Canadian news and journalism outlets have entered into a fierce battle with Google and Meta over the recently enacted Bill C-18, also known as the Online News Act. This legislation, passed by the Canadian government on June 22, 2023, aims to support the Canadian journalism ecosystem by establishing a tax that "digital news intermediaries" such as Google and Meta must pay to the content owners they link to.

In a familiar pattern observed in similar laws like Australia's News Media and Digital Platforms Mandatory Bargaining Code, Meta and Google have retaliated by removing links from their platforms including Instagram, Facebook, and Google Search. Unfortunately, this response undermines the very essence of the bill and is expected to inflict financial harm on Canadian journalism. While Google and Meta argue that they only seek a fair market share for their services, publishers contend that this is unjustified since Google and Meta generate billions in advertising revenue while journalists struggle to make ends meet.
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The advertising industry responds with a call for sustainable, ethical & socially responsible advertising practices

The dynamics at play here are further complicated by the fact that media agencies and brands, responsible for a significant portion of news media revenues, control advertising spend. This advertising spend is the primary source of revenue for Google & Meta, which famously represent 80% of online advertising revenue in the country.

Traditionally, Canadian brands and their agencies have allocated the majority of their advertising budgets to these two companies. However, there is a growing trend, driven by recent legislation and broader shifts in advertising, to directly invest media dollars with local publishers. Many agencies and brands have committed to supporting Canadian publishers in light of this impasse. For example, the A2C in Quebec has already taken steps to incentivize collaboration between agencies, brands, and local publishers. Some agencies view this issue as a matter of ethics and social responsibility. Prominent figures in the agency world, like Sarah Thompson, President of Dentsu Media and Brian Cuddy, SVP Responsible Media Solutions at Cossette have been vocal advocates for supporting Canadian news publishers. In response to the announcement from Facebook that all Canadian news will be removed from their platforms within weeks Sarah took to her LinkedIn to share support for local news “We are at a moment of time where action is required to support local owned media, which is more than news.”

In addition to developments within the Canadian ecosystem, there are emerging trends in how marketers allocate their paid media budgets. Advertising executives are increasingly interested in investing more heavily in contextual advertising and leveraging publishers' first-party data for better targeting. There is also heightened scrutiny around programmatic channels, which lack transparency in terms of media ROI. Consequently, there is a growing preference for direct buying. Moreover, measurement strategies are shifting away from the digital attribution focus of the past decade towards more traditional methods, such as brand lift analysis, media mix modeling, third-party audience measurement, and the use of consumer research data and studies.

In essence, these trends indicate a change in the attitudes and choices of CMOs and agency leaders. They are actively supporting a more open and equitable internet through their advertising investments.
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While the dust settles, open internet publishers can prepare for the future

Similar to other legislations, it is probable that Google and Meta will have to pay millions of dollars directly to media owners to avoid taxation. However, the process of finalizing these deals will require time, leaving publishers to suffer from decreased traffic and increased competition with these tech giants for ad revenue. In the long run, there is a possibility that Google and Meta might modify their platforms by completely removing links. The economic landscape has evolved for these companies, and it is not unreasonable to consider their initial link removal as a test to assess long-term effects on user engagement and potential revenue. 

To minimize risk, publishers can take proactive measures to future-proof their businesses. 

Here are some recommendations:

• Build a direct sales model that is data-driven - By hiring commercial professionals with a strong background in data and educating your sales teams on how your organization leverages data to develop advertising products, you can make a significant impact. Google and Meta have achieved tremendous success by adopting a data-centric approach to advertising sales, and marketers will seek partners who possess similar capabilities. The indirect revenue generated from large platforms and programmatic partners will likely remain at risk as marketers shift their strategies. Publishers who can effectively execute direct sales efforts will reap the benefits of these changes.

• Invest in a data collaboration platform - Google and Meta's value proposition lies in empowering advertisers to leverage their own audience data for precise targeting and robust measurement. Recent advancements in data clean room and collaboration technologies have enabled publishers to directly provide these capabilities while safeguarding user privacy and ensuring scalability. Data clean rooms and collaboration solutions now play a pivotal role in publisher's' ability to offer innovative solutions to advertising partners and drive ad revenue growth

• Work with technology partners that help you manage your data better, faster, and more efficiently - Having partners who possess a comprehensive understanding of audience data is crucial. Developing a robust data strategy can be intricate, encompassing diverse approaches like identity management, real-time audience building, and ad activation system integrations. For publishers, collaborating with forward-thinking partners is vital, as they can provide a versatile system that extends beyond advertising to content personalization and marketing applications.

