In this post, we examine the differences between MarketMuse’s AI content planning and optimization platform and SearchMetrics’ ContentExperience. SearchMetrics is an enterprise SEO platform with some content-related features.
If you’re considering purchasing SearchMetrics primarily for its SEO capabilities, thinking of ContentExperience as a bonus, you may want to reconsider. At least the part dealing with ContentExperience.
Here are five critical differentiators that we cover in detail within this post.
- MarketMuse topic modeling is more sophisticated and more accurate than the model SearchMetrics ContentExperience leverages.
- MarketMuse offers robust content strategy and planning workflows with personalized difficulty metrics.
- MarketMuse provides greater understanding of competitive content than SearchMetrics ContentExperience.
- MarketMuse’s Questions application is far more potent than what SearchMetrics ContentExperience offers. We use natural language processing to analyze a massive corpus of data and find the most relevant questions on a topic.
- MarketMuse Content Briefs offer far more guidance to help writers efficiently and consistently create better content.
To better understand these distinguishing factors we offer examples throughout so you can see for yourself. Let’s get started!
Topic Modeling in MarketMuse vs SearchMetrics
First, we need to look at how each platform addresses topic modeling. The ability to accurately model a topic is critical to all the services we talk about in this post. If a platform provides poor data fidelity (quality) your content efforts could be hampered, to say the least. There’s no value in an optimization executed improperly.
TF-IDF applications typically suffer from several shortcomings, including being heavily keyword driven. The current algorithms used by Google look at content from a topical perspective and not that of a keyword.
Not all Word2Vec implementations are alike. The quality of the model varies greatly depending on its parameters and the size of the corpus. Here’s a post we wrote that provides additional information on what Word2Vec is and how it works.
Regardless of the technology used, it’s the output that counts. This is where SearchMetrics ContentExperience suffers.
Determining the most relevant topics that add to a page’s comprehensiveness is no simple feat. Semantic keyword analysis is a complex endeavor, and there is no unique algorithm that can solve the problem. Thinking otherwise shows a lack of appreciation for the intricacies that are involved.
As our patented methods and systems reveal, we rely on many different algorithms working together as an ensemble to produce the desired output. Here’s more detail on how MarketMuse identifies semantically related topics.
To illustrate the difference in approach between MarketMuse and SearchMetrics, let’s use a real example about the topic “how to grow an avocado.”
Take a look at the screenshot from SearchMetrics ContentExperience listing the “must-have keywords” and “recommended keywords.” At first glance, everything looks fine. It’s only when you take a more in-depth look that you realize the fundamental problem.
All of their suggestions have nothing to do with the topic of growing an avocado. These recommendations all concern the avocado itself, its nutritional value, and its use. But there’s nothing about how to grow the plant.
Contrast that with the topic list offered by MarketMuse. The difference is readily apparent. An article on growing avocados needs to discuss the different varieties, soil and light requirements, watering, different ways of seed starting, optimal growth temperature, etc.
What SearchMetrics’ topic model provides is really a mixed bag of recommendations; it’s far too generalized. Follow them and your content output will most likely be misguided.
For example, some of their recommendations are about the health benefits of avocado. That has nothing to do with growing them! So, if you’re going to write a blog post on that subject, make sure you cover all the important related topics.
Here’s a partial screenshot from MarketMuse of the 50 most important topics related to the benefits of avocados, sorted by relevance.
To write comprehensive content, you need to address all the essential aspects of the subject. SearchMetrics’ topic model misses the mark.
Content Strategy and Planning
More pages. More problems.
It’s hard to effectively prioritize content opportunities when you’re running a large site. Do you update the existing page ‘X’ or create new content around the topic ‘Y’? Which opportunity has the most chance of success? Machine learning and AI can be beneficial to any content team that finds themselves in this situation.
Content Strategy and Planning With MarketMuse
MarketMuse has created a difficulty score relative to today’s Google ranking factors, and the primary new factors are content-specific! We call this score Personalized Topic Difficulty.
You’re most likely familiar with keyword difficulty. It’s a metric that indicates how hard it is for anyone to rank for a topic, regardless of whether or not a website is related to the topic.
Forged in the age of PageRank, it was a welcome addition. But Search has dramatically changed and we now find ourselves living in the age of content.
