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Google’s FLoC poses a threat to identity solutions and advertisers



Google’s FLoC poses a threat to identity solutions and advertisers

“Ultimately, this is Big Tech crushing the little guys in the industry.” Jon Waterman, CEO of advertising marketplace

“We’re going to have a scattered market of policies and regulations across countries and states – that’s already happening. You’re going to have a scatter of different browsers, not all saying the same things. That’s a reality we should all just be prepared for and have our eyes open to.” Michael Zacharski, CEO of Engine Technology and digital marketplace EMX Digital.

“We’re beholden to what the walled gardens – Google, Apple, Facebook – are going to decide to do. Part of being able to combat that is this whole third-party data story. They can’t take it away if you own it.” Sam Ngo, Director, Product Marketing at BlueConic, the CDP.

Three players in the advertising and data spaces reacting to the profound uncertainty in the advertising space which has been growing since the significance of a brief statement issued by Google on March 3 has begun to sink in.

Google set to become another walled garden

Identity and data vendors like The Trade Desk, LiveRamp, Neustar and others have spent months scrambling to devise alternative identifiers which will allow advertisers to re-target effectively once third-party cookies vanish from the Chrome eco-system by 2022. These solutions essentially work by associating behavioral signals with consensually obtained first-party identifiers — hashed emails or phone numbers. Probably the best-known is Unified ID 2.0, developed by The Trade Desk but now under the stewardship of open source alliance

Find out more about and Unified ID 2.0

But did Google’s announcement that “we will not build alternate identifiers to track individuals as they browse across the web, nor will we use them in our products” (emphasis added) undermine this whole approach?

Waterman fears the worst. “Google are saying, if you want to use The Trade Desk, great, use the Trade Desk, but you’re going to be limited to the publishers that they have access to, and that have a unique identifier like an email address or a phone number.” Advertising on Google will be restricted to advertising to Google’s own FLoC audiences; cohorts grouped by behavior at the browser level.

“They’re rebranded the concept of a walled garden as their Privacy Sandbox. It’s kind of a more public-friendly term for their walled garden” added’s VP, Business Intelligence, Justin Nakamura.

“They’re creating this mess for their own gain,” said Waterman.

Zacharski was prepared to entertain several possibilities. “I read it as, Google’s going to be building cohort audiences for you. One interpretation is that Google is becoming the arbiter of who is in which audience, with or without visibility into the recipe of how they make up that audience. One interpretation is that, through FLoC, Google is becoming the ultimate data broker for the space. That makes a difference for how a lot of companies have been thinking about building audiences, and being able to customize audiences and have differentiation of audiences.”

Alternatively, he pondered, they might be saying: “If you’re using first-party it won’t be available through FLoC, but it will be available outside as long as there’s one-to-one consent. That’s the big debate, whether Prebid single sign-on and hashed email or phone number matching is or is not going to be blocked by Chrome.  There’s not great clarity about that yet.”

Worst case scenario, Google becomes a version of Facebook, building its own audiences to sell to advertisers, and offering little or no visibility into how it’s done. Best case scenario, Google will do that for sure, but won’t outright prohibit the deployment of first-party data-based audiences.

“You have varying degrees of certainty, uncertainty, doubt – because the reality is that although there are positions and frameworks out there…there’s still a lot that’s unknown.”

And then there are questions the consumer will ask, said Zacharski: “Which of my data signals are being used to have me qualify for this audience, and by the way can I opt out of being in a cohort?”

Read more about Google’s FLoC alternative here.

The advantages of first-party data

Whatever Google’s position ends up being, there’s little doubt that brands will double down on first-party data — and also little doubt that that won’t fix everything.

“For us, it’s not about a one-to-one replacement for third-party cookies, but really about how we help companies continue to build first-party data assets,” said Ngo. “The point getting rid of third-party cookies was always to be able to put customers at the center.”

Building trust and loyalty can’t be done, said Ngo, if brands are using unreliable, low quality data. Third-party cookies were not a good solution to start with. “There was a lot of jumping on the bandwagon: oh, we can advertise to a segment of customers we never had access to before. Now it’s time to rethink that strategy.”

Blueconic supports its clients by helping them collect and manage first-party data. “We work with publishers where Blueconic powers their paywall. They’re not necessarily asking for a subscription right away, but after the second time a user visits the site, they’ll ask them to sign up for a newsletter. During COVID, some publishers decided to take down the paywall completely for COVID coverage, because that’s the type of relationship they want to have with their customer.”

