Enrichment Depot – Profiting on the Net

Posted by dohertyjf

As we all read last week, SEOmoz has released the second Linkscape index update of November, and with that came updated Domain Authority and Page Authority. Many of you probably noticed a change, either as a result of the broader crawl, or as a result of active linkbuilding you have been doing on your site or client sites.

The purpose of this post is to help us orientate ourselves around what our scores mean and how those might compare to other sites that we are aware of. Remember, Domain Authority and Page Authority are strictly link based, so the metrics can be influenced by either more links from more sites, or a few links from higher quality sites. One should remember, however, that Domain Authority and Page Authority are hard to directly influence, as they are a combination of 30+ data points and work on a logarithmic scale. As Matt Peters noted in his blog post called "Introducing SEOmoz's Updated Page Authority and Domain Authority":

Page and Domain Authority are machine learning ranking models that predict the likelihood of a single page or domain to rank in search results, regardless of page content. Their input is the 41 link metrics available in our Linkscape URL Metrics API call and their output is a score on a scale from 1 to 100. They are keyword agnostic because they do not use any information about the page content.

What I want to do here is provide you a framework through which to benchmark your site against others in your niche. I'm going to take a mashup of tools that are already available so that you can go forth and figure out if you have any new competitors in your SERPs (Search Engine Results Pages). Then you can go forward and dig deeper into those sites in your own way to decide how to beat them. Let's go!

Where Do I Start?

The first step to take is deciding which keywords you want to rank for. For the sake of a more complete view of your market's landscape and SERP competitors, I recommend finding at least 20 keywords that would be very valuable for you. I've taken fewer for the sake of brevity, so here are the keywords I am going to be using for this example:

First Tool – Tom Anthony's Competitive Analysis Tool

Some months ago Tom Anthony, one of our London SEO consultants (who grows a wicked mustache, by the way), dropped a tool that he says can help you do competitive analysis in under 60 seconds with the SEOmoz API. Take your keywords and plug them into the tool. You will receive rows of data on your competitors and will be able to see how your site lines up. For the keywords above, this is the data that we see in the sheet:

Full disclosure: I have no affiliation with any of the sites listed above, other than I buy from some of them periodically.

Note – you will need to make a copy of it and get your own SEOmoz API key in order for this to work for you. Full directions on how to set up the sheet are available on the original post as well. What is important to get out of this list is the list of competitors. From the data provided as well, you can see relatively where your site stands for the search results (or by simply including your site at the bottom of the list and enlarging the sheet to include your metrics as well).

Using the above metrics, if I was doing SEO for skichalet.com, I can see that my competitors to beat directly above me are the-house and Cabelas, but really I am gunning for Backcountry.com and REI.com, and I want to know how they are winning. Let's take this a step further and see why our competitors have a higher Page Authority or Domain Authority.

PA Correlation (thanks to Dr Pete)

Now that you have your competitor's DA and PA, and know roughly where you stand compared to them, you can begin to dissect why their PA or DA is so high. Remember, your metrics can be improved by either a) more links from more sites, or b) a few links from more authoritative sites. If you want to know why your competitor is beating you, I recommend using the spreadsheet in this awesome post about Link Profiling with OpenSiteExplorer. This sheet is useful because, according to Matt Peters, Page Authority is the highest correlated metric against a page's ability to rank well (from a link perspective). This sheet will give you a graph of the average Page Authorities of the sites linking to your competitors. After you have taken the data dump from OSE and plugged it into (LINK) the sheet, you will get a graph that looks like this:

If you want to see your competitors distribution compared with yours, use this sheet, which will show you the two side-by-side like so:

Using this, you can see that while your spread may be similar, the competitor on the left has many more linking root domains (the scale is much broader). That's where you need to start.

DA Correlation

You may also find it helpful to see the overall strength of the sites from which your competitors are getting links and the spread of those Domain Authorities across their backlink profile. For this purpose, I built a spreadsheet based off the PA Tool from Dr Pete above. The steps are exactly the same, but instead of the Page Authority graph you receive the Domain Authority graph:

Right here you may come up against a shortcoming of OSE, in that with sites that have a lot of linking root domains you may not be able to get the lower DA links. So watch out for this.

You can grab the Domain Authority Sheet right here.

