There’s no shortage of Surfer reviews written by members of its affiliate program. But if you’re wondering how it stacks up against MarketMuse Pro, we’ve put together this comparison. Although Surfer costs less than MarketMuse, it’s not the bargain it seems to be. If you’re not up for a long read, here’s the summary.
- MarketMuse patented method of topic modeling is better than that achieved by Surfer’s TD-IDF based process. So, you’ll get better content optimization suggestions.
- MarketMuse tracks your content inventory, analyzing your content and site for better content strategy and planning. That’s something Surfer cannot do.
- MarketMuse offers personalized content metrics, while Surfer has none.
- MarketMuse competitive content analysis heatmap instantly reveals content gaps from which the competition suffers. Surfer does not have this ability.
- MarketMuse content outlines are highly detailed and structured, while those of Surfer are simple and superficial.
- MarketMuse employs NLP as a foundational component, starting with its topic modeling. Surfer offers NLP as an afterthought, employing the services of third-party APIs.
- MarketMuse offers actionable insight on data points that make a difference. Surfer overwhelms users with many data points that have little, if any, impact.
The quality of the topic model is where it all starts. Without a high-quality model, everything else is irrelevant. Worse than that, low fidelity data can lead to poor choices, wasted time, money, and effort. So it makes sense to get this right from the start.
The best way to illustrate how MarketMuse and Surfer differ in their approach to topic modeling is to use an example. Let’s compare the topic ‘how to get more traffic to your blog.’
Here’s the output from both MarketMuse and Surfer.
Although MarketMuse provides 50 relevant topics, plus up to 50 variants for each topic, we’ll just compare against the same number of suggestions we see in the Surfer screenshot.
(sorted by relevance)
|how to get traffic to your blog|
|promote your blog|
|yoast seo plugin|
|increase blog traffic|
|how to get traffic to your blog|
|how to increase|
|how to promote blog|
|how to promote your blog|
|how to promote a blog|
|how to get your blog noticed|
|traffic to your blog|
|drive more traffic|
MarketMuse scans the competitive content from across the entire web to develop robust topic models. Not so with Surfer.
I think the winner is clear about which model offers better suggestions on what topics to cover.
Content Strategy and Planning
The bigger the site, the harder it is to prioritize. Even with a few hundred pages, it becomes difficult trying to determine what is the best course of action. Everyone wants to become an authority, but how do you do that in the most efficient way possible. This is where machine learning and artificial intelligence can be of immense value to content teams of all sizes.
Content Strategy and Planning With MarketMuse
MarketMuse has a deep understanding of your content, its associated topics, and the content of your competitors. It’s why we call it a content intelligence platform. MarketMuse keeps track of the inventory on your site. With the help of personalized content metrics, you can create AI-driven content plans with high confidence that they will succeed.
For any given topic, MarketMuse can determine how well your content could perform, were you to write something 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 information to create personalized authority and difficulty scores.
MarketMuse is the first to offer a personalized difficulty score, ever, in the industry.
MarketMuse Opportunity Score helps prioritize which of your pages and/or topics you should work on. The score is a personalized metric ranking your pages in order of opportunity available. This score is calculated by taking your entire set of live pages and topics, and running them against all evaluation metrics, classifying each page or topic’s potential growth against each other.
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 Surfer
You cannot perform any content strategy or planning with Surfer. Keyword research, which Surfer does provide, is not content strategy.
Surfer lacks personalized metrics that are necessary for creating high-performing plans. It’s just an SEO tool to which they’ve recently added a content editor. That editor can’t help you determine the topics around which you should be creating new content or optimizing existing pages.
In the hyper-competitive worlds of content, it’s impossible to manually research what’s required to create a truly comprehensive piece of content. Thoroughly understanding the buyer’s needs, search intent, competitive content, and your own content performance require the help of AI.
Content Research in MarketMuse
MarketMuse extracts massive amounts of data from the web. We pull content from thousands of pages, using natural language processing to determine not only who covers this topic at an expert level, but EXACTLY what you need to do better.
Going the extra mile ensures high-fidelity data resulting in high-quality recommendations. Our topic model suggests 50 related topics to cover for any given subject.
Plus, our Compete Application enables you to quickly research competitive content to understand how well they cover a subject, including their content score, word count, and content gaps.
