Google, the parent company of YouTube, responded to a report that suggested YouTube advertisers are sourcing data from children viewing videos on the platform.
On Aug. 18, a day after the report surfaced, Google posted a blog reinstating its “strict privacy standards around made for kids content,” which is content marked on YouTube created for children.
The BigTech giant said it has focused on creating kid-specific products like YouTube Kids and supervised accounts.
“We’ve invested a great deal of time and resources to protect kids on our platforms, especially when it comes to the ads they see…”
It said it launched a restriction worldwide for personalized ads and age-sensitive ad categories for its users under 18. Additionally, the post clarified that it does not allow third-party trackers on ads that appear on kids’ content.
Nonetheless, on Aug. 17, data analysis and transparency platform Adalytics published a 206-page report alleging that advertisers on YouTube could be “inadvertently harvesting data from millions of children.”
Some of the claims made in the report include cookies indicating a “breakdown” of privacy and YouTube creating an “undisclosed persistent, immutable unique identifier” that gets transmitted to servers even on made-for-kids videos with no clarity on why it’s collecting it.
Related: Universal Music and Google in talks over deal to combat AI deep fakes: Report
An article from The New York Times also reported on the research from Adalytics, specifically highlighting an instance where an adult-targeted ad from a Canadian bank was shown to a viewer on a video label for kids.
Adalytics reported that since that viewer clicked on the ad, tracking software from Google, Meta and Microsoft, along with companies, was tagged on the user’s browser.
Concerns around Google’s privacy and data collection standards have been raised in exact months, as the company has been releasing more products with artificial intelligence (AI) incorporated.
Less than a month later, a report was published that analyzed AI-powered extensions for Google’s internet browser Chrome, which said two-thirds could endanger user security.
Most recently, on Aug. 15, Google introduced a series of enhancements for its search engine incorporating advanced generative AI features.
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The end is near for Google Discovery ads.
You can now sign up for access to Google Ads’ Demand Gen, the new campaign type announced at Google Marketing Live in May.
Once you’re in the beta, your Discovery campaigns will be automatically upgraded to Demand Gen.
All Discovery campaigns should be “upgraded” to Demand Gen by early 2024.
What is Demand Gen beta? “Demand Gen campaigns combine image + video ads in one place and can be used to drive conversions, site visits and actions like sign-up and add-to-cart across YouTube, Discover and Gmail,” Google Ads Liaison Ginny Marvin explained in a thread on X, formerly known as Twitter.
In addition to YouTube Home, Search and Watch Next, Discover, and Gmail, Demand Gen campaigns work across:
RIP, Discovery ads. Google introduced Discovery ads in 2019.
Why we care. Being able to see how your creative will look across Demand Gen placements is great for advertisers, especially brands with strict compliance and/or brand teams, as PPC expert and SMX speaker Sam Tomlinson points out in an X thread full of reactions and takeaways.
Who is eligible for an upgrade? Right now, all you need is an active Discovery campaign. Google Ads will open Demand Gen campaigns to everyone in October 2023.
How to upgrade. Sign up for the Demand Gen beta via this short form.
New features. Once you sign up for the Demand Gen beta, you can explore these new features:
What Google is saying. Demand Gen was “built to help advertisers who buy on social platforms find and convert consumers with immersive, relevant, and visual creatives that grab attention and spur action in the right moment,” a Google spokesperson said:
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Timeline. Here's what's coming next:
Google's announcement. Get ready to upgrade your Discovery ads to Demand Gen
ITHACA, N.Y. – A Cornell University-led research team has discovered that the algorithm behind Google Ads charged significantly more to deliver online ads to Spanish-speaking people in California about the benefits of SNAP, formerly known as food stamps.
“SNAP is a really important resource to get right,” said Allison Koenecke, lead author of the study and assistant professor of information science. “When faced with an algorithm that has disparate impact, our research asks, how do you pick a strategy to interact with the algorithm to equitably recruit SNAP applicants?”
Californians can apply for SNAP benefits using a website called GetCalFresh, which is developed and managed by Code for America, a civic tech nonprofit that builds digital tools and services for community leaders and governments. Code for America primarily recruits GetCalFresh applicants through Google Ads – for example, spending roughly $400 daily to reach anyone from San Diego County who punches key words and phrases like “how to apply for food stamps” into Google.
However, despite GetCalFresh being offered in multiple languages, Spanish-speakers were filling out proportionally fewer applications than English-speakers. In San Diego County, 23% of families living below the poverty line speak Spanish as their primary language, and yet just 7% had applied for SNAP via GetCalFresh, researchers said.