• Don't forget your biggest advantage, your content! - News publishers are the ultimate storytellers, directly connecting with their audiences. With this unique position, you not only gain invaluable insights into their preferences but, armed with the right tools, also deepen your understanding of them. This fundamental knowledge becomes vital as more publishers creatively leverage data to amplify co-branded content, sponsorships, audience creation, and other aspects of advertising. By employing these strategies, you can draw in more advertisers and bolster your revenues.

Canadian publishers are witnessing promising support from agencies, brands, and the public, indicating a positive trajectory. Coupled with the growth of future-proof data collaboration technologies, this presents remarkable opportunities for news media publishers to revolutionize their advertising revenue generation. The Online News Act, a legislation that foreshadows the future of news consumption, holds great significance not only for Canadians, but also for Americans, as similar bills have reached Congress. In the midst of these advancements, we find ourselves at a critical juncture for the open internet, journalism, and democracy as a whole. Numerous Canadian publishers have already partnered with Optable to safeguard their advertising businesses, and for those who haven't, we are prepared to provide our assistance!

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To work the way they should, data clean rooms need to bring a fluid, real-time, embeddable infrastructure to data collaboration. And at the heart of such an offering, there needs to be an API that allows any client to deploy the data clean room approach across any inventory, any type of audience data and any third-party cloud provider.

In this way, any third-party application or platform should be able to benefit from a data clean room by embedding its API for secure, privacy-preserving data collaboration. 

This in turn enables a complete digital media workflow via API, and taking Optable’s service as an example, it looks like this: 

1. Collecting data at the edge. The API is wrapped in our SDKs for iOS, Android and web to enable this, but it can be done for virtually any other platform.
2. Creating audiences from data onboarded in the platform, whether it’s from traits or available identifiers.
3. Enriching a device graph by feeding identifier associations and user attributes.
4. Creating a data clean room and inviting a partner to match with an audience.
5. Executing a match with the partner by using our open-source matching library and command-line utility that implements various PSI protocols. 
6. Ultimately, all of this is done in order to enable analytics and straight-line activation. Both of these functions are available via API as well. 

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One of the best applications of a data clean room API is in combination with a customer data platform (CDP). An API can be used to properly leverage audience data housed in a CDP, making this data actionable for activation and measurement with third parties. 

Another good example involves walled garden data and inventory. Whether it’s for CTV, audio or traditional web formats, an API can be used to effectively drive advertiser performance anchored in real customer data. 

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Ultimately, the API is here to make it easy to leverage the data clean room approach in any third party platform or application. 

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During lockdown, with Covid raging outside, those with the opportunity to do so turned to their gardens, treating them as sanctuaries, lavishing them with care and attention and cultivating what they could. 

And at about the same time, the ongoing eradication of public identifiers was inspiring a comparable new strategy for publishers. Edged out of the third-party-data-driven world they knew - but which had never really played to their strengths - they busied themselves creating their own walled gardens, their own content fortresses.

What have they grown? More personal data, more insights and a much deeper connection to their audiences - a connection anchored in consent. Publishers’ first-party data is private, relevant, hugely detailed and engaging, and so, like anything built with care and attention, these sanctuaries have a very real value to those they invite in.
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Your data meets mine in a data clean room

First-party publisher data is manna for brands, and especially those who have been carefully tending their own data gardens. Google has found that brands using their own first-party data for key marketing functions achieved up to 2.9X revenue uplift and 1.5X increase in cost savings.

When brands work with publishers to mix their data and build relevant segments and publisher cohorts, the effect is equally compelling: The Guardian last year reported a 65% higher than average brand lift for brands using its first-party data. Wherever you look, the effect of first-party publisher data is emphatic.

However, at every step, old habits need to be questioned. For publishers, the best way to amplify the value of that data has always been to connect it to brands, but for all the obvious reasons, that can’t happen over public programmatic pipes anymore. 

