The Friendly Ghost PowerPR Index for June 2007

Results below, details below results:

fgpowerindex2.gif technorati_reactions.gif yahoo2.gif google.gif blogpulse.gif total.gif
1 Micro Persuasion 10 10 10 10 7 10 10 10 77
2 Online Marketing Blog 10 10 10 10 6 9 9 10 74
3 Center for Media and Democracy 9 9 9 10 7 10 7 9 70
4 NevilleHobson.com 7 9 9 8 6 9 9 7 64
5 a shel of my former self 8 9 8 9 6 9 9 5 63
6 Strumpette 9 9 6 4 5 9 7 6 55
7 On Message Wagner Comms 8 9 5 5 6 6 9 5 53
8 PR Squared 6 9 5 5 6 9 7 6 53
9 PR 2.0 Silicon Valley 6 9 5 5 6 6 7 7 51
10 Pop! PR Jots 5 8 5 7 5 6 9 5 50
11 Communication Overtones 6 9 5 5 6 5 9 5 50
12 Todd And – the power to connect 8 9 5 4 4 6 7 6 49
13 Media Orchard 4 8 5 6 5 9 7 4 48
14 Canuckflack 7 9 5 3 6 6 7 4 47
15 Web Ink Now 5 9 4 5 6 6 7 5 47
16 Spinwatch 4 7 4 5 6 9 7 4 46
17 PR Blogger 4 8 4 5 6 8 7 4 46
18 Marketing Begins at Home 5 8 4 5 6 6 7 4 45
19 PR meets the WWW 5 8 5 5 5 5 7 5 45
20 A PR Guy’s Musings 4 8 4 5 5 6 7 5 44
21 Paul Gillin’s blog – Social Media 5 8 4 4 6 6 7 4 44
22 Strategic Public Relations 5 8 4 5 5 5 7 5 44
23 Pro PR 5 8 4 5 5 5 7 5 44
24 Tech PR Gems 4 7 4 4 5 5 9 5 43
25 Bad Pitch Blog 5 8 4 5 5 4 7 5 43
26 IndiaPRBlog! 4 8 4 4 4 6 9 4 43
27 Media Guerrilla 4 8 5 3 5 7 7 4 43
28 New PR, ranked by readers 4 6 4 4 6 9 5 4 42
29 Drew B’s take on tech PR 4 8 4 4 6 5 7 4 42
30 Blogging Me, Blogging You 5 8 4 4 5 4 7 5 42
31 PR Works 4 7 4 4 5 5 7 5 41
32 New PR 5 8 4 4 5 3 7 5 41
33 PR Communications 4 8 4 4 5 5 7 4 41
34 Common Sense PR 5 8 4 2 5 8 4 5 41
35 ….the world’s leading…. 4 7 4 4 5 5 7 4 40
36 Cooler Insights 5 8 4 4 4 4 7 4 40
37 PR. Differently 4 8 4 3 5 5 7 4 40
38 PR Studies 4 8 4 4 5 4 5 4 38
39 Glass House 3 6 4 4 5 6 7 2 37
40 Buzz Bin 4 7 3 2 4 5 7 5 37
41 Murphy’s Law 4 7 4 2 5 5 6 4 37
42 Piaras Kelly PR – Irish Public Relations 4 7 4 4 4 5 5 4 37
43 Corporate PR 4 7 4 6 4 5 3 3 36
44 bitemarks 4 6 4 4 5 5 5 2 35
45 Client Service Insights (CSI) 3 6 4 3 5 3 7 2 33
46 KDPaine’s PR Measurement Blog 4 6 3 3 5 3 5 4 33
47 Onalytica – analysing online buzz 4 7 4 2 5 4 4 3 33
48 Heather Yaxley – Greenbanana PR 4 7 3 3 4 2 5 4 32
49 Alan Weinkrantz PR Web Log 3 6 2 2 4 4 6 3 30
50 PR Place 3 6 3 2 4 2 7 3 30
51 Young PR 0 0 4 4 5 5 7 5 30
52 Active Voice 3 6 3 4 4 3 3 1 27
53 Wadds’ tech pr blog 2 6 2 2 4 2 7 2 27
54 PR Voice 3 6 3 2 4 1 4 3 26
55 Wired PR Works by Barbara Rozgonyi 4 6 2 1 5 3 2 3 26
56 Friendly Ghost 3 6 2 2 5 2 3 2 25
57 Thicket 3 6 2 1 4 5 3 1 25
58 Naked PR 3 6 2 1 4 4 2 2 24
59 Tech for PR 3 6 1 1 5 2 3 3 24
60 Valley PR Blog 3 6 2 1 4 3 3 2 24
61 Clogger 2 5 2 1 4 1 7 1 23
62 nerd-in-residence 2 5 2 1 4 4 2 2 22
63 Don’t eat the shrimp – Josh Morgan 2 5 2 1 4 3 2 2 21
64 Indian and Global PR 2 6 1 1 5 2 2 2 21
65 Tech PR War Stories 2 5 1 2 5 1 2 2 20
66 New Marketing 1 2 3 1 5 3 4 0 19
67 DummySpit 2 5 1 1 4 1 2 2 18
68 point being: 2 5 1 2 4 1 2 1 18
69 Fusion PR Forum 2 5 1 1 4 1 2 2 18
70 First Person PR 2 5 1 1 4 1 2 1 17
71 All Things PR 2 5 1 1 3 1 2 1 16
72 Teaching PR 0 1 2 1 4 2 3 2 15
73 A communica-holic’s view of PR 1 4 1 2 3 1 2 1 15
74 Corporati 1 2 1 3 3 1 2 1 14
75 The Jive Man 1 2 1 1 4 1 3 1 14
76 Small Business PR and Marketing 1 3 1 1 4 1 2 1 14
77 PRactical P.R. 1 4 1 1 3 1 2 1 14
78 72 Point Blog 1 2 1 1 4 1 2 1 13
79 The last man in Europe… 1 0 1 1 3 1 3 0 10
80 PR India Post 1 1 1 0 2 1 2 2 10
81 On the face… 1 2 1 1 3 1 0 1 10
82 Spudgun 1 3 1 0 0 1 2 1 9
83 Public Relations Rogue 1 2 1 1 0 1 1 1 8

