What is the Readability Score? Meaning and Use Cases

Learn what a readability score is, why it matters for content clarity, and how to use metrics like Flesch-Kincaid to improve your writing. Discover tools, examples, and actionable tips to make your content easier to read.

Sohail Pathan

Last updated on November 22, 2023

Readability Score Explained: How to Measure & Improve Content Clarity

Introduction:

A readability score quantifies how easy a piece of text is to read. Metrics like Flesch-Kincaid, Gunning Fog, and SMOG evaluate sentence length, word complexity, and structure to give a numerical score. Higher readability ensures your audience understands your content quickly, reducing bounce rates and boosting engagement.

Readability scores are crucial for writers, marketers, educators, and developers. They help improve blog posts, legal documents, educational materials, and web content. By analyzing readability, you can optimize your writing for clarity, accessibility, and audience retention. Later in this guide, we’ll show practical ways to calculate scores, interpret results, and use APIs to automate the process.

In the end, reading is like breathing. It is something that we do regularly without thinking much about it. But just as air quality impacts how easily we can breathe, the complexity of what we're reading affects how smoothly we can absorb the information.

So how can we judge whether some text or article is easy to read and understand?

How is the readability score Calculated?

The Flesch Reading Ease score is calculated using a formula that takes into account the average number of words per sentence and the average number of syllables per word. A score below 30 is very difficult to read, while a score in the range of 60 to 70 is fairly easy to read.

In short - the higher the reading score, the easier a piece of text is to read.

If you are curious, here is some more info about the foundation, grading level, and how it’s calculated.

Some common use cases of the Readability Score

Now that we have established what the readability score is, let's try to explore the use cases and how it can be beneficial for different audiences.

Education:

The Flesch Reading Ease score can help instructional designers, teachers, and other educators match the reading materials to their students' reading abilities. For example, a Learning Management System (LMS) can have a Flesh Reading Score feature that can help teachers create content matching the level of the students. This can help them curate the best resources for their students based on their reading abilities or level.

Content Generation

Content creators, like writers, journalists, and bloggers, can use the Flesch Reading Ease score to make sure their content is easy to read and accessible to their target audience. By targeting a specific score range, they can adjust their writing style and word choices accordingly. For example, a blogging platform could offer a nice feature to its writers. This feature would check the readability score of the content before publishing a blog post. This could be beneficial as it could help the writers reach the intended audience and get more engagement.

Legalities:

The Flesch Reading Score can also help in creating legal documents. For example, it could be useful for any tech startup that needs to prepare the terms and conditions for their new app. Using the Flesh Reading Score tool, they could ensure that they write their legal terms in a way that are easy to understand for their users.

Accessibility:

The Flesch Reading Ease score can be used as a guideline for creating accessible content for individuals with different reading abilities. For example, a SaaS company could add readability scoring to their content editing workflows where the content is focused on onboarding, pricing pages, or user guides.

Now that we have covered some of the use cases of the Readability Score and its ability, let's now explore the possible approaches and resources available for calculating the Readability Score. ‘

In general, these approaches are:

Using Visual Tools
Using Open Source Libraries
Using Cloud APIs.

There is no right or wrong approach, it strongly depends on the use case, available resources, availability of developers, etc. Each of the approaches comes with its own benefits and we will see some of them below.

Visual Tools

Readable: Readable is the most known tool when it is readable. This lets you check the readability of text, documents, and websites. It is not just limited to readability but also grammar checks, sentiment analysis, and advanced factors like keyword density and text statistics.

Semrush SEO Assistant: Semrush SEO Assistant is a Chrome extension that primarily creates SEO-optimized content. Using the Flesch-Kincaid score to assess and improve your text’s readability, it offers recommended keywords, tone of voice, and plagiarism checks.
Originality.ai: Originality utilizes AI in addition to the Flesch Kincaid Ease Score checker. It also offers plagiarism detection, fact-checking, and fact-checking services.

These tools are suitable for non-developers like content creators who can identify and evaluate the content for specific audiences. The only challenge is manual effort if you try to extract data from thousands of pages.

Open Source Libraries / Frameworks:

Popular open-source libraries like:

Whelk-i: This is a Java library that is used to perform Flesch-Kincaid readability tests. It has easy-to-understand documentation.
Py-readability-metrics:py-readability-metrics is an open-source library available in Python that D is actively maintained by the community. One of the advantages is this lets you check the readability not only for Flesch-Kincaid but with various algorithms and formulas like Gunning Fog, ARI, Dale Chall, SMOG, Space, and more.

Libraries are a programmatic way that could be suited for medium-scale projects, but they have some limitations depending on the tech stack. For example, there may be fewer robust libraries available for other programming languages. Libraries also need to be updated by their maintainers to stay compatible with new language versions and fixes.

This is where cloud APIs can help bridge the gap. Rather than relying solely on libraries, cloud APIs allow you to access powerful pre-built services over the network through simple API calls.

Cloud APIs:

Sapling: Saplings are offered by naming them as Statistic API. For developers, with simple documentation, it also offers language-specific client code in JavaScript and Python.
SEOReviewTools: SEOReviewTools offers a service that quickly calculates the Flesch-Kincaid readability score for any URL. For developers, with simple documentation, it also offers language-specific client code in Python and PHP
ApyHub: ApyHub's Readability Score & Readability Score Documents is a cloud-based API that enables you to check the readability of texts and documents seamlessly. Users can simply pass the text, PDF, or Docs and get back a response that includes the overall score, grade level, class of the reader, and more. It offers up to 2 million API calls on a free plan. You can even use the visual API Playground to test the output beforehand.

Conclusion :

Ultimately, the Flesch Reading Ease score can assist with creating content that is easy to read and understand, which is important for anyone who wants to communicate their message to their audience effectively. The approach depends on the use case and requirement.

In order to calculate the Readability Score, there are visual tools available. On a programmatic level, APIs like the ApyHub API can help developers incorporate the Readability Scores calculation inside their application and automate the process.

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