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

Why Is Mobile Marketing Shifting to Privacy-First Advertising?

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

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

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

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

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

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

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

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

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

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

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

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

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

What About User Acquisition (UA) Campaigns?

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

What Can Mobile Marketers Do Right Now?

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

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

The past few years have been tumultuous for publishers. The on-again/off-again deprecation of cookies, concerns over MFA sites making programmatic advertising risky, and the rise of generative AI search decimating referral traffic have all posed significant challenges. Despite these hurdles, publishers continue to innovate. As a result, the majority anticipate revenue growth in the coming year.

In July 2024, we surveyed and interviewed publishers to gain insights into their revenue outlook and identify their top opportunities for growth. This report summarizes our findings.

Of course, much has changed since our survey, including Google’s decision to forgo cookie deprecation for the foreseeable future. Still, what’s clear to us is that the talk of cookie deprecation has prompted them to rethink the way they do business and how they can generate revenue.

Key Findings: Direct Deals & Audience Data

• On the whole, revenue will grow. Most respondents (60%) anticipate revenue growth, with 19% expecting significant growth and 41% anticipating moderate growth.
•  2025 will be the year of the direct deal, with 68% of publishers saying it represents their best opportunity for revenue growth.
• Monetizing audience data (50%) and creating new products (46%) are also seen as significant opportunities for growth.
• Looking ahead, 33% plan to leverage audience data, and 23% each consider subscriptions and licensing/syndication as new revenue streams.
• To support these growth plans, 71% of respondents plan to invest in new tools or technologies to ramp up revenue.
• The most invested tools include audience segmentation (65%), identity resolution (50%), and AI-driven/advanced analytics platforms (40%).

Enter your info to download your copy below!

The post Ramping Up Your Revenue: Digital Publishers Reveal Key Growth Strategies appeared first on AdMonsters.

Political advertisers are forecasted to spend over $12 billion across all channels during the 2024 election cycle, marking the highest spend in U.S. history, according to eMarketer. While a significant portion of that budget will go to linear TV, digital advertising remains a critical battleground. 

Election campaigns are turning to advanced techniques like bid shading to stretch their dollars in this high-stakes environment. But what does bid shading mean for publishers? Let’s dig into how this tactic impacts publishers, the challenges it presents, and how to navigate these waters during this unprecedented election cycle.

What is Bid Shading?

Bid shading might sound like some covert operation, but it’s actually a savvy strategy media buyers use in digital ad auctions. Imagine you’re at an auction, but instead of bidding wildly, you have an algorithm whispering the optimal bid in your ear. 

This algorithm analyzes historical pricing data, current market conditions, and the value of the impression to tweak bids just enough to win ad impressions without overpaying. The method is especially crucial in situations like political advertising where budgets, although large, need to be spent efficiently.

Example:

Picture a political campaign aiming to secure an ad slot. Without bid shading, they bid $10 and pay the full amount. But, with bid shading, the algorithm suggests $7.50 based on past data, saving $2.50 while still winning the spot and potentially saving the advertiser 25% on that impression.

The Impact of High Political Budgets on Publishers

With political budgets hitting an all-time high, this influx of ad spend can be both a golden opportunity and a potential headache for publishers. 

The Upside:

1. Increased Demand: More political dollars chasing your inventory means heightened competition, which typically drives up demand and fill rates.
2. Revenue Boost: Those previously unsold ad slots? They’re now hot commodities, filling up quickly and boosting your bottom line.

The Downside:

1. Revenue Volatility: While demand surges, bid shading introduces a layer of unpredictability as bids are adjusted downward, making revenue streams less predictable.
2. Inventory Devaluation: As campaigns use bid shading to cut costs, the perceived value of your ad impressions might take a hit, impacting long-term revenue strategies.

Navigating the Risks of Bid Shading

Bid shading isn’t just a double-edged sword — it’s a whole cutlery set. Here are the risks you need to watch out for and how to handle them:

Lower CPMs:

Bid shading typically results in lower cost-per-thousand impressions (CPMs). Some publishers have reported CPM drops of up to 20% due to bid shading. This is a direct hit to your revenue as bids are systematically adjusted to lower amounts.

What to Do:

Consider implementing dynamic price floors that adapt to market conditions in real time. This ensures bids won’t drop below a certain level, protecting your revenue.

Inconsistent Revenue Streams:

The dynamic nature of bid shading means your revenue from political ads can fluctuate wildly, complicating forecasting and planning.

What to Do: 

Leverage advanced yield management tools to analyze historical data and market trends. This helps you understand and anticipate the effects of bid shading, optimizing your inventory pricing and placement.

Competitive Pressure:

With multiple campaigns vying for ad space, the pressure to lower prices further increases, risking a race to the bottom.

What to Do:

Enhance your auction strategies with techniques like header bidding. By involving multiple demand sources, you can drive up competition for your inventory, balancing out the downward pressure from bid shading.

