Archive for category: Yoast SEO

If you have ever run your writing through a readability checker like Yoast SEO, you have probably come across the Flesch reading score. This metric was developed more than 70 years ago and is still one of the most widely used ways to measure how easy your text is to read. But what does it actually mean, and how does it affect your writing for the web?

In this guide, we will explain how the Flesch reading score works, why it became so prominent in publishing and SEO, and how you can use it effectively today. We will also show you where it fits into the Yoast SEO plugin and why we have introduced new readability checks alongside it.

What is the Flesch reading score?

The Flesch reading score, also called the Flesch reading ease test, was created by Rudolf Flesch in the 1940s. His goal was simple: to give writers a quick way of checking whether their text was easy to understand. The formula combines three basic elements: sentence length, word length, and syllable count. When these figures are combined into the formula, which I’ll explain in just a moment, they generate a score between 0 and 100.

The highest scores are reserved for the easiest text. For example, a score in the 90s suggests that a typical 11-year-old child should be able to read it without any difficulty. A score of around 60 is closer to plain English that a high school student would be expected to understand. Scores under 30 are considered very difficult and are only really found in academic or legal writing.

Here’s a quick overview of the ranges and what they mean:

Just for fun: this article itself scores around 63 on the Flesch reading score, which puts it in the “standard” range.

How the Flesch reading score is calculated

The formula behind the score looks intimidating, but don’t worry, it is surprisingly straightforward. In fact, it’s only based on two things. The total number of words divided by the total number of sentences, which gives us the ASL or Average Sentence Length, and the total number of syllables divided by the total number of words to get the ASW or Average Syllables per Word. Once we have these figures, we enter them into this formula:

206.835 – (1.015 × ASL) – (84.6 × ASW)

This will give us a score between 0 and 100. The longer your sentences and the more complex your words, the lower your score will be.

Let’s take a quick example by looking at this short text below:

“The cat sat on the mat. The dog barked.”

This has very short words and sentences, so it would score in the 90s, which means it is very easy to read.

Now compare it with:

“The domesticated feline reclined languidly upon the woven floor covering, while the canine produced a resonant vocalization.”

This is essentially the same meaning, but longer words and clauses drop the score dramatically, likely into the 30s.

This example shows why the Flesch reading score works well as a proxy for readability. It rewards writing that is concise and simple with a high score and wags a finger at writing that is dense and complex, ultimately giving it a low score.

Why the Flesch reading score became important

The Flesch reading score spread beyond classrooms into business and publishing because it answered a universal question: Is my writing easy to understand?

By the 1970s, the U.S. Navy was using it to ensure that training manuals were clear for recruits. Later, several U.S. states made it part of their official requirements for insurance documents and consumer contracts. Healthcare organizations also began using it to ensure that patient information was accessible.

When personal computers became common, Microsoft Word added the Flesch reading ease test to its spelling and grammar tools. Suddenly, anyone writing a school essay or business report could get instant feedback on readability. That mainstreamed the score and kept it relevant well into the digital age.

In the world of web writing, readability became even more critical. Online readers scan rather than study text. Research shows they decide within seconds whether a page is worth their time or not. That makes clarity a competitive advantage. Tools that included the Flesch reading score gave web writers a way to benchmark themselves and improve user experience.

The Flesch reading score in Yoast SEO

When Yoast introduced readability checks to the plugin, the Flesch reading score was one of the first tools we built in. We popularized the use of tools to score your content. It gave writers using WordPress an instant way to measure whether their content was accessible to a broad audience. You can still find the Flesch reading ease score inside the plugin today, in the insights tab.

This has helped thousands of users discover that shorter sentences and simpler words often improve how people engage with their content. While the score does not guarantee better rankings, it does contribute to a positive reading experience, which in turn can influence user behavior and SEO outcomes.

Why Yoast moved beyond Flesch

The Flesch reading ease score is a useful tool, but it has its limitations. For one, it only looks at sentence and word length, ignoring context, tone, and audience. A medical blog, for example, might score poorly even if it’s perfectly suited to its readers.

