SEO
Top 10 Essential Website Optimization Strategies

Google officially launched 24 years ago in 1998.
A lot has changed since then, but one thing remains the same. If you simply focus on the basics, you can still be highly successful online.
Of course, the basics in 2022 are much different from the basics in 1998. It’s easy to get overwhelmed and distracted. It has never been more important to be disciplined in one’s approach to SEO.
So, the obvious question is this: What are the factors to concentrate on? How can one boost rankings? How can anyone build traffic in such a competitive environment?
This post will delve into which factors carry the most weight and how to optimize for each.
1. Search Intent
As machine learning, artificial intelligence, and deep learning continue to evolve, each will carry more weight in the Google Core Algorithm.
The end goal for Google is to understand the context of a given search query and to serve results consistent with the user intent. This makes advanced-level keyword research and keyword selection more important than ever.
Before spending time and resources trying to rank for a phrase, you will need to look at the websites that are currently at the top of the SERPs for that phrase.
A keyword’s contextual relevance must align with a search query. There will be some keywords and queries that will be impossible to rank for.
For example, if Google has determined that people searching for “Personal Injury Attorney [insert city]” want a list of lawyers to choose from, then a series of trusted law directories will appear at the top of the SERPs.
An individual or single firm will not supplant those directories. In those cases, you will need to refine your strategy.
2. Technical SEO
The foundation for technical SEO is having a solid website architecture.
One cannot simply publish a random collection of pages and posts. An SEO-friendly site architecture will guide users throughout your site and make it easy for Google to crawl and index your pages.
Once you have the right architecture in place, it’s time to perform a technical or SEO audit.
Thanks to the many SEO tools available, an SEO audit is no longer a daunting task. That said, the key is to know how to interpret the data provided and what to do with it.
For starters, you should check the following and fix any issues that are uncovered:
- Check for status code errors and correct them.
- Check the robot.txt for errors. Optimize if needed.
- Check your site indexing via Google Search Console. Examine and fix any issues discovered.
- Fix duplicate title tags and duplicate meta descriptions.
- Audit your website content. Check the traffic stats in Google Analytics. Consider improving or pruning underperforming content.
- Fix broken links. These are an enemy of the user experience – and potentially rankings.
- Submit your XML sitemap to Google via Google Search Console.
3. User Experience
User experience (UX) is centered on gaining insight into users, their needs, their values, their abilities, and their limitations.
UX also takes into consideration business goals and objectives. The best UX practices focus on improving the quality of the user experience.
According to Peter Morville, factors that influence UX include:
- Useful: Your content needs to be unique and satisfy a need.
- Usable: Your website needs to be easy to use and navigate.
- Desirable: Your design elements and brand should evoke emotion and appreciation.
- Findable: Integrate design and navigation elements to make it easy for users to find what they need.
- Accessible: Content needs to be accessible to everyone – including the 12.7% of the population with disabilities.
- Credible: Your site needs to be trustworthy for users to believe you.
- Valuable: Your site needs to provide value to the user in terms of experience and to the company in terms of positive ROI.
Multivariate and A/B testing is the best way to measure and create a better experience for website users. Multivariate testing is best when considering complex changes.
One can incorporate many different elements and test how they all work together. A/B testing, on the other hand, will compare two different elements on your site to determine which performs the best.
4. Mobile-First
Google officially began rolling out the mobile-first index in March 2018. Smart marketers were taking a mobile-first approach long before the official rollout.
According to Google Search Central:
“Neither mobile-friendliness nor a mobile-responsive layout are requirements for mobile-first indexing. Pages without mobile versions still work on mobile and are usable for indexing. That said, it’s about time to move from desktop-only and embrace mobile :)”
Here are some basics for making your site mobile-friendly:
- Make your site adaptive to any device – be it desktop, mobile, or tablet.
- Always scale your images when using a responsive design, especially for mobile users.
- Use short meta titles. They are easier to read on mobile devices.
- Avoid pop-ups that cover your content and prevent visitors from getting a glimpse of what your content is all about.
- Less can be more on mobile. In a mobile-first world, long-form content doesn’t necessarily equate to more traffic and better rankings.