Making Bid Shading Work for You

Bid shading isn’t all doom and gloom—there’s a silver lining if you play your cards right. Here’s how to turn bid shading into an advantage:

Leverage Advanced Analytics: 

Investing in tools that provide deep insights into bidding patterns can help publishers adjust their strategies in real time and identify opportunities to maximize revenue.

Enhance First-Party Data: 

Rich, accurate data about audience segments can command premium prices, even in a bid-shaded environment. Investing in data collection and analysis can increase the value proposition for advertisers.

Dynamic Price Floors:

Setting smart, dynamic price floors can help you maintain control over your inventory pricing. Adjust these floors based on real-time market conditions, like time of day, user demographics, and current events to prevent your CPMs from dropping too low.

Auction Strategies:

Don’t just rely on traditional auction setups. Incorporate header bidding to get multiple demand sources competing for your ad space. Increase competition for inventory and mitigate the impact of bid shading from any single source by relying on multiple SSPs and ad exchanges. This improves the likelihood of higher bids, even with bid shading in play. 

Yield Management:

Invest in robust yield management tools and expertise. These tools help you make data-driven decisions about your ad inventory, optimizing pricing and placement to counteract the effects of bid shading.

Collaboration with Buyers:

Build strong relationships with your advertisers. Educate them about the value of your premium inventory and work together to establish fair pricing and bidding practices. This collaborative approach can lead to more stable and beneficial outcomes for both parties.

When in Rome Leverage Bid Shading to Your Advantage

Bid shading is here to stay, especially in high-budget political advertising cycles. Publishers who adapt and strategically manage their ad inventory can thrive, capturing the full potential of these high-budget opportunities.

While bid shading presents both opportunities and challenges, strategic measures can mitigate risks and maximize revenue. Implementing dynamic pricing, enhancing auction strategies, optimizing yield management, and fostering collaboration with buyers is key to navigating bid shading complexities and staying competitive.

Not all of the predicted $12 billion election cycle budgets will be subject to bid shading. Direct deals, bypassing programmatic auctions, will also play a significant role. Publishers offering unique value propositions, like highly engaged audiences or brand-safe environments, can command premium prices despite bid shading tactics.

The post How Bid Shading and the $12 Billion Political Ad Boom Could Impact Publishers appeared first on AdMonsters.

Media and ad tech conferences have been dominated by discussions about AI and cookie deprecation over the past couple of years. These are important topics, but one equally important topic gets less attention: data strategy.

Everyone wants the mystical data lake that will solve all their data needs and finally make them “data-driven,” the thing everyone claims to be but few actually are.

A data lake can be a great thing but, not unlike a normal lake, it can also be filled with toxic waste and be more like a dump than a beautiful lake anyone wants to touch. Just putting your data in a data lake doesn’t actually fix anything. A data lake is just a fancy marketing term for a database. 

The key to enabling your organization to make data-driven decisions is to make the data accessible to the whole organization and different stakeholders, including those who don’t have a computer science or data science background. 

For example, your ops team may want to know the latency of ad loading or be able to see how many impressions an ad unit generated for a certain audience. They shouldn’t need to know SQL to achieve that.

A SQL prompt (even though it is powerful and one of my favorite tools) won’t help, and a static dashboard won’t help either because you can only think of and design so many things ahead of time. You need something else.

3 Steps to Unlock Data for the Entire Publisher Organization

So, how do you make your data truly accessible — and understandable — to every relevant person within your organization?

1. Ensure you have a solid ETL pipe. You want all the data in one place, but more importantly, you want it normalized across your sources so you are actually comparing apples to apples when reporting. A business user shouldn’t need to know how Magnite or Index Exchange defines their ad types. Their tools should account for these differences.
2. Make the data accessible. Enable the data to be queried with easy-to-use tools that take care of the logic in the background. People are strapped for time, and if it is a hassle to get to the data — maybe they have to submit a ticket to the data science team and wait two weeks to hear back — they are probably not going to do it.
3. Monitor the data for accuracy. One thing that will definitely kill a data strategy is inaccurate or out-of-date data. If users can’t trust the data, they will not use it, instead retreating to manual Excel spreadsheets or other less effective methods.

A data lake won’t make publishers data-driven. But getting all their data in one place is indeed the first step to more efficient, data-driven decisions.

Normalizing the data, making it easy to query, and shoring up its accuracy will help publishers get the rest of the way so that “data-driven” is a real way of doing business and not just a nice-sounding slogan.

The post Data Lakes Won’t Make Publishers Data Driven. Here’s What Will appeared first on AdMonsters.

Floor pricing optimization is making waves again in the publishing world, but have we been overthinking it?

Kean Wang, VP of Product and Strategy at Intowow, dives into the evolution of floor pricing strategies and unveils a refreshing shift from complex mathematical models to the practical realm of behavioral economics. By understanding bidder behaviors and leveraging the strengths of Header Bidding and Google Ad Manager, publishers can streamline their approach and boost revenue without getting lost in the computational weeds.

Floor pricing optimization has regained popularity among publishers. Over the past five years, we have perfected our dynamic floor pricing algorithms. However, it wasn’t until a year ago, as we gained access to more data from major publishers around the world, that I realized we might have been approaching this problem unnecessarily.

