Volume Nine’s Content AI Content Scoring Tool
We’ve been using this internally for our clients, but as of Spring 2018 we decided to release our content scoring tool for fellow marketers, SEOs or owners trying to work their way through content optimization.
Why We built it
Everything else on the market was pretty, but it wasn’t staying up to date with current best practices.
Most of the available content scoring tools use a primary keyword and check to see where and how often it’s included. Some of the enterprise SEO tools available on the market go a step further and use LSI to derive a list of related words. Essentially they crawl the top 10 results of search results for your primary keywords and provide a list of the most frequent words utilized. Not bad, but not quite great either.
We couldn’t find a tool that kept up with how we know Google evaluates content and also what has been most successful for our client base over the past year.
So we built a tool to expedite evaluating and optimizing content for our clients based on the following philosophies:
It’s good to have a primary keywords, but in a post hummingbird world it’s also important to consider secondary keywords mapped to a page.
Keyword density is a thing of the past. Include your keyword at least once in your content, but if you have it too much, you’re going to have a bad time.
Relevancy is in, in a big way. However just copying the most common words from your competitors isn’t that helpful. Google has stated that Rank Brian is one of the top 3 things affecting ranking positioning today. So it stands to reason that utilizing artificial intelligence to evaluate content makes a whole lot of sense.
How we are using artificial intelligence
We started using AI for content scoring before it was the cool thing to do. We built our tool using Alchemy and started seeing massive results for our clients by having a better picture of what relevance to a keyword phrase really means – it gave us a short-cut to improve user experience.
Alchemy was bought by Watson and our tool got a bit of an upgrade and is now utilizing Watson Natural Language Processing to provide related phrases.
Results of the Tool
What we were hoping to see (and saw):
We were hoping to see increase rankings not only for the primary keyword, but for the host of secondary keywords that are related to that primary phrase. Many of our clients started seeing dozens and in some case hundreds of additional related keywords they were getting visibility on.
What we weren’t expecting (but got really excited about):
This methodology did more than increase rankings and drive traffic. In some cases, it actually started improving the conversion rate on the website and in a few we saw a huge increase in average order value. In retrospect, it made sense – the tool was giving us a dialed list of everything a user wanted to know about that keyword phrase, which translated to things like barriers to sale, key product features and trust indicators they wanted.