In today’s privacy-first world, , cookie-based targeting has been a central pillar that both advertisers and publishers have relied on heavily for decades. According to a Deloitte survey, the average projected revenue risk ranged from around $91 million to $203 million per year, with some companies risking upward of $300 million in revenue. A Google study showed that for the top 500 global publishers, the average publisher revenue decreased by 52% with a median per-publisher decline of 64%.

Publishers who have exclusively relied on third-party cookies have begun to feel the heat. Much like advertisers, publishers have been evaluating other strategies to help them grow their revenue while remaining privacy-compliant. Beyond business-as-usual, the progressive loss of signal and reach of cookies presents publishers an opportunity to future-proof their business and generate new revenue streams. This approach is not just a short-term fix, but a sustainable, long-term strategy to future-proof the business against privacy changes.

How are publishers riding the Data Privacy-First World wave?

Publishers are looking to continue to expand their readership and audience trust and audience trust in a privacy-first world, where privacy compliance and transparent data usage are becoming paramount. While large tech companies have traditionally dominated the advertising space, publishers are now taking more control over their ad inventories through privacy-compliant solutions.

​​Topics API is the Privacy Sandbox entrant that was initially introduced as an alternative to third-party cookies, to enable privacy-first, interest-based advertising. To make the most out of Topics, publishers and advertisers must use them with other tools to develop more innovative marketing strategies that cater to the new-age audiences.

Leveraging First-Party Data for Better Targeting

While third-party data has been a staple for targeting, publishers are increasingly focusing on first-party data, which is more reliable and privacy-compliant. Information that audiences willingly share can be used alongside Topics for a more tailored and relevant targeting approach. First-party data is a gold mine that publishers can leverage to monetize audiences and boost revenue numbers. Secure collation of first-party data is essential to collate privacy-safe media that can be monetized by publishers, but they must be cautious with personal data, ensuring that they only use it with user consent and in accordance with privacy regulations with the General Data Protection Regulation (GDPR) to avoid potential legal risks.

"The amount of data publishers can collect from first-party sources is growing, allowing for more personalized and relevant ad targeting".

Evaluating and Upgrading Tech Stacks to Enable Privacy-Safe Data Collaboration

Publishers are working towards evaluating their current tech stacks and upgrading them to create more data clean rooms that enable privacy-safe media collaboration. Publishers can collaborate with advertisers and monetize the data by giving them access to the valuable repository. Effective consent management is crucial for publishers to ensure that the data they collect is used appropriately and in compliance with privacy regulations.

AI-Powered Contextual Advertising: Boosting Monetization and User Experience

AI-powered contextual advertising offers publishers a cookie-free solution that aces targeting and better utilizes first-party data. Contextual ads are proving to be a game-changer for publishers by enabling them to navigate privacy regulations and create a sustainable monetization strategy.

• Contextual AI analyzes the written content of a page and empowers publishers to provide advertisers with an environment that offers the highest levels of brand safety and suitability. Machine Learning (ML) and Natural Language Processing (NLP) capabilities of contextual advertising enable understanding of nuances in language and the ability to semantically interpret editorial content. Brand suitability bridges the divide between risk and opportunity and provides context-based protections for advertisers and publishers. Brand safety ensures they steer clear of any negative or harmful content that can impact user perception and damage the reputation of publishers or advertisers.
• With contextual ads, publishers can have a higher impact on users as they are relevant ads displayed alongside high-quality content. The ads are more relevant and impactful as they speak more directly and personally with the readers, increasing the likelihood of users paying attention and engaging with contextual ads. Publishers who host contextual ads unlock a new, steady revenue stream as the relevance to the content users are currently consuming increases brand recall. Better brand recall and ROI on dollars spent increase the chances of advertisers continuing to buy inventory. By using AI-powered contextual advertising, publishers can expect higher conversion rates as ads are more relevant to the audience’s interests.
• Contextual advertising also enables publishers to enhance the overall user experience. Contextual ads are more relevant to the real-time interests of users, are less intrusive, and do not hamper their browsing experience. A more pleasant overall experience will help publishers grow their readership as users are more likely to come back and recommend them to other readers. It allows publishers to focus on reaching and engaging the right audience, ensuring that the ads displayed are highly relevant and impactful.

Collaborating with a contextual partner will help publishers unearth new monetization opportunities and provide a superior user experience. Engaging creatives, content alignment, and intelligent ad placement ensure contextual ads are seamlessly integrated with the on-page content, thus maximizing visibility, impact, and revenue potential.

Embracing a Privacy-First World for Sustainable Growth

We have partnered with over 11,900+ digital publishers across the globe, and our combination of relevant data and new-age technology helps them make the most out of every ad placement in a privacy-first world. 80% higher viewability, 15% longer in-view time, and 1.3% more click-throughs; our unique, data-backed targeting strategies and innovative methods like custom AI, backed by our in-house contextual AI solution, Liz, have delivered exceptional results when compared to exclusively relying on cookie-based targeting practices.

The ad tech world is steadily shifting to more inclusive and privacy-centric advertising practices that align with the requisites of consumers and data privacy regulations. Fundamentally, audience categorization has largely been based on the demographics and past behavior patterns of users. This practice is based on assumptions and stereotypes that are limiting, not always accurate, and relies on third-party cookies.

The audience selection and classification process plays a crucial role in determining the success of an ad campaign. By collecting data from various sources, advertisers leverage data to display ads to users based on their assumed interests, hobbies, and browsing activities. The main data points include -

• The websites and apps a user chooses to visit, browsing patterns and interactions, and what kind of content they engage with
• Demographics like age, gender, and location
• Interests listed by the user on platforms like social media
• Third-party data

Using this data, marketers profile potential customers who are most likely to buy their product or service and target their ads to those individuals.

What is interest-based targeting?

Consumers have become increasingly apprised of digital advertising practices and are well-informed about their data and personal information being collected whenever they are online. The increase in awareness and rising frustration of consumers around data privacy resulted in the decision to phase out third-party cookies and governments implementing more stringent data privacy regulations. Marketers are facing several restrictions today and the conventional audience categorization and targeting practices will result ineffective as they are built on stereotypes and assumptions, and are not privacy compliant.

While traditional advertising practices reach a broader audience, they are not necessarily effective as everyone who views the ad might not be interested in the product/service, leading to wasted ad spend. Consumers have access to a plethora of information and are bombarded with hundreds of ads daily. A blanket targeting approach sans any personalization or relevance is not just ineffective but could have a negative impact as it disrupts the user journey. Additionally, consumers are also using ad blockers to avoid traditional ads while streaming services give them the option to skip ads.

New-age targeting goes well beyond the conventional, identity-based targeting approach and focuses on a user’s current areas of interest and the context of the content they consume. Breaking away from stereotypes, interest-based targeting is held as a more effective, non-intrusive, and privacy-centric alternative.

The rise of interest-based targeting in the cookieless world

Contextual targeting is a strategy that focuses on categorizing consumers based on what they are interested in at present, by displaying ads that align with the content they are consuming on a web page or app. When the on-page content and context align with the ads, it ensures a seamless, privacy-centric, and non-intrusive customer experience. Interest-based targeting enables personalization and allows marketers to tailor ads to individual preferences, thus enhancing relevance and engagement. Users are more likely to engage and resonate with the ad because it aligns with what they are looking for in the moment and since the ads blend with the content they are reading, the ads don’t hamper their browsing experience.

Seedtag Contextual Audiences help brands go beyond conventional targeting practices and engage with users based on what they are looking for or interested in at the moment. Powered by Liz©, our pioneering AI technology,  custom AI, contextual categories, images, and cookieless sociodemographic models, allows brands to target an audience base that’s diverse, inclusive, and relevant. Our Contextual Audiences evolve from customer input and diverse market research enabling brands to build unique and dynamic audience categories to suit specific business needs.

Interest-based targeting practices like contextual targeting empower marketers to appeal to a more relevant customer base with ads that align with their real-time interests. Contextual ads appear at the most optimal time and place with tailored messaging without violating privacy, thus helping brands reach the desired audiences with a targeting capability that is more flexible and accurate. With interest-based targeting, brands can capture user attention at the ideal moment without relying on cookies, and overcome the limitations of rigid taxonomies and stereotypes.

