Rank in Google With Certainty? – Market Muse Review Updated Data Analysis

The “holy grail” we are chasing with our data analysis is being able to predictably rank an article in Google with certainty!

Our vision is being able to say… given a number of metrics for the keyword and article we can produce an article that ranks well in Google!

 

BEWARE!! – THIS POST HAS A LOT OF DATA!

If you don’t like data/statistics and geeking out on analysis I would recommend you skip this article!

 

I have previously talked about MarketMuse and it’s ability to suggest what keywords to focus on and which to use to add depth, all with the idea to create a better article that ranks predictably well in Google!

I have been using MarketMuse to enhance my money site portfolio but more importantly, provide top quality articles for Content Refined since November of last year and have been learning a lot!

This is where the second round of MarketMuse testing and analysis comes in. Previously we reviewed how the data for MarketMuse relative to Google rankings performed here – https://websiteincome.com/rank-content-in-google-with-certainty/. In that article, I shared the results of Content Refined articles success in Google using different available online tools I use.

While more time has passed and more articles continue to be created I figured we would be able to provide a larger set of data to use for research and provide a stronger analysis of the MarketMuse tool more specifically. So in this round of analysis, we went deeper and came up with more ways to analyze the results that MarketMuse provides each time you run your content through their ‘Content Analyzer’.

In this post I will run through the results of our second MarketMuse analysis in terms of their ‘Content Depth Score’ and ‘Word Count’ metrics on an absolute scale and weighted scale.

What do I mean by absolute and weighted in terms of MarketMuse? Well for absolute scores I used the exact score as provided by MarketMuse to analyze its ability to predict the ability to rank in google. For weighted scores I took the absolute score and divided it by the average and best scores, for the topic as provided by MarketMuse. Using the weighted scoring (which we didn’t last time) we hoped to be able to account for the niche or keyword competition level and recognize how much better than the average or best score you need to be in the certain topic to perform that much better in Google.

Lets Get to the Data!

We analyzed 2 pieces of a data in 3 ways each…

ONE – Content Depth Score

TWO – Word Count

Then tried to make the analysis a little more accurate by comparing (or normalizing) the score of the given article relative to the competition.

Analysis 1.1: Absolute Content Depth Score as a Predictor of Google Rank

Correlation: 38%

Statistical Meaning: There is a weak too moderate correlation that the higher the content depth score the more likely the article will rank.

Importance: 2 / 5 – This low correlation comes from not having a baseline for each topic’s competition. A score of 15 could be a great score for a topic but not be perceived well in this analysis since it is considered to low.

 

Analysis 1.2: Absolute Word Count as a Predictor of Google Rank

Correlation: 30%

Statistical Meaning: There is a weak to moderate correlation that the larger the word count the more likely the article will rank.

Importance: 1.5 / 5 – Once again there is no competition baseline to compare what a competitive word count looks like for a given topic but the correlation in this scenario comes from the larger word count having more room for quality content to be included giving an article more depth. Always something to keep in mind.

NOTE – We saw the very long posts seeming to perform better… 10/12 posts that were over 3,000 words ended up in the top 20.

 

Analysis 2.1: Weighted Content Depth Score vs the Avg as a Predictor of Google Rank

Correlation: 41%

Statistical Meaning: There is a moderate correlation that the higher the content depth score is relative to the average content depth score the more likely the article will rank.

Importance: 3 / 5 – When each content score is compared to the top 10 average in MarketMuse’s database the scores can be compared on neutral grounds. What I thought would be the most successful predictor is. We are excited to continue this analysis and overlay this normalized MarketMuse content score with keyword research data to take this analysis to the next level!

 

Analysis 2.2: Weighted Word Count vs the Avg as a Predictor of Google Rank

Correlation: 39%

Statistical Meaning: There is a weak too moderate correlation that the larger the word count is relative to the average word count the more likely the article will rank.

Importance: 2 / 5 – The highest predictor metric for word counts… this basically says it is important to have your article longer than the average of your competition. 

 

Analysis 3.1: Weighted Content Depth Score vs the Best as a Predictor of Google Rank

Correlation: 29%

Statistical Meaning: There is a weak too moderate correlation that the higher the content depth score is relative to the best content depth score the more likely the article will rank.

Importance: 2.5 / 5 – With the level of correlation it makes hard to trust but still trying to be the best or close to the best in the world of MarketMuse will help!

 

Analysis 3.2: Weighted Word Count vs the Best as a Predictor of Google Rank

Correlation: 22%

Statistical Meaning: There is a weak correlation that the larger the word count is relative to the best word count for a topic the more likely the article will rank.

Importance: 1.5 / 5 – There is usually one article with an astronomical best word count for the topic so this makes it difficult to compare. However being that one article with the best word count is a clear benefit in ranking.

 

SUMMARY

MarketMuse	Content Depth Score	Word Count
Absolute	0.38	0.30
Weighted w Avg	0.41	0.39
Weighted w Best	0.29	0.22

Two Important Take-Aways!

• For our articles that ranked in the top 10 they had an average weighted content depth score vs the average of 132% over the average content depth score of the top 10 in that topic.
• For the articles that ranked in the top 10 in terms of word count, we had a average of 92% of the word count vs the average word count.

The main concept to consider from all this is that while there is no easy or guaranteed way to rank, MarketMuse offers the opportunity to provide a competitive advantage to the varying degrees supported above.

Therefore if you do use it, to maximize its potential, to be most effective it is recommended that you stay above the averages and as close to the best content depth scores while writing between 1,000 – 2,500+ words.

 

Whats Next – Big Stuff Coming! 

Stay tuned over the upcoming weeks as I will continue to roll out additional analysis posts regarding Keyword Difficulty as a Ranking Predictor (what keyword research tool provides the best predictive ability) as well as Other Additional Factors as a Ranking Predictor over the upcoming weeks based on the results of my Money Site and Content Refined’s articles.

 

Want to Benefit from All of This Analysis?

As always I will be happy to keep sharing everything I am learning as we work very hard to get incredibly good at predictably producing content that will perform well in Google!

For you to benefit from all of this effort simply follow along in the posts or if you want to leverage these learnings you can use the Content Marketing team that is producing this data… ContentRefined is working very hard to become the best content marketing company in the world!

To give ContentRefined a try you can use this coupon to save 10% on month 1 – datageek – signup here!