NEWS

SERP Analysis Software For SEO and Ranking?

Published

3 years ago

April 29, 2021

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.

There’s no such thing as LSI keywords — anyone who’s telling you otherwise is mistaken, sorry.

— 🍌 John 🍌 (@JohnMu) July 30, 2019

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

NEWS

OpenAI Introduces Fine-Tuning for GPT-4 and Enabling Customized AI Models

Published

4 weeks ago

August 21, 2024

Max

OpenAI Introduces Fine-Tuning for GPT-4 and Enabling Customized AI Models

OpenAI has today announced the release of fine-tuning capabilities for its flagship GPT-4 large language model, marking a significant milestone in the AI landscape. This new functionality empowers developers to create tailored versions of GPT-4 to suit specialized use cases, enhancing the model’s utility across various industries.

Fine-tuning has long been a desired feature for developers who require more control over AI behavior, and with this update, OpenAI delivers on that demand. The ability to fine-tune GPT-4 allows businesses and developers to refine the model’s responses to better align with specific requirements, whether for customer service, content generation, technical support, or other unique applications.

Why Fine-Tuning Matters

GPT-4 is a very flexible model that can handle many different tasks. However, some businesses and developers need more specialized AI that matches their specific language, style, and needs. Fine-tuning helps with this by letting them adjust GPT-4 using custom data. For example, companies can train a fine-tuned model to keep a consistent brand tone or focus on industry-specific language.

Fine-tuning also offers improvements in areas like response accuracy and context comprehension. For use cases where nuanced understanding or specialized knowledge is crucial, this can be a game-changer. Models can be taught to better grasp intricate details, improving their effectiveness in sectors such as legal analysis, medical advice, or technical writing.

Key Features of GPT-4 Fine-Tuning

The fine-tuning process leverages OpenAI’s established tools, but now it is optimized for GPT-4’s advanced architecture. Notable features include:

Enhanced Customization: Developers can precisely influence the model’s behavior and knowledge base.
Consistency in Output: Fine-tuned models can be made to maintain consistent formatting, tone, or responses, essential for professional applications.
Higher Efficiency: Compared to training models from scratch, fine-tuning GPT-4 allows organizations to deploy sophisticated AI with reduced time and computational cost.

Additionally, OpenAI has emphasized ease of use with this feature. The fine-tuning workflow is designed to be accessible even to teams with limited AI experience, reducing barriers to customization. For more advanced users, OpenAI provides granular control options to achieve highly specialized outputs.

Implications for the Future

The launch of fine-tuning capabilities for GPT-4 signals a broader shift toward more user-centric AI development. As businesses increasingly adopt AI, the demand for models that can cater to specific business needs, without compromising on performance, will continue to grow. OpenAI’s move positions GPT-4 as a flexible and adaptable tool that can be refined to deliver optimal value in any given scenario.

By offering fine-tuning, OpenAI not only enhances GPT-4’s appeal but also reinforces the model’s role as a leading AI solution across diverse sectors. From startups seeking to automate niche tasks to large enterprises looking to scale intelligent systems, GPT-4’s fine-tuning capability provides a powerful resource for driving innovation.

OpenAI announced that fine-tuning GPT-4o will cost $25 for every million tokens used during training. After the model is set up, it will cost $3.75 per million input tokens and $15 per million output tokens. To help developers get started, OpenAI is offering 1 million free training tokens per day for GPT-4o and 2 million free tokens per day for GPT-4o mini until September 23. This makes it easier for developers to try out the fine-tuning service.

As AI continues to evolve, OpenAI’s focus on customization and adaptability with GPT-4 represents a critical step in making advanced AI accessible, scalable, and more aligned with real-world applications. This new capability is expected to accelerate the adoption of AI across industries, creating a new wave of AI-driven solutions tailored to specific challenges and opportunities.

GOOGLE

This Week in Search News: Simple and Easy-to-Read Update

Published

3 months ago

June 30, 2024

Entireweb News Bot

This Week in Search News: Simple and Easy-to-Read Update

Here’s what happened in the world of Google and search engines this week:

1. Google’s June 2024 Spam Update

Google finished rolling out its June 2024 spam update over a period of seven days. This update aims to reduce spammy content in search results.

2. Changes to Google Search Interface

Google has removed the continuous scroll feature for search results. Instead, it’s back to the old system of pages.

3. New Features and Tests

Link Cards: Google is testing link cards at the top of AI-generated overviews.
Health Overviews: There are more AI-generated health overviews showing up in search results.
Local Panels: Google is testing AI overviews in local information panels.

4. Search Rankings and Quality

Improving Rankings: Google said it can improve its search ranking system but will only do so on a large scale.
Measuring Quality: Google’s Elizabeth Tucker shared how they measure search quality.

5. Advice for Content Creators

Brand Names in Reviews: Google advises not to avoid mentioning brand names in review content.
Fixing 404 Pages: Google explained when it’s important to fix 404 error pages.

6. New Search Features in Google Chrome

Google Chrome for mobile devices has added several new search features to enhance user experience.

7. New Tests and Features in Google Search

Credit Card Widget: Google is testing a new widget for credit card information in search results.
Sliding Search Results: When making a new search query, the results might slide to the right.

8. Bing’s New Feature

Bing is now using AI to write “People Also Ask” questions in search results.

9. Local Search Ranking Factors

Menu items and popular times might be factors that influence local search rankings on Google.

10. Google Ads Updates

Query Matching and Brand Controls: Google Ads updated its query matching and brand controls, and advertisers are happy with these changes.
Lead Credits: Google will automate lead credits for Local Service Ads. Google says this is a good change, but some advertisers are worried.
tROAS Insights Box: Google Ads is testing a new insights box for tROAS (Target Return on Ad Spend) in Performance Max and Standard Shopping campaigns.
WordPress Tag Code: There is a new conversion code for Google Ads on WordPress sites.

These updates highlight how Google and other search engines are continuously evolving to improve user experience and provide better advertising tools.

FACEBOOK

Facebook Faces Yet Another Outage: Platform Encounters Technical Issues Again

Published

6 months ago

March 20, 2024

Max

Uppdated: It seems that today’s issues with Facebook haven’t affected as many users as the last time. A smaller group of people appears to be impacted this time around, which is a relief compared to the larger incident before. Nevertheless, it’s still frustrating for those affected, and hopefully, the issues will be resolved soon by the Facebook team.

Facebook had another problem today (March 20, 2024). According to Downdetector, a website that shows when other websites are not working, many people had trouble using Facebook.

This isn’t the first time Facebook has had issues. Just a little while ago, there was another problem that stopped people from using the site. Today, when people tried to use Facebook, it didn’t work like it should. People couldn’t see their friends’ posts, and sometimes the website wouldn’t even load.

Downdetector, which watches out for problems on websites, showed that lots of people were having trouble with Facebook. People from all over the world said they couldn’t use the site, and they were not happy about it.

When websites like Facebook have problems, it affects a lot of people. It’s not just about not being able to see posts or chat with friends. It can also impact businesses that use Facebook to reach customers.

Since Facebook owns Messenger and Instagram, the problems with Facebook also meant that people had trouble using these apps. It made the situation even more frustrating for many users, who rely on these apps to stay connected with others.

During this recent problem, one thing is obvious: the internet is always changing, and even big websites like Facebook can have problems. While people wait for Facebook to fix the issue, it shows us how easily things online can go wrong. It’s a good reminder that we should have backup plans for staying connected online, just in case something like this happens again.