...
Over the last couple years, I’ve spent an increasing amount of time diving into the possibilities Deep Learning (DL) offers in terms of what we can do with Artificial Intelligence (AI). Some of these possibilities have already been realized (more on this later in the post). And, I could not be more excited to see them out in the world.
I believe deeply in the value of making data accessible. In service of that belief, there are few things that bring me as much joy as visualizing data (smart segmentation comes close). There is something magical about taking the tons and tons of complexity that lurks in our data, being able to find the core essence, and then illustrate that simply.
Life is short. It is time to point out an ugly truth, and to be the brave person that you are, the intelligent rational assessor of reality that you are, and kill all the organic social media activity by your company. All of it. Seems radical, but let’s take it one step at a time. To give you a sense of the depth and breadth of ideas I’ll cover today, here are the sections ...
The very best analysts distill, rather than dilute. The very best analysts focus, when most will tend to gather. The very best analysts are display critical thinking, rather than giving into what’s asked. The very best analysts are comfortable operating with ambiguity and incompleteness, while all others chase perfection in implementation / processing / reports.
A rare post today. It looks a little further out into the future than I normally tend to. It attempts to simplify a topic that has more than it’s share of coolness, confusion and complexity. While the phrase Artificial Intelligence has been around since the first human wondered if she could go further if she had access to entities with inorganic intelligence, it truly jumped the shark in 2016.
A story where data is the hero, followed by two mind-challenging business-shifting ideas. At a previous employer customer service on the phone was a huge part of the operation. Qualitative surveys were giving the company a read that customers were unhappy with the service being provided. As bad customer service is a massive long-term cost – and short-term pain –, it was decide ...
Ten years, and the 944,357 words, are proof that I love purposeful data, collecting it, pouring smart strategies into analyzing it, and using the insights identified to transform organizations. In the quest for that last important bit, I am insanely obsessive about 1. simplification and 2. pressing the right emotional buttons.
There is, almost literally, an unlimited number of things you could focus on to create a high impact data-influenced organization. And, as if unlimited is not enough, nearly every month your analytics vendors release new features, you discover new analytics solutions, and as your business is more successful (hurray!) there is a new mobile app to track or a new digital experien ...
Culture is a stronger determinant of success with data than anything else. Including data. [People + Process + Structure] > [Data + Technology] It seems hard to believe. Yet, it is so fantastically true. At least for now. At least until AGI takes over. Why is this formula material? The first part of the equation, for better or for worse, improves in an evolutionary manner.
Today's post comes from a source of deep pain. Analysis Ninjas are valued less than I would prefer for them to be. The post is also sourced from a recent edition of my newsletter, The Marketing – Analytics Intersect. I send it once a week, and it contains my insights and recommendations on those two topics.
Being book smart is good. The outcome of book smart is rarely better for analytics practitioners then folks trying to learn how to fly an airplane from how-to books. Hence, I have been obsessed with encouraging you to get actual data to learn from. This is all the way from Aug 2009: Web Analytics Career Advice: Play In The Real World! Or a subsequent post about how to build a ...
Analysts, honestly, make the world go round when it comes to any successful business – yes, data is that important. As you might expect from any role, they also make a handful of important mistakes. I've written about the biggest mistake web analysts make. Today's post is an adjacent mistake: The cardinal sin of spending too much time with data and in reports! Wait.
An off-topic post this week, to celebrate this incredible outpost you've helped create on the web, Occam's Razor. This month my beloved blog is ten years old. T. E. N! It feels more like five. But, I've already celebrated the blog being five years old! I have to admit life has been a tad bit busy lately, and it took a note from a reader to remind me of the birthday. Her note read: "….
You don't use an ad blocker, right? Of course not! You would never want to take away the opportunity a content creator has online to monetize their work via ads. I know that at least some of you think I'm being sarcastic. I am not, and this post is all about getting the data to show you that I am indeed not being sarcastic.
Here's something important I've observed in my experience in working with data, and changing organizations with ideas: Great Analysts are always skeptical. Deeply so. This was always true, of course. But, it has become mission critical over the last few years as the depth, breadth, quantity and every other dimension you could apply to data has simply exploded. There is too much data.
I want you to sign up for something very, very special I'm doing: Writing short stories from the intersection of marketing and analytics. My goal is to get you promoted, you are going to love it. So. Please do sign up. But, first, as you've come to expect from this blog… Context… Should you own or rent? The logic we are taught from when we were babies is that it is better to own than rent.
If you don't have goals, you are not doing digital analytics. You are doing i am wasting earth's precious oxygenalytics. Let's back up. Let me start with a story. We were brain storming about the next cluster of coolness for Analytics, the conversation quickly went to what Analysts need to look at on a daily, weekly and monthly basis.