Every good blogger likes to keep their finger on the pulse. I opted to put my finger on the traffic pulse. The purpose is to discern how things are going, what has been done well and what needs improvement. Whilst most bloggers might keep this information under their hat and utilize the data to improve their performance I am happy to share it.
I have pioneered a dashboard over the years to better represent the health and wellbeing of my blog. Recently I replaced bounce rate from 1st January 2016, with a new metric (New Vs Old) which measures the mix of new posts launched in the month versus old posts with afterglow.
Results for 2016 So far:
- January 1st – March 31st
- April 1st – June 30th
- July 1st – September 30th
- October 1st – December 31st
Here’s my results for 2015:
- January 1st – January 31st
- February 1st – July 31st
- August 1st – August 31st
- September 1st – September 30th
- October 1st – December 31st
Here’s my results for 2014:
- 1st January – 31st January
- 1st February – 28th February
- 1st March – 31st March
- 1st April – 30th April
- 1st May – 31st May
- 1st June – 30th June
- 1st July – 31st July
- 1st August – 31st August
- 1st September – 30th September
- 1st October – 31st October
- 1st November – 30th November
- 1st December – 31st December
Here’s how 2013 stacked up:
- 1st December – 31st December 2013
- 1st November – 30th November 2013
- 1st October – 31st October 2013
- 1st September – 30th September 2013
- 1st August 2013 – 31st August 2013
- 1st July 2013 – 31st July 2013
- 14th June – 30th June (to be covered as a special edition, watch this space!)
For my full year from WordPress and Jetpack:
Many of the sites that I visit have profit reports which are all well and good but I don’t generate a profit. Most sensible beginners don’t try to engage their audience with a sell so early on. You want to build trust first and if you are like me, skill too. One thing I do look at is traffic and whilst it might seem obvious just to leave a link to net stats of some form, I like to dig through them a bit and see what is going on.
“Be prepared!” – Baden Powell
If you are serious about doing better, learning from the past is important because you will correct mistakes and improve your chances. There is still an element of uncertainty but with all things you can better prepare for the outcomes.
Here you will find monthly traffic reports based on results from my currently used analytics and metrics. At present time I have been using Google Analytics and the WordPress.com Stats to record information. I have also activated tracking with Webalizer and AWstats and when suitable I will display information from these sources.
I started this blog on the 14th June 2013 and it was a good month for traffic. July was my first full month which dropped in interest from the first partial month but has so far seen the highest views. August saw a bit of a decline in numbers due to my continued degree commitments. September was a tough month with one amazing week making up approximately 80% of the month’s traffic. In October all of the weeks were an improvement on the previous month but one particular day saw a massive hike of pageviews from an Indian viewer in Pune, October was definitely golden! In November I managed to stay at pace even though I was away on holiday for a week so overall I am fairly happy about November even though it didn’t have the same spikes that October saw. December was a weaker month but had some good average on site times compared to previous months and was the second highest of 2013.
January 2014 signalled the new year and January was a very good month for visitors. I still have a number of key things I need to get right but I feel that with the right focus the site will go in the right direction. Its good to be feeling that way after 7 months!!
I refer to a particular filter that I use frequently to measure good and bad traffic. This removes low quality views between 0 and 29 seconds and removes anyone viewing my site from Crawley in the UK (because I perform testing and updates from here). This filter is applied through Google Analytics and is referred to as GAF.