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SERP Analysis Software For SEO and Ranking?

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A relatively new type of software analyzes the search engines results pages (SERPs) and provides recommendations based on statistical analysis of similarities shared between the top ranked sites. But some in the search community have doubts about the usefulness of this kind of software.

SERP Correlation Analysis and Lack of Causation

This kind of analysis is called Search Engine Results Page (SERP) Correlation Analysis. SERP analysis is research that analyzes Google search results to identify factors in ranked web pages.

The SEO community has found startling correlations in the past by studying search results.

One analysis discovered that top ranked sites tended to have Facebook pages with a lot of likes.

Of course, those top ranked sites were not top ranking because of the Facebook likes.

Just because the top ranked sites share certain features does not mean that those features caused them to rank better.

And that lack of actual cause between the factors in common and the actual reasons why those sites are top ranked can be seen as a problem.

Just because web pages ranked in the search results share a word count, a keyword density or share keywords in common does not mean that those word counts, keyword densities and keywords are causing those pages to rank.

SERPs Are No Longer Ten Blue Links

Another problem with analyzing the top ten of the search results is that the search results are no longer a list of ten ranked web pages, the ten blue links.

Bill Slawski (@bill_slawski) of GoFishDigital expressed little confidence in search results correlation analysis.

He said,

“The data in correlation studies may be cleaned so that One Boxes and Featured Snippets don’t appear within them, but it’s been a long time since we lived in a world of ten blue links.”

Misleading Analysis?

I asked an AI-based content optimization company (@MarketMuseCo) about SERP Analysis software.

They responded:

“Content optimization tools that scrape SERPs and use term frequency calculations to tell you what to write about are misleading at best.

Most of these tools will scrape content from the top 10-30 search results, extract common terms, and rate their relevance using Google AdWords Keyword Planner from Google’s public API.

Adding words to your content from these types of tools will never lead to comprehensive, expertly written content that, over time, becomes a competitive advantage for your business.”

SERP Analysis Software and LSI Keywords

Some of these SERP Analysis tools promote outdated concepts like LSI Keywords as being important for ranking in Google.

This is a concept that is well known to have little relevance for ranking in Google’s search results.

User Reviews of SERP Analysis Software

Nigel Mordaunt, Director at Australian Search Consultancy, Status Digital Group, told me that he tried SERP analysis tools and was not satisfied with the results.

He offered his opinion of these tools based on his hands-on experience:

“Using those tools do not promote reader satisfaction, which I think is the core of on-page SEO. It more promotes a copycat style of content which mimics 1,000 other sites within your niche.”

Jeff Ferguson (@CountXero), a marketer with over 20 years of experience, Partner/Head of Production, Amplitude Digital (@AmplitudeAgency) and Adjunct Professor, UCLA offered his opinion based on his own experience with these kinds of tools.

Jeff commented:

“I’ve played with a few of these before, and I can see the appeal; however, all too often, their reasoning for doing certain things is based on SEO myths, outdated info, or just flat out made up.

Most of them are great at doing a word count of the content for a given keyword, but word count isn’t a ranking factor. Others are pushing things like “LSI Keywords,” which don’t actually exist in the Google universe.”

More Data Does Not Give You Better Results

Some of these tools will analyze more than the top ten of the search results. They may analyze the top 30 and higher.

But more data does not translate into better analysis. The idea that more data will yield a better analysis is a common misconception.

According to Data Science Consultant Michael Grogan writing in TowardsDataScience.com:

“More data is not better if much of that data is irrelevant to what you are trying to predict. Even machine learning models can be misled if the training set is not representative of reality.

…Is inclusion of certain data relevant to the problem that we are trying to solve?  …it should not be assumed that blindly introducing more data into a model will improve its accuracy.”

Wikipedia has an entry about accuracy and precision, where accuracy is about how close an experiment or analysis is to the truth and precision is how reproducible the results can be, regardless if the results are accurate or not.

“For example, if an experiment contains a systematic error, then increasing the sample size generally increases precision but does not improve accuracy. The result would be a consistent yet inaccurate string of results from the flawed experiment.”

Accuracy is a problem with SERP Analysis in that the typical analysis does not account for all the variables that are responsible for why a web page ranks in the search results.

The reason they don’t account for all the variables is because nobody outside of Google knows what those variables are.

