In short: It’s probably not. But as voices around the digital media industry have been telling us, how businesses approach in-housing is changing. It’s becoming rarer and rarer to hear about brands aiming to bring all functions of their ad tech stacks inside. That’s good because managed tech services deliver significant value to the ad marketplace. If a business wants to replace one of its partners with an in-house solution, it should have a real, practical purpose.

Over the last several years, industry leaders have found that building out all primary ad tech functions internally isn’t just daunting – it’s effectively impossible. Today’s digital marketplace is too complex to strategize exclusively for self-service. Specialized tech partners are better suited to navigate that complexity.

There’s a dire need for quality service in ad tech, and that service is becoming increasingly a priority for businesses. A specialized partnership is more important than ever in this current landscape – with myriad digital channels, rapidly changing industry protocol and new regulations around data. It helps ensure optimal campaign performance while preserving the business’s bottom line. And the choices brands and agencies make to ensure success today show they agree. 

This Isn’t the Same Old Programmatic Marketplace

The reasons why the in-housing trend began are straightforward. As the programmatic market emerged, so did third-party services to guide advertisers and publishers. But in time, businesses started questioning whether the margins were too high and the services were not high enough in quality to justify the investment. Many companies assumed they could build teams and solutions in-house for better customization and lower costs.

The catch is that the in-housing trend started when in-housing was a much easier and more cost-effective proposition. Today, it’s not likely that a brand or agency can learn just a bit about each important tech function and expect that’s enough to replicate it on their own. The proliferation of digital channels is difficult for one business to manage effectively. Those channels require specialized knowledge to transact, analyze, measure, and report on. 

Countless Interlocking Pieces To Oversee

A decade ago, we might have been able to think of “outsourcing” as meaning “one person clicking five different buttons” to manage client services. But today, it’s more like ten people clicking a whole lot of buttons on multiple, distinct platforms – to ensure they’re doing things like maximizing CTV/OTT spend, optimizing social budgets, managing digital out-of-home, avoiding duplicating audiences during attribution, and providing insights that are concise enough to understand real ROI.

It’s too much of a lift in operational cost and human resources for one brand or agency to build and adequately oversee these functions. For brands, agency attrition only increases the burden. With a high-quality managed service, the cost of outsourcing delivers obvious value. 

So, once again, managed services can deliver greater value to businesses than self-service. Specifically, performance-driven managed solutions will take us into the future of the digital marketplace. Otherwise, brands and agencies must figure out how to drive ROI from their in-house solutions that can compete against what specialized managed solutions provide. “Good enough” won’t win against “highest quality.” Businesses looking to in-house tech must seriously consider whether they have the resources to go far beyond “adequate.”

AI Can’t Do All the Heavy Lifting 

Considering the direction so many conversations in the industry have gone over the last several months, you’re probably thinking: Why can’t businesses use AI to tackle some of these challenges? AI does hold promise. But it’s not about to relieve the kinds of headaches brands and agencies are dealing with today. AI may lower the cost of automation, but it still requires a great deal of human oversight, verification, and cross-checking of output and recommendations. 

Innovators must make AI results more consistent, comprehensive, and less prone to inadvertent bias or compliance risk. We should expect this process of optimizing AI tools to play out in years rather than months. In advance of any breakthroughs AI may have in the next five years, companies that want to play ball in the current digital landscape will need managed services by real people.

A Broader View of the Marketplace

Another key benefit of bringing in managed services: You can learn more about the right strategies for a business from the outside than from the inside. We can’t underestimate the value of specialization and customized services. This is one of the top takeaways brands and agencies have gained from the in-housing trend: The skills they wanted to take in-house are too specialized to find all the talent necessary.

Managing first-party data, for example, is a primary focus among brands and agencies, and outsourcing complex data-related tasks is far more efficient than building internal teams. Businesses finding external partners can help them build relationships across the digital ecosystem while recognizing internal teams’ blind spots. 

It’s not as though managed services are replacing in-house teams. Instead, they give in-house teams the ability and flexibility to use a variety of partners that can create synergies in the right structures and ultimately benefit the business’s bottom line amid such digital complexity. Businesses weighing the benefits of in-housing versus outsourcing need to ask themselves: Do they have the internal resources to create the same ROI as a managed-service partner, given the tasks and goals? Industry leaders must look at the best drivers of performance and the best ways to position themselves strategically and competitively in the industry.

The post The Big Debate: Is In-Housing Dead? appeared first on AdMonsters.

While there is a ton of opportunity in the retail media world, there are still challenges. Those opportunities and challenges were top of mind at the 2023 IAB Connected Commerce Summit: Reimagining Retail Media event, where industry experts expressed their views on prioritizing consumers’ needs and the importance of privacy as a trend and strategic imperative.

Driven by technological advancements, changing consumer behaviors, and the need for effective audience engagement, brands are embracing that the future of retail is omnichannel. Likewise, publishers — as partners of retail media networks, providing offsite access to an extended audience — are walking the customer-centric walk. 

Prioritizing a Consumer-Centric Approach

During the “Building Consumer Trust in Retail Media” session, all panelists agreed that putting consumers first does wonders for your business. Yes, your relationship with your partners and intermediaries is essential, but the most important relationship a brand or publisher can have is the relationship with their audience. 

“Consumers need to be at the center of everything, as your relationship with consumers is more important than the advertising,” explained Peter Barry, Vice President of Addressability at PubMatic. “What you do with data, what sort of partners you work with, you have to look through that consumer lens.”