Final Secret Sauce – SERP Analysis Report + Excel

Finally, now that you have gotten a quick overall look at your competitors and know where you stand and what certain domain and page authorities mean for ranking in your niche, you'll want to make this actionable. The above graphs do not go specific enough to be very actionable, so now let's use the SERP Analysis Report (available in the Keyword Difficulty Tool) to put the data for your specific keywords individually (that you used at the beginning to begin finding your SERP competitors)

A while back I presented a spreadsheet that allows you to take the SEOmoz SERP Analysis Report and dump it into an Excel sheet, which then gives you a bunch of graphs showing you where your site is weak. I'd be remiss to not say that I took this idea from Jason over at BusinessHut who gave away the original spreadsheet before the SERP Analysis Tool existed. You can read the full explanation of this sheet over at my site in the post called Making SEOmoz's SERP Analysis Tool More Awesome, but essentially what you can do with this sheet is:

1. Get your SERP Analysis Report for your keyword;
2. Export the data to Excel;
3. Copy and paste the data into the spreadsheet provided;
4. Sit back and compare your site to the competitors to find where you need to improve.

Maybe you'll find that your overall number of linking root domains is way low compared to the others in your SERP:

Or maybe you'll see that your on-page targeting is off (which is great since DA and PA are only links based. Now you get a better site picture):

Get the spreadsheet here.

I hope this post has been helpful for you in finding where you compare against your competitors. Knowing approximately what the benchmarks are for your niche can really help with speedy link prospecting and qualifying your site against others.

For those of you who are interested, here are some popular sites and their Domain Authorities, just for a quick snapshot of the web at large:

Websites taken from Rob Ousbey's post and the Getstat Codex.

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SEOmoz Daily SEO Blog

Tags: Analysis, Authorities, Benchmarking, Competitor, Domain, Page

Posted by Matt Peters

Here at Moz, we take metrics and analytics seriously and work hard to ensure that our metrics are first rate. Among our most important link metrics are Page Authority and Domain Authority. Accordingly, we have been working to improve these so that they more accurately reflect a given page or domain's ability to rank in search results. This blog entry provides an overview of these metrics and introduces our new Authority models with a deep technical dive.

What are Page and Domain Authority?

Page and Domain Authority are machine learning ranking models that predict the likelihood of a single page or domain to rank in search results, regardless of page content. Their input is the 41 link metrics available in our Linkscape URL Metrics API call and their output is a score on a scale from 1 to 100. They are keyword agnostic because they do not use any information about the page content.

Why are Page and Domain Authority being updated?

Since these models predict search engine position, it is important to update them periodically to capture changes in the search engines' ranking algorithms. In addition, this update includes some changes to the underlying models resulting in increased accuracy. Our favorite measure of accuracy is the mean Spearman Correlation over a collection of SERPs. The next chart compares the correlations on several previous indices and the next index release (Index 47).

The new model out performs the old model on the same data using the top 30 search results, and performs better if more results are used (top 50). Note that these are out of sample predictions.

When will the models change? Will this affect my scores?

The models will be updated when we roll out the next Linkscape index update, sometime during the week of November 28. Your scores will likely change a little, and may potentially change by as many as 20 points or more. I'll present some data later in this post that shows most PRO and Free Trial members with campaigns will see a slight increase in their Page Authority.

What does this mean if I use Page Authority and Domain Authority data?

First, the metrics will be better at predicting search position, and Page Authority will remain the single highest correlated metric with search position that we have seen (including mozRank and the other 100+ metrics we examined in our Search Engine Ranking Factors study). However, since we don't yet have a good web spam scoring system, sites that manipulate search engines will slip by us (and look like an outlier), so a human review is still wise.

Before presenting some details of the models, I'd like to illustrate what we mean by a "machine learning ranking model." The table below shows the top 26 results for the keyword "pumpkin recipes" with a few of our Linkscape metrics (Google-US search engine; this is from an older data set and older index, but serves as a good illustration).

As you can see, there is quite a spread among the different metrics illustrated, with some of the pages having a few links and others 1,000+ links. The Linking Root Domains are also spread from only 46 Linking Root Domains to 200,000+. The Page Authority model takes these link metrics as input (plus 36 other link metrics not shown) and predicts the SERP ordering. Since it only takes into account link metrics (and explicitly ignores any page or keyword content), but search engines take many ranking factors into consideration, the model cannot be 100% accurate. Indeed, in this SERP, the top result benefits from an exact domain match to the keyword and helps explain its #1 position despite its relatively low link metrics. However, since Page Authority only takes link metrics as input, it is a single aggregate score that explains how likely a page is to rank in search based only on links. Domain Authority is similar for domain wide ranking. The models are trained on a large collection of Google-US SERP results.