There’s another issue: the Flesch score combines two factors, sentence length and word length, into one number. If your score is low, you won’t know which part needs fixing. That’s why we added separate checks for sentence length and word complexity. Word complexity doesn’t just measure length; it also takes into account a few other elements, like how common a word is. Based on all these factors, it assesses the difficulty of your vocabulary, giving you clearer feedback.

This way, you can still use the Flesch score as a quick guide, but with sharper insights to refine your writing.

Should you still care about the Flesch reading score?

The Flesch reading score remains a valuable guide for writers who want to make their content more approachable. If your text scores very low, it may be worth shortening sentences or replacing long words with simpler alternatives. But you do not need to obsess over getting a perfect score.

Readability is about more than numbers. Think about your audience, their expectations, and the purpose of your content. Combine the Flesch reading score with other readability signals to create a text that is clear, engaging, and optimized for both humans and search engines.

How to use the Flesch reading ease score to improve your writing

We’ve come to the essential question. How can you use the Flesch score to improve your writing? Well, you write for an audience and know your audience the best. Before writing or editing, consider what kind of texts fit your readers. Do you sell clothes or organize photography workshops? Or do you write for a mom blog or make step-by-step DIYs? Your content should be relatively easy to read in all these cases since you are targeting a broad audience.

However, remember that you do not have to chase a high Flesch reading score at all costs. For example, you may write about complex, specialist topics for a specific, more knowledgeable audience. Or, perhaps you are an academic blogging about your research? It makes sense if the Flesch test produces a lower score in those cases.

Still, whatever your situation is, your text always benefits from concise language. So, if you want to benefit from the feedback the Flesch reading ease score gives you, focus on two things:

1. Shorten your sentences

Too many long sentences make your text difficult to read, while short sentences keep the subject clear. When the sentences in your text are short, you allow your readers to absorb the information in your text. As a result, they don’t need to use all their attention to decipher what you want to say. That is why we advise you to break down long sentences; your text will be much easier to read. 

And please, don’t think that by using short sentences, you will oversimplify your text. Let’s compare two short texts to show you what we mean. First, we have this sentence:

My favorite place to visit during weekends is my grandparents’ house near the lake, where we love to fish and swim, and we often take the boat out on the lake.

Did you find this sentence easy to read? Wasn’t it too lengthy, confusing, and difficult to process? Breaking it into two or more sentences can make it much clearer:

My favorite place to visit during weekends is my grandparents’ house. It’s near the lake, where we love to fish and swim. We also often take the boat out on the lake.

These few short sentences are much easier to read. Yet, you give the same information as in the long sentence, so there is no oversimplifying. Using short sentences keeps the subject clear and lets your readers absorb the information you’re presenting.

Shorten your sentences with Yoast SEO

The Yoast SEO Readability analysis helps identify long sentences with its sentence length assessment. You can also use Yoast AI Optimize for sentence length for quick, automated improvements.

2. Limit your use of difficult words

Words with four or more syllables are considered difficult to read, so try to avoid them where possible. Or try not to use them too much. For example, try words like small instead of minuscule, about instead of approximately, and use instead of utilize. We have the word complexity assessment in Yoast SEO Premium to help you with that.

If you want to reach a broad audience, you should also try to avoid using jargon. If you’re a medical expert, you’re probably familiar with terms like analgesic, intravenous, and oophorectomy. However, keep in mind that most people aren’t. When you can’t find a better alternative, make sure to explain it for users who might not know the word.

Conclusion

The Flesch reading score has been around for decades, and it is not going anywhere. It still offers a quick way to test whether your writing is easy to follow, and it continues to play a role in Yoast SEO. At the same time, readability isn’t just about scores. Readability is about meeting your goals. By breaking down the Flesch reading ease score into clearer checks (like sentence length and word complexity), you get actionable feedback to refine your writing. That way, your content stays readable and effective.

So next time you write a blog post, take a look at your Flesch reading score. Use it as a guide, not a rule. The result will be content that your readers and search engines will thank you for.