The value exchange you demonstrate with your consumers is a win-win because retailers benefit from profitable business lines that allow them to reduce sales fees, which is a plus for the consumer. 

Danielle Brown, Senior Vice President, Data Enablement and Category Strategy at Disney Advertising Sales, made it clear that at Disney, the customer experience always comes first, from their theme parks to their streaming platforms. 

“We have spent years building a proprietary audience graph, allowing us to target consumers with highly relevant ads,” Brown said. “The goal is to provide consumers with content and advertising that resonates with their true needs and preferences.”

Transparency and building consumer trust are primary aspects of the retail media business. Since retailers have a surplus of consumer data, responsible data handling is paramount. With this data, retailers can provide valuable consumer insights and media consumption behaviors, closing the attribution loop. That is why starting with a healthy commitment to transparency is the key to success.

Privacy Management: Transparency’s Three Dimensions

When communicating your value exchange, it is necessary to consider consumer privacy as a strategic choice. Why are we collecting their data, and how does it improve the consumer’s experience? Communicating why you are collecting their data and how it improves their experience can go a long way to building and maintaining trust. Transparency is key.

Agencies also play a crucial role in ensuring a better consumer advertising experience, so they must hold themselves accountable for respecting consumer data.

Transparency has three dimensions, according to Amie Owen, US Head of Commerce at UM Worldwide. “First, building trust with your consumers is important by clearly demonstrating the value exchange. Second, it’s best to be transparent with clients, ensuring that all activities are shared and the learning is mutual,” she stated. “Third is nothing other than simplification. Simplify the processes for retailers, consumers, and your internal teams.”

Shifting from Retail Media 1.0 to Retail Media 2.0 

There is a shift happening in retail media from Retail Media 1.0 to today’s Retail Media 2.0. In the early days, Retail Media 1.0 consisted of retailers realizing the power of media revenue and using their platforms to display ads and monetize their audience. Sounds like easy money, right? We’d say so, but things are changing now as consumer expectations changed.

Retail media 2.0 looks at consumer behaviors to focus on their wants and needs, creating the need for a more sophisticated approach. This new version of Retail Media is about establishing a more integrated and collaborative approach between retail and media, focusing on standardization and better measurement practices. It also addresses the challenges of major players like Amazon and emerging Chinese platforms like TikTok, Shein, and Temu. 

During the “Retail Media 2.0: Balancing Personalization and Monetization” session, panelists stressed the importance of embracing a 360-degree approach. Seamlessly integrating physical and digital retail experiences can lead to substantial growth and better monetization.

Looking Forward to the Future of Retail Media 

In the future, AI will play a critical role in retail media, just as it is in every other aspect of digital media and ad tech. For now, AI is being used to redefine data segments and provide personalization for users. However, the long-term implications include machine learning systems taking over the more tedious tasks for shoppers. 

There are several challenges and opportunities in retail media. These include standardizing measurement metrics, closing the gap with industry giants like Amazon, fostering a healthier retail media ecosystem, and building a more diverse talent pool. The future is bright, and while challenges exist, improving the consumer experience is crucial to navigating the challenges.

The post Customer Centricity: The Key To Retail Media’s Successful Future appeared first on AdMonsters.

With ID deprecation well underway and consumer privacy legislation on the rise, publishers face more complex obstacles than ever before. Yet the consumer expectation for personalization remains, as does the extreme competition for engaged eyes and ears. 

When it comes to evolving data monetization, publishers are positioned at various levels of sophistication and preparedness. Notably, each publisher possesses a unique composition of data signals. While some are blessed with substantial strong quality 1P signals, others rely more heavily on cookie-based identity, with limited access to alternative identifiers. Given these diverse circumstances, there’s no one-size-fits-all solution. Nonetheless, there are best practices and levers of control you can employ to shift your strategy and mitigate risk.

The pivotal question emerges: What is the optimal place to start, and what are the best practices for privacy forward data monetization?

First and Foremost, Visibility is Key

A critical place to start is with a thorough understanding of the data signals you have in your arsenal and the data solutions you’ve been selling. Many publishers I’ve spoken with have a significant blind spot when it comes to understanding their data signals and data solutions. You’ll want to understand what percentage of your overall revenue is data-enhanced or has associated targeting. 

Ask yourselves: 

• Of the data I’m monetizing, how does it break out by data source 1P/2P/3P? For 3P, what is the breakout of that partnership share? 
• How does what I’m selling break out by different sales channels so that I understand who’s buying? 
• What about margin and sell-through against these audiences, and how are the patterns changing over time?

Eliminating this informational blind spot is critical to understanding the associated risks and opportunities, as well as enabling the planning of a successful pivot. This tangible data will also be helpful for internal stakeholder understanding and garnering support for subsequent resourcing.

Understand & Prioritize Demand

Likely, you won’t be able to find or create alternative solutions for every audience that once visited your properties. Therefore, it’s imperative to use your analytics and market-facing resources to understand and prioritize demand commensurate with the revenue opportunity. This way, you can best harness your time and resources for the audiences to drive the most data-enhanced revenue.

Diversified Solutions. Play to Your Strengths 

As I previously stated, there is no singular solution for any given publisher, so tactics will vary from publisher to publisher. Thus, the critical question surfaces: Are you maximizing the existing signals and capabilities and creating new signals and solutions?