technorati_reactions.gif yahoo2.gif google.gif blogpulse.gif total.gif

This time I initially tried a different approach: treating the blog scores as a normal distribution so that I could apply the same, proven and statistically sound methodology to every range of numbers and have standardisation across them. This involved calculating z-scores based on the mean and standard deviation, then creating rankings out of ten for each range of z-scores. It sounds simple and I tried to get it to work but it proved fruitless, probably partly because I’m not a statistician but also, I suspect, because it’s not a valid approach anyway. I will however look into this in future.

One of the reasons I think this approach proved so hard was that there are some monster blogs that throw the calculations, namely the top three, Center for Media and Democracy, Online Marketing Blog and, the big daddy, Micro Persuasion. These three in particular, and in fact the next 10 or so blogs, really did throw a lot of the calculations out.

On further examination I noticed that they tended to have a Technorati Authority of 300 or above, so I was tempted to create a ‘super league’ of bloggers to accommodate this. I thought that might prove too controversial and that really we need to have them all in the same table but I do wonder whether I’ve identified two separate populations of blogs within the PR blogosphere: the people like me who tippety-tap away at the end of a hard day’s PR-ing (or, in my case, mostly copywriting), and the ‘super blogs’. What accounts for them? Perhaps they’re run more as an online journal or profit-making enterprise or business; they could have multiple contributors making for a high turnover of quality content; they may have an element of automation that generates traffic; or they may simply be the blogs of people with great clout in the industry who have been around a while, who carry influence that is directly reflected in their scores.

So I’ve decided to stick with my previous method of using percentage bands to create scores with, as far as possible, the same bands used. At least this is standardisation of a kind, but I would very much like to use something closer to an academic approach. If anyone knows a way to do this then please contact me: ideally I would be looking for an Excel spreadsheet into which I can just slot my figures, then it will calculate z-scores for a normal distribution and convert them into rankings out of ten.

Other points to note:

  • I didn’t like the way Alexa lacked figures for quite a few blogs. It seemed unfair to penalise them just because they didn’t use the Alexa toolbar. So, I’ve taken Alexa out. You can see where I was missing data – that’s where you see a score of zero.
  • My Technorati figures are out of ten because, unlike Todd And’s figures, I don’t see the point of making them out of 30. However, I have tried bringing in the rank and blog reactions figures because Technorati seems pretty comprehensive.
  • I’ve included Blogpulse, because the Bloginfluence calculation does. Same with the Yahoo links.
  • I’ve also brought in Google hits and Google Blog hits. I haven’t seen this used before and I don’t understand why not. I think Google hits (looking for the address minus the http:// identifier because that usually returns just one hit) shows a good idea of how much you’re linked to or referred to in the general web world, very like the Yahoo hits score, while Google Blog hits is similar but within the blogosphere. Again, there is data for virtually all the blogs, which is attractive.
  • I realised just before publication that I haven’t hyperlinked all the blog names in the table. You can click them in the PR links blogroll to the left of this page instead.

So what’s wrong with this index? You could say that:

  • It’s unashamedly a home-brewed approach but at least I’m trying to get meaningful figures together.
  • Entry to the list is via my blogroll – which I have built up over months using a combination of recommendation, discovery, and hits from Google news and blog feeds. Over the past few months, if you’ve commented on PR generally, or on my blog specifically, then there’s a fair chance you’re on it. If not then I can add you.
  • It’s not automated so it will go out of date. Strumpette is particularly fond of telling me this.
  • I’m not a statistician, so I’m using basic analysis here. I’m sure someone with more expertise could draw more inferences and arbitrate for some of the difficulties in the data.
  • It doesn’t give any indication of quality. You could infer that quality posts attract high figures but there could be some real gems in there that don’t for whatever reason.
  • In a similar way this also doesn’t show influence. Broadly you could say that popularity does equate to influence but I would expect an analysis of direct and indirect citations using serious automating sentimenting techniques could draw a different picture.