TLDR

• You should care about your score, but do not chase perfection. Balance readability with your audience’s needs
• The Flesch Reading Score measures how easy a text is to read, using sentence length and word length
• Scores range from 0 to 100: higher is easier. For example, 90–100 is very easy, 60–69 is standard, and 0–29 is very confusing
• It became popular in education, government, and publishing before being integrated into tools like Microsoft Word and SEO platforms
• In Yoast SEO, the Flesch reading score still exists in the Insights tab, but we now also use word complexity to provide more accurate feedback

The post The Flesch reading ease score: Why & how to use it appeared first on Yoast.

Read more at Read More

Content summarization isn’t a new idea. It goes back to the 1950s when Hans Peter Luhn at IBM introduced one of the first algorithms to summarize text. Back then, the goal was straightforward: identify the most important words in a piece of writing and create a shorter version. What began as a technical experiment has now evolved into a fundamental aspect of how we read, learn, and share information. Summarization allows us to cut through overwhelming amounts of text and focus on what really matters, shaping everything from research and education to marketing and SEO.

In this article, we’ll explore why summarizing is essential for modern content and how both humans and AI-driven tools are making information more accessible, trustworthy, and impactful.

What is content summarization?

Content summarization is the process of condensing a large piece of high-quality content into a shorter version while keeping the essential points intact. The aim is straightforward: to produce a clear and concise summary that accurately represents the meaning of the original text without overwhelming the reader.

Summarization makes information easier to process. Imagine reading a lengthy report or book but only needing the key takeaways for a meeting. It also helps individuals and businesses grasp the core message quickly, saving time and effort.

There are two main approaches to summarize moder content:

Manual or human-driven content summarization

Think back to the last time you turned a long article into a short brief for a colleague; that’s a perfect example and explanation of manual content summarization. In this approach, a human reads, weighs what matters, and rewrites the core points for easy digestion of information.

Manual content summarization requires critical thinking to spot what matters and language skills to explain important information clearly and concisely.

Clear advantages of human-driven content summarization are:

• The ability to notice nuance and implied meaning
• Flexibility to shape tone and level of detail for a specific audience
• The creativity to link ideas or highlight unexpected relevance
• Judgment to keep or discard details based on purpose

This human-led method complements content summarization AI, giving summaries a thoughtful, audience-aware edge.

AI-driven content summarization

The other approach is powered by technology. AI-driven content summarization utilizes natural language processing and machine learning to rapidly scan through text and generate summaries in seconds. It typically works in two ways:

• Extractive summarization, where the AI selects the most important sentences directly from the content
• Abstractive summarization, where the AI generates new sentences that capture the main ideas in a more natural way

The benefits are clear: speed, consistency, and scalability. AI can summarize website content, reports, or articles far faster than a human team. However, it has limits. Context can be missed, and nuances like sarcasm or cultural references may be overlooked. The quality also depends on the AI model and the original text.

Both manual and AI-driven summarization play a crucial role today. Humans bring nuance and creativity, while AI delivers efficiency and scale. Together, they make summarization an essential tool for modern communication.

What are some of the core benefits of content summarization?

Turning lengthy information into clear takeaways is more than convenient. It makes content meaningful, easier to use, and far more effective in learning and communication. Whether done manually or supported by AI tools, summarization offers key benefits:

Enhances learning and study preparation

Summarizing strengthens comprehension and critical thinking by distilling main ideas and separating them from supporting details. Students and professionals can also rely on concise notes that save time when revising or preparing presentations.

Improves focus and communication

Condensing text sharpens concentration on what matters most. It also trains you to express ideas in a precise and structured way, which enhances both writing and verbal skills.

Saves time and scales with AI tools

Summaries allow readers to absorb essential points without having to read hours of content. With AI tools, this process scales further, reducing large volumes of text into clear insights within minutes.

Boosts accessibility and approachability

Summarization makes complex or lengthy content approachable and accessible for diverse audiences. Multilingual AI tools extend this further, breaking down language barriers and ensuring knowledge reaches a global audience.

Why summarization matters in the modern content landscape?

We live in an age of too much information and too little time. Every day, there is more content than anyone can read, which means people make split-second choices about what to open, skim, or ignore. This makes it more important that your content presents clear takeaways upfront before readers move on. Content summarization is how you win that first, critical moment of attention.

Information overload

Digital work and life produce an enormous flood of text, messages, reports, and notifications. This makes it challenging for readers to find the right signal in the noise. Therefore, text summaries act as a filter, surfacing the most relevant facts so readers and teams can act faster and with less cognitive friction.