Koenecke and her collaborators discovered one possible reason: the default, dollar-stretching algorithm behind Google Ads was working too efficiently and disregarding Spanish-speaking people in the process.
When Google Ads is configured to garner the most SNAP enrollments per dollar, it ends up delivering fewer ads to prospective Spanish-speaking applicants because such ads cost more than those for English speakers, the team found. At the time, for every $1 spent on Google Ads to “convert” an English-speaking applicant into a SNAP benefits holder, it cost $3.80 to convert a Spanish-speaking person – nearly four times more. Another bidding option on the Google Ads platform cost 1.4 times more to reach Spanish-speakers versus English-speakers.
Koenecke and her collaborators can’t definitively explain the difference, since Google Ads is a black box – a proprietary machine-learning tool outside of public review. It could be attributed to any number of factors, like supply and demand or a bug in the system, she said.
For GetCalFresh, the research findings pose an important ethical question regarding how to spend its limited online advertising budget: Should they reach as many Californians as cheaply as possible, even if that means fewer Spanish-speaking applicants, or advertise more to Spanish-speakers, even if that yields fewer total applicants?
Trade-offs such as these are at the heart of Koenecke’s research into fairness and algorithmic systems, which are increasingly being used to help with decision-making in areas with real consequences, like health care, banking and child services. But without additional scrutiny, algorithms – including a seemingly harmless one behind an advertising platform – can exacerbate inequality or produce results that run counter to what people actually want or need, she said.
As a result of the team’s findings, Code for America adjusted its online advertising strategy to directly target more Spanish-speaking prospective applicants.
“It’s important for the field and the public to have productive dialogues about the kinds of metrics we should be using in these algorithmic systems,” she said. “The communities most impacted by the algorithms should be given more power in the decision-making process.”
This research was partly funded by the National Science Foundation and Stanford University.
For additional information, see this Cornell Chronicle story.
Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.
You won’t find the longest list of features with Google Domains; however, you will find that Google Domains does a few things very well. It makes the process of finding an available domain name easy and the process of registering your domain of choice simple. Its interface is clean and free of ads, pop-ups and upsells (all of which are all too common among domain registrars). All domains come with privacy protection, two-factor authentication and the option to easily set up business email through Google Workspace.
It’s quick and easy to register a domain with Google Domains thanks to its intuitive and straightforward search function. It has over 300 domain extensions available, offering a great deal of options for those who are not limiting their search to a .com extension. For those who want a bit of help choosing the right domain name, Google Domains’ search function shows insights for each domain. For example, it might say that it’s a bit long or that it’s more likely to be misspelled or misunderstood.
Privacy protection comes standard, so there is no need to worry about adding it in the registration process. DNS hosting also comes standard, which enables your domain to be found on the internet.
Though Google Domains does not offer email hosting, it does offer email hosting through Google’s premium email service, Google Workspace. What’s different about Google Workspace from Gmail is that—unlike Gmail, which is free and uses the gmail domain (e.g., firstname.lastname@example.org)—Google Workspace enables you to create a professional email address that uses your custom domain name (e.g., email@example.com).
There are three main Google Workspace plans as well as an enterprise plan. Plans start at $6 per month per user for a business email address, 30GB of storage and the ability to host meetings through Google’s video conferencing software for businesses, Google Meet, with up to 100 participants. All plans require a one-year commitment. However, billing is on a monthly cycle, so you pay monthly rather than paying for the entire year upfront.
Google Workspace Plans and Pricing
Google is renowned for being a pioneer in built-in enhanced internet security. When it comes to security features for users, it uniquely offers two-factor authentication for added protection, as well as one-click DNSSEC, which helps to protect your domain against common threats such as DNS spoofing and cache poison attacks. Domain lock is automatically enabled on all new domains, as well as domain permissions which enable users to add users to the domain for management purposes.
To protect your personal information, all Google Domains also come with privacy protection, which means that the information you use to register the domain is not publicly accessible in the WHOIS database.
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In the event that you would like to update your details or have any queries regarding this privacy statement please contact equimedia by any method set out at the bottom of this page.
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According to Cointelegraph, Google, the parent company of YouTube, replied to a report that suggested YouTube advertisers are transferring data from children viewing videos on the platform.
Sources revealed that on August 18, 2023, a day after the report surfaced, Google mentioned in a blog stating that “strict privacy standards around made for kids content,” are the content which is expected to be marked on YouTube created for children.