With Seedtag Contextual Audiences, brands can build a hyper-personalized target group. Backed by AI, this unique targeting capability provides flexibility, scale, and higher accuracy. To know more about the exclusive offering and types of contextual audiences, contact us.

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With the demise of the third-party tracking cookie just months away for Chrome users, digital advertisers who have yet to begin preparations need to catch up swiftly to navigate the transition successfully.

One of the primary alternatives to the deterministic data enabled by cookies is Google’s Privacy Sandbox, which the company describes as “a series of proposals to satisfy cross-site use cases without third-party cookies or other tracking mechanisms.” Initially composed to include audience models like Google’s Federated Learning of Cohorts (FLOC), which was sunsetted in 2022, the Privacy Sandbox includes Protected Audiences (formally known as FLEDGE or “First Locally-Executed Decision over Groups Experiment”) and other APIs that will undoubtedly dictate the contours of the market to come. Businesses across the ecosystem should consider the following details when preparing.

Reevaluating The Focus: Beyond IP Addresses

In the past, digital advertising heavily relied on tracking users through cookies and IP addresses. Protected Audiences and Google Topics moves away from this practice, emphasizing a more privacy-focused approach. It presents a challenge and an opportunity for marketers to improve performance on a device level without resorting to invasive tracking methods.

A crucial aspect of working with Google Topics is to integrate contextual information with situational and device-specific data provided by Google Topics signals. The zip code, for instance, can be a valuable contextual signal. By combining these data sources, advertisers can gain a better understanding of users' preferences and needs, all while respecting their privacy. This approach opens the door to a new world where the cohort can contribute to a more nuanced contextual understanding.

The Evolution Of Performance Marketing

As Protected Audiences and Topics contextual models become increasingly relevant, performance marketers need to adapt to the changing landscape. This transformation involves elongating the marketing funnel and focusing on strategies beyond traditional last-click attribution.

• First-Click Strategies. Performance marketers can adopt first-click strategies to recapture email addresses for retargeting or directly upload data from CRM systems. This shift might result in a longer turnaround time, possibly extending from a six-day window to 10-15 days. However, the potential benefits in terms of privacy and engagement could make it worthwhile.
• Dynamic Creative Optimization (DCO). With privacy concerns taking center stage, it's essential to shift from audience-centric advertising to context-centric advertising. DCO allows advertisers to tailor content to the context of the page rather than focusing solely on the audience. This approach ensures that ads remain relevant while respecting user privacy.
• Redefining Retargeting. Retargeting is evolving. Instead of relying solely on traditional methods, marketers can explore new avenues like email retargeting and mobile site optimizations. These practices add value for the user, offering content, discount codes, tips and trends. It's a broader approach to content marketing, where the emphasis is on reengaging with users in a more meaningful way. Loyalty programs can also play a significant role in this transformation, allowing users to choose their preferred engagement strategies.
• Contextual Lookalikes. One exciting development in this landscape is the emergence of contextual lookalikes. This approach leverages first-party data, whether it's cookie-based or segmentation data, to identify commonalities among users. Instead of relying on tracking and personal data, contextual lookalikes provide a privacy-friendly way to find users with similar interests and behaviors.

In the coming transition, choosing the right partners is crucial. Marketers should seek out tech-forward partners who are committed to responsible and privacy-conscious advertising practices. It's important to avoid partners engaged in arbitrage or those who use "AI" as a copout without a genuine commitment to user privacy.

The Importance Of Retooling Analytics

As performance marketing evolves, it's crucial to retool analytics. Media mix modeling remains essential, even if it's probabilistic. Marketers should look closely at unit economics that can lead to conversion metrics. For instance, understanding the return on ad spend (ROAS) as a "three to one" ratio requires a deep understanding of the step functions involved. This level of analysis is more critical now than ever as privacy and user consent become paramount.

The era of the Privacy Sandbox and its two main APIs, Protected Audience and Topics, signals a significant shift in the world of digital advertising. Performance marketers must adapt to these changes by embracing contextual models, moving away from invasive tracking methods and respecting user privacy. Strategies that elongate the marketing funnel, focus on context over audience and leverage first-party data offer a path forward. By selecting tech-forward partners and retooling analytics, marketers can navigate this evolving landscape successfully, ensuring both effective advertising and user privacy.

By Mike Villalobos, VP of Strategy and Partnerships at Seedtag.‍

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From browsers like Firefox, Safari, and Opera completely banning third-party cookies to their complete demise in 2024 with Google’s phase-out of cookies; all eyes are on privacy and global regulations. The end of third-party cookies marks the beginning of a new era in advertising as the go-to targeting practice worldwide will become obsolete.

In a survey conducted by Statista, 75% of marketers revealed that they heavily relied on third-party cookies. 45% of respondents stated spending at least half of their marketing budgets on cookie-based advertising. With the fundamentals of audience tracking, targeting, and personalization becoming obsolete, there is a lot of debate around what will be the next best approach for audience targeting that will give marketers a competitive edge.

How are marketers preparing for the cookieless world?

Among the options marketers are evaluating, contextual advertising has been one effective stand-out targeting alternative that has gotten the nod from leading global brands. Contextual advertising is backed by new-age tech like AI, ML, and NLP, paving the way for personalized and impactful advertising in the privacy-first world.

Another alternative that has been around for a while but has garnered more importance ever since the deprecation of third-party cookies is first-party data. First-party data is collected with the knowledge and consent of users when they interact with a brand’s website or advertisement, or purchase a product. However, first-party data is not a magic formula. When utilized individually, first-party data lacks the ability to scale, enhance the precision of audience segmentation, or improve ad placement.

Contextual advertising is scalable and allows marketers to create custom audiences. This opens doors to never-seen-before opportunities and delivers advertising strategies that go beyond traditional metrics like impressions and CTRs. Contextual ads rank high across impactful attention metrics that provide insights into more quantifiable data like the quality of user engagement and campaign efficacy. Contextual advertising aces granularity, accuracy, and relevance by placing ads based on the content and context of web pages, thus helping marketers go beyond stereotypical audience segmentation practices that rely on audience demographics, past browsing patterns, and assumptions.

It also ensures enhanced levels of brand safety and brand suitability. Its ability to understand nuances in language and interpret the meaning of content used within a given context empowers brands to avoid harmful or negative content and maximize opportunities. With AI-powered contextual targeting, marketers can display ads in environments where the messaging aligns with a brand’s values and positioning.

Maximizing impact with the duo

What if marketers could take contextual advertising up a couple more notches? By utilizing precious first-party data repositories along with contextual advertising, marketers can further fine-tune their strategy and maximize the impact of a campaign. Based on the audience information derived from first-party data, audiences can be further segmented based on factors like age group, gender, or location. Since this data is collated with user consent, it is compliant with all privacy regulations. With first-party data-backed audience categorization, marketers can tailor messaging to suit very specific audience segments.

For example, with the combination of intel from first-party data with contextual advertising, a brand can target its repeat customer base with a new product launch or launch an exclusive privé members-only sale. Campaigns and messaging are more tailored and relevant to the target audience, driving more impact and ROI. It can also be used to create geo-specific campaigns during a particular time of the year or during festivals that are more prominent in a particular location. For celebrations like Valentine’s Week, curated gifting ideas or product collections can be showcased to specific genders and age groups to drive more engagement.

Fueling contextual advertising with first-party data will empower marketers to strengthen their strategies and create high-impact campaigns that connect with the desired audiences. The duo ensures seamless, privacy-centric, and non-intrusive experiences that customers love.

Interested to learn more about contextual advertising and its capabilities?

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Cue Lover by Taylor Swift…It’s Cupid’s time of the year and the hearts are all afloat. From roses to teddy bears, cards, and jewelry, romance is brewing strong. Couples are on the lookout for the perfect date nights and the ideal gifts to present their loved ones. World over, Valentine’s Day is one of the highlights of February.

