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Our CTO uses Market Brew’s highly-correlated search engine model to inspect “online dating” organic search results, and reveals why $78,000.00 USD per month in revenue is at stake between eHarmony and Spark.com.
Nothing magical or black-hat is discussed here. We will use the Market Brew predictive platform to first reveal the true search ranking situation for the phrase “online dating”, a phrase that brings potential traffic and leads for the online dating industry.
First, how much traffic? The Google AdWords Keyword Tool (below) for “online dating” and all of its long-tail permutations account for just over 1.3 million searches on Google U.S. alone in December 2014. I am going to assume that the majority of traffic for all long-tailed versions of this root phrase will roughly correspond to the analysis we do here for the root phrase.
As you can see from the screenshot, the cost of the “online dating” traffic, using the AdWords Keyword Tool, is $8.33 per click. 1.3 million searches at $8.33 per click is $10,829,000.00 USD worth of traffic (to Google) per month. This article sums up the click-through rate picture very nicely: position #1 gets roughly 36%, position #2 gets 12.5%, and position #3 9.5%.
The Market Brew search engine model defaults to this, but as a user you can change the click-through rates if you want to model an alternative scenario. However, for this scenario, we will go with the published findings. We are looking at #3 jumping to #2, which would be about a 3% CTR increase, or roughly 39,000 additional clicks per month.
So what does this mean in terms of potential revenue? Shayan Zadeh, the CEO of Zoosk has stated that they convert around 10% of all online visitors. According to Statistic Brain, the average online dating customer spends $239 / year, or about $20 / month. So these 3,900 additional conversions mean roughly $78,000.00 USD / month in additional revenue for Spark.com (or an equal loss in revenue for eHarmony.com).
Here’s where it gets interesting. Using the Market Brew system, we can implement the changes to capture this additional $78k / month in a matter of hours. If you were a SEO professional, your billable rate could be $10k / hr and the client would STILL be profitable.
Of the many ways you can use the Market Brew predictive platform, there are two typical approaches that are used. Both involve setting up an Analysis Group first (users can setup unlimited Analysis Groups). The broad approach – is where you add many keywords (hundreds or thousands) and their respective websites, and track (predict) rankings across an entire competitive landscape. The other, which we will use here, is becoming the go-to approach for our users, as it offers hyper-accuracy for any given search engine query.
The first thing you will want to do is create a new Analysis Group. Use the Setup Wizard and it will self-calibrate the search engine model to Google US results, automatically. First, add your keywords. I’m going to target a specific search engine environment here; namely, the phrase “online dating”.
The system will automatically determine which websites to model. You can also add additional websites in this step (not shown), but for this use case, I am going to be inspecting eHarmony.com and Spark.com, which are already listed here.
Let’s go where the money is and inspect the top 3. I’ll throw in 2 more sites (Market Brew requires a minimum of 5 sites to do its self-calibration mechanism). And away we go…in about 100 minutes, we are going to be looking at some amazing data.
First off, it looks like our standard search engine model is working beautifully, once again. All 5 sites are in correct order (according to the comparison against Google US). Our search engine model is already giving us a highly correlated model of what is happening on Google, so no need to manually adjust any of the query scoring boost factors.
This Google snapshot was taken in the Silicon Valley on Jan. 28th, 2015, the date of this writing.
To me, I want to generally see some decent alignment with our model. This picture gives me incredible confidence. Why? You have the leader, OkCupid.com, nailed perfectly. The next two, eHarmony.com and Spark.com, are also in the right order. And finally, you have the two lower sites well below, but also in order. The only weird thing is Spark.com showing it’s registration page on Google, but on Market Brew’s search results, the home page is showing. We will want to see what is going on there – it might be a predictive signal.
Remember, you are seeing things on Market Brew around 45-60 days BEFORE THEY HAPPEN on a search engine like Google. While 100% correlation is great, unless nothing is changing, it rarely will be the case. A Pearson Correlation says 70% or higher is an A, 50% is a B, 30% is a C. 99% of our correlations are 70% or higher. For the curious, this one happens to be 92% correlated (A+).
I’m going to focus on the race for #2, but you could just as easily focus on the race for #4.
The first thing I’d like to point out looking at this right away: highlighted in green, OkCupid.com at #1 is reeeealy far away from the rest of the pack. That would be a great use case to go into our search engine model and to find out what is going on, but that’s for another time.
Highlighted in orange, Spark.com’s position at #3 has more Net Total Link Flow than eHarmony.com at #2, yet still trails eHarmony.com. If you have used Market Brew in the past, you almost know the optimization is going to be semantic in nature. Let’s find out how much and what needs to be done.
First, let’s click on the little Excel icon next to the search bar (not shown) and take a look at the query scoring breakdown.
It looks like both Spark.com and eHarmony.com’s top Market Focuses have missed their marks (by the way, OkCupid.com, you should NOT have a branded keyword in the Market Focus EVER). How much did this effect their total query scores?
For some reason, Spark.com is penalized much more than eHarmony.com. Taking a quick look into their Market Focus Baskets, respectively:
It looks like eHarmony.com has much more correlation with “online dating” then Spark.com, so things check out. Let’s dig right in, and see how Spark.com might bump itself up to the #2 ranking position for “online dating”.
