Well, my people, I’ve done it! I have completed the year long blog following experiment! Can you believe that a year has already passed? Where does the time go so quickly?! For those of you that are unfamiliar with this experiment of mine, allow me to explain. As many of us do, I got really frustrated following blogs that would suddenly stop, or disappear. I started to do some online researching (because, well, that’s what I do!) and some of the articles I found were… eye-opening. Like this post from Hellbound Bloggers which states that ‘…out of every 100 newbie bloggers, around 90 hang up their boots even before enjoying a trivial amount of success’. (Singhal, Harshit, 23 April 2017) or this beauty from the New York Times which cites a 2008 survey by Technorati and says ‘only 7.4 million out of the 133 million blogs that the company tracks had been updated in the past 120 days. That translates to roughly 95 percent of blogs being essentially abandoned…’ ( Quenquay, Douglas,5 June 2009) I kept telling myself, that this can’t just be true! So, I decide to do a little test for myself. You can find the full blogpost here explaining this whole process.
- I followed 1000 blogs at random for 12 months:
- Sites remaining after 1 year: 480 = 48% of total
- Of those 480 sites, 346 had been updated within 7 days.
- Month 1: 80 sites removed in February, which hadn’t updated the site in 2 months, 8% of total
- Month 2: 95 sites removed in March, which hadn’t update in 2 months. 9,5% of total
- Month 3: 0 sites removed in April. 0% of total. This has my attention. What’s happening in April?
- Month 4: 25 sites removed in Maj, which hadn’t update in 2 months. 2,5% of total
- Month 5: 23 sites removed in June, which hadn’t updated in 2 months. 2,3% of total.
- Month 6: 35 sites removed in July, which hadn’t updated in 2 months. 3,5% of total
- Month 7: 29 sites removed in August, which hadn’t updated in 2 months. 2,9% of total
- Month 8: 23 sites removed in September, which hadn’t updated in 2 months. 2,3% of total
- Month 9: 33 sites removed in October, which hadn’t been updated in 2 month. 3,3% of total
- Month 10: 26 sites removed in November, which hadn’t been updated in 2 months. 2,6% of total
- Month 11: 50 sites removed in December, which hadn’t been updated in 2 months. 5% of total
- Month 12: 83 sites removed in January, 2019, which hadn’t been updated in 1 month or more. 8,3% of total
- 18 sites were formatted where the posting dates were unavailable/hidden. 1,8% of total
Although my small, unprofessional experiment shows that 52% of the blogs I followed were left abandoned within the year. This is a large difference to the 75%-95% of failing blogs that I read about.
It does seem to my mind that the reports were accurate in that the larger percentile of blogs left abandoned were within the time frame of the first 3-6 months of the blog’s creation.
Surprisingly, there seems to be an interesting pattern regarding the time of year. This may be entirely coincidence, but it seems that a higher percentage of blogs are ‘abandoned’ during the winter months. I very much want to know why April seems to be a magical month for blogging! Not even 1 blog was left unattended for the 2 month limit during the month of April. Which tells me that something is happening during March/April that is affecting blogging motivation. This may warrant further study, as I am unable to stop thinking about it.
34,6% of the total blogs studied had updated within 7 days of the end of the experiment. Many (but not all) of these blogs have an excess of 1000 followers. This could be approached from the view that more followers, leads to more blogging focus. OR that higher blogging focus leads to more followers. Either or neither could be true.
- Follow 1000 blogs directly from the reader in a range of topics at varying times of day. I didn’t read them, I just hit the follow button on the top few posts under each topic. Wait several hours and repeat so as to gain a variety of nationalities. This lasted several days.
- Once monthly, I would remove the blogs that had not been updated in 2 months. I would collect data and record it in experiment excel file. (colour-coded by month unfollowed)
- On January of 2019 (the final month of the experiment) I removed all blogs which had not been updated in 1 month or more. Data was collected, recorded & coded in excel file.
- On January of 2019, I recorded data as well on all remaining blogs that had been updated within 7 days.
- Recorded data counted and recorded in above ‘results’ section
Methodological issues that could result in false data:
- I was unable to give accurate monthly updates, as I first thought I would be able to. This is due to the fact that 1000 blogs is ALOT and when you go ‘manage blogs’, I noticed that only part of them would display. Even when I waited patiently, changed the order…It still could not display the entire list. This also needs to be taken into account when considering the things that could have affected the outcome of my experiment.
- Blogs followed were followed directly from the reader > discover > tags section. As it would distort data to include some languages, but not others, I used only english language in the tags search (as it seems to be the most widely used language on this platform). This has limited the control group to blogs written in the english language.
- 1,8% of total blogs followed did not show (on my reader or their sites) the date of last update. So there is a 1,8% unknown variable
So this is what I have found, people. I did invest much time into this experiment and I hope that I was able to offer some data that you find interesting. There are some surprises in this which I think may warrant further investigation.
Thank you for reading and you are welcome to share this if you wish.
Pixabay, Feature photo
Quenquay, Douglas, ‘Blogs Falling in an Empty Forest’ New York Times, 5 June 2009
Singhal, Harshit, ‘5 Reasons Why Most Bloggers Quit Blogging Within 6 Months’ Hellbound Bloggers, 23 April 2017
*This blog experiment was a small-scale, personal experiment for blogging/entertainment purposes which should in no way be considered as professional, publishable data.