Keyword Difficulty needs to be augmented by Personalized Difficulty. This way you have a metric that realistically provides insight about your ability to rank for a specific topic.
Read more about Personalized Difficulty in this blog post that touches on additional proprietary MarketMuse Metrics such as Competitive Advantage and Topic Authority.
MarketMuse is a content intelligence platform with a deep understanding of your content, its associated topics, and the content of your competitors. With the help of personalized content metrics, you can create AI-driven content plans with high confidence that they will succeed. This is possible because MarketMuse maintains a continuous inventory of your site.
Give MarketMuse a topic, and it can determine how well it will perform, should you decide to write content on that subject. It does this by assessing how well you’ve covered the topic in the past, how it has performed, how the competition has fared, and other factors. It uses this to create personalized authority and difficulty scores.
As you make decisions about what new content to create and pages to update, these can be assigned to content plans within MarketMuse. Plans are useful for keeping work organized, tracking what tasks have been done, and creating briefs.
Content Strategy and Planning With SearchMetrics
SearchMetrics is an enterprise SEO platform with some page optimization features. They offer no content inventory and provide no personalized metrics to give insight on your ability to rank for a specific topic. Other than simple keyword research, there’s little to help content strategists plan and prioritize their work.
Content Research and Competitive Analysis
As the volume of published content continues to increase, it’s no longer feasible to research, by hand, what’s needed to create expert-level content. Today, AI gives content marketers the advantage in gaining a deep comprehension of buyer needs, search intent, competitive content, and their own content performance.
Content Research and Competitive Analysis With MarketMuse
MarketMuse provides greater understanding of competitive content than SearchMetrics ContentExperience.
In addition to our personalized difficulty and authority scores, previously mentioned, we calculate the content scores for your content and the competition. You can quickly compare how well you cover a topic versus the competition.
Even better is the MarketMuse Heat Map that identifies content gaps vs your competition as well as opportunities for you to go where your competition has yet to follow. It’s compelling stuff!
Read this case study on how MarketMuse Compete and Research applications can be utilized together to make content a real competitive advantage.
Content Research and Competitive Analysis With SearchMetrics
SearchMetrics is fundamentally flawed in its analysis of organic competition in the search results.
For a given topic, SearchMetrics provides a list of the top ranking URLs, the number of keywords the page ranks for and its estimated SEO value, as well as some information on the number of backlinks and social engagement. What we’re missing here is a true content analysis and any truly actionable data points to inform your content strategy.
When it comes to competitive analysis, SearchMetrics is sorely lacking. They use a flawed metric (CPC) and provide no other parameters to offer deep insight into the ranking potential of content. Lacking this, you’re merely shooting in the dark, hoping for success. And hope is a lousy strategy.
Understanding Search Intent Through Questions
Understanding Search Intent is a critical factor in achieving success in the SERP rankings and getting coveted organic traffic. Visitors to a site come expecting answers to their questions. Understanding those questions helps to discern search intent better. You can then use that knowledge to map your content strategy to search intent.
It’s not enough to answer the problem for which people come to your site. You need to solve their next ten questions.
That’s where a robust “questions” application like the one we use as part of the MarketMuse suite makes all the difference. This blog article talks about how MarketMuse helps you discover questions at scale so that you can optimize your content for the questions your audience is asking.
Let’s compare both offerings using an example, ‘how to get ripped abs.’
At first glance, this looks okay. One thing to note is that every result contains the phrase ‘how to get ripped abs’ within it. Sometimes the expression is split, but it’s always there. I suspect they may simply do string matching in their keyword database to find appropriate longtail keyword phrases.
Now let’s look at this partial screenshot of the 50 questions MarketMuse returned for the same topic, ‘how to get ripped abs.’
There’s a big difference in the quality and depth of questions that MarketMuse returns. Our sophisticated approach means that the questions returned aren’t required to match the original phrase, ‘how to get ripped abs.’
As a result, you could even put the topic ‘getting ripped abs’ into MarketMuse Questions app and get similar high-quality, insightful questions. I doubt that’s the case with SearchMetrics.
MarketMuse always offers the best data available for optimizing any topic. Not so with SearchMetrics.
Inferior data leads to substandard optimization. Remember the ‘how to grow an avocado’ topic mentioned earlier?