With Market Brew’s heatmap, you quickly can see #2 is within reach (hot), whereas #1, #4, and #5 are further away (cool). And after analyzing the query score breakdown, we aren’t surprised to see the following recommendation:
As a side note, it’s very interesting to me that for such a competitive market, the search engine model still has a LOT of correlation with the META Title. We’ve seen META Description correlation go away with Google over the years, but META Title is still very strong in many markets.
And even though Spark.com has more Link Flow than OkCupid.com, there are still some very interesting Link Flow optimizations that we can implement. Remember, the Link Flow still makes up 33% of this particular optimization simulation:
Ok, we have all the information we need if we’re Spark.com. This took about 100 minutes of system processing with no user needed, and 10 minutes of user analysis. Now the fun part.
First, let’s go back to the Semantic Score breakdown, where it told us to focus on both Market Focus and META Title.
We will drill into Market Focus first. In Market Brew, you simply click on the Market Focus, and you will have a clear picture of what is going on and how to improve it in under 1 second.
First off, just a simple semantic analysis shows that “online dating” isn’t even the top correlated phrase. We can easily add a few more mentions of “online dating” naturally within the scope of the home page.
Next, the incoming anchor text has very little associated link flow with the keywords “online” or “dating”. There is associated link flow with “daters”, but sadly, this keyword brings 100 times fewer visitors.
So here we simply click on one of the top keywords, here the word “spark”, and view the link listing of all incoming links to this page, filtered with this word.
Again a few seconds gives you an action item for improving Market Focus. Instead of having the current ALT text on this image, “Spark – a fun site for serious online dating” would be a perfect improvement. And “Spark.com” could be “Spark.com – Serious Online Dating”.
For the META Title optimization, let’s just look at the original search listing. OkCupid.com clearly sets the mark with the highest META Title score of 2885.
OkCupid.com’s META Title is clearly much more targeted. Only 4 words, and 2 of them are “Online Dating”. Spark.com, on the other hand, has the keywords in there, but they are targeting other keywords as well – they would be much better off attacking the #2 position for “online dating” and setting up a separate page dedicated to “fun”, “singles”, and whatever keywords they are trying to cram into one title.
Ok, we’ve easily identified the fixes for both the Market Focus and META Title. What about that other 33% of this optimization simulation, the Link Flow? The Link Flow clearly can be improved. With another click of the button, we can view the Webpage Scorecard:
Spark.com has the potential to increase the effective ranking power (Net Total Link Flow, think of it as a “scored” version of PageRank) by about 59% (from 173 to 275). Let’s click on the details tab and take a look at the family of algorithms that are being applied:
The first algorithm, “# of Exact Duplicate Webpages”, clearly shows that Spark.com has some canonicalization issues with it’s home page. Clicking on the penalty reveals what is going on:
Simple fix: add the rel=”canonical” tag to your home page template, pointing to the non query string version (i.e. http://www.Spark.com/).
Next, let’s take a look at that big one…the “Outgoing Paid Links” algorithm. It has the highest effect on our ranking power, at 11.61%.
This is a snapshot screen where Market Brew overlays its data on top of the HTML. You can see how Spark.com’s Home Page is clearly triggering the “Outgoing Paid Links” algorithm. A bunch of external (different top-level domain) sites all together with no text around them. Clearly not editorial, and to a search engine, clearly look like “paid links”.
We can simply consolidate all of these links on one internal page in the site, and just have one link to that page. That removes the external linking from this page (you can use this technique for headers and footers that have this same problem), which will automatically remove this penalty, since this penalty looks for External Outgoing Non-Editorial Links.
The Link Flow Balance screen shows you an internal link flow view of your subdomain. Looking at Spark.com’s Link Flow Balance screen, the top webpage is actually the registration page! This may also explain Google’s initial reluctance to show Spark.com’s home page, and instead showed it’s registration page. Spark.com’s registration page suffers two times the penalties (not shown) than the home page, and is clearly not the correct page to compare against all of its competitors, so I will keep with the analysis of the home page instead.
In a typical broad Analysis Group, you would have 500 keywords here in the “target” column, and your goal would be lining up each phrase with each Webpage’s Market Focus in your site. In this use case, we did a very detailed Analysis Group, focusing only on the phrase “online dating”. So I have omitted the “target” column here.
For Spark.com, the fix is easy: just add more links to the home page internally, until it becomes the top page. Typically this is easily balanced using the header, footer, and some other common components within your CMS. We have already covered how to fix the Home Page’s Market Focus Basket (above), and I will not go into that here.
By the way, Spark.com, having 1% of your Link Flow go to the “Terms, Conditions, and Services” page is a big no-no. If you are doing this, you are effectively throwing out a penny for each dollar you spend on SEO.
I took about 30 minutes out of my day, and produced $78,000.00 USD / month extra revenue for Spark.com. I just needed a beginner’s HTML and SEO skills to accomplish the work of a master SEO professional, and if I’m Spark.com’s SEO person, I’m a hero now.