What Do We Actually Mean by “Cookieless”?

There’s a perception that first-party data is just login demographic data, but it’s so much more than that.

First-party data is all sorts of things, such as contextual and behavioral data. It also includes site navigation patterns and single session page views, time spent on the page, frequency and recency, not to mention multi-session interest topics, and ad placement analytics.

It’s rich data publishers can use because it’s more privacy-forward than third-party cookies. It’s more than contextual, as mentioned before, but it can also scale across all channels (i.e., tablet, CTV, mobile app, desktop) and browsers.

Lastly, first-party data can offer much more accuracy in terms of targeting than third-party cookies. And with them deprecating, now is the time to shift the focus to first-party data. 

Some issues with third-party cookies regarding targeting tactics include:

• Fragmented media buying based on various solutions available across browsers and platforms.
• Campaign reach may be impacted given the likelihood of overlap in targeting strategy due to competition solutions.

The solution would be to consider first-party data, including the publisher’s proprietary IDs, analytical data, and audience segmentation, to run a more successful campaign. Tools powering first-party data matching will become valuable assets to campaign buyers. And lastly, publishers can define audiences based on first-party data to help shape first-party execution.

How Will Third-Party Cookie Deprecation Impact the Market?

Google Chrome has a ⅔ market share, so the impact will be monumental once they deprecate third-party cookies in 2024. The four most significant effects it’ll have are:

– Identity and Ad Targeting: One of the main reasons privacy regulations have come to the forefront is the way third-party cookies collect user data and transfer it to third parties. A proposed alternative is the Privacy Sandbox based on cohort analysis rather than individual user data. There are also universal IDs that can significantly expand the reach of advertising campaigns. This multi-channel and cross-platform offers more advanced and secure identifying and targeting features than third-party cookies. By using first-party data solutions, consumers can have better control over their privacy preferences. Not to mention contextual targeting, which emphasizes content and keywords over-relying on personal information.

– Ad Fraud: Many believe doing away with third-party cookies will increase ad fraud, which is simply not the case. Ad fraud is already rampant and underreported. For instance, bots can dump and get new cookies like users can when they clear cookies from their browsers. Bots can also pretend to be any audience segment an advertiser wants, hurting advertisers by paying for higher CPMs. They can also trick search and cart abandonment retargeting algorithms and way more. So with these practices and more being lost with third-party cookies, less money will be lost to fraud.

– Cost Savings and Better Outcomes: Advertisers can personalize their customer experience better, use CRM retargeting, make the most of first-party data, and use contextual advertising. 

3 Must-Haves in Your Cookieless Arsenal:

Among other considerations, exploring and using tools from companies that have established a presence for the target audience is a great way to fill in the gaps while considering first-party data. It’s also worth taking the time to consider building partnerships to match data and stay privacy-forward. 

As a result, consider these three must-haves for when third-party cookies finally deprecate: 

Data collection optimization — Publishers define a data strategy and decide what data is valuable for targeting purposes.

Industry or first-party identity solutions — Publishers with a significant amount of login information and the right to use it should focus on adopting an industry identity solution or developing a first-party identity solution, enhancing user privacy controls. 

Platform participation preparation — All publishers should prepare to participate in platform solutions, like Google’s Privacy Sandbox. They should work with their partners to understand and prepare for the changes. 

If you want to learn more about addressability and how to unleash your first-party data, check out our Privacy and Identity Prepper Playbook for Publishers.

The post Armed and Cookieless: 3 Must-Haves for Publishers in a First-Party Data World appeared first on TripleLift.

Preparing for Privacy Regulation

Over the years, we’ve seen numerous regional and country-specific data privacy laws and regulations come into play. From the GDPR to the Colorado Privacy Act (CPA) and everything in between, publishers have continually had to shift strategies and optimize to stay compliant. And just when you think you’ve got your data processing activities fully compliant, along comes more potential legislation to flip everyone over their head, such as American Data Privacy and Protection Act. With the turn of the calendar year and increasing regulatory pressure, now is the perfect time for publishers to audit how they collect and use first-party data. They’ll need privacy-forward first-party data strategies and identity solutions to help with the changing considerations around addressability.  Match rates with ID solutions will likely be low and largely replicate third-party cookie dynamics. Some solutions will enable advertisers to use an ID from one publisher to buy from a different publisher. In contrast, others will be truly first-party and used solely to sell the inventory of the publisher with whom the user shared their data. Publishers should look to new and innovative first-party data solutions to protect their data while offering scale to advertisers in both direct and programmatic channels.

First-Party Data Strategies

Forget about Google and whether they will deprecate third-party cookies. Today, over 50% of all web ad requests come from browser environments that already don’t support third-party cookies, including Safari, Firefox, Webview, and Chrome (when consumers use Incognito mode with third-party cookies disabled or other advanced privacy settings).

There are increasing choices publishers can make to improve the addressability of their inventory using their own first-party data.  However, choosing a path can be daunting, with many options that aren’t exactly clear. As the trend toward first-party data becomes the norm, publishers must focus on protecting their data while maximizing near-term value and investing in innovative new solutions that don’t rely on identifiers or fingerprinting.

