Attention metrics are gaining traction, but one fundamental aspect that continues to hold significant value for advertisers is viewability. While advertisers recognize the importance of capturing users’ attention, ensuring their ads are viewable remains a top priority.

Viewability refers to the measurement of whether users see an ad. In the past, publishers could generate revenue solely by placing ads on their websites, irrespective of whether those ads received any views. However, the landscape has transformed dramatically, and advertisers now emphasize viewable impressions. Publishers need to comprehend how the costs of impressions are measured to monetize their digital ad inventory effectively.

To be considered viewable, an ad must meet specific criteria. According to industry standards, an ad is viewable if at least 50% of its pixels are visible on the user’s screen for at least one second. 

But how do you measure viewability correctly? 

vCPM: The Cost of a Thousand Viewable Impressions

Calculating the value of viewable impressions is where vCPM (viewable cost per mille) comes into play. vCPM represents the cost of a thousand viewable impressions, indicating the number of people who see the ads on a web page. It provides advertisers with a clear understanding of the value they are getting from their advertising investments.

While CPM measures the cost per thousand impressions, regardless of their viewability, vCPM focuses solely on viewable impressions. By leveraging vCPM, advertisers can make informed decisions and allocate their budgets more effectively, optimizing their ROI.

To bid on vCPM, advertisers must be aware of the ad’s visibility percentage and the count of viewable impressions, as these factors determine the resulting vCPM. The total vCPM is determined after deducting any portion of the ad that remains outside the screen, rendering it invisible to viewers.

Attention Vs. Viewability

As the industry ushers in the cookieless era, publishers and advertisers also preach the importance of attention metrics. While creating viewability for your ad is essential, some argue it’s losing relevance because it “simply represents a measure of an opportunity for an ad to be seen – not whether a viewer actually saw an ad.” 

Attention metrics grew in prominence because of the lessening popularity of identifiers and the increased difficulty of gaining consumer attention because of the oversaturation of ads online. Brands measure attention metrics through viewability, creative size, interaction, ad position, time of day, publisher or program, audibility, page clutter, device frequency, and eye tracking. Viewability metrics are still vital to understanding attention metrics, so brands need robust measurement tools for viewability. 

The Publisher Benefit

Enhancing viewability and vCPM is a crucial objective for publishers aiming to maximize ad revenue. Several strategies can help improve viewability metrics: 

• Ad Placement Optimization: Placing ads in strategic positions on a web page, such as above the fold or within the user’s natural line of sight, increases the likelihood of viewability.
• Responsive Design: Implementing responsive website design ensures that ads adapt to various screen sizes and resolutions, allowing for a seamless user experience across devices.
• Ad Formats and Sizes: Choosing ad formats and sizes that align with the website’s layout and content enhances visibility and engagement, driving higher viewability rates.
• Page Load Speed: Optimizing page load times reduces user abandonment and increases the chances of ads being viewed before users navigate away from the site.
• Ad Fraud Prevention: Implementing robust ad fraud detection and prevention measures safeguards viewability by eliminating fraudulent or non-human traffic that artificially inflates impressions.

By implementing these strategies, publishers can elevate their viewability metrics, positively impacting vCPM and attracting higher-quality advertisers to prioritize viewable impressions.

Understanding the concept of viewability, measuring it through vCPM, and implementing strategies to enhance viewability benefit publishers in terms of increased ad revenue and ensure advertisers receive the value they seek from their digital advertising investments. As the industry continues to evolve, keeping a keen eye on viewability will be instrumental in driving success for both publishers and advertisers in the digital advertising ecosystem.

The post What is vCPM and How Does It Relate to Viewability? appeared first on AdMonsters.

Of the six states, one stands out: Oregon. On June 22, 2023, the Oregon state legislature passed Oregon Consumer Privacy Act (OCPA) (SB 619). It is the eleventh state in the US to do so and the sixth this year. The Oregon Consumer Privacy Act (OCPA) is notable because it’s the strongest bill passed to date.

With the exception of California, all other US privacy regulations are modeled on the Washington Privacy Act, which was drafted by the Washington State Senate Ways & Means Committee. This bill is limited to companies (data controllers to be exact) that “control or process personal data of 100,000 consumers or more; or derive over 50 percent of gross revenue from the sale of personal data; and processes or controls personal data of twenty-five thousand consumers or more.” For many people, the WPA lacks teeth.

Unique to OCPA

OCPA differs from most other State privacy laws in a few ways. First, it requires opt-in consent for Oregonians aged 13 to 15. 

If signed by the Governor, the law would protect sensitive data that goes above and beyond other privacy laws. First, it requires all data controllers to obtain consent before collecting sensitive data. And it expands the definition of sensitive data to cover such things as national origin, status as transgender or nonbinary, and whether or not the consumer has been the victim of crime. 

Additionally, it would broaden the definition of biometric data to include any data used to identify a resident, not just data collected or used for identification. In other words, scraping social media platforms for consumer photos will be illegal in Oregon if this bill passes.

Civil Penalties on Employees for Violations

The Act gives data controls new incentives to respect the consumer’s privacy, including holding employees personally accountable for any violations. It specifically states,”If a court finds that a director, member, officer, employee or agent of a controller violated sections 1 to 10 of this 2023 Act through an act or omission, the court may find that the controller committed the violation or the court may find that both the controller and the director, member, officer, employee or agent committed the violation and may impose separate civil penalties on each.”

