In the world of digital media, Generative AI sparks both excitement and concern. This is especially true among publishers and independent content creators.

Last week, creators took a stand in New York City with the launch of Raptive’s ‘Keep It Real’ campaign, an advocacy effort designed to raise awareness about the impact of AI on their livelihoods.

As I sat in the room, listening to stories from food bloggers, designers, and country music aficionados, I couldn’t help but draw parallels between their challenges and the ones publishers face.

Digital media and advertising is grappling with a shifting landscape where AI threatens to commodify human creativity and diminish revenue streams. And if creators are rallying together to protect their work, shouldn’t publishers do the same?

Setting the Stage: The Creator’s Call to Action

ABC News anchor Linsey Davis was the surprise host of the day, opening the event by celebrating creators’ work as the “heart and soul of the internet.” Her words resonated throughout, highlighting the core message: creators — and, by extension, publishers — are the lifeblood of the web, facing challenges that deserve urgent attention.

But creators’ work is now threatened by the rise of generative AI, which scrapes content to deliver quick answers, often at the expense of the nuanced stories they bring to life.

Creators vs. AI: Navigating the SEO Shake-Up

The ‘Keep It Real’ campaign centers on a simple but powerful message: AI should innovate responsibly without exploiting the creators who pour their hearts into their work. Creators shared how generative AI scrapes and repurposes their work without consent or compensation. This issue hits home for publishers who have spent years building quality content to engage audiences.

Scott Messer‘s analysis of the latest SEO challenges for publishers sheds light on how Google’s introduction of AI-generated summaries and features like Search Generative Experience (SGE) alters search engine results pages (SERPs). This shift pushes traditional organic results further down the page, impacting CTRs for top organic positions. For creators, this means that even high-quality, nuanced content risks being overshadowed by generic AI outputs, threatening their visibility and revenue.

Kaitlin Leung of The Woks of Life illustrates the value of discoverable, human-created content: “We slowly but surely started to attract people who were so thankful and grateful to have found us because they were also looking for a similar platform to be able to learn about their heritage more, and cook recipes that kind of were always the domain of their parents or their grandparents or their aunts or their uncles.”

However, with AI-driven search results potentially limiting such discoveries, creators like Kaitlin worry that these meaningful connections between content creators and their audiences may become increasingly rare. It’s clear that AI poses threats, but some publishers are exploring ways to unlock AI opportunities that can preserve revenue and drive growth.

The Economic Impact of AI on Creators

Like creators, publishers rely on nuanced, human-generated content to attract audiences, which opens up the gates to advertising dollars. But with generative AI serving up bland, one-size-fits-all information, creators and publishers risk losing their unique voice — and, ultimately, their revenue.

Michael Sanchez, CEO of Raptive, puts this threat into stark perspective: “Let’s put this in human terms for Raptive creators, this is their livelihood. They do this full-time. It is the primary way they feed their families. There are 1000s of creators across Raptive who earn their living from their content and make less than $100,000 per year for one family, if they lose half of their traffic due to AI replacing their content, they lose half of their income.”

Today, 15% of every dollar advertisers spend on the open web goes through a Raptive site, earning creators over $2.5 billion in revenue. So a 50% reduction in traffic would impact individual creators’ revenue and threaten the broader creator economy, which supports millions of jobs.

Building Communities and Connections

Lindsay and Bjork Ostrom of Pinch of Yum said it best: The internet should continue to be a place where independent voices can thrive. It’s a sentiment publishers know all too well.

Echoing this idea, Tieghan Gerard of Half Baked Harvest, emphasized the importance of community building. “The time I spend on social media is the time I spend interacting with my community and building that community, making that community strong, and making those people feel heard. It’s so important. Nobody feels heard anymore, and we have the power to do that.”

The Role of Advertisers: Supporting Human-Generated Content

The ‘Keep It Real’ campaign calls on advertisers to invest in human-generated content that drives real results and engages audiences on a deeper level. As AI-generated content starts flooding the web, advertisers might be tempted to pour money into platforms that offer quick wins and endless streams of generic content. However, this approach undermines the authenticity that both creators and publishers bring to the table.

Marketers should consider how their media plans and spending align with the campaign’s message. How can the industry ensure that advertising dollars support high-quality, human-centric content?

This could mean reassessing where programmatic buys are directed or prioritizing direct partnerships with publishers who maintain human touchpoints in their content.

Publishers It’s Time to Innovate Responsibly

In creators’ rally for responsible innovation, they want it to be known —  they’re not anti-AI; they’re pro-ethical AI. They want to be part of the conversation, advocating for systems that value their contributions.

Publishers, too, must find ways to leverage AI responsibly while supporting the creator economy, ensuring that both creators and publishers can thrive. That might mean adopting practices that respect the human element of content creation or finding ways to collaborate with creators on shared initiatives that promote authentic, valuable storytelling.

Ad Tech and the Human Connection

Programmatically, ad tech builds a bridge between advertisers and the content that audiences consume. This connector role directly impacts the future of human-generated content online.

It’s time to explore how ad tech can support responsible AI practices that don’t undercut the human connections at the heart of the digital ecosystem.

It’s time to ask: How can ad tech support an internet where independent voices can thrive? It may involve prioritizing ad placements on websites that invest in human-generated stories or encouraging advertisers to value quality over quantity in their content partnerships.

What the Ad Tech Industry Can Do to Keep It Real

• Collaboration: Just as creators are banding together to advocate for their rights, publishers need to engage in collective action. Working with industry bodies to push for fair practices in AI use is a start.
• Support Quality Content: Encourage advertisers to align their spending with websites that offer the depth, nuance, and authenticity AI can’t replicate.
• Advocate for Fair Practices: Push for more transparency in AI’s use of content, ensuring that creators and publishers are fairly compensated when their work is used to train AI models.

The Path Forward: Keeping the Internet Human

At the event, creators emphasized that the fight for fair AI use is only beginning. As they advocate for their rights and the protection of their livelihoods, the entire ad tech ecosystem has a stake in this conversation, especially publishers.

By standing together and championing authentic, human-driven content, you can ensure that the internet remains a place where creativity and community thrive. The road ahead calls for collaboration, innovation, and a shared commitment to keeping it real.

The post Creators vs. AI: Can Keeping It Real Save the Internet? appeared first on AdMonsters.

In an era where technology shapes our daily lives, generative AI has emerged as a powerful force in the political landscape, and its role is both revolutionary and potentially dangerous.

With generative AI, politicians can create targeted campaign ads, amplify campaign messages, and engage voters, but there’s a downside. Consider how AI can also be misused for creating convincingly fake campaign ads, disseminating disinformation, and turning voter outreach into voter manipulation.

Dive in as Dinesen delves into the complex world of AI in politics, examining its benefits, risks, and the urgent need for regulation to protect the integrity of democratic processes.