However, when it comes to first-party data, simply staying on trend isn’t a long-term solution. Many first-party data solutions will work now but have degraded performance as the large platforms increasingly limit user agents, IP addresses, and email addresses to create identifiers.

Any solution that relies on these data points will face increasingly degraded performance over the coming years. Further, many of these solutions re-create the dynamics of third-party cookies by enabling one publisher’s data to buy audiences on another publisher.  

To fully take advantage of the first-party trend, publishers must invest in the right solutions quickly. As an alternative to identifiers, innovative first-party data solutions will be released in 2023 that increase addressability and enable scale for advertisers but don’t leak data and don’t rely on user identification. This could mean stable revenue growth in the coming years despite platform changes and new regulations for publishers who invest in these solutions now. 

Curated Deals Services

According to data from eMarketer, programmatic digital display spend on deals (a.k.a. PMPs) has surpassed open exchange spend. That trend will continue as publishers seek to protect their data and maximize the value of their inventory.

To jump on this bandwagon, publishers can work with partners to help them curate their inventory into deals and sell those deals to advertisers. While curating deals has long been a valuable strategy for publishers that sell direct to advertisers, there is also significant value in working with partners who include publisher inventory in highly curated multi-publisher deals. Partners can then help sell those deals to advertisers.

While not a new concept, curated deals are gaining momentum in the market. Advertisers can target the exact inventory and audiences they want to reach, and publishers can participate, with little additional overhead, to drive more revenue.

2023 will be the year publishers embrace curated deals. Publishers will opt to partner with curation services that can work with first-party publisher data in all browser environments and survive significant platform and regulatory changes.  When executed correctly, this process will ensure publisher data remains protected and increase revenue, especially in browser environments that don’t support third-party cookies.

Measurability

Getting a user’s attention is stiff competition. From push notifications to auto-play videos and plenty of algorithms in play to give users what they want, publishers are doing all they can to keep the focus on their page while balancing the quality of the experience.

Publishers need the metrics to back up all the investments spent on new strategies to drive results. We see impression counts slowly fade into irrelevance and be replaced by attention metrics.

Currently, there’s no one standard for attention metrics. Namely because it depends on how and what content is being consumed. For instance, you could consider active time in view to see the amount of time a piece of content or an ad is viewable or how the user interacts with an ad by scroll rate or depth.

Advertisers and publishers who leverage attention metrics to create better content and user experiences will remain a continuing trend in 2023. Check out more AdTech trends for advertisers.

The post Trends for Publishers to Look for in 2023 appeared first on TripleLift.

Centralized Privacy UX

Transparency expectations will continue to drive the need for privacy-centric user experiences. This is an opportunity for companies to create a dialogue with their customers and better engage them about the kinds of advertising they want.

By turning the conversation about ads and privacy into valuable features for consumers (instead of simply solving for privacy legislation), companies can create closer relationships with their customers, better earn their trust and increase overall brand engagement.

This involves companies reviewing all aspects of the privacy UX — notices, cookie policies, consent management, and data subject rights requests handling — to ensure high levels of transparency, easy to use controls and to highlight the value exchange of ads that are tailored to users’ interests funding free to access digital services. At the same time, they can capture consumer preferences related to product preferences, product discovery, and ads from the company.

This year, Gartner predicts that 30% of consumer-facing organizations will offer a self-service transparency portal to provide preference and consent management. Creating this kind of consumer-centric experience will provide opportunities for consumers to better understand the value of the relationship they create with a company by providing their data. 

AI on the Rise

Specifically, machine learning and AI will be necessary to extend campaign reach on the open web when third-party cookies are gone for good. This will likely impact more than half of all ad requests today, including those from Safari, Firefox, and web view, even before Google removes third-party cookies from Chrome.

While consumers provide significant amounts of information to brands they love, consumers usually give less information to publishers. As a result, ID solutions and 1:1 ID matches with publishers will have limited scale. Machine learning will enable advertisers to expand their reach to the audiences they want to connect with, even when an ID match is unavailable.

Ad Personalization

Simply put, ads are more effective when relevant to the consumer. In a digital ecosystem reliant on first-party data, new solutions to create effective ads that reach the right audience at the right time will be a primary focus next year and in years to come.

Google delayed the end of third-party cookies again. Initially planned for Q2 2022, then deferred to 2023, and shelved until 2024, it will push the industry into the first-party data era. First-party data from publishers and advertisers will replace data from third-party cookies and vendors.  

As such, the digital marketing ecosystem must agree on and implement a portfolio of solutions based on first-party infrastructure and transparent consent mechanisms for capturing and sharing data. 

SSPs and DSPs must innovate with new technology to preserve first-party data privacy while leveraging digital advertising. It’s increasingly clear that there are new ways of targeting digital ads that better protect individuals’ privacy rights. The future will focus on private matching, cohorts, and aggregations to enable targeted digital advertising and measurement while protecting advertisers, publishers, and consumers’ data. SSPs and DSPs capable of securely processing bid requests with first-party data will emerge triumphant and command a more significant market share. 

