This new era of journalism is sticky for publishers. They are currently faced with revenue loss, layoffs, and much more since tech giants are prioritizing clicks over quality content. They invest heavily in creating reliable information, yet the rise of AI-fueled search results threatens to divert traffic away from their sites, potentially cutting off vital revenue streams. 

To stay afloat, publishers continue to focus on diversifying their revenue streams. From launching e-commerce platforms to fostering vibrant online communities, they are rethinking their strategies to build stronger, more direct relationships with their audiences. This shift not only helps mitigate the risks posed by AI-driven search engines but also enhances brand safety and boosts audience lifetime value. By embracing these changes and prioritizing community engagement, publishers can create sustainable business models that support quality journalism.

We spoke with Max Weiss, OpenWeb’s Chief Strategy Officer, about his work at OpenWeb, how the new era of digital media is affecting publishers, and ways they can thrive in this new norm.  

Andrew Byrd: Can you walk me through the work you do at OpenWeb?

Max Weiss: OpenWeb is on a mission to build a healthier open internet. We do this the best way we know how: by building innovative technologies that turn content creators (publishers, brands) into the hosts of thriving, healthy communities. Our best-in-class moderation tech leverages AI to keep those communities healthy and engaging, bringing data and revenue to publishers. Today, we work with more than 5,000 top-tier publishers, hosting more than 150 million active users each month.

As the Chief Operations Officer, I collaborate with our CEO & founder, Nadav Shoval on our mission to help the media industry thrive on the open internet (simple, right?). On a day-to-day basis, I spend a lot of time meeting with leaders in the media industry and working with my teams (product, partner success and trust & safety most often) to help them solve their problems, from audience retention to addressability.

AB: How has the media industry evolved recently, and what are the main challenges publishers are facing today?

MW: Even for an industry marked by constant change, the past year has been eventful. We’ve seen a lot:

• Huge advances in AI changing everything from traffic sources to staffing needs.
• Dramatically falling search and social media referral traffic.
• Google’s flip flop on deprecating third-party cookies more times than I care to recount. 
• Slow-moving but advancing government regulations.
• New social channels for reaching and engaging audiences (which tends to further distract publishers and drain their resources).
• And more…

All together, this means many publishers face risks to their bottom line. There’s a widespread acknowledgement that they need to diversify revenue streams. That’s where we come in – we believe, as do an increasing number of publishers, that building a strong, loyal community is the best way to push back against the tide.

AB: Can you elaborate on the importance of diversifying revenue streams for publishers and how it can impact their sustainability?

MW: From ecommerce and events to entirely new and productized verticals (like for instance, WSJ’s Buy Side and recipes vertical), publishers are doing so much to diversify their revenue. These initiatives are most successful when they’re built on top of a thriving, loyal community — one that congregates around the publishers’ content, most commonly in the comments sections. That community of users and super users multiply the impact of everything else a publisher does to diversify revenue. After all, if a publisher launches a store, who do you think is buying the t-shirt or hat with the publishers’ logo on it?

To get there, publishers need to change their mindsets. They need to begin to think about their content at the beginning of a conversation and themselves as the host of that conversation, rather than simply posting content to social media or their website. We’ve seen it work countless times. A strong community increases time on site, pages per session and return traffic — and increases revenue.

AB: How is AI influencing search results, and what are the potential benefits and drawbacks for publishers?

MW: AI-powered search is just the latest example of how tech companies are taking publishers’ content, monetizing it, and then keeping that new revenue for themselves.

AI-powered search is an existential threat to publishers as it cuts them off from any form of revenue they would generate from web traffic. 

At worst, this is a zero-sum game: AI results keep traffic on search engines themselves, and away from publishers. But publishers are pivoting and building direct traffic streams to rely less on SEO and more on strategies that use 1:1 relationships with users to bring traffic directly to their own sites. By turning inward, publishers will be able to focus on what they do best – fostering and hosting communities around content –something an AI search summary can never do. 

AB: Can you explain the role of community engagement platforms like OpenWeb in helping publishers build a community of registered users?

MW: OpenWeb provides publishers a tailored and unique community engagement experience. The community is similar to a social media platform, all hosted directly on their properties. OpenWeb fosters engaged conversations around topics that matter, in turn, building loyalty with their readers.

A staggering 88% of online users won’t return to a site if they have a bad peer-to-peer experience. In short: negative interactions can cause readers to completely write off a site, even if they aren’t part of the conversation.

Healthy community drives more registrations by converting passive readers into engaged and registered users. Online, engaged communities can help publishers make more revenue from their readers, by making their site a destination and engaging with users. 

AB: How can publishers balance the need for premium inventory with ensuring brand safety and focusing on audience lifetime value?

MW: Thanks for this question. This is one of the things we at OpenWeb have spent years working on. Publishers can increase LTV and maintain high levels of engagement by hosting a community — starting with comments. That has been known for decades, at this point. But starting in the mid-2010’s, brand safety and suitability were called into question. 

