It is possible to properly attribute blekko search traffic referrals by implementing advanced Web analytics configuration techniques.

Is the extra effort worth the trouble? Certainly investors are betting on blekko. In late September, blekko received an addition $30 million investment, half of which was from Russian search engine Yandex.

Why Web Analytics Systems Can’t See Blekko’s Search Keywords

The underlying difficulty many Web analytics systems encounter in recognizing blekko as a search engine is due to a reliance on search engines to specify the search keywords in the request for the destination webpage by using parameters in the referrer URL.

Unfortunately, blekko deviates from what has historically been the de facto standard for transmission of search query information. In the absence of advanced tool configuration, traffic from blekko will show up in a referring sites report instead of an organic search traffic report.

While this scenario is better than nothing, it makes keyword analysis difficult. Knowledge and analysis of search query keywords is a key element of search marketing as a user’s search keywords express their intent when selecting a site from a listing of search results.

In the following discussion, Google Analytics will be used to illustrate solutions, but the same data transformation logic can be applied to other tools as well. The technically inclined are encouraged to read on. Everyone else might want to pass this article on to their technical staff for analysis and implementation.

Deconstructing & “Fixing” The Blekko Search Referrer

A typical blekko referrer URL contains blekko’s domain name, the parameter ws and the user query. Spaces between multiple query words are replaced with plus signs.

In the following example, the user’s search keywords stop+blekko+indexing follow http://blekko.com/ws/ in the search engine results page URL, visible in the browser address bar.

Figure 1: A blekko search result with user keywords in the result URL

Unfortunately, this isn’t in the form most Web analytics systems were designed to recognize when processing organic search traffic.

The URL piece ws/ needs to be expressed as a parameter, in the format name = value, i.e. ?ws=stop+blekko+indexing.

Thus: http://blekko.com/ws/stop+blekko+indexing needs to be transformed into http://blekko.com/?ws=stop+blekko+indexing

Two Possible Solutions To Solving The blekko Attribution Problem

There are two potential solutions to proper recognition of blekko as a search engine by Web analytics systems. The first approach is to modify the raw data sent to the Web analytics data collection system. The second is to transform the data collected by the Web analytics system before it is processed for reporting.

Option 1: Modify The Search Referrer Sent To Google Analytics

The blekko referrer URL needs to be transformed into the de facto standard format which includes the user query using URL parameters, e.g. ?query=keywords, a format recognized by most Web analytics systems. JavaScript is well suited to this type of task.

The HTML standard doesn’t allow direct manipulation of the document (page) referrer, but the referrer sent to the Google Analytics data collection system can be changed by assigning the modified value to a special parameter, _setReferrerOverride.

In the asynchronous Google Analytics tracking code which follows, the code in bold will transform blekko referrer URLs and assign the result to _setReferrerOverride.

The code:

• assigns the page referrer to the variable blekref
• tests to see if blekref contains the string http://blekko.com/ws/
  • if so, tests to see if http://blekko.com/ws/already contains URL parameters, which start with a ?
    • if so, substitutes the ? with a & which indicates successive URL parameters
  • substitutes ws/ with ?ws=
  • places the modified URL in the Google Analytics variable _setReferrerOverride

<script type="text/javascript"> var _gaq = _gaq || []; _gaq.push(['_setAccount','UA-xxxxx-1']); var blekref = document.referrer ; if (~blekref.indexOf('http://blekko.com/ws/')) { if (~blekref.indexOf('?')) { blekref = document.referrer.replace('?','&'); } blekref = blekref.replace('/ws/', '/?ws='); _gaq.push(['_setReferrerOverride',blekref]); } _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); </script>

Note: this code will need to be modified if blekko changes their URLs, such as using www.blekko.com in addition to blekko.com.

As with any code changes, do be sure to consult current Google documentation and fully test changes before putting them in production. JavaScript errors in a page can stop successive JavaScript from being executed. No warranties are provided, implied or otherwise!

Tell Google Analytics How To Recognize blekko As A Search Engine

Once blekko’s referrer string has been transformed into the standard query parameter = keywords format, the second and final step is to add blekko to Google Analytics’ list of known search engines.

This also has to be done within the Google Analytics tracking code inserted in each page of the website.

The syntax to add a search engine is of the form:

_gaq.push(['_addOrganic','blekko','ws']);

where blekko is a string in the referrer domain and ws is the query parameter name.

This has to be inserted somewhere before the ['_trackPageview'] call, i.e. from the above example we can change

_gaq.push(['_trackPageview']);

to

_gaq.push(['_addOrganic','blekko','ws'],['_trackPageview']);

A more in depth discussion on working with the _addOrganic configuration option can be found in an article on Google Analytics search engines list customization.

Tracking Page Speed In Google Analytics?

During testing, it emerged that Google Analytics would ignore the value of _setReferrerOverride if _trackPageLoadTime was specified.

Using the Google Analytics debugger, it became clear that Google was deprecating _trackPageLoadTime so the message is simple: remove _trackPageLoadTime from existing tracking code to avoid unforeseen consequences.

Option 2: Transforming Collected Data

Should sites not be able to modify their Google Analytics tracking code, or should their Web analytics system not provide a referral override option, there is a second approach which should work as well. The technique involves transforming the collected data before reports are created.

In Google Analytics, Profile filters perform this task. Filters are a wonderful, but underutilized, Google Analytics feature and this is a great example to show off their potential. The process is:

1. Identify search referrals from blekko
2. Update the medium, source and term campaign fields accordingly.

Unfortunately, Google Analytics only allows a profile filter to update one field at a time, so it will be necessary to create multiple filters.

To do this, enter the Google Analytics administration area and create new advanced custom profile filters as illustrated below. Filters can be created at the account level, making it easy to quickly apply the filters to multiple profiles.