Convergence of SSP and DSP

New ways to execute ad campaigns without third-party cookies or mobile identifiers will emerge through the convergence of the SSP and DSP roles.  However, it’s likely to be more of a shift in how publishers and advertisers engage with the AdTech ecosystem than disintermediation. SSPs and DSPs can play to their strengths to continue delivering value to the market, and publishers and advertisers should be open to working with new partners to achieve their goals.

Notably, SSPs maintain the most vital relationships with publishers and provide the most significant scaled footprint for advertisers to show ads across multiple publishers. DSPs maintain the most robust relationships with advertisers and support their advertising goals with tooling and process support. This isn’t likely to change, but data system changes will require advertisers to work more closely with SSPs and publishers to work more closely with DSPs to execute digital advertising.

Ultimately, use cases once fulfilled by a DSP will also be fulfilled by SSPs and vice versa. Very soon, to target first-party data-enabled inventory, advertisers will need to work directly with SSPs who have the most access to publisher first-party data and are best positioned to facilitate the match between advertiser and publisher data sets when IDs are not available. Publishers will find value in working directly with DSPs to create unique targeting solutions based on ID matches between advertiser and publisher data sets. Advertisers need to recognize the strengths of SSPs and DSPs and prepare to work with them in new ways to facilitate digital ad delivery based on a shifting data landscape.  Advertisers should be focused on getting to know the SSPs in the space and evaluating the solutions they offer to achieve their advertising goals.

The Explosion of OTT and CTVs

In recent years, we’ve seen an explosion in OTT and CTV. With more and more streaming services hitting the market, it’s no surprise that CTV has reached almost 200 million users, diverting consumer attention from linear television. Streaming is garnering the attention of content-hungry viewers. It’s becoming an attractive place for brands to allocate their marketing dollars, specifically programmatic budgets. According to PwC, programmatic TV advertising will make up one-third of all TV ad revenue worldwide by the close of 2022.

Of course, while all these are exciting, we still have to remember the context we’re going into in 2023. 

Ending Thoughts — Don’t Spend Less, Spend Smart

A potential recession looms, various macroeconomics are at play, and plenty of cost-cutting will likely be implemented in marketing budgets. However, by prioritizing and knowing what trends to look out for, you can make the most of your marketing efforts in 2023.

Check out 2023 trends for publishers.

The post AdTech Trends for 2023 — What Advertisers Need to Know appeared first on TripleLift.

The Addressability Spectrum, in Brief

Cookieless addressability is the ability to identify individual consumers as they move across online domains so they can be targeted with advertising. There are viable solutions available such as first-party data. TripleLift has previously discussed the value of looking at addressability as a spectrum by seeing addressability as a range of approaches: 

The cohort/group approach (less individual addressability). Based on grouping consumers into cohorts, the cohort/group approach is an industry-wide collaborative effort. Espoused by Google’s Privacy Sandbox, this approach is evaluating and iterating on group/cohort proposals on a browser-by-browser basis that’ll solve some advertisers’ targeting use cases. This browser-level approach can significantly impact advertisers, who may need to set up and run separate browser-based campaigns that solve for Privacy Sandbox.

The first-party data approach (mid-level individual addressability). As discussed more fully below, the first-party data approach lies in the middle of the addressability spectrum. This approach helps publishers package their data, making a wealth of first-party information available to advertisers.

The cross-domain identifiers approach (greater individual addressability). The cross-domain identified approach is based on:

• deterministic data, such as device data
• more threatened probabilistic identifiers, such as IP addresses

The approach is typically offered by ID solution partners who match advertisers’ email data with publishers’ login data. This provides more individual addressability on the addressability spectrum —but at times, this may mean limited scale, among other issues.

Leaning into the Portfolio Approach

Most advertisers agree that choosing one approach on its own won’t work—not even the cross-domain identifier approach, even though it lends itself to use cases that marketers are already familiar with. Instead, a portfolio, or multi-modal, approach is the better option for de-risking the future.

Dealing with addressability is about more than choosing the right approach, though. Advertisers need to target multiple data types to find matches with inventory across the addressability spectrum. And they should consider each of the different approaches. But first-party data bring invaluable insights to the ad-purchasing process. Because of this, it represents the key to maximizing addressability across the system.

The Spotlight on First-Party Data

The writing’s on the wall: Third-party cookies are going, and they’re not coming back. So what does this mean for advertisers? 

A portfolio approach to addressability covers all the bases: 

• integration with leading cross-domain ID solutions to take advantage of valuable cross-domain data whenever that data exists
• leveraging the wealth of first-party data that publishers have already accumulated and will continue to collect
• continuing to solve for the Privacy Sandbox by testing and challenging its proposals 

But on a closer examination, it’s clear that first-party data deserves to be advertisers’ main focus.

More than Just Login Data

There’s a common misconception among advertisers that first-party data consists of login information only. The reality is that publishers collect many different types of first-party data, including: 

• login data
• contextual data, which can provide a certain degree of information about what users are reading
• other publisher-owned data (for example, site analytics, survey data, customer support/feedback data, and purchase histories).