People scan and skim, so clarity wins

Web reading behavior has been stable for years: most users scan pages rather than read every word. Good summaries present the core idea in a scannable form, increasing the chance your content is understood and used. That scannability also improves the odds of search engines and AI LLM comprehension surfacing your content as a quick response to user queries.

Trust and clarity for readers and systems

A clear and crisp text summary signals that the author understands their topic and values the reader’s time. That builds trust. On the search side, concise and well-structured summaries are what engines and AI systems prefer when generating featured snippets or AI overviews. Being chosen for a snippet or overview can boost visibility and credibility in search results.

Faster decision-making

When stakeholders, readers, or customers need to act quickly, summaries provide the necessary context to make informed decisions. Whether it is an executive skimming a report or a user checking if an article answers their question, summaries reduce the time to relevance and accelerate outcomes. This is also why structured summaries can increase the chance of being surfaced by search features that prioritize immediate answers.

Prominent use cases of content summarization

Content summarization is not a nice-to-have. It is one of the main reasons modern content continues to work for busy humans and businesses. Below are the most practical and high-impact ways in which the summarization of modern content is currently being used.

Business reports

Executives and teams rely on concise summaries to make informed decisions quickly and effectively. Executive summaries and one-page briefs transform dense reports into actionable insights, enabling stakeholders to determine what requires attention and what can be deferred. Effective summaries reduce meeting time, expedite approvals, and enhance alignment across teams.

Educational content

Students and educators use summaries to focus on core concepts and to prepare study notes. AI-driven summarization tools can generate revision guides, extract exam-relevant points, and turn long lectures or papers into study-friendly formats. These tools can support personalized learning and speed up content creation for instructors.

Marketing strategies and reporting

Marketers rely on summaries to present campaign performance, highlight key KPIs, and share learnings without overwhelming stakeholders. Condensed campaign briefs and executive summaries enable teams to iterate faster, align on priorities, and uncover insights for strategic changes. Summaries also make it easier to compare campaigns and track trends over time.

Everyday consumption: news digests, newsletters, podcast notes

Readers and listeners increasingly prefer bite-sized overviews. Newsrooms use short summaries and AI-powered digests to connect busy audiences with high-quality reporting. Podcasts and newsletters pair episode or article summaries with timestamps and highlights to improve discoverability and retention. Summaries help users decide what to read, listen to, or save for later.

Content Summarization & SEO: Does it Benefit in Boosting Organic Visibility?

Did you know that content summarization can help your SEO strategy? Search engines prioritize clarity, relevance, and user engagement, and concise summaries play a role in meeting those criteria. They not only shape a smoother user experience but also help search engines quickly grasp the core themes of your content.

Boosting click-through rates

Summaries also support higher CTRs in search results. A clear and compelling meta description written as a summary can serve as a strong preview of the page. For example, a blog on “10 Healthy Recipes” with a summary that highlights “quick breakfasts, vegetarian lunches, and easy weeknight dinners” is more likely to attract clicks than a generic description.

Improving indexing and relevance

From a technical standpoint, summarization helps search engines with indexing and relevance. Algorithms rely on context and keywords, and well-written summaries bring focus to the essence of your content. This is especially important for long-form blogs, case studies, or reports where the main ideas may otherwise get buried.

Winning featured snippets

Another growing benefit is visibility in featured snippets and People Also Ask sections. Summaries that clearly answer a query or highlight structured takeaways increase the chances of being pulled into these high-visibility SERP features, directly boosting organic reach.

Extending multi-channel visibility

Content summarization also creates multi-channel opportunities. The same summaries can be repurposed as social media captions, newsletter highlights, or even adapted for voice search, where users want concise and direct answers.

Supporting AI and LLMs

Lastly, in the age of AI, summaries provide context for LLMs (large language models). Clean, structured summaries make it easier for AI to process and reference your content, which extends your reach beyond search engines into how content is surfaced across AI-powered tools.

How to write SEO-friendly content summaries with Yoast?

The basics of an effective summary are simple: keep it clear, concise, and focused on the main points while signalling relevance to both readers and search engines.