First Party Data. You knew this was coming. We can answer in unison that 1P strategy has to be an area of focus, but what steps are you taking to maximize the impact of your 1P assets? Pep talk — this is data that’s differentiated to you, isn’t commoditized (hopefully), and is within your control to be of solid quality and lasting. Evaluate and consider all the declared, observed, and inferred data sets at your disposal. Are you leveraging them to create desirable solutions? Are there opportunities for you to develop panel-based offerings and modeled solutions? Always remember the relationship between scale and precision to develop offerings that will adequately map to your client’s needs and KPIs.

Not every publisher’s business is well poised for a login. Having a logged-in user creates immense opportunities for 1P offerings. Remember that logged-in doesn’t mean a paywall, nor must it be required or offered for an entire user base. There are many best practices a publisher can utilize to increase a user’s likelihood of logging in. It comes down to value exchange and whether or not you reward users properly for the information you want them to share. 

Ask yourselves: 

• What is your primary asset that might be valuable to exchange? 
• Is there early access to information, premium features, events, trials, etc.? 
• Is there a subset of your audience that would be highly receptive to a login invitation? 
• What cuts of your audience or questions might you want to test? 

To succeed in this capacity, you’ll want proper value exchange and to make the login process as frictionless as possible.

Contextual. Contextual solutions have many benefits, and increasingly, marketers are seeking these offerings. Absent reliance on individual identifiers, contextual solutions are privacy-forward and offer efficient real-time adjacency to content of interest. Contextual offerings should be low-hanging fruit for every publisher to explore and create aligned to customer needs.

2P Data. Marketer use of their 1P assets has been steadily growing for years. Brands have been making strides in increasing these data sets and their sophistication in practical use. Having the technology, process, and business guidelines in place to partner with marketers in this way will open up revenue for publishers.

Data Collaboration. Data Clean Room solutions have the potential for privacy-safe data collaboration and many clean rooms support use cases for activation, data enrichment, as well as measurement. Initially slower than expected adoption, marketers, pubs, and agencies are increasingly evaluating Data Clean Rooms. They also open up the possibilities for increased insights-based selling, particularly for publishers who don’t have their own proprietary insights tools.

ID Solution Testing. Given the many ID solutions available in the market, there is potential for enabling cross-device audience reach. Evaluating and testing these solutions is another lever for publishers to flex amidst declining identifiers to garner scale and performance potentially.

Packaging & Pricing. In addition to better leveraging existing assets and creating new solutions, consider your packaging and pricing efforts. 

Ask yourselves: 

• Are your data offerings structured optimally and priced to yield maximum market value? 
• Are you allowing customers to buy your most premium targets without minimum spend requirements or media commitments that will make their media efforts more impactful?

Sales Enablement & Commercialization

The evolution of your offering will only be as good as your ability to communicate and sell through these changes to your buyer. Be sure your evolving data strategy is also effectively commercialized and communicated to sales. You can’t overstate the complexity of these changes, so you’ll want to be thorough in your rollout to sellers and those on the front lines. 

Remember that these challenges are industry-wide and not unique to any given publisher. Continue to hone reporting mechanisms and put the proper market feedback loop in place so that you can monitor your progress, improve, and drive replicable wins. 

The post Data Monetization in the Era of ID Deprecation: Best Practices to Pivot and Evolve Your Data Strategy appeared first on AdMonsters.

In this context, Cornelius Frey, Co-Founder and CEO of Opinary, outlines his company’s approach to collecting and leveraging first-party data through interactive user engagement. That offers not only a solution to the challenges posed by the demise of third-party cookies but also holds the potential to reshape the future of digital advertising. 

By seamlessly integrating polling and voting tools into the online experiences of top publishers, amongst other things, Opinary fosters genuine connections with users, producing high-quality data that is willingly shared. 

Don’t sleep on the power of first-party data—whether you’re thinking about cookieless environments or not—because you cannot underestimate having direct connections with your audience.

Opinary’s First-Party Data Strategies

Andrew Byrd: Can you tell me about Opinary and how your company works with first-party data?

Cornelius Frey: Opinary entirely changes the way, quality, and scale of how first-party data is collected: away from prying on users’ behavior to try and infer who they might be or what they might want – and towards building an open, ongoing dialogue with users that they willingly engage in. 

This dialogue on publishers’ sites creates a triple impact:

• Better page metrics and audience relationships
• Additional high-quality, non-invasive ad inventory
• A key source of scalable first-party data 

AB: Your voting tools are a core part of your business? Why is this an important facet? Does this help with your first-party data assets? 

CF: We use polls that ask pertinent questions in the middle of a publisher like, say, NBC, the FT, the Times of London, or Der Spiegel, and have over a quarter of a billion users interact with these every month. Users engage because they have a view and – a core human trait! – they want to see how they compare to millions of other users. 

For instance, they will want to see precisely why other readers may also be interested in buying that electric vehicle – and will happily compare themselves on socio-demographic dimensions. Any data we ever collect is actively declared by our users, raising both its quality and privacy compliance compared to existing data solutions in the market. 

The Cookieless Concerns

AB: The entire industry is preparing for the complete deprecation of third-party cookies. Why is first-party data critical in preparing for this industry change?                                   

CF: As the pendulum swings away from third-party cookies, publishers have the chance to play a vital role in helping advertisers still run effective, performant campaigns – and regain control and benefit from a more critical position in the value chain, rather than being just the providers of pixels on their page for ad inventory. 

This is because their intimate knowledge of their audience – beyond mere contextual signals – can help deliver campaigns targeted in full privacy compliance even after the end of the free-for-all third-party cookie bonanza, for instance, via premium directly sold seller-defined audiences or by enriching their programmatic offering. Publishers have been doing a great job building the pipes for that transition through upgrading their DMP infrastructure, for instance. They must fill those pipes with first-party insights about their audiences at scale. That’s where Opinary audiences come in. 