“What I consider the most significant part of the Act is the potential for officers, directors, and employees to be personally liable for violations.  I have not seen a provision like this in any other privacy law,” said Wayne Matus, Co-Founder, General Counsel & EVP at SafeGuard Privacy, a privacy compliance platform.

Data Minimization a New Wrinkle for ID Matching?

OCPA’s data minimization requirements could be challenging for some marketers. For example, those who want to use customer emails to match their IDs to reach them on their CTV devices. The law says that businesses may not process personal data for purposes that are not reasonably necessary unless they obtain consumer consent.

At issue: OCPA explicitly defines personal data to include derived data and device data that can link one or more consumers in a household. In other words, the law recognizes that personal data goes beyond direct or explicit information and includes data derived from other sources or devices that can be connected to individuals or their households. 

While the law doesn’t mention universal ID matching specifically, it requires all companies to obtain opt-in consent from consumers before collecting or selling their personal information, including data that could potentially link their mobile device to a household CTV.

“The data minimization is huge.  It is one of the biggest issues the trade groups have against the draft federal privacy law.  It has the potential to minimize not only data but the value of data. And it hurts creating a profile,” said Matus.

Finally, the bill establishes minimal transparency requirements. For example, if requested, businesses must provide consumers with a list of third parties with whom they’ve shared their personal data. And that’s not all, they must also explain the categories of companies that those third parties fall into so that the consumer can understand the types of entities involved and how they process their data.

The post Oregon Sets the Bar: Landmark Consumer Data Privacy Bill Becomes the Strongest in the Nation appeared first on AdMonsters.

But publishers are not without controls to keep the bottom at bay — flooring, the process of setting a minimum price for ad inventory, empowers publishers to keep inventory pricing competitive with other channels (e.g., direct sales).

Flooring is a simple concept: a publisher sets the minimum CPM they are willing to accept for an ad placement, and an advertiser must pay this amount or higher to display the ad. Publishers using Google Ad Manager (GAM) set their CPM floors for the open exchange using Unified Pricing Rules (UPRs), ensuring that any bids accepted from their programmatic demand partners meet their minimum pricing requirements.

This is where the simplicity ends and the anxiety begins. Set your floors too low, and you miss out on revenue from advertisers who are willing to pay more. Set them too high, and you miss out on fill.

Continuously establishing the right CPM floors to earn the highest revenue for your ad inventory without sacrificing fill rate is simply impossible to do manually. But it is possible to automate through dynamic flooring.

A Floor-Shifting Odyssey

The holy grail of yield management is that sweet spot that maximizes both CPMs and fill rate — but this sweet spot is a constant-moving target. CPM variations occur based on content, traffic source, seasonal spending trends, macroeconomic factors, user data, tech variables like device type, browser, operating system, and every combination of these CPM “ingredients.”

Some publishers dedicate hours, full days, and even team members to analyzing CPM data and updating UPRs. They spend a lot of time and effort on a process that results in low and untraceable success. Other publishers prefer to “set and forget” their UPRs. They may not be sacrificing time and mental sweat equity to maximize yield, but they are leaving money on the table by not passing optimal floors.

Even if you could manually set floors effectively, GAM limits the number of UPRs you can create. To achieve optimal CPMs, you’d want to pass custom floors at a granular level. Each page on your site earns differently, so you want a unique floor for every URL and all the other CPM variables.

Dynamic Flooring to the Rescue

Dynamic flooring is a way to intelligently and proactively adjust your floors based on real-time data from every pageview. With each impression, a dynamic flooring solution learns and improves its ability to create the right floor at the right time. It will automatically generate a real-time floor based on a smart prediction of the value of the current pageview.

Several variations of dynamic flooring have appeared over the years, and they are not all created equal. Many publishers have even grown wary of the term dynamic flooring as providers have not optimized revenue but instead, shuffled it among partners. This favors one or more demand partners to others’ detriment and fails to drive incremental revenue.

Ultimately, dynamic flooring is not about getting your UPRs right. The way to achieve the ideal flooring system is to control the win rate of your SSPs. Doing this will create pricing pressure on your whole revenue stack.

An ideal flooring system should:

• Set an infinite number of granular floors based on page content, user data, traffic source, technical specs, and other variables;
• Continually adjust floors based on the latest data (this might mean that floors are adjusted every few minutes);
• Pass the optimal CPM floor for every ad placement on every pageview; and
• Automate your flooring optimization.

When you implement smart publishing tech that accesses the latest, granular data from every pageview, it’s like having 50,000+ UPRs simultaneously working for you and automatically updating in real-time.

Finding the Right Solution

Dynamic flooring solutions are springing up faster than identity partners. Look under the hood, before you sign the vendor with the lowest price and biggest promises, Ask them these questions:

• How does your technology create optimal floors for every pageview?
• How recent is the data you’re using to set floors?
• How can you prove that your solution makes me more money and isn’t just shuffling my revenue?

If they can’t show their work, work with someone who can!

Dynamic flooring is one of the best tools to earn more from the open exchange, which is especially important when strange economic circumstances stymie the flow of direct-sold campaigns. However, picking the right solution requires more than a price-tag check—be sure you’re prepared to tell the difference between revenue shuffling and true dynamic flooring.

The post What Is Dynamic Flooring? appeared first on AdMonsters.