Higher Value than Third-party Data

Data collected by third-party cookies have historically been inaccurate because the third-party cookie is a method of data collection prone to errors. It’s difficult, for example, to know the specific origins of third-party data or how up-to-date or complete that data is.

However, the value of first-party data lies in how it’s collected. Publishers obtain this data directly from the source: their users. This means they know how, where, and when specific data was collected, something third-party data sets can’t provide.

Look to Where the Opportunity Lies

With only 10% of users estimated to be cross-domain identified, cross-domain solutions are predicted to represent a minority of the data available. This means most of the opportunity lies in choosing a mix of first-party data and cohort targeting — tactics represented by the rest of the addressability spectrum. And it’s an opportunity for advertisers to take advantage of now.

Advertisers need to take action now, and first-party data is the approach that allows them to do just this. Environments where third-party cookies are non-existent or limited — for example, Safari, Firefox, or even unidentified users in Chrome — are fertile testing grounds for first-party data today. Advertisers don’t need to wait until 2024 for total third-party cookie deprecation to ensure they’re set up for success. 

For Advertisers, Wait-and-See Isn’t a Viable Option

There’s an overall industry need for viable, compliant solutions. But to succeed, these solutions must:

• Allow for consumer privacy and controls
• Reflect industry-wide adoption and scale
• Do more than merely try to replace third-party cookies 

First-party data is poised to be a powerful tool because of the rich insights it holds.  Advertisers can’t afford to take a wait-and-see approach when they can take action now. They can do this now by working with their supply partners to test first-party-based campaigns in third-party cookie-constrained environments. 

The post Advertisers’ Approaches to Cookieless Addressability appeared first on TripleLift.

Why Cross-Domain ID Solutions Don’t Stack Up: HEM

HEM is a cross-domain ID solution that uses hashed emails, a form of deterministic data—data supplied directly by users—to create identifiers. It works by matching publisher-collected emails with advertiser-collected emails to create an anonymized ID. This anonymized ID can be applied to some of the same use cases as third-party cookies.

Why HEM Is Trending as a Cookiefree Alternative

Add in the benefits of HEM, and there’s good reason why many in the industry see HEM as a viable successor to the third-party cookie:

• Deterministic data is generally high value and accurate because consumers supply it directly.
• Because it’s based on deterministic data, HEM is considered more privacy-compliant since consent is implied.
• The nature of email use means that a user’s email rarely changes and can be tied to that specific user. 
• And finally, HEM enables tracking across domains without being reliant on cookies. 

But while these elements combine to present HEM as an elegant solution in a world without third-party cookies, on closer examination, there are clear reasons why it’s not as smart as it seems. 

HEM’s Major Weakness

The root of HEM’s potential efficacy lies in its ability to track individuals across domains. But this ability is also its Achilles’ heel: tracking users across domains impacts consumer privacy, and there’s little doubt that privacy will continue to be a regulatory priority. 

This means web browsers and platforms like Apple and Google actively prioritize privacy protection. A current example is Apple’s iCloud+ Hide My Email, which enables individuals to generate unique, random email addresses that can be used just like their personal email. These emails automatically forward to the individual’s email, where they can be replied to like a regular email, all while keeping the personal email private. 

This aspect alone derails any long-term potential of HEM to replace third-party cookies. But HEM also faces other difficulties:

Collection challenges. Emails are often costly and difficult to collect. For example, even those publishers doing well see only around 10-15% of traffic logging in. And while brands have fewer problems collecting emails, the emails they collect are typically from existing customers rather than non-purchasing website visitors.

Difficulty of scaling. Even if a publisher were to have a phenomenal 80% login rate, each hashed email from that publisher could only be matched with a hashed email from one advertiser. But to scale, that hashed email needs to be associated with several different domains across the web. 

And other scaling obstacles exist. For example, wide adoption is required to scale, but the adoption rate is roughly 10%. Add to this the lack of a standardized approach to email collection, resulting in a higher potential of the same emails not matching, and the scaling problem becomes evident. 

These issues point to the unlikelihood of HEM’s capacity to rise to the top as a viable third-party cookie option. 

Why Cross-Domain ID Solutions Don’t Stack Up: Fingerprinting

While HEM uses deterministic data, fingerprinting is an ID solution based on probabilistic data such as IP addresses and user agents. This data is used to create data points stitched together to generate an ID of a device or browser. 

Fingerprinting comes in two flavors, active and passive. Active fingerprinting requires some form of code, such as Javascript, on a local client, so users can potentially detect it. Passive fingerprinting, on the other hand, utilizes web requests and doesn’t require any code to be executed, making it less likely to be detected.

Why the Industry is Eyeing Fingerprinting’s Potential

Like HEM, fingerprinting offers several benefits that enable industry players to replicate some of the techniques that work within a third-party-cookie environment:

• Passive fingerprinting can collect IP addresses and user agent information undetectable to the user, so it’s not intrusive to the user’s experience. 
• Unlike cookies, the data is stored server-side rather than user-side, and it’s harder to block or delete. 
• Regarding scalability, it’s easier to collect probabilistic data than deterministic data.
• And finally, fingerprinting enables tracking across domains without the need for cookies.