The Publisher Benefits

AB: How are you working with publishers like The Times and Yahoo to use first-party data to enhance their advertising strategies?

CF: Integrating our tools helps these publishers increase the scale of first-party data directly collected by a factor of >3x, as well as the quality: it delivers signals of intent that are so strong that they provide an immediate performance uplift in advertising campaigns enriched by them. 

We work with publishers directly and with ecosystem partners like Piano, Adobe, and 1plusX to help lift the potential of first-party data and sell better, more performant campaigns at higher CPMs. Along the way, the engagement we create increases time on site, and we drive newsletter sign-ups and subscription rates by converting highly engaged users post-vote to the publisher’s most relevant offerings. 

AB: Any final advice for publishers and advertisers who want to use their first-party data assets to the fullest? 

CF: The most promising strategy for using first-party data assets goes to the timeless core of good journalism: engage your audience directly, don’t be afraid of asking them questions, and be open and honest about the excellent value exchange that can happen when you build a direct relationship with your readers, rather than relying on an ecosystem of middlemen. Given where industry and regulatory trends are going, for those publishers embracing this, there may be a bright future for digital publishing around the corner, and we’re happy to be a part of it. 

The post Opinary’s First-Party Data Strategies: Building Audience Engagement and Publisher Success Through Meaningful Interactions appeared first on AdMonsters.

From the start, Jon Roberts kicked off PubForum Coronado Island with profound insight giving the event great momentum. Much of the audience left with the lasting idea that sometimes unexpected journeys lead to groundbreaking discoveries. 

Don’t be afraid to take risks and try new things, publishers. We see this through Roberts’ unique career journey and his assistance in shifting Dotdash Meredith to focus on improving user experience instead of bombarding users with ads. The strategies he and his team implemented to increase user engagement and better understand the publisher’s audience helped reshape Dotdash Meredith’s revenue model positively.

While his journey from research scientist to a digital media professional might seem far-fetched, this path is more common than one may think. From this crossover of disciplines, we see that data analysis, experimentation, and problem-solving skills from the scientific world are of high value in digital media. 

There’s a science behind increasing revenue and effectively targeting audiences in a cookieless world. According to Jon Roberts, these are your four keys to success:

Take Risk: No Risk, No Reward

If there’s one thing science and data have in common, it’s experimentation. Starting his career focusing on dark matter and cosmic phenomena at prestigious institutions like CERN and NASA, Roberts sees data as the central theme in making a transition from science to digital media. Our industry holds loads of data, and its potential for guiding decision-making and audience targeting is immense. The scale of data available presents a playground for experimentation.

At Dotdash Meredith, Roberts and his team implemented transformative strategies that seemed crazy at first since they challenged the conventional approach. These moves were made when the company was small, so at that time, no risk meant no reward. They took revoked ads from web pages in hopes of enhancing user experience. While this calculated risk initially seemed backward, it paved the way for their innovative revenue model. 

Analyze your practices and closely examine ad placements. This can help you identify bad ads. At one point, Dotdash Meredith had to remove a ton of ads from their webpages. This move initially hurt their revenue but helped shape the advertising landscape overall. 

Unravel the Floor Pricing Strategy

Floor pricing can be very complex, which is why it is important to think strategically. According to Roberts, the first step is to break down the value of all the slots to learn what the market will pay. Different domains have different values. Different content drives a different value and then different slots. 

When you look at those features and floors by grouping your inventory that fallsl into these buckets, you can see valued inventory and then push the price up to see how the market responds. 

“We intentionally let 15% of the ads go to house ads because that actually makes us more money because it pushes up what people pay,” Roberts explained. “If you let people buy that 15% of inventory for what they’ll pay for it you get all the long tail scammy advertisers of the internet buying them for pennies. If you put the floor at $10, for example, the people who would have paid $5 for it end up paying $10.”

Develop a Real Understanding of User Intent 

Understanding user intent in the present moment is far more valuable than relying solely on historical data. It’s time to say goodbye to the cookie-based approach and hello to an intent-based approach.

Roberts encourages publishers to think more keenly about intent-based targeting, as it harnesses real-time users’ behavior on content from their tailored ads to match their behaviors. Users’ interests and actions are in constant flux, so present behavior must be at the forefront. 

When you work with the right advertisers, on the right content, with the right message, you will see your engagement go through the roof. If a consumer is on a page doing one thing and the ad on the page is relevant to what they are doing, they will surely click it. 

Historically, contextual targeting doesn’t scale, so you have to talk about the context on the page and feed the user’s intent. 

Think Outside the Typical Measurement Box

Another thing that Roberts highlights is that targeting is easy, but measurement is hard, and while calling targeting easy may be a stretch, getting the targeting to work is relatively straightforward. Getting it to run through all the pipes is more of a challenge because the businesses are so reliant on cookies at this time.

At DotDash Meredith, they are experimenting with some SSP and DSP partners, and learning just how deep the cookie logic is in the weeds. This is where measurement is critical Roberts says, “If you can run a campaign on a cookieless market but can’t explain to your boss that it worked and you cashed out, what’s the point?” 

“We just have to acknowledge that we could never measure everything. If you go through the list of ways clients are looking to measure the efficacy of campaigns, you’ll see first click attribution, or even 30-day lookbacks,” Roberts explained. “But you also have sales lift, brand lift, foot traffic to store. The industry has told itself that deterministic tracking of Internet ads is the only way to do it. So, therefore, if you can’t track, it doesn’t exist.” 