Despite restricting to only link metrics, the new Page and Domain Authority models do a good job of predicting SERP ordering and improve substantially over the existing models. This increased accuracy is due in part to the new model's ability to better separate pages with moderate Page Authority values into higher and lower scores.

This chart shows the distribution of the Page Authority values for the new and old models over a data set generated from 10,000+ SERPs that includes 200,000+ unique pages (similar to the one used in our Search Engine Ranking Factors). As you can see, the new model has "fatter tails" and moves some of the pages with moderate scores to higher and lower values resulting in better discriminating power. The average Page Authority for both sets is about the same, but the new model has a higher standard deviation, consistent with a larger spread. In addition to the smaller SERP data set, this larger spread is also present in our entire 40+ billion page index (plotted with the logarithm of page/domain count to see the details in the tails):

One interesting comparison is the change in Page Authority for the domains, subdomains and sub-folders PRO and Free Trial members are tracking in our campaign based tools.

The top left panel in the chart shows that the new model shifts the distribution of Page Authority for the active domains, subdomains and sub-folders to the right. The distribution of the change in Page Authority is included in the top right panel, and shows that most of the campaigns have a small increase in their scores (average increase is 3.7), with some sites increasing by 20 points or more. A scatter plot of the individual campaign changes is illustrated in the bottom panel, and shows that 82% of the active domains, subdomains and sub-folders will see an increase in their Page Authority (these are the dots above the gray line). It should be noted that these comparisons are based solely on changes in the model, and any additional links that these campaigns have acquired since the last index update will act to increase the scores (and conversely, any links that have been dropped will act to decrease scores).

The remainder of this post provides more detail about these metrics. To sum up this first part, the models underlying the Page and Domain Authority metrics will be updated with the next Linkscape index update. This will improve their ability to predict search position, due in part to the new model's better ability to separate pages based on their link profiles. Page Authority will remain the single highest correlated metric with search position that we have seen.

The rest of the post provides a deeper look at these models, and a lot of what follows is quite technical. Fortunately, none of this information is needed to actually use these Authority scores (just as understanding the details of Google's search algorithm is not necessary to use it). However, if you are curious about some of the details then read on.

The previous discussion has centered around distributions of Page Authority across a set of pages. To gain a better understanding of the models' characteristics, we need to explore its behavior on the inputs. However, the inputs are a 41 dimensional space and it's impossible (for me at least!) to visualize anything in 41 dimensions. As an alternative, we can attempt to reduce the dimensionality to something more manageable. The intuition here is that pages that have a lot of links probably have a lot of external links, followed links, a high mozRank, etc. Domains that have a lot of linking root domains probably have a lot of linking IPs, linking subdomains, a high domain mozRank, etc. One approach we could take is simply to select a subset of metrics (like the table in the "pumpkin recipes" SERP above) and examine those. However, this throws away the information from the other metrics and will inherently be more noisy then something that uses all of them. Principal Component Analysis (PCA) is an alternate approach that uses all of the data. Before diving into the PCA decomposition of the data, I'll take a step back and explain what PCA is with an example.

Principal Component Analysis is a technique that reduces dimensionality by projecting the data onto Principal Components (PC) that explain most of the variability in the original data.  This figure illustrates PCA on a small two dimensional data set:

This sample data looks roughly like an ellipse. PCA computes two principal components illustrated by the red lines and labeled in the graph that roughly align with the axes of the ellipse.& One representation of the data is the familiar (x, y) coordinates. A second, equivalent representation is the projection of this data onto the principal components illustrated by the labeled points. Take the upper point (7.5, 6). Given these two values, it's hard to determine where it is in the ellipse. However, if we project it onto the PCs we get (4.5, 1.2) which tells us that it is far to the right of the center along the main axis (the 4.5 value) and a little up along the second axis (the 1.2 value).

We can do the same thing with the link metrics, only instead of using two inputs we use all 41 inputs. After doing so, something remarkable happens:

Two principal components naturally emerge that collectively explain 88% of the covariance in the original data! Put another way, almost all of the data lies in some sort of strange ellipse in our 41 dimensional space. Moreover, these PCs have a very natural link to our intuition. The first PC, which I'll call the Domain/Subdomain PC projects strongly onto the domain and subdomain related metrics (upper panel, blue and red lines), and has a very small projection onto the page metric (upper panel green lines). The second PC has the opposite property and projects strongly onto page related metrics with a small projection onto Domain/Subdomain metrics.

