Two motivations for this Rants & Ramblings post:
I haven’t taken the content marketing aspect of my blog very seriously and have been curious about who actually reads the content.
Have been wanting to see how this site’s analytics capabilities have evolved (note: Squarespace, at the time of this writing).
Let’s see what we find out!
By Device Type: 60% Desktop, 37% Mobile, 2% Tablet, 1% Unknown
By Source: 43% Direct, 32% Google, 12% Facebook, 11% LinkedIn, 3% Others
Pretty interesting finding! In the Others category, it shows how many traffic referred from CRMs.
By Browser: 46% Chrome Desktop, 16% Mobile Safari, 13% Chrome Mobile, 10% Facebook App, 16% Others
By Operating System: 43% Windows, 25% iOS, 16% Android, 7% macOS, 9% Others
More than half of my site’s traffic originates from Canada. BC dominates with 66% representation, followed by 13% from Ontario, 10% from Quebec, 5% from Alberta, and the rest is scattered.
Another 20% of my site’s traffic originates from the USA. California, Oregon, New York, and New Jersey all represent >10%, with Texas following at 7% and the rest of the states are all sub 5%.
There was a massive spike in searches landing on my site throughout the summer. I assume this corresponds to my research / start up project.
Top 5 queries driving traffic on my site: “joshua tiong”, “excel ninja”, “dhamma surabhi”, “burden of leadership”, and “merritt meditation retreat“
*Note: it bugs me that this can’t be calibrated for time period comparison or averages on a fixed time horizon.
5 most-read blog posts
Year to date, based on total page views:
Interesting to me:
#1 on the list nearly doubles the page view count of #2, and is more than 5x the page views for #5..
This is not the list I would have expected.
The capability to dig into performance for individual posts would be amazing.
Least-read blog posts
There’s literally one engagement on each. Who is reading these!?
I wonder if I’ll ever be inclined to take writing on my blog more seriously.
I wonder what Squarespace’s customer segmentation and product feature usage breakdown looks like.