Figure 2: Blekko set campaign medium filter.

The above filter selects referral traffic from Blekko which contains /ws/ in the URL and changes the Google Analytics Campaign Medium from referral to organic (required for blekko traffic to appear in the organic search report).

Currently, it isn’t strictly necessary to include the Field B requirement, but it may be helpful in order differentiate from paid search should Blekko offer it in the future. Note that the values referral and organic must be in English, even if the Google Analytics interface is in a different language.

Figure 3: Blekko set campaign source filter

Google Analytics will automatically identify blekko.com as the source of traffic, however, some may want to see the source report as “blekko” instead of “blekko.com” in their reports, so as to be consistent with the other search traffic sources. The above filter, which is optional, will do just that.

Figure 4: Blekko set campaign terms filter

The set campaign terms filter captures the user’s search query and places it in the Campaign Term field, the source of the keywords which appear in the Google Analytics organic search traffic report.

The key is in the regular expression specified in Field A:

^http://blekko\.com/ws/(.+)\??

It says, select referrers which start with http://blekko.com/ws/, capture everything that follows up to a question mark, which may or may not be present, and put the result in the campaign terms field.

Astute readers might note there is still one problem remaining: multiple keywords will still be separated by one or more plus signs which should be converted to spaces.

Unfortunately, it doesn’t seem that Google Analytics supports global (multiple) substitution using filters, but in the spirit of crowd sourcing, a reader may want to chime in to improve this last step.

One work around might be to create multiple substitution filters which will replace a single + with a single space:

Figure 5: Filter to substitute one plus sign, +, in blekko search keywords, with a space

Once the profile filters are created, they need to be activated by apply them to each Google Analytics profile.

The order in which the filters are applied is not important, with the exception of the plus sign substitution filters, which must come after the set campaign term filter. A Google Analytics best practice is to keep at least one profile without any filters as once data has been transformed by filters as there isn’t any way to revert filter changes.

An unadulterated profile is also helpful in troubleshooting any issues which may arise. New filters can (and should) be tested on a new “throw-away” profile before being applied to production profiles.

A Note About blekko’s Slash Tags

One of Blekko’s distinguishing features is the ability, encouraged by blekko, of users to further restrict their search queries using search operators and filters, what blekko calls slashtags. As the slash tags do condition the user’s query, and to a degree express the user’s intent, neither of the approaches illustrated above attempts to remove slashtags, if present, from the search query keywords.

For our purposes here in Link Week, I’ll be reviewing the Site Explorer, Backlink History, Neighbourhood Checker, and Clique Hunter.

Basic Tool Functions

First up is the Site Explorer, which takes your URL and returns tons of information: Summary, Top Backlinks, Referring Domains, and Top Pages. Each section is represented on the results page, but you can click on the tabs and get more in-depth info if you like. You can choose the Fresh Index or the Historic Index and run the report on either the domain, the subdomain, or the page itself.

My favorite tool, the Backlink History, also shows up here in the results page but not in its own tab. Now, a note on the Fresh vs. Historic Index: the Fresh index gives you information from a rolling 30 day period and is more, um, fresh, while the Historic index gives you everything in Majestic’s history for a site.

The Domain Information gives you your Referring Domains and External Backlinks, so you can quickly tell if you have a lot of sitewides (if you have 10k backlinks and 10 referring domains, yes, you have a lot of sitewides.)

Your backlinks and referring domains are broken down into educational and governmental and the following information is displayed: Referring IP Addresses, Class C Subnets, Indexed URLs, Images, Nofollow Links, Redirects, Frames, and Deleted Links. You’ll also see a number called the Majestic Million which is a list of the top one million domains as rated by Majestic SEO.

The Backlink History shows your 2 charts: 1 is your external backlinks discovery over the past 12 months and the other is your referring domains discovery over the past 12 months. You can click on these two charts in order to go directly to the Backlink History tool and get more information.

The Top Backlinks area shows the Source URL, Anchor Text, Target URL, and Last Crawl Date.

The Referring Domains area lists the top domains that link to your URL.

The Top Pages area lists your top pages: Title, URL, AC Rank (which is a measure of how important a page is based on the number of unique referring external root domains), Date, External Backlinks, and Referring Domains.

How To Interpret The Link Data

This is a wealth of information for analyzing a backlink profile. If you’re analyzing your own site, I see numerous uses:

• Identifying the top pages that link to you and making sure these links stay up. It’s tricky to watch all your backlinks if you have a lot of them, but if you’re too overwhelmed, just identify the top ones and track those.

• Identifying your site’s top pages so that you can continue to build good links to these in particular (and go through your site to ensure that your top pages link to other pages that you think are critical but aren’t viewed as top ones just yet.)

• Identifying pages of lower importance so that you can work on their content in hopes of generating more backlinks.

For competitive analysis, this information can easily be used to see where you stand compared to others in your niche.

For potential link partners, use this data to identify the top pages on a site and go after a link on that page. With so much information, there are truly countless ways of using this data to help better your link building efforts.

Note: I’d love to include a screenshot here but the information you get takes up a large amount of space and I don’t think I can do it justice. Since you can see the Site Explorer for free, even if you can’t get all the detailed data, I’d suggest checking it out for yourself.

Next up is the Backlink History, which has been something I have relied upon many times (especially when clients are trying to convince me that they know their competitors aren’t matching/beating their own link building efforts.) You can again use either the fresh or historic index here and you can compare up to five domains. Currently, subdomains are ignored.

This tool shows backlink discovery by month, so let’s get a screenshot of a few SEO sites to compare (Disclaimer: I write for the three sites used here):

What you see here is the default view, which is a set of two graphs: backlinks discovery and referring domains discovery in non-cumulative view.