- Don’t use mobile as an excuse for cloaking. Users and search engines need to see the same content.
5. Core Web Vitals
In July of 2021, the Page Experience Update rolled out and is now incorporated into Google’s core algorithm, as a ranking factor.
As the name implies, the core web vitals initiative was designed to quantify the essential metrics for a healthy website. This syncs up with Google’s commitment to delivering the best user experience.
According to Google, “loading experience, interactivity, and visual stability of page content, and combined are the foundation of Core Web Vitals.”
Each one of these metrics:
- Focuses on a unique aspect of the user experience.
- Is measurable and quantifiable for an objective determination of the outcome.
Tools To Measure Core Web Vitals:
- PageSpeed Insights: Measures both mobile and desktop performance and provides recommendations for improvement.
- Lighthouse: An open-source, automated tool developed by Google to help developers improve web page quality. It has several features not available in PageSpeed Insights, including some SEO checks.
- Search Console: A Core Web Vitals report is now included in GSC, showing URL performance as grouped by status, metric type, and URL group.
6. Schema
Schema markup, once added to a webpage, creates a rich snippet – an enhanced description that appears in the search results.
All leading search engines, including Google, Yahoo, Bing, and Yandex, support the use of microdata. The real value of schema is that it can provide context to a webpage and improve the search experience.
There is no evidence that adding schema has any influence on SERPs.
Following, you will find some of the most popular uses for schema
If you find the thought of adding schema to a page intimidating, you shouldn’t. Schema is quite simple to implement. If you have a WordPress site, there are several plugins that will do this for you.
7. Content Marketing
It is projected that 97 zettabytes of data will be created, captured, copied, and consumed worldwide this year.
To put this in perspective, that’s the equivalent of 18.7 trillion songs or 3,168 years of HD video every day.
The challenge of breaking through the clutter will become exponentially more difficult as time passes.
To do so:
- Create a content hub in the form of a resource center.
- Fill your resource hub with a combination of useful, informative, and entertaining content.
- Write “spoke” pieces related to your resource hub and interlink.
- Write news articles related to your resource and interlink.
- Spread the word. Promote your news articles on social channels.
- Hijack trending topics related to your content. Promote on social media.
- Use your smartphone camera. Images and videos typically convert better than text alone.
- Update stale and low-trafficked content.
8. Link Building
Links continue to be one of the most important ranking factors.
Over the years, Google has become more adept at identifying and devaluing spammy links, especially so after the launch of Penguin 4.0. That being the case, quality will continue to trump quantity.
The best link-building strategies for 2022 include:
9. Test And Document Changes
You manage what you measure.
One recent study showed that less than 50% of pages “optimized” result in more clicks. Worse yet, 34% of changes led to a decrease in clicks!
Basic steps for SEO testing:
- Determine what you are testing and why.
- Form a hypothesis. What do you expect will happen because of your changes?
- Document your testing. Make sure it can be reliably replicated.
- Publish your changes and then submit the URLs for inspection via Google Search Console.
- Run the test for a long enough period to confirm if your hypothesis is correct or not. Document your findings and any other observations, such as changes made by competitors that may influence the outcome.
- Take appropriate actions based on the results of your tests.
This process can be easily executed and documented by using a spreadsheet.
10. Track And Analyze KPIs
According to Roger Monti, the following are the 9 Most Important SEO KPIs to consider:
- Customer Lifetime Value (CLV).
- Content Efficiency.
- Average Engagement Time.
- Conversion Goals by Percent-Based Metrics.
- Accurate Search Visibility.
- Brand Visibility in Search.
- New And Returning Users.
- Average Time on Site.
- Revenue Per Thousand (RPM) And Average Position.
The thing to remember about these KPIs is they are dependent upon your goals and objectives. Some may apply to your situation whereas others may not.
Think of this as a good starting point for determining how to best measure the success of a campaign.
Conclusion
Because the internet has no expiration date, mounds of information and disinformation are served up daily in various search queries.
If you aren’t careful, implementing bad or outdated advice can lead to disastrous results.
Do yourself a favor and just focus on these 10 essentials. By doing so, you will be setting yourself up for long-term success.
More Resources:
Featured Image: Rawpixel.com/Shutterstock
SEO
Google Analytics 4 Features To Prepare For Third-Party Cookie Depreciation