In today’s rapidly changing environment, seasonal events like Valentine’s unfold every other day. It is important for brands to not just track, but truly understand these special occasions to capitalize on them. We analyzed the evolution of content creation and its consumption to show how this day impacts the open web. In 2023, Valentine's Day was an engaging and relevant topic, with a particular interest in high-profile couples and commercial promotions. The data showed a steady increase in the number of views as Valentine's Day approached, peaking on February 20th, with the top articles indicating a mix of celebrity news, product promotions, and romantic rumors.

So what’s trending this Valentine’s?

According to our 2024 analysis, the interest in content is mirroring a pattern very similar to that of the previous year. However, we are experiencing a higher viewership when compared to the same time period last year. As a result, we anticipate a substantial increase in views, with the peak expected to reach a staggering 500,000 views on the most prominent days!

The top category with over 15% article distribution is events and attractions, followed by pop culture and family and relationships hovering over 10%. Travel, music and audio, food and drink, and movies are the next set of categories with a 5 - 10% distribution. The last 3 in the top 10 are television, home and garden, and sports.

What are the areas of interest of the Valentine's Day-focused audience?

1. Garnering over 2.82M impressions, Love Life is a key interest area where the content centers on the romantic journeys of individuals. The content interest ranges from finding a partner to tying the knot and building a family. The top keywords include power couple, baby son, beautiful family, heartfelt message, closeness, life together, and happy marriage.
2. Love life is followed by Celebrities Relationships with 2.4M impressions. The content shines the spotlight on well-known celebrities and public figures, delving into the intricacies of their breakups, romantic escapes, and the elaborate ways in which they celebrate Valentine's Day. Some prominent keywords are relationship timeline, Georgina, Kardashians, Gigi, Love Island, couple, Taylor Swift, celebrity news, and daily celebrity.
3. Up next is the much-talked-about Valentine’s Day Plans with 2.32M impressions. This genre places the importance on enhancing the celebration of love and connection through activities and arrangements that couples can enjoy together. This includes keywords like a romantic date, hotel, romantic stroll, romantic dinner, laser tag, authentic Italian, night sky, and outdoor adventure.
4. With 2.05M impressions, Rom-Coms are next in line, emphasizing the charm of romantic comedy films and the relaxed, comforting atmosphere they provide. Some trending keywords are Ryan Gosling, Love Actually, Dicaprio, Cameron Diaz, Jennifer Aniston, comedy film, streaming platform, and pride.
5. Valentine’s Day Presents come in fifth, gathering 1.53M + impressions by throwing light on the importance of thoughtful presents as a tangible expression of love and appreciation, thus enhancing the romantic connection. The top keywords are gift box, wishlist, Etsy, gift card, pet shop, spa treatment, happy valentine, chocolate, and jewelry.

These areas of interest and keywords are unique to this Valentine’s season. Seasonal audiences have a high affinity for particular environments within the content universe. Brands must engage with this audience pool by sharing the right messaging within their realm of interest at the most optimal time. This requires a shift from the ordinary.

Move beyond traditional audience segmentation based on stereotypes and go contextual to deliver a scalable strategy for the open web. With Seasonal Audiences powered by Liz, brands can engage audiences with a privacy-centric strategy during the peak of specific global seasonal events like Valentine’s Day.

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As the phase-out of third-party cookies begins, marketers worldwide are pondering over ideal alternatives and weighing in on what could be the ideal replacement solutions. The DoubleVerify report, Post-Cookie Questions: The Evolution of Advertising Strategies and Sentiments revealed that publishers and advertisers are divided on which solutions they believe hold the greatest promise in replacing cookie-dependent solutions. 47.3% of publishers said publisher first-party data activation was their top choice while 49% of advertisers picked advertiser first-party data activation. Social media targeting, Google Topics, Attention-based metrics, and contextual advertising were among the other solutions.

Interestingly, the report also found that  96% of publishers surveyed said that contextual advertising capabilities will be important for their businesses in 2023. 94% of advertisers stated they were planning to rely on contextual advertising for some or most of their buys in 2023. However, contextual targeting has significantly evolved over the past few years, transforming from a mere cookie-replacement alternative to a must-have strategy for future-proof, privacy-first advertising.

The magic of AI-powered contextual targeting

Today, contextual targeting is backed by AI, ML, and NLP capabilities that enable the possibility to go beyond just keywords, understand nuances in language, and semantically interpret content. Contextual targeting’s ability to understand the meaning and sentiment of full pages of content with their complete context is opening doors to several new targeting possibilities.

For example, let’s take an article titled Makeup for Everyone: Organic products for all skin tones and types. Earlier, contextual targeting’s capability was limited to identifying that it is an article on makeup products in a lifestyle publication. The new and enhanced contextual targeting understands and interprets that it is an article on organic beauty products for people of different skin types and colors.

Contextual targeting’s ability to derive that level of granular detail about an article ergo means a heightened understanding of the readership, their mindset, and interests; fundamentally changing the way audiences are segmented and targeted. Advertisers can leverage pre-defined contextual  audiences, modify them, or even build their own personalized audience segments based on who they want to reach with a particular message.

Displaying a vegan beauty product ad to women who are interested in premium beauty products that are cruelty-free, vegan, and suitable for acne-prone skin; that’s the level of granularity, accuracy, and relevance contextual targeting brings to the table. It presents an opportunity for advertisers to look beyond conventional, stereotypical audience segmentation and targeting practices that are not very detailed or precise.

Contextual targeting: More than just a cookie deprecation alternative

Contextual targeting fueled by AI is not just an option or alternative but a door to a whole new world of possibilities in digital advertising. Advertisers and publishers can finally look beyond standard taxonomies, demographics, traditional cohorts, or off-the-shelf audience segments. It’s a chance to finally break free from the ordinary and meet users within their realm of current interests, at the right time. Contextual targeting empowers advertisers to unearth new opportunities and capitalize on those that were overlooked or never even considered before. While zero and first-party data gain more importance, contextual targeting can help brands maximize the impact they can create using this data repository.

Contextual targeting’s ability to understand the meaning of content within a set context significantly boosts brand safety and brand suitability as it avoids any negative or harmful content and provides brands an environment where the values and ideas fit seamlessly with their own. In the ever-evolving digital landscape, contextual targeting presents an opportunity for advertisers to level up their strategy and win big. The difference lies in the approach; marketers who look at contextual targeting as just an option to overcome the privacy limitations won’t reap much when compared to those who go all in to make the most out of it.

Ready to shift gears and embrace new-age contextual targeting?

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It’s 2024, the year of privacy is finally here. Google announced the deprecation of third-party cookies back in 2019 and the world has been abuzz ever since. The countdown has finally begun. January 4th marked the pivotal change as Google Chrome began the third-party cookie phase-out by initiating its restriction for 1% of users. Google also revealed that it plans to ramp up third-party cookie restrictions to 100% of users from Q3 2024. However, it was finally announced that the cookie deprecation would not take place as such.

With this, the digital advertising world marks a fundamental change in ad strategies and the go-to source of user targeting will soon cease to exist. Now publishers and advertisers must look for alternative approaches to reach users with tailored content that matches their preferences. As traditional, cookie-dependent practices become obsolete, the need to transition is inevitably clear. In a survey conducted in late 2022, 59% of respondents stated that they were either accelerating their readiness for a cookieless future or keeping it a high priority.

In anticipation of the cookieless future, Google introduces Privacy Sandbox. The Privacy Sandbox is Google’s initiative that aims to provide phase-out support for third-party cookies when new solutions are in place. It plays a crucial role in enabling advertisers and publishers to continue offering content online by ensuring a balance between user privacy and the sustainability of online services, reducing cross-site and cross-app tracking.

Digital marketing in the privacy-first world

Beyond Google’s Privacy Sandbox, advertisers are also exploring other alternatives to third-party cookies to make a seamless transition and create effective privacy-first ad strategies. One of the more obvious emphasis has fallen on first-party data. Data collected with the knowledge and consent of users, first-party data refers to the information that a brand collates from users when they interact with the brand’s website and marketing/advertising literature or make a purchase. This data gives advertisers insights into user preferences that help them segment audiences and deliver ads that align with their interests.