You can view the charts in Monthly, Cumulative, or Normalized forms, see them as a Spline, Line, Column or Area chart, and choose whether you want to see data from 1 year, 2 years, 5 years, or all time.

Majestic SEO advises that you use the Normalized view and/or compare domains in order to get the most comparable data down at the bottom of the page. In these charts, you’ll see how you compare to your competitors.

It’s interesting to compare the two charts as well because of the difference in referring domains and backlinks discovery (and for those of you who are new to link building concepts, referring domains would show a value of 1 even if there were 150 links to a site on that same site, but it would show a value of 150 if you were looking at backlinks.)

According to the chart in the screenshot, Search Engine Land has traditionally built more backlinks than the other two but the referring domains numbers between SEL and Search Engine Journal are quite close. (Poor SEO Chicks.) This would make me suspect that Search Engine Land is generating more instances of multiple links on the same domain. In any case, this is a seriously great tool to use to see how your backlinks/referring domains compare with others.

Now we’ll turn to the Neighbourhood Checker, which accepts either a domain or an IP address. As usual, you can choose either fresh or historic data. This tool shows you the most backlinked domains hosted on any IP or subnet so that you can get a better idea of potentially dangerous cohosted sites.

When you enter your site or IP, you get two lists: one that shows what is cohosted on your IP, and one that shows what is cohosted on your subnet. Here’s an edited screenshot, as I don’t want to rile anyone up:

The data shown lets you check the site out by visiting it, going to the Site Explorer, or seeing its Backlink History, so checking out what’s cohosted is pretty simple. You’re shown the location of the IP, referring domains, and external backlinks to each domain listed.

I would recommend using this tool in conjunction with others that give you a fuller picture, of course, since with the rise in spammy sites over the past decade, it’s truly difficult to run a report like this and not find something that might seem a bit dangerous at first glance. There are many ways in which this data could be interpreted, so I’ll leave that up to you.

Last but not least is the Clique Hunter which allows you to enter up to ten unique root domains (with a minimum of two) and shows you a representation of the main sites that link to the sites you’ve entered, therefore identifying your cliques.

The thickness of the line indicates that more links come from that domain to the domain it points to, so as you can see in the screenshot below, there are lots of links on blogspots that point to Search Engine Land.

Further down, you can better filter your results by increasing your minimum number of matches, number of results shown, and the depth of analysis. You can then sort the data by about a dozen metrics, ascending or descending, then sort further (like you’d do with a spreadsheet.)

You’ll see a list of domains along with the number of linked domains to those sites, matches, Alexa rank, and numbers for your queried domains. For each domain listed, you can visit the site, view the backlink history, see it in Site Explorer, or create an exportable CSV report. There are also links at the bottom that will allow you to view the queried domains in summary form on the Bulk Backlink Checker and the Backlink History.

Interestingly, this tool was inspired by Aaron Wall’s Hub Finder (my favorite of his set.) Just as with the Site Explorer, there is a multitude of great information here and I can see tons of ways to use it for link building but the main one is simple:

Identify the sites that link to your competitors but not to you, yet. Pursue links on those sites.

It’s worth mentioning that Majestic has a cool plugin that works in either IE (gasp) or Firefox. It lists Majestic SEO as one of your search engines so you can simply choose it and go to the Site Explorer page for a site.

Link Tool Takeaways

So there you have it…another amazing suite of tools that can ramp up your link building efforts, complete with a blog, video tutorials, and a constantly updated index.

Overall, Majestic is extremely easy to use and is quite intuitive, so even for a true beginner, I can’t see these tools being overwhelming. The amount of data could potentially overwhelm someone but honestly, that’s not a bad thing in my opinion. I’d rather have more than less. With the different packages available, even a small or solo operation would be well-advised to use this system.

Majestic also has a great blog that is searchable and contains posts about latest updates, along with tons of training posts and videos. If you can’t figure out how to use one of their tools, it’s not for their lack of trying. I actually found it all quite straightforward and intuitive though, and even for a novice tool user, I don’t think you’ll be stumped.

Finally, there is the API: I did not test this but it’s worth noting as it enables you to access key functions and gives you a development area where you can test applications without affecting your subscription resources (which include set numbers of reports you can run a month, for example.)

While we’re on the subject of reports, there are two types: standard and advanced. All subscription plans provide access to standard reports, which can be run for any website. A standard report gives you what Majestic believes is the key set of information including an overview, backlinks information, and anchor text information. Advanced reports gives you absolutely everything you could possibly want to know about a domain. These reports are also downloadable so that you can further analyze the data.

To sum it up, this is a massively powerful set of tools if you’re interested in link building. It’s intuitive, fast, and due to the different tiers of pricing, there’s an option for everyone. If you need less link-focused tools this may not be the suite for you, because there are no rank checkers or code validators, but for link building, it’s seriously top notch.

If you click on the SEO Tools link on the topnav, you’ll see a list of both free and paid tools. However, other pages on the site did lead me to a few other tools not specifically listed there, so I’ll do my best to give you a comprehensive list of what’s out there with regards to link building tools, since that’s the focus of this review.

Listed on the nav bar, we have the following tools that I have reviewed for link building purposes:

• Local Rank
• Hub Finder
• Competitive Research

Other particularly interesting public link tools I found through digging on the site include:

• Link Harvester
• Link Suggestion Tool
• Link Popularity Comparison Tool

There are also free Firefox add-ons (SEO for Firefox is included in this review), keyword tools, analytics tools, PPC tools, a rank checker, a site health check, and more. That’s one thing that makes this suite of tools so valuable; you don’t get tools that are only built for one aspect of marketing.

SEO For Firefox Plugin

First up is the free plugin SEO for Firefox. The SEO for Firefox plugin is truly one of the most indispensable tools out there in my opinion. All of my link builders use it and it’s my go-to quick analysis tool.

