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Keyword density helper – This tool comes with a built-in keyword density helper in some ways similar to the likes of SurferSEO or MarketMuse the difference being, ours is free! This feature shows the user the frequency of single or two word keywords in a document, meaning you can easily compare an article you have written against a competitor to see the major differences in keyword densities. This is especially useful for SEO’s who are looking to optimize their blog content for search engines and improve the blog’s visibility.
You can also easily compare text by copying and pasting it into each field, as demonstrated below.
Ease of use
Our text compare tool is created with the user in mind, it is designed to be accessible to everyone. Our tool allows users to upload files or enter a URL to extract text, this along with the lightweight design ensures a seamless experience. The interface is simple and straightforward, making it easy for users to compare text and detect the diff.
Multiple text file format support
Our tool provides support for a variety of different text files and microsoft word formats including pdf file, .docx, .odt, .doc, and .txt, giving users the ability to compare text from different sources with ease. This makes it a great solution for students, bloggers, and publishers who are looking for file comparison in different formats.
Protects intellectual property
Our text comparison tool helps you protect your intellectual property and helps prevent plagiarism. This tool provides an accurate comparison of texts, making it easy to ensure that your work is original and not copied from other sources. Our tool is a valuable resource for anyone looking to maintain the originality of their content.
User Data Privacy
Our text compare tool is secure and protects user data privacy. No data is ever saved to the tool, the users’ text is only scanned and pasted into the tool’s text area. This makes certain that users can use our tool with confidence, knowing their data is safe and secure.
Compatibility
Our text comparison tool is designed to work seamlessly across all size devices, ensuring maximum compatibility no matter your screen size. Whether you are using a large desktop monitor, a small laptop, a tablet or a smartphone, this tool adjusts to your screen size. This means that users can compare texts and detect the diff anywhere without the need for specialized hardware or software. This level of accessibility makes it an ideal solution for students or bloggers who value the originality of their work and need to compare text online anywhere at any time.
In the digital age, online reviews have become a critical component of consumer decision-making, especially as e-commerce platforms, like Myntra, have gained popularity.
Crunchbase notes that Myntra received 59.7 million monthly visits last month (as of May 2025), and further, on the Google Play Store, the app has 100 million+ downloads.
As the popularity of shopping apps has grown, so too has the volume and influence of user-generated content, considering that consumers often rely on product reviews to assess quality and usability before making a purchase.
However, with advancements in artificial intelligence (AI), a new phenomenon has emerged: the generation of product reviews using AI models.
This study investigates the prevalence of AI-generated reviews on the Myntra shopping app. Through this analysis, we hope to provide insights into how AI-generated reviews are shaping the shopping experience on Myntra.
By analyzing review data over time and using our proprietary Originality.ai AI-detection tool, we aim to:
We also aim to contribute to the broader conversation on the ethical use of AI in e-commerce and the need for clearer guidelines to ensure that consumers can distinguish between authentic and machine-generated feedback.
In comparison with other shopping platforms, Myntra and Walmart appear to be monitoring AI in reviews, even while it's rising in others, like Flipkart.
This is particularly interesting to note, as Walmart acquired Flipkart in 2018, following Flipkart’s acquisition of Myntra in 2014.
Let’s dive a little deeper into the rate of AI content year on year to track the volume of AI content on Myntra from 2018 up to 2024.
The analysis of reviews on the Myntra shopping app reveals a clear upward trend in the prevalence of AI-generated content during that time, but not one that has become high overall — indicating that Myntra may be taking steps to moderate AI content.
Let’s take a closer look:
In 2018, the rate of AI-generated reviews was relatively low, at approximately 0.86%.
Over the following years, the rates fluctuated slightly but remained modest, with 0.55% in 2019, 0.79% in 2020, 0.61% in 2021, and 0.65% in 2022.
These small variations suggest that AI-generated content remained a minor component of the overall review landscape during the earlier years of the study period.
However, a notable increase began in 2023. That year, the rate of AI-generated reviews rose to 2.56%, indicating a significant shift compared to prior years.
This trend accelerated further in 2024, with AI-generated reviews making up 5.98% of all reviews analyzed.
This growth suggests a potential broader adoption of AI technologies for content creation by users, sellers, or automated systems supporting the platform.
Looking across the entire study period, that represents a 597% increase over the six-year period. Yet, overall AI content levels in Myntra reviews remained low.
The key takeaway for Myntra? While the rate of AI reviews on Myntra is rising, the majority of reviews as of 2024 are still human-written.