Work with your Privacy Sandbox teams. Targeting is a piece of that, and much of Privacy Sandbox is about measurement and attribution, PPID for frequency capping, and the attribution API to have anonymous but full attribution. These are all tools that need to exist to solve the measurement problem. 

From being a physicist to transitioning into the media industry, Robert’s story is a testament to the power of multidisciplinary thinking and applying scientific principles to solve complex problems in new domains. He has used his expertise in data analysis, experimentation, and understanding complex systems to pave the way for innovative approaches to user experience, targeting, and measurement in the digital media landscape. 

As the ad tech landscape continues to evolve, the infusion of scientific thinking has the power to drive the industry forward.

The post Identifying the Broken Publisher Revenue Model to Create New Opportunities appeared first on AdMonsters.

With billions flowing through programmatic channels worldwide, the incentive for fraudsters to ply their craft was just too great.

Finally, the industry had enough. In 2014, the Trustworthy Accountability Group (TAG) was established to cultivate confidence and trust in digital advertising by facilitating collaboration among players across the supply chain to uphold quality and brand safety standards.

On June 21, TAG released its fifth consecutive fraud benchmark report for Europe, and for a fifth year in a row, IVT rates in TAG Certified Channels were below 1%.

Some Channels More Problematic Than Others

At least in Europe, some channels are more problematic than others. For instance, desktop display and video have IVT rates of 1.54% and 1.30% respectively. CTV isn’t far behind with 1.28%.

CTV Improved Steadily throughout 2022

Throughout 2022, CTV IVT rates exhibited a downward trend in each quarter, but it is important to note that this pattern may not necessarily reflect future trends as it could be influenced by other factors within the CTV marketplace.

Mobile in-app video and display formats consistently maintained lower IVT rates throughout the quarters, exhibiting stability over time.

The Caveat

It’s not as if all campaigns in the European markets studied show low rates of IVT. The report takes pains to point out that less than 1% fraud is only attainable in campaigns that run through fully TAG Certified Channels. These are channels in which every entity — publisher, ad tech platform, agency — have achieved TAG Certification Against Fraud.

The post What 5 Years of Minimal Fraud Should Tell the Market appeared first on AdMonsters.

The same was true when she first started in the workplace, very different from the era of diversity, equity, and inclusion we proclaim now. Despite some underlying racial tension, she allowed her work to speak for itself and has subsequently touched every side of the ad tech industry.

Eng watched the digital media industry evolve into what it is today, and now she works with the IAB as VP of Measurement, Addressability, and Data Center. Her focus at IAB is setting standards, best practices and guides for various topics such as cross-channel measurement, data clean rooms, attention metrics, terms & conditions, etc. One she considers a challenging but fulfilling position.

“When I started working at IAB, Google had just announced the deprecation of the third-party cookie. The industry was evolving just as I started a new career phase, ” Eng said. “Going in, I knew that there were going to be some complex challenges in terms of what we could tackle and what we couldn’t and that we’re probably not going to satisfy the entire industry. Everyone’s always looking for standards. But at the same time, it’s not an easy process and requires a lot of patience and collaboration.”

Early Childhood: Finding Space and Identity

Andrew Byrd: Can you tell me a little about yourself? Where did you grow up and how did your upbringing influence your character and work ethic today?

Angelina Eng: I grew up in a blue-collar family. My father worked in a jewelry manufacturing company, and my mother was a seamstress. She also tried entrepreneurship with a dry cleaning business and owned a sewing factory and jewelry store for a little bit. I could see my parents working hard to acclimate to the neighborhood, my father more than my mother. That mentality has influenced me to this day.

At home, we were very in tune with our Chinese culture, but on the outside, I was an outlier. Outside of my house, it was tough. I was one of the few Asian people in my community, and it was difficult not to experience some form of racism when that was the case. I was one of the shortest girls in class. I didn’t wear the same kind of clothes that everyone else did. I wore the bottleneck glasses. I always had the sense of being the odd one out.

I remember feeling the same way going into the workforce. I started at Y&R advertising, and the industry was still predominantly white male, but I did have a lot of women role models in the organization. There was no overt racism, but an underlying sense was apparent. I remember the executives would often look to others for new pitch meetings. So I had to learn to have a voice and I took on the philosophy I heard from the animated movie Robots. It said, “You find a need, and you fill a need.” I wanted to let my work speak for itself.

Finding the Right Career Path

AB: How did you start your career in ad tech and digital media? 

AE: It’s a funny story. I started school pursuing a psychology degree, but my classes were at 8 in the morning, and I didn’t do well. I started accounting afterward but could not get past macro and microeconomics, which were too structured. My final major was home economics, now called consumer and life sciences. It was more than just cooking and sewing. We learned nutrition, but there were also some marketing and strategy courses. That’s where my interest in advertising started. 

To get my foot in the door, I started working as an administrative assistant in the U.S. Army account at Y&R, and this was around the time the internet was beginning. One of the VPs at the company was responsible for launching the Army’s first website. I worked with them and the digital team to build the website internally through an up-and-coming company called Brand Dialogue. During that time, I had to decide if I wanted to go the traditional media route or take a risk and join this new digital medium on the rise. They had a position open, and I used my experience from the Army account and joined the digital side of the group.

The Evolution of the Digital Media Industry

AB: You are an ad tech vet with over thirty years of experience. What are your thoughts on how the ad tech ecosystem has changed over the span of your career? Has the evolution been good, bad, or a mixed bag? 