Fingerprinting’s Major Weakness

Fingerprinting has the same Achilles’ heel as HEM: its ability to track users across domains means it’ll be a regulatory target. 

In fact, browser interventions designed to prevent fingerprinting have already been implemented or are currently underway. Google has stated its anti-fingerprinting goals, for example. And Apple has rolled out anti-fingerprinting initiatives such as opt-in requirements for mobile device IDs and its iCloud Private Relay, which masks IPs by sending requests through two separate internet relays. Masked IP techniques, in particular, make fingerprinting IP addresses virtually useless. 

Fingerprinting also comes with a slew of other issues, including:

Lack of consent. Regardless of the type of fingerprinting used—active or passive—there’s no user consent. From a privacy perspective, this is highly problematic. 

Needs deterministic data. While it’s easier to collect, probabilistic data doesn’t score well when it comes to accuracy, as it’s based on probabilities and inferences. So instead, it’s best used to enhance deterministic data and provide scale.

Lack of persistence. Unlike email addresses or phone numbers, people change devices and browsers more frequently, making fingerprinting less persistent than HEM techniques. 

These issues mean that fingerprinting isn’t just a runner-up to HEM-based ID solutions. It’s also unlikely to qualify as a contender in a post-third-party cookie world.

Alternatives to Cross-domain ID Solutions

Cross-domain solutions fall short, but how can they be avoided? Fortunately, there are some viable alternatives with long-term potential.

Google’s Privacy Sandbox

Google’s Privacy Sandbox is aptly named: it’s a playground for innovation and experimentation, where the industry can solve for targeting use cases using behavioral cohorts rather than individual identifiers to create a set of open standards on which to base a cookieless ad ecosystem.

While the Privacy Sandbox continues to be an exciting industry-wide initiative, it’s already faced several challenges:

• The evaluated proposals will solve some targeting use cases, but cohort analysis will only be marginally helpful for other use cases. 
• There’s been significant pushback from vendors already about efficacy. So the question is, will proposals be practical or widely adopted?
• Solutions are browser-by-browser, requiring significant changes in how advertisers set up their campaigns.

First-party Data

In a world without third-party cookies, first-party data, with its ability to provide rich insights about customers and visitors in a privacy-compliant manner, will be more valuable than ever. Made up of more than just log-in information, first-party data can be collected from numerous sources, including visitors’ website behavior, survey results, social media interactions, and customer feedback. 

Despite its value, though, first-party data is up against several obstacles:

• Like all deterministic data, first-party data tends to be costly to collect and difficult to scale.
• Many organizations aren’t structured to collect data in one central storage place across all their systems.
• To get the most out of first-party data, it’s necessary to add meaning to it through contextual and behavioral elements.

Seller Defined Audiences

A concept developed by IAB Tech Lab, seller-defined audiences is a specification that creates a standardized taxonomy based on context and first-party data. It aims to enable both publishers and advertisers to scale publishers’ first-party data without the risk of data leakage. 

While sound in theory, the concept isn’t without its issues. Because individual publishers self-define segments within the standardized taxonomy, buyers can lack consistency when purchasing a particular audience segment. 

For example, while one publisher might define its “basketball fanatic” segment as someone who reads articles about NBA game scores, another publisher might define that same segment as someone who reads any NBA-related article, including celebrity-based reporting. 

Combining Approaches: Opportunities in the Making

While each of these alternatives offers promise, they each confront obstacles that must first be addressed. In the current experimentation environment, the answer may lie in combining approaches. For example, pairing the power of first-party data with the standardized taxonomy offered by seller-defined audiences has the potential to provide both publishers and buyers with the best of both worlds:

• Level of engagement data—the number of articles read, time on page, scroll depth—adds the behavioral elements that take the data beyond just context. 
• The platform defines the segments within the standardized taxonomy rather than individual publishers.
• Publishers can remove specific segments from inventory (for example, to use for targeting direct ads), giving them complete control over access to their inventory.

For advertisers, the benefit of this combined approach is quality, consistency, and simplicity: They can stay focused on the buy without worrying about anything else.

Publishers benefit because they can put more highly engaged readers into a programmatic environment without fear that their data will be used for media purchases on other sites. The result? Publishers can raise CPMs while leveraging their first-party data in a cookie-constrained environment. 

TripleLift’s platform, which uses 1plusX to define its segments, is one example of such an approach. The platform also strips any unnecessary information from the bid requests going out to buyers, resulting in packaged deals for buyers based on segment IDs and the bid request, with no identifiers to connect data between domains.

How Do the Solutions Compare to Third-Party Cookies? A Note About Measurement

The challenge for any potential cookieless solution lies in measurement. Unfortunately, the reality is, no matter how viable the solution, it’s impossible to make a comparison to third-party cookies because of how success is currently measured. 

This challenge reflects several issues:

• Current metrics are, undeniably, not very accurate.
• Widespread adoption of ID identifiers is necessary before accurate measurement can be attained.  
• More testing within a cookieless environment is needed to obtain the numbers necessary to develop better metrics. 

