The 2024 AdMonsters Dream Team comprises carefully selected industry powerhouses recognized for their exceptional innovation, dedication, and trailblazing spirit in turning digital ad challenges into realized revenue gold.

These ad ops wizards and revenue rockstars were chosen to represent who AdMonsters would hire if they were launching an ad ops team. They have earned their places among the best of the best, redefining the boundaries of possibility in the dynamic world of ad tech. The Dream Team will be celebrated at Publisher Forum Boston, taking place August 4-6, with roundtables, in-depth conversations and networking with fellow publishers.

Meet the 2024 Dream Team
AdMonsters is proud to introduce the inaugural members of the 2024 AdMonsters Dream Team and their appointed roles:

Scott Messer – CRO
Current: Principal & Founder, Messer Media

Matthew Kent – SVP, Client Services
Current: VP, Client Services, Tubi

Connie Walsh – SVP, Yield & Monetization
Current: VP, Advertising, Legacy.com

Linda Chen – VP, Revenue Operations
Current: Director, Programmatic Revenue Strategy, Chegg

Zip Nguyen – VP, Business Intelligence
Current: Business Intelligence & Yield Lead, BBC

Pooja Singh – VP, Data & Analytics
Current: Director, Data Science, Kroger Precision Marketing

Kevin Antoine – Head of Programmatic
Current: Head of Digital Inventory Optimization, Graham Media Group

Addy Atienza – Head of CTV Revenue Operations
Current: VP, Programmatic Revenue and Operations, Streaming TV, Trusted Media Brands

Catherine Beattie – Head of Mobile Monetization
Current: Director of Programmatic, WeatherBug

Lauren Farber – Head of Sales Operations
Current: Advertising Tooling & Infrastructure, Netflix

Kimberly Hall – Sr. Director, Ad Operations
Current: Director of Digital Ad Operations, & Technology, Farm Journal

Jasper Liu – Sr. Director, Yield Management
Current: Sr. Programmatic Yield Analyst, Daily Mail/Mail Online

Sarah Webb – Manager, Ad Products
Current: Ad Production Coordinator, Bloomberg

See the Dream Team and learn more here.

“We are absolutely thrilled to introduce the AdMonsters Dream Team, celebrating the top talent in digital advertising operations. These professionals have demonstrated exceptional innovation and dedication, embodying the essence of our community and charting the course for its future. We eagerly anticipate how their expertise will inspire and elevate the entire industry,” said Becky Peck, Group Publisher, AdMonsters.”

“The Dream Team initiative underscores our commitment to fostering excellence and leadership within the AdMonsters community,” added Lynne d Johnson, Content Director, AdMonsters. “By bringing together these industry leaders, we are creating a powerful platform for collaboration and growth. We can’t wait to see the magic they will bring to our events and the broader digital advertising landscape. We look forward to the innovation, leadership, and inspiration the 2024 Dream Team will bring to the AdMonsters community and the digital advertising industry at large.”

About AdMonsters Dream Team
The AdMonsters Dream Team program celebrates the most influential and innovative minds in digital advertising operations. Members are handpicked for their outstanding contributions and leadership in their fields. As Dream Team members, they will receive widespread recognition, participate in exclusive Publisher Forum events, and enjoy special privileges designed to further enhance their professional journey.

For publishers in the digital advertising industry, the Dream Team represents an unparalleled resource of expertise and innovation. The insights and leadership of these professionals will empower publishers to navigate the complex digital ad ecosystem, optimize their revenue streams, and enhance audience engagement. By collaborating with the Dream Team, publishers can stay at the forefront of industry trends and achieve sustainable growth.

About AdMonsters
AdMonsters is the leading community for digital advertising operations and revenue optimization. We provide insights, training, and networking opportunities to help professionals and organizations stay ahead in a rapidly evolving industry. With a focus on collaboration and innovation, AdMonsters is dedicated to supporting the success of its members and the digital advertising ecosystem.

Media Contact:
Trish Borrelli
Sr. Marketing Director
AdMonsters, AdExchanger and Folio:
tborrelli@accessintel.com

Visit admonsters.online/dreamteam24 for more information.

