Tag Archives: digital-marketing

Programmatic Curation Surges Ahead: What is it, and why is it so hot?

by Eric Picard

As programmatic advertising continues to evolve, the concept of curation has become a critical focus. My article from a few years ago, The Fifth Wave of ad tech highlighted the rise of “privileged programmatic”, but today’s discussions center around the nuanced roles of curation. To truly understand its implications, we need to dig into the distinctions between manual and smart curation, and clarify how these approaches differ from traditional ad networks and the proto-curation methods established by programmatic buyers using PMPs.

Ad Networks: The Initial Curators

In the early days of programmatic advertising, ad networks acted as intermediaries, facilitating transactions between buyers and sellers. However, their model was fundamentally flawed. By exploiting market inefficiencies, ad networks engaged in arbitrage—buying low and selling high—without significantly enhancing transactional value. This approach, while initially convenient, soon revealed its limitations as advertisers grew wary of inflated costs and minimal value addition.The recognition of ad networks’ inefficiencies spurred a shift towards more transparent and efficient transaction models. Although some ad networks persist, their model is increasingly viewed as outdated and incompatible with the demands of a sophisticated programmatic ecosystem.

Proto-Curation: Traders using PMPs

For over a decade, advanced programmatic buyers have employed a strategy that could be termed proto-curation. This involves negotiating with publishers for privileged access to inventory, resulting in the manual creation and management of a vast array of Private Marketplace (PMP) deals within DSPs. These PMPs offer buyers curated inventory aligned with their specific needs, but managing thousands of such deals is labor-intensive and complex, and negotiating for privileged inventory access has varied results. This proto-curation is distinct from the curation models we see emerging today, and is the answer to the question of why curation is different from the approach trading desks have taken with PMPs for the last decade.

The Evolution of Curation: Standard and Smart Approaches

In recent years, curation has evolved into two distinct forms: Standard Curation and Smart Curation. Both approaches build upon the foundations laid by proto-curation, yet they offer unique methodologies and benefits.

Standard Curation involves human intervention to select inventory based on specific buyer criteria. This approach is akin to proto-curation but is more focused and refined, and often done on behalf of the publisher. Manual curators negotiate inventory access with publishers, ensuring that DSPs receive bid opportunities that meet predefined criteria. This method provides a critical layer of control and efficiency that open exchanges cannot offer, making it indispensable for buyers seeking to optimize their programmatic strategies. This curation is happening inside of platforms designed to improve and streamline the work buyers have been doing for the last decade by providing strong workflow and tools to streamline the process of curating inventory through PMPs.

Another piece of the puzzle is that curation is done typically on the sell-side of the ecosystem. It’s in the publisher’s best interest to curate inventory from their end and to ensure that any privileged access to inventory is coming through curation platforms, so they can preserve prices and margins. Sometimes the manual curation is done by the publisher’s sales team, sometimes it’s done by a third party on behalf of the publisher.

Frequently these platforms bring together audience data as a differentiator, sometimes they act as the means for an advertiser to bring their own first party data to the media environment. Publishers typically put PMPs from their curation partners into higher privileged positions in the ad server than those done for advertisers and agencies directly – because it’s in the publisher’s interest to increase curated inventory’s value. Examples of these curation platforms include Permutive and Audigent.

Smart Curation, on the other hand, leverages advanced technology to enhance the curation process. By utilizing proprietary algorithms, signals, and data, smart curation refines inventory selection, aligning buying decisions with advertisers’ strategic goals. Unlike manual curation, smart curation minimizes human intervention, relying on advanced technology to streamline processes and maximize efficiency. Examples of smart curation include Yieldmo and OneTag.

Note – for all forms of curation, every vendor in the ecosystem is developing some curation product that proposes to be the way that curation should be done. Nearly every SSP/Exchange has a curation tool or marketplace, lots of the older data companies are getting into the curation game, and there are several standalone curation platforms on the market now. The goal of this article is to get you up to speed on what everyone’s talking about, and go a bit deeper into why it matters.