For quite some time, we adopted a purely mathematical approach to floor pricing optimization, focusing on determining each price P that maximizes the RequestRPM according to the function 

RequestRPM(P) = SellThroughRate(P) × eCPM(P)

for each infinitesimally meaningful inventory segment. If demand is static, the calculations are straightforward and manageable. However, randomness introduces uncertainty in a more realistic scenario where hundreds of thousands of campaigns run concurrently and complete at different times. This uncertainty significantly complicates the computational process and requires intensive predictive modeling to find an optimal solution.

It turns out that an easy way out is to approach the problem from a completely different discipline – behavioral economics.

A Simple and Elegant Approach

In the real world, campaigns are managed by DSPs who bid for impression opportunities in auctions. These DSPs vary widely in their technical capabilities and operational strategies. So, if we could target the behaviors of different types of bidders and provide the right incentives and signals to facilitate communication and competition among them, we could reach an alternative solution that is more elegant. This approach allows the market to optimize by itself to maximize publishers’ benefits without too much interference and the need for excessive calculations.

Generally speaking, bidders buy through two open auction channels: Header Bidding and Google Ad Manager (GAM), both of which are extensively integrated by most publishers. By analyzing bidding behaviors across these channels, we have consolidated the following best practices:

1. For Header Bidding, set up floor prices low enough on SSPs to encourage bid tendencies but high enough to filter out low-quality ads.
2. On Google Ad Manager, use the winning Header Bidding bid prices and dynamically trigger Unified Pricing Rules (UPRs) to provide competitive price signals through Google Ad Exchange and Open Bidding.
3. Ensure that Header Bidding line items are correctly priced on GAM with your net earnings to facilitate an efficient unified auction.

These best practices take advantage of a key behavioral distinction between these two channels of bidders: 

Google Ad Manager bidders, predominantly Google Ads and DV360, primarily adjust their bids based on floor price signals, whereas Header Bidding bidders make extensive adjustments in response to changes in win rates.

Excessive floor prices do not stimulate Header Bidding bidders; instead, they block their bids and reduce competition. By allowing more Header Bidders to participate in auctions, we maximize the competitive bid signals sent to GAM. On GAM, triggering these signals with UPRs can restore the “last look” advantage for Google bidders, encouraging higher bids that benefit publishers. (Google’s decision to cancel this feature was due to pressure from other SSPs, but this move also negatively impacted publisher revenue.)

With more competitive bids from Google bidders taking over some winning opportunities from Header Bidders and driving down their win rates, Header Bidders are incentivized to adjust their bid prices, which in turn encourages more competitive bids from Google. This fosters a perpetual cycle of healthy competition across these two channels.

For publishers with extensive Header Bidding coverage, these best practices are generally sufficient. Beyond this, additional efforts would likely yield only marginal benefits unless you are determined to invest intensive R&D to further optimize price ranges specifically for Google bidders across each traffic segment, where the benefits could add up to be significant.

More About the Behavioral Distinction

Upon further research and some reverse engineering, we were able to gain a clearer understanding of the factors contributing to such a behavioral difference.

For DSPs, floor prices are one of the pre-auction signals useful for optimizing bid decisions to maximize campaign ROIs. However, for floor prices to serve as reliable indicators, the environment must meet three criteria:

1. Floor prices, along with the associated traffic metadata, should be consistently supported across all stakeholders.
2. Floor prices must maintain their integrity during transmission and should not be lost, overridden, or manipulated down the supply path.
3. To benefit from these signals, bidders must possess powerful predictive capabilities with the technical bandwidth to perform cost-efficient real-time calculations.

Only Google, with its unified and streamlined programmatic ad supply path, meets these criteria across all stages. Information from publisher web pages is collected by the standardized Google Publisher Tag (GPT) library, consistently formatted as ad requests, and transmitted to the centralized Google Ad Manager. From there, bid requests are uniformly assembled and sent to DSPs via a robust server-to-server connection using the Authorized Buyer Real-Time Bidding Protocol.

On the buy-side, Google Ads and DV360, operating with powerful predictive capabilities leveraging Google’s highly integrated cloud infrastructure, can accurately estimate ad performance using real-time client-side signals and determine reasonable bid prices for each impression opportunity before an auction occurs. 

In contrast, for Header Bidding, every bid request is processed by at least two entirely separate parties (e.g., publisher-hosted Prebid.js, vendor wrappers, or SSPs) before reaching DSPs. Even for large DSPs with strong predictive capabilities, such a fragmented supply path makes it difficult to ensure the integrity of information, forcing them to downplay the option of adjusting bid decisions based on real-time sell-side signals. A rather reliable source of information is win rate data, which each bidder processes post-auction but is often delayed and lacks granularity.

These disadvantages of Header Bidders are particularly evident when we compared bid CPM trends from early to subsequent ad refresh instances or across different ad position series. For example, for the same inventory, when comparing the CPM of the first ad to the fifth ad refresh, average bid prices from Google bidders can drop by over 50%.