Follow @AdMonsters on LinkedIn for the latest updates and announcements.

The post AdMonsters Announces Inaugural 2024 Dream Team Picks appeared first on AdMonsters.

Given the breakneck speed of digital innovation nowadays, publishers need a competitive advantage. Standing out comes from the power of rapidly and accurately analyzing data. Take The Weather Company, for example, the global titan in weather data and forecasting, is supercharging their mobile analytics game after joining forces with Lotame and AWS Clean Rooms.

This powerhouse collaboration has slashed insight generation time by an eye-popping 98% and boosted query efficiency sevenfold, enabling The Weather Company to deliver data that’s not just fast but razor-sharp and hyper-relevant to its clients and partners. AWS Clean Rooms facilitates this by providing a secure environment where companies can collaborate on datasets without sharing or copying the underlying data, enhancing data privacy and compliance.

But let’s talk specifics. By digging deep into the behaviors and preferences of their travel audience, The Weather Company unlocked insights that go beyond the surface, fine-tuning strategies for travel advertisers. For instance, by analyzing user interactions on The Weather Channel mobile app, they can distinguish between frequent and infrequent travelers and preferences toward air versus land travel. This granular insight has allowed The Weather Company to craft finely tuned, targeted, and effective advertising strategies that deliver exceptional results for their advertising partners.

In our exclusive Q&A, I spoke with Dave Olesnevich, Head of Data & Advertising Products at The Weather Company, to unpack the technical challenges and victories of the integration. We explored how AWS Clean Rooms enhances data privacy and compliance, tackles the unique hurdles of mobile data, and shapes the future of ad targeting and campaign efficiency.

Lynne d Johnson: Given the increased scrutiny on data privacy and compliance, how does the AWS Clean Room technology help The Weather Company navigate these complexities? How has this transformed your day-to-day operations?

Dave Olesnevich: AWS understood the assignment when it came to creating a privacy-forward environment where multiple parties can collaborate with data quickly and easily. CISO’s office is more amenable to the clean room environment versus moving data out of house for engagements.

The AWS Clean Room isn’t magic though — participants have to bring high-quality data to the table in order to create insights that become actionable. We can control what data is accessible on a case-by-case basis, which is a table-stakes feature. The Weather Company now has a new way of working with our customers to create value. We’re still in the earlier days of utilizing data collaboration platforms for advertising engagements at scale, and I expect a lot more usage in the future.

LdJ: With the new system reducing the insight generation time by 98%, could you discuss how this acceleration has transformed your approach to ad targeting and campaign efficiency? How quickly can changes in weather patterns now influence ad placements?

DO: Time to value is going to change when we fully operationalize the system. The value is first to our customer, we can help them achieve their desired outcomes with a reduced number of hops in the process. The LOE to produce actionable insights for the C-suite is at our fingertips, so it’s not just paid, but owned and earned for the CMO and BPO, with opportunities for the CFO and COO as well. As weather becomes increasingly more impactful to the bottom line, we can help leaders harness weather intelligence for use across their business.

LdJ: How have these faster insights already impacted a campaign or strategy? What have been the most significant impacts on your business and client interactions?

DO: Now more than ever, we’re able to develop what we call a Weather Strategy for our customers across the enterprise, with less time blocking and tackling and more time spent unlocking the value of the insights to drive desired outcomes for advertisers across their entire media mix. Like many in our ecosystem, we’ve been working with Lotame and AWS for a long time. We’re all leaning in to build the next generation of advertising.

LdJ: Looking forward, how does The Weather Company plan to further leverage this enhanced data processing capability? Are there new types of data analytics or services you’re aiming to explore that were not feasible before?

DO: We’re just getting started. Targeting, measurement, attribution. We’re working with our customers to help them understand how weather impacts their customer behaviors and their business operations. End-to-end weather impact in advertising, from planning through activation and measurement is the future state.

The post Weathering Data Storms: How The Weather Company, Lotame, and AWS Clean Rooms Supercharge Mobile Analytics 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.