Analyzing Search Results Yields Flawed Results

Analyzing the search results has consistently yielded questionable results. One can analyze the results and tease out something like a possible search intent.

But to claim to identify factors that are responsible for why a site is ranking is questionable.

I mentioned to Bill Slawski that I was writing about SERP Analysis Software and he quipped:

“I laughed my head off after reading the —– website. Word count has never been a ranking signal at Google. Neither has keyword density.”

Everyone has their opinion about this kind of software. Some people may find value in it.

It’s up to you to research and determine if this kind of software is useful for you.

Searchenginejournal.com

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OpenAI Introduces ChatGPT Plus with Monthly Subscription of $20

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Open AI - Chat GPT

OpenAI, the leading artificial intelligence research laboratory, has launched a new product – ChatGPT Plus. The new product is an advanced version of its previous language model, ChatGPT, and is available for a monthly subscription of $20. The company aims to provide a more sophisticated and efficient conversational AI tool to its users through this new product.

ChatGPT Plus is a state-of-the-art language model that uses advanced deep learning algorithms to generate human-like responses to text inputs. The model has been trained on a massive corpus of text data, allowing it to generate coherent and contextually relevant responses. The model is designed to handle a wide range of conversational topics and can be integrated into various applications, such as chatbots, customer support systems, and virtual assistants.

One of the main advantages of ChatGPT Plus over its predecessor, ChatGPT, is its ability to generate responses in a more human-like manner. The model has been fine-tuned to incorporate more advanced language processing techniques, which enable it to better understand the context and tone of a conversation. This makes it possible for the model to generate more nuanced and appropriate responses, which can greatly improve the user experience.

In addition to its advanced language processing capabilities, ChatGPT Plus also offers improved performance in terms of response generation speed and efficiency. The model has been optimized to run on faster hardware and has been fine-tuned to generate responses more quickly. This makes it possible for the model to handle a larger volume of requests, making it an ideal solution for businesses with high traffic websites or customer support centers.

The monthly subscription fee of $20 for ChatGPT Plus makes it an affordable solution for businesses of all sizes. The company has designed the pricing model in such a way that it is accessible to businesses of all sizes, regardless of their budget. This makes it possible for small businesses to take advantage of advanced conversational AI technology, which can greatly improve their customer engagement and support.

OpenAI has also made it easy to integrate ChatGPT Plus into various applications. The company has provided a comprehensive API that allows developers to easily integrate the model into their applications. The API supports a wide range of programming languages, making it possible for developers to use the technology regardless of their preferred programming language. This makes it possible for businesses to quickly and easily incorporate conversational AI into their operations.

In conclusion, OpenAI’s launch of ChatGPT Plus is a significant development in the field of conversational AI. The new product offers advanced language processing capabilities and improved performance, making it an ideal solution for businesses of all sizes. The affordable pricing model and easy integration make it accessible to businesses of all sizes, and the advanced language processing capabilities make it possible for businesses to improve their customer engagement and support. OpenAI’s ChatGPT Plus is set to revolutionize the conversational AI industry and bring advanced technology within the reach of businesses of all sizes.

Visit OpenAI.com to read more and to get the latest news about ChatGPT.

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What can ChatGPT do?

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ChatGPT Explained

ChatGPT is a large language model developed by OpenAI that is trained on a massive amount of text data. It is capable of generating human-like text and has been used in a variety of applications, such as chatbots, language translation, and text summarization.

One of the key features of ChatGPT is its ability to generate text that is similar to human writing. This is achieved through the use of a transformer architecture, which allows the model to understand the context and relationships between words in a sentence. The transformer architecture is a type of neural network that is designed to process sequential data, such as natural language.

Another important aspect of ChatGPT is its ability to generate text that is contextually relevant. This means that the model is able to understand the context of a conversation and generate responses that are appropriate to the conversation. This is accomplished by the use of a technique called “masked language modeling,” which allows the model to predict the next word in a sentence based on the context of the previous words.

One of the most popular applications of ChatGPT is in the creation of chatbots. Chatbots are computer programs that simulate human conversation and can be used in customer service, sales, and other applications. ChatGPT is particularly well-suited for this task because of its ability to generate human-like text and understand context.

Another application of ChatGPT is language translation. By training the model on a large amount of text data in multiple languages, it can be used to translate text from one language to another. The model is able to understand the meaning of the text and generate a translation that is grammatically correct and semantically equivalent.