This is exactly where Yoast can make your life easier. With AI Summarize, you can generate instant, editable bullet-point takeaways that boost scannability for readers and improve how search engines interpret your content.

Want to take it further? Yoast SEO Premium unlocks extended AI features, smarter keyword optimization, and advanced SEO tools that save you time while improving your visibility in search.

What is AI text summarization?

AI text summarization uses artificial intelligence to condense text, audio, or video content into shorter, more digestible content. Rather than just cutting words, it preserves key ideas and context, making information easier to absorb.

Today, summarization relies on large language models (LLMs), which not only extract sentences but also interpret nuance and generate concise, natural-sounding summaries.

How does AI text summarization work?

AI text summarization relies on a combination of sophisticated systems that help a large-language model deeply understand the content, decipher patterns, and generate content summaries without losing any important facts.

Here’s a brief overview of the process of AI-powered content summarization:

• Understanding context: AI models analyze entire documents, identifying relationships, sentiment, and flow rather than just looking at keywords, allowing the AI models to understand at a deeper level
• Generating abstractive summaries: Unlike extractive methods, which simply copy existing sentences, abstractive summarization paraphrases or rephrases content to convey the essence in fresh, coherent language
• Fine-tuning for accuracy: LLMs can be trained on specific domains such as news, legal, or scientific content, so the summaries reflect the right tone, terminology, and level of detail

Benefits of AI text summarization

The true power of AI summarization lies in the value it creates. By blending scale with accuracy, it turns information overload into actionable knowledge.

• Scales content summarization: Handles hundreds of pages or documents in minutes, which would otherwise require hours of manual effort
• Ensures consistency: Produces summaries in a uniform style and structure, making information easier to compare and use
• Saves time and costs: Frees up teams, researchers, and analysts to focus on insights instead of spending time reading
• Improves accessibility: Makes complex content digestible for wider audiences, including those unfamiliar with technical details
• Supports accuracy with human oversight: Editors can refine summaries quickly while still benefiting from automation

Practical use cases of AI summarization

AI summarization is not just theoretical. It has already become part of how businesses, teams, and individuals manage daily information flow. Here are some of the common applications of AI summarization which have become a part of our live:

• Meetings: Automatically captures key points, decisions, and action items in real time
• Onboarding: Condenses company or project documentation so new team members can understand essentials quickly
• Daily recaps: Summarizes Slack, Teams, or email threads into clear, concise updates
• Surfacing information: Extracts relevant context from long reports, technical documents, or customer feedback, ensuring that critical insights are never overlooked

In fact, AI agents are already being used in professional settings to summarize key provisions in documents, with 38% of professionals relying on these tools to expedite the review process. This demonstrates that AI summarization is not just a future possibility, but an integral part of how modern teams manage complex information.

In summary, don’t skip the summary!

Summarization is no longer a sidekick in your content strategy; it is the main character. It fuels faster human learning, strengthens SEO by making your pages clearer to search engines, and ensures AI systems don’t misrepresent your brand. When your content is easy to scan, you reduce bounce rates, improve trust, and increase visibility across platforms where attention spans are short.

This is exactly where a tool like Yoast SEO Premium becomes invaluable. With features like AI Summarize, you can instantly generate key takeaways that work for readers, search engines, and AI overviews alike. Instead of manually condensing every piece of content, you achieve clarity at scale while maintaining editorial control. Summarization is not just about making content shorter; it is about making it smarter, and Yoast helps you do it with ease.

So, to summarize the summary: invest in doing this right, because the future of content depends on it.

The post Why is summarizing essential for modern content? appeared first on Yoast.

Read more at Read More

We’ve all asked a chatbot about a company’s services and seen it respond inaccurately, right? These errors aren’t just annoying; they can seriously hurt a business. AI misrepresentation is real. LLMs could provide users with outdated information, or a virtual assistant might provide false information in your name. Your brand could be at stake. Find out how AI misrepresents brands and what you can do to prevent them.

How does AI misrepresentation work?

AI misrepresentation occurs when chatbots and large language models distort a brand’s message or identity. This could happen when these AI systems find and use outdated or incomplete data. As a result, they show incorrect information, which leads to errors and confusion.