Zero-party data is always a great option as the data is directly and intentionally shared by the user to receive personalized communications from the brand. Both zero and first-party data are collected with the user’s consent and are authentic sources of information that brands can rely on as they are accurate and compliant with data privacy regulations.

Other options of programmatic advertising include demographic, geographic, or device-based targeting but these don’t offer the ability to create and share relevant content to users. Zero and First-party targeting practices are also limiting as advertisers are restricted to their existing audience base. Advertisers and publishers need a privacy-safe solution that combines relevance with scale.

Contextual targeting has emerged as a front-runner in the transition to the cookieless world as it bridges the gap between relevance and scale and offers a new-age, non-intrusive solution. Looking at data beyond a user’s browsing history or leveraging third-party cookie data, contextual targeting focuses on a user’s current interests based on the content they are consuming. Without tracking a user’s browsing patterns or using alternative IDs, contextual advertising powered by AI goes beyond stereotypes and enables precise targeting. Network Level Analysis (NLA) provides real-time insights and recognizes trends that power more effective strategies by reaching the right audiences where they are.

Contextual advertising is pushing the boundaries by transcending conventional, stereotypical, and invasive practices of categorizing users based on interests and past browsing patterns that are not always accurate. Instead, the focus lies on placing ads on web pages where the on-page content and context align with the ads. This ensures the ads match the content a user is currently consuming, maximizing relevance without violating their privacy.

Built for scale, contextual targeting empowers advertisers to create custom audience categories that align with their brand based on contextual cues. It presents an opportunity to elevate to a future-proof strategy that embraces diversity and inclusivity through a more in-depth understanding of audience preferences. Contextual targeting’s ability to understand nuances and semantically interpret content also enhances brand safety and brand suitability by eliminating the display of ads beside negative or harmful content and ensuring ad placement falls in line with the overall message and tonality of the brand.

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Custom AI has become an indispensable tool for agencies seeking a competitive edge in the rapidly evolving digital marketing landscape.

Beyond its initial application in audience targeting, custom AI is revolutionizing various aspects of digital advertising, from lookalike audiences and bidding strategies to measurement and optimization. Its most profound impact, however, lies in introducing campaign objectives into automated decision-making across marketing organizations, indicating a new era in contextual advertising strategy.

While audience targeting has been a foundational application of custom AI in digital advertising, its potential extends far beyond. Forward-thinking advertisers have leveraged custom AI to guide their contextual strategies for years. As the industry moves toward a privacy-first future, this application of custom AI promises the most significant breakthroughs.

Moving beyond lookalike modeling, custom AI is unlocking cookieless audience targeting

Digital advertising has shifted from predefined audience targeting to adopting more sophisticated, custom AI-driven methods. Initially, brands relied on predefined audiences for user targeting, a necessary compromise given the technological limitations of the time. However, this approach often sacrificed accuracy for simplicity.

Lookalike modeling represented a significant leap forward, enabling brands to expand their target audiences by identifying users with characteristics similar to their specific brand audience. This technique became a staple in the toolkits of major platforms like Facebook and Google.

The latest advancement in this evolution is fully customized targeting designed for the privacy-first web.

This approach employs custom AI to build campaign-specific machine-learning models using first-party data and contextual signals. These models analyze URLs, scoring them based on their semantic relevance to a brand’s campaign brief. The result is a refined selection of content that aligns closely with the campaign’s objectives, surpassing the accuracy of standard segments.

Custom contextual AI is driving improved ad recall

A critical aspect of audience targeting with custom AI is the quality of the underlying audience data and the integrity of the matching process. A study by Truthset highlighted the reliability issues in data used for ad targeting and audience measurement. The study found that matches between hashed email addresses and postal addresses across various data providers were accurate only about 51% of the time, casting doubt on the accuracy of such audience data matches.

Several innovations underpin custom AI’s data integrity and advanced targeting capability. For example, network-level analysis (NLA) is crucial, examining the entire universe of URLs to discern content clusters, trends and semantic relationships. Content retrieval techniques scan this network, identifying URLs that align with the advertiser’s brief. A custom AI model, built and trained with this filtered content set, classifies new articles and ensures that only the most relevant ones are selected for the campaign.

The efficacy of custom contextual AI is evident in its results. For instance, Seedtag’s Affinity Index, which measures context relevancy for the intended audience and message, is typically 92% higher than scores derived from predefined taxonomies. Moreover, ads placed using this technology enhance ad/content fit by 9%, leading to significant uplifts in ad recall (22%) and message association (19%) compared to standard IAB categories.

Custom contextual advertising allows advertisers to adapt in a privacy-first environment

With the progressive loss of reach of third-party cookies, first-party data will play a more important role. However, translating this limited data into scalable marketing campaigns poses a significant challenge.

Contextual targeting, focusing on the environment of the ad placement rather than gathering information from potentially unreliable audience data, ensures relevance to the content being consumed at the moment. This approach bypasses the uncertainties of personal data matching, offering a powerful and sustainable alternative to traditional methods.

Custom contextual advertising, therefore, emerges as a key solution in a privacy-first world. It adapts to the evolving digital landscape and outperforms standardized segments, offering a more accurate and reliable method for placing ads in relevant contexts.

As the digital advertising industry grapples with signal loss and heightened privacy standards, custom contextual AI stands as a beacon of innovation, guiding the way to more effective, responsible and sustainable advertising practices.

By Chad Schulte, Senior Vice President of Agency Partnerships and Strategy at Seedtag.

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They say, a picture is worth a thousand words; holds mighty true in today’s world where the human attention span hovers around the 8-second mark. Users encounter numerous ads as they surf through the digital world, making it impossible for text-heavy formats to garner many eyeballs.

The human brain processes images 60,000 times faster than text, and 90% of the information transmitted to the brain is visual. From a human perspective, visualization works best as we respond and process it better than any other type of data. The human brain can recognize a familiar object within 100 milliseconds, and a study by MIT estimates that just 13 milliseconds are sufficient to recognize even unfamiliar images.

Marketers have access to myriad formats like full image, in-image, and videos, to garner one of the most valuable resources of the digital age, attention. Engaging visuals and succinct messaging capture consumer attention and leave a lasting impact.

Win big in the attention economy with the right blend of content and context

Nike, Apple, Budweiser, and Coca-Cola are a few brands that have nailed advertising campaigns that struck a chord and left the world talking for years. That’s the power of creativity.

Creativity plays a crucial role in capturing attention in a digital landscape where consumers are bombarded with information and messages. In a crowded marketplace, ads that are unique, imaginative, and distinctive help brands distinguish themselves and attract attention. Images or videos that are visually appealing are more likely to be shared and remembered. So, add to the mix striking visuals and innovative designs, and that’s an ad strategy that can capture attention quickly.

Contextual advertising enhances the effectiveness of capturing attention by tailoring ads to the specific context of a user's current line of interest. It leverages Artificial Intelligence (AI) to analyze the content and context of web pages, and places ads in the most optimal locations without using any third-party cookies. Since the ads align with the content users are currently engaging with, they are more relevant and personalized, thus increasing engagement.

Contextual advertising uses deep learning, computer vision, and natural language processing to aggregate insights that enable brands to target specific audiences by understanding the context in which the content will appear. Context relates to the content a user is currently consuming making ads more broadly applicable and effective than relying on individually identifiable signals.

Contextual AI can also provide contextual creatives that resonate with users and capture their attention. There are various formats that advertisers can choose from, such as in-article, in-image, and in-video. Using contextual signals, Dynamic Placement Optimization (DPO) ascertains the most suitable location to place the ads.

The power of creativity: Metrics in the attention economy

Attention metrics provide more information for quality arbitrage, and help make smarter decisions. Vendors like Lumen and Adelaide are judging the quality of media based on the probability of attention given by any person to a creative placement. While it may not be considered a media currency yet, measuring creative and placement effectiveness based on the attention amassed is a fair assessment to get insights.

