Did You Know? Understanding Your Raven Content Scores

How To

Did You Know? Understanding Your Raven Content Scores

One of the best features of Raven’s Content Manager is the ability to analyze your content and get structure and keyword recommendations.

This is done though our integration of Copyblogger’s Scribe, which helps users optimize content for SEO. Raven also gives you a readability score for your content, including the age level and grade level of the text and your score on various readability tests.

Let’s take a tour of Raven content scores. First, we will need to add content.

How to add content to the Content Manager

Navigate to Content > Manager and you’ll see a couple of options.

Screen Shot 2013-07-12 at 10.55.28 AM

Click the Add Content button to write a brand-new piece or paste in an existing piece of content. Click the Order Content button to order quality content with a click of a button with Raven’s Textbroker integration.

Once you click the Add Content button you will be directed to the create page.

Screen Shot 2013-07-12 at 10.56.39 AM

From there, you’ll add your content into the fields given: title, the content itself, meta description, tags to help you organize the content on your blog or site, and the keywords you’re focusing on for that piece.

You must have the title, content, and meta description boxes filled out to run a Scribe analysis. Once all three green checkmarks are visible, you can select “analyze”.

Screen Shot 2013-07-12 at 10.57.55 AM

Or click the Save button at the bottom of the page to analyze your content later. Just look for the Analyze with Scribe button at the top right of the page.

Screen Shot 2013-07-12 at 11.00.12 AM

When you click the Analyze with Scribe button, Raven will start retrieving your content’s metrics and provide you with an analysis report. 

So what do all these scores mean?

At the very top of the page you will find the Content Statistics, which contain the Scribe Site Score, the Scribe Document Score and the Readability Score.

Screen Shot 2013-07-12 at 11.01.57 AM

Scribe Site Score: The Site Score calculates how well a particular piece of content relates to the rest of your website’s content. A website that has content with a common thread or theme could be viewed by the search engine robots as a more reliable source of information for that topic. Therefore, it might be more likely to show up in the SERPs for general searches related to that topic. This is valued on a range of 0 to 100, with 0 being the lowest and 100 the highest.

Scribe Document Score: The Document Score calculates how well a particular piece of content is optimized for the search engine robots – for example, is it missing any key information such as a title or meta description? Those things can influence SERPs for specific searches. This is valued on a range of 0 to 100, with 0 being the lowest and 100 the highest.

Readability Score (analyzed by Raven): An age and grade level score indicating how difficult a document is to read based on structure and word choices.

If you click on the Readability Score results, you can find even more specific content scores.

Screen Shot 2013-07-12 at 11.04.38 AM

Readability Metrics

Flesch-Kindcaid Reading Ease: The Flesch-Kincaid Reading Ease score is the result of a mathematical formula that incorporates the average number of syllables per word and the average number of words per sentence per 100-word block of text. Results are measured on a scale from 1-100.
Recommended level: On the 1-100 scale, 1 is very complicated to read and 100 is very easy to read. Most readability resources recommend writing to 60-70 range.

Flesch-Kincaid Grade Level: Like the Flesch-Kincaid Reading Ease score, this is a mathematical formula that measures syllables and sentence length. However, the results are given as an academic grade level, from 0-12. Negative results are rated at 0, and any grade level over 12 is listed as 12.
Recommended level: It depends on your audience, but 7th-8th grade is a good standard – that captures more than 80% of U.S. adults.

Gunning-Fog Score: The Gunning Fog index focuses on “complex” words – those with three or more syllables – as part of its mathematical formula for readability. The result? A grade-level score from 1-unlimited.
Recommended level: According to UsingEnglish.com, “The New York Times has an average Fog index of 11-12, Time magazine about 11. Typically, technical documentation has a Fog Index between 10 and 15, and professional prose almost never exceeds 18.” The ideal score is between 7 and 8, depending on your audience.

Coleman-Liau Index: The Coleman Liau Index relies on the number of characters instead of syllables per words for its calculation. It returns a U.S. grade-level score from 1-12.
Recommended level: 7-8, depending on your audience.

SMOG Index: This index analyzes words with three or more syllables from 30 sentences (10 from the beginning, middle and end, respectively) of your text to determine the U.S. grade level that should be able to read that text.
Recommended level: 7-8, depending on your audience.

Automated Readability Index: The Automated Readability Index mathematical formula has two variables: characters per word (instead of syllables) and words per sentence. Its scores correspond to U.S. grade level. If you get a score with a decimal, round up to the next whole number.
Recommend level: 7-8, depending on your audience.

 Word Count: Total number of words included in the content.

Are you ready to analyze your content? Raven Pro accounts come equipped with 20 Scribe analyses per month, while Agencies get 50. If you go beyond your allotted Scribe analyses, additional ones are only 27 cents each.

And if you already have a Scribe account, you can easily connect it to your Raven account via API key. This allows you to use the allowances from your own Scribe account instead of from your Raven usage allowance.

Screenshot 2:21:13 1:08 PM

It’s not eye-REEN, it’s e-RAE-nee. You can’t underestimate this gentle woman, who speaks fluent Spanish, cooks, and is earning a psychology degree for fun.

More about Irene Phelps | @RavenIrene

Comments are closed on this post