As a result, publishers got out of the habit of interacting with their users on their own properties, and outsourced those community-building efforts to the social platforms. But, with advances in AI and Machine Learning, it is now not only possible but profitable for publishers to host healthy, engaged communities at scale. Quality conversations are one of the best ways to transform casual visitors into loyal users who drive more engagement, spend more time on-site, and are more likely to return over time — that’s LTV.

The post The Shift to Community-Driven Revenue in Digital Publishing a Q&A with Max Weiss, OpenWeb appeared first on AdMonsters.

As Google’s Android Privacy Sandbox gears up for its anticipated 2025 launch, mobile marketers need to stay ahead of the curve. Remerge, a leading Demand Side Platform (DSP), is at the forefront of this transition, collaborating  with Google and other ad tech partners, such as Verve, AppsFlyer, Adjust, and Singular, to ensure a seamless shift. Luckey Harpley, Staff Product Manager at Remerge, sheds light on what this means for the future of mobile marketing and how to navigate this new landscape.

Why Is Mobile Marketing Shifting to Privacy-First Advertising?

The rise of AI and sophisticated machine learning algorithms showcases the benefits of new technologies, but it also highlights the dangers of these advancements. People want more control over how big tech businesses manage their data. The advertising world is moving towards a privacy-centric future and marketers must adapt.

Apple made the first privacy move on mobile with the launch of its App Tracking Transparency (ATT) framework in 2021. Google’s answer is the Privacy Sandbox, a set of APIs to facilitate the selling, buying, and targeting of in-app ad placements, without requiring third-party cookies in Chrome or cross-app identifiers on Android. For Android, this will provide tracking and reporting via its Attribution API, targeting through Topics and Protected Audiences APIs, and data collection and handling via the SDK Run Time.

Why are DSPs Like Remerge Already Working on Solutions for the Android Privacy Sandbox?

It’s important to avoid a situation like the ATT rollout, where advertisers and publishers were left in the dark before its launch and struggled to understand how to run campaigns after it came into effect.

We want to ensure everything is ready for mobile marketers to run privacy-compliant advertising campaigns on Android without experiencing a drastic decline in performance. Android maintained its position as the leading mobile operating system worldwide in the first quarter of 2024, with a market share of 70.7% so this transitional period is crucial for the well-being of the mobile marketing ecosystem.

Does Google’s Decision to Keep Third-Party Cookies on Chrome Change Anything?

Google recently announced that they no longer plan to deprecate third-party cookies on Chrome and emphasized giving users the choice to opt-in to tracking. This update is unrelated to mobile. A similar approach is likely to happen on Android, where the GAID remains intact, and users can choose whether to share this with advertisers. In this scenario, nothing would change for mobile DSPs and their investment into Google’s APIs – the Android Privacy Sandbox would remain an essential framework for privacy-preserving advertising campaigns.

What Has Remerge Tested and Why Should Mobile Marketers Take Notice?

Remerge’s Research and Development team has been working on the Sandbox for over 1.5 years. They’ve focused on testing the Protected Audience API, which will allow advertisers to run retargeting campaigns on Android.

Tests have been completed with Mobile Measurement Partners (MMPs) like Adjust, AppsFlyer, and Singular. This includes developing a proof-of-concept for Custom Audience Delegation, a mechanism required for remarketing in Sandbox. This allows an MMP SDK to add users to custom audiences on behalf of advertisers based on their in-app behavior. Additionally, the first DSP/SSP on-device bidding test was conducted with Verve. These are small steps but important milestones for Sandbox testing, demonstrating that the Protected Audience API and custom audiences mechanisms are working as planned and validating product capabilities.

How Will a Mobile Marketing Manager’s Life Change When the Sandbox Rolls Out?

Advertisers won’t experience a considerable change in the buying process. At Remerge, marketers will continue to share their user data, desired campaign segmentation, and budget with the Account Management team as usual. Remerge will still be able to target users according to activity within an advertiser’s app and run creatives such as static and video. There’ll be no changes to CTR and CPX reporting, and for ROAS reporting, the data will likely have limited dimensionality, focusing on campaign and country-level reporting.

Google and its partners are doing the heavy lifting on the technical setup. Compared to ATT, the Android Privacy Sandbox is not only far more powerful with its targeting capabilities but also much more complex. This is a completely new tech stack with privacy-preserving mechanisms, and while we might see some performance dips initially, the long-term benefits are expected to be significant.

What About User Acquisition (UA) Campaigns?

While the focus has been on retargeting and the Protected Audience API, the Protected App Signals is supporting UA on Android. Although no industry players have made proposals on the Protected App Signals API yet, advertisers should reach out to their UA partners to discuss their plans.

What Can Mobile Marketers Do Right Now?