It’s not hard to imagine a virtual assistant providing incorrect product details because it was trained on old data. It might seem like a minor issue, but incidents like this can quickly lead to reputation issues.

Many factors lead to these inaccuracies. Of course, the most important one is outdated information. AI systems use data that might not always reflect the latest changes in a business’s offerings or policy changes. When systems use that old data and return it to potential customers, it can lead to a serious disconnect between the two. Such incidents frustrate customers.

It’s not just outdated data; a lack of structured data on sites also plays a role. Search engines and AI technology like clear, easy-to-find, and understandable information that supports brands. Without solid data, an AI might misrepresent brands or fail to keep up with changes. Schema markup is one option to help systems understand content and ensure it is properly represented.

Next up is consistency in branding. If your brand messaging is all over the place, this could confuse AI systems. The clearer you are, the better. Inconsistent messaging confuses AI and your customers, so it’s important to be consistent with your brand message on various platforms and outlets.

Different AI brand challenges

There are various ways AI failures can impact brands. AI tools and large language models collect information from sources and present it to build a representation of your brand. That means they can misrepresent your brand when the information they use is outdated or plain wrong. These errors can lead to a real disconnect between reality and what users see in the LLMs. It could also be that your brand doesn’t appear in AI search engines or LLMs for the terms you need to appear.

At the other end, chatbots and virtual assistants talk to users directly. This is a different risk. If a chatbot gives inaccurate answers, this could lead to serious issues with users and the outside world. Since chatbots interact directly with users, inaccurate responses can quickly damage trust and harm a brand’s reputation.

Real-world examples

AI misrepresenting brands is not some far-off theory because it has an impact now. We’ve collected some real-world cases that show brands being affected by AI errors.

All of these cases show how various types of AI technology, from chatbots to LLMs, can misrepresent and thus hurt brands. The stakes can be high, ranging from misleading customers to ruining reputations. It’s good to read these examples to get a sense of how widespread these issues are. It might help you avoid similar mistakes and set up better strategies to manage your brand.

Case 1: Air Canada’s chatbot dilemma

• Case summary: Air Canada faced a significant issue when its AI chatbot misinformed a customer regarding bereavement fare policies. The chatbot, intended to streamline customer service, instead created confusion by providing outdated information.
• Consequences: This erroneous advice led to the customer taking action against the airline, and a tribunal eventually ruled that Air Canada was liable for negligent misrepresentation. This case emphasized the importance of maintaining accurate, up-to-date databases for AI systems to draw upon, illustrating a major AI error in alignment between marketing and customer service that could be costly in terms of both reputation and finances.
• Sources: Read more in Lexology and CMSWire.

Case 2: Meta & Character.AI’s deceptive AI therapists

• Case summary: In Texas, AI chatbots, including those accessible via Meta and Character.AI, were marketed as competent therapists or psychologists, offering generic advice to children. This situation arose from AI errors in marketing and implementation.
• Consequences: Authorities investigated the practice because they were concerned about privacy breaches and the ethical implications of promoting such sensitive services without proper oversight. The case highlights how AI can overpromise and underdeliver, causing legal challenges and reputational damage.
• Sources: Details of the investigation can be found in The Times.

Case 3: FTC’s action on deceptive AI claims

• Case summary: An online business was found to have falsely claimed its AI tools could enable users to earn substantial income, leading to significant financial deception.
• Consequences: The fraudulent claims defrauded consumers by at least $25 million. This prompted legal action by the FTC and served as a stark example of how deceptive AI marketing practices can have severe legal and financial repercussions.
• Sources: The full press release from the FTC can be found here.

Case 4: Unauthorized AI chatbots mimicking real people

• Case summary: Character.AI faced criticism for deploying AI chatbots that mimicked real people, including deceased individuals, without consent.
• Consequences: These actions caused emotional distress and sparked ethical debates regarding privacy violations and the boundaries of AI-driven mimicry.
• Sources: More on this issue is covered in Wired.

