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In recent years, the digital advertising industry has come face to face with a barrage of new policies and regulations. With concerns mounting over data privacy, consumer protection, and AI, new laws have sprung up at a variety of levels—from state, to federal, to global. This regulatory frenzy underscores a complex balancing act between commercial interests and consumers’ needs.
Consumers accept ads’ presence in our digital ecosystem, with 95% saying they would prefer ads to paying higher costs for an ad-free online experience. A further 88% say they want ads that are personalized to their interests and needs—personalization that is largely dependent on the personal information that consumers do (or do not) share.
However, that being said, there is still a strong desire among consumers and regulators alike for increased transparency and consent around data collection and usage that’s built upon deep distrust of companies’ data practices, with 81% of Americans saying they are concerned about how companies use the data they collect about them and 67% admitting they have little to no understanding of what those companies are doing with that data once they collect it.
Advertisers, then, are faced with a daunting task: Prioritize consumer privacy and adapt to new and ever-evolving regulation, while simultaneously delivering personalized digital advertising experiences that resonate with audiences.
This challenge was at the forefront of conversations at the IAB’s recent Public Policy & Legal Summit, where industry leaders explored this juxtaposition and shared critical considerations for advertising teams. Whether in discussions around bias in AI, presentations on state-specific privacy legislation, or conversations on how to address kids’ safety online, navigating this complex landscape demands not only attention, but conscious action.
While federal regulation has remained largely in limbo, there’s been a flurry of enacted legislation at the state level. In 2023, new consumer data privacy acts took effect in California, Connecticut, Colorado, Utah and Virginia. By early 2026, the number of state-level laws will grow to 14 states.
In the absence of a federal framework, advertising teams are left with a patchwork of regulation—and one that varies significantly from state to state. These laws range from relatively baseline (for instance, VCPDA), to enhanced (like the Colorado Privacy Act), all the way to business-friendly (such as the Utah Consumer Privacy Act).
With such significant variation, a one-size-fits-all approach will not suffice. Many advertisers have attempted to find the strictest regulation—namely, California’s regulation, the CCPA and CPRA—and simply adhere to that in the hopes it will cover all their bases. However, regulation is evolving so rapidly—and there are many different types of consumer data—that trying to find and adopt the “strictest” laws will likely hinder teams and create self-imposed limits where they are not necessary. Instead, those organizations that prioritize flexibility, bolster their legal and technical teams, and take the time to truly understand these different policies and regulations will be most well-positioned for success.
Generative AI was, unsurprisingly, another major topic of conversation. The technology has garnered significant attention since its public debut in late 2022, generating considerable buzz within the digital advertising ecosystem. However, its oversight and regulation pose challenges, given the rapid pace at which this technology is evolving and becoming accessible.
Though the US has yet to enact widespread laws governing its use, President Biden signed an executive order in late 2023 aimed at addressing the “safe, secure, and trustworthy development and use of Artificial Intelligence.” Additionally, the House introduced a bill that would create a commission to spearhead AI regulation.
Despite a lack of codified regulations, FTC leaders shared a few primary focus areas that should be top of mind for advertising leaders as they navigate AI. First, they encouraged teams to conduct AI-focused risk assessments and to ask their vendors to do the same, so that they can evaluate and mitigate any potential risks, such as privacy, security, or bias. They also flagged that advertisers need to be particularly attuned to the risk of bias in AI, since the data and content these models are trained by is generated by humans—and humans, inherently, have biases. Though these tools can prove useful across many aspects of digital advertising, it’s crucial that they be consistently and critically evaluated.
As the technology continues to develop, regulators are certain to prioritize its oversight to ensure that AI is employed in ways that safeguard human safety and prioritizes trust.
Regulation of the advertising industry appears to be focused on simultaneously protecting consumer privacy and ensuring their safety and security online. But regulators are also using these laws to address larger societal risks and issues that inevitably arise in an increasingly digital world. This convergence of privacy, trust, and safety was a major theme throughout the summit, and advertisers must recognize the significance of this overlap as they navigate today’s complex regulatory landscape.
The balance of power around user data in marketing appears to be swinging away from corporations and toward consumers, and companies will be well-served to take notice and act accordingly. Take, for example, the FTC’s recent action against Amazon: The agency’s complaint relates specifically to consumer data, but it goes beyond standard privacy protections and accuses the company of using data to manipulate people into unwittingly spending more than they intend, alleging that Amazon’s “manipulative, coercive, or deceptive user-interface designs known as "dark patterns” essentially “trick” customers into auto-renewing their Prime subscriptions.” The move indicates a new regulatory outlook where protecting consumers’ data isn’t enough, and companies must also ensure that data isn’t being used in a way that harms consumers or goes against their best interests.
