Linkedin Headline Optimization Series: 2 Terms by Location and Learning some R

My Linkedin Headline became a real project once I decided to pull all sorts of random stats from my searches of Linkedin and then plot them in Excel. As promised in my first post in this series, lets take a look at how various job titles break down by city in the US and English speaking country. Who has more analysts? Where do all the hackers live?


First let me discuss my data gathering methods: I used the Linkedin people search feature and each of the following terms one by one - analyst, associate, consultant, executive, expert, hacker, manager, planner, resident, and specialist. This gave me numbers of profiles that either matched to the headline, current job, or previous job titles. I then recorded various info: industry, location, and education. 

For example, I searched for "analyst" and then recorded that 246,227 profiles came up for Greater New York City Area.

This time, rather than spend a full day making various versions of charts, I decided to practice some R. I've dabbled very lightly in R and Python, almost exclusively copying exercises provided by Nathan Yao of Flowing Data. Today, thanks to Nathan's Getting Started with R guide, I was going to use the statistical programming language to do all the heavy lifting.

I simply ran some code, and had all my answers.

HAHAHAHAHAH. Are you kidding? I just started using R, and I can honestly say I have no clue yet what I'm doing. It took me hours and countless Error messages to barely eek out the following charts. Too bad all the labels are overlapping and the scale is logarithmic.

Screw R, it was back to Excel. Keep in mind this data is only directional, since I might be double/triple/quadruple counting one profile (e.g. if that person was once an associate and then a manager). However, because Linkedin doesn't provide total number of profiles by city, it's the best I can do. Still you'll be surprised to see what I come up with.

So here's my first output, percentage with each phrase by city, I'll share the whole excel file once I'm done with the blog series.

Lets see what this looks like.

!!! I was actually quite surprised by this finding. But let me sum up what I'm seeing.

1. Every major city seems to have the same ratio of titles

There are almost the same percentages of analyst, associate, consultant, executive, expert, hacker, manager, planner, resident, and specialists in all seven cities that I looked at!

Lets see if I can enumerate these percentages by averaging them:

manager	37.5%
associate	13.5%
consultant	12.5%
executive	11.8%
specialist	9.9%
analyst	9.4%
expert	2.7%
planner	1.4%
resident	1.2%
hacker	0.1%

This means, every major city I surveyed has 4 managers for every executive/specialist/analyst and 3 managers for every associate/consultant. Hacker is super unknown across the country.

I was also really curious to find out which city is the douchiest. I considered "expert" to be one of the douchiest title terms one can use, but sadly there wasn't a city that was a clear standout - everyone was at 3% douchiness.

Lets take a look at country data, again here's the source data I'm using, converted to percentages for the chart.

You'll notice a couple of things:

• Manager hovers at a similar percentage as when we looked at countries, though Australia and UK love the "manager" title (at 48%)
• "Executive" is most popular title in India, almost by a factor of 2 compared with every other country, while "Analyst" is least popular in India by a factor of 1:3.
• "Hacker" is almost non-existent across the board in profiles. If you're in Australia, you can really stand out from the other 498 profiles with a phrase like that.
• And...
• The US leads in Residents and Specialists (both minuscule percentages)
• The UK has 50% more consultants than the US, but 50% less associates

Ok, that's it for this post. Next up in this series I'll look at which schools produce what titles.