Advertisers should start finding a partner equipped to run mobile marketing campaigns on Android. Early adopters like Remerge, who have helped shape components of the Privacy Sandbox framework, will be well-positioned to hit the ground running when it launches.

The post What Should Mobile Marketers Know About the Android Privacy Sandbox Launch? appeared first on AdMonsters.

The streaming wars are  entering a new generation, marked by Paramount’s potential revival through Skydance and the emergence of unconventional social media entrants like LinkedIn, X (formerly Twitter), and TikTok. 

Increased merger and acquisition (M&A) activity is also shaping the advertising space as legacy media players adapt to shifting consumer preferences toward streaming. This transformation underscores the growing complexity of the media landscape and the necessity for advertisers to diversify their campaigns and reach their audiences effectively.

The revival of Paramount through Skydance exemplifies how traditional media companies are reinventing themselves to stay relevant in the streaming age. Skydance, known for its high-quality content and production capabilities, can potentially breathe new life into Paramount’s streaming offerings, attracting new subscribers and retaining existing ones. This move highlights the importance of content quality and brand recognition in the highly competitive streaming market. Here are other ways to approach the new generation of entrants while still ensuring effective reach and campaigns.

Programmatic and CTV Integration

At Dstillery, we have seen firsthand how brands and marketers are refreshing their strategies to navigate this evolving environment. Integrating Connected TV (CTV) into hands-on programmatic buying platforms and leveraging clean room data matching are key strategies that marketers and brands use to better understand the impacts of CTV advertising compared to standard linear television.

With its ability to deliver highly targeted ads to specific audiences, CTV is rapidly gaining traction among advertisers across all parts of the funnel and becoming a factor when looking at budgets. By using programmatic buying platforms and clean rooms to combine fragmented reporting from walled gardens, advertisers can better target the right audience and optimize budgets. Yet, this tactic is still in its early growth stages

Adopting AI Targeting and Measurement Technology

Adopting AI targeting and measurement technology is crucial. These advanced tools help media buyers understand and then find customers on the most relevant types of content, genres, networks, or categories. AI-driven insights can reveal patterns and trends in consumer behavior that might not be immediately apparent through traditional methods. 

For instance, an AI system can analyze vast amounts of data such as aggregated historical reporting or ACR data related to their campaigns to better understand and optimize against their desired KPI and audience. 

One of the critical aspects of effective targeting in  streaming is understanding how ID-based targeting translates into CTV delivery to better identify your audience. While cookies allow for a 1:1 relationship between an ID and a single browser for targeting, these cookies do not exist on other devices, and so must often be probabilistically matched to a household via an IP address. This means that while one person in a household may belong to a given audience, ads will be shown to everyone in that household. It is essential to consider this when selecting your audiences or using content-based optimizing features to better fine-tune your targeting.

The Streaming Players

The continuing growth of ad-supported tiers on leading streaming platforms and potential entries of social players like LinkedIn, X, and TikTok further intensifies the competition. These platforms bring unique strengths and audiences, challenging traditional media companies to innovate and adapt. 

LinkedIn, for instance, could leverage its professional network to offer niche content tailored to career development and industry insights, while TikTok’s short-form video format appeals to younger audiences looking for quick, engaging content. X’s vast user base and real-time engagement capabilities could position it as a formidable player in live-streaming events.

Increased M&A activity among legacy media players reflects their efforts to consolidate resources and expand their streaming capabilities. These media giants aim to enhance their content libraries, technological infrastructure, and market reach by acquiring or merging with other companies. This trend will likely continue as companies strive to stay competitive.

What Is in Store for Advertisers

These developments mean advertisers must navigate a more fragmented media environment. Diversifying campaigns across multiple platforms and formats is essential to reaching the best audiences. Advertisers must stay abreast of the latest trends and technologies to engage viewers and measure the impact of their efforts.

Overall, the new generation of streaming wars presents challenges and opportunities for advertisers. By starting to take CTV into your programmatic buying platforms, leveraging clean room data matching, and adopting AI targeting and measurement technology, advertisers can better navigate the fragmented media landscape and reach their desired audiences. 

Understanding the nuances of both ID-based and content-based targeting, as well as staying informed about industry trends will be crucial for success in this dynamic environment. As the streaming wars evolve, advertisers must remain agile and innovative to stay ahead of the competition.

The post Conquering the Streaming Wars: An Advertisers’ Guide to Reaching Audiences in  Fragmented Media  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.

AI is a crucial growth driver across various aspects of commerce advertising, from content creation to targeting and personalization, according to mrge’s latest State of Commerce Advertising Report.

To learn more about the transformative role of AI in commerce advertising, we chatted with Felix Witte, General Manager and SVP Publishers & Advertisers at mrge. He gave us an in-depth look at the report, showcasing specific examples of revenue increases and operational improvements.

In our conversation, Witte also addressed the challenges posed by Google’s anticipated updates, which are expected to significantly impact content quality and data protection. Transparency is also a crucial concern for the industry, with 94.4% of respondents citing so.