Generative AI and Politics

OpenAI certainly changed the world in November 2022 when it introduced ChatGPT, the first popular and widely available generative AI tool. Public reaction was varied. Many warned it was the end of numerous careers (indeed, the Hollywood writers’ strike was partially due to fear that ChatGPT would eliminate their jobs).

And a great many experts worried that ChatGPT would usher in a new era of fake news, disinformation, and more believable scams as generative AI can create text that feels legitimate to the average person. This isn’t an idle fear as one study found that large language models (LLMs) can outperform human authors in terms of convincing people.

Election officials are sounding the alarm over the use of generative AI in creating political ads, phony but convincing campaign fundraising letters, as well as orchestrating voter outreach initiatives. These officials weren’t wrong; we’ve already seen generative AI used for such purposes. In January 2024, registered Democratic voters in New Hampshire received fake Joe Biden robocalls telling them not to vote in the primaries so that they could save their vote for November.

This is not to say that all use cases for generative AI in the political sphere are nefarious. Many legitimate political parties and candidates see generative AI as a useful tool in amplifying the impact of their political ads. For instance, they can use it to deliver highly targeted ads at the household level, including those encouraging voter turnout. In fact, generative AI can help less-resourced campaigns compete against well-funded ones.

That said, generative AI can (and likely will) have harmful impacts on elections across the world, and it’s well worth our time to be aware of its dangers, and take steps to mitigate them.

Insufficient Oversight in AI-Generated Political Ads

There’s no doubt that AI can create high-quality text that many people and voters find quite credible. But therein lies the danger. 

Most reasonable people assume that the ads they hear or see have been endorsed by a campaign and vetted by the media source that runs them. In the US, radio and television ads end with the candidate saying, “I’m [candidate name] and I approve this message.” Internet-based ads are exempt from this disclosure requirement, a loophole that the Honest Ads Act of 2017 sought to close (it didn’t pass).

Today, few regulations require political ads to disclose the role of AI in their creation. The one exception is the EU AI Act, which classifies AI systems used to influence voters in political campaigns as “high-risk” and therefore subject to strict regulations.

The United States government has failed to enact a national AI disclosure law, even as the 2024 presidential election looms. In the absence of a national law, a dozen or so states enacted laws regulating the use of AI and deepfakes (more on that later) in political advertising and requiring disclosure. Those states are California, Florida, Idaho, Indiana, Michigan, Minnesota, New Mexico, Oregon, Texas, Utah, and Wisconsin. Additionally, Google said last year it would require AI disclosure on political ads, and Meta soon followed suit.  

But there are challenges to these efforts. Common Cause, an advocacy group focused on promoting ethics, accountability, and reform in government and politics, says the Florida law is too weak to be effective as it imposes fines, but no mechanisms for removing offending ads. In Wisconsin, the Voting Rights Lab warns that the state law is too narrow, regulating only candidate campaigns and not special interest group ads.

The bigger challenge is that it’s up to the ad creators to self-disclose, an unlikely event for people bent on fear-mongering, and even if an ad is deemed violative, it will still be in circulation for it is spotted and identified. In other words, AI-generated ads with misinformation will still have ample opportunities to be seen and believed by a great many voters.    

Generative AI Hallucinations

Another challenge is AI hallucinations. Most AI tools warn the user that responses may contain incorrect information (see graphic below), which means a campaign may willingly or inadvertently create campaign ads containing false information.

This isn’t a theoretical concern. Research from a European non-profit organization, AI Forensics, found that one out of three answers provided by AI was wrong. Microsoft’s Bing search bot gave wrong answers when asked basic questions about elections in Germany and Switzerland, often misquoting its sources.

In the United States, misleading and incorrect responses from chatbots threaten to disenfranchise voters. AI-generated responses told users to vote at locations that don’t exist or aren’t official polling stations. Columbia University tested five AI models, and all failed to provide accurate responses to basic questions about the democratic process.

In the U.S., misinformation about voting times and locations is a tried-and-true voting suppression tactic, so it’s concerning that generative AI will allow its practitioners to be more effective.

Inherent Bias of Generative AI

All AI is trained on data; the accuracy of the AI is wholly driven by how well the training data is vetted and labeled. Data is often inherently biased for many reasons. In the political sphere, LLMs are trained on news stories that concern elections and candidates, but liberal news sites block AI bots as a matter of course, whereas right-wing ones welcome them. The result is that the AI models are trained on data skewed to a particular point of view that may not reflect a total body of opinion. 

Going further, some people intentionally seek to influence the responses of a chatbot. In 2023, The New York Times reported that David Rozado, a researcher in New Zealand, used prompt engineering to create right-wing ChatGPT. This revised chatbot was intentionally designed to give right-wing answers

Political Manipulation

Perhaps the biggest concern is that AI will be used to manipulate the voter, as the fake Biden robocalls sought to do.

This isn’t a new fear, of course, as we’ve seen AI used in political manipulation long before the widespread availability of ChatGPT. For instance, in the 2018 midterm elections in the US, election officials were warning voters to be aware of deep fakes. To raise awareness of just how realistic deep fake videos can seem, Oscar-winning filmmaker Jordan Peele created a video in which a fake Barack Obama says “stay woke.” The message is clear: don’t believe what you hear on the internet.

Despite the warning, deep fake videos and images appear in the media.  In June 2023, Florida Gov. Ron DeSantis’s presidential campaign shared fake AI-generated images depicting Donald Trump embracing Dr. Anthony Fauci, the former head of the National Institute of Allergy and Infectious Diseases (NIAID) and someone who Trump came to loathe. Trump supporters targeted African Americans with fake AI images, as part of a strategic ploy to convince voters that Trump is popular among Black voters.

Deep fakes also played a key role in the 2023 Argentine elections. Candidate Sergio Massa’s team created a video featuring his main rival, Javier Milei, describing the revenues that could be gained by selling human organs and suggesting that parents could consider having children as a “long-term investment.” Despite the video’s explicit AI-generated label, it was quickly shared on different platforms without disclaimers.

Over in Turkey, President Recep Tayyip Erdoğan’s staff shared a video depicting his main rival, Kemal Kiliçdaroğlu, receiving the endorsement of the Kurdistan Workers’ Party, a designated terrorist group. Although this video was clearly fabricated, it didn’t stop voters from viewing and sharing it widely. 

Given what we’ve already seen occur, it’s no surprise that election experts call generative AI a “political super-weapon.” Jen Easterly, director of the Cybersecurity and Infrastructure Security Agency, takes it one step further, saying that AI poses “epoch-defining” risks, including the widespread proliferation of disinformation.

When People Aren’t Real: The Rise of Bots & Psychochats

There’s one final threat to consider: AI posing as humans to sway how people think and ultimately vote. Once again, nefarious players have access to sophisticated tools to help them deploy their schemes.

For instance, bots have been effective at disseminating disinformation with a great deal of speed and efficiency. In 2019, The New York Times reported that Epoch Media Group created over 600 fake media profiles, all featuring profile photos generated by AI. Those profiles were then deployed to distribute fake news and disinformation.