Core to these successful campaigns is comprehensive, culturally nuanced data that takes these audiences’ habits, views, perspectives, and patterns into account. Unfortunately, there is an ongoing lack of both across minority populations.

As brands and agencies look to delve into specific demographics, the depth of the insights available to them tends to diminish significantly.

Any campaign must resonate with the lived experience and shared values of the communities it is attempting to reach. Proceeding without this essential knowledge runs the risk of being seen as inauthentic, or worse, offending and invalidating the cultural experience of thousands of people. Critical marketing blunders like these have been seen time and time again, across nearly every industry.

Marketers must (and can) do better — it is time to unite the creativity our industry is known for with an engineering mindset to create authentic and nuanced campaigns. The first step is not only understanding which insights you are searching for, but how specifically to go about uncovering them.

Numbers Tell the Story

Often, brands and agencies know which multicultural group they would like to approach with their messaging, but do not know where to begin otherwise. Collecting quantifiable data on these audiences is often one of the most impactful ways to begin to authentically build a narrative that your consumers can connect with.

In a recent graduate class, one of the professors said something that resonates deeply with the feedback I receive from clients during data discussions. The professor referenced the timeless wisdom of Edwards Deming, stating, “Without data, you’re just another person with an opinion.”

Yet, in today’s world, where marketers are inundated with data, the statement takes on a new form: “Without an opinion, you’re just another person with data.” This shift underscores the importance not just of data collection, but of its interpretation. It’s the nuanced understanding and application of these insights that are pivotal to the success of any marketing campaign.

Doing this impactfully requires a sophisticated overlay of data from multiple sources. Consider which customers you are actually trying to target. This goes beyond a specific racial or ethnic group — consider factors such as where these consumers are located and their purchase history within your product or service sector. These factors can help determine their existing brand perception, and inform your strategic approach, to suit the goals of your campaign.

Alongside these logistical factors, a deep understanding of cultural context is necessary. Your research must encompass your audiences’ specific shared values within their local communities which a range of lived experiences, shared history and other socioeconomic factors can influence.

Seek out and listen to various unique perspectives and utilize your awareness of the present moment to deliver an informed and conscientious message that resonates with the individuals you aim to reach.

Embracing Emergent Technology

No discussion of modern marketing strategy would be complete without mentioning artificial intelligence. This emergent technology has its place across both campaign planning and execution. For example, utilizing a combination of qualitative and quantitative analysis, AI technology can both refine and accelerate the research process, delving into large datasets and uncovering patterns for marketers to extrapolate into actionable insights. However, beyond data processing, this emergent solution has a range of practical applications that marketers should explore.

In considering multicultural campaigns, AI technology can take on another essential task: assisting in accurate translations. For example, this innovative technology is capable of streamlining the initial translation process via inputting more sophisticated prompts. This goes beyond ensuring accuracy and extends to adding in other essential elements such as audience cultural nuances, location, and other valuable external contexts.

Innovative methodologies like these, complemented by a deep understanding of technology’s potential and limitations can creatively utilize analytics and ultimately lead to better campaigns. However, these approaches should never be undertaken without defined and robust oversight. Tasks such as ensuring correct linguistics and deriving insight from patterns are distinctly human in nature and ensure that the correct nuances and subtleties are accurate and culturally attuned.

With a robust view of consumer data, informed human oversight and the assistance of emergent technology, authentic and relevant cultural campaigns are not only possible but should become the norm. As the diversity of the national population grows, marketers must embrace an ongoing educational mindset, alongside a holistic evolution of the entire campaign planning and execution model, to better serve diverse consumers and communities.

The post Marketing Engineering – Uniting the Power of Cultural Insights and Data Analytics appeared first on AdMonsters.

In a league of their own, the AdMonsters Dream Team seeks to assemble a powerhouse squad comprised of ad ops wizards and revenue rockstars who continually surpass expectations, turning digital ad challenges into golden opportunities. This is not just any team; it’s a dream team of innovators and achievers who redefine the boundaries of possibility in the dynamic world of ad tech.