Data privacy regulations like Europe’s GDPR, California’s CCPA, and now the amended CPRA disrupted businesses as they grappled with the challenge of ensuring compliance. 

To better help the industry comply with the notice and choice obligations required under said new laws, IAB Tech Lab collaborates with industry stakeholders and local trade bodies to support the development of frameworks like IAB Europe’s Transparency and Consent Framework (TCF) and the IAB’s US Privacy Framework. 

However, building distinct technology solutions for every jurisdiction was not sustainable. In September 2022, the IAB Tech Lab first launched the Global Privacy Platform (GPP) and recently closed public comment for the next version of the API.

Understanding the Global Privacy Platform (GPP)

As an industry, we must ensure that we provide the appropriate transparency and choice as required by law. More importantly, we need to consistently communicate user consent and choice preferences, ensuring that all parties can comprehend them properly.

 By doing so, we can handle users’ data in a manner that aligns with their preferences. GPP aims to solve the challenge of creating a common language for everyone in the ecosystem. This solution was developed over several years involving stakeholders from across the ecosystem, including publishers, advertisers, and ad tech vendors.

The key components of the GPP that should be understood are the privacy string and the available string transport mechanisms. These mechanisms include a field in the Regs object in openRTB, parameters and macros for URL-based services, and a standard API. It is the API portion of the GPP that the IAB Tech Lab is updating, but more on that later.

The GPP string can carry privacy signals for any supported jurisdiction. It currently supports privacy signals for Europe’s GDPR, Canada, and five states in the US that have privacy laws (California, Virginia, Utah, Colorado, and Connecticut). Notably, the GPP is extensible and goes beyond just supporting jurisdiction and also allows support for other industry signals, such as the Global Privacy Control (GPC).

Exploring GPP API v1.1

Delving into the specifics of the update, it’s important to understand what remains unchanged. The GPP string, a core component of the protocol, will stay as is. There are also no updates to how the GPP string is passed in openRTB and using the defined macros and parameters. Let’s dig into the changes in the GPP API.

The primary changes to the API were born from industry feedback that it needed to better support callers of the API who operate within an iframe on a web page. Version 1.1 of the API includes callback support for all commands. This allows vendors who work within an iframe to use all the available commands that the API supports rather than just a subset.

In addition to adding callback support, version 1.1 of the API includes updates to status codes. While this may sound insignificant, on the surface, it is vital for callers of the API. There are additional explanations for several of the existing status codes. Still, the most important of the updates is the addition of a new event called signalStatus with potential values of “ready” or “not ready.” This new event adds a lot of clarity to when a GPP string, the representation of the user’s consent and choice preferences, is ready to be used. This will reduce the potential for confusion or misrepresentation.

 To reduce the number of calls needed to extract the appropriate information, version 1.1 of the API includes several optimizations to the objects returned by the API. These optimizations also help with reducing the complexity of vendor scripts.

Details are available here for those looking to dive deeper into the specifics of the updates included in version 1.1.

Implications of the Update on GPP Implementers

All stakeholders, including publishers, advertisers, and consent management platforms (CMPs), along with any vendors utilizing the API for GPP string retrieval, are urged to support the new version of the API which was finalized earlier this month. The enhancements are designed to better infer the privacy signals and enrich interactions with the API. For those vendors that aren’t interacting with the API and instead rely on fetching GPP strings via openRTB or URL macros, there’s no need for any changes. You are unaffected by this update.

As privacy regulation continues to evolve, so will the Global Privacy Platform. The GPP is ready to adapt and evolve to meet the needs of a global privacy landscape that shows no signs of standing still.

The post What Is the Global Privacy Platform (GPP) API v1.1? appeared first on AdMonsters.

Transparency in the programmatic supply chain is one such challenge prevailing in the industry. With so many parties involved in the supply chain, it has become even more difficult to keep track of ad spend and quality. That is why the industry needs Supply Path Optimization (SPO). 

Supply Chain Optimization is a process of increasing transparency and efficiency in the programmatic supply chain by cutting down the number of intermediaries that are not adding significant value. 

Why Is Transparency Needed?

Transparency in the supply chain involves a lot more than just making information available to all parties. It involves creating an environment of trust where all stakeholders feel confident that they are receiving fair and honest information.

This includes details about ad placements, ad inventory, and pricing. Ensuring transparency is important because it promotes better communication and helps build strong working relationships between publishers and advertisers.

Benefits of SPO

It is often perceived that SPO only benefits advertisers, but that is simply not true. Both the supply side and demand side can greatly benefit by optimizing supply path efficiencies:

• • Increased Transparency: SPO provides better visibility and insights about the ecosystem — the intermediaries involved, exact ad spend on impressions, etc. It enables advertisers to tackle the issue of bid duplication and enables publishers as well as advertisers to identify and eliminate unnecessary or fraudulent players. 
• • Brand Safety for Advertisers: With SPO, advertisers feel more confident about their brand image and safety. They can eliminate the SSPs who do not follow their brand safety guidelines. 
• • Increased Revenue Opportunities: Streamlining SPO can ensure that publishers receive the highest bids possible for their ad inventory ultimately increasing ad revenue.
• • Reduced ad fraud: SPO can help publishers reduce ad fraud by ensuring that their ads are only displayed on legitimate websites.
• • Increased Efficiency: SPO can help publishers and advertisers improve the efficiency of their programmatic advertising inventory and ad campaigns by reducing latency and improving transparency.