Google will roll out new features and integrations for Google Analytics 4 (GA4) for first-party data, enhanced conversions, and durable ad performance metrics.
Beginning in Q1 2024, Chrome will gradually phase out third-party cookies for a percentage of users, allowing for testing and transition.
Third-party cookies, which have been central to cross-site tracking, are being restricted or phased out by major browsers, including Chrome, as part of its Privacy Sandbox project.
The following features should help advertisers “unlock durable performance” while preserving user privacy.
Support For Protected Audience API In GA4
A key feature of recent updates to Google Analytics 4 is the integration of Protected Audience API, a Privacy Sandbox technology that is set to become widely available in early 2024.
This API allows advertisers to continue reaching their audiences after the third-party cookie phase-out.
What Is The Protected Audience API?
The Protected Audience API offers a novel approach to remarketing, which involves reminding users about sites and products they have shown interest in without relying on third-party cookies.

This method involves advertisers informing the browser directly about their interest in showing ads to users in the future.
The browser then uses an algorithm to determine which ads to display based on the user’s web activity and advertiser inputs.
It enables on-device auctions by the browser, allowing it to choose relevant ads from sites previously visited by the user without tracking their browsing behavior across different sites.
Key Features And Development
Key features of the Protected Audience API include interest groups stored by the browser, on-device bidding and ad selection, and ad rendering in a temporarily relaxed version of Fenced Frames.
The API also supports a key/value service for real-time information retrieval, which can be used by both buyers and sellers for various purposes, such as budget calculation or policy compliance.
The Protected Audience API, initially known as the FLEDGE API, has evolved from an experimental stage to a more mature phase, reflecting its readiness for wider implementation.
This transition is part of Google’s broader efforts to develop privacy-preserving APIs and technologies in collaboration with industry stakeholders and regulatory bodies like the UK’s Competition and Markets Authority.
The Protected Audience API offers a new way to connect with users while respecting their privacy, necessitating a reevaluation of current advertising strategies and a focus on adapting to these emerging technologies.
Support For Enhanced Conversions
Rolling out in the next few weeks, enhanced conversions is a feature enhancing conversion measurement accuracy.


Enhanced conversions for the web cater to advertisers tracking online sales and events. It captures and hashes customer data like email addresses during a conversion on the web, then matches this with Google accounts linked to ad interactions.
This method recovers unmeasured conversions, optimizes bidding, and maintains data privacy.
For leads, enhanced conversions track sales from website leads occurring offline. It uses hashed data from website forms, like email addresses, to measure offline conversions.
Setup options for enhanced conversions include Google Tag Manager, a Google tag, or the Google Ads API, with third-party partner support available.
Advertisers can import offline conversion data for Google Ads from Salesforce, Zapier, and HubSpot with Google Click Identifier (GCLID).
Proper Consent Setup
To effectively use Google’s enhanced privacy features, it’s essential to have proper user consent mechanisms in place, particularly for traffic from the European Economic Area (EEA).
Google’s EU user consent policy mandates consent collection for personal data usage in measurement, ad personalization, and remarketing features. This policy extends to website tags, app SDKs, and data uploads like offline conversion imports.
Google has updated the consent mode API to include parameters for user data consent and personalized advertising.
Advertisers using Google-certified consent management platforms (CMPs) will see automatic updates to the latest consent mode, while those with self-managed banners should upgrade to consent mode v2.
Implementing consent mode allows you to adjust Google tag behavior based on user consent, ensuring compliance and enabling conversion modeling for comprehensive reporting and optimization.
Consent Mode integration with CMPs simplifies managing consent banners and the consent management process, adjusting data collection based on user choices and supporting behavioral modeling for a complete view of consumer performance.
Durable Ad Performance With AI Essentials
To effectively utilize AI, marketers need robust measurement and audience tools for confident decision-making.
Google provided a general checklist of AI essentials for Google advertisers. In it, advertisers are encouraged to adopt AI-powered search and Performance Max campaigns, engage in Smart Bidding, and explore video campaigns on platforms like YouTube.
Google also offers a more in-depth checklist for Google Ads, Display & Video 360, and Campaign Manager 360.


More Ways To Prepare For The Third-Party Cookie Phase Out
As third-party cookies are phased out, it’s essential to audit and modify web code, especially focusing on instances of SameSite=None using tools like Chrome DevTools.
Adapting to this change involves understanding and managing both third-party and first-party cookies, ensuring they are set correctly for cross-site contexts and compliance.
Chrome provides solutions like Partitioned cookies with CHIPS and Related Website Sets.
At the same time, the Privacy Sandbox introduces APIs for privacy-centric alternatives, with additional support for enterprise-managed Chrome and ongoing development of tools and trials to assist in the transition.
As Google continues to update resources and documentation to reflect these changes, stakeholders are encouraged to engage and provide feedback, ensuring that the evolution of these technologies aligns with industry needs and user privacy standards.
Featured image: Primakov/Shutterstock
SEO
4 Ways To Try The New Model From Mistral AI