When it comes to agile collection of third-party data, one size does not fit all. “One of our customers, Belgian Cycling Factory, instead of asking for email addresses, what they actually ask for is a bike registration number because that’s a unique identifier – but at the same time, they’re offering them extended warranties; so it’s about creating that value exchange,” explained Ngo.

“Blueconic is the technology that enables them to be able to design that experience, and then on the back-end helps them manage all that first-party data, ensuring that it stays high quality, and that we’re merging profiles as we recognize that someone is the same person – whether it’s across brands or within one website.”

Ngo views first-party data as a way of stepping off the Google treadmill. “If you haven’t been building your first-party data, it’s getting to the point where it’s too late to do it. It’s more important than ever, or you’re perpetually in this chase of, what’s Google going to do next?”

And the disadvantages

“For marketers, the notion of I have my first-party data, maybe I’ll be able to activate that –that’s great, but maybe that’s not the best type of data to acquire new customers,” said Zacharski. And that’s if you get buy-in from consumers in the first place.

“We still don’t know how comfortable consumers will feel putting their personal information into these systems. Maybe they’ll feel great about it, maybe it’ll be mixed. As an industry I don’t know if we’ve done enough work to build that bridge to the consumer so they really understand what they’re agreeing or not agreeing to,” said Zacharski.

Even the aggregation of huge volumes of first-party data by enterprises (think Procter &Gamble or Starbucks) doesn’t solve that problem. “With P&G, they have a lot of brands and a lot of people coming to those websites,” said Waterman, “but those are the only places at which they can capture that audience. If they’re already on their site, they’re already probably interested in buying something relevant. The value add that they had before – or they have now but won’t have in the future – is being able to re-target the user that came to their brand and buy that impression on a display of their video ad when someone is on, say, ESPN. That’s what they’re going to lose.”

Then there are the unanswered questions about what FLoC will allow. “It’s a matter of how compatible [first-party audiences] will be with the mix of technologies that will be available. You may have the regulatory consent, but does the plumbing in each environment, despite your verifiable legal standing, allow you actually to connect with those audiences?”

Engine Technology and are preparing for the future in different ways, the former by focusing on CTV, the latter by relying on intent data.

“You have a new class of advertising with CTV,” explained Zacharski, “where the big screen in the living room is now the device you’re consuming content through. It’s like an app in its technical format, but it’s also a consented format.”

That’s part of Engine’s strategy, but it’s also committed to providing multi-channel opportunities to advertisers; it’s participating in industry-wide discussions on the future of addressability; and finally, said Zacharski, “we’re going to watch and respond.”

The multi-channel offering is based around Engine’s Device Graph+ solution. This combines data from Engine’s own SSP with data from Automatic Content Recognition (ACR) providers and attribution metrics from a third party. “We’re not targeting individual consumers, we’re getting to the household level,” said Zacharski. By associating devices with a household, Engine can provide options like advertise on CTV, re-target on mobile.

Zacharksi will say no more than that this will offer clients cookie-less targeting capabilities for the next 18 to 24 months.

A search space outside Google and Bing

“Three years ago, four years ago,” said Waterman, “we decided to focus purely on intent and contextual targeting. We use a level of audience targeting, like geography, but we focus primarily on intent for this reason: there’s no way to capture audience targeting at any scale with just Unified ID 2.0.”

This approach relies on the presence of’s technology across a very large number of publisher websites, and in particular their search engines. “We define intent as a keyword search,” said Waterman. “We sell search intent outside of Google and Bing. We go out there into the marketplace, which is a very fragmented space without Google and Bing, and we capture that audience to drive to our clients, our advertisers.”

This aligns well with content marketing – articles or advertorials written with the express purpose of getting readers to reveal their intent or interest through their clicks. “We’re going to capture that and drive that user towards our particular advertiser who’s selling that particular product.” In effect, it’s analogous to a B2B funnel strategy, but scaled.

“We market ourselves purposefully as an extension outside of Google and Bing,” said Waterman. “We sell diversification of your ad spend, and that is lately resonating more with clients and advertisers, because they don’t want to give all the spend to one or two companies. They don’t want to give all their data to one or two companies. They want to keep it open.”