Dig into the Q&A for a comprehensive view of the current and future state of commerce advertising backed by data and insights from the report.

AI as a Revenue Driver

Lynne d Johnson: The report highlights AI as a significant growth driver. Can you provide specific examples or case studies where AI has substantially increased revenue for commerce advertisers?

Felix Witte: AI is extensively being used in managing product listings on search engines. Tools like GPT-4 and Jasper.ai can generate product descriptions, specifications, and listings automatically. By inputting basic product information, AI can produce detailed, SEO-friendly descriptions that save time and maintain consistency for publishers. When looking at the advertiser side, we noticed that AI is being employed across the whole value chain.

For example, a large sports apparel company is using AI and machine learning to analyze customer data and predict future purchasing behaviors. They use these insights to tailor their marketing efforts more effectively.

A large beverage company utilizes AI-driven analytics and machine learning to analyze social media interactions and customer feedback. This allows them to create more targeted and personalized ad campaigns.

A leading online publisher uses AI to create a dynamic content recommendation engine that adapts to user preferences in real time. They also employ AI to optimize their native advertising, ensuring that ads are more relevant to readers.

At mrge, we use AI to optimize partner program selection as well as using automated bidding to ensure the best traffic is directed to our partners.

The AI market is expected to grow from $184.00 billion in 2024 to $826.7 billion in 2030. We believe a large part of this growth will be driven by the commercial and operational upsides that AI offers.

AI’s Expected Impact: AI is viewed as having high potential in advanced targeting and personalization, content creation, and campaign optimization.

Navigating Google Updates

LdJ: The anticipated Google updates are a major concern for the industry. What specific changes are expected, and how should advertisers and publishers prepare to mitigate potential negative impacts?

FW: In the second quarter of 2024, Google severely penalized performance marketing outside its walled gardens. Content white-label solutions have been effectively eliminated. Content sites have lost one of their key growth drivers (commerce content on their sites) and are now struggling to determine new growth strategies. AI regulation has been tightened to favor the classic Google search, which coincidentally started experimenting with the inclusion of coupon and discount codes. Industry experts believe Google will continue to become more restrictive regarding the types of traffic, specifically:

• Content quality: Emphasis on original, high-quality content over thin, low-quality content.
• EAT (Expertise, Authoritativeness, Trustworthiness): Continued focus on E-A-T criteria, particularly for Your Money or Your Life (YMYL) sites, which include many affiliate marketing websites.
• Page experience: Incorporation of Core Web Vitals into ranking signals, affecting how pages are assessed based on user experience metrics.
• Product review: Enhanced algorithms to evaluate the depth, quality, and authenticity of product reviews, favoring comprehensive, insightful content.

Additionally, past Google changes were focused on English-speaking countries only. We expect that Google will extend its policy to all languages.

Google Updates Impact: Emphasis on high-quality content and strict data protection rules.

Enhancing Transparency​

LdJ: With 94.4% of respondents highlighting the importance of transparency, what measures are being implemented to enhance transparency within the industry, particularly in ad placements and revenue reporting? What steps is mrge taking to improve transparency in Commerce Advertising transactions and reporting?

FW: To improve transparency and efficiency at scale, we have implemented direct integrations with affiliate networks. These integrations allow for seamless data exchange and real-time tracking, ensuring that all parties have immediate access to performance metrics and detailed insights. This level of transparency helps in building trust between advertisers and affiliates, as it provides a clear view of traffic sources, conversion rates, and overall campaign effectiveness.

Our approach also includes maintaining a high level of responsiveness to advertiser requests. We understand that timely and effective communication is crucial for successful campaign management. By prioritizing advertiser needs and swiftly addressing their inquiries, we ensure that their campaigns run smoothly and any issues are resolved promptly. This proactive stance not only improves campaign performance but also fosters long-term partnerships with our clients.

Additionally, we employ proactive click screening through 24metrics, a sophisticated tool designed to detect and prevent fraudulent activities. This tool continuously monitors clicks and conversions, identifying any anomalies or suspicious patterns. By filtering out invalid traffic and ensuring that only genuine clicks are counted, we protect advertisers from fraud and enhance the overall quality of the traffic we deliver. This proactive approach to fraud prevention reinforces our commitment to providing reliable and effective affiliate marketing solutions.

Transparency Importance: 94.4% of respondents consider transparency crucial​.

Investing in Partnerships

LdJ: The report mentions increased investment in partnerships as a key opportunity for revenue growth. Can you elaborate on the types of partnerships that are most effective and provide examples of successful collaborations?

FW: The most relevant partnerships are between advertisers and suitable publishers, including:

• Coupon and deal sites
• Product comparison and review sites
• Buy Now Pay Later sites
• Social media platforms, blogs, forums, and niche content sites

We believe that successful partnerships are based on regular communication, a clear exchange of partnership goals, and a strong alignment between the publisher’s audience and the advertiser’s products.

