The post I wrote last week on 13 Truths about Social Media Measurement did well, and I thought it would be interesting to look at some stats around it in detail. As of today, it’s in the top 10 posts on my blog in terms of visits/traffic of all time (and that’s just a few days after it posted).

So this is a bit of a post mortem on that post, what happened around, it, and some conclusions I can draw about it.

Note that the intent here is NOT to get you tangled up in my specific numbers. My numbers are what I have to work with, so that’s what I’m using. It’s all in the relative data. The hope is that I’ll help you consider how you might analyze your own blog performance, content, or other initiatives, and illustrate a bit about the longer term results of a blogging investment.

Analysis Period

For ease of tracking and a solid, uncluttered snapshot, I did this analysis for the 24 hour period from when the post hit to the following day at the same time. So this is not an analysis “to date” of this post, but it’ll certainly be interesting to revisit this content in 30 days and do some analysis around the lifespan of a popular post. For the purposes of pulling together this post, I had to draw a line in the sand somewhere.

Specific Statistics:

Bit.ly link: 1,613 clicks

Website visits: 3,192
I get anywhere between 40K and 60K uniques a month right now (with the exception of March where I surged to 100K in large part because of this post). So this post represents about 6% of my total monthly traffic for May.

Other Stats: (various sources)
Comments: 31
Shared Items (Google): 84
Delicious Bookmarks: 126
Facebook Shares: 48
Likes: 14

Traffic Sources: (per Google Analytics)
Direct: 31%
Feedburner: 15%
Twitter: 12%
Google (organic): 5%
Delicious: 5%

# of Tweets of the post: 702 (analysis by Radian6)
30% of the posts did NOT include my name, blog name, or twitter handle. just the article title.

15% of the posts didn’t include the “13 Truths” part of the title, and amended it to their own language.

There’s undoubtedly an additional slush factor in those that replied, shared, etc and included a link but totally different language or words. That’s gravy, in my mind. This tells me that when you’re analyzing a post’s carry, you have to consider how it might morph in the translation and spread and realize you’ll always have a margin of error.

Potential Twitter Reach (also provided by Radian6): 2,466,697
I’m still not sold on the value of this number. It looks impressive on paper. But see the conclusions section below for some thoughts about it.

New subscriptions to the blog: +/- 200
I’d love to say this is perfectly accurate, but Feedburner doesn’t always play nice. I could have tracked this better by putting a unique subscription link with tracking code on the post itself, but others would have undoubtedly clicked the main sub link anyway.

To the best I can tell, I gained about 200 subscribers because of one post. That’s about a 6% conversion rate based on visits in the same time period. I’d also love to put in better tracking (using Google Analytics goals) to see how those subscriptions convert by referral sources, i.e. whether the traffic from Delicious bounces and leaves, or tends to actually subscribe and stick around.

Emails inquiring about speaking, input/consulting (which I don’t do): 4
Time Spent writing the blog post: approximately 60 minutes.

My former billing rate as a consultant averaged $275/hour. So you could say my investment was $275 worth of time. If were to take a single speaking engagement at even half my standard rate that found me because of this post, my ROI would be about 1700%. If I were in the consulting or service business, a single account landed this way could pay for itself several thousand times over.

That’s just for one post, though, that’s part of a long effort of blogging consistently and with purpose. See more in the conclusions about that.

Referrals to my company site (Radian6): none
Of note here is that I didn’t link to Radian6 or mention it anywhere in my post. Other posts I’ve done on measurement HAVE sent traffic through to the Radian6 site, but only when I’ve mentioned the company and linked to it specifically (or my guest author has; this post that Matt wrote last week drove nice traffic through to Radian6’s website). More on that below.

Other Conclusions, Thoughts, and Analysis

Twitter
It’s clearly a key place for me to continue sharing my content, as it gets good reach. Half the traffic for the day can be attributed to the bit.ly link, which I only shared on Twitter. On the other hand, it’s important for me to consider more avenues for distributing content in the future, because I’m putting too many of my eggs in the Twitter basket right now.