It’s not that hard to come up with AI-generated profile pics; a simple Google search serves up numerous sites allowing you to create realistic headshots and photos for social media. These bots can then be used to engage with voters who may be on the fence or provide people, who are intent on voting, to go to a non-existent polling station.

Psychochats goe one step further. These are avatars of candidates and are deployed online to interact with potential voters. It’s only a matter of time before psychochats are used by campaign opponents to spread misinformation on their rivals, similar to Sergio Massa’s smear campaign against Javier Milei.

Think this is too outlandish to be true? Politico reports that Meta is already experimenting with licensed AI celebrity avatars. And, Hello History invites users to “have in-depth conversations” with historical people of the past.

Democracy in Peril: Why We Must Act

When elections are marked by rampant misinformation, the very foundation of democracy is compromised. At the end of the day, misinformation leads to the formation of governments formed under false pretenses. Chaos results when governments lack the necessary legitimacy to govern effectively. 

The erosion of trust brought on by deep fakes, AI-generated lies, and psychochats undermine the democratic process, ultimately threatening the stability of societies. Never has it been more important to protect the integrity of information during election cycles. AI tools are cool and offer tremendous benefits to everyone in the digital media industry. But we must also acknowledge their potential for abuse, and work tirelessly to control how they’re used.

The post AI’s Role in Political Manipulation appeared first on AdMonsters.

When it comes to ad tech, Jack Smith is no stranger to innovation. With over 25 years of experience and seven patents in AI and machine learning, DoubleVerify’s Chief Innovation Officer knows a thing or two about navigating the digital wild west. In DoubleVerify’s latest Global Insights Report, they uncovered a nearly 20% surge in MFA sites, fueled by the rapid rise of AI-generated content.

The report reveals that MFA impression volume increased by 19% in 2023, with a staggering 73% jump in “Low-tier” MFA impressions. These sites, which blend MFA and non-MFA characteristics, are reshaping the internet faster than a Netflix show drops spoilers.

Using advanced AI technology, DoubleVerify analyzed over three dozen “High-tier” MFA websites, finding numerous instances of likely AI-written content, including examples like HeroInvesting’s Clint Eastwood aging article and Noteabley’s Best Steakhouses list. These sites often bombard users with ads, making the user experience as pleasant as navigating through a maze of pop-up ads in the early 2000s.

In this Q&A, Smith breaks down the complexities of distinguishing high-quality AI content from the low-tier junk flooding the internet. We dive into DoubleVerify’s sophisticated blend of AI and human review and explore how advertisers can protect their investments amid the explosion of MFA sites.

Join us as this ad tech luminary shares his insights and strategies for staying ahead in the ever-evolving world of AI-driven ad tech. Whether you’re an advertiser looking to make the most of your budget or a publisher striving to maintain quality, this conversation is packed with valuable takeaways.

Lynne d Johnson: Your report touches on the surge in MFA sites. However, the digital landscape often sees legitimate sites misclassified as MFAs due to their ad strategies or content distribution tactics. Can you explain DoubleVerify’s criteria for distinguishing true MFA sites from legitimate content sites that might superficially appear similar due to high ad-to-content ratios or aggressive monetization strategies?

Jack Smith: This is a great point, and thank you for raising it. When it comes to MFA content, we believe nuance and surgical categorization — not blunt, one-size-fits-all lists — are key to safeguarding advertiser investments and supporting quality publishers and, more broadly, the open internet.

We were the first verification vendor to really define MFA content in an effort to create a common yardstick from which to evaluate. While we have a clear overall definition — DV defines MFA sites as those whose sole purpose is to deliver advertisements — our definition also considers nuance. MFA sites can be identified by analyzing several factors across their ad monetization activities, ad traffic sources, and approach to content creation. That combination of criteria needs to be robust to properly distinguish content in a way that’s fair and equitable for content creators. 

With that in mind, DV’s approach allows for the deepest and most nuanced level of analysis, preventing miscategorization and false positives. For example, a website may feature a significant number of ads while still registering high rates of direct and search-enabled traffic. In this instance, the publisher would not meet our definition of MFA. For sites we do classify as MFA, we have a tiered system of high (more egregious examples), medium, and low. Advertisers can then make decisions on the tiers and how they best fit or don’t fit into their campaigns. For DV to classify a site as MFA, it really needs to consistently show high signs of arbitrage both in terms of heavy reliance on paid traffic and arbitrage traffic.

For DV to classify a site as MFA, it really needs to consistently show high signs of arbitrage both in terms of heavy reliance on paid traffic and arbitrage traffic.

Also, just as an inclusion or exclusion list-only approach doesn’t allow for nuance in categorization, we don’t solely rely on AI for classifying content. Algorithms can be biased just like people and are not infallible. To ensure protection and support publisher monetization, we blend AI with expert human review to help ensure that sites that don’t ultimately qualify as MFA content, including those owned by underrepresented groups or news publishers, are not incorrectly flagged. We also regularly audit our categorization criteria, which is critical as the space evolves quickly.  

As a result, publishers have embraced and supported our MFA solution. We also developed it with feedback from the community to ensure responsible and thoughtful categorization.

LdJ: With the report highlighting a 19% increase in MFA sites largely driven by AI-generated content, how does DoubleVerify differentiate between low-quality AI-generated content and high-quality AI content that might also be prolific in ad placements? Are there specific markers or technology you use to make this distinction clear?

JS: AI-generated content is an interesting topic because there is often a rush to judgment. Just as many rush to say all MFA content is fraudulent or bad, we’ve seen the same about AI content. Ultimately, AI-supported content can range from high to low quality. We’ve seen trusted publishers in the financial space, for example, rely on AI for quality reporting for years. AI can be an additive tool for quality journalism. 

At DV, for these reasons, we don’t automatically or bluntly label AI content as “bad.” However, we do believe it’s problematic when AI is used to create low-quality content at scale, while coupling that with a heavy reliance on paid and arbitrage traffic to take in ad dollars that would otherwise go to quality publishers. For instance, DV has found some sites that publish in excess of 1,000 pieces of content per day, powered by AI. That level of output usually comes at a cost to quality. We factor these considerations into our evaluations of MFA and quality more broadly.

As new Gen AI tools have emerged, tracking AI content can be a difficult task given its growing volume. To help us with this process, we built our own proprietary AI to detect and analyze replicated and AI-generated content across the web. In doing so, we also gain so much more data and signals to help better understand the use of AI in MFAs, but also fraud and other areas.

LdJ: Given the significant growth in ‘Low-tier’ MFA impressions, could you elaborate on the real-world impact this surge has on publishers and advertisers? How do these ‘Low-tier’ MFA sites specifically dilute the efficacy of digital advertising campaigns, and what measures can advertisers take to safeguard their interests?