“Ad operations and digital revenue teams are at the forefront of driving revenue for their publishing organizations. The goal of our AdMonsters Dream Team initiative is to not only recognize these superstars, but also to elevate the role of ad ops professionals in the eyes of senior management and bring greater visibility to the skillsets and talent that make these individuals successful,” said Lynne d Johnson, Content Director at AdMonsters. “We’re excited to build an inspiring and unstoppable lineup of talent and shine a light on the remarkable individuals who are driving positive change and pushing boundaries in our industry.”

The call for nominations is open for ad ops professionals and their peers to nominate a deserving colleague or themselves.

Each Dream Team Member Receives:
• Recognition in the AdMonsters Dream Team feature story
• A free ticket to Publisher Forum Boston
• Participation on a panel at Publisher Forum Boston
• Super unique Dream Team SWAG
• Generous discounts for their team to upcoming AdMonsters events
• Digital badge and creative assets for well-deserved bragging rights!

Nominations are entirely free, offering a prime opportunity to elevate an outstanding colleague or put yourself forward for recognition.

Nomination Deadline: May 10, 2024: Learn more and submit a nomination here.

The post Announcing the AdMonsters Dream Team: Nominations Now Open for the Inaugural Fantasy League of Ad Tech All-Stars appeared first on AdMonsters.

As cookies make open web advertising more complicated, the big tech platforms, especially Google and Meta, are using AI to make buying ads on their platforms easier than ever before.

As a result, brands and agencies will be less likely to work with independent publishers, who require that they sift through an individualized catalog of ad products, where tech platforms offer greater ease and scale.

This gap — how easy it is to buy ads on a platform or publisher site and achieve the desired outcomes of digital advertising — will be the dominant challenge for publishers in the years ahead. It represents the synthesis of privacy changes and AI.

The good news for publishers, though, is that they, too, can use AI to make reaching their highly valuable audiences easier. Here’s why publishers need to make it easier to buy ads — and what they can do to bridge the gap.

The Age of AI, or the Advertising Easy Button

By leaning into AI for their ad solutions, big tech companies like Google and Meta are pushing ad buying further into the self-serve era. Take Meta’s Advantage+ for example.

To compete with Google and Meta, publishers must create easy buttons of their own to make it simpler for advertisers to do business with them.  

Through Advantage+, Meta enables advertisers, with as few inputs as possible, to leverage AI to find audiences on Facebook and Instagram and automate their campaigns. The challenge is no longer campaign planning. Advertisers need only tell Meta what outcomes they want, and the tech giant will do the rest.

To compete with Google and Meta (who have taken up 46.6% of the ad market as they’ve made it as frictionless as possible to advertise through their platforms), publishers must create easy buttons of their own to make it simpler for advertisers to do business with them.

Publishers’ Opportunity to Simplify — and Compete

Simplifying the ad buying experience for advertisers requires going beyond the traditional self-service system publishers have offered through the automated guaranteed (AG) model.

The traditional AG model places the onus on buyers to understand the intricacies of inventory options and how to make campaign adjustments manually across a labyrinth of platforms and tools.

It doesn’t have to be this way. Publishers also have the opportunity to leverage AI and automation to significantly reduce the friction in ad buying (and without having to undergo a costly overhaul of their existing infrastructures).

Three places publishers can incorporate AI and automation into the buying process are inventory discovery, media plan adjustments, and performance visibility.

3 Places Publishers Can Incorporate Ai and Automation Into the Buying Process

Inventory Discovery

Publishers can use machine learning-powered analysis of past and current campaign data to generate optimized ad product suggestions for each buyer. That way, publishers save advertisers the time — and clicks — needed to mine through interminable catalogs to find suitable products and generate the highest possible ROI.

Media Plan Adjustments

The next area publishers can automate is booking and media plan adjustments.

After deciding on a media plan, most advertisers have to log in manually to multiple tools and platforms on the publisher side to ensure sufficient inventory and book their orders. Not to mention the manual data entry (and re-entry) required for buyers to tweak their order based on availability or potential campaign changes.

Rather than putting the burden on buyers to go through multiple logins whenever they want to place or change an order, publishers should use robotic process automation to streamline these often tedious steps in the buying process.