Partnership Growth: Increased investment in strategic partnerships is seen as a key revenue growth driver.

Capitalizing on Emerging Trends

LdJ: Considering the optimistic outlook for the second half of 2024, what key factors does mrge believe are driving this positive sentiment, and how can advertisers and publishers best capitalize on this anticipated growth? What emerging trends or technologies do you foresee shaping the future of commerce advertising beyond AI and Google updates?

FW: In the second half of the year, several factors drive growth:

Economic stabilization and recovery, characterized by lower inflation and a return to growth, play a significant role. Changing consumer patterns also contribute, with a higher share of spending allocated to essential items like food, electricity, and heating. Additionally, consumers are becoming more cost-conscious, showing a preference for value products, which leads to lower basket values but increased interest in coupons and discounts. The Q4 seasonality, marked by major commercial events such as Black Friday and Christmas, further boosts e-commerce and affiliate marketing.

To capitalize on these trends, businesses should focus on helping consumers mitigate the impact of inflation by providing money-saving opportunities. Planning ahead by forging partnerships with publishers early ensures a strong reach during the crucial Q4 period. Adapting to emerging product trends is essential, as identifying in-demand products based on changing consumer patterns can enhance success.

Moreover, several other trends are shaping the landscape. Video marketing continues to grow in relevance, while AI-driven customer support and interactions are becoming more commonplace, with a shift towards direct messages instead of traditional email or chatbots. There is also a continued trend towards eco-friendly products and conscious travel. Lastly, the upcoming US elections are expected to have a significant impact on e-commerce and overall economic development.

Emerging Trends: Approaches to maximize growth through upper- and mid-funnel activities, such as strategic partnerships, social media engagement, and creating valuable content.

The post AI Boosts Commerce Ad Revenue by 32%: Insights from mrge’s State of Commerce Advertising Report appeared first on AdMonsters.

Algorithms shape our world in ways we never imagined, influencing everything from the news we consume to our political beliefs. In this article, Søren H. Dinesen, Co-founder and CEO of Digiseg explores critical trends in digital media through a curated list of must-read books, exploring the intricate relationship between algorithms, media, and privacy. These works dissect the creation of echo chambers, the rise of filter bubbles, and the profound impact these phenomena have on political discourse and societal polarization.

The Algorithmic Influence: Shaping Our News and Beliefs

Dinesen reviews key titles that unravel how algorithms narrow our perspectives and distort our cultural and democratic frameworks. By examining these influential books, he provides a comprehensive overview of the challenges and implications of living in an algorithm-driven world, urging us to rethink how digital media shapes our reality.

Let’s dive in.

The Media Manipulation Machine: A Closer Look

In their book The United States of Distraction: Media Manipulation in Post-Through America, Dr. Nolan Higdon and Mickey Huff tackle urgent questions facing America. Key among them: How did we get to the point where citizens decide what’s true based on the number of people who believe it, rather than facts or reality?

Consider some of the outlandish things Americans believe:

• Three in ten believe the 2020 presidential election was stolen from Donald Trump
• About 25% say there is at least some truth that COVID was planned
• 22% believed that the “storm” predicted by QAnon would occur
• 7% believe chocolate milk comes from brown cows

One would think it’s easy enough to dispel such ridiculousness … isn’t that what the media is supposed to do? Provide reality checks for a reading public? Sadly, vetted journalism isn’t convincing anyone because distrust of the media is at an all-time high.

Echo Chambers: The Rise of Filter Bubbles

How did we arrive at such a sad state of affairs? Over the past 10+ years, numerous scholars have concluded that the root of all our troubles begins with the deployment of algorithms. Algorithms are designed to present us with the information we have shown a propensity to consume, which in turn, limits the range of information we see and what we believe.

The Impact of Digital Isolation on Democracy

In 2011, Eli Pariser coined the term “filter bubbles” in his book, The Filter Bubble, What the Internet is Hiding from You. Two years earlier, Google had deployed AI to its search results, narrowing sources to just those the algorithm predicts will interest the user.

To Pariser, it was the dawn of the great dumbing down of people as the range of information they were exposed to was limited. We thought we had access to the full spectrum of global information — that we were traveling along a great information superhighway — but with algorithms deciding what we see, that is no longer the case. An important onramp — Google Search — merged with its algorithmic offramp, unbeknownst to us.

Radicalization Through Algorithms: How Big Tech Went Wrong

But that was only one of the challenges. The other was how it groups us into clusters of people who think like us, trapping us into “filter bubbles.” Today we call those bubbles echo chambers.

All of this narrowing and grouping is fueled by AI — algorithms that track our online activity and preferences, then selectively show us content that aligns with our existing beliefs and interests. With enough positive reinforcement from others on the internet, it comes as no surprise people can fall for conspiracy theories.