JS: The growth of low-tier MFAs really speaks to the earlier topic you raised about nuance and categorization. What we classify as “low-tier” covers sites or sections with a blend of MFA and non-MFA content — for example, sites where only a section or a subdomain exhibits MFA content or characteristics. These publishers make up the highest percentage of MFA publishers, which highlights the need to have different tiers so they can be treated differently. 

Ultimately, we classify, and it is up to the advertiser to determine if MFA inventory aligns with their own performance outcomes and is suitable for their brand. However, by having this nuanced categorization, brands have the freedom and tools to decide if and to what extent they want their ads to be served on MFA sites.

LdJ: As AI technology evolves, so too do the strategies for generating and monetizing content on MFA sites. What are DoubleVerify’s plans for staying ahead in this technological arms race, particularly in terms of improving detection mechanisms and helping advertisers avoid these pitfalls?

JS: We heavily invest in R&D at DV, more than any other verification provider, and most other technology companies in our space. This emphasis on innovation has given us a substantial lead in the market, providing an edge over tech advancements that may negatively impact advertiser investments and transparency. This strategic focus ensures we anticipate future developments and adapt quickly.

Beyond the tech, the arms race in AI isn’t just about countering the technology itself — it’s also about aligning with a brand’s preferences for how advertising is incorporated into an environment. Effective policy plays a critical role in maintaining this alignment, ensuring that our solutions continually meet the evolving needs of advertisers.

LdJ: With the proliferation of MFA sites and AI-generated content, what are the broader ethical implications for the digital ecosystem? How does DoubleVerify envision the future of online content quality, and what role do you believe regulatory bodies should play in curbing the growth of low-quality, ad-centric platforms?

JS: This is a great question. AI-generated content is already subject to some regulation, and it’s inevitable that more regulations will emerge. As the technology improves, the regulatory landscape is likely to evolve and expand, which we support to help ensure the safety of the Internet.

Interestingly, these regulations often focus on end-consumer protection and enhancing transparency rather than directly curbing the creation of the content. This means that AI-generated content will continue to proliferate within the digital ecosystem. Even if it’s labeled transparently due to new rules or standards implemented by large tech companies, we, at DV, need to help advertisers navigate this growth. Our role is to support their ability to advertise safely and effectively alongside and around this content, but really any content, whether AI-created or not.

__

Jack is responsible for ensuring alignment between DV’s commercial and product organizations. He manages senior level product relationships with key customers, identifies new client-driven product opportunities and supports sales efforts. Prior to joining DV, Jack served as Global Chief Product Officer, Investment at Group M, where he developed products and platforms that empowered teams to make better decisions about where to invest over $80 billion of media spend. Previously, Jack co-founded the machine learning company Solariat, which was acquired by Genesys. He brings over 25 years of experience in executive strategy, technology, client and market insight to his role as Chief Innovation Officer. Jack holds seven patents in AI and machine learning for signal detection in natural language and the prediction of consumer media consumption.

The post The Rise of AI-Driven MFA Content: Insights from DoubleVerify’s Global Report appeared first on AdMonsters.

Generative AI (Gen AI) is revolutionizing digital advertising by enhancing efficiency in media buying and publisher monetization, enabling businesses to achieve unprecedented levels of efficacy and efficiency and optimized operations.

As the Director of Advertising at a forward-thinking media company, I’ve seen firsthand how this technology reshapes audience connections and drives business growth. Here are some tips and considerations for businesses to incorporate this technology and amplify growth.

Personalization That Truly Resonates

One of the most exciting aspects of Gen AI is its ability to create hyper-personalized ad experiences. We’re moving beyond basic demographic targeting by using AI to analyze massive amounts of user data. This reveals insights that allow us to tailor ads and content recommendations to individual interests, behaviors, and real-time contexts. Dynamic creative optimization, powered by AI, is a secret weapon. It autonomously generates and adjusts ad variations based on user interactions, making every impression relevant and engaging. This leads to higher click-through rates, improved conversions, and stronger ROI for our clients.

Media Buying, Supercharged

We’ve implemented AI-powered media buying platforms for real-time bidding, placement, and budget adjustments. This allows our team to focus on strategy and creativity, while the AI optimizes our campaigns for maximum efficiency and impact. Google Ads Gen AI tools now enable media buyers to create and test templates without the need for a designer and offer predictive analysis for informed decisions on churn, seasonality, ad performance, LTV, and pricing fluctuations. These advancements significantly improve campaign efficiency and effectiveness.

Agility in Real-Time

The digital world moves fast, and Generative AI gives us the agility to keep up. We can now adjust our ad and content strategies on the fly, reacting to the shift in user behavior or emerging trends in a matter of hours or even minutes. This level of responsiveness is essential for staying ahead of the competition and delivering results that consistently exceed expectations.

Overcoming Challenges, Embracing Opportunities

Of course, there are challenges to address. Organizations often face skill gaps, so investing in upskilling and reskilling programs and fostering a culture of learning and experimentation is crucial for Gen AI adoption. Ensuring data quality and compatibility with existing infrastructure is also essential. Despite these hurdles, the potential rewards are huge.

Ethical considerations are also very important. As publishers, we must responsibly steward user data, protect user privacy, be transparent about how the information will be used, and operate within ethical and legal guidelines to build trust with our audiences.

The Road Ahead

Generative AI is still in its early stages, but it’s already clear that it’s a game-changer for digital advertising. As we continue to explore its capabilities, I’m excited about the possibilities it holds for creating more meaningful connections with audiences, improving efficiency, driving business growth, and shaping the future of our industry. It’s time for all businesses to assess their current processes, stay informed about Gen AI advancements, and foster industry collaborations to maximize the benefit of utilizing this technology.

The post Generative AI: A Game-Changer for Digital Advertising appeared first on AdMonsters.

Pending publisher licensing deals with OpenAI aside, one part of the news organization finds generative AI extremely useful, and in some instances, transformative: the Ad Ops team. AdMonsters has interviewed numerous Ad Ops people across several organizations to see if and how they’re using it.

Reshaping Ad Ops With Generative AI

Ad Ops professionals aren’t just dabbling in generative AI; they’re diving in deep and successfully putting it to work to improve their daily jobs and elevate the overall Ad Ops team. It isn’t a surprise that they’ve largely sidestepped the challenges others have faced using generative AI. As tech-savvy people, Ad Ops professionals are well aware of the limitations of all AI and take active steps to mitigate the pitfalls and problems.

This Publisher Pulse looks at:

• • Popular generative AI tools used by Ad Ops team members
  • Ad Ops personas — distinct ways that interviewees use generative AI to elevate their performance or the performance of their teams
  • AI use cases
  • How generative AI will transform the Ad Ops Teams
  • Tips for getting the best results out of AI
  • Sample outputs

Enter your info to download your copy below!

The post AdMonsters Publisher Pulse: Ad Ops Reimagined — A Guide to Reshaping Ad Ops With Generative AI appeared first on AdMonsters.

In November 2023, OpenAI rocked the world when it released ChatGPT to the general public. The chatbot set imaginations on fire, promising to create articles, screenplays, poems, and other works without human intervention.