What’s good about it?

  • This time around I’ve tried to make it more consistent. I’ve tried standardising on my analysis and I’ve used metrics that should work for virtually every blog. That’s why I abandoned Alexa this time around and Bloglines last time, because it just didn’t seem fair to mark blogs down if they didn’t have these figures.
  • It uses publicly available metrics that other sites use too. Bloginfluence makes calculations using Technorati and Yahoo links, Google Page Rank is a nice indicator and the Blogpulse data also seemed comprehensive.
  • It doesn’t use any subjective scores based on my personal preferences.
  • It’s very pretty.
  • Finally, whatever you think about my approach or whether or not you like tables, it’s interesting to see who’s where in the PR blogosphere. Well, I think so anyway. Then again perhaps I’m dull. 

There is probably much more to be said on this topic, so I’ll add the disclaimer that I can’t be held responsible for any inaccuracies in this information, or for any consequences if you act on this information, and stop here. You can say the rest! I’m going on holiday.

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11 thoughts on “The Friendly Ghost PowerPR Index for June 2007

  1. Nice list again. Must have took you some time.

    What’s the Technorati Reactions bit? Is that the same as the ‘Blog Reactions’ when you do a URL search in T/rati?

    Weird how I’ve only got a score of 1 and mine’s slightly higher than Drew’s and he’s got a score of 4.

    Or have I gotton it wrong? Either way, nice list.

  2. Hi Stephen,

    OK, I did check all the figures, I promise, but I’ve been through all the Technorati figures again and yes, there was a small chunk that seemed to have shifted. So, I’ve fixed that and now you’re comfortably above Drew. Many apologies – I don’t want to publish and be damned! I will double (actually triple) check all the figures tomorrow cos I want this to be right. Regarding time, well it’s the initial setting up that takes the longest, particularly figuring out the best approach to analysis and enabling ready transfer from Excel to WordPress, but now it’s just data entry which takes an hour or so – not too painful.

  3. Ha! Sorry mate – it wasn’t a stab at you (or my pal Drew either).

    You know what happens when you put a blogging list together – some egos get stroked and some don’t. Good for you for taking the time to do it.

    P.S. Which agency are you from? :-)

  4. Good work Ghost.

    For future league tables, how about you put in brackets the ranking for each blog the previous month? Then we’ll be able to see who’s in the ascendancy and who’s dropping like a stone.

    Happy holiday!

    TWL

  5. No worries – I know it was just a query but I really do want to make this work properly.

    I’d rather not say which agency I’m from, not least because it has staff blogging rules which state we shouldn’t be identifiable as its staff. Strange, I know, becayse most others consider it a way of engaging, promoting their cause, etc. Perhaps I’ll get that changed.

    But also, I like to preserve my anonymity – hence the pseudonym – simply so I can mouth off and say what I like without fear of redemption.

    I know some of my colleagues subscribe but even within the agency it’s not widely known that I run this blog. And I’d like to keep it that way!

    Cheers
    FG

  6. Hi TWL – you must be posting at exactly the same time as me!

    I did consider it this time around but now that I’ve standardised on which metrics to use and the spreadsheet’s all set up, I think I’ll do it from now on. Power150 doesn’t, but that doesn’t mean I shouldn’t (fight your way through those negatives!).

    Regards
    FG

  7. FG:
    You’re quite the blogging statistician.
    Thanks for the list – great resource.
    Very flattering to be included!
    Looking forward to visiting a few new blogs.
    Barbara Rozgonyi, Wired PR Works

  8. Pingback: Can the PR power be tracked as well as counted? « Heather Yaxley - Greenbanana views of public relations and more

  9. Great stuff in here. Love the disciplined approach and clear explanations. What is missing is whether these things are going up or down over time. I’m tracking my own ranking but I’m wondering if we couldn’t feed this all into our Dashboard system so each blog could track his/her own results over time?

  10. The idea of individual blogs tracking themselves is a *really* good one and is in fact on my list of things to think about.

    I was going to suggest at some point that the list could be made up of people submitting their own figures instead but decided I needed to put *some* effort into this, at least at the very beginning.

    Also the movement is of critical interest. I’m hoping to build this into future releases, although note that Todd And’s Power150 doesn’t calculate this information (it’s a bit tricky shuffling things around in Excel but I’m sure I can figure it out).

    The more I think about it the more we really do approach an ‘index’ like a financial index, in that we could analyse the top five climbers/droppers, the most active, that sort of thing. It would be fascinating to see this in real-time using ASP solutions such as those provided by KTS.

    To help me with all of this – the problem of it taking time to compile, plus that of movement – I’m also looking into automation tools such as the Easy Bee which seems to hold promise although I’ve yet to decide whether this really will do what I need.

  11. Pingback: Social media index « Technobabble 2.0

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