privacy

Privacy Sandbox

Privacy Sandbox: keeping the conversation going in 2024

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The introduction of Google’s Privacy Sandbox and impending deprecation of third-party cookies are reshaping the ad tech industry – which is undergoing arguably its most significant transformation in a decade.

Two recent industry debates, hosted by The Women in Programmatic Network and IAB Tech Lab respectively, brought together key stakeholders to explore the implications of these changes. 

Here’s our key takeaways on the challenges and opportunities that lie ahead.

1. The impact on revenue and reporting

One of the most pressing concerns raised during these meetings was the potential impact on revenue and reporting. For publishers, for instance, “the yield gap between Chrome and Safari inventory is about 25%,” according to one participant. 

This suggests that while the removal of third-party cookies may not be as catastrophic as some fear, it will undoubtedly require adjustments to current monetisation strategies.

But time is of the essence. As one industry leader pointed out, “buyers should look at what’s happening to their reporting now.” Shifting to Privacy Sandbox will necessitate new ways of tracking and measuring ad performance, which could pose challenges for advertisers used to relying on third-party cookies.

2. The need for testing and engagement

The IAB urges the industry to start testing tools, emphasising the importance of being prepared, with one participant advising: “if you haven’t started testing yet, IAB Tech Lab has, alongside its [Fit Gap Analysis] report, provided a bunch of tools to help.”

The sentiment was echoed by others, who stressed the need for the industry to actively engage with the changes. As one participant noted, “it’s important to start talking about it internally within your organisations and at least form a steering group, or a collection of two or three individuals, who are focused on it.”

3. The challenge of resource allocation

Transitioning to Privacy Sandbox is not only a technical challenge, but also requires resources to manage. As one participant noted, “this is a serious time suck and an unnecessary burden in many ways.”

Smaller publishers, in particular, may struggle to allocate the necessary resources to navigate these changes. “Publishers might be looking at one or two tech heads [to oversee the transition]. And smaller publishers, who also have less resources to put on direct sales partnerships, are therefore really reliant on the open marketplace and being able to monetise inventory that they have.”

4. The role of Google

Google’s role in this transition has been a topic of much discussion. As one industry leader pointed out, the tech giant has “inserted a new layer of ad tech with literally no oversight, no responsibility, and no contracts.” This raises questions about transparency and governance in the new paradigm.

The sentiment was echoed by others, who expressed concerns about Google’s dominance in the industry. As one participant attested, “quite a lot of us are heavily reliant on Google.” 

Indeed, this reliance on Google underscores the importance of ensuring the transition to Privacy Sandbox is fair and transparent.

5. The potential for a new advertising model

Despite the challenges, some industry leaders see the opportunity for a new, more effective advertising model. As one person admitted, “maybe the way we as an industry have been running targeted ad campaigns wasn’t actually that perfect anyway. Maybe there was a huge amount of wastage. Maybe it’s not been great for the planet. Maybe there are better ways of doing this.”

This sentiment suggests a potential silver lining to such a transition. While it will undoubtedly pose challenges, it’s without doubt an opportunity for the industry to reassess current practices and develop more effective, sustainable advertising models.

Google’s response

In a further development, Google posted a riposte to the IAB Tech Lab’s Privacy Sandbox Fit Gap Analysis, acknowledging their effort while pointing out perceived inaccuracies and misunderstandings.

Google emphasised that the Privacy Sandbox aims to enhance user privacy while supporting digital advertising, noting that it’s not designed to be a direct replacement for third-party cookies or cross-site tracking. Instead, it aims to adapt and invent new approaches to meet business objectives without compromising user privacy. 

Google addressed technical assessments, clarified misconceptions, and highlighted areas where ad tech providers also need to innovate on top of the sandbox. It also welcomed further collaboration and feedback from IAB Tech Lab and the wider industry, reaffirming its commitment to phasing out third-party cookies by the second half of 2024, contingent on resolving remaining competition concerns.

The road ahead

The transition to Privacy Sandbox is a complex process that raises many questions and challenges. However, it also presents an opportunity for the industry to reassess current processes and develop more innovative ad solutions. 

As we continue to navigate this shift, it will be crucial to keep the discussion going and engage with the tools and resources available. The future of digital advertising may be uncertain, but discussions like this will provide valuable insights into the challenges and opportunities that lie ahead.

As one industry leader aptly put it, “whichever way you look at it, it’s going to be an interesting year.” 

Indeed, the journey to cookieless solutions promises to be just that.

Welcome to the data party

Where’s the data party right now?

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The difference between zero-, first-, second-, and third-party data

Data is incredibly valuable to marketers, agencies, and publishers, since it is used to power advertising models and generate revenue. And the amount of data we produce is accelerating. The global volume of data reached 64.2 zettabytes in 2020, and this is predicted to double by 2025.

However, privacy regulations, such as GDPR and CCPA, have made data an increasingly difficult resource to tap. In response, the online advertising industry has developed different classifications of data to help with the handling process. So, what do the terms zero-, first-, second-, and third-party data mean?