But when news organizations began experimenting with it, the results were mixed. Generative AI’s tendency to hallucinate has led to some embarrassing episodes for publishers. And, publishers are rightly concerned about large language models (LLMs) using their content as training data without compensation or credit.

But one part of the news organization finds generative AI extremely useful, and in some instances, transformative: the AdOps team. AdMonsters has begun interviewing AdOps folks across several organizations to see if and how they’re using it. 

If you’re in AdOps and are using it, we’d love to hear from you (contact us at Content@admonsters.com).

We will publish our findings as part of our Publisher Pulse series. In the meantime, we thought our readers would find some initial findings interesting.

AdOps + Generative AI: A Perfect Match

First and foremost, AdOps professionals aren’t just dabbling in generative AI; they’re diving in deep and successfully putting it to work. This isn’t a surprise; as tech-savvy people, AdOps folks are well aware of the limitations of generative AI and take active steps to mitigate the pitfalls and problems. 

To begin, they’re versed in the emerging field of prompt engineering (some have even taken the Coursera class in it), so they know how to query the LLM tools in ways to receive accurate and appropriate responses for the task at hand, whether that’s generating code for an ad fix or creating emails that speak more directly to the background of the recipient.

They also double-check all responses to ensure accuracy. The prompt bar of every LLM includes a warning against incorrect information, and AdOps people heed that warning.

Elevating the AdOps Team

We anticipated the interviewees to describe how generative AI helped them manage their time better, taking on the grunt work and freeing up time for big-picture thinking. To be sure, that’s happening; AdOps team members use generative AI to glean insights from campaign data, troubleshoot ad issues, create HTML templates, and insert campaign data into matrices for reports, among other repetitive and time-consuming tasks. 

AdOps folks also use AI to create training tools and resources for new hires. For instance, users can upload a training deck to Claud.ai, and it will create a script that explains things like how to create a deal ID. 

Elevating the Individual

AdOps teams also use AI in ways we hadn’t imagined, such as polishing their communications to coworkers and clients to elevate themselves, as well as their teams. For instance, ChatGPT is helping a harried analyst sound less brusque and overly direct in emails to clients, and a director of programmatic ad sales we interviewed uses it to get a deeper background on a client’s industry so that emails come across as more dialed into the recipient’s needs. 

In both of  these instances, AI helps AdOps sound more human, relatable, and empathetic. We love the irony of people using machines to sound more human.

An Omnivore Approach to Generative AI Tools

We asked the interviewees which AI tools they use, and their answers are pretty much anything they can get their hands on: ChatGPT, Gemini, Claud.ai, Perplexity.ai, among others.

What’s more? They can explain the subtle differences between each, such as when each model was last trained and which has the most recent data. They also have tips for using these tools to get the best results (which we’ll share in the Publisher Pulse so stay tuned).

The AdOps Team of the Future

While generative AI has been largely overhyped, it will undoubtedly transform the AdOps team in significant ways.

As Jared Collett, Sr. Director of Ad Operations and Analytics at Major League Fishing explained, “Generative AI drastically reduces the mundane tasks of writing and rewriting proposals, emails, procedures and so much more. It is an amazing assistant to bounce coding solutions off of as well. With all this (and more) I can focus more on revenue growth and product development, while my team can focus more on being proactive and doing more for our direct sold clients.”

We Want to Hear From You

Are you using generative AI to help you work more efficiently? We’d love to hear from you. Please send an email to Content@admonsters.com and we’ll schedule a 15-minute interview.

The post The AdOps Team of the Future appeared first on AdMonsters.

The rapidly evolving landscape of AI and its integration into the publishing sector was the highlight of AdMonsters recent discussion with Burhan Hamid, a pivotal figure in the media and ad tech ecosystem.

Hamid’s journey — from his extensive experience in data engineering and media to his passion for specialty coffee roasting to leading innovations at Time.com — underlines his distinctive approach to technology and media and also shapes his viewpoint on the intersection of AI and publishing.

Before diving into the main event, AdMonsters Content Manager, Yakira Young, and Hamid held a lively discussion about virtual kitchens and fusion cuisine, as well as Hamid’s obsession with coffee. That passion led him to learn everything about the origins of roasting coffee, from learning how to roast coffee himself to launching a coffee editor and running that business out of his brother’s virtual kitchen in Maryland.

But guess what? Hamid doesn’t drink coffee. “Some people who know me might be surprised by this, but I drink tea every morning. I have something called Chai every morning. My body handles tea a whole lot better than it handles coffee. So I save the coffee for special occasions,” he shared.

Introduction to a Tech and Media Visionary

Young also asked him which song best describes his leadership style, to which he responded Incubus’, “Are you in?” “The words in there are really, ‘It’s always better when everyone is in.’ And that’s my leadership style,” he explained. “I like to have everybody commit and be collaborative and all in on the work they’re doing. We have a small but really close team, where everybody is in.”

Considering over the past six months Hamid built a data engineering and martech team from the ground up to re-platform TIME.com,  he really needed a lot of teamwork to make the dream work — rejiggering the front end, back end, and pretty much all of the infrastructure.

Reflecting a deep-seated curiosity and a knack for innovation, Hamid set the stage for his insights into the AI realm, where his dual roles in tech and media provide a balanced viewpoint on emerging technologies.

AI in Content Personalization and Recommendation

A key focus of the discussion was the role of AI in personalization and improving content recommendation, areas where Hamid’s team has been pioneering at TIME. He highlighted his team’s efforts in employing machine learning to enhance user experiences, emphasizing the potential of generative AI to revolutionize content creation and delivery.

Addressing AI Challenges and Ethics

However, Hamid also addressed the challenges and ethical considerations in deploying AI, particularly in content authenticity and verification. The conversation delved into the complex relationship between AI technologies and the journalistic content they rely on, emphasizing the need for licensing and attribution models to maintain integrity and trust in journalism.

AI Misconceptions and Workforce Impact

Addressing common AI misconceptions, Hamid emphasized that AI tools are meant to augment human work, not replace it. AI, he says, enables more effective and efficient work. He envisions AI as a democratizing force in knowledge access, democratizing information beyond traditional search engines.

Looking Ahead to PubForum Austin

Hamid expressed excitement to delve deeper into AI’s ethical considerations and practical applications across various media roles in his upcoming keynote at PubForum Austin, during his keynote, The Publisher’s AI Advantage: Leveraging the Power of AI to Stay Ahead of the Curve. His collaborative leadership style, inspired by the ethos of the song “Are You In?” by Incubus, promises a session of engaging and insightful discourse.

The post #PublisherPOV: Leveraging the Power of AI w/ Burhan Hamid, SVP, Data, Product, Engineering at TIME appeared first on AdMonsters.

Amid their lawsuit against the NYT, OpenAI faces privacy scrutiny in Europe after a multi-month investigation into ChatGPT’s data collection methods. Italy’s Data Protection Authority gave OpenAI 30 days to respond to the allegations. 