PageRank is the only thing that is automatically pulled into the tool, so if you want other metrics, you’ll have to customize it. There is some very helpful advice from Aaron about how to configure the extension to use the least resources so I’d highly recommend reading his instructions.

This extension can easily be turned on and off so that it’s not running nonstop, which I really like. Firefox is slow enough. Obviously, there is a lot of link data here. Metrics are as follows (listed in as small a space as possible since there are so many):

PR, Google Cache Date, Traffic Value, Age, del.icio.us, del.icio.us Page Bookmarks, Diggs, Diggs Popular Stories, Stumbleupon, Twitter, Y! links, Y! edu links, Y! gov links, Y! Page links, Y! edu page links, OSE links to page, OSE links to domain, Blekko domainlinks, Technorati, Alexa, Compete.com rank,, Compete.com uniques, Cached, Dmoz, Bloglines, Page blog links, wikipedia, dir.yahoo.com, BOTW, Business, Majestic SEO linkdomain

You can doubleclick a metric in the popup window and be taken to the source for further digging. I didn’t get data for many of the metrics, however, but issues like this are discussed in the instructions, as some of the data sources might not always be reliably pingable.

You can use SEO for Firefox as an on-demand service, like I do (which means that you can easily just rightclick, go to SEO for Firefox, and look up the page) or you can run it all the time and you’ll see the data at the bottom of the SERPs like this:

Again, the data you see is clickable and leads you to the source for more information.

Another handy part of this tool is that you can highlight nofollow links and external links and see images’ alt attributes through SEO XRay, which is a feature on the extension that gives you even more cool information such as is seen in the following screenshot:

How would you use this to help build links?

For starters, it tells you just about everything you need to know about a site that you’re thinking about getting a link on, and it’s a great way to do some competitive analysis. It’s not a tool to show you where to build links, but it’s a great analysis tool to firm up your decision.

As always though, don’t let metrics alone be the deciding factor in whether or not to pursue a link. Some sites may show low metrics for certain things (like the dreaded PageRank) so use caution when evaluating a site strictly by numbers.

Pros

• I love the on-the-fly capability of this, as I hate running tools that slow down my browser.
• I like that you can either see the desired data by clicking and grabbing it on the page, or by viewing it in the SERPs.
• For a quick overview on a site, I don’t know of anything that I find more useful.

Cons

• If you aren’t using Firefox, you’re out of luck.
• Not all of the data sources return information all the time.

Local Rank

Next we have Local Rank. Local Rank is a Member’s Only tool. The tool runs on the premise that sites that are well linked to from top results might get a rankings boost in Google for certain keywords.

Fields are as follows:

• The Keyword field is where you enter the keyword…pretty self-explanatory.
• The Scan First (x) Results lets you choose from the default 100 to 1000 results. This tells the tool how many results to scan.
• The Find LocalRank links pointing at the top search results field lets you choose from the default 10 to 50 results and tells the tool how many top results to find links to.
• The Region/Country field lets you choose where you want your query to be run, with Google.com as the default. From what I can tell, there are choices for just about every country-specific Google.

When you submit your query, you’ll see results like the following:

The tool lists the URLs found for the initial query along with crawl dates and both Yahoo and Majestic link counts.

It then uses a re-ranking algorithm to identify a list of sites that have are frequently cited from those sites. These are your likely link targets and they’re listed in the matrix below the initial results set. There is also a link to the Competitive Research Tool which is quite handy, and the matrix can be exported.

Here’s a screenshot:

Each URL has associated numbers running across the top, along with checkmarks that indicate that the site to the right of it is linking to the site at the top of the matrix. (Note: I did have to ask Aaron to clarify this one.)

Pros

• The Yahoo and Majestic link count data is pretty cool and takes you to the source in case you want to do any extra digging.

Cons

• While I was able to see the Yahoo data from the links in the results listed above the matrix, all of the non-URL results that I clicked on in the results matrix sent me to a Yahoo site explorer page with no results.

Competitive Research Tool

Now we’ll turn to the Competitive Research module which is a tool that’s only available to members. Enter in a URL or keyword, choose a datacenter, and you’re provided with competitive information including organic and pay per click.

Since I also do PPC work, this is a particularly cool tool for me because I could use it to help make recommendations about where to put the marketing efforts.

If you put in a URL you’ll just get data for that one in particular, and if you input a keyword, you’ll see a list of URLs along with corresponding numbers but the results available are a bit different, so it’s worth playing around with, using both URLs and keywords, in order to get a full picture.

You can either enter a URL or a keyword for this one. For the first example, I’ve entered the keyword “umbrellas” as it’s looking a bit rainy outside today. You need to make sure to hit the Keyword button of course (and obviously the Domain button if you’re entering a URL) and then choose a Google datacenter.

The keyword report shows you CPC, Competition, and Ave. Volume for your keyword and several related ones.

To get even more specific domain-related information, choose the Domain option. For this example I’ll use the New York Times since they are a well-known site and certainly can’t complain about being outed anywhere for anything.

Here you’ll see the following: Domain, Rank, Organic Keywords, Organic Traffic, Organic Cost, Adwords Keywords, Adwords Traffic, and Adwords Costs for the domain summary itself.

Next, you’ll see the following for fields for keyword-specific organic data: Keyword, Pos, Traffic %, Costs %, Costs CPC, Volume, Total Keyword value, Value of #1 Ranking, Current Position Value, Upside Potential, Upside Potential %, and URL. That’s a plethora of great data.

The data doesn’t stop here, however.

We also get tons of Adwords-specific information about the keywords (and quite honestly, I will just bore you if I continue to list all the fields so suffice it to say, you’ll be buried under information here), along with competitors’ information (again in both organic and Adwords-specific formats), then Potential Ads/Traffic Buyers listed in both Organic to Adwords Competition and Potential Ads/Traffic Sellers listed in both Organic to Adwords Competition.