How does SPO work?

To make sure that SPO works in the most optimum way, advertisers need to come up with certain strategies to apply. One of the ways advertisers could reclaim control and optimize the path is by limiting the number of SSPs and ad exchanges they work with and work with a select number of partners. They would also need to focus on cutting off resellers from the market and opt for bids that offer them the best chance of winning. It is always important to make sure that every bid must bring a unique value attached to it in an auction-themed environment.

Implementation

One of the best ways to implement SPO is to make sure that multiple routes are being avoided to buy or sell inventory. The lesser the paths, the less the chances of duplication.

According to recent studies more than 60% of buyers currently think that SPO has reduced the chances of fraud while the buying power has also been enhanced for at least 30% of the buyers in the landscape, along with this roughly 20% of them have seen a more transparent Fee structure due to the same.

SPO Implementation steps include:

• Assessment:

Developing a thorough grasp of your programmatic supply chain is the first step in deploying SPO. This includes the process of figuring out all the intermediaries who are buying and selling your ad inventory. 

• Evaluating and consolidating intermediaries: 

Once all the intermediaries have been identified, evaluate the ones which are unnecessary or ‘bad actors’, the ones adding costs and latency to the page load time.

Based on the evaluation, consolidate the significant ones and eliminate the ones not adding value to the supply chain. 

• Monitoring the results: 

SPO is an ongoing process and it needs to be measured regularly. This will help in analyzing the efforts if the goals are being achieved or not. Based on the analysis, those efforts can be streamlined and optimized. 

This can be a complex process at times and can be achieved by having the right resources in place. Also, working with an SSP or DSP partner can be considered to simplify the process. 

What Are the Best Practices for Buyers and Sellers to Facilitate Supply Path Optimization

There are several best practices for buyers and sellers to facilitate supply path optimization. These include the use of ads.txt, sellers.json, a lesser number of SSPs, and adherence to industry standards including brand safety and relevance. 

Ads.txt and sellers.json are text files that are placed on a publisher’s website, which allows buyers to verify the identity of the seller and ensure that they are buying ad inventory from authorized sources. Reducing the number of SSPs can help optimize the supply path by reducing the complexity of the supply chain, which can lead to better efficiency and transparency.

Uses of AI for SPO

The use of AI for SPO is becoming increasingly common in the ad tech industry. AI algorithms can help automate the process of analyzing data, identifying inefficiencies, and optimizing the supply path. This can help buyers and sellers make better decisions, reduce costs, and improve efficiency.

With the growing changes in the current landscape, it is expected that AI tools will also be able to help in the execution of policies to optimize the supply path and can also aid inventory management issues.

Measurement and Enhancement of SPO Efforts

Measurement and enhancement of SPO efforts are essential for ensuring that the supply chain remains transparent and efficient. Regular monitoring and analysis of data can help identify areas for improvement and enable stakeholders to make data-driven decisions. 

By enhancing SPO efforts, buyers and sellers can optimize their supply chain, reduce costs, and improve their ROI.

Recent Industry Developments

Recent industry developments, such as the implementation of the OpenRTB 2.6 draft, Ads.txt 1.1, and Transparency Center, have further advanced the cause of supply chain transparency and optimization. 

The OpenRTB 2.6 draft includes new features that make it easier to detect and prevent fraud. Ads.txt 1.1 includes a new field that allows publishers to specify their direct relationships with advertisers, making it easier for buyers to identify authorized sellers. The Transparency Center provides a centralized location for buyers to view information about ad inventory and verify the identity of sellers.

Next Steps for Buyers and Sellers

Supply chain transparency and optimization are essential for the ad tech industry to thrive. Buyers and sellers must work together to create a transparent and efficient supply chain that benefits all stakeholders. By following best practices, utilizing AI, and embracing recent industry developments, the ad tech industry can continue to evolve and drive growth in the digital advertising space.

The post What Is Supply Path Transparency & Optimization? appeared first on AdMonsters.

In ad tech, artificial intelligence is used for predictive modeling and real-time campaign optimization. DSPs use the technology to determine winning bids, and the sell-side uses AI to organize and tag inventory.

However, these days, there’s a new kid on the block that has the streets watching. Generative AI took the ad tech world by storm, but is the new IT girl a fad that will fade away in a few years, or does it have the staying power to impact the future of the advertising ecosystem? Experts have mixed opinions. 

For example, DMEXCO conducted a study surveying 500 industry professionals, and nearly three-quarters of them stated they found generative AI useless for their business. 

“Around one in ten of those surveyed in marketing, communication, and media may already be testing AI in terms of content production and search engine optimization, but most communicators are still cautious or even skeptical about actually using AI in their companies,” a DMEXCO representative said. 

On the other hand, publishers and tech platforms are adopting generative AI tools such as ChatGPT into their systems. Microsoft, Meta, and Snapchat have integrated generative AI technology into their business on a large scale. Publishers like Insider and Bloomberg are using or testing generative AI in their newsrooms. 

What Is Generative AI? 

 Generative AI does as its name suggests; it generates content. The content ranges from images, videos, text, audio, and other mediums. This subtype of artificial intelligence could disrupt every aspect of the advertising industry, from brainstorming to copyrighting to targeting ads. 