Use SearchMetrics and you’ll end up optimizing for avocados in general. That’s bad!
That’s not the case with MarketMuse, where you always get the best data available for any given topic.
Natural Language Generation
Artificial intelligence offers content marketers the ability to scale content production.
Using the latest advancements in natural language, MarketMuse NLG Technology creates a preliminary article for a chosen topic based on its corresponding content brief. The draft strives to attain all the essential content metrics while requiring minimal editing. The content created is unique, so the output can be used as is, without duplicate content and plagiarism concerns.
Well-designed and information-rich content briefs enable writers to quickly and consistently create expert-level content every time. Creating briefs with this level of detail is impossible to achieve at scale, when done manually. Although both MarketMuse and SearchMetrics offer briefs, they’re nowhere near the same in terms of quality.
SearchMetrics Content Briefs
As of this update in October 2021, it appears SearchMetrics no longer offers a Content Brief product. Previously, their Content Brief offering was a very basic one, consisting of a cursory list of keywords, questions to answer and a target word count.
MarketMuse Content Briefs
Want to see a content brief that provides far more guidance to help writers efficiently and consistently create better content? Take a look at this MarketMuse Content Brief.
These briefs consist of two components – the executive summary and the outline view. The executive summary provides an overview of the strategy outlined in the brief to create a comprehensive piece of content on the chosen topic. The outline view is the blueprint that the writer will use to craft their piece of expert-level content.
The executive summary provides a marketing executive with the background necessary for why this content should be created and how. The summary opens with information about the target score, potential increased monthly views, and suggested word count, along with a description of what these indicators mean. It provides a path to the best content following these critical steps.
Determine Ideal User Intent and Audiences
This section explains who the audience is and why they are searching for this topic.
Discover Questions to Answer
This section dramatically reduced the time a writer spends on researching a topic. The most important questions on the topic will be found here.
Choose Your Article Title
Here we see several titles that are ranking for the topic plus suggested terms to include in your title to set yourself apart.
Find The Most Relevant Subheadings
Subheadings convey the structure and meaning of your article and help establish topical authority. Using subtopics that best answer your audience’s questions helps craft an article that is easy to read and quick to rank.
Terms to Include
Mention these terms in your article to help establish topical authority. These subtopics are linked to your primary focus topic through search indexes, so it’s vital that they are included.
Link to The Best Internal and External Pages
Internal links help create authoritative content clusters. Relevant external links are good for your audience and search engines expect to see them in trustworthy articles.
Information in the Outline Brief is designed to help writers create better content faster. This includes an article structure complete with subheadings so that writers spend less time on research and get more done.
Suggested Word Count
On the right side of the brief is a suggested word count based on the average and taking into account the target word score. Each section also has a recommended word count displayed as a percentage of the total word count. This gives writers an idea of how much space to devote to a subsection without getting side-tracked in meeting a specific word count target.
Suggested Title and Title Variants
One suggestion is provided along with several variants should the writer wish to refine the title further.
This is a list of subtopics to mention, some of which can be included in the article’s introduction. ‘Suggested Dist.’ refers to the number of times to mention a topic without it appearing awkward and unnatural.
A MarketMuse Content Brief typically contains several subheadings. Each one follows the same format:
- Suggested subheading
- Suggested word count for that section (expressed as a percentage of the total word count)
- Questions to answer
- Topics to mention including their suggested distribution
- Internal link with anchor text (the anchor text is a highly relevant topic while the suggested link is a page that’s a good match for that topic)
- External link (the anchor text is a topic with lower relevance with a suggested link of high authority and quality)
External links are chosen based on anchor text with low topical relevance for a special reason. We want to link to a high-quality, authoritative source that’s not in direct competition with the topic our article targets. This is achieved by choosing topics that are adjacent to the central theme, thus providing value to both the audience and search engines while helping to achieve the goals of the article as well.
MarketMuse offers many workflows designed especially for content strategists and their teams. AI-driven content plans, highly structured and detailed content briefs, plus MarketMuse NLG Technology (natural language generation), means content teams can do more, better, and faster.
SearchMetrics is an SEO platform that offers a limited content experience with substandard topic modeling, superficial competitive analysis, simple questions-based insight, and no natural language generation.