I was reading comments on Krugman’s The Third Depression yesterday (which has gotten a lot of attention as he used the “D” word to describe the world economy) and wondered if the OP-ED could be analyzed – remembered that BackType can look at specific URLs or websites and determine the recent conversations around them – but I haven’t found the BackType particularly useful because of it’s limited scope and time-frame.
As soon as I got to BackType, I noticed some changes which are moving in the right direction and now allows comparisons between up to three URLs ac cross more Social Media Channels (Facebook, Twitter, FriendFeed, MySpace – etc).
Going from the general to the specific – I compared The New York Times with The Huffington Post and then saw I could add The Wall Street Journal; initially I thought of my friends at Adaptive Semantics and the reality Huffington Post may be surpassing the New York Times in traffic, as I mentioned in a previous post.
I’m able to look at 6 months of trend data in a new visualization I don’t think they did not have before. I also was able to add more URLs to my comparison by manipulating URL string in the browser address bar (not sure what the limit is).
There’s another report on Audience that wasn’t there before.
The chart above implies that the New York Times “community” of Twitter users actively shares more links with each other about the New York Times stories than users who go to the Huffington Post.
There’s also a link on the BackType site to sign up for a private beta account to test their new analytics platform – this looks promising. I already had a regular account so I logged in and found what looked to be new measurements – if they were there before I didn’t notice it – in this case, shared links across several Social Media Channels related to my Twitter Account.
But what I really wanted to do is analyze the impact of Paul Krugman‘s article in comparison to other stories or articles going on at the same time or in a related time frame – this is more like a problem that you might want to solve in PR (not that I’m particularly tied to Public Relations – I’m not – it’s that I see opportunities and insights in any field I get involved in).
One application would be to look at all the OP-ED articles at New York Times over the last two days (there are other types of comparisons we could do, as well).
By far, Paul Krugman’s article is the most shared in Social Media channels of those published this weekend in the New York Times (across the channels being measured).
Clearly, BackType wasn’t designed to compare 6 articles – but you can jimmy rigg more articles to the URL string, as I mentioned earlier (though the graph might get hard to read).
True, we don’t know what those numbers in the table above really mean and they are not tied yet to site analytics (or if there is a way to come up with a composite score by weighting – something that would fit the Digital Footprint Index I wrote about last year) – so we don’t know if the “Social Impact” translates into actual visitation and activity on page because we don’t that data available to work with (ie: The New York Times WebTrends or Omniture account access).
Still, what BackType does with comparing Social Impact of URLs across channels is something Radian6, Sysomos and some of the other platforms for “Social Monitoring” also offered – they have the data – they just are not designed to answer the same questions – but in this case, the questions should be answered.
I was not able to compare “audiences” across different URLs – apparently it only works for a single URL but I got something that is “priceless” in the summary tab (which you have to do in the individual URL level right now) – the estimated number of individuals who might have read or been influenced by Paul Krugman’s article, 2.2 million of the online audience – something no other platform I’ve seen offers – at least, not in this form and not at this granular page level – and this platform is free.
Also, the private beta claims to offer more “accurate” numbers past the 2.2 million estimated – will be looking forward to getting access to the beta.
Remember – I’m getting a estimated reach number on a individual page – not the website – the page or article itself.
I can see the lightbulbs going on in your heads now – as they are going on in mine – if I could do this with a few OP-EDs in the New York Times – why can’t the New York Times do this with all their online content – period? My guess is, they could – but it might be extremely manual – though there is an API that BackType offers – and with some programming – I would think this would be an excellent area for Newspapers to get involved in, or Magazines, or PR Firms (chuckle).
Let’s turn the key one more time – what if we wanted to chart the effect of one story or online placement on another? Suppose your putting a multi channel campaign and you want to see how your messages are influencing each other – or even, if there is any “lift” from one message to another? I think BackType might be able to do something like that. While I have personally worked on campaigns where this question comes up, the events (or URLs) are often separated by a week or two – I don’t have an example on hand to use that I can talk about so I’ll do something else by offering to show Paul Krugman’s The Third Depression was discussed by his followers in other online publications.
In this case I took Krugman’s OP-ED and compared it with 4 others in my RSS feed that referenced his article today.
There was a little interplay between Ezra Klein’s article in the Washington Post and Paul Krugman’s OP-ED in the New York Times – but little else is showing – I’m pushing BackType to it’s limit graphics wise – so the urls cover the legend data.
You can get influencers for each URL (but not all of them, together) – and I won’t go into that here – this post is long enough – but lets’ just get the estimated reach numbers of each article – just to end this long post.
Ezra Klein – Does income inequality cause financial crises? This page reached a maximum of 33,737 people (estimate)
The Third Depression – TalkLeft: The Politics Of Crime This page reached a maximum of 3,497 people (estimate)
Ezra Klein – Wonkbook: Robert Byrd dies; G-20: Prelude to Depression or wise turn from spending? This page reached a maximum of 31,036 people (estimate)
Op-Ed Columnist – The Third Depression – NYTimes.com This page reached a maximum of 2,235,646 people (estimate)
memeorandum: The Third Depression — Recessions are common; depressions are rare. (Paul Krugman/New York Times) This page reached a maximum of 5,695 people (estimate)
That’s about as much as I’m going to say – if you want a report that goes far beyond this – your going to have to have to hire me to produce it (btw, this page is going to be revamped soon – but you can reach me though it).
The weird thing about all of this is the free tools, in this case, BackType, is actually superior to any to the paid tools for this particular use case – that might not be true in 6 months – but it is true today – which shows just how volatile and changing online analytics and audience measurement is becoming, especially in Social Media.
I can’t even count the times I’ve been out and forgotten to check-in at various locations, robbing myself of precious Foursquare points. With geofencing, I could have been automatically checking in as I went from place-to-place, or perhaps a push notification would have reminded me after I was within the perimeter of the geofence for a certain amount of time.