Attention time is a crucial metric that advertisers are closely monitoring in today’s attention economy. Attention time refers to the amount of time a user or consumer spends actively engaged with or paying attention to a particular ad. Relevance, creativity, format, placement, etc. all have a significant impact on this metric.

Research shows that in-image ads are 4x more effective while in-video ads are 6.7x more effective in maintaining attention. Common display ads have 1.5 seconds of viewer attention as against in-image ads at 6 seconds. Regular video ads have 0.6 seconds average viewer attention while in-video ads get 4 seconds.

According to Lumen’s research, as the view time for an advertisement increases, more impressions are converted into sales. For example, an ad that was viewed for 3 seconds was converted to a sale on 50% of occasions. For brands and marketers serving ads, every second counts. Contextual ads have greater engagement rates, boost impressions and brand recall, and help build a memorable and consistent brand identity.

Leveraging consumers’ natural inclination to look at imagery and acing ad placement with context has a direct impact on the bottom line and sales numbers. In-image contextual ads get noticed 3.5 seconds faster and drive attention 3.4 seconds longer. They also have a 4x stronger breakthrough and 3.9x higher purchase intent. These numbers further rise for in-video ads.

The future of Attention Economy

Going a step further, leveraging GenAI capabilities can further strengthen contextual targeting strategies. At Seedtag, we utilized the powers of GenAI and launched a capability that gives brands and agencies the capacity to build tailored creatives based on the context of the surrounding page-level content.

With GenAI, advertisers can create more sophisticated creatives that perfectly match the context of the content in an article or web page. Our contextual AI platform’s Deep Learning, Computer Vision, and Natural Language Processing capabilities enable it to understand the desired outcome of a campaign and creates prompts to modify the original creative to optimize for the best possible outcome.

The combination of GenAI and contextual advertising will empower brands to not just create stellar creatives, but ensure that they are relevant to the context in which they’re served. By create campaign creatives that seamlessly integrate with the context in which they are displayed, brands can win the attention battle and drive better results.

Get in touch to know more about our exclusive GenAI capabilities for contextual advertising.

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Streaming services are one of the most sought-after subscriptions of the decade. The pandemic was a catalyst that boosted demand, and the number of streaming service subscriptions passed 1 billion worldwide for the first time in 2020. As of March 2023, 78% of all American households subscribe to at least one or more streaming services. With 231 million subscribers, Netflix ranks as the most subscribed video streaming service globally.

The steady rise of popular streaming services like Netflix, Amazon Prime, Hulu, and Disney+ has contributed to the popularity of Connected TV or CTV. Connected TVs have become the choice among the masses because it gives them the flexibility to connect to the internet, and seamlessly switch between traditional television and online streaming. In 2023, a whopping 88% of U.S. households owned at least one internet-connected TV device, while the number of CTV users amounted to more than 110 million among Gen Z and Millennials.

Investing in Connected TV advertising

With a constantly rising viewership, advertisers quickly began exploring CTV advertising, recognized its potential, and have been making significant investments in the past few years. In 2023, CTV advertising spending in the United States was expected to grow by 21.2% to reach 25.09 billion USD. CTV ad spend is expected to grow to 40.9 billion USD by 2027.

A seamless and convenient option to deliver ads where the masses are, CTV ads are similar to YouTube ads. Marketers can serve personalized, skippable ads to target audiences while they are streaming content on their TVs. The appeal of CTVs has grown owing to more widespread and reliable internet connectivity.

Additionally, beyond the ability to pick between traditional TV and streaming, since connected TVs are connected to the internet, they are highly versatile and support additional features. They give users access to OTT streaming, social media browsing, and watching traditional television as scheduled, delivered through streaming TV apps over the internet rather than traditional broadcast networks.

As television devices become more affordable and a variety of content becomes more accessible, the audience is naturally inclined towards having the option to take their pick and have full control over what they watch.

Marketers: Get acquainted with FAST

FAST, or Free Ad-Supported Television, refers to streaming television services that are available to viewers at no cost. So, how do they generate revenue? Simple; advertising. These platforms do not charge users any subscription fee but, similar to subscription-based streaming services, they offer a variety of on-demand content. They rely solely on advertising for monetization to support their operations.

FAST platforms typically offer a range of content, including movies, TV shows, news, and sometimes live TV channels. Advertisers pay for ad slots, and the ads are displayed during and between content streaming. This revenue supports free access to content for viewers. Some examples of Free Ad-supported Streaming TV services include Roku Channel, Tubi, Pluto TV, Crackle, Peacock, and Samsung TV Plus.

Marketers have been investing in advertising on FAST platforms because it allows them to reach a diverse and sizable audience base and a broad demographic range. Another key aspect is that it allows marketers on a tight budget to reach a large audience without spending significant ad dollars. It is a more cost-effective option when compared to expensive traditional TV advertising.

As the “cord-cutting trends” rise and more viewers shift away from traditional cable in favor of streaming services, FAST opens up new opportunities. It allows marketers to stay relevant and reach audiences on platforms where they are increasingly spending their time. Marketers can explore innovative ad formats like interactive ad experiences and sponsored content to engage viewers. Tracking campaign effectiveness is also better on FAST platforms by accessing metrics such as impressions, click-through rates, and engagement that provide valuable insights.

Making the shift to CTV and FAST

Offering a unique opportunity to meet the audience where they choose to spend a significant amount of time watching content of their choice; CTV advertising and FAST platforms present marketers with a great alternative to traditional ad practices that are pricey and stereotyped. Traditional TV ads just display ads but with CTV and FAST, brands can choose what content they want to advertise beside. This gives marketers more flexibility to align messaging and design with user interests and brand values.

• Improved understanding of viewer interests
• Ads that are non-intrusive and relevant to the current content browsed by the audience
• Messaging in line with the brand's ideas and values
• Compliant with all privacy laws as it does not leverage third-party cookies

They also offer more control and transparency, allowing marketers to have a clearer understanding of where their ads are being displayed. Thus, the newer methods help marketers elevate brand safety, brand suitability, and the overall use experience.

Let’s take an example - You are a regular on a travel channel and passionately follow a particular show that covers unique experiences in lesser-known locations. If a brand curates exclusive, personalized travel itineraries and experiences, you fall under its “ideal target consumer” category. The chances of you wanting to know more about what they do, how they do it, and possibly wanting to plan an experience are much higher. So, if you see their ad during or right after your show, you are likely to explore more.

Still in its early days, CTV and FAST are growing rapidly but come with some challenges. While significant improvements have been made, measurement and tracking of campaigns on television still have certain difficulties. Ad blocking and ad fraud also continue to be significant obstacles in CTV targeting. However, partnering with the right experts and staying tuned to updates and enhancements in the space can hugely benefit marketers. The ability to leverage the latest tech and reach a wider audience that was not accessible before unfolds newer possibilities and opportunities that brands and marketers must explore to stay on top of their game.

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There are various reasons why the audience is tired of ads today. What tops the list is the age-old practice of violating user privacy and accessing their personal data to target users as they browse the web. Data privacy has been a hot topic for a while as consumers and advocates created a lot of noise around privacy, making for governance laws like GDPR and CCPA that advertisers must comply with.

Going beyond privacy, traditional targeting strategies carry another tag - stereotypes. Fundamentally, cookie-based advertising involves collecting user data like interests, browsing, and behavioral patterns. Users are grouped into categories mostly basing the entire categorization process on assumptions, stereotypes, and third-party cookies. The results are rather apparent today - Users are left irritable as irrelevant and intrusive ads disrupt their browsing experience.

Advertisers pay a hefty price as poor audience categorization results in incorrect targeting, wasted ad dollars, has a negative impact on user experience, and damages the brand image. The world is also actively championing diversity and inclusivity initiatives, and advertising needs to level up to meet audience preferences.

Old is new: Contextual targeting

The phasing out of third-party cookies has paved the way for various “new” advertising strategies that will help navigate the cookieless world. However, a solution that dates back to the very roots of advertising has garnered the trust and interest of both advertisers and the audience - Contextual advertising.