It’s one thing to believe that chocolate milk comes from brown cows (when I was young I thought trees made wind by bending back and forth). But when AI-curated content leads someone to ransack a Target outlet or bring a gun to a pizza joint to free kids held as slaves, it’s time to admit we have a problem.

This is a theme that is echoed by Stanford University Professors Rob Reich, Mehran Sahami, and Jeremy M. Weinstein in their book, System Error: Where Big Tech Went Wrong and How We Can Reboot. They argue that when Big Tech’s hyper-focus on a single metric — say YouTube’s decision to prioritize time spent consuming videos — bad things happen. They’re not wrong, as it’s now understood that the tuning of an algorithm to prompt binge-watching leads to the radicalization of users and the spread of conspiracy theories.

Memes as Propaganda: The Online Battle for Truth

In the book Meme Wars: The Untold Story of the Online Battles Upending Democracy in America, Harvard’s Joan Donavan and others argue that memes serve as the bedrock of conspiracy theories, helping to make the unbelievable believable. Clever, and easy to go viral, memes like “Stop the Steal” can move entire cohorts of people to act violently and in anti-democratic ways.

Conspiracy Theories and Algorithmic Fuel: A Dangerous Mix

Memes are particularly effective at swaying people and recruiting them to extremism (the book Accountable: The True Story of a Racist Social Media Account and the Teenagers Whose Lives It Changed describes how Googling “black on black crime” will lead people down a white supremacist rabbit hole). 

One of the reasons why memes are effective at converting people is that they break down offensive and outlandish beliefs into bite-sized and memorable riffs. They serve as a starting point to a process that slowly eases people into horrific belief systems. Recruiters of extremist beliefs understand this, and they’ve honed their skills. This, by the way, isn’t just an American problem; it’s global. 

Cultural Flattening: Algorithms Blunting Creativity

In her book, The Next Civil War, Stephanie Marche also warns that algorithms make us more extreme, but she says they add another wrinkle: they make it easy for racist and violent people to find one another. In the days before the Internet, a disaffected youth would have trouble joining a white supremacist or neo-Nazi group because such people were  underground. Today, social media algorithms will recommend them as something users may be interested in.

But it’s not just the worst parts of society that algorithms distort. Algorithms are also blunting the best parts of cultural life, as Kyle Chayka’s recent book Filterworld: How Algorithms Flatten Culture clarifies.

He warns that algorithms have effectively constricted our access to information, serving the lowest common denominator of content because such blandness will appeal to the largest number of people. This results in books, music, and even physical spaces such as cafes, all reading, sounding, and looking alike because algorithms have taught us to expect no better. Groundbreaking ideas are penalized because they don’t have the same level of virality as the more market-tested ones. Put another way, algorithms are flattening the global culture.

A Broken Promise: The Internet’s Failed Information Superhighway

The internet was supposed to be an information superhighway, providing unrestricted access to ideas to anyone with an interest in learning. But instead of providing easy access to ideas and information, the algorithms that now rule the Web are shrinking what we’re exposed to, and in many ways, our free will. Instead of being presented with new ideas, we are grouped into cohorts of people who amplify our beliefs and prejudices, setting the stage for outlandish, post-truth beliefs.

The Path Forward: Reclaiming Our Shared Reality

Shared truths are essential to functioning societies—- this candidate won an election, the Earth is round, not flat, and climate change is an urgent issue that needs addressing. Without a basic set of facts we can all believe in, humanity will only get more mired in the deception and misinformation that is propagated by AI, with people of differing opinions retreating further into their corners.

It’s our duty to prevent that from occurring.
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This is the third article in Digiseg’s Privacy Series. The first, Privacy Signals, AI in Advertising & the Democratic Dilemma, takes a broad view of the issues of private signals and one-to-one signals as we see them. The second, Surveillance Capitalism 2.0, examines how emerging privacy-centric solutions track user behavior just as much as cookies ever did.

The post Echo Chambers & Political Discourse: Essential Reads on Media Manipulation and Algorithms 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.

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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.

The Cannes Lions International Festival of Creativity 2024 was a whirlwind of innovation and insight, from the buzzing panels to the casual yet powerful conversations outside The Palais. While Elon Musk’s headline-grabbing interview drew a lot of attention, the ad tech discussions in the quieter corners truly stole the show. Publishers showcased their latest strategies to diversify revenue, leverage AI, and champion transparency in a rapidly evolving industry.

Amid the seaside backdrop and occasional gusts of wind that even interrupted a Yieldmo rooftop panel, industry heavyweights shared their visions for the future. From AI-enhanced campaign execution to the power of community-building, the sessions were rich with actionable insights and collaborative spirit. Let’s dive into how leading publishers are navigating these trends and setting the stage for what’s next.