AE: So many things are still the same but have evolved drastically over time. When it comes to measurement, there’s been much sophistication that has happened over time. There was no ad serving, DSP, or social media when I started. There weren’t these dashboards that people could go in, and suddenly their campaigns were running.  

Brands’ general business needs and philosophy regarding targeting audiences and connecting with outcomes have stayed the same. What has changed is the data set and the amount of data we have. We’ve also come to a place where we need to be conscientious about consumer privacy, which we didn’t consider before. It’s only been within the last three years that it started to be concerning. Much of that has to do with a couple of different forces. One is remarketing. We have companies with programmatic and remarketing technology solutions that consumers and government representatives believe that the industry wasn’t being responsible with data privacy, and consumers became aware of that. Cambridge Analytical exposed consumer data was being shared with companies they didn’t even know existed.

There was also the rise of big tech and the walled gardens. They’ve created a marketplace where some publishers and advertisers believe they have very few choices but to go through them. They feel they have little options to scale their business without particular walled gardens.

Working Towards True DEI

AB: Like other industries, the new era of digital media also strongly focuses on DEI standards. How do you think the ad tech industry is handling the move toward diversity for the AAPI community and other marginalized groups? 

AE: When it comes to DEI, we’re starting to have good conversations and some progress. It’s become elevated within the last year and a half to two years. We’ve talked about it for a long time but have not reached the point where we’re all satisfied. I love seeing more diverse commercials and ads that reflect various groups. Although, I do think there is lack of Asian representation. Usually, when people talk about diversity, especially when they decide whom they are marketing and messaging, Asian Americans are not a priority or first to come to mind.

There are also a wide variety of ethnicities and cultures within the Asian community, so it is a challenge to understand how to market toward them. From Chinese to Korean to Bangladesh, we are all so culturally different. That can be difficult when trying to speak to the Asian community.

Here at IAB, we’ve discussed how brands commit to spending X percentage of their spend toward diversity or minority-owned or focused content. There’s a struggle with investing in accredited companies, wanting certain-sized companies, and worries about whether a company is culturally relevant to that community. But how brands invest is not all equal. It’s discouraging that companies are like, let’s invest 3% or 6% of our spend on diversity, but that is not close to reflecting the actual diversity in the country.

AB: Any final words you would like to add? 

AE: I’m most proud that during my career, I got to be a representative and a figure in the industry where you, as an Asian American, can have a voice, thrive in different areas, and don’t have to pigeonhole yourself into a career set. I went from account management, media planning, buying to ad ops to analytics, and now I have a position that encompasses all that. 

People must expand their skill sets, knowledge, and network as much as possible. If you’re Asian or part of a marginalized group, it’s important to represent you front and center.

The post Celebrating AAPI Month: Angelina Eng Reflects on the Evolution of the Digital Media Industry appeared first on AdMonsters.

The daily routine of an ad ops manager, whether they work for a marketing agency or represent a web content publisher, is pretty much like a board game. Stumbling blocks are all around, even when they do not expect them. Not that ad ops managers should “beat the card” in the blink of an eye. Otherwise, the challenge isn’t considered accepted, and the cost of failure is too high, like lost revenue, customer churn, or rising TCO. 

Are there lifehacks for ad ops managers to come out on top even when the cards and fortune seem to be against them? We’ve gathered grandmasters around the table for the Ad Ops Challenge board game.  

Meet Vladimir Lyubarskiy, Oxagile’s Chief Solution Architect, who’s an old hand at this game, continually interacting with ad tech clients, knowing their reasons for frustration inside out, and helping them deal with it.  

We also have a guest, Oxagile’s ad tech expert partner and advisor, to absorb his business advice on how to counteract ad ops issues — whether a supply or demand-side pain — on the go. 

Are you up for the Ad Ops Challenge board game? 

Showing the First Card “DSP Diversity” 

What challenges does it hide? 
Disparate statistics

Scenario Behind 

An advertising operations manager at a marketing agency is sick and tired of accumulating ad statistics from miscellaneous demand-side platforms. Aiming to address all client wishes, the agency picked five DSPs for daily use, including DV360, The Trade Desk, and Samsung DSP, which added to the headache caused by exhausting reporting activities.  

Days are stolen from extracting data from several isolated systems and then aggregating uncoordinated reports into one clear picture to demonstrate ad efficacy. Good old methods like Google Docs do not work, as they’re more about manual operations than process automation. The question is, how to redeem the ad ops manager from professional burnout?

What the Move Should Be 

Vladimir Lyubarskiy: “That’s exactly the story we banged against while liaising with a digital advertising agency operating across the Latin American market. A couple of DSPs were actively utilized – and tons of side effects to overcome, among which was a daily reporting challenge.  

Instead of persuading the client to make do with obsolete would-be reporting tools, our team designed the architecture of a DSP aggregator solution. Its primary benefit for reporting was the ability to gather the advertising statistics from all DSPs to introduce meaningful dashboards to all interested parties.” 

AdTech advisor: “Occasionally, the DSP Diversity card represents a no less serious challenge for ad ops managers serving the supply side’s best interests. They’re permanently watching how their inventory spaces perform, aiming to generate win-win sales packages that are both highly demanded by their clients and profitable for their business.  

An aggregation tool can go far beyond DSP functionality and speed up getting the insights for AdOps specialists responsible for managing multiple supply-side solutions.” 