However, for Header Bidders, the average win bid CPM only decreased by 3%, which falls within the margin of statistical error. Such inability to perform per-impression bid adjustments from Header Bidders can also be highlighted by the fact that, on average, they purchase the same inventory with the same level of CTR and viewability performance at approximately a 35% premium compared to Google bidders.

To further pinpoint the issue, we took the same Header Bidding bidder and compared its bidding behaviors across two different channels: Header Bidding and Open Bidding (a unified server-to-server bidding solution provided by Google).

Under the same floor pricing strategy for the same bidder, through Open Bidding RequestRPM could be improved by 8 to 10%, compared to only a marginal 2% improvement through Header Bidding. This suggests that a fragmented supply path is the primary factor preventing per-impression bid adjustments for Header Bidders, forcing bidders through this channel to forgo floor prices and focus on win rate signals instead.

Future Outlook for Floor Pricing Strategies

Floor prices, like other real-time client-side signals, provide valuable information that encourages bidders to recognize the fine nuances in publisher inventory. However, these signals can only be effective when information integrity can also be guaranteed across the entire supply path.

The above behavioral distinctions between Google bidders and Header Bidders underscore the importance of Supply Path Optimization (SPO) and demonstrate how a more streamlined supply path can encourage bidders to utilize more sell-side signals, ultimately improving efficiency across the industry.

But for now, with these simple yet elegant best practices, publisher ad inventory is effectively categorized into two groups: one with extensive competition from both Header Bidders and Google bidders, and the other with only Google bidders. Publishers with more inventory in the first category can significantly benefit from the competitive cycle facilitated by these simple steps.

However, for publishers whose inventory primarily falls into the latter category, an active floor pricing strategy using a traditional mathematical approach is still necessary to realize the huge growth potential from Google demand.

The post Are We Overcomplicating Floor Pricing Optimization? appeared first on AdMonsters.

Developed with insights from industry leaders like Paul Brenner at Vibenomics, the IAB and its partners designed the 2024 Digital Out-of-Home (DOOH) & In-Store Retail Media Playbook to enhance the execution of DOOH and in-store retail media strategies. The playbook serves as a guide for retailers and brands to navigate and implement these media channels effectively. It focuses on practical applications, advanced targeting methods, and leveraging retailer data to optimize shopper engagement and campaign success.

Brenner tapped into Vibenomics’ tailored approach to retail media to shape his insights for the Playbook. As a leader in providing in-store digital advertising technology and services, Vibenomics focuses on aligning with retail media owners’ business models, providing technology and infrastructure that respect ownership and operation dynamics. 

We chatted with Brenner about the roles of retail media, shopper marketing, and category teams in modern merchandising. Our conversation also explored advanced data targeting methods to understand shopper behavior and outline strategies for measuring the success of DOOH and in-store campaigns. Brenner provides insights into leveraging retailer data and in-store technologies to create a cohesive, dynamic shopping environment that bridges traditional merchandising with innovative retail media strategies.

Andrew Byrd: What is the primary focus of the 2024 Digital Out-of-Home (DOOH) & In-Store Retail Media Playbook?

Paul Brenner: At a high level, it’s crucial to understand the distinction between digital out-of-home (DOOH) and in-store media. The IAB faced difficulties because many mistakenly believed that DOOH included in-store media. 

After a thorough discussion, we concluded that DOOH ends at the venue’s entrance. The retailer and brand can achieve the most attributable results inside the venue. This is because in-store media is owned and operated, allowing for more direct control and measurement of impact. 

In contrast, DOOH is a third-party solution that operates independently of the venue’s internal media strategies. This fundamental difference in operation and attribution is why these two types of media are categorized separately and viewed through different lenses.

AB: What role did Vibenommics take in working on the Playbook and what perspective do you bring to the retail media space? 

PB: Vibenomics is designed explicitly for retail media, ensuring that our partnerships with various retail media merchants respect their ownership and operation of the media. We provide the technology and physical infrastructure, aligning our strategy with their business model for venue operations. 

This approach differs from digital out-of-home advertising, where the focus is on investing in signage and seeking foot traffic. Instead, we follow the lead of retail media owners, ensuring our financial models, operational methods, approval processes, and creative control align with their rules of engagement.

As part of Vibenomics, I focus on ad tech and advertising within Mood Media. I leverage my experience working with numerous retail media networks to understand the diverse approaches to building retail media spaces. I bring insights from our current brand partnerships to refine our playbook and advance the industry.

AB: How does the playbook envision using disruptive in-store technology to enhance the shopping experience?

PB: Over the past five years, I’ve observed the evolution of retail media from within the stores, especially on the periphery of the retail media landscape. This shift has seen omnichannel strategies integrate on-site and off-site elements as retail media companies have the freedom to design webpages and leverage data and shopper insights as they see fit. Shopper behavior has predominantly been a digital experience, whether through apps or online interactions. Now, there’s a need to merge this digital experience with the physical world, considering new approaches to privacy and delivering what consumers truly need for better preparation.

