Bored of sorting massive lists of links in all kinds of different directions to understand the link profile of a new site?

Struggle to understand how to gather actual insights about link profiles from lists of thousands of links and persuade management of the actions needed?

Don’t panic. Help is at hand.

I’m going to share some data visualisation tips today that I reckon I could use to beat up on Rand in a presentation-off (umm, again). We have recently been doing some deep dives into clients’ and prospects’ link profiles which gave me an excuse to mash up some Linkscape API data in Excel. I’ve used Linkscape data, but you could use any link analysis tool you like as long as you can get some metric to sort the linking domain by (I have used domain mozTrust in most of the examples below). Equally, I’ve used Excel, but you can use any data analysis package you like. If you want to use Excel, you will need the Data Analysis Toolpak (for the histogram function).

I’ll get into how to make the charts in a minute, but first I’m going to just show you some pretty pictures:

Impress the boss

This one is of questionable use (I think there are better ways of actually visualising the data) but it’s pretty, and bosses like pretty (allegedly). This is a surface chart of number of linking domains by domain mozTrust shown across 4 data points – all links, links to the homepage and links to the next two strongest pages:

The bit of insight this does give us at a glance is that the vast majority of the site’s very low DmT links go to the homepage and that the most trusted domains linking to the site (DmT >= don’t link to the homepage or the next two strongest pages.

The same chart just showing links to the homepage compared to all links which shows the top end a litle more clearly:

Gathering insights

I think this data is actually easier to see as a line chart like this (locations A and B are the top two strongest pages on the site after the homepage):

What we just about see here is some bumps up at the top end of the DmT scale in the light blue line which is the same bit of insight I mentioned above.

Drilling down

Diving into this data to show only the top end of the DmT scale, we get:

And we see that although the homepage and these top two location pages are the most powerful pages on the site, they are not the ones with the links from the biggest / most trusted sites. This is an area for further examination that would be hard to discover by looking at endless lists of links.

This is just an example of the kind of insight you can gather. I’m showing off tools and techniques here rather than specific insights. I’ll leave you to do your own playing to discover interesting things about your clients and competitors. I didn’t know what I was going to find when I started diving into the data for this site. You likely won’t know either, but graphs are great discovery tools. Sometimes, of course you find nothing of interest:

Comparing just the top two pages doesn’t give us any very meaningful insights except that the big links out at 6.5-7 DmT to location A probably explain why it’s more powerful than B. It might be more insightful at a lower granularity.

Equally, I haven’t yet learnt to understand the meaning that I am sure is buried in charts like this one:

This is the number of links to a whole site by the mR of the linking page. Like the mythical guys who can understand network traffic by watching LEDs blink on routers, I’d love to be able to look at this kind of chart and really understand things. The closest I’ve got so far is that I think these charts should look roughly smooth in the absence of manipulation. If we assume that the difficulty of acquiring a link is roughly correlated to its strength and that we get links at a rate inversely proportional to their difficulty, then I think this chart should look roughly like a Poisson distribution:

Which this one does, so I’m happy.

Persuading management / bosses

The next thing that some of these charts helps with is making the case to management when you know something is true, but they need more persuading. This next example takes two different sites (neither of them is the site above) that are in different industries but have remarkably similar link characteristics at the macro level (don’t ask me how I found these sites – I am just that sad). The spider chart shows how similar they are:

However, if we dig in a little further, we find quite a difference behind the scenes:

The red site seems to have loads more decent links (mR 4, 5, 6) than the blue site. So how does the blue site end up with similar domain metrics?

It’s all about the relatively small number of very powerful links the blue site has. Zooming in on mR 6 & 7 links:

f you were just to look at this chart, you might imagine that the red site was getting more juice passed via these links than the blue site is. However, you’d be being fooled by the logarithmic scale. In terms of total juice passed by just these mR 6 and 7 links, the actual story is:

n other words, the blue site is competing almost purely on the basis of the big mR 7 links it has that the red site doesn’t. That’s kinda interesting in terms of strategy generation isn’t it?

How do you do this analysis?

Pretty much everything in this post was generated using the histogram function in Excel running over Linkscape API data. It’s pretty straightforward with the online help. The only gotchas I noticed that you might need to know about were:

1. Align the ‘bins’ (which are the x-axis values on most of the charts above) either with mR / mT intervals (e.g. 1, 2, 3, 4, …) or go much more granular (e.g. 0.1, 0.2, 0.3, ….). Anything in between tends to generate artifacts
2. The bin range has to be on the same sheet as the data – if you try to pull in a bin range from another sheet, it fails silently
3. If you want to do the surface chart, you need to do some interpolation between your points. In the examples above, I just did a linear interpolation (i.e. drawing a straight line between the different page levels) – so if the homepage has 100 mR 2 links and the next page has 50 mR 2 links, I just created 10 imaginary pages with 55, 60, 65, 70… mR 2 links to spread the surface out far enough to see it. This may not be the best way of doing things. I’d love to hear from anyone who has a better method

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‘ve been connecting with a lot of site owners who are re-entering or ramping up their efforts in the blogosphere. I suspect this has something to do with the focus on content creation + linkbait in the SEO world’s dialogue as well as the potential new traffic streams bloggers are feeling from the surge of linking via Twitter. Whatever the case, there’s a few critical pieces that can help make for greater SEO value from blogging and feeds in general (and most of these haven’t been covered in my previous posts on blog optimization).
#1 – Control Your Own Feed

It’s hard to write something better than Danny Sullivan’s terrific piece on Staying Master of Your Feed Domain. The concept is that you can utilize services like Feedburner, but you want those feed URLs to originate from your domain (so you keep the link juice you’re earning):

To make this work, you need your hosting provider to create a CNAME entry for a new subdomain you’ll create. If they can’t do that easily for you, find a new hosting provider. I highly recommend ours, Tiger Technologies. Cheap, easy for you to do this yourself, plus Digg-tested.