Curation isn’t just about Curated Audiences

While this is a significant use-case, curated inventory against audiences defined in advertiser first-party data, potentially with lookalike audiences, it’s not the only use case. Many curation engines are not using user data or targeting audiences. Many are curating using contextual data, some with other performance signals. This is an important distinction because there have been several movements to rebrand curation against the concept of Curated Audiences, which in my mind are a subset of curation overall.

Dispelling Misconceptions: Curation vs. Ad Networks

Beware anyone telling you that curation is merely a rebranded version of ad networks. This simply isn’t true, and is often thrown out by very experienced people in the industry as a way to diminish the value of curation – but saying it sounds smart while truly missing the point of what curation is. While both models involve intermediaries, their methodologies and value propositions are fundamentally different.

Ad networks thrived on market inefficiencies, engaging in arbitrage without adding significant value beyond transactional convenience. Conversely, curation—whether manual or smart—focuses on optimizing inventory selection without engaging in arbitrage. Curation grants inventory access ahead of buyers coming in directly through their DSP through the open exchange. Curation provides DSPs with refined bid opportunities at higher levels of privilege in the auction to improve results. There are no hidden costs or markups; instead, curation aims to maximize advertisers’ investments by aligning inventory with campaign goals.

Navigating the Programmatic Ecosystem with Curation

To fully appreciate curation’s value, it’s important to understand the programmatic ecosystem’s complexity. From Supply-Side Platforms (SSPs) to Pre-Bid Frameworks and Ad Server prioritization rules, numerous factors influence buyer-seller relationships. Advertisers lacking privileged access risk losing valuable impressions, a challenge that curation effectively addresses by refining bid opportunities.

The impact of this kind of privileged inventory access:

Imagine two bids on the same root impression that is sent to the exchange – even from the same DSP. Bid 1 could be $5.00 against the open exchange. Bid 2 could be $5.00 against a curated PMP. Bid 2 will always win because the publisher is going to favor (give privilege to) the PMP that they are curating for that advertiser. To make it even more complicated, some publishers may give enough privilege to curated PMPs that cost doesn’t even matter. If Bid 1 through the open exchange was $50, and Bid 2 through the curated PMP was $5 – Bid 2 would always win.

DSPs evaluate each bid opportunity provided by exchanges and SSPs, valuing them based on campaign objectives. While comprehensive, this approach is inefficient, as most bid opportunities hold little value for a specific campaign. And DSP bidder algorithms are valuing every bid opportunity – when not every bid opportunity even warrants any scrutiny. Buying a bad piece of inventory just because the cost is low enough doesn’t really help lead to good outcomes. Consequently, the shift towards PMPs and curated inventory has become a strategic necessity to screen out inventory that shouldn’t be in consideration.

Standard curation continues to provide value, especially when curators negotiate priority access with publishers. Meanwhile, smart curation utilizes technology to either streamline the process, or to find powerful new ways to define and value inventory altogether. Smart curation is not the evolution of curation, it’s a subset of curation that defines and values inventory differently based on proprietary data and advanced algorithms and data to make informed decisions earlier in the bid stream than the DSP. Both approaches have value in enhanced access to inventory, increases in performance, increases in efficiency and offering significant value beyond what DSPs alone can achieve.

Strategic Implications and Future Directions

As programmatic advertising advances, the strategic implications of curation are profound. Advertisers must discern which platforms and technologies offer genuine value, distinguishing between superficial buzzwords and solutions delivering tangible results.Publishers, too, should embrace the transparency and efficiency that curation offers. By collaborating with advertisers and technology providers, they can increase yield, preserve pricing, and unlock new revenue streams that enhance their competitive edge in a rapidly evolving market.

The lessons from previous ad tech waves remain relevant. Balancing innovation with value creation is critical, and success hinges on our ability to adapt and evolve. Curation represents not only a technological advancement but a strategic shift poised to redefine programmatic advertising’s future. By navigating this new terrain thoughtfully, advertisers and publishers can unlock new opportunities and drive meaningful results in an increasingly competitive market.