Don't worry if you didn't follow all of that technical mumbo jumbo in the last few paragraphs. Here's the key point: instead of talking about number of links, followed external links to domains, linking root domains, etc. we can instead talk about just two things – an aggregate domain/subdomain link metric and an aggregate page link metric and recover most of the information in the original 41 metrics.

Armed with this new knowledge, we can revisit the 10K SERP data and analyze it in with these aggregate metrics.

This chart shows the joint distribution of the 10K SERP data projected onto these PCs, along with the marginal distribution of each on the top and right hand side. At the bottom left side of the chart are pages with low values for each PC signifying that the page doesn't have many links and they are on domains without many links. There aren't many of these in the SERP data since these are unlikely to rank in search results. In the upper right are heavily linked to pages on heavily linked to domains, the most popular pages on the internet. Again, there aren't many of these pages in the SERP data because there aren't many of them on the internet (e.g. twitter.com, google.com, etc.) Interestingly, most of the SERP data falls into one of two distinct clusters. By examining the follow figure we can identify these clusters:

This chart shows the average folder depth of each search result, where folder depth is defined as the number of slashes (/) after the home page (with 1 defined to be the home page). By comparing with the previous chart, we can identify the two distinct clusters as home pages and pages deep on heavily linked to domains.

To circle back to search position, we can plot the average search position:

We see a general trend toward higher search position as the aggregate page and domain metrics increase. This data set only collected the top 30 results for each keyword, so values of average search position greater than 16 are in the bottom half of our data set. Finally, we can visually confirm that our Page and Domain Authority models capture this behavior and gain further insight into the new vs old model differences:

This is a dense figure, but here are the most important pieces. First, Page Authority captures the overall behavior seen in the Average Search position plot, with higher scores for pages that rank higher and lower scores for pages that rank lower (top left). Second, comparing the old vs new models, we see that the new model predicts higher scores for the most heavily linked to pages and lower scores for the least heavily linked to pages, consistent with our previous observation that the new model does a better job discriminating among pages.

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SEOmoz Daily SEO Blog

Tags: Authority, Domain, Introducing, Page, SEOmoz's, Updated

Miro from cu.cc asked why his whole domain was labeled as having malware when it did not have malware on it.
Google’s JohnMu replied to him in the Google Webmaster Help forums saying that subdomains can impact the parent domain. John said:

Search Engine Roundtable

Tags: Domain, Google, Label, Malware, Subdomains, Whole

SEO Book.com

Tags: Category, Domain, Killer, Names

SEO Book.com

Tags: Cutts, Domain, Down, Google's, Keyword, Matt, Names, Talks

One of the questions I get asked quite regularly is how do I choose a new domain name for a project I decide to work on. There are quite a few aspects I take into account that I will share with you.

Exact Match Domains – If you can get an exact match domain, do it. Google says they might be working on lessening its effect on rankings … maybe … but, either way, I would still prefer an exact match domain over any other domain. Period. That said, getting an exact match domain name that isn’t already registered is going to be pretty difficult. Not everyone is going to be able to spend 5 million on a domain, but there are plenty of times when it’s worth it.

Keyword Domains – If you can’t get the exact match domain, getting a domain with the keyword in it is the next best thing. I prefer to get the keyword toward the front if possible (ie LasVegasHotelDeals.com as opposed to DealsLasVegasHotels.com).

Brand Name or Trademarked Domains – I can tell you from first hand experience you want to avoid these like the plague (see Truth behind GoogleDashboard.com) . If you want to register NFLSexKittens.com to keep someone else from doing it, go ahead, but don’t develop on it; instead, develop on the generic FootballSexKittens.com domain. Just trust me: these types of problems never end well.

Misspellings or Creative New Spellings – IMHO Google has gotten really good at correcting misspellings–so good, in fact, it’s rarely worth actively chasing misspellings. Additionally, avoid made up words that are missing vowels unless you have a huge marketing budget. Flickr.com may look like a good domain now but a lot off $$$ was spent on getting people to not go to Flicker.com before it was purchased and redirected.

Hyphens – Coming from the guy who writes on a hyphenated domain, I can tell you: don’t do this. It’s a huge PIA and the dash just never works when spoken.

Length – When I talk about length, I’m talking about the actual number of characters, not the registration period. Shorter is almost always better than longer.