Instead, the most efficient, effective, privacy-safe way for publishers to make their private data available for analytics and activation is through a new, proper, data clean room-enabled infrastructure. 

The proportion of publisher inventory that transits through clean rooms - what we call clean room media - is growing, as brands and publishers realise in unison that their old channels are drying up and new ones are needed.
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We’ve been here before - only different

In fact, the shift is uncannily reminiscent of the old programmatic revolution - the very architecture the new privacy-conscious world is now working to replace. Just like clean room media, programmatic started small and ended up huge, as the scale of the opportunity - and the opportunity cost of ignoring it - became apparent. 

But clean room media is many leaps ahead of the old programmatic free-for-all, in that it allows publishers to easily monetize their newly available audience data in a safe, privacy-preserving way. And it gives brands bespoke data - better than anything they might have found in the old marketplace. 

So brands get what they need: more precision and performance through exclusively available audience data, while leveraging the data they’ve been carefully collecting and enriching in their own CDPs.

Publishers, meanwhile, get the reward for the deep, private, inimitable relationships they have developed with their users.

And, crucially, in this new ecosystem, consumers get more control and more privacy protection than ever before.
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Exponential growth of clean room media

One publisher that uses Optable has seen its share of clean room media increase six-fold over the past few months, and it’s expected to continue growing exponentially.

So, just because programmatic is yesterday’s technology, does not mean that the technology of tomorrow shouldn’t adopt its trajectory.

Before outstaying their welcome, third-party cookies gave us the very worthwhile expectation of openness, interoperability and ease of use - all attributes of clean room media.

In the same way, tomorrow’s data solutions need to echo the revolutionary, problem-solving qualities that made programmatic the success it was - only with the addition of privacy, exclusivity, a better deal for brands and publishers and a renegotiated consumer contract.

As clean room media continues to grow as a category, it’s exciting to see more and more publishers and brands adopt this new way of transacting.

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In today's data-driven world, concerns about privacy and data security have never been more critical. k-Anonymity is a privacy concept and technique that plays a pivotal role in safeguarding sensitive data. Let’s explore what k-anonymity is and how it‘s used to protect personal information.

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What is k-Anonymity?

k-Anonymity is a privacy model designed to protect the identities of individuals when their data is being shared, published, or analyzed. It ensures that data cannot be linked to a specific person by making it indistinguishable from the data of at least 'k-1' other individuals. In simpler terms, k-anonymity obscures personal information within a crowd, making it impossible to identify a particular individual. 

The 'k' in k-anonymity represents the minimum number of similar individuals (or the “anonymity set”) within the dataset that an individual's data must blend with to guarantee their privacy. For example, if k is set to 5, the data must be indistinguishable from at least four other people's data.

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How Does k-Anonymity Work?

To implement k-anonymity, data must be generalized to make it less identifiable, while ensuring that each data point is identical to a minimum of ‘k-1’ other entries. This is commonly done through two methods:

1. Generalization: Data attributes are generalized to broader, less specific categories. For example, an individual's age may be generalized from their precise age to an age range, like 25-34.
2. Suppression: Certain attributes may be entirely removed or suppressed if they are considered too revealing. For instance, exact dates of birth or home addresses may be suppressed to protect individual identities.

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How are Marketers Using k-anonymity?

Online retailers use k-anonymity to protect customer data while analyzing purchase histories and preferences to enhance their services and recommendations. 

For example, individual users can be associated with data cohorts based on their interests on their mobile device. An advertiser can then target individuals in specific cohorts. This way, the advertiser does not learn any personally identifiable information (PII) and only learns that a specific individual belongs to certain cohorts. And as long as the cohorts are k-anonymous, they protect users from re-identification, especially for large values of k.

A drawback to using k-anonymity is that sometimes revealing just the cohort a user belongs to can leak sensitive information about a user. This is true, especially when the cohorts are based on sensitive topics such as race, religion, sexual orientation, etc. A simple solution to this problem is to use predefined and publicly visible cohort categories, such as in Google Topics.

In any case, cohorts can still be combined or correlated and used to re-identify users across multiple sites. That said, k-anonymity is often combined with other privacy protections to further reduce the probability of re-identification.