Performance Visibility

When it comes to performance visibility, publishers can use AI to send buyers real-time alerts on campaigns. In doing so, publishers save their buyers’ ops teams from having to sift through anOMS or other systems to assess the performance of individual campaigns or surface any campaign issues that need immediate attention.

The AI-first Future of Open Web Publishing

Of course, AI and automation alone may not iron out all the details that more nuanced campaigns bring. But even if AI and automation only get a given advertiser 60 to 80% of the way there with the buying process, savvy publishers would still have saved their buyers hours — if not days — of tedious data entry. And even a 10 to 20% performance improvement in advertising results would represent a massive gain across a few hundred billion dollars of annual ad spend.

By leveraging AI and automation to create operational efficiencies and improve ROI, publishers won’t just better compete with the walled gardens and simplify the ad buying process for advertisers (and prevent headaches for operators). They’ll also enable buyers to take on more campaigns and increase spend while empowering themselves to service more deals — and generate more revenue opportunities at a much lower cost.

The post Publishers Need an Easy Button to Compete with AI-Enabled Platforms 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.

The demise of the third-party cookie once sent waves of fear through the digital advertising ecosystem, but not anymore. That’s because, in the years that followed Google’s original cookie deprecation announcement, the industry has been hard at work innovating new ways for publishers to segment their audiences so that their advertising partners can target them.

For Ravi Mittal, Founder and CEO of Vuukle, the most obvious way to get highly valuable data, including purchase intent and sentiment, is for publishers to ask them. Recently he launched Quizzly.ai — a tool that is part quiz and part game that early tests show readers are eager to use.

We talked with Ravi about how tools like quizzes can fit into the publisher’s and advertiser’s strategies.

AdMonsters: Vuukle recently announced Quizzly.ai. What is that exactly?

RM: It’s an AI-driven quiz that publishers easily embed in their sites using JavaScript. Then the code extracts the content of the page, whether that’s text or images, and sends it to a quiz AI engine. The engine looks at the content and turns the interesting bits into a question-and-answer format.

So take the AdMonsters article on the 10 Commandments of CTV. The chart to the left is the first question of an eight-question quiz that the tool created in real-time.

These quizzes appear at the bottom of the article, which encourages the user to test their understanding of what they just read. The quiz tells the reader whether they’ve answered correctly or incorrectly.

It’s a great way to increase engagement with the publisher’s content.

AdMonsters: Can the tool understand video content as well?

RM: We’re working on it. Soon.

AdMonsters: Does the tool ask the users’ opinion of what they just read, or are the questions about the content itself?

RM: We trained the AI model to pick out specific types of sentences, which enables it to create quizzes on the fly.

AdMonsters: I can see how it would prompt more engagement for people who take the quiz, but how many actually do that?

RM: That’s a great question. We asked ourselves the same question after we built the quiz unit but hadn’t launched it as an official product. But we tested it, and based on the data, it seems people have a natural tendency to test themselves. Without any incentive whatsoever, we’re seeing 8 to 10% user engagement rates for the quizzes.

AdMonsters: How can publishers turn that 8 to 10% engagement into audiences for segmentation and targeting purposes?

RM: Excellent question. There are a few ways to do that. First, we can create quizzes that include sponsored comments that ask about brand preferences, products, brand recall, or any number of things. Those sponsored questions come after the first two questions that are based on the article content itself.

As an example, we recently worked with an electronics manufacturer that was keen to do a brand measurement study. The sponsored question asked about a product or product category of interest. When users answered the question it provided the brand with the information it wanted, but it also informed the publisher about the types of content of interest to their readers. This allowed the publisher to create a unique audience segment they could offer to their advertisers.

AdMonsters: Don’t brands typically hire a comScore or Nielsen to get that data?

RM: Yes, it’s an $80 billion market. Now publishers can get in on it, and tap into a new revenue stream.

AdMonsters. That’s great. What’s the other way for publishers to build their first-party data set?