Bigger and bigger monsters

“The politicians have no understanding of what this is essentially doing; it’s creating bigger and bigger monsters,” said Waterman. We all love Google and we all love Amazon and we all use Facebook, but crushing the other competition that’s our there – that’s small, but keeps these guys honest – that’s the fear that I have. This is going to kill companies for sure, and unless you adapt and pivot very quickly, more of the wallet share is going to go to the big guys.”

Waterman continued: “What Google has effectively done is build its own walled garden. You go to Facebook, it’s a walled garden, you go to Amazon, it’s walled garden. You go to, it’s a walled garden; but now, everywhere Google sits within the eco-system, all the tentacles they have out there, is all part of that walled garden.”

Zacharksi is more tentative. “We’re not in the final inning. There’s going to be more ideation and more collaboration to come. There’s  multiple storylines happening as we watch this movie. The storylines are going to start to interconnect.”

This article first appeared on MarTech Today

Kim Davis is the Editorial Director of MarTech Today. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space.

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Exploring the Evolution of Language Translation: A Comparative Analysis of AI Chatbots and Google Translate




A Comparative Analysis of AI Chatbots and Google Translate

According to an article on PCMag, while Google Translate makes translating sentences into over 100 languages easy, regular users acknowledge that there’s still room for improvement.

In theory, large language models (LLMs) such as ChatGPT are expected to bring about a new era in language translation. These models consume vast amounts of text-based training data and real-time feedback from users worldwide, enabling them to quickly learn to generate coherent, human-like sentences in a wide range of languages.

However, despite the anticipation that ChatGPT would revolutionize translation, previous experiences have shown that such expectations are often inaccurate, posing challenges for translation accuracy. To put these claims to the test, PCMag conducted a blind test, asking fluent speakers of eight non-English languages to evaluate the translation results from various AI services.

The test compared ChatGPT (both the free and paid versions) to Google Translate, as well as to other competing chatbots such as Microsoft Copilot and Google Gemini. The evaluation involved comparing the translation quality for two test paragraphs across different languages, including Polish, French, Korean, Spanish, Arabic, Tagalog, and Amharic.

In the first test conducted in June 2023, participants consistently favored AI chatbots over Google Translate. ChatGPT, Google Bard (now Gemini), and Microsoft Bing outperformed Google Translate, with ChatGPT receiving the highest praise. ChatGPT demonstrated superior performance in converting colloquialisms, while Google Translate often provided literal translations that lacked cultural nuance.

For instance, ChatGPT accurately translated colloquial expressions like “blow off steam,” whereas Google Translate produced more literal translations that failed to resonate across cultures. Participants appreciated ChatGPT’s ability to maintain consistent levels of formality and its consideration of gender options in translations.

The success of AI chatbots like ChatGPT can be attributed to reinforcement learning with human feedback (RLHF), which allows these models to learn from human preferences and produce culturally appropriate translations, particularly for non-native speakers. However, it’s essential to note that while AI chatbots outperformed Google Translate, they still had limitations and occasional inaccuracies.

In a subsequent test, PCMag evaluated different versions of ChatGPT, including the free and paid versions, as well as language-specific AI agents from OpenAI’s GPTStore. The paid version of ChatGPT, known as ChatGPT Plus, consistently delivered the best translations across various languages. However, Google Translate also showed improvement, performing surprisingly well compared to previous tests.

Overall, while ChatGPT Plus emerged as the preferred choice for translation, Google Translate demonstrated notable improvement, challenging the notion that AI chatbots are always superior to traditional translation tools.


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Google Implements Stricter Guidelines for Mass Email Senders to Gmail Users



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Beginning in April, Gmail senders bombarding users with unwanted mass emails will encounter a surge in message rejections unless they comply with the freshly minted Gmail email sender protocols, Google cautions.

Fresh Guidelines for Dispatching Mass Emails to Gmail Inboxes In an elucidative piece featured on Forbes, it was highlighted that novel regulations are being ushered in to shield Gmail users from the deluge of unsolicited mass emails. Initially, there were reports surfacing about certain marketers receiving error notifications pertaining to messages dispatched to Gmail accounts. Nonetheless, a Google representative clarified that these specific errors, denoted as 550-5.7.56, weren’t novel but rather stemmed from existing authentication prerequisites.