A note on false positives: False positives in AI detection occur when human-written content is identified as AI. False positive rates can vary by AI detection model and company. At Originality.ai our Lite model has an under 1% false positive rate, and our Turbo model has an under 3% false positive rate. So, the rates of AI content in Myntra reviews in this study are in-line with or slightly above AI detection false positive rates.
After looking at the percentage of AI reviews on Myntra across recent years, the results are a pleasant surprise.
While our findings and research on Myntra indicate that AI review content is rising (by over 597% during the period studied, 2018 to 2024), just over 94% of the reviews in 2024 are still human-written.
This is further emphasized in a comparison with other shopping apps.
According to our research:
In 2024, Likely AI reviews sat at just 5.98% for Myntra, which is lower than our findings for Flipkart and Walmart.
In comparison, our Flipkart Study found that in 2024, 19.83% of reviews were Likely AI, emphasizing a notable increase in AI content.
Then, our Walmart Study found that although in 2024, 7.75% of reviews were Likely AI, there was a stall in the growth of AI content in Walmart reviews from 2023 to 2024 (when levels hovered around 7.8%) after surging by 80.8% from 2019 to 2023.
Aside from being shopping apps, Myntra, Flipkart, and Walmart are connected by acquisitions.
According to Crunchbase, Myntra was founded in 2007 and was then acquired by Flipkart in 2014 for $300 million.
Just a few years later, in 2018, Crunchbase notes that Flipkart was acquired by Walmart for $16 billion.
In the context of our study, this indicates that some shopping platforms appear to be monitoring AI usage (such as Myntra and Walmart) — even while it's rising in others (Flipkart).
Further, AI moderation decisions may be conducted on a platform-by-platform basis even when the companies are connected via acquisitions (in this case, by Walmart’s acquisition of Flipkart and Flipkart’s previous acquisition of Myntra).
This study demonstrates that while AI-generated reviews are becoming an increasingly visible component of the Myntra shopping app experience, as of 2024, 5.98% of Myntra reviews are likely AI, meaning that just over 94% of reviews are human-written.
Whilst the platform has experienced a rise in AI reviews from 2018 (especially since the launch of ChatGPT in 2022), the overall percentage remains low, showing that Myntra is still prioritizing the importance of genuine customer reviews as a signal of trust and authenticity.
However, Myntra will need to ensure it remains on top of generative AI reviews, especially as the tools continue to improve and become more mainstream.
The rise from 2018 to 2024 suggests that Myntra must begin to seriously consider policies and detection mechanisms for AI-generated content to ensure that this figure remains low and customer trust remains high.
To help with this, Myntra should offer transparency about review origins, add clear labels, and incorporate AI detection tools to moderate content.
In conclusion, this study into Myntra AI reviews shows that although the percentage of AI reviews has risen in recent years, the brand also shows signs that it is managing to handle the volume of AI-generated content.
As we have touched on before, the importance of real user reviews and authentic experiences could not be more important in the era of AI. Not only is it a positive sign that the levels of AI content remain low at Myntra, but it is also rapidly becoming a competitive edge.
For brands that are seeking ways to tackle and identify AI reviews, moderation tools such as the Originality.ai AI Checker can help maintain transparency.
To maintain authenticity with users and clients, businesses must consider:
Do you have concerns over whether a post or review you’re reading might be AI-generated? Use the Originality.ai AI detector to find out.
Read more about the impact of AI on online platforms:
This study systematically analyzed the prevalence of AI-generated reviews on the Myntra shopping app. The dataset, in CSV format, included review text, date, ID, score, and user interactions.
Initially, Unix timestamp data in the 'at' column was converted to a readable datetime format using Python's pandas library for time-based analysis. The processed data was saved separately for consistency.
To detect AI-generated reviews, a custom Python script used the Originality.ai API to scan reviews with at least 50 words, returning an AI-likelihood score and a binary AI classification. Reviews that were too short or encountered API issues were excluded. Retry mechanisms and periodic saving ensured reliability during the scan.
After scanning, results were aggregated yearly to measure trends in AI-generated content. Only successfully scanned reviews with valid dates were analyzed. Visualizations, including line and pie charts, were created to highlight trends and the 2024 AI vs. human-generated review distribution.
This methodology ensured accurate, reproducible results through robust preprocessing, external AI detection, and careful data management.
No, that’s one of the benefits, only fill out the areas which you think will be relevant to the prompts you require.
When making the tool we had to make each prompt as general as possible to be able to include every kind of input. Not to worry though ChatGPT is smart and will still understand the prompt.
Originality.ai did a fantastic job on all three prompts, precisely detecting them as AI-written. Additionally, after I checked with actual human-written textual content, it did determine it as 100% human-generated, which is important.