For me, I simply make a subdomain called feeds for any domain I’m dealing with. Since searchengineland.com is our main domain, our feed domain is feeds.searchengineland.com.

Once I’ve created this, the MyBrand magic lets FeedBurner take control of where the domain points to. That let’s me turn the FeedBurner feed address for us into http://feeds.searchengineland.com/searchengineland.

But wait — I thought it was about keeping control? Relax. I’m giving them control because I want to. If they went all evil, I’d just change the CNAME record and point that subdomain to wherever I want. I own the domain. I control where it ultimately points to.

Sadly, SEOmoz doesn’t do this, and it’s a pain to switch (though at some point, it may be worth that trouble). If you’re new to feed publishing or are early in the game, it makes a lot of sense to move now, before it becomes more painful.
#2 – Get Your Feed Listed Across the Web

There are some great directory lists like this one from TopRank Blog and this one from Ari Paparo. However, my advice here would be to go after not just the generic lists, but the more specific feed lists, aggregators, portals and yes, other blogs & news sites that can put your posts in front of an audience that’s passionate about your topic.

In the technology field, for example, places like Alltop, Techmeme, PopURLs, even the NYTimes technology page list feeds from a variety of sources. Those are amazing links and incredible sources of traffic, too (Alltop recently entered SEOmoz’s top 30 referring domains for traffic to the site). If you’re committed to getting the most out of your feed, you need to identify the portals in your niche that command share, traffic and page views, make a feed worthy of being posted and get their attention. Emails are surprisingly effective, but nothing beats an in-person conversation.
#3 – Use Absolute URLs in Your Feed

Scrapers, both good and bad, are going to scoop up your feed and re-publish it, including the links. If you use absolute URLs in your markup (e.g. http://www.seomoz.org/blog/rand-loves-the-nfl) rather than relative URLs (e.g. /rand-loves-the-nfl) your chances of getting link equity and PageRank back from those who re-publish goes up significantly. Note that this is a general disagreement with JohnMu (who posted on this topic last year, though not specifically as it relates to feeds).
#4 – Record Feed CTR & Links You Earn as “Conversions”

Through feed tracking, you can determine the posts that received the greatest/fewest clickthroughs. You can also use your web analytics or tools like Linkscape, Yahoo!, Technorati or Blogscape’s SMM Prototype to see how many links each post has earned (Backtweets is another good one if you want to record tweets). Treat those links andd clicks like a conversion – write more posts like the ones that have success and shy away from the posts that don’t earn much love/attention. Great bloggers don’t start out great (I certainly didn’t). They learn over time what’s successful and effective and get consistently on that track.
#5 – Full Text Feeds are Generally Better for SEO

The argument over partial text vs. full text tends to be about earning the clicks and interactions on your site (full text means people can read off-site and may never click through, while partial text really annoys some subscribers), but from a raw SEO perspective, full text has a few benefits.

* All things being equal, you tend to get more subscribers with full text than partial, which boosts your numbers, gives you wider distribution and increases the liklihood you’ll earn a link from those readers.
* Full text feeds get re-published in full, and that means links further down in the content potentially pass value back to you.
* Blog and feed lists are sometimes picky about partial feeds, and may opt not to include your site.
* Potential distribution partners like full text, because it gives them the opportunity to keep the visitor on their site (but if these deals get done, they almost always mean link juice back to you).

Obviously, business goals may overrule this recommendation, but it’s wise to be aware of the possible impact.

Since it’s a short list, I’d love if anyone in the comments can link to posts or recommendations (yes, even if it’s your own stuff!) that can also be helpful on this subject.

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Well now, it’s been quite some time since an article was posted on here so I feel like I owe everyone something really good.

It’s common in seo to make suggestions to potential clients to not go after that elusive one word phrase. But by doing so, and with seemingly all seo professionals on board, has it gotten easier to get ranked for one-word phrases?

I’ve personally have been able to get some top rankings for clients of mine within the past year – I’m not saying this to brag, but if everyone’s drinking that kool-aid, how will anyone know how hard it is to go after one word?

Now, there are those that will tell you that a one-word phrase doesn’t convert. In my experience, these phrase drive a ton of traffic to the site (as much as up to 10k unique visitors a day) – of course not all of them convert.

But about 20% do.

Yes, 20% of all people coming in on a one-word phrase converts at that rate for something on the site. Maybe not for the phrase that brought them in, but that person converts on something.

Now, using WebTrends or Google Analytics will tell you the phrase on which the person came in from, but to get the granular level detail, the only system I’ve been able to come up with and rely on is a site database capturing system. It’s been custom created, but it can track all the pages visited and will tell you that if someone originally came to the site for the term “KVM” but ended up buying USB Cables, that data is retained.

Now, all of a sudden, those one-word phrases are looking pretty good. And, with soo many seo’s purposely not going after them, I think it presents an opportunity to grab those top rankings for those magical traffic drivers.

So, go get those words!

-To your online success!

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