Critics have called out generative AI’s spread of misinformation and data privacy concerns for quite some time. There are also concerns about deep fakes — such as using artists’ voices to create new music or the horrific fake explicit images of American pop princess Taylor Swift.

This technology is evolving much faster than regulation can control. But regulators like Italy’s Data Protection Authority are working to ensure we can all reap AI’s benefits while complying with data ethics. 

As Italy’s privacy watchdog readies its case against OpenAI and OpenAI prepares its response, it could set new precedents in AI regulation standards. 

A History of Data Collection Misfires and the Lawsuits They Bore

Should the EU court confirm the breach, OpenAI faces a potential €20 million fine, or up to 4% of global annual turnover. Beyond financial penalties, data protection authorities can mandate changes in a company’s data processing methods for violating privacy laws. This could lead to altered data collection practices or even cessation of the tech’s usage in regions where they enforce compliance.

Given its history with legal challenges over its data collection practices, OpenAI is no stranger to the intricacies of AI data handling. This includes the notable lawsuit brought by The New York Times for allegedly using copyrighted data to enhance their chatbot’s intelligence. 

Attorney Justin Nelson, representing the New York Times in the lawsuit, accused OpenAI of “building this product on the back of other people’s intellectual property. OpenAI is saying they have a free ride to take anybody else’s intellectual property since the dawn of time, as long as it’s been on the internet.” 

In both cases, OpenAI responded that the lawsuits were without merit — a big shocker. In the case of the NYT lawsuit, OpenAI released a public statement saying that using publicly available internet materials is fair use. 

In response to Italy’s DPA, they said, “We believe our practices align with GDPR and other privacy laws, and we take additional steps to protect people’s data and privacy. We want our AI to learn about the world, not about private individuals. We actively work to reduce personal data in training our systems like ChatGPT, which also rejects requests for private or sensitive information about people.” 

The Regulatory Perspective and the Implication for the Ops Industry

Last year, Italian authorities raised GDPR concerns about OpenAI, temporarily banning ChatGPT’s local data processing. The March 30 provision cited issues like the lack of a legal basis for personal data collection, AI’ hallucinations,’ and child safety problems. The authority suspected GDPR breaches in Articles 5, 6, 8, 13, and 25. 

AI regulators are fighting tooth and nail for industry-wide standards, and no sign of their momentum stopping. For example, the FTC launched a new inquiry into five major AI players investigating how their investments and partnerships impact competition — Alphabet, Amazon, Microsoft, Anthropic, and OpenAI. More specifically, the FTC is examining “whether tech giants are using their power to trick the public, and whether the AI investments allow giants to ‘exert undue influence or gain privileged access’ to secure an advantage across the AI sector.”

“Just as we’ve seen behavioral advertising fuel the endless collection of user data, model training is emerging as another feature that could further incentivize surveillance,” said FTC chair Linda Kahn. “The FTC’s work has made clear that these business incentives cannot justify violations of the law.”

As the Ad and Rev Ops industries prepare their AI capabilities, and I know they are, they must also be cognizant of the potential pitfalls of using this technology. Mark Sturino, VP of Data and Analytics, Good Apple, said at his Keynote address at AdMonsters Ops in 2023 that publishers can differentiate themselves by utilizing AI technology to provide insights and transparency. Still, they must be careful in using AI to create targeted audiences. 

“AI is playing more of a role from a publisher selection perspective. At least at Good Apple, it is less and less about flash, and it’s more about the actual results you’re giving us because everybody will be judged based on performance,” said Sturino.

The post ChatGPT Under Fire for Allegedly Violating EU Privacy Laws appeared first on AdMonsters.

In 2023, Generative AI was the new kid on the block, and everyone wanted to see what all the hype was about. There were ups and downs with experimentation, regulation, and practical use, but industry experts predict that digital media can use AI to its full potential if we learn to use it responsibly. 

However, if publishers and advertisers want to take full advantage of what generative AI offers, they must put in the work. As Jeremy Haft, Chief Revenue Officer, Digital Remedy, said, “2024 marks a pivotal year as the buzz surrounding Generative AI transforms into tangible actions within the advertising industry.” 

There are still some kinks to work out. The New York Times just sued OpenAI for copyright infringement and we are still trying to get a hold on these chatbots. 

Will Generative AI initiate an iRobot-style takeover? Most digital media experts don’t think so. However, more brands plan to integrate the tech into their workflow. Here’s how experts say it will happen: 

AI Will Evolve Marketing Roles vs. Taking Them Away

Trend # 1: When Generative AI first popped on the scene, fearmongers predicted that they would take our jobs. But here, our experts predict that it will enhance them. 

“Brands and agency leaders will leverage this technology actively. Generative AI’s increasing integration across the programmatic supply chain is poised to enhance operational efficiencies, reduce performance lag, and minimize spending waste. Its true impact enables brands to extract and act upon more robust real-time insights. With emerging AI tools, advertisers gain unprecedented flexibility in querying and applying insights, unlocking new possibilities beyond the capabilities of traditional machine learning.” – Jeremy Haft, Chief Revenue Officer, Digital Remedy 

“AI enables marketers to evolve their organizational roles by streamlining workflows and enhancing efficiency. While AI is a powerful tool, it still requires human oversight. For example, we’ll see content creators transition into more of an editing and curation role, collaborating with AI to easily produce content that resonates with target audiences. Meanwhile, roles like SEO managers will integrate AI as a core responsibility, leveraging Generative Search Experience technology for improved search visibility and user experience, ensuring efficient and effective strategies. This relationship between AI and human expertise will define the future of marketing roles.” – Monica Ho, CMO of SOCi

“In 2024, agency roles will undergo a significant transformation shaped by AI and technology. This shift necessitates completely reconfiguring skill sets and structures across industries and channels. Agencies embracing AI and automation will thrive by leveraging these technologies to analyze vast amounts of data, predict trends, and craft targeted strategies that auto-optimize across channels, KPIs, etc. Meanwhile, brands aiming to conquer contentious terrain will blend technology with deep cultural insight and empathy. The key lies in merging technological insights with authentic storytelling, allowing agencies to embrace innovation and forge meaningful connections with target audiences.” – Oz Etzioni, CEO and Co-founder of Clinch 

“AI is in its ‘Napster moment’ and is here to stay, so Publishers should learn how to weaponize it rather than fight it. The NYT just hired a dedicated editor for all things AI. I am excited to see how a ‘model digital news publisher’ like the New York Times sets the pace for AI. There have been some negative headlines, but I believe ‘AI for good’ exists in our industry. I am excited to see how the NYT will evaluate and implement it to enhance user experience while empowering staff to do more while maintaining journalistic integrity. There is a lot of busy work behind the scenes that AI could be adopted for while making life easier for staffers in multiple departments, whether it’s rev ops, ad ops, video creation, program analysis, consumer marketing, or sales intelligence. ” – Adam Hua, Co-Founder, Aeon 

AI V. Fraud: Who Comes Out on Top? 