ChatGPT is the most popular form of generative AI. The technology takes text-based input and generates text-based outputs. Users can ask questions such as “What is the largest monument in the world?” or “How can I start understanding the programmatic supply chain?” The tech even allows the user to be creative. For example, for a recent AdMonsters event, we asked ChatGPT to write a song about ad tech in the style of a Beyonce song. Here are the results: 

I’m in the ad tech game, ain’t no shame

I’m the queen of targeting; it’s my claim to fame

I got the data; I got the insight

I know your interests; I know what you like

Chorus:

I’m in the ad tech game, making waves

Driving engagement, like it’s Beyoncé’s stage

I’m always innovating, never slowing down

I’m the queen of ad tech, wearing my crown

While the song won’t be winning any Grammys, the results show that the technology is intuitive enough to pick up some of Beyonce’s signature cadences while also sprinkling in knowledge about ad tech. 

Critics have also accused the tech of stealing jobs. With its ability to generate content, some have tested its skills. Actor Ryan Reynolds recently created an ad for his company, MintMobile, where the script was entirely written by ChatGPT. 

Despite some industry skepticism, publishers and agencies are integrating the tech. Microsoft is one of generative AI’s most prominent investors. They invested $1 billion into OpenAI, the company that created ChatGPT. ChatGPT is now incorporated into the Bing search engine, Office apps — Word, PowerPoint, and Outlook — and its Azure Cloud Service. Even ad tech vendor Admiral integrated ChatGPT into its Visitor Relationship Management platform to automate visitor engagement and generate publisher revenue. 

What Are the Concerns With Generative AI? 

The list of benefits for the tech is long, but industry experts have also raised concerns. 

The most pressing issue is the spread of misinformation. OpenAI even posted a disclaimer on its website. It reads: “All the information on this website is published in good faith and for general information purposes only. ChatGpt Connect does not guarantee this information’s completeness, reliability, and accuracy.” 

The tech is only as good as the information it receives. If the data aggregated into the tech is false, so will the output. Some businesses have already banned posting answers generated by ChatGPT. Stack Overflow, a platform used to generate questions, prohibits users from posting answers created by ChatGPT because of the model’s low accuracy rate. Often these answers have the appearance of truth, so it is hard to falsify them. 

In addition, generative AI could open new questions about data privacy. Some technologists are worried about how AI will disrupt targeted advertising once companies can upload their data to a model’s neural network. From the consumer’s perspective, how will they feel about artificial intelligence having access to personal data? 

There are efforts to regulate the tech. In March, The White House and the European Commission had their first official meeting to discuss the development of AI tech and how they can regulate it. The European Union created the Artificial Intelligence Act in 2021 for that very purpose; the emergence of generative AI upended those regulations. 

“There are potentially real benefits from large language models and applying those to various social problems, specifically writing more secure code to make sense of a lot of the data and insights out there,” a senior administration official from the White House said. “We want our economy to get those benefits, but there’s also real worry about it. The same vulnerability analysis one might do for cybersecurity; one might also do to find vulnerabilities to hack.”

Generative AI and the Advertising Ecosystem

We’ve already heard claims about how generative AI will vastly change the advertising ecosystem, but how? 

Customer Targeting: According to AI experts, generative AI can help brands target customers more directly and effectively. AI has the potential to sift through large data sets and find hidden patterns. Machine learning can highlight which customers are most likely to make a purchase based on their demographics and past purchase history.

Personalization: There are also claims that generative AI can help produce marketing assets and web content that is more personalized to the consumer. If brands aggregate the users’ data into the tech, it can help determine if an ad or web content aligns with a consumer’s interest. 

Testing: The tech can also help you measure the performance of a marketing campaign. You can give generative AI access to your company’s ad performance data, and it will generate answers for what you can do next. Experts warn that human intervention is necessary for this part of the process. 

The post What Is Generative AI and How Is It Changing the Advertising Ecosystem? appeared first on AdMonsters.

The days of online behavior being viewed and tracked for targeted advertising are over as consumers exercise their privacy rights and opt out of sharing their data with third parties. 

Cookie-blocking browsers, regulators, and tech are giving users the tools, awareness, and choice to protect their data by opting out of data sharing, creating a hidden web, and leaving just 30% of the open web addressable. 

Targeting must be sustainable, based on direct and not third-party relationships, and reach 100% of users while respecting their data choices —publishers’ privacy-forward cohorts. 

Publisher cohorts are consumers that are grouped based on a shared characteristic within a publisher’s environment. They are built from first-party publisher data and don’t rely on ad-tracking or third-party cookies. But advertisers need scale and standardization. This is where standard cohorts come into play. 

Scale and Standardization

Standard cohorts are interest-based publisher cohorts that can be generated automatically based on publishers’ first-party data. They are created using Natural Language Processing and the IAB 1.1 Audience Taxonomy, leveraging consistent and standardized behavior inputs. This solves for inconsistencies such as publisher A defining a food-lover as someone who visits pages on restaurant reviews and chef profiles twice in  60 days while publisher B defines a food-lover as someone who views one piece of recipe content over 90 days.

Much like privacy-safe publisher-defined cohorts, standard cohorts enable publishers to trade their rich audiences responsibly, without identifiers, which protects consumers. Third-party intermediaries are taken out of the equation to ensure publishers gain value from the one-to-one connection they have with their audience and the rich data and insights. 

In a recent interview with AdMonsters, Scott Messer, Principal and Founder of Messer Media, lamented the challenges of buyers seeking to activate unified audience definitions across multiple publishers and “publishers having unique inventory and wanting to label things uniquely.” He added that with standard cohorts “publishers are providing standardized ingredients, which allows advertisers to know exactly what they’re buying.”  

