SEO
Creating SMART SEO Goals For Your Enterprise Business
A goal is only as useful as the thoughtfulness of creating it.
Like many overused marketing terms and cliches, a “goal” can become an overbearing or meaningless word or purposeless objective.
Employers may hand them down without fully understanding the feasibility of accomplishment. Employees may feel pressured to meet assigned goals, realistic or unrealistic, without a plan for how to reach them.
In particular, marketing leadership often overlook SEO goals if they assume organic is a cost-free acquisition channel that will automatically work for them behind the scenes.
Those who’ve worked in SEO for even a short time know that’s not how it works.
Especially in enterprise organizations.
While it can be challenging to determine the full impact of one’s SEO efforts, there are multiple KPIs and productive methods of tracking the effect of optimizations.
The most useful method of creating meaningful goals is applying the SMART framework to your KPIs.
You can apply the SMART framework to any goal, company, or business. But for SEO, there are particular considerations to include in your goal-building process.
And by layering SEO throughout this process, you’ll find goals that accurately reflect the impact of your SEO efforts and demonstrate you can deliver what you promised.
What Is A SMART Goal?
SMART stands for Specific, Measurable, Actionable, Realistic (or Relevant), and Timely (or Time-bound).
When creating any goal, ensure that those five dimensions apply to your goal.
As part of the goal-setting process, ask yourself each of these questions:
- What specifically is it that you plan to measure?
- Do you have a way to measure the KPI?
- Can you make an actionable impact on this KPI?
- Is the specific item you’re aiming to improve realistically changing based on your actions? Is it relevant to your company objectives?
- In what timeframe do you estimate showing your efforts’ impact on the KPI?
Go through these and only proceed to the next question if you can determine a reasonable answer to each.
Once you’ve answered each question, transform your findings into a definitive statement. And there you have it.
Applying The SMART Goals Process To SEO
The five principles of SMART can be applied to any business, company, or client.
But when creating SMART goals specifically for SEO, here’s how you should think about applying each to your goal-building process.
Specific
The purpose of SMART goals is to demonstrate the impact of specific marketing efforts, or in this case, your search and site optimizations.
Ultimately, you want to prove that your optimizations increased your business’ or client’s objectives and goals
Therefore, start the set-up of each SMART goal by choosing one particular KPI.
Limiting each goal to one KPI helps ensure the accuracy of the remaining four qualifications of SMART.
When picking a KPI for SEO, start by checking if you can tie your SEO KPIs into broader business goals and objectives.
That way, you can demonstrate how your search optimizations support your company or client’s marketing conversion funnel.
Within the funnel, these KPIs often start with total impressions on the SERP (Search Engine Results Page)and end with sales, purchases, or other financial transactions.
SEO KPIs Across The Marketing Funnel
Top Of Marketing Funnel (Awareness)
- Total impressions.
- Page 1 search volume.
- Clicks from search engines.
- CTR from search engines.
- Users from search.
- Pageviews from search.
- On-page conversions from search traffic.
- Earnings from search traffic.
Bottom Of Marketing Funnel (Conversion)
You may be inclined to rely on other SEO metrics such as specific results types, including Answer Boxes (also known as Featured Snippets), or People Also Ask placements.
However, there are two reasons to avoid those types of metrics.
They can drastically fluctuate in unrelated ways to your efforts, and more importantly, they don’t directly tie to the bigger picture business goals of traffic and conversions.
In contrast, Page 1 placements represent the number of times your content shows up on Page 1 of the SERP. There’s less than a 2.5% chance of a click if your content is not on Page 1.
So your presence on Page 1 is a huge indicator of the organic traffic you may be able to drive.
Similarly, conversions and earnings from search are particularly powerful KPIs to include in your goals as they help prove SEO and Content Marketing ROI, both critical determinants of marketing success.
Overall, it’s essential to ensure that our goals are crystal-clear and connected to our business objectives so everyone from the boardroom to the marketing department understands what success looks like.