Billboard Quality – A few years ago, there was a thread on WMW about domains having billboard quality, or specifically how memorable is the domain name that someone sees on a billboard. If you can get a more memorable domain that is longer, go with that instead of the shorter one, but it really should be more memorable.

TLD – if you can, always try to get the .com, .net, and .org variations. If you can’t, get .com first, .org second, .net only if it’s an exact match; otherwise choose again … really. Don’t use country TLD’s unless they are going to be used in country. IMHO Google doesn’t have this sorted out yet for all TLD’s that don’t have residency restrictions. I’ve complained about it multiple times to multiple Googler’s who chuckle at my predicament.

2AM Rule – Everyone I know has some variation of this story … it’s late and maybe you had a drink or two. You check some domain names and find they haven’t been registered yet. You expand your search and find more. The next day you wake up to 0 of new domains you registered that quite likely have typo’s in them or don’t seem like anywhere near as good an idea. No domain registrations after 2 AM. End of story.

Whois Info – Using the “creative” whois info can get you into trouble with domain ownership if someone presses the issue. If you are going to use private whois info, don’t link up the account with the same adsense or google analytics account. Google will figure it out. I have seen some evidence that having real info that matches address info can help your rankings.

Length of Registration – Registering a domain for multiple years may not help you, but it will never work against you.

Related posts:

1. Hey Network Solutions Sniffing Domain Searches By Chance … People have been making accusations that domain companies have been…
2. Value of Choosing a Domain Name One of the more popular questions from SEO’s or webmasters…
3. million spent on a domain? Here’s why. Recently Slots.com sold for 5.5 million dollars, when the general…
4. WordPress SEO: How to Choose a Permalink Structure For this post we’re going to be taking  look at…
5. The Domain Question for Matt Cutts All right since Matt Cutt’s and I are well on…

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This post originally came from Michael Gray who is an SEO Consultant. Be sure not to miss the Thesis WordPress Theme review.

How to Choose a New Domain

Graywolf’s SEO Blog

Tags: Choose, Domain

SpyFu is announcing their new tool called “SpyFu Recon Beta” that gives some essential organic keyword insight and I have been lucky enough to give it a test drive.

For any given domain, the tool builds a huge report reflecting the domain keyword positions, changes and potential.

Let’s take a quick look at what data is waiting for you inside:

1. Your Keyword Positions and Value – Visualized

Your SEO Dashboard consists of various visualizations of your keyword positions, clicks they drive and value they result in:

• Amount of keywords in top search results
• Number of unique pages that rank organically
• Total organic clicks per month
• Value of organic clicks per month

2. Your Biggest Gains

One of the most valuable section of the report is the one listing your most notable keyword standing changes: your most valuable gains in organic search as well as your most notable newly-ranked pages:

• Biggest gains;
• Most valuable keywords;
• Newly ranked pages;
• New keywords (You weren’t ranked on before);
• Top site sections summary
• Biggest opportunities (good keywords you are almost on top)
• “Keywords Not Ranked On But Should Be” (keywords your direct organic competitors show up for on top but you don’t);
• Keyword overlap in your SEO & PPC campaigns

3. Grouping Your Keywords

The awesome part is that the tool will categorize your keywords by the core term and create the report for keyword groups with the biggest gains:

Apart from showing your already high-traffic keyword groups, the tool also lists “Keyword groups with high potential“.

4. Your Organic Search Competitors

The tool offers some very solid competitor insight:

• See the list of your top organic competitors and their best keywords;
• See keywords your competitors are good at (while you are not).

Overall, browsing the report turned out to be an amazing experience to me as I had a chance to discover some absolutely new and promising opportunities. That being said, I’d say the tool does a great job. I’d love to hear your thoughts!

SPYFU RECON CONTEST :

Search Engine Journal & SpyFu will be giving away 3 free SpyFu Recon accounts (for 6 months) so you too can take SpyFu Recon for a test drive and try it out with your SEO strategies.

Just tweet the following :

Enter to *WIN* a FREE #SpyFuRecon account from @sejournal & @spyfu : http://bit.ly/h03FEp [Please RT & Enter]

And/or Leave a Comment Below on why you WANT SpyFu Recon!

Check out the SEO Tools guide at Search Engine Journal.

