Rank In Google With Certainty – 2 Metrics Reveal That You Will Definitely Rank Well in Google!
Over the last few months we have published a LOT of GREAT content for customers in all industries at ContentRefined.com
Wouldn’t it be amazing if we could say with statistically significant confidence what metrics an article needed to hit in order to perform well on Google?
See Inside Our Content Marketing Continuous Improvement Process!
We track a lot of data for every article we publish including date published, word count, MarketMuse score, keyword difficulty scores and ultimately search position.
With all this data we had to analyze and boil the information collected down to some actionable insights!
In this post, you will get to see the proprietary data from ContentRefined on how different metrics most impacted the current ranking position of an article.
Why Share All This Exclusive/Proprietary Data???…. Stupid Not To!
Honestly I am geek for this stuff and very very excited about the results so I am happy to share!
If you want to benefit from our experience, you can sign up to ContentRefined and have our team create optimized content for your site!
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Questions I Will Try to Answer:
- What measurable content metrics impact the final search ranking of a product the most?
- How does the MarketMuse score correlate with SERPs?
- Do we have enough data to do some multi-variable regression analysis and say with x% confidence that if an article is ____ long with a Market Muse score over ____ trying to rank for a keyword with a competition score of under ___ it will be on the first page 90% of the time.
Data Analysis Method (unless you are a super-geek feel free to skip):
For the following analysis, we have configured MarketMuse Content Score, Ferzy Keyword Competition Score, SECockpit Keyword Competition Score, and SEMRush Keyword Competition Score into data sets for the keywords from each article written by the Content Refined process during the months of December 2016 to March 2017.
These data sets, based around the article keyword, are then taken and combined with the article Google Ranking (using SERPFox) to run a correlation analysis.
Finally data points that were outliers, not published or published within the last 30 days were removed.
The purpose of this analysis is to determine the strength and significance of each metric as it relates to the Google Search Rank for the target keyword. Knowing which combination of scores provides the best correlation about how well an article will rank can vastly improve our ability to produce articles that deliver marketing results!
Moving forward this will help us refine (pun intended) our content creation process as we focus on the metrics that will help predict an articles ability to perform.
This analysis will help us evolve from the “spray & pray” method of content marketing currently used and help us engineer the creation of content that delivers results!
A lot of keyword research tools provide an estimation on the Keyword Competitiveness / Difficulty / Competition score. But… which score is the best indicator that if the score shows it is easy to rank for the article you create for it actually ranks?
What Competition Score Is The Best Indicator Of Our Ability to Rank for a Specific Keyword?
Here is what our data showed when we compared 3 Keyword Competition scores to the final SERP of an article…
- SECockpit – My favorite keyword research tool had a weak Correlation of 32%
- SEMRush – My favorite site reverse engineering tool and also an okay free keyword research tool has a low correlation of 38%
- Ferzy – A new tool dedicated to analyzing all aspects of a keywords difficulty had the best correlation with a moderate correlation of 45%
The numbers show SECockpit had the widest spread and was the worst at predicting the eventual ability of an article to rank for a given keyword.
The best was Ferzy with a Ferzy score of under 30 showing the ability of these articles to rank quickly!
Our Secret Weapon – Article Topical Depth Score vs SERP
The difficulty of the keyword is one very important metric clearly but what about the “quality” of the article in terms of the articles ability to rank?
We use MarketMuse for our own money sites and as part of the ContentRefined content creation process. We have found it very helpful as a guide for our already great writers to help them cover a topic in depth and not just superficially.
Think of it as a very powerful (and VERY expensive) Google Suggest tool that provides important keywords relevant to the topic we are writing about.
What we wanted to determine was how well would articles rank based on their MarketMuse score and if there any correlation.
Here are the results showing the MarketMuse score vs. SERP for the data set of articles…
MarketMuse Correlation = -61%
Meaning – There is moderate to strong correlation saying that the higher the MarketMuse score is the more likely the article is going to rank well in Google.
Multi-Variable Regression Analysis
So what does the data reveal in terms of the magic combination of Competition Score, Market Muse Score and (some other magical metric) that results in 100% certainty you rank #1 every time?