In an era where data is the new gold, ensuring its privacy and security has never been more critical. Secure computation, is a powerful branch of cryptography, allowing companies to perform computations on sensitive data without revealing the actual information being processed. In this blog, we’ll explore what secure computation is and how it’s used to protect consumer data.

What is Secure Computation?

Secure computation is a cryptographic technique that enables multiple parties to jointly compute a function over their individual inputs while keeping those inputs private. This is known as "encryption in use" because the underlying data remains encrypted while it is being processed on remote servers or in the cloud.

The primary goal of secure computation is to ensure the confidentiality, integrity, and privacy of data throughout the computation process. It accomplishes this without relying on a trusted third party, making it particularly valuable in scenarios where data sharing and privacy are paramount. This means that two or more parties can collaborate on data analysis or computations without exposing their sensitive data to one another.

How are Media Companies and Brands Using Secure Computation to Collaborate?

Secure computation is applied in a range of scenarios where privacy and data security are paramount. Naturally, secure computation is a great fit for data sharing and collaboration among publishers and advertisers.

Both publishers and advertisers can benefit from a type of secure computation called Private Set Intersection (PSI) protocol. It allows two or more parties to compute the intersection of their private datasets without revealing any information about the records not in the intersection. Optable, for instance, provides an open-source matching utility that allows partners of Optable customers to securely match their first-party data sets with them using a PSI protocol.

How does secure computation work?

Secure computation can be implemented in two main ways: 1) via pure cryptography (using Fully Homomorphic Encryption (FHE) and Secure Multi-Party Computation (MPC)) or 2) through secure hardware (using Trusted Execution Environments (TEEs).

Fully Homomorphic Encryption

FHE is an incredibly powerful tool for protecting data privacy in the digital age. It enables analytics to be performed on encrypted data without ever having to decrypt it. The ad tech industry can certainly benefit from full-scale analytics without the risk of exposing personally identifiable information (PII).

While FHE has the potential to revolutionize the advertising ecosystem, it is unfortunately quite computationally intensive and limited in its current capabilities. Therefore it is not yet ready for widespread adoption. There is ongoing research to make FHE more efficient and functional in the future.

Secure Multi-Party Computation

MPC is a form of secure computation that uses a cryptographic protocol to enable two or more businesses with private data to perform a joint computation while keeping their individual inputs private. Each entity only learns what can be inferred from the computation result.

Often, the secure computation part is outsourced to two helper servers. Before data leaves a user's device, it is encrypted to both helper servers, which decrypt it partially and perform computation on the partially encrypted data. Neither server is ever able to see the original user data.

MPC protocols provide a high level of security but come with a tradeoff. They require sophisticated cryptographic operations which incur higher computation and communication costs. This makes this technology tailored for specific tasks, which can get very expensive.

How Does Optable Use MPC?

In the past year, Optable has been a leading contributor to the IAB Tech Lab’s Open Private Join and Activation (OPJA) that enables interoperable privacy safe ad activation based on PII data. At the heart of OPJA is a secure match using a PSI protocol that allows advertisers and publishers to match their PII data. One of the ways to perform this match is using MPC — the respective clean room vendors act as the MPC helper servers, which jointly compute the overlap without ever learning the identifiers not in the overlap.

In an age where data privacy is a growing concern, secure computation emerges as a vital technology that plays an important role helping companies comply with data protection regulations while still fostering innovation and cooperation among business partners.

When we launched the company earlier this year, in the middle of a global pandemic, our thesis was fairly simple:

• As privacy becomes a feature across the board, both tech platform changes and increased regulation will make a huge impact on ad tech
  

• This will create a movement where publishers and advertisers (as well as a slew of intermediaries) will have to actively ask users to share some data on themselves and get a permission to use it
  

• The infrastructure that enabled data-driven advertising to function was built on cookies and IFAs, and it’s about to disappear
  

• As a result, this data-sharing infrastructure is moving underground where collaboration will continue, but data will be shared using secure, privacy-preserving protocols
  

This all will result in a gradual onset of confusion and chaos, but ultimately, eventually, the ecosystem will be better off. The mess created by the programmatic revolution will be replaced by less wasteful, more ethical, more secure, new ways of dealing with ads.

