Here’s a live case study with some eye candy. Case of the supermodels.

About a week ago, I stumbled across what may very well be the holy grail of search keywords.  These are keywords that, according to Google AdWords Keyword Tool, have the lowest possible competition (i.e. competition score of 0) and receive tens, if not hundreds, of thousands of local monthly searches.

I am referring to this as the holy grail, because we’re not  talking about a small handful of search keywords.  I’m not talking 5, nor 10, nor even 50 search terms.  I’m referring to hundreds upon hundreds of these keywords that you can dig up in the matter of 30 minutes.

Now, don’t worry.  This is not an eBook sales page and I’m not selling you anything.  You won’t need to spend $17 to discover what this big “secret” is all about.

So what is this holy grail?

It is celebrity names.  I’m using the term celebrity lightly.  Even someone on the D-list has the potential to amass 20,000+ local monthly searches, as I will illustrate shortly.

Let’s look at an example.  Have you ever seen the show Pretty Little Liars?  Neither have I and I never will.  However, I have heard of it.  (When I used to live in Hollywood, there was a billboard advertising it just down my street.)  The show has a lot of pretty young faces, but none of them are famous.

Anyway, I will show the potential of celebrity names using Pretty Little Liars.  Here is their cast, as listed on IMDb (http://www.imdb.com/title/tt1578873/)/

Recognize any of the names?  Probably only Chad Lowe.  Next, type them into Google AdWords Keyword Tool and check out the results.

The only keyword with a hint of competition is Chad Lowe, because he is an established actor.  All the other names get searched a ton on Google, but have 0 competition.  “Lucy Hales” receives 110,000 local monthly searches and almost a quarter million global searches!  There are 2 other names receiving about 50,000 local monthly searches, many with 20K+ and 30K+.  In fact, the least popular search phrase still gets 4,400 searches a month.

I didn’t kid you.  Pretty promising, right?

Now, Pretty Little Liars is just one TV show.  Plus, we didn’t even exhaust their full cast list.  You can find thousands of TV shows on IMDb, even more movies.  Think about the number of actor name keyword phrases this generates.

Moreover, this is only a fraction of the whole celebrity name playing field.  Beyond just actors, we have musicians, athletes, models, etc.

These celebrity name-based searches cater to a number of different types of web sites.  For instance, if we just focus on the TV & Film industry still, you can create any of the following types of sites:

• TV show fan site
• Celebrity fan site
• Movie blog
• TV blog
• TV show spoilers
• TV show gallery
• Video download site
• And so on…

The question that remains is whether these holy grail keywords will indeed translate into massive amounts of search engine traffic.  This is the question I hope to solve through this case study.

In this case study, I will create a fashion models gallery site.  There will be some nice eye candy, to keep you engaged. 😉  Let’s call this the Case of the Supermodels.  Like the Case of 300,000 and Counting, this will be a live case study.  I will be posting updates in real time.  The first phase of this case study will be to gain organic search engine traffic by ranking for the names of targeted supermodels.  The next phase will be then to monetize this traffic.  I have a couple thoughts around this already and will test some monetization tactics that will be new-ish to me.

Today, I have already registered a fresh domain name: clubsupermodel.com.  See my GoDaddy receipt below:

I have pretty much created the site.  Later today, I will upload it and then run the Rapid Google Indexer to get the domain indexed.

Day 1 – 8/4

• Registered ClubSupermodel.com.
• Uploaded the site.
  • Club Supermodel is a photo gallery site of supermodels.  In its current design, it is semi-autopilot and autoscale.  I wrote a script that will automatically pull photos from various sites.  However, the process isn’t completed streamlined.  I need to moderate the photos to check that they are all relevant.  (In the way the script currently works, most photos are not relevant.)  For each photo uploaded, the site will automatically create a new page for it (i.e. autoscale).  I am focusing on photos that are more “rare,” which constitutes personal pics, cell phone pics, family and friends photos, etc.  This is the value-add component of the site and also differentiates Club Supermodel from other galleries showcasing the same models.
  • Upon launch, the site has 179 photos and about 200 pages.  I picked 10 models to start off the site and will begin SEO over the next few weeks focused on only 2-3 models.  With time, I will be adding more models to the lineup.  There is not much text, yet.   I will be adding more text content over the next couple  days and will provide more detail on this topic when it happens.  I have integrated some social media components (i.e. Facebook Like button, G+ button), as social proof seems important in the post-Panda update era.
  • Also, I added in a couple banners to fashion-related affiliates I found off LinkShare.
• Integrated Google Analytics.  As I start seeing SEO results, I will begin posting regular traffic statistics from Google Analytics.
• Ran the Rapid Google Indexer for clubsupermodel.com.