RM: Another way to collect first-party data is to ask questions that are relatively generic but are tied to IAB categories, such as, “How often do you visit local attractions.” The user responses are stored in the publisher’s GAM or Google Ad Manager. Later on, if a brand wants to target audiences to visit a local attraction, the publisher has a segment of users who answered the question, “frequently” or “monthly.”

These questions provide an opportunity for publishers to ask users questions and record their preferences as definitive purchase intent. It’s deterministic, not probabilistic data.

AdMonsters: So it’s always building audience segments with those generic questions, even if they aren’t sponsored?

RM: Yes, and those questions can be very specific about purchase intent. Are you planning to move in the next six months, or renovate your kitchen, or purchase a new car?

These questions provide an opportunity for publishers to ask users questions and record their preferences as definitive purchase intent. It’s deterministic, not probabilistic data.

AdMonsters: That sounds like a real selling point for the publisher who wants to sell premium audience segments based on purchase intent.

RM: It is a benefit because it’s based on real data that came directly from the users, rather than the guesswork of an SSP or DSP that segments users based on a handful of online behaviors.

Publishers can use the data they collect, to build segments, which they can offer to brands as highly qualified audiences.

AdMonsters: And at higher CPMs because they’re more premium and more unique. But of the 8 to 10% response rate of the people who take the quizzes actually answer those market research and sponsored questions?

RM: We’re seeing about a 40% completion rate. One of the reasons why we get a high response rate in the quizzes themselves and the sponsored questions is we’ve gamified it. Users who take the quizzes in their entirety have the opportunity to participate in a leaderboard.

The leaderboard also drives engagement, page views, and revenue. The more questions the reader answers correctly, the higher they’ll be on the leaderboard. This provides an incentive for readers to refer back to the article prior to answering questions. That’s good for them, and it’s good for the publisher.

AdMonsters: Leaderboards certainly provide an incentive to people who like to play online games. What is your recommendation for deploying these quizzes? Are there some sections or topics that perform better than others?

RM: That’s an interesting question. In the past, quizzes haven’t been major drivers of engagement because the onus was on the publisher to create and deploy them. But when you can automate the process and create quizzes on the fly, things get really interesting. Suddenly it becomes possible to create a quiz for every article and have them embedded on every page.

We recommend quizzes for every article published, even sponsored articles, as each quiz is an opportunity for the publisher to collect data and create really unique audiences.

AdMonsters: I can see why that makes sense for a sponsored article, but does it make sense for The New York Times to have a quiz on every article? I would think the users would stop seeing them after a while.

RM: I agree with you to a degree. There are some topics, say war or crime, where you wouldn’t want a quiz, and especially a quiz with sponsored content. But we can suppress quizzes based on the sentiment of the article.

There are some topics, like sports and politics, that are highly conducive to these quizzes because there are a lot of stats and trivia and people like testing their knowledge. Politics and sports consistently get 10% or higher engagement rates. Articles on relationships see even higher engagement with the quizzes.

AdMonsters: Speaking of politics, next year we will see $10 billion in political ads. People are very wary of generative AI and disinformation. What do you say to publishers who worry about AI-generated quizzes?

RM: That’s a fair question. There are many types of AI, and we’ve chosen a strategy that is risk-averse. We’re using content that is contained in an article itself and has been vetted by the editorial staff. We’re not using generative AI to create new text, and that’s an important distinction. We’re telling people that to get high on the leaderboard, they need to refer back to the vetted content in the article.

AdMonsters: So in addition to boosting engagement and dwell time, the publisher is improving reader comprehension?

RM: That’s right.

Ravi Mittal, Founder and CEO – Vuukle/Quizzly

Ravi Mittal is a highly accomplished entrepreneur and technology enthusiast with a strong background in Information Systems Engineering. He graduated from Imperial College London and quickly jumped into the corporate world, beginning his career at the prestigious Goldman Sachs.

In 2012, Ravi founded Vuukle, a revolutionary commenting platform that has since become one of the largest in the world. This innovative platform is utilized by over 500 websites across the globe, transforming the way users engage and interact with online content. Under Ravi’s leadership, Vuukle has expanded its offerings to include a range of cutting-edge products such as social share bars, reactions, push notifications, real-time analytics, and Quizzly.ai.