In a significant leap in large language model (LLM) development, Mistral AI announced the release of its newest model, Mixtral-8x7B.
magnet:?xt=urn:btih:5546272da9065eddeb6fcd7ffddeef5b75be79a7&dn=mixtral-8x7b-32kseqlen&tr=udp%3A%2F%https://t.co/uV4WVdtpwZ%3A6969%2Fannounce&tr=http%3A%2F%https://t.co/g0m9cEUz0T%3A80%2Fannounce
RELEASE a6bbd9affe0c2725c1b7410d66833e24
— Mistral AI (@MistralAI) December 8, 2023
What Is Mixtral-8x7B?
Mixtral-8x7B from Mistral AI is a Mixture of Experts (MoE) model designed to enhance how machines understand and generate text.
Imagine it as a team of specialized experts, each skilled in a different area, working together to handle various types of information and tasks.
A report published in June reportedly shed light on the intricacies of OpenAI’s GPT-4, highlighting that it employs a similar approach to MoE, utilizing 16 experts, each with around 111 billion parameters, and routes two experts per forward pass to optimize costs.
This approach allows the model to manage diverse and complex data efficiently, making it helpful in creating content, engaging in conversations, or translating languages.
Mixtral-8x7B Performance Metrics
Mistral AI’s new model, Mixtral-8x7B, represents a significant step forward from its previous model, Mistral-7B-v0.1.
It’s designed to understand better and create text, a key feature for anyone looking to use AI for writing or communication tasks.
New open weights LLM from @MistralAI
params.json:
– hidden_dim / dim = 14336/4096 => 3.5X MLP expand
– n_heads / n_kv_heads = 32/8 => 4X multiquery
– “moe” => mixture of experts 8X top 2 👀Likely related code: https://t.co/yrqRtYhxKR
Oddly absent: an over-rehearsed… https://t.co/8PvqdHz1bR pic.twitter.com/xMDRj3WAVh
— Andrej Karpathy (@karpathy) December 8, 2023
This latest addition to the Mistral family promises to revolutionize the AI landscape with its enhanced performance metrics, as shared by OpenCompass.
What makes Mixtral-8x7B stand out is not just its improvement over Mistral AI’s previous version, but the way it measures up to models like Llama2-70B and Qwen-72B.
It’s like having an assistant who can understand complex ideas and express them clearly.
One of the key strengths of the Mixtral-8x7B is its ability to handle specialized tasks.
For example, it performed exceptionally well in specific tests designed to evaluate AI models, indicating that it’s good at general text understanding and generation and excels in more niche areas.
This makes it a valuable tool for marketing professionals and SEO experts who need AI that can adapt to different content and technical requirements.
The Mixtral-8x7B’s ability to deal with complex math and coding problems also suggests it can be a helpful ally for those working in more technical aspects of SEO, where understanding and solving algorithmic challenges are crucial.
This new model could become a versatile and intelligent partner for a wide range of digital content and strategy needs.
How To Try Mixtral-8x7B: 4 Demos
You can experiment with Mistral AI’s new model, Mixtral-8x7B, to see how it responds to queries and how it performs compared to other open-source models and OpenAI’s GPT-4.
Please note that, like all generative AI content, platforms running this new model may produce inaccurate information or otherwise unintended results.
User feedback for new models like this one will help companies like Mistral AI improve future versions and models.
1. Perplexity Labs Playground
In Perplexity Labs, you can try Mixtral-8x7B along with Meta AI’s Llama 2, Mistral-7b, and Perplexity’s new online LLMs.
In this example, I ask about the model itself and notice that new instructions are added after the initial response to extend the generated content about my query.


While the answer looks correct, it begins to repeat itself.


The model did provide an over 600-word answer to the question, “What is SEO?”
Again, additional instructions appear as “headers” to seemingly ensure a comprehensive answer.


2. Poe
Poe hosts bots for popular LLMs, including OpenAI’s GPT-4 and DALL·E 3, Meta AI’s Llama 2 and Code Llama, Google’s PaLM 2, Anthropic’s Claude-instant and Claude 2, and StableDiffusionXL.
These bots cover a wide spectrum of capabilities, including text, image, and code generation.
The Mixtral-8x7B-Chat bot is operated by Fireworks AI.


It’s worth noting that the Fireworks page specifies it is an “unofficial implementation” that was fine-tuned for chat.
When asked what the best backlinks for SEO are, it provided a valid answer.


