How has Trump got to be so close to becoming the most powerful person in the world?
Here’s a partial answer…
Trump is a life-long salesman. He has a huckster’s knack for selling a feeling.
He uses language differently from other candidates.
Watch this video to see analysis by the NerdWriter on how his 220 word answer to this question from Jimmy Kimmel is so effective:
Isn’t it un-American and wrong to discriminate people based on their religion?
- He keeps his language simple
- Of his 220 word answer, 172 or 78% of them are just 1 syllable
- He uses words in a “rhythmic series like a volley of jabs ending with one of his buzz words“
- 39% of his words are 2 syllables long
- Only 4 words have 3 syllables
- Merely two of his words have 4 syllables
- Trump tops an analysis of all 26 candidates put through the Flesch-Kincaid reading test. His words rate at a 4th grade reading level. Meanwhile, Clinton’s are 8th grade.
- He often speaks in the 2nd person: addressing with commands
- He talks as if you already agree
- He ends sentences with strong punchy words like problem or root cause
- He repeats a lot, especially his favourite words
- He knows when to sound incredulous or forceful
- But most of all he knows what matters is not the topic, but you.
Outspoken Bootstrapper Speaks
David Heinemeier Hansson is one of my favourite people. He’s a super-successful bootstrapping co-founder (of Basecamp), creator of one of the most widely used programming frameworks (Ruby on Rails), best-selling author and a Le Mans car racing champion. All kinds of fascinating angles and factoids for the tech startup founder in this podcast interview with Tim Ferriss. MUST LISTEN
Meet the Perennials
Gina Pell makes a compelling case to quit stereotyping customers by age. Much better to focus on patterns of what people are interested in instead.
Consumers Buy ‘Why’
Don Osmond writes that “Storytelling marketing is not about tricking the mind; it’s about endearing the brand to the hearts of its clients and customers” and “Consumers purchase on the basis of why; the how, when, where, and what are merely circumstantial. Why we do what we do and why we purchase what we purchase are inextricably linked with our stories.” SPOT ON
Big Funding for Big Data
Josh Nussbaum argues that the past need for significant upfront capital for tech infrastructure, is being replaced by the need to collect significant data to seed machine learning-based startups. To me this makes sense where expensive, bespoke hardware is involved but not necessarily to acquire customers to get the data. INTERESTING
Two Top Investor Tests
Marc Andreessen (top VC) expands on the two tests investors apply in deciding whether to invest in entrepreneurs: 1) Can they get a warm intro?, 2) Can they successfully present to Andreessen Horowitz’s full partnership? INSIGHTFUL
When Can You Trust a VC?
Serial entrepreneur and investor, Jenny Lefcourt, offers advice on how to know whether to trust a VC. 1) Does the VC have your back? Will they share info about you? 2) Do they invite you to do due diligence on them? 3) Do they offer advice with empathy? Do they truly appreciate your efforts? 4) Do they listen more than they talk? 5) How do they behave when things are not going well? Talk with founders they’ve invested in who’ve been through tough times. YOU’VE BEEN WARNED
Banks Will Become Invisible
Jim Marous explains why the bank of the future is set to disappear. Not because they’ll die (though many will) but because they’ll learn to get out of the consumers way. AI-powered, natural language voice and message interfaces will be the order of the day. SPOT ON
Apple Has Lost It!
Steve Blank (the godfather of lean startup) argues why companies that replace innovative leaders with mere executioners are doomed to fail. He uses Microsoft and Apple as examples. (Though I’d add that Microsoft seem to have since learned their lesson having ditched Ballmer) BRILLIANT
All Jobs Are Toast
All work can be divided into four types: routine and non-routine, cognitive and manual. Until recently we pinned our hopes on clinging onto jobs that: 1) require so little thought, we pay people little to do them, and 2) jobs that require so much thought, we pay people well to do them. Scott Santens explains why AI is on the threshold of taking over these last vestiges of jobs. A universal basic income is our only hope. SCARY
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