It starts with three core functions that have to be satisfied by a new generation of customer data management technologies:

First, we need to deal with the identity crisis, with third-party cookies and IFAs slowly crumbling. We need a way to collect data that is respectful of the user and backed by consent, yet still uses identity data at the core. Without third-party cookies and IFAs, this will lead to a translation layer: from personal profiles stored by the publisher on the user to an addressable cohort across various touch-points (open web as much as mobile, CTV and audio). In addition to using local storage for data collection, there is also an opportunity to make use of first-party cookies, just like it was in the good ol’ days.

Second, although we do ingest data from CDPs and DMPs, assembling audiences and preparing them for anonymized activation using existing ad tech infrastructure is part of the the new way of working with audience data.  This activation can happen through ad servers, ad exchanges or other content personalization technologies.

And third, we need better ways to transact based on audience data.  When it comes to advertising, the value of data is amplified when it transits between partners. Cookie and IFA-based transaction models created a lot of trust issues which actually prevented great use of this data. The new generation of data management technologies will be decentralized, where partners will run their individual instances of the platform, and use secure multiparty computation protocols to collaborate.  This is a bit complicated at first, but ultimately this layer will enable the fundamental fabric of how ads are targeted and measured.

That, in essence, is what we do.

A mere 6 months after launching the company, we are starting to roll out our product to customers. It’s quite difficult to describe what the product IS, but we feel that calling it a Data Connectivity Platform is the best way to describe the core value that we’re bringing.

Having pre-seeded the company ourselves, we are also starting a fundraising process for our seed round. Our team counts 9 people now, and we are very much excited to grow it and accelerate our growth.

The crisp February air of Toronto welcomed a select group of media & advertising thought leaders to Optable's exclusive summit. The agenda promised deep dives into data strategy, privacy's impact, and navigating the ever-evolving media landscape. And it definitely delivered.

Data Collaboration Takes Center Stage

The opening panel, "How Publishers & Advertisers Are Using Data to Build Better Ad Campaigns in the Age of Privacy," kicked things off with a bang. Data collaboration emerged as the undeniable hero, bridging the gap in a fragmented ecosystem. Panelists from La Presse, The Globe & Mail, and Advance powered by Loblaw discussed their shared journey: adapting data strategies, wielding identity solutions, all while dancing around the ever-changing privacy regulations. The panel was moderating by Optable's own Ioana Tirtirau, Head of Customer Success, who helped the crowd to glean actionable insights that could be implemented within their own businesses.

One key takeaway? It's not just about the tech. "The future of advertising lies in finding the sweet spot where data insights combine to create a better experience for the audience and ultimately create business growth. Data is the interface with which were able to create better advertising partnerships." said one publisher exec. The audience couldn't have agreed more, recognizing the need for meaningful campaigns that respect customer privacy and provide real insights into customers’ wants and needs.

Privacy: The Driving Force (and Opportunity)

Deloitte's fireside chat shifted gears, focusing on the elephant in the room – privacy. Experts dissected the seismic shifts caused by regulations and platform moves, highlighting not just the challenges but also the opportunities. "CCPA, GDPR, Law 25, cookie deprecation – it's all about building trust," emphasized a Deloitte speaker. "And trust generates loyalty & engagement, which is the real gold in this game."

Beyond Trends: The Human-Centric Shift

The summit wasn't just about buzzwords and tech. It was about understanding that data and privacy are inherently human-centric. At its core, advertising is about connecting with people, and in the privacy age, that means that collaboration is key.

The cocktail hour wasn't just a networking opportunity; it was a testament to the energy and ideas bubbling up from the room. From Optable's own data experts to seasoned ad veterans, everyone recognized that the future isn't pre-programmed – it's in the hands of innovative minds who can harness data, respect privacy, and ultimately, rethink and rearchitect the media & advertising ecosystem to be more impactful for audiences and more sustainable for businesses.

Key Takeaways:

• Data collaboration is growing rapidly, with the major cloud ecosystems acting as stewards.
• Privacy regulations create challenges, but also unexpected opportunities.
• Third party cookies are officially on their way out and will create a forcing function to re-think our ecosystem.

Optable's 'State of Data Collaboration' in Toronto wasn't just a glimpse into the future; it was a blueprint for navigating it. Armed with actionable insights and a renewed focus on the human element, data & advertising professionals left the venue empowered to redefine success in the privacy-first era.

