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Two Daily Must Haves


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Richard Branson On Good Brands


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A Million Dollar Writer On How To Be A Million Dollar Writer


wealthymatters“Many writers have a not-so-secret fantasy. They labour intensely for years on a masterpiece, hoping that an influential publisher or literary agent will “discover” them, and they’ll be catapulted to fame and fortune. That’s a nice fantasy, but with one problem: it doesn’t happen that way. It never does, or at least almost never. Okay, rarely it happens. But you’re more likely to be struck by lightning on the same day you win the Powerball, than you are to be “discovered” in this way. You must discover yourself! You must identify what makes you different, what “special sauce” you add to this common craft (writing) that makes you a distinctly differently voice on a common subject. In what way are you a player with a unique, unduplicable advantage?

To succeed, you must realize you are not actually in the “writing business.” You are in the business of You, Incorporated. It is your unique personality, and the fascinating persona you share with the world, that shapes how that world sees you. Done right, this can make you an irresistible character to whom people are attracted as their chosen and trusted authority. Done wrong, this can break the ties between you and your readers. Specifically, instead of promoting and advertising your highly-developed craftsmanship as a writer, you must be in the business of promoting you. You cannot rely on word-of-mouth, or critical acclaim, or impersonal ad campaigns. You must conscientiously promote yourself, and intentionally craft the way customers perceive you. Read more of this post

How To Choose Your Business


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When Data Science Led To Losses


wealthymattersAbout 5 years ago, a telecommunications company wanted to be able to predict whether a customer would cancel their service or not. If the company could catch a customer right before they fall out and convince them to stay put, then the company keeps revenue.

So the analysts and data scientists were set off to races on developing a model that could help the company better predict when customers were planning to quit their service.

After about a year and a couple hundred thousand dollars worth of resource hours the team had developed a successful model. It was 85-90% accurate. They then worked with process managers, and customer service teams to develop playbooks and guides to help approach customers who may not be interested in the service. A few more hundred thousands of dollars dropped into the project. Once they felt like the algorithm was set and the team members were trained they went forward to implement the project. Read more of this post

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