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Programmatic Ads in 2024

A privacy-centric new world

By Eric Picard

I’ve been writing about advertising technology and digital advertising since 1999. Every five to seven years we go through a new wave of transformation. The current wave is the Privacy wave, and it’s transforming the way that the infrastructure of the ad technology space functions. Previously we were reliant on digital identifiers, generally enabled by cookies on the web, and AdIDs in the mobile app space, but today these mechanisms have been deprecated or are in the process of being deprecated. This has decimated a huge swath of the industry that relied on these IDs to make all sorts of decisions, including linking together multiple tracking methodologies – to power 3rd party data. That industry has shrunk significantly, since users are becoming impossible to track that way.

This transformation is largely driven by increasing consumer demands for privacy and stringent regulatory requirements. Today, the focus has shifted towards privacy-centric methodologies, with first-party data taking center stage. In this comprehensive overview, we’ll explore the current state of programmatic advertising, delve into the innovative strategies employed to maintain effectiveness while upholding privacy, and highlight the strategic implications for advertisers.

Understanding Programmatic Advertising Today

At its core, programmatic advertising is the automated buying and selling of online ad space, allowing brands to target specific audiences at scale. This process involves real-time bidding (RTB), where ad inventory is bought and sold on a per-impression basis in a few hundred milliseconds. Programmatic platforms use sophisticated algorithms to analyze vast amounts of data, enabling advertisers to reach their desired audiences with precision.

Without cookies and AdIDs, the whole industry is in the process of retooling.

The Role of First-Party Data

First-party data refers to information collected directly from consumers either through brand-owned channels such as websites, apps, and loyalty programs on the advertiser side, or through the publisher’s relationship with the consumer. This data is gathered with explicit user consent, making it both reliable and compliant with privacy regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).

The importance of first-party data cannot be overstated. It provides a comprehensive view of consumer behavior, preferences, and demographics, enabling advertisers to create personalized and relevant ad experiences. By leveraging first-party data, brands and publishers can build direct relationships with their customers. This data can be used in many valuable ways, but importantly can be used to deliver the correct advertising to consumers, and to measure effectiveness of advertising.

Privacy-Centric Targeting Methodologies

In response to the growing emphasis on privacy, advertisers have adopted several innovative targeting methodologies that prioritize user rights while maintaining effectiveness:

Contextual Targeting: In a world where user data is increasingly protected, contextual targeting offers a privacy-friendly alternative. This method involves placing ads based on the content of the web page rather than individual user data. For example, an ad for hiking gear might appear on an article about nature trails. By focusing on the context rather than the person, advertisers can maintain relevance without compromising privacy. Contextual has been around forever, but new approaches to contextual are being used in much more sophisticated ways. What’s old is new again.

Cohort-Based Targeting: Google’s Privacy Sandbox initiative popularized the concept of privacy-first approaches to targeting users, their first broadly discussed version was called Federated Learning of Cohorts (FLoC), which groups users into cohorts based on similar browsing patterns. Google has reiterated and revised their approach several times, and hasn’t really gotten traction. But that’s mostly because they’re Google, and the industry isn’t sure they trust the approach they have come up with. While Google’s approach isn’t gaining traction, the overall approach of building privacy-safe cohorts of users for anonymous targeting is sound, and may well get cracked at the industry level sooner or later. This approach allows advertisers to target clusters of users with shared interests, removing the need for individual tracking.

Identity Solutions: With the decline of third-party cookies, identity solutions have emerged as a viable alternative. These solutions use hashed identifiers like email addresses or phone numbers to create a persistent identity across different platforms. The success of these solutions depends on user consent and robust data protection measures, offering a way to recognize users while respecting their privacy. While these approaches work technically, getting to scaled anonymous identity is a real challenge that still is being overcome.

Data Clean Rooms: These secure environments allow brands and publishers to collaborate and combine their first-party data without exposing user identities. Data clean rooms enable advertisers to gain insights and enhance targeting precision while adhering to privacy regulations. By facilitating data collaboration in a controlled setting, clean rooms offer a solution to the challenges posed by privacy laws. Note that while this approach overcomes the legal issues, it’s still not quite clear that consumers will be accepting of the approach as it becomes normalized and written about in the press.

Beyond Basic Targeting: Curated Audiences and Inventory

Publishers lost a lot of ground in the first wave of programmatic advertising, which pushed all the power to the media buyer. This created a long period of data asymmetry where publishers didn’t know why an advertiser was buying any given impression – and the knowledge of their own audience was ignored by the buyer. Things have changed with the loss of 3rd party data, cookies and IDs.