Content Research in Surfer
Surfer does not support any workflows that allow for content research. Enter a keyword into their Content Editor and you’re immediately funneled into a workflow to set up a content guideline. There are no specific modules for investigating the related topics for a subject, the most important questions, or the best links to use.
While Surfer does offer keyword research, that is no substitute for content research. If you’re not sure why then read this post on how keyword research doesn’t help create better content.
Competitive Content Analysis
Competitive content analysis reveals the level of quality necessary to successfully position your site as the expert on your topic. For any piece of content, you want to know what are the must-have topics, the important topics, and gaps where you have the opportunity to differentiate your content from the competition.
Competitive Content Analysis With MarketMuse
MarketMuse uses a heatmap to display competitive information from the top 20 results in the SERP so you can quickly identify content gaps and other topics that are important and necessary to include within your article.
It also provides a content score for each URL. This Content Score is a reflection of how well the page covers a given topic.
Competitive Content Analysis With Surfer
Surfer is incapable of analyzing the content of a page. There is no content score to provide insight into how well the competition covers a particular topic. Also, their data points are based on a very small collection of documents (corpus) which has a dramatic impact on its accuracy.
Surfer SERP Analyzer takes the approach that more data is better. Content marketers have more than enough data; what’s required is better insight.
Don’t count on Surfer to help much in this regard. For example, knowing how many bold words, paragraphs, or images the competition uses won’t help create better quality content.
Although they claim that text length, keyword density, and the number of headings are ranking factors, that’s simply not true. The concern here is that following this sort of ‘advice’ can lead you seriously astray.
Content outlines provide a framework for writers to create an article and against which editors can evaluate. The purpose of an outline is to ensure each piece of content is comprehensive and meets the necessary performance criteria. A well-structured outline also reduces the burden of research and increases writer efficiency.
MarketMuse outlines are more detailed and structured with multiple sections, each with its own list of topics to mention, questions to answer, and links to include. There are outlines for new content as well as existing pages, taking into account content on the page. Surfer outlines are much simpler with no structure, a basic list of terms to include and questions to address. They offer no outlines for optimizing existing pages.
Content Outlines With MarketMuse
A MarketMuse Content Brief consists of three sections; the executive summary, outline brief and Optimize. There are two types of content briefs; one for creating new content and another for updating an existing page. Both are very similar, but briefs for existing pages take into account the content that already occurs on the page.
Anyone can access a specific MarketMuse Content Brief through a shared link like this https://briefs.marketmuse.com/5dcea032113fd495b1b14c66.
Let’s examine each section to understand their purpose and function better.
MarketMuse Content Brief – Executive Summary
As its name implies, the executive summary provides a marketing executive with the background necessary for why this content should be created and how it will be done. 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.
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 when you’re writing.
This section looks at some relevant questions surrounding this topic so you can make sure your content is focused on what’s important to your audience.
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.
Similar to the previous sections, you see subheadings that rank for this topic plus some terms that you should include to differentiate your post from the competition.
Terms that can guide your content toward topical authority.
A list of all the relevant subtopics related to the subject. The size of this varies with the number of subheadings and target word count.
Link to external and internal pages
Suggested links and anchor text for the most appropriate internal web pages. Same thing for external links, but these are to non-competitive sites.
MarketMuse Content Brief – Outline
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)
Note that each section has its own set of related topics. While there is some overlap between the sections and the main topic, the resulting list is far more extensive than what’s found in SurferSEO.
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.
The third tab in this shareable MarketMuse Content Brief is Optimize. It works just like the Optimize app, except it’s prepopulated with topics from the brief. Writers can use this in two ways:
- Craft the article directly in Optimize (content score and word count automatically updates as you write)
- Create a post using your favorite word processor and then check it with Optimize prior to submission
Surfer refers to their outlines as guidelines. A guideline for a topic is based on a list of competitors. Users are expected to choose from the top 10 in the SERP, in order to create the competitive data that drives the outline.
Requiring users to determine their competition is a serious flaw in the Surfer worfklow. Every URL that appears in the SERP is a competitor. To think otherwise is a grave mistake.
Also, using such a small corpus results in data quality and fidelity issues, with a topic model that doesn’t tell the full story.
The first section deals with the content structure, specifically the number of words, headings, paragraphs, bold words, and images. This data, based on the chosen competitors, is for the most part irrelevant.