Measurable
Fortunately, most SEO metrics are easy enough to track, as long as you have the right platforms, tools, and/or software set up to ingest your data:
- Website analytics, traffic, and acquisition sources can be tracked through tools such as Google Analytics, Adobe Analytics, or other tracking software.
- Search engines let you track your visibility, rank, and clicks of keywords that show your website through tools such as Google Search Console and Bing Webmaster Tools.
- Platforms such as BridgeEdge, Conductor, and Semrush capture your keyword rankings, rank changes, keyword MSV, result types, and so on for keywords you’ve tracked and those you research. Some have integrations that allow you to ingest your website’s data and crawl it.
- Site crawling can also happen with separate tools like ContentKing and DeepCrawl that track technical SEO components, such as title tags, meta descriptions, and alt tags, flag site errors, monitor Core Web Vitals like site speed, and more.
Before adding any of the metrics from these sources, you’ll need to establish a benchmark for it.
Timing and reporting will be discussed in greater detail when we get to the T in SMART, but essentially, your goal needs a comparison between two different points in time.
To compare data effectively, you’ll have to establish the baseline for the previous month, if not the year.
Unfortunately, it can be especially difficult to prove certain changes resulted in specific measurable metrics for SEO. And that needs to be expressed clearly when constructing and explaining your goals.
However, using segments to track specific pages you’ve updated and keywords for which you’re trying to optimize will help demonstrate whether results improved after your optimizations.
And by trying to ensure that you (or your content or web team) make your optimizations as close together as possible, you’ll have an easier time tracking changes over time.
Attainable And Achievable
There are many achievable and actionable ways to impact organic search performance.
SEO initiatives include keyword research, competitive analysis, site auditing, data analysis, resulting in optimization recommendations for new content, existing content, and technical fixes that improve the conversion funnel.
And hopefully, helps you beat out your competitors.
But not all SEO efforts can be tracked or clearly measured. Some challenges include not knowing the following:
- When Google crawls a new web page or recrawls an optimized one.
- When the SERP is updated to show optimized content.
- If the content is still relevant to consumers at that time to encourage clicks.
- If anything breaks on your site that causes errors or hurts rank or Core Web Vitals.
That last one represents why site health, internal/external linking, or other technical SEO metrics aren’t recommended for SMART Goals. There are just too many variables that you can’t control.
But by constructing your SMART Goals in a way that follows the conversion funnel, you can see the full picture that should more clearly highlight trends in organic success.
If any part of the funnel fluctuates unexpectedly, that may help flag external issues negatively impacting your success.
Plus, as long as you plan out your optimizations in advance, you can align your monthly goals to the level of impact you plan to have.
As long as you make those updates, you can get a sense of what you can achieve a month after each round of updates goes live.
Even if you don’t have SMART Goals for all parts of the funnel, tracking them will still help you better understand the role of organic at each stage and help you evolve your goals.
Realistic
Achievable also means realistic. Regardless of leadership expectations or the desire to set aggressive goals, you need to set reasonable expectations.
An up-and-coming company or one with very low SEO maturity may be able to set steep goals, at least initially, if they plan to implement improvements to the basic tenets and foundations of SEO.
A company already has a fairly high level of SEO maturity if they’ve optimized technical components, they are monitored frequently, and content is optimized regularly. It may only grow 7%–12% in metrics like organic traffic year over year.
So company context is key.
Before choosing specific metrics and estimating the improvement you’ll make, ask yourself:
- Can you realistically make headway on the keywords that you’re going after?
- Is there actual interest in the pages you’re trying to optimize?
- Will your optimizations actually go live?
- Do you have the resources to do the necessary SEO research and publish changes?
- Do you have the reporting set up to measure your KPI?
- Does the expected impact you intend to have on SEO match the SEO maturity level of the company or client you’re optimizing for?
Any one of these should be considered blockers when creating a SMART Goal.
Some versions of SMART use Relevant as the R.