Wow. For all of the sets of data, you have the option to get even more information. This tool alone could take up an entire review and I doubt I’d still cover it all.

So how would you use this for link building?

Tons of ways, I’m sure – but I’ll cover just a few ways I’d use the data.

1.  Just as it’s good to use organic data in conjunction with PPC data in order to maximize your outlay and resources, it’s good to use both of these to help decide where to hit links the hardest. By showing you what your URL ranks for in Google alongside the traffic percent and cost per click of that keyword, you can decide which anchors to go after.

2.  By using a keyword, you can see a list of related competing keywords alongside their cost per click and current value. Depending upon my budget, I’d make decisions on where to spend the most money to get the best results.

3.  Figure out how your competitors are doing in organic and paid search in order to better tailor your link efforts.

Pros

• This data is fantastic and the tool is easy to use. I love that it combines PPC and organic in a way that is applicable to link building. Usually, you don’t get that in one tool.
• The report runs quite quickly which is always nice.
• I like that you can either do this by keyword or by domain, depending upon your needs.

Cons

• Honestly, I can’t think of any, unless you happen to be a person who hates great data.

Hub Finder

The Hub Finder is another member’s only tool that finds instances of co-occurring links. It runs on the premise that a site that links out to several competitors in the same field should have editorial integrity and be willing to link to you as well. You can plug in between two and ten of your competitors in order to identify sites that link to as many of them as you specify.

So let’s get started with the fields and what to do with each one. Straightforward for many of you, but I’m such a literalist that I did have to ask Aaron a few questions in order to understand what to do with two of the fields.

• The Subject can be used to pull a list of relevant sites to query from either Google or Yahoo. You can also just enter your own URLs.
• The Results field is a dropdown list of 1 to a default value of 20 that simply specifies how many results you’d like to see when you run the tool.
• The API field is used to specify whether you want to use the API or Yahoo, Google, or both of them at the same time.
• Min Match tells the tool how many minimum matches to show, meaning that if you want to only see sites that link to all 5 of your competitors, you’d choose 5. If you wanted to see sites that linked to just 2 of your 10 competitors, you’d choose 2. Nice and straightforward stuff, even for me.
• The Depth field is used to specify how many top inbound links you want to search through for each domain, ranging from the default of 50 to 250.
• The optional Include This Site field is one that I did have to ask about, as I wasn’t sure what the purpose was. The answer made perfect sense: this field is used to force the inclusion of one URL in particular. I’ll share Aaron’s example here:

“an example…a site competing against one of my sites rebranded to a new URL. so I found links to them that were on any page that had links to other top sites in that vertical. figuring some of those are resources pages that might be willing to list more sites in the niche, I can then manually contact them & let them know about the updated link or broken link or whatever & then also pitch the link I want promoted as well.”

• The Link Type field is used to select either Domain or Page values.
• The Application field is used to select either Sort By or Must Link. Options are Sort By and Must Link.

So let’s get started, using a nice SEO example with the major SEO sites listed, forcing the include for the SEO Chicks site.

The results are mapped with a number corresponding to each competing URL, along with Xs that denote which sites have co-occuring links. There’s a highlight function that is activated if you click on one of the numbers that denotes a URL so you can more easily see specific instances of co-occurrences.

The results set also contains links to the following:

• Whois (W)
• Archive.org (A)
• Google cache (H)
• DMOZ (D)
• Yahoo Directory (Y)

You’ll see the IP address for each URL and be able to click through to the sites themselves. The report is also downloadable which is always handy.

Pros

• There is a lot of documentation for the Hub Finder, which was helpful.
• I love the results report, which makes it very easy to quickly see which sites link to competing URLs but not your own.
• It uses Yahoo mainly, not Google. Hooray!
• In addition to loving the results report, I love the results, period. Finding co-occuring links is a great way to find new opportunities for your own site.
• The report is downloadable.
• The report runs quickly.

Cons

• Error checking messages are non-existent on this tool. If you do something wrong, you just won’t see results and you may not understand that it is because you have misused the tool. I had to ask a few questions in order to understand how to use this properly, even after reading the instructions. Once you understand how exactly to use it, it makes sense of course, but I do think that error messages would be helpful to users.
• Some functionality just didn’t make sense to me. For example, if you choose the default Sort By in the Application, you will see results that don’t necessarily link to the site that you may have put into the Include This Site field. If you choose the Must Link, you’ll only see results that link to that site at a minimum. To me, this is a bit confusing since I’d assume that including a site would take care of this.
• The example image used in the instructions page had a field in it that was not present in my current version.

Bottom line: I’ve used this tool before (long enough ago that I forgot how it worked, oddly enough) and always been a fan of it. I love the idea behind it and the fact that it’s a great source for new links. Error checking messages are something I seem to need due to being a bit of a clumsy user, but as I said, once you understand what to do, the tool is straightforward.

Wrapup

My favorite tool in this suite was the Hub Finder. It’s straightforward and applicable to the way I build links. I also rely upon the SEO for Firefox plugin but that’s a free tool. I could also use more error messages as I have said, due to being a bit spastic and clicking without reading things carefully.

I would probably not purchase a membership strictly for the tools. However, the forum alone is worth the price. Heck, the monthly wrapup that Aaron does is worth the price! I do keep up on what’s going on but his October wrapup, available only to members, alerted me to tons of articles that I had not seen. If you’re busy and can afford the cost, I’d become a member for that alone as it honestly did cover just about everything that happened. Participants in the forum seem to be extremely open and helpful and just in skimming a few topics, I learned a lot.