Sadly no data combination gave us the statically significant confidence we felt comfortable reporting but here is one very interesting takeaway from the data…
Of the 9 articles included in the analysis that had a MarketMuse score greater than 40 and a Ferzy competition score of under 30 8 of the 9 (88%) ranked in the top 10!
If this holds when we get more and more data to analyze it is indicative that we have an almost 90% chance of ranking in the top 10 when we create a good article that covers a topic in depth (ie MM score over 40) and are going after a low competition keyword (Ferzy score of under 30).
Clearly, this is a sweet spot for where we want our articles to be positioned to have the highest chance of delivering predictable results!
Conclusion – How have our systems changed?
We aren’t done… as more and more articles are created we will track more and more data for us to crunch on. This ongoing analysis will continue to help us better define what articles will perform well in Google!
At ContentRefined.com we are continually trying to really really dial in our content marketing skills and deliver world class content but more than that we are a marketing first content agency focused on delivering results!
Moving forward we will work to aim at what looks to be a sweet spot for the articles we are creating whenever possible…
- MarketMuse Score greater than 40
- Ferzy Keyword Competition Score less than 30
As we continue to refine our process we will continue to add requirements to our articles and costs to our process so we continue to deliver articles with a higher confidence of being able to rank and deliver results!
As a result of continuing to improve our process, we will be raising our prices in the very near future at ContentRefined.
NOTE – All existing and new clients, in the very near future, will lock in the current lower prices but will receive the benefits of our continually improving process!
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Powerful post, brother. I love this kind of Data. Bonus, short and easy to read!!
Would love to know Long Tail Pro, Ahrefs and Moz scores and correlations, if you have a VA who is bored and wants to roll all of those into another article. Sure some people will whine about transparency, but give me enough data points and YOUR blog and I’ll trust it. 😉
I’d be curious is there is a certain search traffic (monthly volume) correlation that explains why your score is 88% and not 95% . Are you seeing ANY correlation between search volume and difficulty ranking?
This article data is solid gold dude! Shared!
Thanks Brad, appreciate the share!
Not sure if the value is there for Market Muse. Very expensive.
Hi Emmett, very fair point… definitely not a “must” for people as it is very expensive! I wish I had enough data to quantify the benefit it offered but unfortunately, I do not.
Great post Jon!
Very insightful post Jon, always interesting to see the behind-the-scene work of a successful business like ContentRefined.
Your process is even more data focused that I initially assumed and it’s great to see that it continues to improve.
Thanks for the mention as well.
your image show chinese words”改善”，so suprise haha, i am china seoer. like your article.
Great article, I like the data-driven approach to content creation.
One huge point I think should’ve been addressed is the domain the content was published on.
We all know how much this can affect rankings.
Were the articles placed on new sites? What kind of metrics did the websites have? Did you get better results from domains with higher metrics? Were they all placed on the same site?
Can’t wait for your reply
Hi Blaine, definitely agree that could be a big factor. We did not look at it in this analysis but plan to look at the DA / TF of the site in the future. These articles were published on many different sites which shows that these results can be predicted regardless of the site you are posting on.
MarketMuse surely looks interesting, just betting the price will be a bit steep as mentioned here at least for my use..sure they’ll have their target. Great piece Jon, I am sure your results are also an inspiration for a lot of folks with your dedication and commitment brother…nice to see you really kicking it in 2017.
And indeed, regarding Ferzy, the current offer Nick has is great and priced very, very nicely for the current overdelivery. I like that research tool. I replaced SemRush with Ferzy now for competitive keyword research ideas on my end, and it’s yet another solid tool compared to the others you also listed for value/money.
Keep all those great pieces coming Jon..nothing beats case studies and I surely
devouring each of them..regards
Wow, what a gem!
Everything we are doing now is heavily to do with great content. Picking the best topics with lower competition and really searching for these has served us well. We are finding we need alot less links to rank.
Super interested in this Marketmuse
Jon,
Thank you for the data-driven article! Great to see actual info instead of hype (like other folks).
Something that wasn’t included, but curious if you tested – does this same correlation continue on higher more competitive KW?
In my experience techniques that work on low comp KW’s does not always translate to higher comp KW’s.
Advice/Experiences?