But incorporating specific KPIs from within the conversion funnel that aligns with broader business objectives and goals – all of which are already built into this process – will ensure relevancy.
Time-bound And Timelined
Results should be demonstrable within an allotted time frame.
Establish a timeline with start and end dates to track when you expect to see your desired results based on when you begin your work.
This drives you to accomplish your goals in a set period and proactively manages leader and colleague expectations if someone asks you to speed up your efforts or asks why you haven’t achieved any of your goals sooner.
The actual optimizations you’ll want to measure, whether they are content or technical, can often be counted as soon as they go live, especially when SEO experts have direct access to edit their website.
But to adequately measure the impact of SEO efforts and prove effectiveness, either content or technical, you generally have to wait at least a month to begin measuring meaningful results.
Their impact could be visible as soon as the search engine crawls the page where the change happened.
But their impact needs at least a month to account for delays in crawling, for the change to reflect in the SERP, and for users to start engaging with content.
Especially if you have a site that is crawled less often, it may take Google an extended amount of time before it recrawls your site, allowing it to recognize the change.
Considerations Of SEO SMART Goals
Once you have considered all five of these components, carefully consider how they apply to the work you do regularly.
If you don’t find that your projects allow you to establish such goals, then perhaps it’s time to rethink your efforts or connect with your manager on expectations, available resources, and tracking options.
Framework For Creating SMART SEO Goals
To start building your own SMART goals for SEO, apply this process to each:
- Pick any of the KPIs. One at a time.
- Ensure that it aligns with broader business goals.
- Review all SMART concepts and confirm you can apply the principle to your work using the following matrix.
SEO SMART Goals Matrix
Examples Of SEO SMART Goals
Based on this framework, you might create SEO SMART goals such as:
- Move 20 optimized pages currently on Page 2 to Page 1 between 2022 Q2 and 2022 Q3.
- Increase clicks from Google by 6% MoM (May to June 2022).
- Increase organic traffic to your website by +10% by August 2022.
- Maintain a base of 20,000 organic visitors per week.
- Increase organic traffic to optimized pages by +16% within two months of the optimizations (July 2022).
- Increase organic downloads by 7% per page between new content published in ‘22 1H and new content published in 2022 2H.
- Increase revenue by 5% from organic sources for the next three months (June–Aug 2022).
Customizing Your SMART Goals For SEO
While you could adapt any of these goals to suit your SEO objectives and for any business, you’ll still have to consider the customizations needed.
When working on the R part of your SMART Goals, make sure you align the percentage increase with the extent of the effort you’ll be able to actualize.
Base the increases on original levels of impressions, organic users, and conversions per optimized page and total MSV and original placement of keywords.
If you have time, test out the impact of your optimizations for one or two months to determine the type of lift you see and aim to replicate that moving forward.
Regardless of customizations, ensure that your process follows the central tenants of SMART, as summarized in this infographic:
-
Image created by author, May 2022
Challenges When Creating SEO SMART Goals
In some cases, you may need to broaden your goal to get it approved.
While you may not have a choice in the matter, inform leadership that the numbers you estimate are based on the impact you believe you will have on the pages and keywords you are optimizing for.
Certain technical improvements, structural and speed enhancements, and optimizations on components that impact more of the site (headers, footers, pages with multiple incoming and outgoing links, etc.) may help overall findability.
But they are fairly difficult to attribute to specific actions and are especially challenging to report on.
Stick to reporting on your more trackable efforts.
Conclusion
Building goals is a challenging process.
It’s a serious task that takes careful consideration, team collaboration, and, most notably, the ability to deliver what you proposed is necessary to reach the goals.
And just because you create a goal using the SMART process doesn’t mean you’ll always be able to meet it, let alone surpass it.
But the SMART framework – when applied conscientiously, accurately, and honestly – will ultimately help you help yourself.
It will support your ability to prove your value when implementing SEO and demonstrate how both you and your endeavors benefit your company and its goals.
Featured Image: Natee K Jindakum/Shutterstock
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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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