New Means of Monetization 

With standard cohorts, advertisers can buy at scale and collaborate with multiple publishers, which has many benefits for both.

For publishers, it unlocks a new means of monetization via private deals with advertisers. It helps publishers make all-important connections and seize growing buy-side demand using their audience data. This data truly represents and addresses 100% of audiences and will be the new currency of responsible audience activation. Standard cohorts also help publishers unlock demand across SSP partners and their respective advertisers, who seek privacy-safe and publisher-permissioned audiences. 

With these cohorts, advertisers gain a sustainable alternative to third-party data; audience reach in cookie-blocked environments, and clarity and transparency around audience composition and definition. It gives advertisers the confidence and transparency of a clear taxonomy qualified similarly across publishers, i.e., standardization. 

Advertisers that are working in this way are seeing results. A global beverage CPG brand, for example, course-corrected over-indexing in Chrome to reach double the previously hidden audience in Safari, helping solve their addressability problems. The campaign delivered 2.1x the number of impressions served in Safari vs. Chrome, resulting in a 21% lower CPC compared to the benchmark and a 123% higher CTR compared to the benchmark. 

Protecting Data and Value 

Standard cohorts give publishers and advertisers a sustainable alternative to the dwindling third-party data open marketplace and protect them as data and audience owners. Publishers and advertisers bring value with their direct relationship with the consumers. 

For publishers, standard cohorts go a step further and protect their valuable assets – with data being siloed per publisher and never exposed to advertisers or third parties, preventing the decoupling of data from inventory.

Given the advertising industry’s privacy climate, standard cohorts greatly benefit the consumer, protecting their data with a privacy-preserving approach to targeting, just like publisher cohorts. With the added scalability standard cohorts provide, advertisers and publishers have a sustainable way of targeting relevant audiences in this new era of digital advertising.

The post What Are Standard Cohorts? appeared first on AdMonsters.

Advertisers and brands should keep podcasts as a promotion channel in their media plan because podcast ads are effective and memorable.

Traditionally, podcast monetization relied on host-read sponsorships: ads were baked into the show, effectively becoming part of the content forever. However, suppose a new FTC guideline — about endorsements reflecting the experience of the advertising party — gets approved. That would place more scrutiny on the definition of personal endorsements done by podcasters, similar to other media. 

The next evolution in podcast advertising was the ability to dynamically insert ads into the podcast, enabling more flexibility in planning and managing campaigns. However,  sales strategies remained largely the same: the publishers (or their sales arm) negotiated an insertion order with the advertisers (or their agencies). 

The Rise of Ad Trading in Podcasting

Programmatic advertising changes how agencies and independent trading desks trade ads: it uses computers to create efficient marketplaces where one or more bidders compete for a particular opportunity.  

Programmatic podcast advertising is gaining market share, and more and more publishers are interested in integrating it within their monetization strategy, dramatically increasing revenue generation. 

Old-school hosting platforms cannot trade programmatically, but now these efficiency features are available on the platforms that seriously invested in ad tech from the early days.  

In this article, we will explore the value chain of podcast monetization and how programmatic advertising has changed the game for publishers and advertisers alike. However, we all know that with opportunities come unique challenges, so let’s start with the difficulties. 

Publisher-side Challenges 

Coherent ads in line with content: This is easy from a direct sales approach.  But it is more of a challenge with programmatic buys at scale.

Finding a sponsor/brand/agency: Finding the right sponsor or brand to support content can be a significant challenge for publishers. With so many options, it can be difficult and lengthy for publishers to stand out and attract the right brand for their audience.

Running campaigns across inventory: Ad operation teams manage campaigns, but ensuring that a campaign runs smoothly across the entire inventory requires technical expertise and resources.

Renewing a sponsor or finding new ones: Sales ops is another challenge for publishers when it comes to advertising. Finding new sponsors and renewing existing relationships requires a dedicated sales team and a well-established process.

Reporting and doing make-goods: (If under-delivered) or giving inventory for free (if over-delivered). Ensuring that the right metrics and measurement solutions are in place and that the inventory is utilized effectively is essential for success.

Advertiser-side Challenges

Targeting capabilities (content and audience): On the demand side, finding the correct audience and delivering the right content can be difficult without the necessary data, tools, and resources. Especially today, where privacy and security laws are constantly getting more constringent. 

Brand safety & suitability: Ensuring brand-safe and suitable content is also challenging for demand side partners. This requires a strong understanding of the content itself and the audience.

Monitoring and Reporting on ROI: Finally, monitoring and reporting on ROI can be challenging for demand-side partners. To achieve success, it is important to have the right tools to monitor the correct metrics and ensure that the ROI is measured effectively.

Solution

At Spreaker from iHeart, we have developed the secret sauce for successful programmatic podcast advertising. 

Conveniently the solutions all begin with S — we like to call it the 3 S’s of monetization and advertising success:

•     Sustainability
•     Scalability
•     Safety

Sustainable: Avoid the “once in a Blue Moon”

When starting a podcast, you want to make sure that earnings, supported by multiple ad opportunities, are constantly coming in. Publishers should not let any inventory remain unsold. It also means the programmatic strategy is fully compatible with other revenue streams, including direct sales and sponsorships. Conversely, advertisers can rely on programmatic buys to customize and adjust their clients’ needs throughout the year.  