With over a decade of experience in adtech, Ravi has become a recognized expert in the field. He has closely worked with SSPs, DSPs, and publishers, gaining valuable insights into the complexities of the digital advertising ecosystem.

The post How Can Publishers Best Gauge User Intent and Sentiment? Ask Them. appeared first on AdMonsters.

The recent decision by Google’s GA4 to deprecate numerous attribution models, nudging marketers toward Data-Driven Attribution (DDA), has sparked considerable debate in the advertising community. While the crux of the matter is the black-box nature of DDA — we’re unsure of its internal workings — a more profound issue lies beneath the surface: should marketers care about how tools function as long as they deliver results?

Google’s paradigm shift in attribution methodology represents not just a change but a call to action. Success in this era of marketing demands a marriage between creativity and rigor with a healthy dose of proven expertise. Measurement and attribution have surged in prominence and now require a richer understanding to deliver results to the CFO, CEO, and board. How do we know how to trust, though? How do we know someone has that expertise?

Blind Faith in Tools Marginzalizes Marketing

In industries such as medicine, law, and accountancy, professionals undergo stringent certifications and barriers to entry — something conspicuously absent in marketing. It’s easy to lump marketers into a homogenous group, often undermining their advice. But what differentiates an exceptional marketer from an average one?

Some argue dialogue is the key, but relying solely on conversations is not how we delineate a credible doctor from an imposter or a lawyer from a charlatan. Seeking experts implies banking on their superior knowledge. Boards, CFOs, and CEOs must know the right questions to ask marketers to properly determine credibility and expertise. This is where Google’s move to DDA and other black-box approaches within our industry are dangerous.

Imagine if you went in for an MRI and the doctor wasn’t allowed to look at the images but instead had to trust whatever diagnosis the machine spit out. We wouldn’t stand for it, yet in marketing, this is becoming commonplace! The mindset that if something is effective, the nuances of its operation don’t matter, is harmful and inexcusable for marketing professionals. Blind faith in tools, such as DDA, without comprehension only further marginalizes our profession.

It’s Time to Pull Back the Curtains

Transparency is pivotal as we tread the realm of measurement and attribution. While major tech platforms are reshaping the landscape, they haven’t fully illuminated the intricacies of how their attribution models function.

Thousands of data scientists converging on a “best ever” measurement and attribution algorithm is exciting for our field. Still, platforms are self-interested and it is our job to extract maximum value from a marketing dollar. This can only be done with unobstructed visibility into measurement and attribution processes, offering clarity on user pathways and pinpointing those primed for client conversions.

For example, does the attribution methodology consider the “mental weight” of a video ad compared to display? Likely. What about in-stream vs. out-stream? Perhaps. What about frequency within each ad type? Frequency thresholds? Search behavior and previous brand interactions?

Of course, the big question is, at what point do platforms have more information about a brand or product than the brand or product themselves, but aren’t sharing it? “We can’t share your MRI images with you because we have MRI images of everyone in the country,” isn’t reassuring!

Agility Is Indispensable to the Future of Marketing

As the digital marketing world experiences seismic shifts, agility is indispensable. The emergence of AI and novel attribution methodologies necessitates brands to not only fathom but to interrogate.

Armed with lessons from the past, marketers can contextualize current strategies and forecast trends. Yet, embracing new technologies mandates fresh skills. Absent these, marketers risk obsolescence.

To truly thrive, marketers must invest in understanding today’s tools and methodologies. In other sectors, professionals care about the intricacies, the hows, and the whys, even if results are achieved. In marketing, unquestioning trust in machinery and tools can be our downfall. Our commitment today will shape our relevance and value tomorrow.

The post Navigating the Power of Data-Driven Attribution: A Call for Transparency, Expertise, and Understanding appeared first on AdMonsters.

Being a teacher taught Sturino how to interact with people, deal with situations, and simplify concepts – skills he regularly uses as VP of Data and Analytics at media agency Good Apple.