There are also training videos, tons of archived articles, downloadable strategy guides, and quick start checklists. If you’re just starting out in SEO, I’d say this program would definitely benefit you. If you’re a seasoned SEO and want to get the same kind of information that you tend to get only at bars after a conference, this is what you’re looking for.

Majestic SEO is a popular tool used by SEOs for competitive link analysis. The main alternatives to the tool include SEOmoz’s LinkScape, RankAbove’s SEO Drive and the soon defunct Yahoo Site Explorer, amongst others.

The OpenApps feature allows developers and third-parties to build modules on the data. It allows developers to build modules to let their users request data from the Majestic SEO toolset. It is available to “all Majestic SEO subscribers on all plans,” while the commercial API is restricted to full reseller licensees. There is also no service level commitment to use the Open App method.

For more details on how to access the Majestic SEO OpenApps, see the blog and the developer area. Finally, for an example tool, see this page.

Related Stories:

• Enterprise SEO Tools, Part 2: The Cloud
• Yahoo Shutting Down Site Explorer This Year
• Link Building Tool Review: SEOmoz PRO
• Worthy Alternatives To The Useless SEO Data Provided By Search Engines
• SEOMoz’s New Toolbar & Linkscape Doubles In Size

We use the PPC permutator to help us rapidly expand keyword lists from simple ideas. Let’s work with an example. Consider the following keyword ideas related to a hypothetical bicycle shop. Using the tool, we take three simple ideas and generate 48 keywords.

• Terrain: mountain, road, touring
• Bike Synonyms: bike, bicycle, cycle
• Product: tire, tires, tube, tubes

We enter them in the tool, like this:

Push-Button List Generation

The tool built an extensive list of keywords from a few keyword ideas. If you can imagine typing out a list like this, the time savings might be an obvious benefit.

The more valuable benefit in my opinion is that it lets the campaign manager remain in “creative” mode without having to task-switch to “manual labor / typing” mode. The tool does the work of generating the list as the output. The campaign manager generates more ideas as the input. While this is valuable all by itself, there is more.

Change Input Easily

If we decide we also want to generate keywords like “bike tire” (i.e.: combining only the last two keyword ideas, skipping the first), then we just check a box and the tool makes it happen. Likewise, if we start selling “fixie” bike tires, we can simply add “fixie” to the list. The tool will generate the new keywords.

So another benefit is that it lets us change input easily without paying the penalty of having to produce the list again. We just refine the input and click a button.

Now if you have been doing PPC for some time, using tools to generate keyword lists may not be a new idea. Tools are available online, and you may have one of your own. Before you go, there is more. What if you want to place these keyword ideas into campaigns and ad groups?

Organize Keywords Into Campaigns & Ad Groups

In PPC it is important to break long lists of keywords into tightly themed ad groups. The key benefits of putting keywords in separate, tightly themed ad groups are clear: We can write targeted ads pointed at targeted landing pages.

We also get some sanity and manageability: ad level URLs, default ad group bidding, etc. The PPC permutator can help.

Let’s build ad groups based on the “root” idea of each keyword. We want separate ad groups for the terrain types, and for the tire type, but do not want separate bike synonym ad groups because we believe they all perform similarly and we want them in the same ad group. (By the way, if we wanted to put the bike synonyms into separate ad groups, we could do that too. This is just an example.)

This is one feature that is not always found in a tool of this sort. We can add some “meta data” about the “root” of each word, and the tool carries that information forward for us to use. First, we add the roots for each word:

Then we use that information to help us generate campaigns and ad groups in the output:

We have some options here. We could have changed the “sequence” of the ad group names if we wanted “Product(Tire) Type(Mountain)” rather than “Type(Mountain) Product(Tire)”, for example.

We also could have chosen to use the bike synonym root and generated ad group names like “Product(Tire) Type(Mountain) Bike(Cycle)”. We could use a different naming convention and change the separator to “+”, e.g.: “tire+mountain+cycle”. The tool helps us organize keywords into campaigns and ad groups according to our needs.

Define Match Types

In PPC, we also want to produce keyword lists with match types. Once again, the tool is ready to do the heavy lifting for us. Of course, in practice we would not blindly add “everything on all match types” — this is just an example.

The tool also works with AdWords’ Broad Match Modifier. We just add the “+” to the original words where we want it, and the tool caries it forward (and removes it for non-broad-match instances of the keyword).

Conclusion

The PPC permutator is one of several tools we use around our PPC shop. The primary benefits we see are:

• Push-button list generation
• Change input easily
• Organize keywords into campaigns and ad groups
• Define match types

If you would like a copy of the PPC permutator, feel free to send me an email. You could also adapt these ideas to your own tools. Have fun out there.

Up until now, this tool used small green bars to display the competitiveness of keywords. The more green in the bar, the more competitive the term was:

Now the Google tool is only showing text-based descriptions of competitiveness: Low, Medium or High:

While the competitiveness has been replaced by text in the web version, the good news is that Google has maintained the granularity as to how this ranking was assigned. In the previous version of the tool, users could download a report to get the exact number that made up the green bar. This is still the case with the new changes. So users who require more information can still download the report to a spreadsheet and get the same information:

For any of those who regularly use this competition metric, the new competitive labeling is as follows:

• Low — Competitiveness number under .33
• Medium — Competitiveness number between .33 and .66
• High — Competitiveness number over .67

“This column shows the number of advertisers worldwide bidding on each keyword relative to all keywords across Google. The shaded bar represents a general low-to-high quantitative guide to help you determine how competitive ad placement is for a particular keyword.”

Among the new features, the most important from a search marketing perspective are these:

• Expanded data: Yahoo Clues now includes a full year of data, up from just a month
• Wider coverage: It includes all English-language searches made globally

The new Yahoo Clues also offers a “Top Trends” tab (as part of its new look-and-feel) that lets users explore and analyze the most popular search terms on Yahoo. But the expanded data is also part of the regular Trend Analysis tool that lets you compare two search terms and dissect the differences by demographic, location and more.