Four-party state

The ad tech industry uses four different classifications of data, depending on the degree of separation from the source of information.

Zero-party data

This relatively new term describes data which is willingly shared directly with the recipient, e.g., a customer who bought a sneaker submitting a survey to the brand. Arguably, this is a type of first-party data, the distinction being that it’s intentionally handed over rather than automatically collected.

Zero-party data also refers to edge computing ad solutions, where data is processed on-device rather than transmitted elsewhere online. This protects user privacy by minimising the data collected, while still allowing behavioural targeting and personalised ads, thereby circumventing legal restrictions on the amount of data allowed to be sent to the bidstream.

First-party data

Data which is gathered directly, for instance from customers, visitors, or social media followers. This includes information from email interactions and behaviours on a website or app. First-party data differs from second- or third-party data in that there is no intermediary between the supplier and the recipient of the information.

First-party data includes first-party cookies and advertising IDs which identify individual visitors, such as GAID, IDFA, and UID. Identity solutions use these IDs to track user behaviour while they interact with a website or app, in order to serve behavioural and contextual ads. However, targeted ads relying on first-party data alone can be sub-optimal, since their reach is limited to information from a single platform or site.

Second-party data

This refers to data collected from a partner who has in turn gathered it directly from visitors or customers. Although the data is supplied by another agent, the distinction made from its close third-party relative is that second-party data is sourced from a trusted partner, with whom there is a direct agreement on how the information is to be exchanged and used. The transaction takes place in a closed environment, such as a data cooperative, or a data “clean room” which provides the utmost security and privacy. Second-party data is usually used to periodically enrich first-party data to gain insights.

As with zero-party, there is some contention over the term ‘second-party data’, and the disagreement makes its definition a little woolly. In fact, when the Winterberry Group asked industry experts for the definition, responses ranged from “someone else’s first-party data”, to “there is no such thing”. After pinning down some specifics, the researchers proposed that any commercialisation or licensing of second-party data transforms its state into third-party. But this is by no means a hard-and-fast rule.

Third-party data

This pertains to any data received indirectly, via an intermediary agent who is not the original source. In ad tech, this data is usually gathered, aggregated, and packaged to be sold to companies to build advertising strategies.

Third-party data has historically been the most sought after in personalised advertising, allowing one-to-one retargeting of an online user. This can be achieved via cross-tracking cookies, where a user’s profile follows them online and is appended with data from each site they visit. Knowing so much about a user enables hyper-targeted ads to be served to them. However, third-party data now sees the most legal scrutiny due to the privacy implications of tracking users so closely across different sites, hence the phasing-out of third-party cookies.

So… where’s the party?

If all this has left you confused about the classification of data, you’re not alone. The rise of zero-party data, and the explosion of second-party data, are a result of initiatives by the industry to avoid falling foul of privacy regulations while retaining access to sources of data which make advertising models effective. In the age of big data, just make sure you know the legal requirements when handling it, so you can avoid having your party busted.

Image courtesy of Joshua Sortino

Life beyond the cookie

The third-party cookie is crumbling: what’s next for publishers?

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The third-party cookie has enabled marketers to serve targeted online ads for the last two decades, allowing websites to remain free, while ensuring content publishers are paid for their work.

But now, in response to privacy concerns and new regulations, web browsers are quickly deprecating these snippets of code. Apple blocked third-party cookies by default in Safari, while in January, Google announced a complete replacement in Chrome by 2022.

Despite this, the majority of digital advertising still relies on them. In response, we recently spoke to leading industry experts about the future of the ad tech ecosystem. We asked: how smaller publishers in particular can adapt.

Here’s what we found:

Dare to diversify

There isn’t yet a predominant replacement for third-party cookies, so we don’t know where (or when) the industry will settle. In the meantime, there’ll be a fracturing of ad tech. The key strategy for publishers during this transition phase will be to sell ad inventory in multiple different ways.

The most promising solutions avoid falling foul of both data laws and privacy-conscious tech developments:

Subscriptions. While this may be supplemental to ad revenue for smaller publishers, it’s crucial to renew focus on building a first-party subscription base. The advice from industry leaders is to offer a value exchange and make users feel like an exclusive member of a club.

Contextual intelligence. Contextual targeting serves ads based on the content of the webpage (e.g., training shoes on a fitness forum), whereas behavioural targeting uses individuals’ browsing activity. Although behavioural targeting has come to dominate the web, there’s little evidence that it improves revenues. Meanwhile, AI and machine learning have drastically improved contextual methodology, earning it the moniker ‘contextual intelligence’. Many industry leaders think it’s worth betting on this supercharged comeback.

Data clean rooms. These are a legally compliant and accurate way for publishers to continue using behavioural targeting. They can compare their first-party visitor data with those in ‘walled gardens’, e.g., Google and Facebook, to optimise ad matching. However, clean rooms can be expensive and therefore not necessarily viable for publishers with smaller datasets.