Image: DSP aggregator solution architecture 

The Next Card Is “Campaign Setup”

 Is any challenge concealed? 
Wasting time and efforts 

Scenario Behind

The more manual movements involved, the higher the risks of errors during the ad campaign setting processes. An AdOps manager, who works for a digital advertising company, relies on a handful of DSPs, which slows down the launch of any advertising activities.  

Despite utmost concentration, he’s not immune to flaws, as each system incorporates a few specific nuances related to ad campaign tunes. Maneuvering between different DSPs commonly crystallizes in accidental processing lapses. What about fixing this human-centered, error-prone paradigm? 

What the Move Should Be 

AdTech advisor: “It’s not rocket science, but automation is key. The right strategy is to seize the opportunity given by ad campaign runner software solutions instead of going on with tiresome hand labor leading AdOps managers to nowhere or too ungrateful processing and poor ad campaign outcomes.  

On top of multiple DSPs, such tools introduce a common UI for ad campaign setup. No need to follow a longer route by switching between DSPs and tracking custom settings for each. You want to make essential changes once, and they’ll be scaled across all DSPs.” 

Vladimir Lyubarskiy: “That’s the scheme that works for our AdOps Challenge board game in case ad operations specialists suffer from the tedious ad campaign creation. From a technical perspective, it’s possible to integrate all DSPs taking part in the ad campaign management under one roof through an API – no cheating, process optimization only. A unified UI marvels when there’s a need to switch between ad campaigns and perform tiny fixes instantly. 

It’s High Time for the “Performance Metrics” Card  

Any hidden threats? 
No unified measurement  

Scenario Behind

The heterogeneity of ad campaign performance metrics, depending on distribution channels (linear, digital, or CTV) and geo, audience, and device type, hinders an AdOps manager from making up an all-embracing picture of an ad campaign’s success. When clients’ expectations are not satisfied due to the absence of measurability standards (they’re frustrated by disputable performance measurements), the AdOps specialist experiences the drawbacks of linear TV measurement and fights against CTV attribution issues.   

Feeling the acute need for a functional measurement solution, he’s querying which would be the best bet here. 

What the Move Should Be  

Vladimir Lyubarskiy: “Some of the ad campaign requirements can be addressed by involving existing platforms and audience measurement products like Samba TV. 

Pay heed to Nielsen, which laid a foundation for linear TV advertising measurement. Despite being considered a bit outdated, it’s moving forward and introducing a new Nielsen ONE Ads product for measuring media. Comscore, VideoAmp, and iSpot.tv also act as advanced solutions for ratings and audience measurement.”

Let’s Move on to the Card “Smart Targeting”

What does it keep from us?
Lack of data 

Scenario Behind  

A marketing agency’s bidding around all media channels is still far from the ultimate bidding strategy. The absence of their data for a more thorough analysis prevents them from enriching DSPs’ significant data selection. Is a shift from an all-around ad presence to smart bidding possible? And if so, what are the ways to target more wisely and access lucrative audience categories? 

What the Move Should Be 

AdTech advisor: “While marketing agencies suffer from the lack of fully owned audience records, even companies with the ability to collect such data also experience targeting issues. Significant data losses are common after the data management platform (or DMP) processing steps in, so it becomes challenging to reap their fruits. 

To recap, brands with data sets can’t avoid a partial leakage after sending data to DMPs when bringing them to a common standard. No in-house data available? This case jeopardizes the efficiency of ad targeting.” 

Vladimir Lyubarskiy: “To be fair, publishers and content owners are not sitting on their hands, continually combating this data lack issue through metadata enhancements. Although metadata management allows for enriching audience data with contextual, some unsatisfied demands on the advertisers’ side remain. The latter needs a more thorough understanding of the environment where their ad assets occur. And there are grounds for hope.  

Time to get out a Joker from the sleeve. Its name is Computer Vision, and this is one of the true ways to improve ad targeting tactics with AI technologies to gather contextual data for better comprehension of the audience’s needs. The prize will be optimized conversions.” 

“Order Management” Card Enters the Game 

What can go wrong here? 
Reconciliation hurdles 

Scenario Behind

An ad ops manager in charge of order management and tracking often finds himself at the crossroads, thinking about how not to get lost in numerous accounts and accurately process both incoming and outcoming payments.

In the meantime, multicurrency accounts and systems should be carefully managed, and this process is not necessarily automated, so the ad ops specialist should watch all transactions closely. 

Profit margin calculations also request careful guidance to gauge the revenue degree. Is this process doomed to chronic manual operations? 

What the Move Should Be 

Vladimir Lyubarskiy: “Not necessarily, if we choose the automation path again. This will provide us with a tool for accumulating all systems and line items to answer the question “Who owes who?” and generate unified reports transparently depicting all payment transactions.” 

“Client Collaboration” Card Comes Into Play 

There’s the snag! 
Processing lags 

Scenario Behind 

A huge TV production studio embracing many digital and linear channels is actively targeted at monetizing advertising across all these platforms. What’s going on now? The truth is that an ad ops manager feels ill at ease trying to wade through the info on the available ad inventory spaces scattered across a range of applications. Selling flow processing is full of pitfalls, which unsettles the advertising operations specialist and results in a few mistakes. Clients seem furious as their requests are kept on ice, and above all, it takes ages to generate competitive ad inventory offerings for advertisers the production studio collaborates with.  

What the Move Should Be

Vladimir Lyubarskiy: “Here I see the demand for converged video ad workflows around a multi-platform content distribution model. So this time, our Joker is likely to be called automation – we’re coming closer to the goal of monetizing advertising on both linear TV and digital (OTT) channels in an efficient fashion, leveraging an established process from direct sales of primary inventory to programmatic to backfill remnant inventory. 