Compare this to the response offered by Google Bard.


3. Vercel
Vercel offers a demo of Mixtral-8x7B that allows users to compare responses from popular Anthropic, Cohere, Meta AI, and OpenAI models.


It offers an interesting perspective on how each model interprets and responds to user questions.


Like many LLMs, it does occasionally hallucinate.


4. Replicate
The mixtral-8x7b-32 demo on Replicate is based on this source code. It is also noted in the README that “Inference is quite inefficient.”


In the example above, Mixtral-8x7B describes itself as a game.
Conclusion
Mistral AI’s latest release sets a new benchmark in the AI field, offering enhanced performance and versatility. But like many LLMs, it can provide inaccurate and unexpected answers.
As AI continues to evolve, models like the Mixtral-8x7B could become integral in shaping advanced AI tools for marketing and business.
Featured image: T. Schneider/Shutterstock
SEO
OpenAI Investigates ‘Lazy’ GPT-4 Complaints On Google Reviews, X

OpenAI, the company that launched ChatGPT a little over a year ago, has recently taken to social media to address concerns regarding the “lazy” performance of GPT-4 on social media and Google Reviews.

This move comes after growing user feedback online, which even includes a one-star review on the company’s Google Reviews.
OpenAI Gives Insight Into Training Chat Models, Performance Evaluations, And A/B Testing
OpenAI, through its @ChatGPTapp Twitter account, detailed the complexities involved in training chat models.


The organization highlighted that the process is not a “clean industrial process” and that variations in training runs can lead to noticeable differences in the AI’s personality, creative style, and political bias.
Thorough AI model testing includes offline evaluation metrics and online A/B tests. The final decision to release a new model is based on a data-driven approach to improve the “real” user experience.
OpenAI’s Google Review Score Affected By GPT-4 Performance, Billing Issues
This explanation comes after weeks of user feedback about GPT-4 becoming worse on social media networks like X.
Idk if anyone else has noticed this, but GPT-4 Turbo performance is significantly worse than GPT-4 standard.
I know it’s in preview right now but it’s significantly worse.
— Max Weinbach (@MaxWinebach) November 8, 2023
There has been discussion if GPT-4 has become “lazy” recently. My anecdotal testing suggests it may be true.
I repeated a sequence of old analyses I did with Code Interpreter. GPT-4 still knows what to do, but keeps telling me to do the work. One step is now many & some are odd. pic.twitter.com/OhGAMtd3Zq
— Ethan Mollick (@emollick) November 28, 2023
Complaints also appeared in OpenAI’s community forums.


The experience led one user to leave a one-star rating for OpenAI via Google Reviews. Other complaints regarded accounts, billing, and the artificial nature of AI.


A recent user on Product Hunt gave OpenAI a rating that also appears to be related to GPT-4 worsening.


GPT-4 isn’t the only issue that local reviewers complain about. On Yelp, OpenAI has a one-star rating for ChatGPT 3.5 performance.
OpenAI is now only 3.8 stars on Google Maps and a dismal 1 star on Yelp!
GPT-4’s degradation has really hurt their rating. Hope the business survives.https://t.co/RF8uJH1WQ5 pic.twitter.com/OghAZLCiVu
— Nate Chan (@nathanwchan) December 9, 2023
The complaint:


In related OpenAI news, the review with the most likes aligns with recent rumors about a volatile workplace, alleging that OpenAI is a “Cutthroat environment. Not friendly. Toxic workers.”


The reviews voted the most helpful on Glassdoor about OpenAI suggested that employee frustration and product development issues stem from the company’s shift in focus on profits.


This incident provides a unique outlook on how customer and employee experiences can impact any business through local reviews and business ratings platforms.


Google SGE Highlights Positive Google Reviews
In addition to occasional complaints, Google reviewers acknowledged the revolutionary impact of OpenAI’s technology on various fields.
The most positive review mentions about the company appear in Google SGE (Search Generative Experience).


Conclusion
OpenAI’s recent insights into training chat models and response to public feedback about GPT-4 performance illustrate AI technology’s dynamic and evolving nature and its impact on those who depend on the AI platform.
Especially the people who just received an invitation to join ChatGPT Plus after being waitlisted while OpenAI paused new subscriptions and upgrades. Or those developing GPTs for the upcoming GPT Store launch.
As AI advances, professionals in these fields must remain agile, informed, and responsive to technological developments and the public’s reception of these advancements.
Featured image: Tada Images/Shutterstock
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