I got popped the question again… No, not the marriage one (10 happy years this month), but the blog ROI one.

While there have been lots of exercises in determining ROI or value, the calculations have tended to be rather arbitrary–basing it on the AOL/Weblogs deal for instance (FYI, we’re up to $15,242.58 now, from $12,419.88 in November, the last time I checked).

Charlene Li of Forrester posted recently on the topic (Charlene is the author of Forrester’s first report on blogging).

There was a good, but inconclusive discussion accompanying her post. The general sense seems to be that it’s still difficult to attach real ROI numbers to blogging. I’d love to see someone do a time-series study of market cap of Fortune 1000 companies before and after blogs were started–but I have yet to see anything like that.

Lacking that, I did do some digging to see what’s been written on the subject. There’s been lots of discussion on the qualitative, but little on the quantitative. In fact, there’s a real aversion to the quantitative: it might sell blogging short.

I’ve found four attempts to quantify blog performance/return/valuation. They’re by Stowe Boyd, Easton Ellsworth, David Wiley (his equations focus on newsgroups, but translate easily) and Jason Stamper.

Rather than talk about the merits and disadvantages of each (read the posts for good comments to that end), I thought I’d try to collect them, identify all the factors they use in their calculations, and start folks thinking about other ways to quantify blog performance.

HERE ARE THE VARIABLES WE SHOULD BE TRACKING:
a=average number of daily hits
b=number of barren messages (posts with no comments or trackbacks)
c=number of total comments on a blog
d=average number of daily sales leads generated by the blog
f=number of first time visitors
g=cost per sales lead generated
h=total number of inbound hyperlinks
i=investment in blogging (in hours spent per day)
l=total number of pageloads
m=mean reply depth (average number of replies to each post)
n=total number of messages (p + c + t)
p=number of total posts on a blog
q=arbitrary measure of quality
r=number of returning visitors
s=number of spam comments or trackbacks
t=number of total trackbacks to the blog
u=number of unique commenters and trackbacks, including author
v=number of unique visitors
w=hourly wage of the blogger
y=average yield for blog-related advertisements

AND HERE IS WHAT OUR FOUR MATH FANS DID WITH THIS INFORMATION:
Stowe Boyd’s Conversational Index: CI = p / c + t
Easton Ellsworth’s Modified CI: MCI = p / [(cq + tq) / u]
David Wiley’s Adjusted Mean Reply Depth: aMRD = m ( ( n – b ) / n)
Jason Stamper’s Blog Value Index a: BVIa = [ a ( y / 1000 ) ] / iw
JS’s Blog Value Index b: BVIb = dg / iw
JS’s Blog Value Index c: BVIc = [ a ( y / 1000 ) + dg ] / iw

(I didn’t use their original variable names, and tweaked the equations a bit. For instance, Eaton suggested that different posts and comments might be more valuable than other posts, so I added the quality variable.)

So for those of you who enjoy playing with numbers in spreadsheets, have some fun. let me know what you find…

Share on Facebook

Share/Save