Scalable: From Download #1 to #1 Billion

No podcast starts with one million downloads on the first day, so progressive audience growth needs to be accompanied by a scalable revenue stream. Moreover, dynamic ad injection coupled with programmatic buys allows publishers to place and replace ads over time after the initial exclusivity and grace period at scale.

On the buyer side, brands and advertisers use advanced audience targeting, reach, scale, real-time campaign monitoring, and attribution reporting to justify investing wisely in programmatic.

Safe: Safety Lasts

Safety should come first, but it’s also last in podcast advertising. Safety creates a bond of trust between the publisher and the advertiser by targeting safe content and by making sure that the ads are correctly assigned to the targeted content. Under this umbrella, the ad tech and programmatic ecosystem can provide tools to empower brand safety and eventual suitability (with products by companies like Barometer and Sounder and many others), content transparency, and ad quality at scale, like our AI + human solution called M.A.G.D.A..

The 3 S’s of monetization success, Sustainability, Scalability, and Safety, are the crucial combination for any publisher looking to monetize their podcasts and advertisers looking to invest their budget wisely. 

By focusing on these three key factors, we can ensure that podcast advertising efforts are effective, efficient, and profitable for both advertisers and publishers. 

The post What Are the 3 S’s of Programmatic Podcast Advertising? appeared first on AdMonsters.

Many of the processes in current and long-standing ad ops workflows are heavily manual, like audience targeting, campaign set-up, optimization, and data analysis, to name a few.

This doesn’t feel like it’s setting ad ops teams up for success. They are typically working on parallel campaigns across different ad servers and platforms, resulting in heavily fragmented data, making it difficult to track and analyze campaign metrics when done manually.

Manual ad ops lead publishers to face challenges such as error rates, large numbers of make goods, longer revenue recognition processes, and lack of ability to optimize workflows for efficiency. Not to mention, these processes create a hefty amount of manual work that is repetitive in nature and prime for automation.

“Manual processes in operations create inefficiencies and consume time that could be better spent on revenue-generating activities. Their reliance on constant human input is prone to human error generating even greater inefficiencies in fixing mistakes.” Gordon Tatomirovic, Projects and Partnerships Lead – Digital Operations, Nine.

But publishers aren’t the only ones trying to navigate through these challenges.

The Inefficiency of Legacy Workflows

We are seeing a trend of ad monetization driven by manual ad ops processes bleeding into various industries. Many ad ops processes utilized by new media players, including retail media networks, CTV, and streaming companies, are adaptations of legacy processes and workflows used by long-standing publishing and media brands.

The speed at which retail media networks, CTV, and streaming media have grown in recent years has created a need to continuously run their processes as quickly as their respective industries and the ad monetization revenue models they utilize are evolving. The rapid growth in the industry, coupled with the demand for targeted audience reach, has left little to no time for these increasingly popular platforms to evaluate their processes and optimize for speed and growth. These new players are quickly encountering challenges that took publishers and legacy media brands years to face and address because of their rapid growth and digital nature.

The legacy methodologies that worked in the past no longer serve today’s modern digital media players. With the cost of new eyeballs and audience targeting getting steeper each day, these platforms need to create more sophisticated offerings that enable growth at scale for both their business and their clients.

The path to achieving optimal efficiency and output is through automation and AI integration to streamline existing processes and workflows.

The Rise of AI and Machine Learning

Technology has become a vital tool across all industries to enable efficiency. Let’s look at automation in the same light.

Brands that leverage ad monetization strategies intend for automation to become a tool in the existing MarTech stack that enables companies to take the menial, repetitive tasks off ad ops plate and free them up to focus on account and client management and business growth strategies. Implementing automation and AI into existing processes and workflows should be seen as an opportunity to grow and expand skills.

Teams and individuals who are inputting data into spreadsheets, manually checking and cross-checking targeting, or pulling data from multiple sources to create manual reporting could use that time to instead focus on more advanced strategies and other elements of the process that are harder to automate. The ability to make connections between brands and end customers will always be human-driven, and elements of these emotion-based processes, like design and messaging or building relationships with clients, must be driven by humans.

Automation is also a key factor in enabling career growth and development. The need for people to do remedial tasks takes time away from higher-level thinking and strategy, which ultimately will be what drives great results. By providing teams with the tools they need to automate certain functions, businesses are also enabling these teams to upskill and grow as professionals.

“Through our partner, Theorem, we have been able to use their screenbot technology to eliminate thousands of man-hours worth of work a year, and our team can better use this time in servicing our clients. Further, Theorem has been able to automate many of our reporting requirements, saving countless hours.” Gordon Tatomirovic, Projects and Partnerships Lead – Digital Operations, Nine.

AI isn’t about taking jobs away from people. It is about freeing up their time to contribute more to the overall growth of their business and having more time to focus on their professional development and career pathing.

Implementing Automation Strategies

We’ve talked about the need for automation. Now it’s time to dig in and talk about the how.

How can media companies and business units implement automation into their workflows?

As a result of the manual elements of most workflows, many publishers face challenges when it comes to error rates, large numbers of make goods, longer revenue recognition processes, and lack of ability to optimize workflows for efficiency.

The first step in establishing how to best automate is for companies to pinpoint where current processes are slowing them down and preventing them to scale. When automating, it is first important to remember where the processes have come from. Having a deep understanding of existing processes within media organizations and identifying elements that could be automated to increase speed and efficiency while eliminating error rates is key.