Case 5: LLMs generating misleading financial predictions

• Case summary: Large Language Models (LLMs) have occasionally produced misleading financial predictions, influencing potentially harmful investment decisions.
• Consequences: Such errors highlight the importance of critical evaluation of AI-generated content in financial contexts, where inaccurate predictions can have wide-reaching economic impacts.
• Sources: Find further discussion on these issues in the Promptfoo blog.

Case 6: Cursor’s AI customer support glitch

• Case summary: Cursor, an AI-driven coding assistant by Anysphere, encountered issues when its customer support AI gave incorrect information. Users were logged out unexpectedly, and the AI incorrectly claimed it was due to a new login policy that didn’t exist. This is one of those famous hallucinations by AI.
• Consequences: The misleading response led to cancellations and user unrest. The company’s co-founder admitted to the error on Reddit, citing a glitch. This case highlights the risks of excessive dependence on AI for customer support, stressing the need for human oversight and transparent communication.
• Sources: For more details, see the Fortune article.

All of these cases show what AI misrepresentation can do to your brand. There is a real need to properly manage and monitor AI systems. Each example shows that it can have a big impact, from huge financial loss to spoiled reputations. Stories like these show how important it is to monitor what AI says about your brand and what it does in your name.

How to correct AI misrepresentation

It’s not easy to fix complex issues with your brand being misrepresented by AI chatbots or LLMs. If a chatbot tells a customer to do something nasty, you could be in big trouble. Legal protection should be a given, of course. Other than that, try these tips:

Use AI brand monitoring tools

Find and start using tools that monitor your brand in AI and LLMs. These tools can help you study how AI describes your brand across various platforms. They can identify inconsistencies and offer suggestions for corrections, so your brand message remains consistent and accurate at all times.

One example is Yoast SEO AI Brand Insights, which is a great tool for monitoring brand mentions in AI search engines and large language models like ChatGPT. Enter your brand name, and it will automatically run an audit. After that, you’ll get information on brand sentiment, keyword usage, and competitor performance. Yoast’s AI Visibility Score combines mentions, citations, sentiment, and rankings to form a reliable overview of your brand’s visibility in AI.

Optimize content for LLMs

Optimize your content for inclusion in LLMs. Performing well in search engines is not a guarantee that you will also perform well in large language models. Make sure that your content is easy to read and accessible for AI bots. Build up your citations and mentions online. We’ve collected more tips on how to optimize for LLMs, including using the proposed llms.txt standard.

Get professional help

If nothing else, get professional help. Like we said, if you are dealing with complex brand issues or widespread misrepresentation, you should consult with professionals. Brand consultants and SEO experts can help fix misrepresentations and strengthen your brand’s online presence. Your legal team should also be kept in the loop.

Use SEO monitoring tools

Last but not least, don’t forget to use SEO monitoring tools. It goes without saying, but you should be using SEO tools like Moz, Semrush, or Ahrefs to track how well your brand is performing in search results. These tools provide analytics on your brand’s visibility and can help identify areas where AI might need better information or where structured data might enhance search performance.

Businesses of all types should actively manage how their brand is represented in AI systems. Carefully implementing these strategies helps minimize the risks of misrepresentation. In addition, it keeps a brand’s online presence consistent and helps build a more reliable reputation online and offline.

Conclusion to AI misrepresentation

AI misrepresentation is a real challenge for brands and businesses. It could harm your reputation and lead to serious financial and legal consequences. We’ve discussed a number of options brands have to fix how they appear in AI search engines and LLMs. Brands should start by proactively monitoring how they are represented in AI.

For one, that means regularly auditing your content to prevent errors from appearing in AI. Also, you should use tools like brand monitor platforms to manage and improve how your brand appears. If something goes wrong or you need instant help, consult with a specialist or outside experts. Last but not least, always make sure that your structured data is correct and aligns with the latest changes your brand has made.

Taking these steps reduces the risks of misrepresentation and enhances your brand’s overall visibility and trustworthiness. AI is moving ever more into our lives, so it’s important to ensure your brand is represented accurately and authentically. Accuracy is very important.

Keep a close eye on your brand. Use the strategies we’ve discussed to protect it from AI misrepresentation. This will ensure that your message comes across loud and clear.

The post When AI gets your brand wrong: Real examples and how to fix it appeared first on Yoast.

Read more at Read More