The map you see at the bottom of that screenshot is another new feature that lets you map and visualize search activity.

Yahoo Clues launched last November and, in this writer’s opinion, it’s great to see the tool continuing to get attention from Yahoo.

Google has also done some cool things with search data, including forecasting Flu Trends and predicting the impact of the Gulf oil spill on tourism in Florida. Now, they’ve created a tool to enable you to correlate search trends with any data you might want to throw into the mix. How awesome is that? (Hint: very awesome.)

With Google Correlate, you can upload data charted over either time or space and Google will look for matching patterns in search volumes. If you don’t have data of your own to upload, you can simply specify search terms, and Google will calculate the trending pattern and show matching patterns.

As Google notes in their documentation, this is sort of the opposite of Google Trends:

Google Correlate is like Google Trends in reverse. With Google Trends, you type in a query and get back a data series of activity (over time or in each US state). With Google Correlate, you enter a data series (the target) and get back a list of queries whose data series follows a similar pattern.

It appears that right now, you can either upload time-based data or state-based data (but not international data). You can even just draw a line on a graph and see what correlates!

I have apparently drawn the line that most correlates to people searching for Homelife Communities (an Atlanta builder):

The comic Google created to explain the new tool is careful to point out (multiple times!) that correlation does not necessarily equal causation.  The states where Glee is performing in concert and searches for [the dreamiest] may have the same spikes, but that doesn’t necessarily mean the two are related.

They might be though. At O’Reilly’s Where 2.0 conference last month, I did an Ignite talk showing that people were interested in Rebecca Black everywhere, but were only really interested in March Madness in states that had teams participating.

Interest in Rebecca Black:

Interest in March Madness (states with participating teams and state-based search interest):

I feel like there could be some really interesting integrations between this and Google’s Public Data Explorer, but Google Correlate is in labs, so give it some time.

If you want to check it out for yourself, Google has a tutorial, FAQ, and whitepaper.

Psychology has shown that many of our day-to-day behaviors are deeply related to our personalities, beliefs, and cultures. In the same spirit, I believe we can learn about people’s professional inclinations from their analytical behavior.

Google Analytics & A Tour Of Jerusalem

Recently, I presented at a Google Event in Israel on the subject of Analytics and Testing. Following the event, I traveled to Jerusalem with Timo Josten, Google Analytics Partner Program Manager for EMEA. As we approached Jerusalem, I decided to build the tour based on his Google Analytics preferences.

I asked him what is the first report he looks at when checking a new Google Analytics account, his answer: the Traffic Sources report. That’s because he believes that the sources of traffic tell a lot about the company’s marketing efforts and about the visitors themselves.

Based on that, we started by visiting the old city alleys (image below), as I understood that he is the kind of person that dives into the numbers to understand the visitors and then zooms out to understand the big picture. We started from inside and then moved out to a bird’s eye view.

In a different instance, I also had the pleasure of taking Bryan Eisenberg to Jerusalem. I asked a similar question: “what is the first report you look at when looking at a new Web Analytics account?”

Bryan explained that he usually looks at the big picture and then zoom in to see the details and understand visitor behavior better. Based on that, I took him to a spot where we could view the whole city and then we “zoomed in” to the old city alleys.

In summary, I believe that good analysts can be divided in two types of people: those who start broad and then drill down with the big picture in mind, and those who start on the details and broaden their view with a good notion about the numbers.

Google Analytics Psychological Test

People usually believe that one person’s friends can tell you a lot about that person’s beliefs and characteristics. Expanding on this same idea, I believe that the Web Analytics industry should promote the saying: “tell me what is your preferred report, and I will tell you who you are.”

In a previous post, I discussed the Web Analytics Process and the importance of building Key Performance Indicators that are customized based on a person’s interest. Below I provide a few personalities that can be discovered from Web Analytics behavior analysis.

The Hawk – Dashboard View

According to Wikipedia, “Hawks are widely reputed to have visual acuity several times that of a normal human being.” This enables them to fly very high and still be able to find the preys.

The same is true for analysts that focus on the so called bird’s eye view: they analyze the big picture and are able to find insights that will show where to focus the attention.

This view is especially important for online marketing managers or website owners, people that want to know the bottom line but also additional success metrics (such as engagement, campaign success, and visitors return rates).

The Slot Machine – Ecommerce View

When a person goes to a casino, he or she has one main objective: to make money. Especially slot machine addicts. This is not to say that they do not have fun along the way, but they are result driven and they will hardly move their focus.

Some people, when looking at Google Analytics, cannot move their eyes from the ecommerce reports. This view is especially important for senior managers or sales people, who mainly want to check the website results and compare it to other channels.

The Psychologist – Content View

Some people like to understand what other people think and like. Those people usually become psychologists, but once in a while they miss the target and become web analysts. Their main interest is to understand what visitors are reading on the website and if they are enjoying it.

The content reports are especially important for content specialists, editors, and analysts looking to understand what is the most engaging material on the website (which will bring insights into how to organize the website and where to advertise).

The Historian – Sources View

Historians are known for researching the past and trying to understand how we got where we are, and if history is likely to repeat itself. Traffic Sources tells us just that: how people got to the website (sometimes even their intentions via keywords) and how visitors from each background behave.

Traffic sources are especially important for marketing managers looking to understand how marketing campaigns are working and for SEM managers looking to optimize SEM campaigns.

The Geek – Technology View

Geeks just can’t help themselves: they will open Google Analytics and go straight to the Operating Systems and Browsers report. With Google Analytics v5 it is even easier, as there is a whole set of reports named Technology.