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The need to safeguard sensitive data and ensure the confidentiality of transactions has never been more critical. The Trusted Execution Environment (TEE) emerges as a pivotal technology in the demand for increased data privacy. In this blog, we will delve into the world of TEE, understand what it is, and explore its applications as a privacy-enhancing technology.

What is a Trusted Execution Environment?

TEE is a secure and isolated area within a computer or mobile device's central processing unit (CPU). It’s designed to execute code and processes in a highly protected environment, ensuring that sensitive data remains secure and isolated from all other software in the system. It achieves this level of security via special hardware that keeps data encrypted while in use in main memory. This ensures that any software or user even with full privilege only sees encrypted data at any point in time.

How Does TEE Work?

Using special hardware, TEEs encrypt all data that exits to the main memory. And decrypt back any data returning before processing, allowing the code and analytics to operate on plaintext data. This means that TEE can scale very well compared to other pure cryptographic secure computation approaches.

TEEs also offer a useful feature called remote attestation. This means remote clients can establish trust on the TEE by verifying the integrity of the code and data loaded in the TEE and establish a secure connection with it.

How Can Media Companies Benefit From TEEs?

TEEs are an attractive option for media companies who want to safely scale their data operations in a secure environment. TEEs offer the following benefits:

• Tamper-Resistance: The hardware-based security of TEE provides tamper-resistant execution of code.
• Secure Communication: Remote attestation provides a way to establish trust between TEEs and remote entities, enabling secure communication.
• User Trust: TEE builds trust among users, assuring them that their data and transactions are protected.

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Now, let’s look at a real-world example of data collaboration using a TEE. In our last blog post, we saw that one way to perform the secure matching in the IAB’s Open Private Join & Activation proposal is using an MPC protocol. Another way to perform this secure matching is using a TEE. With TEE, only one helper server is involved. First, the advertiser and the publisher establish the trust of the TEE via remote attestation. Then, they -each forward their encrypted PII data to the TEE server which decrypts them and performs the match on plaintext data.

TEEs come with their own privacy risks. They are vulnerable to side-channel attacks, such as memory access pattern attacks, which can be exploited to reveal information about the underlying data. Adding side-channel protections can help counter these attacks, but significantly increases the computational overhead. Fortunately, despite this TEEs scale very well.

In an industry facing ongoing scrutiny over data privacy concerns, TEEs are becoming a standard. This PET technology will continue to evolve and we expect to see it playing an increasingly vital role in data collaboration. 

Optable Core Values

We value diversity and inclusion and believe that the sum of different cultures, opinions and beliefs creates a stronger team that will deliver great results. A group of people with the desire to succeed. All pulling together in the same direction. Knowing that every single person has your back. With respect, trust, and the knowledge that any single one of our teammates is capable of taking the lead at the right time. With this attitude we all win. And when we don’t, we try again.  Because we learn quickly and don’t give up. 

Empathy

Showing empathy towards each other is probably the best way to get the most out of any given team. Every day brings new challenges but also new opportunities to reconsider how we see and value our colleagues. Empathy also helps us focus on listening. It forces us to reflect on our actions and words and it brings us closer together.

Trust

Building trust in our relationships is our promise. We are all about transparency in communication and actions. We are honest, we own our role, decisions, actions, and their consequences. We strive for an environment where we can rely on each other.  Trust is earned. And we never, ever make fake promises.

Innovation

Challenging one’s own thinking and having the mindset to strive for continuous improvement is what innovation means to us. We encourage curiosity, challenge assumptions, take calculated risks,  and anticipate changes. Failure is welcomed. It’s what allows us to learn and generate new ideas while enabling us to embrace changes and drive faster towards success.

Enthusiasm

Promoting excellence in the workplace is what enthusiastic employees do. It’s infectious, and an example for those around them to follow. It’s the core understanding that energy comes from energy so we recognize and reward those brave enough to smile in the face of challenge. We play to win as a team and lift everyone’s spirits to bring joy, satisfaction, and results.

Bias for Action

Taking initiative and embracing change help create a successful business. We don’t spend too much time overthinking decisions. We prefer acting on possible solutions instead of waiting for the perfect one. If it needs to get done, we identify solutions and start building. We are not perfectionists, but we work relentlessly to improve.