The challenge lies in transforming traditional, static signage—like cardboard stands and paper shelf tags—into more cohesive and engaging elements that offer consumers a seamless digital-to-physical experience. Instead of simply navigating around static signs, consumers should encounter dynamic, noticeable, helpful promotions that drive their behavior and enhance their in-store discovery and exploration process.

AB: What roles do retail media, shopper marketing, and category teams play in the context of merchandising within the retail sector?

PB: Retail merchandising professionals must now incorporate insights from Retail Media Networks. This shift means traditional trade deals and merchandising strategies, like shelf placement and promotional value, can no longer be considered in isolation. 

Instead, retail media, shopper marketing, and category planning merge into a single, integrated conversation. Brands increasingly need to allocate more of their budgets to retail media, drawing funds from traditional merchandising investments. This necessitates closer collaboration between teams, a focus we specialize in. 

To create a cohesive strategy, we aim to bridge the gap between traditional merchandising and retail media by controlling the environment, creative aspects, context, and store mobility.

AB: What types of data are emphasized for advanced targeting in the playbook, and how can they be used to understand shopper behavior?

PB: The current playbook focuses on execution, providing insights for brands, retailers, and service providers leveraging retailer data and in-store technologies for maximum shopper benefit. The initial version mainly covered retail media standards with a brief in-store section, reflecting the evolving nature of in-store experiences. 

This playbook now addresses utilizing retailer data and technologies to enhance the shopper experience. It differentiates between online (one-to-one audience) and in-store (one-to-many audience) advertising, highlighting the challenges of demographic variability in stores. 

By analyzing shopper transaction data, retailers can adjust in-store strategies to improve spending and category share, integrating first-party data into the broader shopping experience. For instance, mature retailers can evaluate how creative impacts spending per trip, household, and category share across both digital and in-store environments, aiming to translate online insights into in-store successes.

AB: What methods does the playbook suggest for measuring the success of digital out-of-home and in-store retail media campaigns?

PB: There are two approaches to consider. One is a straightforward control test, which is easier to execute. For instance, we could test a campaign with a major home improvement customer by isolating a test group from a larger control group. We would then analyze pre- and post-campaign effects on shopping behavior using statistically relevant data.

The second approach, announced with Microsoft last year, involves taking a brand’s media plan and extending the control test to in-store activities. This includes examining product listing ads, search strategies, and in-store tactics. We then determine which tactic or combination of tactics drives greater lift or increase.

In essence, we perform both isolated and combined tactic tests. By comparing in-store tactics alone with combined on-site and in-store tactics, we can assess their impact on category share and lift. This dual approach has provided valuable insights into optimizing the integration of online and in-store shopper data.

The post In-Store Retail Media Strategies Reimagined with Paul Brenner From Vibenomics appeared first on AdMonsters.

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

Share your insight in our 5-minute survey.

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

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

The post AdMonsters Publisher Pulse Survey: Unlock the Keys to Ramp Up Your Revenue Strategies 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.

Reaching the right audience at the right moment is critical to business success. However, if the company’s budget is limited, this is not easy. Modern technologies, such as programmatic buying, may come to the rescue, allowing small and medium enterprises to advertise cost-efficiently and reach their marketing goals faster.

Why Programmatic (and What’s That, Really)?

Traditional advertising was mainly manual: it required finding a website where you’d like to place your banners and communicating with its owners. It was a time-consuming and suboptimal solution, plus often, it was expensive. Today, there’s a modern alternative called programmatic advertising. The word “programmatic” refers to how it operates: instead of people, the algorithms buy and sell ad space.

But it’s not just automation that makes programmatic so enticing – it’s also relevance. This technology can ensure your ads will be seen by the right audience in the right context. For instance, you’ve seen programmatic ads when shopping on Amazon. This company shows customized ads to visitors based on their purchasing and browsing history. 

Programmatic advertising revolutionizes the industry, making it easier for global companies and small and medium businesses to access large target groups.

Let’s look at some data to prove this point. According to Statista, in 2023, global spending on programmatic advertising reached $558 billion. By 2026, this number will likely grow to $700 billion. Also, the share of programmatic advertising in digital spending worldwide has increased since 2020. In 2020, it constituted 77.04%, in 2023 – 81.06%, and in 2029, it’s projected to reach 84.92%.

In 2021, 45% of small business respondents in the USA said they paid for digital advertising. They spent $534 monthly on average, and 93% of small companies planned to increase this amount.

So, programmatic advertising is undoubtedly the future. And it’s worth delving deeper into the subject. 

A Closer Look at Programmatic Advertising and Its Benefits 

Basically, the programmatic advertising process looks like this:

• A company creates an ad campaign, describes the audience (demographics, location, etc.), and decides on a budget.
• The ad is downloaded to the programmatic exchange via a dedicated platform. The exchange conducts auctions for ad space: who’s willing to pay more for showing their ad wins.
• A user visits a website participating in the exchange and sees the winning ad. 