As the name says, these reports are very important for IT personal in order to understand which technology visitors are using and how to optimize website performance for that. In addition, it might also be important to senior management to drive decisions regarding mobile strategy (see Mobile Marketing for E-commerce).

Closing Thoughts

In summary, I believe that online professionals have different ways and interests when looking at data. It is possible to understand more about a person’s perspective by asking questions related to how he or she approaches and analyzes the data.

With SEM representing almost half of the digital advertising industry revenues, this channel is more important than ever and new tools are popping up to help us get the most return on our investment.

TenScores is a perfect example of one of these laser-focused tools. Founded by Chris Thunder, TenScores is a tool that performs a very simple, yet powerful function. Once you link your AdWords account to the platform, you’ll be able to monitor your individual Quality Scores and their historical performance. Nice, eh?

For those of you who obsess over your Quality Score, this is the tool for you. And for those of you who aren’t following your QS obsessively…why not?

I spoke with Chris about his background, the history behind his tool, and what’s on the road map for TenScores.

Q: What’s your background in search marketing?

Chris: I got bit by the bug in late 2007. I had an idea for a website I wanted to create but I wanted to test if there would be interest in it before actually creating it. That’s when I discovered AdWords. I was fascinated by ad writing and how changing just one word would have a dramatic impact on my CTRs and conversions.

Q: How did you get the idea for TenScores?

Chris: When I started managing other people’s accounts, I noticed one thing: none of them knew anything about Quality Score and the dramatic affects it has. Often, Quality Score was the first thing I had to improve when I had a new client. I knew I could help a lot of people save money with AdWords if only they could learn what kind of ‘quality’ Google wants.

I was consistently getting 10/10 Quality Scores so I decided to write a how-to eBook about it, hence the name TenScores. As I was finishing the book, a long time friend of mine came to live in my city, little did I know it would spark the beginning of a business partnership. He has excellent programming skills and was interested in what I was doing.

Since AdWords doesn’t give any historical data on your QS, and since QS fluctuates quite a lot, I asked him to create a simple tool I could use to monitor quality score evolutions in the accounts I was managing. What he did for me was tremendous. I would upload a file every day and see how my client’s QS had evolved. I could see where I was making progress and where things were going in red.

I thought other people would enjoy using a tool like this one so we decided to create a free membership site for it and see if there was interest. And there was interest indeed.

Q: What’s your thoughts on Quality Score in general?

Chris: Mixed feelings. On one hand, it can get really frustrating when you seem to do everything right but Google doesn’t want to raise your QS and you end up paying high bids for no apparent reason. On the other hand, when you do manage to increase your QS to 10 for example, the reward is great! Your traffic increases and your costs drop dramatically.

What annoys me the most is the little cloud of secrecy that surrounds it. Google asks its advertisers to be 100% transparent but they don’t follow that advice themselves. QS is still hidden is new accounts, most people don’t know that other advertisers mistakes can impact your own QS and … many times you’ll have low QS but no one at the Google headquarters will be able to tell you exactly what you’ve done wrong.

It’s very, very frustrating

Q: What does the tool do? What are the benefits? What are the negatives (right now)?

Chris: The idea is to have historical data on your keywords’ quality scores (and first page minimum bids), see when they rise or fall so you can optimize accordingly.

For example, if you have keyword that has a QS of 6/10, you can look at its history. If you see that it was at 7/10 at some point in time, you know something happened and you can make the change easily to get it back to 7. The simple change from 6 to 7 can mean quite a lot in terms of ROI if it’s a high traffic keyword.

The manual tool we have can do that but the process is a little bit cumbersome. Uploading file after file everyday can be exhausting. The automatic tool that we’re launching in a few weeks will monitor whole accounts in regard to keywords’ quality score fluctuations – with no action needed from the user, except simply logging in.

Q: How do users win at QS management using TenScores?

Chris: Well, they simply get insights about the quality of their campaigns that are unavailable in AdWords. It helps them optimize quickly where it has the most impact. Not only that, but there’s a little bit of training for those who are not familiar with Quality Score.

Those who don’t know how important it is or how to optimize it, those who want to enhance their knowledge on effective ad copy writing, those who want to learn the right way to create ad groups … we give them access to the original TenScores eBook that I used to sell for $69.

Q: What are some upcoming changes/features?

Chris: Right now it is simply a reporting tool, it doesn’t make any changes in the AdWords account. We’ll first try to make the reporting features as complete as possible and then think of ways TenScores can interact with AdWords accounts to improve performance, if possible.

For example, we’ll add email alerts for quality score. That’s something not available in AdWords. We’d like our users to get alerts when an important keyword has fallen under a certain quality score threshold.

We will add the possibility for users to set goals of quality score achievements and be able to track their progress. For example, if you want your top 10 keywords to be above 7/10, you’ll be able set that goal, TenScores will give you optimization ideas and track the progress of that objective – until you reach it.

We’re thinking of creating a tool that can take a quick look at a landing page and spot potential problems that could lead to ‘poor landing page quality’. Those are things I think would be great for me, but I’m sure people will bring us better ideas and our ears are open. Very wide open.

Chris: Now that I’ve answered your questions, I’d be delighted to hear your thoughts and feelings about TenScores. Maybe even give us some tips on how to move forward and the features you think would be most beneficial to you as a marketer or your readers.

Josh: Ah, you turned this around on me.  Hey, I’m the one asking the questions around here. Ha! Okay, that is a good question. I’m glad to hear that you want to build it out so you are able to go beyond just monitoring your QS, but also are able to make changes to your accounts from inside the system.

Overall, I think it’s a handy piece of gear that can be in the toolbox of any search engine marketer. For some accounts, QS isn’t much of an issue, but for others, it’s holding back their success. It’s SEM accounts like these that would be benefit most from your tool.