While it’s a difficult challenge, it’s not insurmountable: a cookieless environment already exists in Safari as a testing ground for industry players. And there’s a corresponding opportunity to see how effective these solutions are within a third-party environment in Chrome while third-party cookies still exist. 

The Uncertain Future of Cross-Domain ID Solutions 

While cross-domain solutions are more privacy-friendly than third-party cookies, they face uncertainties that make them unsuitable as a long-term solution. For example, in addition to the need for widespread adoption, their cross-domain nature subjects them to a higher regulatory focus, similar to the scrutiny placed on third-party cookies. And this means their status will remain perpetually in flux.

In the long term, the right solutions will prioritize privacy. And the viable alternatives to cross-domain ID solutions described above are already doing just that. First-party data, in particular, allows the industry to create more predictability in the future. 

Eliminating cross-domain ID solutions doesn’t mean the industry will be left floundering. On the contrary, the enormous gap created by the deprecation of third-party cookies has created an environment ripe for innovation, collaboration, and experimentation. And for the industry as a whole, this spells opportunity.

The post Why Cross-Domain ID Solutions Won’t Replace Third-Party Cookies appeared first on TripleLift.

Traditional contextual advertising works by matching a webpage’s content with an ad’s content. Instead of using data about the user, the automated system displays relevant ads based on the page’s content. For example, an article on the NBA finals would likely match up to a sports drink advertisement. So there’s still a place for contextual advertisements. Still, as the cookieless future draws near, advertisers need to look for channels with the same or better performance achieved historically using cross-domain identifiers.

The answer is an evolution of old-school contextual advertising. Instead of relying solely on content relevance, this new approach will include an analysis of each publisher’s audience into segments by demographic (if available) and by interest. Additionally, ad buyers can further apply user behavior and engagement metrics to target their ideal audience. These new capabilities will generate much better ad performance than traditional contextual advertising and will therefore be a vital advertising approach in the cookieless future. This article will cover the changes in contextual buying, what advertisers need to start experimenting with, and incorporating this into their media plans.

The New Layers of Contextual Advertising and Why Advertisers Need Them

With third-party cookie deprecation, many SSPs (Supply-Side Platforms) are leaning heavily into Universal IDs to become the replacement for cross-domain identifiers. Unfortunately, this is a dwindling amount of internet traffic. When third-party cookies are fully deprecated, 90% of traffic will be expected to lack a cross-domain identifier. This means ad buyers must look at new approaches to meet their advertising goals. Ad sellers are looking to improve the results of contextual advertising to fill this gap.

Traditional contextual advertising assumes that any person reading content relevant to the advertised product or service will be interested in the product or service. Logically, everyone knows that won’t be true for every viewer, so lots of spending on ad dollars go to wasted impressions. That said, contextual advertising is future-proof from data privacy concerns since it doesn’t require data identifiers. So how can it be improved?

The first step that publishers are making is to create audience segmentation. Within a publisher’s site, they can create segments based on audience interest determined by the content they’ve consumed. These segments will likely follow the IAB Tech Labs Audience Taxonomy but will be up to the publisher to define levels of engagement. For instance, if a person views a sports page on the site, they could group them into a Sports Interest segment. 

Going deeper, publishers will look to define levels of interest within each segment. So if a person consumes three sports articles within 14 days, they might be grouped into a sub-segment of the Sports Interest group called Sports Fanatics. This new layer of audience segmentation will allow advertisers to be more targeted in their ad spend.

The Challenge: Every Audience Segment Definition is Unique to Ad Sellers

While deeper levels of audience segmentation are a significant improvement, it’s also creating a new challenge for advertisers. For example, the IAB Audience Taxonomy has over 1500 segmentations with up to 6 levels (or tiers) for each segment. The problem comes from how each publisher defines these segments’ rules. 

Considering the Sports Fanatic example, one publisher may define a Sports Fanatic as consuming three sports articles within 14 days, while another publisher defines their Sports Enthusiast segment as having read 1 article in 30 days. Another still may define it as two articles within seven days. 

This causes a big problem for advertisers—both in efficiently making ad purchases and attempting to compare results. 

A Middle Ground is Needed to Deliver Consistent Results

To address this challenge, a layer of consistency needs to be added. Using an SSP that matches up one audience segmentation taxonomy across publishers so ads across sites can be equally measured and compared can achieve consistency. This would also open up the ability for custom segmentations. For example, suppose an advertiser considers a Sports Fanatic to be anyone that consumes four sports pages a month. In that case, that segment could be created and applied as a taxonomy across publishers for consistent ad buying at scale. This will also save ad buyers significant time not having to look at all the segment definitions of each publisher and purchase site by site.

Beyond efficiency in ad buying, there’s also an opportunity to improve the quality of audience segments. This involves quantifying the impact of contextual buying through behavioral and engagement signals. For instance, understanding the time on the page, scroll depth, clicks, and other behavioral metrics can be added to the interest segments to improve quality. For example, with those metrics, advertisers could target Sports Fanatics who consume four sports pages a month AND stay on the page for more than 45 seconds AND scroll to more than 50% of the page. This would ensure a higher quality of engagement.