Built on the principle that targeting remains strictly contextual, this advertising strategy truly focuses on protecting consumer privacy and helps advertisers adopt a more inclusive targeting practice. With contextual targeting, advertisers can steer clear of third-party cookies’ discriminatory practices and not limit targeting based on outdated methodologies. Instead of drawing conclusions by relying on factors like age, race, gender, location, or other such characteristics, advertisers can adopt a privacy-first strategy that enables them to display relevant ads to the most suitable audience by aligning with their real-time interests.

Women like the color pink, prefer skinny jeans, invest extensively in makeup products; the assumptions are plenty. Instead of making conjectures, it is unquestionably better if brands could show ads relevant to people based on the content they are actually consuming. Relevancy helps maximize impact.

Powered by Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) capabilities, contextual targeting presents an innovative alternative to stereotypical and non-privacy-compliant strategies. The ability to understand nuances and semantically interpret content makes contextual targeting all the more impressive as it allows advertisers to expand their horizons while elevating brand safety and suitability. Not only does contextual targeting eliminate the appearance of ads alongside negative or harmful content, but it also ensures ad placement aligns with the overall brand message and tonality.

Are you equipped to rise beyond stereotypes and dated advertising practices?

Contextual advertising empowers brands to make the most of AI-driven contextual targeting and elevate to inclusive advertising practices. With contextual targeting, half the battle is already won. You already know that the user is somewhat related to your product or service because ad placements are purely based on their current area of interest.

AI does a deep dive and analyzes the written and visual content of a web page, to understand the content and context. This analysis helps advertisers develop an understanding of what customers are browsing, their areas of interest, and how they engage and interact with content. Beyond just analyzing specific URLs that are limited to certain predefined categories, Network Level Analysis (NLA), looks at the entire universe of URLs. NLA develops an understanding of the network as a whole to understand content clusters and topics that audiences are engaging with at that moment. By appearing where a user is showing interest with an offering that aligns within that realm of interest, brands are more likely to not just convert better but win customers for life.

Like the Backstreet Boys sing, “But I want it that way…”; well, you can. Advertisers can cherry-pick who they want to target and users see only those ads that align with what they’re currently looking for. Truly inclusive and unbiased, contextual targeting is interest-based and does not profile a user based on who they are.

It’s a win-win for all parties involved, and an ideal alternative to cookie-based targeting practices.

Explore more about contextual advertising with us.

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The open web or walled gardens; an ongoing debate that has further intensified since Google’s announcement on the phasing out of third-party cookies. Before we get to what works better and what customers prefer, let’s cover the basics.

What is the open web?

Open web refers to the part of the internet ecosystem where information and resources are freely accessible to all users without any restrictions. Websites, apps, or any other online property that is not owned by a major technology company is typically categorized under the open web.

What are the walled gardens?

Walled gardens refer to closed internet ecosystems controlled by large corporations like Meta, Apple, Instagram, and Amazon without involvement from any outside organization. These big technology corporations ensure that all data, information, and technology stay within the organization, and the entity also controls user access to data, content, and services within the ecosystem.

So, what is the debate around?

For a long time, consumer trends showed a clear inclination towards walled gardens, as users spent significantly more time on platforms like Facebook and YouTube. Naturally, marketers began investing a significant part of their ad budgets in these walled gardens. However, there has been a radical shift in consumer behavior in the past few years.

According to a recent survey, 30% of people said they use Facebook less today than a year ago, while just 8% said they use the open web less than before.

What are the reasons behind this paradigm shift in consumer preference from walled gardens to the open web?

• The survey revealed the number one reason cited by consumers as lack of relevance. Across Facebook, Instagram, YouTube, and Amazon, consumers felt the content displayed on walled gardens was not as relevant as it used to be before.
• Another factor that marketers should pay heed to is the consumers’ state of mind. Consumers said they are more likely to be “zoning out and not paying attention” when browsing walled gardens.
• Transparency is another factor that consumers stated when referring to content like news on walled gardens.

Thus, the open web is increasingly becoming the preferred choice among today’s consumers. According to the survey:

• 48% of consumers spend more than 1 hour browsing the open web, while walled gardens stand at 30%.
• Consumers are 4x more likely to say they will increase their open web usage over the next 12 months than decrease it, compared to both Facebook and Instagram where they said they will decrease usage.
• People are not just spending more time on the open web. The majority are also “curious and in a mood to learn more” making it an ideal place for advertising.
• 74% of people said they trust articles on news sites or apps more than walled gardens, and that they turn to the open web when looking for high-quality content.
  

The advertising landscape: Open web vs. Walled gardens

Ad budgets have been flowing into walled gardens for years now, but there seems to be a clear misalignment. With the audience revealing where their interests lie, marketers need to reevaluate their strategies. The change in audience preferences could be the reason certain campaigns don’t perform like they used to or content does not receive the same traction as it did in the past.

Marketers and brands must be more watchful of where their ad dollars are being spent, if campaigns are meeting their objectives, and what returns they are giving to brands. Today’s consumers are spending more time on the open web than walled gardens and this shift is only going to continue to widen in the coming days, putting an end to the walled gardens monopoly.

Why are marketers moving beyond walled gardens?

With the demise of third-party cookies expected to occur in 2024, marketers are exploring alternatives to walled gardens to diversify their advertising strategies and reduce reliance on closed, proprietary platforms. Also, as consumers shift their preferences, it is but obvious that marketers must relook strategies and advertise where their consumers are.

Some of the factors that are driving marketers away include:

• Marketers don’t get full visibility into their campaign performance or customer insights because these platforms keep the granular data to themselves. This takes away the opportunity for brands to dive into the details and gather more meaningful insights that can help fine-tune campaigns and improve customer engagement. Restricted access to user data and lack of transparency hinders effective audience targeting and analytics.

• The need to comply with data privacy laws has further tightened the ropes around data collection and usage, increasing the challenges within walled gardens.
• The closed ecosystem limits marketers’ visibility into ad fraud and brand safety concerns.
• Competition for ad inventory and the closed nature of walled gardens make advertising more expensive.
• These closed ecosystems limit opportunities as they restrict access to marketing content within the ecosystem and only target consumers who are active users of the platform.

Consumers are more actively exploring the open web as it provides a wider range of choices, access to varied content, and diverse opinions and viewpoints. It also gives users greater control over their online data privacy.

Striking the right balance

Consumers’ shifting preferences and marketers’ hunt for alternatives have put the spotlight back on contextual targeting. Contextual advertising is becoming one of the most sought-after targeting strategies that empower marketers to create more effective campaigns. It allows marketers to display relevant ads to the desired audience by analyzing the content and context of web pages.

Contextual ads enable brands to provide a better user experience by creating a non-intrusive campaign that does not hamper the browsing experience of consumers. AI and ML models analyze millions of web pages to determine the content that best aligns with a campaign’s messaging and context, thus placing creatives in the most optimal locations without leveraging any third-party cookies. Since the ads are based on the content of the web page being viewed, contextual targeting ensures that the ads are relevant to what users are currently interested in.

Unlike the limitations of walled gardens, contextual advertising guarantees transparency. Marketers can deliver relevant ads without needing extensive user profiling or personal data, addressing privacy concerns and regulatory restrictions. With more control over where the ads appear, contextual advertising also promises the highest levels of brand safety and suitability.

Our joint research project with Havas and Kia revealed a 70% view rate for contextual ads vs. 64% for cookie-based ads, a 43% increase in brand awareness as against cookie-based ads’ 18%, and 29% higher digital ad recall.

Explore our contextual AI solution that is built to power new-age, privacy-first advertising strategies.

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Generative Artificial Intelligence or GenAI shines bright as the ‘it thing’ of this decade. GenAI goes beyond traditional Artificial Intelligence (AI) tasks like classification or prediction, and has the ability to create original content like images and text.

The growth of genAI tools has been explosive in the past year and the latest McKinsey Global Survey revealed that organizations are using genAI regularly in at least one business function.

The survey further revealed that nearly 25% of surveyed C-suite executives are personally using genAI tools for work. While more than 25% of respondents from companies using AI said genAI is already on their boards’ agendas. 40% of respondents said their organizations will increase investment in AI overall because of advances in genAI.