Let’s first look at the number of bold words and images. What is that!? These are completely irrelevant metrics. The quality of your content and its performance won’t suffer if it fails to meet these suggestions. As for the number of headings and paragraphs. Not helpful! These metrics provide no insight. Editorial decisions like this need to be based on your content and its subject matter.
The next section covers the terms to use in the content. These don’t appear to be sorted by relevance making it hard to determine what’s most important. Also, there are a lot of questionable terms in their modeling. For example, the primary keyword ‘seo services’ includes terms like ‘touch,’ ‘popular,’ ‘providing,’ ‘read,’ ‘star’ and a dozen other similar suggestions.
The last section addresses the questions to answer. These aren’t questions that have been uncovered through content analysis. Instead, these are question-type keyword phrases related to the primary keyword. You’ll find this data to be limited and of questionable quality.
Content optimization is about creating the best content experience for your readers. For this to happen, the most relevant topics on a given subject need to be adequately addressed.
Content Optimization With MarketMuse
The MarketMuse topic model is very robust. As a result, the Optimizer application shows 50 related topics for a given subject (focus topic).
MarketMuse Content Score takes into account the proper usage of related topics in competitive pieces across the web. In Optimize your content score is updated live, based on your coverage of relevant topics, as you write. It shows how your content stacks up against the competition.
Every mention of a topic in the related topic list earns a point, with a maximum of two points for each item. Since there are 50 related topics in the list for any given topic, the theoretical maximum is 100.
The Average and Target Content Score section breaks down significant ranges of Content Scores. The Average number shows how comprehensively articles ranking for this term are commonly written. The Target score shows the coverage you want to meet or exceed.
The current Content Score visualization graph displays your progress toward a target content score, showing if your content currently has below average (red), average (yellow), or target coverage (green).
MarketMuse also tracks your word count and shows how it stacks up against the rest of the content performing well for your query. This is the word count of the content you are working in the writing area and changes as you write.
Average and Target Word Counts are derived from extracting content across expert pieces that cover this same topic.
The word count bar shows how close you are to fulfilling the target word count. It will fill up as you write, being filled all the way means the target was hit or exceeded.
Related Topics Table
This table shows the essential topics to include in your article and approximately how often they should be mentioned. The core related topics are ordered by relevance to the focus topic.
Distribution, abbreviated to DIST, shows a range of how often you mention this topic in your piece. Suggested Distribution shows MarketMuse’s recommendation concerning the number of times you may want to mention this topic. Clicking on a related topic in this list reveals a slide-out with variants of that topic you can use to enrich your writing.
Content Optimization With Surfer
SuferSEO offers a similar content optimization experience but misses some critical details. First, they have no method of scoring the content, making it difficult to discern the extent of topical coverage. Furthermore, it’s difficult to determine how your content compares to the competition
Second, the suggested terms don’t appear to be sorted by relevance, making it hard to understand which are the most important.
Third, the poor visual layout of the list of terms creates extra work for the user. You can’t quickly determine which terms are frequently used and which are not; that requires some mental gymnastics.
Fourth, the word count feedback lacks an adequate frame of reference. That means the only context a user has is how close they are to the target count. The critical part of the equation that’s missing is how their content relates to the average. A detail like this is what provides greater insight.
Natural Language Processing
How MarketMuse Uses NLP
Natural language processing is embedded deep within the MarketMuse platform, from our patented method of topic analysis to the way we surface appropriate questions and generate text via MarketMuse First Draft natural language generation.
How Surfer Uses NLP
Surfer has bolted a couple of NLP APIs onto their platform in a way that almost feels like it’s a solution looking for a problem.
They use APIs from both IBM Watson and GoogleNLP to determine article and entity sentiment analysis respectively. For the most part, understanding the sentiment of the top 10 competitive articles or the entities within doesn’t help to create better content.
At best, sentiment analysis is a distraction when it comes to writing articles. At worst, it can be extremely misleading resulting in a waste of effort and resources.
Surfer also relies on Google NLP API to provide additional terms that are “important to rank for a given search query.” But Surfer only sends the top ten ranking pages to the API, which is a very small collection of documents from which to draw conclusions.
Although Surfer is inexpensive, cheap might be a more appropriate description. Their approach to topic modeling leaves much to be desired as their content recommendations are shallow at best and often inappropriate. Much of your time will be wasted on following suggestions that have no to little influence on content success.