Learning from Bezos

Posted by Dan Temkin on November 29, 2017

Code used to develop this analysis can be found on my Github

word cloud made from amazon shareholder letters in the shape of amazon logo

Recently, I came across an editorial on Medium.com entitled “What I learned from Jeff Bezos after reading every Amazon shareholder letter”. As the title suggests, the editorial is centered around the author’s take-aways after reading the statements made by Jeff Bezos at the annual Amazon shareholders meeting from 1997 to 2016 link. In the peice, the author chose to highlight several key tenets that stood out in the letters to the Amazon shareholders. Each representing the individual sections of the article, they were as follows:

  • It’s all about the long-term…
  • Customer centricity as a north star
  • High-quality, high-velocity decision-making
  • Put effort into inputs, not financial outputs
  • Raise the bar on hiring… again and again

Many of the author’s thoughts were compelling I was still left wondering if there was an analytical way to come to the same conclusions? While from basic keyword grouping some of the same qualities could be infered such as Amazon’s customer-oriented business model and the focus on strategic decision-making. However, that there was a lack of concentration on financial outputs also seems to have been a dubious proposition by the author given the keyword distribution. Though without a more contextual analysis I cannot say for certain.

In any case, the word cloud produced by a frequency distribution of the 200 most used keywords in the letters, can be seen above. A table of the top 10 keywords and their counts can be found below. I hope you enjoy, and feel free to take my code off of github and tinker around a bit. My stop-words selection was a bit crude but I really did it with an eye towards function over fashion. Although, for those that are interested I am currently in the process of working on a post dedicated to the process of creating a custom NLP pipe with spaCy.

As always any comments and/or questions are appreciated.

Top 10 Words  
Word Frequency
customer 412
million 105
business 99
sales 76
time 75
service 74
cash 73
term 69
experience 65
company 63