In the AI adoption race, organizations exploring genAI capabilities in conjunction with traditional AI are further ahead, have the first mover’s advantage, and are reaping more benefits. The ever-evolving adtech landscape is leaving no stone unturned in making the most out of genAI to level up.

How is the adtech landscape leveraging the latest in AI?

GenAI unlocks a whole new world of opportunities by providing creative assistance that enables marketers and advertisers with data-backed creative assistance to be more efficient and deliver more impactful campaigns.

From text and creatives to ads and marketing, the evolution of AI and the adoption of next-gen AI models like ChatGPT by Open AI, Bard by Google, and Microsoft Bing is creating huge waves of change and opening doors to never-seen-before possibilities.

This marks the beginning of a new era that is transforming the future of work by bringing together the power of human and artificial intelligence.

AI can assist through the entire process from research to content generation and distribution. It can expedite the creative process by suggesting design elements, layouts and color schemes, and help create more suitable ad copies, product descriptions, and marketing content.

What are the benefits of leveraging Generative AI in advertising?

Adopting genAI can help advertisers save time and resources by enabling them to produce content faster and with ease. By enhancing various aspects of advertising campaigns and strategies, genAI can have a significant impact on the adtech landscape.

The capabilities and use cases of genAI in advertising are vast:

• Produce large volumes of high-quality content across formats like text, image, and video, with ease.
• Analyze customer data and create personalized ad campaigns that have higher engagement and conversion rates.
• Help advertisers in the creative process by suggesting ideas that inspire them to explore newer avenues, and curate fresh, innovative campaigns and messaging.
• Easily create multiple ad variations, simplify A/B testing, and boost ad performance and ROI.
• Explore vast datasets, evaluate, and derive takeaways on key aspects like customer behavior, preferences, and market trends.
• The ability to hyper-personalize at scale using the learnings from AI.

The fusion of Contextual Targeting and GenAI: Fueling new-age advertising strategies

AI is no replacement but an assistant for humans to do more, better, and faster. The two big factors that are currently ruling the adtech landscape are Contextual and Generative AI.

What if you could bring the two together? Imagine the magic that can be created by capitalizing on these two revolutional tools?

Here’s how we leverage the two at Seedtag and enable brands to reap maximum benefits:

• Our proprietary AI-powered contextual technology, Liz©, has the ability to analyze and comprehend expansive volumes of written and visual content to derive insights that help determine the best place to place an ad that will resonate with customers.
• Our GenAI capabilities leverages the learnings from Liz© to provide more relevant creative inputs on colors, image elements, and text to further enhance the quality of the ads.

Advertisers and creative agencies are using the best of AI and contextual advertising to curate strategies and generate content that perform better than the conventional ones.

Contextual targeting primarily addresses the big concern of privacy and enables advertisers to make data-driven decisions, and reach their target audience without leveraging any third party cookies.

The intelligence from the analysis then enables generative AI in the creative process and empowering advertisers to work more efficiently and create more engaging and personalized campaigns.

While AI empowers customers with data to drive decision making, genAI uses these data points to understand patterns and create new content like text and images. The new content created by genAI is data-backed and hence more capable of identifying elements like the best keywords, colors, and images to use for a particular campaign. The two complement each other and power more effective ad campaigns by elevating brand messaging and creatives.

Benefits for advertisers

When used together, they allow advertisers to:

• Produce high-quality, contextually relevant content by analyzing the context of a webpage or app and generating ad creatives that match the content and context of the page.
• Generate personalized and contextual ad messaging based on a user’s current search or area of interest.  
• Analyze the content and context of web pages or apps to identify relevant keywords and phrases that can be used to better target ads to specific content categories or topics.
• Optimize ad copy to match the context and language style of the content it appears alongside.
• Create narratives that align with the content and context ads appear alongside, and adapt ad content in real-time based on changing contextual factors.

Applying Contextual Targeting practices coupled with GenAI capabilities: The business impact

Developing a strategy that incorporates gen AI into contextual targeting strategies can help brands deliver more relevant and engaging ads to their desired audience. It allows them to align their advertising efforts by ensuring ads seamlessly integrate with the surrounding content and context, making it less intrusive and more engaging.

Using the duo together forges a much stronger strategy that offers myriad benefits:

• Copies and creatives generated by integrating gen AI and contextual targeting are more optimized and relevant. Thus, they garner more attention, increase click-through rates, improve ad performance, and channel a better user experience overall.
• The pair reinforces brand safety and suitability by ensuring that brand elements and messaging remain consistent across ad creatives and text. Content generated is contextually relevant and reflects the brand’s identity while avoiding ad placements on websites or apps with inappropriate or controversial content.
• Contextual targeting with gen AI can boost ROI on advertising spends by optimizing ad creatives, messaging, targeting, and placement.
• The combination can also protect brands from ad fraud by ensuring ads are displayed only on relevant and desired web pages and apps.

On the whole, using contextual targeting and gen AI in tandem enables brands to derive more value, gives them a competitive edge, and helps them future-proof their business. Advertisers can curate more personalized experiences that customers love and engage with, which in turn increases customer satisfaction and brand loyalty.

Early adoption of gen AI in integration with contextual targeting will enable brands to develop strategies that not only give a competitive advantage but help them adopt tech that is integral in the advertising space. It is an opportunity to level up and better position themselves in the ever-changing landscape for continued success.

Explore our contextual AI solution that is built to provide brands a premium advertising approach. To know more, get in touch.

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Connected TV (CTV) advertising is a rapidly growing segment within digital advertising, enabling brands to reach specific audiences through internet-connected devices. But what is CTV advertising? It refers to the delivery of video ads on smart TVs, gaming consoles, and other devices connected to the internet. Unlike traditional linear TV advertising, CTV offers precise audience targeting, allowing advertisers to measure the effectiveness of their campaigns with advanced analytics.

Internet-connected devices like Smart TVs have become one of the most sought-after products in the last decade. Access to OTT video streaming has become a must-have, especially among the younger generations.

Statista's 2023 research revealed that 92% of US households were reachable by CTV programmatic advertising, while Gen Z and Millennial CTV users amounted to more than 110 million.

With the rapid change in opting for CTV experiences over linear television and the solid foothold OTT platforms have gained globally, advertisers have quickly noticed the digital migration, putting advertise on CTV targeting in the spotlight. Despite the slowdown triggered by the pandemic, the research reported that CTV ad spending in the United States increased by 33% in 2022. The latest projections suggest that the expenditure will more than double and surpass USD 38 billion by 2026, accounting for more than 5% of US ad spending.

CTV targeting: For the new era of television

With a higher viewership, increased streaming time, and higher revenue numbers; the explosive rise of CTV and OTT services has powered an evident shift in advertising spending. Revenue in the OTT Video segment is projected to reach USD 315.50bn in 2023, with OTT Advertising being the most prominent segment having a market volume of USD 206.90bn in 2023. A report suggests that nearly 50% of marketers would spend more on CTV targeting if they had high-quality first-party data to back their targeting strategy.

Like most other new areas of advertising, CTV targeting has its challenges.

• Since it's a relatively new ad space, there are a lot of knowledge gaps. This makes it harder to get organization buy-ins and budgets for exploration. Additionally, audience fragmentation across platforms and devices makes audience targeting tougher.
• Measurement and tracking of campaigns on television have always been challenging. With CTV involving multiple devices, how can marketers track campaign performance or measure the effectiveness of your campaigns to understand if the ads reach the desired specific audience? The lack of standardized measurement makes it hard to evaluate the effectiveness of campaigns.
• Ad blocking and ad fraud continue to be significant challenges in CTV targeting.
• With access to limited audience information like demographics and geography, audience targeting poses a challenge. Marketers need access to audience data to create effective CTV campaigns that deliver ads to the right audience.
• Limited ad inventory makes quality and scale difficult, as limited spots are available during peak viewing times.

Contextual advertising and CTV targeting

A strategy that is purely driven by the analysis of content and context, contextual advertising can enable marketers to overcome these challenges and enhance advertise on CTV strategies. Unlike behavioral targeting, which requires audience data to aid CTV campaigns, contextual AI focuses on targeting audience segments by placing ads alongside relevant streaming content that aligns with the audience's interests.