There were 686 tweets of the post and 1,613 clicks on the shortened link, which means that every tweet accounted for an average of 2.35 clicks.

Also important to note: my potential “impressions” on Twitter were nearly 2.5 million. It goes without saying that  the percentage of inactive accounts on Twitter – some say as many as 70-80% – skews these numbers. And if there were only 1,613 clicks out of those 2.5 million impressions? That’s an overall conversion rate from attention to action (in this case just a click) of WAY less than 1% (.0006% to be exact).

What would be interesting is to somehow figure out where those 686 tweets and their subsequent clicks fall in within my network (i.e. are they direct connections, or separated by a couple of degrees), and somehow map the resulting click throughs to those degrees of separation. That could start showing how “impressions”  on Twitter dilute (or not) as they drift away from the original source, or from close connections. My hypothesis is that the heavy percentage of the actual traffic would come from the first couple of degrees.

That’s more than I have the chops for right now, though. I’d need some API help with that one.

Delicious
Delicious bookmarks can drive great traffic too, but the types of posts that get bookmarked there are of a specific stripe that I can’t just churn out constantly.

This one hit the Delicious “Popular” posts page, which undoubtedly helped raise some awareness for the post and generated some traffic.

Posts on measurement are clearly still very wanted and well read, so that’s a viable content subject. List posts work, as all of the last several list posts I’ve done have hit Delicious pretty well and driven significant traffic. Good intel for content strategy, but obviously not something you can do every day. Fatigue for content counts for something, so the popular, bookmarkable stuff has to be interspersed with other content.

Radian6 Referrals
My blog can and does drive visible traffic and leads to Radian6. So it’s a good way to keep my bosses invested in the idea that spending time on my own blog is a good thing for THEM. But if that’s part of my goal (and it is), I have to be sure and specifically ASK readers to go there (by means of mentioning my company and linking to it in a post, with disclosure of course). Obviously I can’t do that all the time, or folks would see me as a walking plug for my employer. But it’s something to keep in mind.

Content Spread
This post also got picked up in some newsletters, other publications, and aggregate sites (with permission and attribution). It also got picked up by annoying scraper sites that don’t credit or link back to the original work.

Practical, educational content spreads. And it finds new life in other channels and more mainstream industry publications if it’s written to be applicable to more than the immediate audience. Even the spammers and scrapers like to pick up content that’s driving traffic.

Also of note: Sticky titles and lists posts work well, and unique titles make for easier analysis and tracking of how they spread and get shared.

The Blogging Commitment
Blogging can pay off, big time. BUT. I’ve spent over two years building my audience, traffic, and consistently putting out content (some well received, some not). The burn is slow, and you have to keep earning the attention in order to keep it. I started at ZERO, just like everyone else.

It’s not enough to just get traffic. You have to get people that want to take a seat at the table and hang around for a while. I’d also love to find a way to analyze at what rate my existing subscribers share content and pass it along, as that can help me understand one aspect of long term subscriber value, and how invested my readers are in the content overall.

And what content works? Well, that’s a matter of listening to your audience, participating in the larger community, and delivering stuff that meets needs and interests of those people. Simple, right? Nope. Lots of work. Time. Effort. Learning.

Can You Apply Any of This?

This wasn’t so much intended to show the performance of a single post as to get you thinking about how you can analyze the performance of your content, and measure some readily available things in order to draw some insights about what you’re doing.

I’m not doing this for every post, of course, but by focusing my analysis on the far ends of the scale – the posts that are ghost towns and the ones that go gangbusters – I can continually understand what my audience, social network communities, and other people are finding worth reading. And this is hardly professional, bullet-proof analyst-level drilldown, but what do I need that for? More work than it’s worth. At this point I’m just looking for some validation of my hypotheses.

So was this helpful to you? Again, don’t get mired in my  specific stats, but look at the methods, the data captures, the smashing together of a few different numbers to see how you might put a similar framework in front of the content you create to learn what’s working, what’s not, and help you fine tune your strategy.

Questions? Comments? I’m all ears.