Recently Chris made a post “Hidden phpMyAdmin Features” which became fairly popular on Reddit and several other sites. I was curious not only what sort of traffic this would bring, but what the quality of traffic would be like.

Total Visitors

• 8,282 Visits (98% New Visitors)
• 8,104 Unique Visits

Now at a glance this seems to be a decent surge in traffic but it’s not that black and white. Here is why:

The amount of new visitors is, as expected, quite high, though how many of them actually read the content, commented, and will be returning?

The Bounce

The bounce rate is determined by taking the amount of visitors that go to a single page and exit on the same page. Essentially this means they visited our single post, and didn’t bother to see if there was anything else on the site. Now once again this is to be expected as the majority of the traffic came solely for the purpose of reading that single article.

• 93.67%

So roughly 7,595 of the visitors we received never left the original blog post, while 513 of them clicked off to another page.

Time On Site

Now this is a fairly obvious metric, though it means the average amount of time people spent on your site.

• 14 Seconds

That’s right, 14 seconds. Now I’m not sure the average reading speed of reading for internet users, though this would seem that it’s a little on the short site. I’m lead to believe a large portion of the visitors simply skimmed the page rather than fully reading and understanding the content.

*NOTE* The last sentence may be interpreted wrong: I believe the majority of people quickly glance / speedread the content and if something catches their eye, they’ll go back and try to absorb the information. Obviously our post is somewhat niche since it deals with phpMyAdmin which is popular, though it still interests a small portion of the internet community as a whole.

Page Views

This is another obvious metric, and somewhat of a obsolete one, though interesting nontheless.

• 9,047

Now if we take this number and subtract the total amount of unique visitors we arrive at 939. Now the astute person would notice that this is almost double of the above number I arrived at regarding the bounce rate. This just simply goes to show you that statistics obviously aren’t 100%, and depending on the mechanism used to measure the statistics these will vary. Regardless I find it interesting to see an almost 100% difference – any one have any idea as to why?

Traffic Sources

This metric is simply tells us what percent of visitors came from where (direct, referring, or search engines)

• Direct Traffic: 12.90%
• Referring Sites: 87.09%
• Search Engines: 0.01%

Now this is clearly wrong – this blog literally has no real traffic. Unfortunately if a browser doesn’t send referral data, or a website redirects in a way to not send the data it’ll count it as direct traffic. What somewhat surprised me is how large of a margin of error this is.

Referrals

Now this is the fun metric – where the heck did all of this traffic come from. Obviously being on the front page of /r/programming and Reddit caused the majority of traffic, though not all of it:

• Reddit.com – 6,060 visits
• Direct (none) – 1,070 visits
• Popurls.com – 316 visits
• StumbleUpon.com – 307 visits
• Delicious.com – 142 visits
• Google.com – 106 visits
• Wired.com – 68 visits
• Jimmyr.com – 40 visits
• Twitter.com – 18 visits

Keep in mind we only posted this on Reddit, everything else came organically by word of mouth, aggregator, and so forth. This also shows the discrepancy in the referral / direct reporting, showing 1,070 direct visitors.

*NOTE* Since this site is so new and lacking content, all references to Google are from their applications such as Google Reader, GMail, etc.

Conclusions

If you get on the front page of Reddit / submit a popular story you will receive a surge in traffic, though a large portion of those people will simply glance / exit right away and will likely never return.

Also you need to take your statistics with a grain of salt – there is a fair margin of error when you start trying to dissect the statistics.