Companies can use various types of programmatic ads, such as video ads, audio ads, and out-of-home (OOH) ads on billboards and displays. Today, video format is the most popular option, although OOH usage is growing in retail and other industries.

Every business, regardless of size, can experience the advantages of programmatic buying. But what are the benefits, exactly?

1. Cost-Effectiveness – Programmatic buying allows SMEs to control their budget and spend exactly as much as they are ready. Moreover, you can always be sure your ad will reach the right audience, so your money won’t go to waste. Companies often spend a significant share of their marketing budgets on traditional ads, like in magazines or on TV. Sure, many people will see this campaign, but how many belong to your target audience? With programmatic buying, every time your ad is displayed, counts.

According to Google News Initiative, direct ads cost two to four times more than programmatic ads. The numbers are $10-20 per thousand impressions for direct ads and $1-5 for programmatic ads.

For example, capturing the right audience’s attention was challenging for the Canadian clinic Whistler Medical Aesthetics. They tried traditional advertising channels like radio and magazine ads but weren’t satisfied with the cost-efficiency ratio. The company wanted to attract new customers, but the conversion rates were low. 

Eventually, with the help of consultants, they changed the strategy and focused on several types of programmatic ads. After the first month, traffic to their website grew by 60%. The clinic spent 50% less but got 25% more in return.

2. Advanced Targeting – Programmatic buying helps small and medium businesses identify and reach the right target groups, which is challenging with traditional advertising. The secret behind it is the approach’s core: focus on the audience, not the website. After all, for a company, it doesn’t really matter where the potential customer sees its ad. What matters more is what happens next. The programmatic approach suggests delegating the choice of websites to algorithms. 

So, to run an efficient campaign, a company needs to target the audience appropriately. It can choose among multiple targeting options and combine several in one campaign. The most popular criteria are demographics, interests, and online behavior. The better you describe the audience, the higher the engagement and conversion rates.

For example, a non-profit organization, The Amanda Foundation, wanted to speed up the process of adopting homeless cats and dogs. They decided to try programmatic advertising to reach people interested in hosting pets. Advanced targeting helped the organization identify the right audience and create a profile for potential pet owners. For instance, young people prefer more active dogs, while older people would likely adopt a calmer animal. The campaign’s results exceeded expectations: all the pets found new homes.

3. Real-Time Optimization – Programmatic campaigns are more flexible than traditional advertising. Moreover, the ad’s performance is measured in real-time, and the campaign can be adjusted on the go to get better results. Data on total views, conversions, impressions, etc., is recorded all the time while the campaign is running.

Here are the mechanisms enabling real-time optimization:

• Bid adjustments allow changing the frequency of ad showings depending on the device, location, time of day, etc. There’s also an option to adjust bids based on performance metrics. This helps a company maximize its return on investment in advertising.
• Ad placement optimization. Programmatic buying allows placing ads in the best possible location on the web pages and changing it if performance metrics aren’t good enough.
• Audience retargeting. Programmatic advertising aims to increase conversion rates. Hence, it can reach people who have already interacted with a company. It helps to engage non-customers and offer something new to existing clients.

4. Flexible budgeting – Programmatic advertising allows companies to set a spending limit, and they can decide whether it will be per day or for the whole campaign. Small and medium businesses often can’t afford pricey advertising, so it’s crucial to keep the budget under control. Luckily, programmatic buying helps prevent overspending.

As you can see, the benefits of programmatic advertising are convincing. Now, let’s determine how to achieve the best results using this technology.

Better Targeting for Better Outcomes

Programmatic buying isn’t a magic wand. Companies still need to do their homework to make it work, i.e., get to know their customers. With demographics, it’s not hard; you just need to analyze the data you already have. But if you aim for advanced targeting, you’ll have to discover more: what are your customers’ interests? What do they do in their spare time? What do they value the most? Consider conducting an online survey or interviewing your customers to collect this data.

The more you know about your audience, the more targeting options you can use. Among them:

• Behavioral Targeting – This option focuses on customers’ online activity, such as visited websites, cart abandonments, purchases, etc. A simple example is ads with a particular product you start seeing after visiting an online store and looking at similar products. If implemented correctly, behavioral targeting helps companies increase sales and conversion rates. For example, the children’s clothes brand Sunuva couldn’t afford a big sales team but needed a sales boost. Behavioral targeting was the answer: the company focused on cart abandonments and offered visitors relevant product recommendations. It helped increase turnover by 8.9% since the first day.

• Contextual Targeting – This option allows ads with relevant content to be placed on websites. For example, watching an interview with a famous athlete on YouTube and seeing the ad for a brand-new sneakers model results from contextual targeting. Marketers discovered that such advertising increases conversion (and irritates the audience less). Some more examples are knife ads on the website with recipes and sports equipment ads next to the article about the exercise routine.