Moreover, Google has verified that commencing from April, they will initiate “the rejection of a portion of non-compliant email traffic, progressively escalating the rejection rate over time.” Google elaborates that, for instance, if 75% of the traffic adheres to the new email sender authentication criteria, then a portion of the remaining non-conforming 25% will face rejection. The exact proportion remains undisclosed. Google does assert that the implementation of the new regulations will be executed in a “step-by-step fashion.”

This cautious and methodical strategy seems to have already kicked off, with transient errors affecting a “fraction of their non-compliant email traffic” coming into play this month. Additionally, Google stipulates that bulk senders will be granted until June 1 to integrate “one-click unsubscribe” in all commercial or promotional correspondence.

Exclusively Personal Gmail Accounts Subject to Rejection These alterations exclusively affect bulk emails dispatched to personal Gmail accounts. Entities sending out mass emails, specifically those transmitting a minimum of 5,000 messages daily to Gmail accounts, will be mandated to authenticate outgoing emails and “refrain from dispatching unsolicited emails.” The 5,000 message threshold is tabulated based on emails transmitted from the same principal domain, irrespective of the employment of subdomains. Once the threshold is met, the domain is categorized as a permanent bulk sender.

These guidelines do not extend to communications directed at Google Workspace accounts, although all senders, including those utilizing Google Workspace, are required to adhere to the updated criteria.

Augmented Security and Enhanced Oversight for Gmail Users A Google spokesperson emphasized that these requisites are being rolled out to “fortify sender-side security and augment user control over inbox contents even further.” For the recipient, this translates to heightened trust in the authenticity of the email sender, thus mitigating the risk of falling prey to phishing attempts, a tactic frequently exploited by malevolent entities capitalizing on authentication vulnerabilities. “If anything,” the spokesperson concludes, “meeting these stipulations should facilitate senders in reaching their intended recipients more efficiently, with reduced risks of spoofing and hijacking by malicious actors.”

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Google’s Next-Gen AI Chatbot, Gemini, Faces Delays: What to Expect When It Finally Launches




Google AI Chatbot Gemini

In an unexpected turn of events, Google has chosen to postpone the much-anticipated debut of its revolutionary generative AI model, Gemini. Initially poised to make waves this week, the unveiling has now been rescheduled for early next year, specifically in January.

Gemini is set to redefine the landscape of conversational AI, representing Google’s most potent endeavor in this domain to date. Positioned as a multimodal AI chatbot, Gemini boasts the capability to process diverse data types. This includes a unique proficiency in comprehending and generating text, images, and various content formats, even going so far as to create an entire website based on a combination of sketches and written descriptions.

Originally, Google had planned an elaborate series of launch events spanning California, New York, and Washington. Regrettably, these events have been canceled due to concerns about Gemini’s responsiveness to non-English prompts. According to anonymous sources cited by The Information, Google’s Chief Executive, Sundar Pichai, personally decided to postpone the launch, acknowledging the importance of global support as a key feature of Gemini’s capabilities.

Gemini is expected to surpass the renowned ChatGPT, powered by OpenAI’s GPT-4 model, and preliminary private tests have shown promising results. Fueled by significantly enhanced computing power, Gemini has outperformed GPT-4, particularly in FLOPS (Floating Point Operations Per Second), owing to its access to a multitude of high-end AI accelerators through the Google Cloud platform.

SemiAnalysis, a research firm affiliated with Substack Inc., expressed in an August blog post that Gemini appears poised to “blow OpenAI’s model out of the water.” The extensive compute power at Google’s disposal has evidently contributed to Gemini’s superior performance.

Google’s Vice President and Manager of Bard and Google Assistant, Sissie Hsiao, offered insights into Gemini’s capabilities, citing examples like generating novel images in response to specific requests, such as illustrating the steps to ice a three-layer cake.

While Google’s current generative AI offering, Bard, has showcased noteworthy accomplishments, it has struggled to achieve the same level of consumer awareness as ChatGPT. Gemini, with its unparalleled capabilities, is expected to be a game-changer, demonstrating impressive multimodal functionalities never seen before.

During the initial announcement at Google’s I/O developer conference in May, the company emphasized Gemini’s multimodal prowess and its developer-friendly nature. An application programming interface (API) is under development, allowing developers to seamlessly integrate Gemini into third-party applications.

As the world awaits the delayed unveiling of Gemini, the stakes are high, with Google aiming to revolutionize the AI landscape and solidify its position as a leader in generative artificial intelligence. The postponed launch only adds to the anticipation surrounding Gemini’s eventual debut in the coming year.

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