Day 2 – 8/5

• Today, I start on SEO for the site.  The initial efforts will target 2 supermodels:
  • Candice Swanepoel keyword stats:
    • “candice swanepoel” – low competition; 368,000 global monthly searches; 110,000 local monthly searches
    • “candice swanepoel photos” – low competition: 9,900 global; 1,900 local
  • Doutzen Kroes keyword stats:
    • “doutzen kroes” – low competition; 246,000 global monthly searches; 33,100 local monthly searches
    • “doutzen kroes photos” – low competition; 4,400 global; 720 local
• On-site SEO:
  • For each of these girl, I will write up a 500+ word bio on their profile page.  This will go at the bottom of the page.  Note that these are unique articles.
  • I will also add <meta description> tags across all pages.
• Off-site SEO:
  • I will queue up 2 3-tiered SEO Matrices using Link Pushing (see this article for more info) for the 2 girls.  Then, I will overlay both Matrices with a 4th tier of social bookmarks (using Backlinks Genie).
  • I will use Backlinks Genie to social bookmark the 2 profile pages and 2 gallery pages.
  • As a result, this will use up a few iterations of my Backlinks Genie account and slow down the Backlinks Genie case study by a cycle or two.
  • I will also put up some footer sitewide links anchoring “candice swanepoel” and “doutzen kroes” across a couple of my well indexed content sites.

Day 4 – 8/7

• I added approximately another 150 photos between the 2 targeted models just now.  To do find and gather such a large number of photos so quickly, I had to download them from other fan sites.  I used this free software called HTTrack Website Copier to accomplish this.

Day 6 – 8/9

• The off-site SEO work with both Link Pushing and Backlinks Genie started processing today (i.e. they were in queue prior to today).  Over the next week or so, I should start to see some SERP movements.
• Meanwhile, out of curiosity, I checked my Google Analytics stats.  So far, Google has sent over 13 visits.  Though a statistically insignificant sample size, the results looked quite promising.  Here are the aggregate stats for these visitors:
  • Pages/Visit = 5.77
  • Average Time on Site = 56 seconds
  • Bounce Rate = 38%

Day 11 – 8/14

• I’m vacationing in Vancouver now, but here’s quick update on the case study…
• I noticed some decent SERP movements:
  • Candice Swanepoel = 51
  • Candice Swanepoel photos = 23
  • Doutzen Kroes = 70
  • Doutzen Kroes photos = 12

Day 12 – 8/19

• After a 5 hour delay, I finally returned home a couple days ago.   And, tomorrow, I’m moving to lower Manhattan in New York City. 🙂  Before I get packing, here’s another update…
• Content changes:
  • Added pagination to the galleries.  This should improve the user experience, and hopefully also increase page views, lower bounce rates, and increase average page views per visitor.
  • Loaded in more photos.  I will be doing this every 1-2 weeks and will not post an update each time.
• SERP movements:
  • Candice Swanepoel = 36
  • Candice Swanepoel photos = 15
  • Doutzen Kroes = 39
  • Doutzen Kroes photos = 11
  • I’m tracking SERPs for all other listed models and found some to have gained top 100 positions, despite not having done any SEO targeting those terms and URLs.

Day 25 – 9/1

• Sorry guys, I’ve been kinda neglecting this case study.
• I’m still seeing some upwards movements in the SERPs from the link push SEO Matrices I kicked off a while back.  However, it’s very minor.  So, yesterday, I decided to kick off more link pushes targeting “Candice Swanepoel.”  Unfortunately, I have so many link pushes queued up that they won’t be fired off till the 13th.  (I really like the Link Pushing service, as you can see, and am on the 50 pushes per month plan.)   Unless there’s something significant worth noting, I won’t be updating for a few weeks, after the new SEO back links take effect.
• SERP movements:
  • Candice Swanepoel = 29
  • Candice Swanepoel photos = 12
  • Doutzen Kroes = 23
  • Doutzen Kroes photos = 9

Day 47 – 9/23

• I’m not where I want to be yet.  However, still moving up the ranks slowly, but surely.  Here’s the latest.
• SERP movements:
  • Candice Swanepoel = 19
  • Candice Swanepoel photos = 11
  • Doutzen Kroes = 21
  • Douzen Kroes photos = 10
• Traffic for 9/17 – 9/23:
  • Only 60 visits, but 531 pageviews (i.e. 8.68 pages/visit).  People love ’em pics of supermodels! 😀
  • Bounce rate: 33%.  This is very good.
  • Average time on site: 2 min, 25 sec.
  • I’ve received traffic from 17 keywords w/ 10 related to either “Candice Swanepoel” or “Doutzen Kroes.”  This week, I’m hovering between page 3 (bottom) and page for “Candice Swanepoel,” but the term still brought in 19 unique visits.

I will update this case study with status updates in real time.