A Quote by Mickey Drexler

Data is very important, but you have to be good at reading the data in an emotional way. If you look at a selling report, there's an emotional trend to what's selling. — © Mickey Drexler
Data is very important, but you have to be good at reading the data in an emotional way. If you look at a selling report, there's an emotional trend to what's selling.
I have to have an emotional connection to what I am ultimately selling because it is emotion, whether you are selling religion, politics, even a breath mint.
I feel that when I listen to music - not that it's bad - it's not emotional. It has a gimmick to it. It's selling something: the artist, the producer, something. The emotional capacity is very small, for the listener as well.
Opposition to immigration is an emotional argument, and human beings are emotional, not robots powered by data.
Fashion is emotional, and the way women look at it is emotional, so it's very important to try to connect with a woman's idea of how she might feel.
My study is NOT as a climatologist, but from a completely different perspective in which I am an expert … For decades, as a professional experimental test engineer, I have analyzed experimental data and watched others massage and present data. I became a cynic; My conclusion - 'if someone is aggressively selling a technical product who's merits are dependent on complex experimental data, he is likely lying'. That is true whether the product is an airplane or a Carbon Credit.
Emo always meant emotional. Any kind of art or music should be emotional. If its not, than it's pretty much just a jingle selling bleach or pizza.
Let's look at lending, where they're using big data for the credit side. And it's just credit data enhanced, by the way, which we do, too. It's nothing mystical. But they're very good at reducing the pain points. They can underwrite it quicker using - I'm just going to call it big data, for lack of a better term: "Why does it take two weeks? Why can't you do it in 15 minutes?"
With Street View, you're curating a data set capable of incredible emotional resonance for the person interacting with it because everyone grew up somewhere. And if your house is in this dataset, that's going to provide some emotional context for you.
Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
Selling is the most important skill as an entrepreneur. I'm not talking so much about selling a product so much as selling yourself, team, and deals.
Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.
Because Comic Con in San Diego is crazy, and it's very commercialized, and it's corporate, and it's all about money and selling, selling, selling... I think people want to go to smaller, specialized cons.
I will talk about two sets of things. One is how productivity and collaboration are reinventing the nature of work, and how this will be very important for the global economy. And two, data. In other words, the profound impact of digital technology that stems from data and the data feedback loop.
Every company has messy data, and even the best of AI companies are not fully satisfied with their data. If you have data, it is probably a good idea to get an AI team to have a look at it and give feedback. This can develop into a positive feedback loop for both the IT and AI teams in any company.
If you're a cyber-criminal, the days of stealing data and then selling it for cash in the dark web - they're not so profitable as they used to be.
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