The industry has responded by rallying around the sell-side of the market for the first time in many years. The outcome is what is being called Curated Audiences and Curated Inventory. Effectively the sell-side of the market has access to an immense amount of information on their side of the fence, about the consumers visiting their sites, and about the behavior of those consumers. This all is Publisher First Party Data, and is able to be blended with other data sources by the Publisher to create large pools of inventory that are curated to the needs of the buyer. Vendors and the publishers themselves have found ways to build high scale and highly effective targeting and optimization technologies based on these approaches, and package the inventory into programmatic deals (PMPs):

Curated Audiences: Publishers can create pre-defined audience segments based on aggregated data insights and consumer behaviors. These segments are crafted using a combination of consented user data (the consumer said the publisher can use it) and non-personal data, ensuring compliance with privacy regulations. By curating audiences, advertisers can buy advertising at scale that allows them to reach relevant consumers without relying on intrusive data collection methods.

Curated Inventory: Publishers can package their ad inventory using their own data and intelligence, often with the support of sophisticated external data providers. This approach allows advertisers to target ads to appropriate audiences without using personal data. For instance, sophisticated geo-targeting can be employed to deliver regionally relevant ads, enhancing user engagement without compromising privacy. Some vendors use decades old approaches in new ways, using census and other forms of data that allow demographic, psychographic, and other types of targeting by overlaying the location of the user when they receive the ad against known information about that location. For instance, assuming someone on a golf course at 3PM is likely a golfer.

These curated solutions provide advertisers with powerful tools to reach their desired audiences while navigating the complexities of privacy regulations.

Strategic Implications for Advertisers

The shift towards privacy-centric methodologies is not just a technical adjustment; it’s a strategic imperative. Advertisers must align their programmatic strategies with these approaches to maintain consumer trust and comply with legal requirements. This involves investing in data infrastructure, nurturing direct customer relationships, and staying informed about regulatory changes.

Moreover, as privacy becomes a selling point, brands that demonstrate a commitment to safeguarding user data can differentiate themselves in a crowded marketplace. Transparent data practices and clear communication about how consumer data is used can build loyalty and encourage engagement.

Overcoming Challenges in the Programmatic Space

While the transition to privacy-centric advertising offers numerous benefits, it also presents challenges. Advertisers must adapt to new technologies and methodologies, requiring investment in training and infrastructure. Additionally, the loss of third-party cookies necessitates a reevaluation of measurement and attribution models, as traditional methods may no longer apply.

To overcome these challenges, collaboration within the industry is crucial. Brands, agencies, publishers and technology providers must work together to develop standards and best practices that prioritize privacy while delivering effective results. By fostering an ecosystem of transparency and cooperation, the industry can navigate the complexities of programmatic advertising in 2024 and beyond. The IAB Tech Lab is a great example of an industry organization working to drive this kind of collaborative adoption and roll out.

The Future of Programmatic Advertising

As we look to the future, programmatic advertising will continue to evolve in response to technological advancements and changing consumer expectations. The integration of artificial intelligence (AI) and machine learning will enhance targeting capabilities, allowing for even greater personalization while respecting privacy. Additionally, the rise of connected devices and the Internet of Things (IoT) will present new opportunities for advertisers to engage with consumers in innovative ways.

Ultimately, the key to success in programmatic advertising lies in embracing privacy as a core value. By doing so, advertisers not only comply with regulations but also foster trust and loyalty among their audiences. In 2024 and beyond, the challenge will be to innovate continuously while keeping consumer privacy at the forefront of every decision. As the landscape continues to evolve, staying informed and adaptable will be essential for advertisers seeking to thrive in this dynamic environment.

The current state of programmatic advertising is characterized by a delicate balance between effective targeting and stringent privacy requirements. First-party data has emerged as the linchpin of modern advertising strategies, offering a path to personalization that respects user privacy. By adopting innovative targeting methodologies and maintaining a strong commitment to privacy, advertisers can successfully navigate the programmatic landscape, building lasting relationships with their audiences in the process.

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