SpyFu Recon: Your Domain Keyword Position Insight “that Sells for You”

Search Engine Journal

Tags: Domain, for You”, Insight, Keyword, Position, Recon, Sells, SpyFu, “that

Large companies often must deal with the problem of disgruntled former employees and customers with axes to grind. These individuals can take their case to the Internet to get a wide hearing. What can you do about it Well if you re Bank of America you can throw money at the problem by purchasing a lot of domain names….

Comcast® Business Class – Official Site Sign Up For Comcast Business Class, Make Your Business a Fast Business
Search Engine Optimization, Google Optimization – RSS Feeds

Tags: America, Bank, Domain, Goes, Name, Shopping, Spree

Driving Leads Through Smart Domain Development presentation from Affiliate Summit West 2009, which took place January 11-13, 2009 in Las Vegas, NV.

Speaker:

• Monte Cahn, CEO & Founder, Moniker.com / SnapNames.com

Are domains a part of your affiliate marketing strategy? If not, they should be. Discover the power of direct navigation and learn how domains can impact SEO/SEM.

Slides from this session are available at http://www.slideshare.net/affsum/driving-leads-through-smart-domain-development-presentation

More details on Affiliate Summit at http://www.affiliatesummit.com/

Note: the companies and positions listed above were current as of the time of the conference. Some of this information may have changed since then.

Video: Driving Leads Through Smart Domain Development

Affiliate Marketing with Shawn Collins

Tags: Development, Domain, Driving, Leads, Smart, through

According to Matt Cutts, speaking at a recent PubCon, Google will be looking at why exact domain matches rank so well. For example, if you have a site at blue-widgets.com it may rank a bit too well for the keyword phrase [blue widgets].

Curious.

Don’t Google know?

More likely, Matt would not make a concrete statement, one way or the other. “Yes, exact Match domains rank better!”, is not something Matt is likely to say.

Secondly, the implication is that exact match domains are a problem.

Why Use Exact Match Domain Names

Exact match domains names, as the name suggests, are domain names that match the search keyword term. i.e. Hotels.com, shoes.net, planetickets.org etc.

Is it a good idea to adopt this strategy for SEO? Ask ten different SEOs and you’ll likely get ten different answers.

On the plus side, an exact match may help you target one, specific keyword phrase. Your link text and domain name match up naturally. The domain name will likely be highlighted in Google’s search results, thus giving the listing more visibility. There may be ranking advantages, depending on who you ask.

On the negative side, an exact match only “helps” you target one keyword. It may be too generic for wider applications, such as brand building. Exact match domains may be over-hyped, and not worth a premium. There are, after all, many domains ranking #1 that aren’t exact match, so it is debatable how much SEO advantage they actually provide, particularly as Google keeps pushing brand.

Is There A Problem With Exact Match Domains?

So why would Matt imply exact match domain names might be a problem?

It is understandable that some in the SEO community – perhaps an SEO working on client sites, or those who don’t own any exact match domains and see others ranking above them – would have a vested interest in making a noise about the competition. If webmasters make enough noise about it, then Matt Cutts may feel a need to respond.

The supposed ranking power of exact match is probably a red herring. The problem Google may be hinting at is that exact match may be more likely to be involved with spam, thin affiliate, or other low value content than other types of domains. In other words, it becomes a quality signal.

If that is the case – and I’m not saying it is – then that may be the reason Google would look closer at exact match domains, not the fact that a domain matching a keyword is somehow evil.

Because it isn’t.

There is nothing wrong with owning an exact match domain.

Should You Buy Exact Match Domain Names?

Aaron covered this question in an earlier post, Why Exact Match Domains Aren’t As Important As Many SEO’s Believe.

In summary, it depends.

It comes down to business fundamentals. If you’re trying to build a unique brand, and resulting keyword stream, then an exact match domain name will be a hindrance rather than a help. You’ll forever be competing with generic search traffic. Keyword domains names aren’t particularly memorable.

The premium that an exact-match domain name commands, when sold on the after-market, may not be worth it. You don’t need an exact-match domain name to rank well, so the money may be better spent getting a new domain name to rank. Or, alternatively, you could buy an existing site that already ranks well for your keyword, and others, for similar money as an inflated exact match domain.

Finally, if you’re competing with a clear market leader, then generic isn’t going to help you much. i.e. owning searchengine.com isn’t going to make Google lose any sleep. You may also be over-looking an opportunity to differentiate your offering against the market leader in terms of brand. Think Blekko vs searchengine.com.

SEO Book.com – Learn. Rank. Dominate.

Tags: Domain, Exact, Match, Name, Should