In addition to chatbots and language translation, ChatGPT can also be used for text summarization. This is the process of taking a large amount of text and condensing it into a shorter, more concise version. ChatGPT is able to understand the main ideas of the text and generate a summary that captures the most important information.

Despite its many capabilities and applications, ChatGPT is not without its limitations. One of the main challenges with using language models like ChatGPT is the risk of generating text that is biased or offensive. This can occur when the model is trained on text data that contains biases or stereotypes. To address this, OpenAI has implemented a number of techniques to reduce bias in the training data and in the model itself.

In conclusion, ChatGPT is a powerful language model that is capable of generating human-like text and understanding context. It has a wide range of applications, including chatbots, language translation, and text summarization. While there are limitations to its use, ongoing research and development is aimed at improving the model’s performance and reducing the risk of bias.

** The above article has been written 100% by ChatGPT. This is an example of what can be done with AI. This was done to show the advanced text that can be written by an automated AI.

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Google December Product Reviews Update Affects More Than English Language Sites? via @sejournal, @martinibuster

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Google’s Product Reviews update was announced to be rolling out to the English language. No mention was made as to if or when it would roll out to other languages. Mueller answered a question as to whether it is rolling out to other languages.

Google December 2021 Product Reviews Update

On December 1, 2021, Google announced on Twitter that a Product Review update would be rolling out that would focus on English language web pages.

The focus of the update was for improving the quality of reviews shown in Google search, specifically targeting review sites.

A Googler tweeted a description of the kinds of sites that would be targeted for demotion in the search rankings:

“Mainly relevant to sites that post articles reviewing products.

Think of sites like “best TVs under $200″.com.

Goal is to improve the quality and usefulness of reviews we show users.”

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Google also published a blog post with more guidance on the product review update that introduced two new best practices that Google’s algorithm would be looking for.

The first best practice was a requirement of evidence that a product was actually handled and reviewed.

The second best practice was to provide links to more than one place that a user could purchase the product.

The Twitter announcement stated that it was rolling out to English language websites. The blog post did not mention what languages it was rolling out to nor did the blog post specify that the product review update was limited to the English language.

Google’s Mueller Thinking About Product Reviews Update

Screenshot of Google's John Mueller trying to recall if December Product Review Update affects more than the English language

Screenshot of Google's John Mueller trying to recall if December Product Review Update affects more than the English language

Product Review Update Targets More Languages?

The person asking the question was rightly under the impression that the product review update only affected English language search results.

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But he asserted that he was seeing search volatility in the German language that appears to be related to Google’s December 2021 Product Review Update.

This is his question:

“I was seeing some movements in German search as well.

So I was wondering if there could also be an effect on websites in other languages by this product reviews update… because we had lots of movement and volatility in the last weeks.

…My question is, is it possible that the product reviews update affects other sites as well?”

John Mueller answered:

“I don’t know… like other languages?

My assumption was this was global and and across all languages.

But I don’t know what we announced in the blog post specifically.

But usually we try to push the engineering team to make a decision on that so that we can document it properly in the blog post.

I don’t know if that happened with the product reviews update. I don’t recall the complete blog post.

But it’s… from my point of view it seems like something that we could be doing in multiple languages and wouldn’t be tied to English.

And even if it were English initially, it feels like something that is relevant across the board, and we should try to find ways to roll that out to other languages over time as well.

So I’m not particularly surprised that you see changes in Germany.

But I also don’t know what we actually announced with regards to the locations and languages that are involved.”

Does Product Reviews Update Affect More Languages?

While the tweeted announcement specified that the product reviews update was limited to the English language the official blog post did not mention any such limitations.

Google’s John Mueller offered his opinion that the product reviews update is something that Google could do in multiple languages.

One must wonder if the tweet was meant to communicate that the update was rolling out first in English and subsequently to other languages.

It’s unclear if the product reviews update was rolled out globally to more languages. Hopefully Google will clarify this soon.

Citations

Google Blog Post About Product Reviews Update

Product reviews update and your site

Google’s New Product Reviews Guidelines

Write high quality product reviews

John Mueller Discusses If Product Reviews Update Is Global

Watch Mueller answer the question at the 14:00 Minute Mark

[embedded content]Searchenginejournal.com

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