“We’ve invested a great deal of time and resources to protect kids on our platforms, especially when it comes to the ads they see,” Cointelegraph added.
It is expected that Google has launched a restriction worldwide for personalised ads and age-sensitive advertisement categories for its users under the age of 18 years. Furthermore, the post also explained that it will not allow third-party trackers on ads that appear on kids’ content, Cointelegraph concluded.
(With insights from Cointelegraph)
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According to a study by Aviva, in 2020 the average UK household had 10.3 internet-connected devices. This amounted to a 26% increase on a similar study in 2017, which revealed UK homes had an average of 8.2 connected devices. Based on an average UK household of 2.4 people, this works out at around 4.3 connected devices per person, many of which will be devices capable of distributing media such as smartphones, laptops, desktops, connected TVs, connected radios, tablets and e-readers.
This presents some challenges for digital marketers trying to understand the impact their display, audio and video ad campaigns are having on website traffic, let alone low-funnel conversions like sales or leads. After all, despite what you might have heard, most people do not spend all their time on their phone, and many people’s internet browsing habits have now evolved to the point where they think nothing of switching between devices for different tasks.
It’s easy to imagine a scenario where someone sees an ad on their connected TV, researches the advertised brand on their phone and clicks a search ad, then navigates directly to the site on their laptop to complete a purchase. This kind of behaviour is common and may even be something you yourself have done. But from an attributional perspective it is highly complicated: here is a customer journey with three touchpoints spread across three different devices, with no direct way of connecting the ad clicks and impressions to each other, or the final purchase.
In website analytics platforms like GA4, this kind of cross-device behavior can manifest as a general underestimation of the impact of prospecting activity on conversions, and an overestimation of the impact of lower-funnel activity such as search ads. In the example above, for instance, the purchase would probably never have happened if the person had not been served an ad on their connected TV to begin with. But GA4 would have no idea that CTV impression had even happened. At best, GA4 would supply all the credit for the conversion to the paid search ad the user clicked on their phone. At worst, GA4 would assume the conversion on the user’s laptop was from a direct website visit, and not attribute the conversion to any advertising activity at all.
These kinds of reporting biases aren’t just minor irritants for pedantic ad ops managers like me. Marketers of all kinds have grown used to using data to support tactical decisions, and for many advertisers the reports generated by analytics platforms inform where budget is allocated. This means that any measurement bias which is not accounted for could lead to a cycle of worse-than-expected marketing performance.
Despite the fact it is often undervalued by website analytics, when it’s done right cross-channel prospecting and brand awareness advertising can have a big impact on conversions. In 2017, 31% of sales in the US involved touchpoints across multiple channels, and that figure is likely to have increased since. For brick-and-mortar retailers cross-channel advertising is even more important, with omni-channel shoppers averaging a 30% greater lifetime value than single-channel.
Market-making media advertising may not drive conversions with the same immediacy of paid search ads, but over the longer term it assists in brand recall and customer retention and leads to higher volumes of website traffic and in-store footfall which, with an optimised sales journey, can lead to more conversions. Put simply, there is a reason Coca Cola pays for TV ads in premium slots over the Christmas period, and it’s not because everyone who sees the ad is immediately rushing out into the wintery night to grab an ice-cold cola for their stocking. As a company, there is no way for Coca Cola to deterministically link impressions of these TV ads to specific sales, but the overall benefits to their brand and bottom line are enough to justify the expense.
Google provides a couple of solutions for marketers looking to more accurately attribute cross-device conversion journeys. GA4 has a data-driven attribution model and provides a ‘conversion paths’ report based on the gclid and utm parameter data of website visitors. For advertisers who are ad serving, Campaign Manager 360 offers cross-device conversion reports. But both GA4 and CM360 are reliant on Google’s statistical attribution modelling, which itself is dependent on logged-in Google account data. When it comes to something like connected TV or radio, or even mobile display advertising, marketers should be asking themselves how many people are likely to be logged-in to a Google account on those kinds of devices, and how this might be biasing Google’s modelling in favour of search ads?
As things stand, the best way of accurately attributing cross-device conversional data is almost certainly to develop a bespoke model that takes data points from multiple sources and combines them to produce a more nuanced picture of the influence of different channels on conversions over a long period. If this sounds like a daunting task, that’s probably because it is one! Luckily equimedia have a wealth of experience and expertise in this area, so if you would like to discover more about cross-channel media advertising and attribution, reach out to us now to find out how we can help.