What Advertisers Need to Consider to Prepare for Cookieless Advertising

Advertisers must agree that continuing with third-party cookies and Universal IDs will be a game of diminishing returns. The audience will continue to shrink as data privacy laws will continue to eliminate identifiers. Therefore, looking into alternative ways to capture the attention of 90% of the digital audience that won’t have identifiers is critical for ad buyers to begin working on.

The evolution in contextual advertising capabilities is a great place to start with this exploration. Advertisers should consider the audience segments they want to reach and known qualifiers to measure their interest levels. When ready, begin experimenting with mid-funnel ads with CTAs to gain confidence in results before running brand impression ads. The other thing advertisers need to think about is attribution. It doesn’t exist in this approach, but is it required? SSPs are already testing the efficacy of this new advertising approach against third-party identifiers, so proof of accuracy and ad performance will be available. Finally, advertisers must shift from attribution to ad performance matched with business outcomes.

Vendors’ ongoing testing shows that the evolution of contextual advertising to smart segmentation will result in the same or better ad performance. An extra benefit to ad buyers is that publishers will put more high-value audience definitions into programs because the data can’t be leaked. All first-party data will be stripped from the deal using a Deal ID. With the addition of behavioral metrics, this approach has the potential to be extremely high quality and a great mechanism to add to media plans.

The post Contextual Advertising Evolved — Advertisers Take Note appeared first on TripleLift.

How Third-Party Cookie Deprecation Impacts Measuring Effectiveness in Digital Advertising

At its core, advertising is about delivering a message to consumers who aren’t interacting with your brand in your brand’s context. For example, advertisers put billboard ads to reach consumers who aren’t subscribed to email newsletters. They buy ads on websites they don’t own to reach the millions of consumers who haven’t visited their websites yet. This activity is inherently cross-context. Because advertising requires cross-context activity, measuring effectiveness requires both contexts to contribute data to understand whether an ad was effective.

Linking an individual across contexts has been typically achieved through third-party cookies. As a user goes from one context (domain) to another, the cookie on their device travels with them. For example, this makes it easy to observe if the user who’s seen an ad on a website is also the user who purchased a product or service. Thus, confirming that the advertising dollars were well spent on that website.

But as browsers and platforms deprecate third-party cookies, the opportunity for cookies to travel with the user is no more, severing the browser infrastructure to measure ad effectiveness. At the same time, European publishers are heavily incentivized to reduce the number of third-party measurement providers permitted on their pages, further severing the ability to measure outcomes.

What Does Cookieless Measurement (Actually) Mean?

When we talk about cookieless measurement, we mean a measurement without browser-provided cross-context linking, whether via cookie or some other state maintenance mechanism.

In the next few years, digital ads measurement will distill down into three non-mutually-exclusive buckets:

Cohort-Based Measurement

Cohort-Based Measurement is based on a minimum number of users in a bucket. This is measured using the bucket’s name rather than the individuals in a bucket. Cohort-based Measurement measures how many members of a targeted audience likely resulted in the desired action. Cohorts can be built into the browser (FLEDGE calls them Interest Groups or via the Interoperable Private Attribution proposal) or implemented via Deals.

Forward-looking SSPs will provide success metrics at the deal level for advertisers and brands. Because these cohorts can be created and measured without personal data, expect these to be a crucial part of advertising portfolios.

Individual-Based-Identifier Measurement (e.g., email)

This is a measurement based on a common token known by both the publisher where an ad is viewed and by the advertiser where conversion occurs.

This type of measurement requires both parties to know the same identifier for a user. This includes a user-provided email address to either share with or rely on a trusted third party to compare overlap between emails that viewed an ad and emails that converted. Assuming both parties can solicit this information from the user, this strategy will also need to rely on explicit user consent by the data controllers and therefore is likely to be limited in its scale.

Walled gardens will use this for their own measurement.

Survey-Based Measurement 

Survey-based measurement includes surveys, observation panels, and other methods of soliciting user input. Some advertising goals are brand awareness, prompting recall, or measuring brand affinity.

The Future Of Cookieless Measurement is Now. Get Ready.

Today, we see the beginnings of these changes across our industry, with investments in cohort-based measurement, increased marketing around panel-based solutions, and acquisitions that align with the first-party, privacy-first future of digital advertising.

The post Measurement Without Third-Party Cookies appeared first on TripleLift.

Digital advertising is changing rapidly. This is in response to increasing demands for consumer privacy from governments, privacy advocates, companies, and consumers worldwide. These changes impact the digital advertising ecosystem and force companies to reconsider how they understand advertising and the internet.

For over a decade, digital advertising has focused on reaching individual consumers with tailored ads. Based on insights or inferences about their online behavior. However, this is being challenged due to the global shift towards greater privacy and data security.

When Apple updated iOS devices to iOS14.5, the ad industry saw how addressability would change when third-party cookies are deprecated. According to mobile app analytics company Flurry, the global opt-in rate for IDFA on iOS is 25%. However, the US opt-in rate is only 18%. So, advertisers will track only 18% of all US-based iOS users on their iPhones or iPads, and only on individual apps that earn permission.

This shift forces the industry to redefine how digital advertising is understood and delivered.

What’s Addressability?