• Geotargeting –  is a location-based option. Simply put, you reach customers in a certain geographical location and show them your ad. For instance, a restaurant may target people within a 3-block radius. Another popular tactic is to target customers in locations (country, state, city, ZIP code, etc.) that have already shown high conversions. For example, the cider maker Marners launched a campaign in four UK cities to sell tickets to its sponsored events. The company chose the locations where, according to the data, people were the most likely to buy tickets spontaneously. The campaign was a huge success: not only were all the tickets sold, but people also ended up on a waiting list.

For small and medium companies, a wise ad placement strategy requires considering relevance, time, and exposure. This is when targeting options come into play. Any business can choose one of them or combine a few to ensure the best possible result.

Managing Campaigns with Programmatic Platforms

Modern programmatic platforms offer small and medium companies practical solutions to manage their ad creatives effectively. For instance, businesses can:

• Customize Their Digital Ads – If a company has done its homework, it knows much about target groups. So, it can customize ads for different customer segments and channels. After all, the “one fits all” approach rarely works; you often need more than one creative option.

• Conduct A/B Testing – A company can test two or more different ad creative options and compare the results. For example, a clothing store can experiment with different images and offers, monitor their performance and draw conclusions. This helps make more informed decisions, reach the right audience with the right message, and, eventually, save money.An impressive example here is Lacoste. A designer brand decided to boost its summer sales in France, the UK, and Germany and turned to programmatic advertising. First, they conducted audience analysis and defined customer profiles. Then, they harnessed the power of A/B testing: they ran various versions of creatives, adjusted them, and tested new ads. The process continued until the company reached the best results. The campaign resulted in 19,749,380 impressions and 2,290 new sales.Sure, small and medium companies’ budgets are much more humble than Lacoste’s, but they still can analyze data and experiment with A/B testing.

• Use Dynamic Creative Optimization –  Since the programmatic approach includes permanent performance tracking and users’ behavior, it allows companies to adjust creatives, such as images and messages, in real time to ensure their ads are as relevant as possible for viewers. How does it work? A company must create a flexible template with elements that may change, such as calls to action (CTAs), images, etc. Then, track the metrics of each option, if necessary, eliminate inefficient versions, and add new ones.

Creatives play a vital role in engaging customers and increasing conversions. So, one of the company’s primary tasks is to ensure they deliver the message to the right audience in the best possible way. 

Customer segmentation is essential to achieving outstanding results. Dynamic creative optimization will be the most efficient if you’ve identified critical segments of potential clients. You can divide them by demographics, interests, or online behavior. Later, it will help you connect to each segment with the most relevant version of the ad. 

Last but not least, programmatic platforms measure ad performance and create sophisticated reports that companies can use to improve their decisions. The typical set of metrics includes clicks, impressions, conversions, and return on ad spend (ROAS). This data is enough to evaluate the campaign results and compare your expectations with reality.

Today, programmatic buying is changing the market rules. With its cost efficiency, budget allocation flexibility, advanced targeting, and real-time optimization features, small and medium businesses can achieve the success they could only dream about, reach a wide new audience, and learn much more about existing clients. So, why not try it as part of your marketing strategy?

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Is Google Search broken? Definitely not, and that’s the wrong question to ask.

Two weeks ago, a beleaguered product review site, HouseFresh, dropped an update about their battle, and frustration with Google Search and the state of SEO competition overall. Similarly, SEO experts like Lily Ray and Glenn Gabe have been documenting the rollercoaster of the latest algorithm updates that have walloped publishers across the board.

We are all used to competition and tough days, but it is impossible to prepare for the agony of a foundational shift. The speed of change is accelerating, so it may be helpful to climb a bit higher on the mountain and gain some perspective. Here are my takeaways:

1. Don’t hate the player, hate the game 
2. Unless the player is Google (They’re playing a different game) 
3. Play a different game

And that’s the hardest part. Everything that publishers have held holy about traffic is suddenly upside down. The traffic walls are closing in, and few exit routes are available.

Don’t Hate the Player, Hate the Game

For most of us, the rules of the traffic game are set by the search and social platform giants. We spent countless hours obsessing over the Facebook and Google Search “guidelines” to find exploitable advantages. When the preferences of these benefactors shifted whimsically, publishers were quick to adapt, pivot, or die.

Publishers learned early that building empires on borrowed traffic was risky, but compared to social media’s turbulence, Google felt like a predictable bedfellow. Conquering search was hard but meaningful. It was an artful dance of scaling quality content, or at least being of enough quality to win a coveted first position on a search results page. It was one of the few areas in digital publishing where your “library” held a residual value.

We live in a relatively free capitalistic society, and as such, anyone is allowed to enter the ring and play the game. Kudos to my publisher comrades for finding that angle, that wedge, that thing that made your scale possible. Perhaps we were jealous of those gains, but we were never mad at you for doing them.

As Brian Morrissey so eloquently put it, everything in media is a “racket.”  The pursuit of traffic is a hustle, and the monetization of that traffic is a racket. It’s survival of the fittest, but fitness is subjective to the rules of the game.

Desperate for success and strong on the scent of promised pageviews, publishers doubled down on perilous traffic games. Some flourished in influencer videos, native articles, social games, or long-tail SEO. Some ended in a bang, but many are bleeding out from a thousand paper cuts. Yet, scores of publishers find a way to carry on.