A custom software solution will let the ad inventory seller switch between numerous apps, increasing the overall converged efficiency of an ad selling flow. Regarding the already existing options that help you manage linear and digital ads with relative ease, these are WideOrbit and Landmark. I’m not saying they are a plaster for all sores – they’re still offering different flows for linear and digital, which clamors for further adjustments.” 

Last but Not Least: “Chasing Higher Sales Revenue” Card

What lies beneath? 
Forecasting gaps 

Scenario Behind

Being a part of the TV industry’s leading content provider and distributor, an ad ops manager is becoming increasingly puzzled when brands and marketing agencies request the approximate spend on ad inventory. Making a bad bargain is likely to happen if not to generate different inventory package prices. But how do you determine which inventories should be higher priced so as not to sell too cheap? 

What the Move Should Be 

Vladimir Lyubarskiy: “I’d create a solution powered up with prediction mechanisms, letting AdOps specialists forecast impressions as accurately as possible across linear and digital channels. Why is it advantageous for both parties? The content distributor generates converged ad sales packages and determines premium inventory spaces, thus maximizing revenue, while their clients get a transparent picture of upcoming expenses.” 

Is there an AdOps Challenge card that’s still in the deck, unopened, that you want to beat? Oxagile has more Ad Tech tricks to help you achieve that. Just give them a sign, and you’ll triumph in this game. 

The post How to Win a Board Game Full of Ad Ops Burning Challenges 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.

TransUnion recently announced a partnership with Datavant, the industry’s most trusted health data connectivity solution. Datavant’s irreversible, encrypted “tokens” will help TransUnion match de-identified patient demographic data with healthcare clients’ first-party and licensed third-party data. 

We spoke with Michael Schoen, EVP of Marketing Solutions, TransUnion, about what the health ecosystem can expect and how this collaboration will affect healthcare publishers. 

Yakira Young: Can you go into more detail about TransUnion’s new partnership with Datavant?

Michael Schoen: In partnering with Datavant, TransUnion can now enable healthcare, pharma, and other brands to evaluate and optimize the effectiveness of their marketing efforts. The partnership will also allow Datavant’s ecosystem of partners to connect to demographic data available in TruAudience®, TransUnion’s comprehensive suite of solutions. For example, we see companies leveraging this partnership to measure the impact of marketing on prescription volumes in a HIPAA-compliant way and adjust their campaigns’ targeting and media channel mix to improve results.

YY: How does Datavant help organizations securely connect health data?

MS: Datavant works to reduce the friction of data sharing across the healthcare industry with technology that protects patients’ privacy while supporting the linkage of patient health records across datasets. 

As mentioned, the company’s industry-leading software generates irreversible, encrypted tokens to enable TransUnion to match de-identified patient demographic data with healthcare clients’ first-party and licensed third-party data. This enables organizations to understand better, reach, and measure the effectiveness of campaigns to specific audiences.

The top 30 pharma brands use Datavant’s privacy-first data connectivity solutions, more than 2,000 hospitals and 15,000 clinics.

YY: What are de-identified patient insights and measurement solutions, and how are they useful for healthcare brands?

MS: TransUnion connects its demographic and lifestyle data to healthcare data, while Datavant software enables de-identification tools, which do not leverage personally identifiable information, to help customers protect patient privacy. 

This integration will allow healthcare and pharmaceutical companies to improve outcomes across the full lifecycle of patient engagement, especially measurement of outreach effectiveness. 

YY: How will TransUnion’s TruAudience marketing solutions benefit healthcare brands in this partnership?

MS: The U.S. healthcare and pharma industries are expected to spend nearly $18 billion dollars on digital advertising in 2023 alone. We’re enabling them to spend these dollars in the most effective way possible. 

We can connect the dots between those consumers and physicians who may be exposed to campaign activity and those who are then writing prescriptions. It unlocks a much more granular view of marketing effectiveness in a privacy-safe way.

Beyond offering a measure of the ROI of outreach, the tool also allows for optimization. 

 Marketers can use it to fine-tune the channels used and personalize creative across audiences. TransUnion can leverage more granular-level data sets to fine-tune the optimization of marketing campaigns.

YY: Will patient privacy be protected while accessing health data?

MS: By working with Datavant and leveraging their tokenization technology, we can connect TransUnion’s consumer data in a de-identified and HIPAA-compliant way.

YY: How will this partnership impact health publishers such as Everyday Health and WebMD?

MS: TransUnion can now bring real-world data and its end-to-end marketing solutions to publishers. With TransUnion’s measurement solutions, healthcare and pharma companies will also gain more insight into which health publishers impact their campaigns most.

YY: Will health publishers have access to the de-identified patient insights and measurement solutions?

MS: Yes, Datavant’s healthcare data tokenization software can be utilized to implement TransUnion’s TruAudience marketing solutions across companies in the healthcare ecosystem.

YY: How can health publishers use this partnership to improve their content and services?

MS: Health publishers can now leverage this partnership to combine real-world data with TransUnion’s consumer insights, allowing publishers to tailor content and services around the most up-to-date demands and interests of consumers.

YY: What are the potential benefits for patients in this partnership?

MS: This partnership enables patient data to be used responsibly, as the tokens used are encrypted and irreversible, thus minimizing the risk of re-identification. In addition, this data will be used to improve aggregate patient outcomes.

The post Here’s How TransUnion Is Decoding Health Data With Datavant appeared first on AdMonsters.