“Addressability” is a term often used in digital advertising. It describes how much of an audience is identifiable for ad targeting and online measurement.

Third-party cookies and device identifiers, like IDFA, enable high addressability across websites and mobile apps. As a result, companies in the digital advertising value chain can recognize individual consumer devices as people use them for browsing the internet or using mobile apps.

Specifically, almost all programmatic ad targeting today is based on the ability to track consumer devices across websites and apps. When third-party cookies deprecate in all significant browsers, information about online consumer behavior will be available on a website-by-website basis. Still, it won’t be readily available across websites.

This change represents a tremendous shift in how advertisers need to think about targeting ads to consumers and measuring the success of their ad campaigns.

Introducing a New Response to Privacy Changes

The industry needs a more nuanced definition of addressability in response to every major browser moving to deprecate third-party cookies and mobile app platforms, like Apple iOS, making mobile advertising identifiers opt-in only.

The Addressability Spectrum (shown below) provides a visual framework for handling addressability once the web browsers and app platforms impending changes take effect.

Collectively, the categories displayed in this diagram represent the future state of addressability. Each ad impression will fall into one of these addressability categories. Working from left to right in the diagram, the definitions below explain what addressability will mean.

1. Unknown:

This segment of consumers is already working to hide their online behavior. They may be using multiple VPNs, the Tor browser, or taking other actions to prevent their online behavior from being tracked. This segment is tiny, and advertisers don’t generally target these consumers, but they’re included here for completeness.

2. Cohorts:

Cohorts are effectively groups of consumers with similar behaviors. They’re often referred to as “audience segments.” Privacy Sandbox proposals like FLoC and FLEDGE propose that cohorts be used to target consumers instead of targeting individuals.

3. First-Party Identified:

This is a segment of individual consumers identified on a website-by-website or app-by-app basis. Using first-party cookies or local browser storage can achieve this with pseudonymous identifiers. It may also be achieved when a consumer chooses to create an account on a website and provides an email address or other unique information.

4. Cross-Domain Identified

This is a segment of individual consumers identified across different websites or apps. Once third-party cookies are deprecated in all major browsers, this may only be achieved with identity solutions like Liveramp RampID or ID5. Consumers who opt-in to IDFA on iOS apps fall into this category.

Examining the Internet Through the Lens of the Addressability Spectrum

These impacts will apply to all channels, including web and mobile apps. Thinking about how the Addressability Spectrum will apply to websites provides a lens into the challenges advertisers will face once third-party cookies are deprecated, and mobile device identifiers are opt-in only. A similar analysis can be done for mobile apps as well.

Below, four stereotypical websites illustrate how the new definition of addressability along a spectrum creates challenges for advertisers compared to current advertising methods.

Note: Outlier websites don’t fit this model but are few and far between. Most websites will fall neatly into these descriptions.

• long-tail-site.com is representative of the vast majority of websites on the internet. These websites typically have low monthly traffic but monetize with programmatic advertising. Generally, these websites will be able to identify less than 2% of their consumers with cross-domain identifiers.

• Popular-publisher.com is representative of high-quality, high-traffic websites or high-quality niche websites that have consistent viewership. However, these websites can identify less than 2% of their consumers with cross-domain identifiers. In addition, many of these websites have tried to increase the number of cross-domain identifiable visitors. Still, they’ve been unable to compel their visitors to create accounts or sign up for emails at high rates.

• Login-publisher.com is representative of high-quality, high-traffic websites with consistent viewership. These websites can identify 10-15% of their visitors because they’ve found ways to incentivize visitors to create accounts or sign up for subscriptions. Further, these websites are some of the largest and most popular online websites.

• Popular-brand.com is representative of internet brands driving purchases or consumer signups for goods and services. The most popular brand websites may be able to identify as much as 20% of their visitors because they have products that people love and return for more.

Redefining Addressability in Digital Advertising 

When viewed through the lens of the Addressability Spectrum, it becomes clear that addressability will change significantly when third-party cookies are deprecated in all major browsers, and mobile device identifiers become opt-in only on iOS and Android.

While some websites and apps will be standout performers that can earn cross-domain identifiers from more than 10% of their visitors, the vast majority of websites and apps won’t.

As more privacy regulations are passed, technical blocks to workarounds like first-party click redirects and device fingerprinting are put in place, consumer transparency, control, and consent are increasingly required for the capture and use of consumer information to power digital advertising, and those cross-domain identifiers will be less and less valuable because consumers are expected to restrict the capture and use of their data to the websites and businesses they trust.

The digital advertising ecosystem must think about addressability differently to address this future state. The opportunity for advertisers lies in solving for cohorts of consumers as proposed in Google’s FLoC or FLEDGE and leveraging supply partners to use first-party audience information.

TripleLift’s Building for the Future

TripleLift is focused on a portfolio strategy to solve for the future of addressability. Our products will use the best available data from across the addressability spectrum on every ad impression to ensure that a campaign will reach the intended audience.

How campaigns are planned and success is measured will need to change to reflect the available data and capabilities. Still, TripleLift has the experts and experience to help guide your advertising to successful outcomes.

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