AI and Human Governance: A Dynamic Duo

During a lively Yieldmo rooftop panel on the Evolution of AI in Ad Tech, participants faced an unexpected challenge: the wind. Yet, the show went on with Craig Miller from Amazon Web Services, Valerie Davis of Assembly Global, Jesh Sukhwani from Lenovo, and Yieldmo Co-Founder Teddy Jawde leading a robust discussion on generative AI. Sukhwani emphasized the irreplaceable role of human governance in AI implementation, noting, “AI is there to improve productivity and provide a more seamless decision-making process. It is not there to overtake and think for humans.”

Future Today: Leveraging Contextual Buying 

Future Today is making waves with its latest integration with IRIS.TV, allowing the publisher to contextualize its vast content library into various segments, like travel, food, and fitness. This move has standardized the process of contextual buying, making it easier for advertisers to target specific audiences. Co-founder Vikrant Mathur highlighted the importance of this integration for revenue growth, especially with the ongoing cookie deprecation bringing contextual advertising back into focus.  

“IRIS.TV is trying to standardize the process of contextually buying itself,” Mathur explained. “If I have a movie and another publisher has the same movie, sometimes how we pass information to the buy-side is not the same. IRIS.TV allows us to pass and receive signals in a way that makes sense to everybody, which is crucial for standardization.”

In the last quarter or so, revenue from leveraging IRIS-enabled private marketplace deals has been in the six figures for Future Today, and it’s growing. 

The Daily Mail: Dominating in the World of Video 

DMG Media’s Hannah Buitekant shared the company’s ambitious global video strategy, positioning video as the future of revenue diversification. As the leading video publisher on TikTok, with over 13 million followers and one billion monthly views, the Daily Mail combines creativity and tech to expand its video operations. Buitekant advised that authentic content tailored to each platform is crucial for success, emphasizing agility in content development across YouTube, TikTok, and Instagram Reels. According to Buitekant, managing director of digital at DMG Media, innovation within publishing is in the company’s DNA. 

“The video content needs to feel authentic to the platform it appears on, so take that into account when developing new offerings,” Buitekant said. “What works on YouTube may not work on TikTok or Reels, so publishers need to remain agile and amenable to quickly pivot and change formats when rolling out new content platforms.”  

Bloomberg Media: Innovating with Content

Bloomberg Media’s presence at Cannes was marked by discussions about women’s leadership and the power of AI in the C-Suite. Ashish Verma, Global Head of Bloomberg Media Studios, discussed the company’s focus on “content innovation,” combining data science and strategy to connect authentically with their audience. Verma pointed out that live journalism events and bespoke brand content are integral to their diversified media strategy.

“Bloomberg Media has been a heavily diversified media company for many years; one of our points of pride is content innovation, which means that our content is ours and on owned channels, but also social platforms and video distribution streaming services,” Verma explained. “We’ve had a robust live journalism events business for several years, and it plays a part in our diverse offering. In 2025, we will focus on continuing to expand the product offerings from Bloomberg Media Studios, which produces bespoke brand content and experience in a way that understands and connects with our audience — from print to audio and video.”

When asked about AI, Verma noted, “With the growth of AI, we are finding that business-to-business executives are seeing greater value in meeting to discuss key trends and do deals face-to-face and hearing from our journalists face-to-face. Cannes itself was in AI overdrive. Up and down the Croisette, every tech institution was talking about its tools (which were fantastic to play with).”

Mediavine: Don’t Sleep On The Power of a Strong Email Strategy

With the hype surrounding AI and a bunch of new strategies, tools, and technologies on the market, let’s not forget an area thats data rich and has  never steered us wrong: email. When we asked Eric Hochberger, co-founder and CEO of Mediavine, about how publishers can boost revenue these were his sentiments:

“As we reach the halfway point in 2024, it’s a critical time to have conversations with publishers on how they can better diversify their revenue and traffic sources for next year. One approach publishers should consider is a robust email strategy for audience connection and first-party data.

It’s key to reinforce the prioritization of human-made content industry-wide by implementing a framework for vetting mass-produced, undisclosed generative AI content. The most effective way to protect against a generative AI content takeover is by making sure bad actors aren’t incentivized to produce it. Not only because it’s essential for a free web but because it performs better for marketers. Looking ahead at 2025, this will have the biggest impact and wield the greatestcreative influence, boosting revenue for publishers and demonetizing low-quality generative AI content.” 

OpenWeb: Building Community for Revenue Diversification 

Max Weiss, OpenWeb’s Chief Strategy Officer, highlighted the importance of community in today’s media landscape. With AI search tools impacting traffic and cookie deprecation on the horizon, publishers are focusing on building loyal user bases. Weiss noted that a strong community amplifies every new revenue stream, and OpenWeb’s mission is to foster a thriving ecosystem for publishers and content creators. 

“The business model of today’s media industry is under threat. At Cannes, the conversation was about diversifying revenue streams to keep growing while AI-fueled search results impact traffic and cookie deprecation looms. So many publishers are renewing their focus on building a community of registered users — they know that every new revenue stream, every innovation, is amplified by a strong base of loyal users.”

