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.

Screenshot from Google, December 2023

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.

Screenshot from Google, December 2023

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.

Screenshot from Google, December 2023

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

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.

Screenshot from Perplexity, December 2023

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

Screenshot from Perplexity Labs, December 2023

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.

Screenshot from Perplexity Labs, December 2023

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.

Screenshot from Poe, December 2023

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.

Screenshot from Poe, December 2023

Compare this to the response offered by Google Bard.

Screenshot from Google Bard, December 2023

3. Vercel

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

Screenshot from Vercel, December 2023

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

Screenshot from Vercel, December 2023

Like many LLMs, it does occasionally hallucinate.

Screenshot from Vercel, December 2023

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.”

Screenshot from Replicate, December 2023

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

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.

Screenshot from X, December 2023

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.

Screenshot from X, December 2023

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.

Screenshot from OpenAI, December 2023

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.

Screenshot from Google Reviews, December 2023

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

Screenshot from Product Hunt, December 2023

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:

Screenshot from Yelp, December 2023

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.”

Screenshot from Google Reviews, December 2023

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.

Screenshots from Glassdoor, December 2023

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

Screenshot from Google, December 2023

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).

Screenshot from Google SGE, December 2023

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