Trend #2: The digital media industry has been fighting against fraud for decades, but will AI be the new tool to hinder these bad actors from carrying out their treacherous plans? Last year, we saw companies like IAS and DoubleVerify using AI to detect MFA sites, and our expert sees this trend continuing.  

“AI will continue to be a valuable content tool for advertisers, scaling dynamic content creation and enabling unprecedented content marketing. The rise of new-gen AI tools like ChatGPT and Anthropic has made creating content more cost-efficient and manageable overall, especially for global brands. The challenge is that we see the flip side of that value proposition, with bad actors leveraging these tools to build content farms and MFA sites, posing a significant problem for the digital ad supply chain and media quality. Fortunately, AI serves as a counterweight here, enabling more AI-powered review and classification of content to scale verification and ensure media quality and performance.” – Dan Slivjanovski, CMO, DoubleVerify

Brands Need to Give up Some Transparency to Realize AI’s True Potential

Trend #3: We always discuss transparency in ad tech, but are we ready to be vulnerable with AI technology? Our next experts believe we must be more transparent with AI to utilize its full capabilities. 

“The industry has grappled with many transparency-related issues, from brand safety concerns to outright fraud. So, it’s understandable that increased automation – through the adoption of AI – would raise concerns. But right now, those concerns are holding back progress – a realization many brands will need to come to in 2024. Just as consumers accept that self-driving cars work without exactly understanding how brands and agencies will have to accept some opacity to elevate their ad strategies and harness the true power of AI. That doesn’t mean brands should abandon due diligence or testing, but marketers will eventually have to relinquish the concerns of not seeing the AI ‘think.’ Advertisers that can embrace this testing methodology and evolve their adoption of AI will separate themselves from the pack.” – Patrick Gut, VP, US, Adlook

“At Forbes, we’re focusing on three core ideas around AI: how it can help engage readers, improve journalists’ workflow efficiency, and power new products across all of our various platforms. Most recently, we released our AI-powered search, Adelaide, which allows our audience to use conversational AI to search across the site.

The importance of a human-led approach to AI will also build in 2024 as we collectively continue to learn that using AI to better our current business practices (and people), rather than replace them, is paramount. As brands develop AI-powered experiences in content and advertising, using AI efficiently will build trust and bolster retention, with both users and brand partners benefitting. Advertisers will want to align with AI contextually and holistically, having it integrated into the products and experiences they are purchasing. Transparency will be critical and draw partners to those with a thoughtful, human-centric embrace of this game-changing technology.” – Alyson Williams, SVP, Digital Operations & Strategy, Forbes

AI or Not AI? That is the Question

Trend #4: Everybody wants to be AI nowadays. At least, according to our next expert, who sees a trend where brands are labeling basic automation as AI. Although he’s not alone, in preparation for CES in Las Vegas, Dipanjan Chatterjee, VP and principal analyst at Forrester, raised the same concerns. 

“In the whirlwind of AI developments this past year, the rise of generative AI has left skeptics scrambling to catch up with the tech-savvy crowd. Critics dismissed it as a mere gimmick, but it has become a hot commodity, with individuals and companies alike eager to ride the AI wave for a boost in sales. Some have even taken creative liberties, labeling their basic automation processes as cutting-edge AI. Prepare for an onslaught of “AI capabilities” becoming the latest buzzword for ad tech companies, whether genuinely AI-driven or just a touch of tech glitter.”  – Jared Collett, Senior Director of Ad Operations, Major League Fishing  

*This content was written by Jared Collett and edited using Chat GPT*

The Year of Responsible AI

Trend #5: Since generative AI is relatively new, in 2023, we saw it go through some learning curves. For example, OpenAI has a pending New York Times lawsuit that called them out for using copyrighted material to train AI models. Our expert predicts that in 2024, AI ethics will be all the rage. 

“If 2023 was the year of Generative AI, 2024 will be the year of Responsible AI. Amid all the excitement, experimentation, and more than a few warnings about an AI-driven extinction event (bah!), few marketers had the time to pause and ask the hard question about the risks of AI for their company and their customers. That’s about to change as more marketers turn their attention to Responsible AI – and that’ll be a good thing for individual brands and the entire industry.

In practice, I’d expect marketing organizations to put a premium on guidelines, governance, and standards. Ethical stances and brand safety will be front and center, as it hits home that the marketing end-user – not the model or app provider – is the last (and maybe even first) line of defense regarding the responsible use of AI technologies. As more brands stand up and scale up marketing AI programs, ad hoc experimentation will give way to objective-driven, strategic implementations. Companies will deploy AI in ways that deliver value to them while reflecting the values of the company and (this is critical) respecting the consumer’s rights. In the end, 2024 will be the year marketing AI starts growing up – and responsible AI practices will be at the center of this vital evolution.” – Greg Verdino, Principal Analyst and Founder, CognitivePath Research, Inc.

“Perhaps even more impactful will be the role of governmental regulation and legal challenges on grounds of intellectual property infringement. While fair use precedents and the nature of the technology behind generative AI make it unclear how claims like the recent New York Times lawsuit will pan out, it seems inevitable that AI companies that profit from the intellectual property of others will need to figure out licensing deals to continue to operate legally. Such changes will eventually impact the consumer, whether in increased prices or reduced availability of some types of generated content.” – Kyle Alan Hale, Solutions Architect, Rightpoint

“In 2024 synthetic data will replace a majority of the human-generated, human-labeled data that is currently used to train AI models. That’s because it is faster, cheaper and easier to generate synthetic data to train a model than it is to source, curate, clean and label real data – and since it’s synthetic there is no private data embedded in it, making it automatically compliant with GDPR, HIPAA and a host of other regulations.” – Dave Matli, CMO, Nurdle AI

Let’s Get Personal

Trend #6: The digital media industry is always looking for better ways to tailor content to consumers’ needs, and our next expert believes AI will do just the trick. 

“We can also expect to see publishers creating endless personalized content, accounting for the nuances of tone and style. Forget one-size-fits-all content. Generative AI will enable publishers to personalize articles, videos, and newsfeeds. Publishers can also serve content to the narrowest, most valuable audience segments, building readership and making a sticky user. Imagine a world where all the content you read is written in your preferred style, tailored to your specific location and current events. This level of personalization has the potential to redefine reader engagement and loyalty.” – Michael Persaud, Head of Programmatic, a360media

The post The AI Takeover: AdMonsters 2024 Generative AI Predictions appeared first on AdMonsters.

2023 felt like the beginning of the end. It was like the perfect maelstrom.

A recession was forecasted. Oh no, no it wasn’t. Ad spend was plummeting. Oh wait, it started inching back up again.  For publishers, there was just no way to make heads or tails out of the year that was the last before the 3P cookies’ demise.