Edge Computing. Marking the age of “zero party” data, this data-conservative approach is becoming a popular way for publishers to sell remaining inventory.

Data is collected and analysed directly on the user’s device, rather than on a server, which allows publishers to serve behavioural ads while completely respecting the user’s privacy.

Test and test again

With so many options available, validating their effectiveness will be just as important. Chris Hogg, EMEA Managing Director at data management platform, Lotame, stresses that now is the time to start testing.

“Test solutions and strategies while third-party cookies are still around to compare against. Ask for proofs of concept around Safari and Firefox inventory. The fact we don’t have cookies in some of the other browsers presents a good opportunity for publishers to test out solutions and tactics today rather than later.”

Consequently, publishers will need to be far more involved when it comes to their audience data. Mattia Fosci, Founder and CEO of edge computing solution, ID Ward, urges smaller content providers to approach data analysis with both partnerships and off-the-shelf technology.

“While it may not be viable to hire a full-time data analyst, don’t underestimate the importance of analysis on your bottom line. Publishers should have more control of their audience data, but they do not need to build their own in-house solutions… Instead, publishers should work with partners that protect and enhance their relationship with their own audiences.”

Turn obstacles into opportunity

While ad tech’s brave new world is an uncertain place, one thing’s for sure – it puts publishers in a much stronger position than before. As David Reischer, Head of Product at edge computing solution, Permutive, explains, “The death of the cookie is a huge opportunity for publishers to course correct on what has happened, with their data being aggregated at scale, repacked and sold as audiences or models.”

Now, publishers can use their first-party data to bring brands even closer to audiences. By being prepared, respecting privacy, and fostering user loyalty, the entire industry stands to benefit from the change.

Head over to What’s New in Publishing to download the full report.

Image courtesy of Pezibear

Deepfake technology

Is deepfake technology a threat to society?

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You’d be excused for being sucked into the recent hype as one of the most famous actors in the world joined TikTok. The 53-year-old is seen practising his golf swings, falling over in a store, telling anecdotes and performing a magic trick with a coin. Already, the account has 11 million combined views and a following 383,000.

Only… it isn’t Tom Cruise. These videos are highly sleek deepfakes – the latest technology causing a storm across the world.

What are deepfakes and how do they work?

Deepfakes are highly realistic videos or audio recordings that look and sound like the real thing. They are constructed using a new application of machine learning called Generative Adversarial Networks (GANs) in which two deep neural nets are trained in tandem based on the way our human brain works. Both are trained with same data, but each with different a different task.

Input real video and audio data of a specific person and the software recognises patterns in speech and movement. Introduce a new element to the software such as someone else’s face and voice, and a deepfake is born. As with most AI applications, the amount of data available determines the sophistication of the end product. This explains why Tom Cruise – one of the most photographed celebrities – has become a number one deepfake target.

Potential dangers

So far, deepfakes have mostly been created or used by amateurs on social media platforms. However, their future potential to be used in a malicious manner is of real concern. Experts suggest deepfakes are an imminent threat to the erosion of democracy. In an era of fake news and clickbait, widely-circulating deepfakes, such as those of highly authoritative figures making believable yet false claims, is detrimental to reputation and public trust. Deepfakes have the power to skew our perception of reality to such an extent that genuine reality is something we plausibly deny.

Deepfake software applications such as DeepfakesWeb and Faceswap are increasingly accessible to the public with no experience needed to get started. In the wrong hands, deepfakes can easily be used to enter fake events as evidence in court tribunals, as well as posing personal security risks to data currently protected by face and voice recognition. As deepfakes mimic and transcend security barriers, they leave the door open for increased malware and cyber attacks.

There is a strong likelihood that criminals will use deepfakes in the future, for instance in phishing attacks, or in extreme cases, to blackmail individuals for ransom. With the technology being used for such basic ruses as imitating the voice of a family member or friend asking for a money transfer, deepfake technology is undoubtedly establishing smoother routes of operation for cybercriminals – at an alarming rate.

Net positive for humanity?

Using state-of-the-art technology, deepfakes hold considerable potential for everyone, regardless of who we are or how we communicate. In a 2019 campaign for Malaria No More UK, deepfake technology simulated David Beckham delivering an anti-malaria message in nine different languages. Here, the positive global impact of deepfake technology was evident whilst enabling influencer marketing to reach the next level.

Moving away from media, deepfakes are also on track to deliver revolutionary benefits within the healthcare sector by aiding the development of new disease treatment. Researchers have already trained algorithms to create ‘fake’ MRI brain scans that are just as accurate in detecting brain tumours as algorithms trained using real medical images, but without using real patient data.

The potential benefits of deepfakes to society mark exciting tech prospects, equipping us with the ability to impact at scale and speed. However, as the tech becomes more widely available, so too does the opportunity for misuse. We need to be questioning its morality and safety within our society now, before it’s too late.

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