This publisher resiliency, however, comes at the price of polluting our resources. The distribution platforms (search, social, reader apps) are curators of content, responsible for delivering its customers an experience far from the garbage of the web. But we can’t have nice things, and we tilted these platforms beyond their intended capabilities. So did we break Google Search? Not really, but kinda.

The Pandemic broke Google Search. The recent SEO content explosion and resulting chaos were a perfect storm that Google wasn’t ready for. The surge in online shopping meant the world needed a gazillion more “best of” articles, and every gadget needed a review. Simultaneously, scaled SEO tools were being democratized, enabling just about anyone to find the right topics and keywords for expansion or attacking competitors. Throw in some zero-interest financing, AI-powered content generation, SEO-threadbois and a social-traffic squeeze, and you get an unmitigated overgrowth of…crap.

Google Is Playing a Different Game

The Tsunami of Crap, however, is part of a much larger weather pattern known as “the Enshittification.” By that logic, Google’s prerogative to dominate the ads business may summon its demise. The internet’s recent pivot to SEO ushered in hundreds of high-powered competitors of varying quality to the SERP battles. Content volume was metastasizing at unfathomable rates, and it was harming the utility of Google’s search results. Searchers resorted to manually adding “in Reddit” to queries or leaving Google entirely and using non-Google AI chatbots. I don’t think Google panics very often, but I’m pretty sure someone said, “I think we have a problem.”

In typical fashion, the Google Search team rolled out a steady barrage of ranking algorithm updates. They prioritized Reddit and Quora posts and other pre-filtered sources like Instagram and Twitter. Google launched Search Generative Experience(SGE) to stem the tide and flex some anti-competitive muscles. In their latest rounds of updates, Google handed out the dreaded manual action to publishers, a certain death knell for most.

Unphased, Google marches forward, as if this were all part of the plan. Amidst the chaos, the revenue teams were busy carving up the SERP page. Ads, SGE, and more ads.

Google is playing a fundamentally different game than everyone else in Search. Without a doubt, Google’s top prize is its “Google Ads” products. They are optimizing for their outcomes, which explicitly do not include sending traffic to publishers.

If you think that Google is optimizing for making revenue on your GAM account, think again. In 2023, Google pulled in 56.9% of its ad revenue ($175 BILLION) from “Google Search & Other,” and only 10.2% of revenue ($31 billion) from the Network.

They gained $12.6 billion in Search revenue YoY, and only lost $1.5 billion in the Google Network. Google footnotes that the “The overall growth [in Search & other revenue] was driven by interrelated factors including increases in search queries resulting from growth in user adoption and usage on mobile devices; growth in advertiser spending; and improvements we have made in ad formats and delivery.” (emphasis mine)

Got that last part? You’re not going crazy. Total search queries are up, traffic to publishers is down, and Search revenue is up. Google is here for the ads, their own ads.

Google Ad’s job is to sell products and take credit for it. Google will fight relentlessly to disintermediate anything that stands between a user and the product Google is promoting on behalf of a paying client. Generative AI searches will do this very well, as the service will synthesize myriad sources (including Reddit) to return a sourceless result and a well-placed carousel of ads. Raptive posits that SGE will cost creators  $2B in revenue,  and others predict traffic losses of 10%-25% and higher by 2026. 

In a recent interview on Bloomberg Originals, Google CEO Sundar Pichai discusses the shift in search and answers if Google Search is broken. Spoiler alert: he doesn’t think it’s broken but he does acknowledge that the AI boom created a glut of content and it’s Google’s responsibility to provide users with a quality experience.

Play a Different Game

It’s not about digital web publishers. Consumers are Google’s customers, and advertisers are their clients – everyone else is just expendable. HouseFresh is right about many things, especially that “Google doesn’t owe HouseFresh traffic.” Despite all that publishers, content creators and the general public have given to Google (ahem, structured data), Google doesn’t owe any of us anything.

A media company’s mission is to create and monetize their intellectual property. Under that lens, there is so much possibility, but it all starts with good IP and a plan. Endurance comes from adaptability. And that’s the hardest part.

It’s not easy to just uproot your business and find a new game to play, let alone be successful at it. Not everyone can be a direct traffic destination, and not everyone has the momentum to upstart a newsletter business. Sure, there are successful media companies that found a different game at their inception, but it’s unreasonable to expect that everyone can find a new niche.

I am truly empathetic for brands that will not survive, and I know that journalism, fair democracy, and so much more are at stake here. The internet is forever, but how it works will always change. But humans crave information and diversion, and thus media will endure.

As creators, we must always look forward and anticipate change. Make unforeseen pivots a planned part of the business plan. We must make investments based on their future return value, not based on justifying the sunk costs of our past. Let it go.

It’s time to take a long look out on the horizon and start to chart your new course. It’s out there for us, but we must work hard to find it. Godspeed to all.

The post Surviving the SEO Shake-Up: Publishers vs. Google’s New Game appeared first on AdMonsters.