Political ad spend is on the rise, but there are ad quality challenges for any publisher wanting to jump into that pool. We’ve got a playbook for navigating those waters.  Targeting and metrics are getting a remix and creative could use a facelift. We’ve got a playbook to guide you through attention’s dominance.

What about bad ads, are they tarnishing consumers’ perceptions about your media properties? We surveyed 250 consumers to give it to you straight — along with publishers’ tips for cracking down on those bad actors and making the user experience a priority.

And finally, we took a deep dive into how widely contextualized AdOps data shared with sales and ad product teams. The truth is, AdOps teams are rock stars (party on) but sales teams might not be taking full advantage of their data stardom. We’ve got a playbook for that too. All it involves is making meaningful workflow changes to focus on revenue-generating tasks.

You really should download one of these (if not all of them).

AdMonsters Publisher Playbooks of 2023

AdOps Are Rock Stars. Are Sales Teams Taking Advantage of Their Stardom?

AdOps teams are data superstars, sitting on a treasure trove of information that contains rich and nuanced context. Many can say which ad units perform best, by format, section, industry and vertical. Some can accurately predict the ROAS advertisers can expect to see from their campaigns.

This is the kind of data that attracts advertisers, especially during a recession when their budgets are smaller and all focus is on performance and business outcomes.

But are publishers taking full advantage of these amazing resources? Our survey indicates they are not. There’s not enough collaboration between AdOps and the sales, product, and business intelligence teams. This is caused by a combination of tech limitations and interdepartmental inefficiencies.

More worrisome, only 22% of AdOps teams say they have access to a wealth of data and insights, which means the remaining 78% can’t help their colleagues succeed in their jobs to the fullest possible extent.

Now that advertisers are cutting back on campaigns, publishers need to work harder to attract brands to their sites. Detailed performance data distributed to all the teams that need it can help publishers win more business and revenue. As it stands, they’re leaving money on the table. Download this playbook now!

How Bad Ads Affect Consumer Perception of Publishers

Publishers have always struggled with bad ads. Nefarious players and scammers, who sought to exploit the digital advertising ecosystem to steal money or data from consumers, have been around almost since the first ad was placed.

But as the world became more digitized, and as global wealth (and access to it) went online, bad actors stepped up their game. Online scams beginning with a digital ad are now dizzyingly complex, with fraudsters going to great lengths to appear legitimate to their victims.

Not surprisingly, malvertising is now a major crime, with 46% of consumers saying they, or someone they know, has fallen prey to a scam. According to the FBI, American consumers lost $10 billion to online scammers in 2022, and 2023 promises to be an even worse year for consumers.

Malvertising and malware are upending digital advertising, with the FBI warning consumers to install ad blockers, and the New York Times telling its readers that “if it’s advertised, you probably shouldn’t buy it.”

Programmatic advertising burst onto the scene in the mid-2000s promising better monetization opportunities for publishers and better access to audiences for brands. That promise led to a robust industry; in 2022 global revenues topped $173.74 billion worldwide.

The scales have tipped, and programmatic has become more of a liability than an asset. Last year, Bloomberg News made headlines when it announced it was pulling the plug on open programmatic, citing bad ads and the impact they had on the reader’s experience.

They’re hardly alone. Jared Collett, Sr. Director of Ad Operations and Analytics, Major League Fishing, also said his company changed who they work with as a result of bad ads. “We’ve had to sever relationships with various programmatic partners and ad networks because they couldn’t get control over the bad ads they were sending us. I would rather serve a house ad, or no ads than serve a bad ad.”

Worse, bad ads are eroding consumer trust in publishers. For 77% of consumers, a bad ad is a signal that the publisher cares more about making money than it does about their safety. Another 64% say that seeing a bad ad on a single site tarnishes the entire industry. It’s fair to say we’re at a crisis point.

“This finding is really important. It brings home the point that rightly or wrongly, the reputation of the advertiser and the reputation of the publisher are really tied together. This is something media organizations will need to address.” said Amnon Siev, CEO, GeoEdge. Download this playbook now!

Targeting and Metrics Evolution: Are Publishers Ready for Attention’s Dominance?

Our survey results reveal that 2024 promises to be a year of rapid innovation, with publishers rethinking what’s possible:

The New Metric: Attention. As the digital advertising landscape undergoes transformations that limit the use of traditional identifiers, publishers are adapting their measurement practices to meet their advertising clients’ expectations. Driven by advertising demand, 82% of publishers said that attention metrics, which evaluate the amount of attention a consumer spends with content, are important or very important to their organizations. We see new metrics emerging, and publishers reporting some success, but new tools and education are still required.

Innovative Ad Formats & Ad Placements. Publishers are realizing that there is a significant opportunity to drive higher attention rates by experimenting with new and innovative ad formats (45%) or ad placements (55%), signaling a new era in which the advertising sector turns its focus from innovating in targeting to innovating in creative and placement.

Targeting Capabilities. While cookie-based targeting was mediocre at best, it did enable advertisers to scale their campaigns and develop proxies for their ideal audiences. Today, however, publishers are seeking privacy-compliant ways to home in on receptive audiences. Key among them: leveraging their first-party data.

Indirect Monetization. Some publishers appear open to granting permission for indirect representation of their inventory, allowing marketers to access approved pathways via ads.txt and other sources, even from non-direct partners. To maintain and optimize the list over time, publishers implement monitoring, regular communication, audits, and data analysis. This ensures a strong ecosystem of indirect partners, maximizing monetization while maintaining control and quality assurance. Download this playbook now!

Navigating Political Ads for the 2024 Season

A staggering $10 billion will pour into the political advertising arena to sway American voters during the 2024 Election cycle. While $10 billion is a boon for digital media stakeholders, that money comes with severe risks.

Navigating misinformation and disinformation will be a key challenge of this election cycle, driven by the widespread availability of sophisticated AI tools. Digital publishers and CTV stakeholders face direct and negative effects on their business, from drops in user engagement to broader societal mistrust.

The proliferation of generative AI, deepfakes, and sophisticated malvertising tactics have empowered fraudsters and foreign governments to distribute deceptive ads via programmatic channels. This alarming trend has forced digital media entities into a rapid and rigorous process of establishing, overhauling, and strictly enforcing political ad quality policies.

Ultimately it falls to publishers to serve as the final bastion of defense for their audiences. Publishers must undertake the critical task of determining whether specific advertisers and promoters of sensitive, hot-button issues can be permitted to run ads on their sites and under which conditions, while simultaneously ensuring malicious actors are kept at bay.

This Playbook provides a robust framework for an ad quality strategy, essential for setting up robust election advertising guidelines. It delves into the tools available to publishers for increased visibility and control, shedding light on challenges in the upcoming election cycle. The Playbook’s goal is to empower publishers to guarantee that political ads on their platforms are informative and accurate and enhance both user experience and their reputation. Download this playbook now!

The post AdMonsters Publisher Playbooks of 2023: Political Ads, Attention Metrics, Bad Ads, Ad Ops Are Rock Stars appeared first on AdMonsters.