Vahan Petrosyan
searchenginejournal.com
I use this tool most frequently to check for AI content personally. My most frequent use-case is checking content submitted by freelance writers we work with for AI and plagiarism.
Tom Demers
searchengineland.com
After extensive research and testing, we determined Originality.ai to be the most accurate technology.
Rock Content Team
rockcontent.com
Jon Gillham, Founder of Originality.ai came up with a tool to detect whether the content is written by humans or AI tools. It’s built on such technology that can specifically detect content by ChatGPT-3 — by giving you a spam score of 0-100, with an accuracy of 94%.
Felix Rose-Collins
ranktracker.com
ChatGPT lacks empathy and originality. It’s also recognized as AI-generated content most of the time by plagiarism and AI detectors like Originality.ai
Ashley Stahl
forbes.com
Originality.ai Do give them a shot!
Sri Krishna
venturebeat.com
For web publishers, Originality.ai will enable you to scan your content seamlessly, see who has checked it previously, and detect if an AI-powered tool was implored.
Industry Trends
analyticsinsight.net
Tools for conducting a plagiarism check between two documents online are important as it helps to ensure the originality and authenticity of written work. Plagiarism undermines the value of professional and educational institutions, as well as the integrity of the authors who write articles. By checking for plagiarism, you can ensure the work that you produce is original or properly attributed to the original author. This helps prevent the distribution of copied and misrepresented information.
Text comparison is the process of taking two or more pieces of text and comparing them to see if there are any similarities, differences and/or plagiarism. The objective of a text comparison is to see if one of the texts has been copied or paraphrased from another text. This text compare tool for plagiarism check between two documents has been built to help you streamline that process by finding the discrepancies with ease.
Text comparison tools work by analyzing and comparing the contents of two or more text documents to find similarities and differences between them. This is typically done by breaking the texts down into smaller units such as sentences or phrases, and then calculating a similarity score based on the number of identical or nearly identical units. The comparison may be based on the exact wording of the text, or it may take into account synonyms and other variations in language. The results of the comparison are usually presented in the form of a report or visual representation, highlighting the similarities and differences between the texts.
String comparison is a fundamental operation in text comparison tools that involves comparing two sequences of characters to determine if they are identical or not. This comparison can be done at the character level or at a higher level, such as the word or sentence level.
The most basic form of string comparison is the equality test, where the two strings are compared character by character and a Boolean result indicating whether they are equal or not is returned. More sophisticated string comparison algorithms use heuristics and statistical models to determine the similarity between two strings, even if they are not exactly the same. These algorithms often use techniques such as edit distance, which measures the minimum number of operations (such as insertions, deletions, and substitutions) required to transform one string into another.
Another common technique for string comparison is n-gram analysis, where the strings are divided into overlapping sequences of characters (n-grams) and the frequency of each n-gram is compared between the two strings. This allows for a more nuanced comparison that takes into account partial similarities, rather than just exact matches.
String comparison is a crucial component of text comparison tools, as it forms the basis for determining the similarities and differences between texts. The results of the string comparison can then be used to generate a report or visual representation of the similarities and differences between the texts.
Syntax highlighting is a feature of text editors and integrated development environments (IDEs) that helps to visually distinguish different elements of a code or markup language. It does this by coloring different elements of the code, such as keywords, variables, functions, and operators, based on a predefined set of rules.
The purpose of syntax highlighting is to make the code easier to read and understand, by drawing attention to the different elements and their structure. For example, keywords may be colored in a different hue to emphasize their importance, while comments or strings may be colored differently to distinguish them from the code itself. This helps to make the code more readable, reducing the cognitive load of the reader and making it easier to identify potential syntax errors.
With our tool it’s easy, just enter or upload some text, click on the button “Compare text” and the tool will automatically display the diff between the two texts.
Using text comparison tools is much easier, more efficient, and more reliable than proofreading a piece of text by hand. Eliminate the risk of human error by using a tool to detect and display the text difference within seconds.
We have support for the file extensions .pdf, .docx, .odt, .doc and .txt. You can also enter your text or copy and paste text to compare.
There is never any data saved by the tool, when you hit “Upload” we are just scanning the text and pasting it into our text area so with our text compare tool, no data ever enters our servers.
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This table below shows a heat map of features on other sites compared to ours as you can see we almost have greens across the board!
We studied how Originality.ai’s multilingual AI detector stacked up to state-of-the-art AI content detectors across a range of Arabic datasets, as per the study “The Arabic AI Fingerprint: Stylometric Analysis and Detection of Large Language Models Text.” These are our findings.