The next step in the automation process is understanding the business’s current and future goals and objectives. Companies must consider the existing and future states of the business when analyzing where and when to implement automation across existing processes and how that will evolve as the business grows at scale. Starting with back-end automation implementation will help resolve current challenges that will enable better visualization of elements within additional workflows and processes that are prime for automation.

The bottom line is that automation isn’t just a “nice to have” anymore – it’s become necessary for business success. The speed at which industries move today forces companies to reevaluate their processes and find areas to increase efficiencies to drive sustainable revenue and reduce human errors. Overall, automation isn’t a bad thing. If anything, it frees up time for employees to pursue their passions and play a bigger role in the business’s overall success.

Companies must understand now is the time to automate. And if they don’t, they are going to be left behind.

The post How Can Ad Ops and New Media Players Eliminate Inefficiencies? appeared first on AdMonsters.

For example, in the digital advertising landscape, programmatic advertising has revolutionized how advertisements are bought and sold, using technology to automate the process and deliver targeted, data-driven campaigns. This has only been further compounded by the emergence of ‘Header Bidding,’ which offers a more streamlined and efficient way for publishers to monetize their inventory and for advertisers to reach their desired audience. 

A recent study showed that header bidding led to a 23% increase in fill rate and a 20% increase in average CPM. With these benefits and more, it’s no wonder why header bidding has become a popular and essential tool for publishers looking to maximize their monetization potential.

What Is Header Bidding and How Does It Work?

Header bidding, or pre-bid or advanced bidding, is a programmatic advertising technology. It is a real-time programmatic auction where multiple demand partners bid on a single impression. 

Header bidding allows publishers to offer their ad inventory to multiple SSPs (Supply-Side Platforms), ad networks, and ad exchanges to bid before sending the bid call to the ad server. This results in a more competitive and transparent bidding process, as demand sources compete against each other for the same inventory in real-time.

Behind the Scenes:

Header bidding works by incorporating a JavaScript code snippet into the header of the publisher’s website. So, when a user visits a page, this JS code sends out an ad call to all configured demand partners to bid on the available ad units. While the header auction happens, Google Publisher Tag is paused. Once the bids are received, they are sent to the ad server for the second auction round. Based on the configuration set by the publisher, the ad server filters out the winning bid and serves the creative on the user’s page. 

What’s interesting to note here is that all these auctions happen while the page loads on the user’s browser. And as soon as the page loads, the aim is to display the ads at the required places. 

Benefits of Header Bidding

Before header bidding, publishers and advertisers relied on the ‘Waterfall or Daisy-Chaining’ method to buy and sell media. In waterfall, a series of demand partners sent ad requests, each given a priority based on their past performance and the estimated value of the ad inventory. So, if a demand partner sitting at level 1 cannot fill the ad request, the bidding call will go to the next bidding partner sitting at level 2. The bid request will keep on moving down until it is sold off. 

As the bid request trickles down the hierarchy, it often results in a slow and inefficient process, with many ad impressions going unsold. Also, as the partners are arranged based on their past performances, it might happen that a bidder who is willing to bid more but is sitting at level 2 or 3 might never get a chance to bid. The method lacks transparency and limits the ability of publishers to earn maximum revenue.

Header bidding evolved as a replacement for the waterfall method and brought great relief to the users as it allowed:

1. Increased competition: Header bidding allows multiple demand sources to bid on the same inventory simultaneously, leading to increased competition and higher CPMs for publishers.
2. Improved transparency: It provides greater visibility into the bidding process, allowing publishers to understand the value of their inventory better and make informed decisions. 
3. Faster load times: Header bidding enables publishers to load bids from multiple demand sources in parallel, reducing latency and increasing the number of impressions served. The bidding happens during a fixed timeframe. 
4. Flexibility: It allows publishers to make real-time adjustments to bidding strategies, enabling them to optimize for specific inventory and respond quickly to changes in market conditions.
5. Better targeting: Header bidding provides more advanced targeting capabilities as publishers can share relevant data with the demand sources in real-time. This, in turn, allows advertisers to reach specific audience segments and helps publishers increase revenue by providing more personalized ad experiences to the users.

How to Set up Header Bidding?

Setting up header bidding can be complex, but it’s worth the effort. The first step involves the integration of a header bidding wrapper, a piece of JavaScript code that is placed in the header of a publisher’s website. The wrapper communicates with demand sources, allowing them to bid on inventory in real-time. Once the container is in place, publishers can integrate demand partners, such as ad exchanges, SSPs, and ad networks. They will also need to configure the settings to meet their specific needs.

Owing to the technical complexity of the setup, it’s always advisable to look out for a header bidding provider. A good header bidding provider will handle the setup, bring in good demand sources, and offer complete transparency. 

Wrapping up

The benefits of header bidding are numerous, and for publishers looking to maximize their revenue, it is an essential tool in their arsenal. By partnering with a trusted header bidding provider, publishers can access the latest technology, expert support, and valuable insights to help them achieve their revenue goals. 

With the right partner, the benefits of header bidding are endless, and publishers can rest assured that they are making the most of their ad inventory and reaching their target audience with the most effective and relevant advertising. 

The post How Can Publishers Boost Their Ad Revenue with Header Bidding? appeared first on AdMonsters.