“I taught a room full of second-graders working in their second language. I was trying to simplify concepts and pay close attention to what the kids had to say – every day, every word, every phrase,” remembered Sturino. “It was similar to being a data analyst. It’s so easy to talk above somebody’s head, but you must ensure you understand your audience and simplify it.”

 Throughout his decade-long tenure at Good Apple, Sturino grew the data science practice into a trusted and integral capability. During his keynote, “How AI is Reshaping Media Buying and Selling,” at the AdMonsters Ops Conference, Sturino will share how media agencies and publishers can best incorporate AI to solve challenges from ad effectiveness and consumer engagement to brand safety and cross-device targeting. 

From Baseball Cards to Mathematical Theorems

From an early age, Sturino was always a numbers person. 

 “I was one of those kids who looked at the stats on the back of my baseball cards. I’d have two different cards, and if one player had a better batting average and the other player had more RBIs, I’d try to figure out who was the better player,” recalled Sturino. 

In college, Sturino enjoyed a mathematical proofs class where he had to make a case to prove the validity of a theorem. Finding joy in the exercise, he also learned patience for thinking through multistep processes and the curiosity to understand them. 

“I think patience is a big part of what makes a good analyst. It is more than being good with numbers. You must also understand where the numbers came from, the conditions under which the data was gathered, or how it joins with other data,” said Sturino. “How everything comes together is a lot like building that proof.”

Sturino says that although the theorem is used in higher math, you must build the theorem first, and he thinks that realization was how he ended up working in data and analytics.  

Every Apple Is an Analyst

At Good Apple, Sturino ideated and led the development of Crisp, the agency’s first proprietary data integration and management platform. Crisp was born out of necessity. It started with noticing how a client report was time-consuming, involving multiple team members, and several data sources. That time and effort were not sustainable.  

“I think where we saw an opportunity was not in solving the problem at hand but looking at the bigger problem overall and building a structure that worked for where we want to be in five years,” said Sturino.

Good Apple’s philosophy is that every Apple is an analyst. The media and analytics teams are heavily integrated, and the development of Crisp has been organically driven by analysts building tools that solve the problems they see in the teams’ everyday work.

Working closely with the agency’s pharmaceutical and retail clients, Sturino uses the Crisp AI capabilities to help pharma clients leverage an automated tool for creating custom content scans. Crisp interprets what is on a page, compares it to what’s allowed within that content space, and alerts Good Apple’s teams when something’s wrong. 

“Crisp is that first line of defense that can work faster and more often than a human could. We’re still doing our checks, but we’re adding an additional layer on so we can be more compliant,” said Sturino. “I think it’s an overabundance of caution that you see in the pharma space, and AI can play a big role in helping to add to that.”  

AI’s Impact Across Media Buying and Selling

Good Apple builds relationships with publishers and focuses on understanding what’s happening within a media interaction. When it comes to AI, Sturino thinks publishers can differentiate themselves by leveraging the tech to provide insights and transparency.

“If you look at where we started with pixel optimizations from programmatic partners, they have a pixel on the site and say they will automate towards this. But you never really learn what changes it’s making or what audiences it’s chosen to bid on. You get some information, but you don’t really know what’s working behind the scenes.”

Sturino says there is some risk for pharma clients having a publisher’s algorithm create a targeted audience using medication for off-label use. 

“That’s obviously a very problematic situation, and I think it’s limited the rollout of AI and ML on the pharma side of things,” stated Sturino. “An algorithm doesn’t care if it’s causation or correlation.”

From a media landscape perspective, Sturino says that when using publisher scorecards for RFIs and building media plans, AI is being weighted heavier and heavier. Agencies are no longer simply looking to check the AI box, but want to know how publishers are optimizing AI, such as tying in offline data or if they have their own data sources.

 “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 what are the actual results you’re giving us because, at the end of the day, everybody will be judged based on performance,” concluded Sturino.

And if all this talk about Good Apple’s ‘core’ value of measurement driving media decisions has you wondering about Sturino’s favorite fruit, it is, of course, a Granny Smith apple.

The post AdMonsters Ops Keynote Mark Sturino: Leveraging AI for Media Buying and Selling appeared first on AdMonsters.