On foreseeing the future of AI development, Weiss said, “While AI can help publishers drive efficiency and streamline processes, it also has the potential to eat into publishers’ traffic. Publishers must focus on lifetime value, loyalty, and community to grow in this new era. At OpenWeb, our mission has always been to create a thriving, healthy ecosystem for the open internet with publishers and content creators at the center.” 

Embracing Transparency: Publisher Panels Insights

Bridging the Gap: Control vs. Transparency in the Streaming and CTV Landscape 

At an OpenX panel, Rose McGovern, Head of Programmatic & Digital Ad Sales at DirecTV, stressed the importance of passing contextual signals to ensure audience targeting while complying with privacy regulations. The discussion also touched on innovative ad formats and the shift from cookies to persistent identifiers.

She elaborated on the importance of passing contextual signals, such as genre, rating, and network, rather than series-level data. This specificity ensures publishers can reach the right audience while remaining compliant with privacy regulations. Moving away from cookies towards more persistent identifiers like universal IDs was discussed to protect customers and enhance targeting accuracy.

Looking ahead, Rose expressed a desire for more innovative ad formats and the need to move beyond the traditional 15- and 30-second spots. She pointed out, “If we can’t run cool ad formats programmatically, then we are really lame. We must innovate and scale these formats to keep up with the evolving CTV landscape.”

Insights into the Evolving Open Internet Market

During a panel hosted by Ogury, Gabriel DeWitt, Head of Monetization at Yahoo, and Heather Carver, Chief Revenue Officer at Freestar, highlighted the complexities of ad monetization and the need for greener infrastructures. They emphasized collaboration in addressing issues like MFA sites and the importance of incrementality in ad formats.

As DeWitt pointed out, “Running ads for a publisher is very complicated and has become more complicated over time, so increasing numbers of publishers need help with their ads.”

Carver highlighted that SSPs must be more carbon-effective, and buyers should choose more efficient paths. Monetization challenges often lead publishers to create complex, wasteful bid request systems. She talked about the positive impact of collaboration in combating issues like MFA (Made-for-Advertising) sites, stating, “We should celebrate the content owners who are actually trying to create good consumer relationships and not just try to drain the money from buyers.”

Paul Bannister, Chief Strategy Officer at Raptive, noted that constrained caps require better tools to bring incremental demand, and better signals should judge the effectiveness of partners. When asked if there was something he’d like to see changed, Bannister responded, “Instead of open RTB, I think about close RTB. There are too many bad actors extracting value. I’d love to work out a way to restrict access to make it a more premium supply.”

The ROI of Openness: Enhancing Publisher Performance Through Transparency

Mike Racic, President of Prebid and Saiful Ahmed, SVP Ad Tech, Global Investment at OMG Global discussed fostering transparency and trust within the programmatic supply chain. They introduced new initiatives to combat ad fraud and enhance Supply Path Optimization (SPO), underscoring the need for standardized and transparent practices.

Racic highlighted the importance of transparent technology solutions. He emphasized Prebid’s commitment to solving publishers’ problems by connecting them to the marketplace transparently. He also announced that Prebid is working with Human to launch an initiative to combat ad fraud, which will be unveiled at their summit in October. “Everything we do is transparent,” he stated, underscoring Prebid’s approach to building trust through clear and open practices.

Ahmed introduced OMG’s Accountability Transparency Framework (ATF), which sets legally binding agreements to push transparency and protect the programmatic trading ecosystem.

He noted, “We give our clients full disclosure into media tech and data costs and domain-level reporting.”

Chen, Co-founder and CRO of RISE, discussed the role of data in SPO and why it’s important  for publishers to understand how SSPs and DSPs classify their inventory. He highlighted the need for transparency in inventory segmentation and value assessment.

All panelists concluded that we can’t dismiss MFA sites as bad without proper standardization and compliance. With transparency supported by clear industry-wide standards, we can address this ongoing issue.

Shaping the Future of Ad Tech

The Cannes Lions 2024 was a testament to the power of innovation and collaboration in the ad tech industry. From leveraging AI to building strong communities and embracing transparency, publishers are navigating a complex landscape with creativity and strategic foresight. As the industry evolves, these insights and strategies will be crucial in shaping the future of ad tech and media.

The post Power Moves: Publishers Unveil Cutting-Edge Revenue Strategies and AI Innovations at Cannes Lions 2024 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.

How do publishers plan to rev up their revenue in the coming years?

Share your insight in our 5-minute survey.

We want to understand where you see the biggest opportunities and challenges in the digital publishing landscape. Your feedback will help us identify key trends, innovative strategies, and potential obstacles in pursuing sustainable growth and profitability.

Let’s uncover where the opportunities are together, as an industry. Your contributions to this survey will help other publishers better understand the industry’s challenges, and learn the strategies to help them sustain, and even thrive. Results will be announced at Publisher Forum Boston, August 4-6.

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