For example, contextual advertising can enable sports and fitness equipment or apparel brands to target viewers interested in live sports and sports-related shows. The video ads displayed are relatable and lie within the viewer's realm of interest, increasing visibility and reducing the possibility of showing the ads to viewers who are less likely to be interested in the product.

Additionally, advertisers can leverage gaming consoles as another prime avenue for advertising on CTV. Many modern gaming consoles support streaming services, allowing advertisers to reach a younger, highly engaged audience that frequently consumes video content on demand. This expands the reach of CTV advertising beyond traditional smart TV users and into the growing gaming community.

One of the key advantages of connected TV advertising is its ability to track video completion rate effectively. Since viewers are more likely to watch an entire video ad on CTV than on other digital platforms, advertisers can ensure that their messaging is fully delivered. This metric is crucial for measuring engagement and understanding how effectively an ad influences a viewer's decision to purchase after viewing an ad.

The future of CTV advertising

Advertise on CTV is promising, with advancements in AI and machine learning enabling even better ad placements and audience segmentation. As more brands invest in OTT advertising and fine-tune their CTV campaigns, the industry will see improved ROI and deeper insights into viewer behavior. Marketers who adapt early and integrate CTV advertising into their digital strategies will gain a competitive edge in reaching highly engaged audiences.

Contextual advertising-backed CTV targeting is more effective than demographic or geography-based targeting. It allows brands to render ads to viewers who are more likely to have a genuine interest in their products or services and not just show ads based on age or location.  

With this, marketers also elevate brand safety, brand suitability, and user experience -

• Improved understanding of viewer interests
• Ads that are non-intrusive and relevant to the content being viewed by the audience
• Messaging in line with the brand's ideas and values
• Compliant with all privacy laws as it does not leverage third-party cookies

CTV advertising is building future-ready strategies and brands are already leveraging it to steer ahead. Have you explored CTV targeting yet?

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Phasing out of third-party cookies, brand safety and brand suitability, privacy laws, and changing customer preferences are among the top factors that have brought the spotlight back on contextual advertising in the global ad tech landscape. Contextual ads are increasingly becoming the preferred choice among advertisers, publishers, and customers today.

A factor that plays a key role in helping brands reach their desired target audience is the audience selection process. An audience refers to a group of people with similar interests and shared characteristics. This crucial element helps brands reach the right individuals who are most likely to be interested in their product or service.

Traditionally, audience categorization is a process where people are grouped based on their interests and past behavior patterns. This method is limiting because it tends to group individuals based on stereotypes, and relies on third-party cookies. Poor categorization of personas can have a negative impact on marketing efforts and campaigns as the categories are not 100% accurate, resulting in incorrect targeting and wasted ad dollars.

We live in a world that is embracing diversity and inclusivity with open arms and actively steering away from stereotypes. Brands looking to level up their advertising game need to keep up with the changing times and better understand audience preferences.

What if they could go a step further with their targeting strategies?

What are Contextual Audiences?

Contextual advertising focuses on placing ads on web pages where the on-page content and context align with the ads. Contextual audiences refer to individuals who are identified and grouped based on their online behavior and the context of the content they are currently engaging with.

At first glance, contextual audiences may seem very similar to the traditional audience categorization process where people are grouped based on their interests. However, the key differentiator is that contextual audiences do not leverage any personal data, and create audience groups solely based on contextual cues.

Instead of using the most common and typical way of grouping individuals based on personal information, contextual audiences use the power of context to group people. Contextual audiences ensure scalability, privacy adherence, and greater precision, making it a method ideal for the post-cookie world.

What challenges do Contextual Audiences solve for customers?

Contextual audiences are a targeting capability that enables brands to ace audience segmentation and targeting by displaying ads that are most relevant to them.

• With the deprecation of third-party cookies and the implementation of tighter data privacy laws, brands need a solution that empowers them to reach the desired target audience.
• Consumers have raised concerns about data privacy and do not want to be tracked or are already untrackable. In a world that puts data privacy on the front seat, this targeting capability is a great way to deliver relevant ads without violating privacy.
• It is also a great way to reach out to the most relevant customers with ads that better align with their real-time interests, using the right message, and displaying them at the right time.

Go a step further with Seedtag Contextual Audiences

The conventional way brands understand their audience does not work anymore as they are built on stereotypes, clichés, and non-privacy-compliant strategies. Contextual audiences can help brands find a diverse, inclusive, and relevant audience base using privacy-first technology.

Seedtag Contextual Audiences can help customers do all of that and more! Crafted using Custom AI, contextual categories, images, and cookieless sociodemographic models, our contextual audiences evolve from customer input and diverse market research.

Powered by Liz, our pioneering AI technology, Seedtag Contextual Audiences are built to deliver audiences that are unique and dynamic to suit specific business needs. Using AI models, our contextual audiences create a comprehensive network that generates audience categorizations that are relevant to a brand, whilst respecting consumer privacy.

Types of Contextual Audiences

To empower brands with our unique, AI-powered targeting capabilities, Seedtag offers three types of audiences:

• Signature Audiences: These are audiences defined by Seedtag and backed by insights provided by Liz, panelists, and research data. Brands can seamlessly activate pre-defined and tested audiences with clear interests and attitudes toward their products. Signature Audiences provide very accurate results with room for a certain degree of customization to better suit brand needs.

Examples: ​​Luxury Car Enthusiasts, Adventure and Outdoor Enthusiasts, and Environmentally Conscious Consumers.

• Off-the-shelf Seasonal Audiences: Similar to contextual audiences but more focused on a particular event in time, this type has a clear start and end date for activations, and takes advantage of interest spikes throughout the year.
  Examples: Black Friday sale, Earth Day awareness, and F1 Grand Prix season.
• Custom Audiences: These are one-of-a-kind audiences engineered to help brands solve specific challenges. As the name suggests, this goes beyond the pre-set audiences, leverages the targeting capabilities of Liz, finds exactly where the users are, and creates a tailor-made audience targeting strategy.

What sets Seedtag´s Contextual Audiences apart from regular audiences?

Traditional audience targeting methods typically leverage cookies, and the audience categorization is based on stereotypes. This contributed to the increase in the popularity of contextual targeting methods which are interest-based. It targets the most relevant users at the right time with content that aligns with their current mindset.

However, even contextual targeting cannot solve every challenge and it has its limitations when it comes to scale. Seedtag contextual audiences go beyond these limitations and provide a targeting capability that is cookie-free, flexible, accurate, and precise.

Seedtag's contextual audiences are future-proof, thoroughly tested, built for scale, and backed by advanced AI models. The audiences are constantly updated using our network analysis capabilities to optimize targeting precision and meet KPIs. With Custom AI, our targeting capability offers unique audience definitions and real-time improvements.

We partnered with Metrix Lab to evaluate the effectiveness of our custom AI in delivering precision at scale to unique target audiences. The research revealed that using custom AI, which is the backbone of our contextual audiences, affinity went up by 92%.

• Seedtag’s Custom AI model allows brands to craft unique contextual territories based on the audiences’ interests.
• Our technology goes well beyond classic contextual technologies. We leverage external and internal innovation in the AI ecosystem to bring new capabilities like contextual audiences that go beyond standard taxonomies. For example, curating a campaign targeting automotive enthusiasts or city drivers and urban commuters.  
• Brands can create unique, tailored audiences without any dependencies on cookies.
• Our targeting capability is constantly evolving and improving as it is based on real-time data from our network.
• It enables brands to engage with users at the most optimal time by effectively delivering personalized and optimized experiences.

Contextual audiences by Seedtag are advanced and garner users by capturing their attention at the ideal moment, without relying on cookies. It also addresses the reach and scalability issues that many brands currently face and is a flexible solution that goes beyond rigid taxonomies or stereotypes. The unique targeting capability fueled by AI offers greater precision and helps achieve higher accuracy when compared to traditional targeting practices.

Get in touch with us to know more about our latest targeting capabilities powered by AI models.

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