This shift in power between consumers and corporations is also evident in regulators’ approach to children’s data—a particularly pressing issue, given that one in three internet users globally is a child under 18 years old. Marketing leaders must remember that kids’ data is, inherently, sensitive data, and that there are strict regulations aimed at safeguarding both this data and the kids themselves. This has been especially evident in social media, where regulators are concerned not only with the collection of children’s user data, but also the digital environment that data is subsequently used to create. Social media algorithms, in particular, have come under fire for their role in increasing mental health concerns, with some states passing legislation aimed specifically at restricting algorithms that target young users.
The FTC has also proposed changes to the Children’s Online Privacy Protection Rule (COPPA) that would shift the onus from parents to providers for ensuring that all digital spaces are safe and secure for children. Though only recommended changes at present, the rules can serve as useful guidelines as advertising teams consider how they’re collecting, storing, and using kids’ data to create experiences for these users online.
Navigating ever-evolving regulation can be challenging, though there are certain strategies that can help.
First, advertising teams should constantly assess their relationships with vendors and third-party partners and review the processes they have in place to ensure they’re meeting all necessary laws and regulations. The IAB recently launched a new tool called the IAB Diligence Platform, which aims to guide these assessments by sharing a set of standardized privacy diligence questions for professionals across the digital advertising industry.
It also helps to have a strong legal team that can stay abreast of new regulatory developments and craft internal guidance and best practices. When regulations inevitably change, these legal teams can assess the implications for your organization, compare them with existing protocols to develop updated guidance, and share these changes in a way that is clear, consistent, and accessible.
Additionally, marketing and agency leaders should invest in internal training and education to ensure teams' compliance with any new rules or regulations. Leaders should ensure they establish clear communication channels to relay regulatory changes affecting their teams, conduct thorough briefings on updated legal guidance and clearly outline the implications of these changes for day-to-day operations.
Advertisers should also be deliberate when selecting vendors and partners to ensure they share similar values and priorities around data privacy and regulatory adherence, but organizations cannot simply rely on their vendors and assume that they’re checking all the boxes when it comes to adhering to regulations—all of this is a shared responsibility, and teams that acknowledge and embrace that can meet today’s regulatory demands proactively and effectively.
In today’s complex digital ecosystem, prioritizing consumer privacy and safety isn’t simply a best practice—it’s a necessity. Balancing consumer data privacy and online safety with the delivery of personalized advertising experiences poses a unique challenge. However, by staying informed on the latest regulation and legislation, maintaining flexibility, and committing to making decisions centered around consumer needs, advertising teams can cultivate trust while still delivering tailored messaging that resonates with their target audiences.
AI remains the pivotal topic of conversation across the world of business—from Wall Street, to board rooms, to sales pitches, to paid media.
In the advertising world, AI has already been at work for over a decade, powering programmatic advertising and optimizing media buying across the open internet. Today, new developments from the realm of generative AI (GenAI) are set to revolutionize the landscape even further.
As agencies and CMOs navigate these new opportunities, their leaders must balance two directives: First, embracing AI tools to increase efficiencies, grow revenue, and stay at the cutting edge of innovation. And second, protecting their businesses from the threats that come along with these tools. It’s a fine line to tread, but leading organizations are finding ways to approach these new technologies so that they benefit their businesses and bottom lines while minimizing liabilities.
To do this, advertisers must thoroughly understand the risks posed by AI. The most significant ones fall into three main categories: brand safety concerns tied to GenAI-created misinformation, considerations around how AI-generated advertising will land with a consumer base that’s largely wary of AI, and potential legal risks to agencies and brands related to data privacy and deceptive advertising practices.
Industry leaders must grow increasingly knowledgeable on these topics and develop best practices, processes, and skillsets across their teams to ensure any forays into new AI-driven advertising tools are safeguarded against risk.
AI offers many promising benefits for advertisers, from cost efficiency to speed to ease of launch. However, those advantages also come with some significant brand safety concerns. It’s important for advertisers to understand these threats, implement safeguards around their use of AI, and stay up to date on this quickly developing landscape in order to make the most of these tools and solutions without opening themselves up to consumer backlash and wasted spend.
Generative AI is one of the biggest drivers of brand safety concerns, with 99.5% of industry professionals believing that GenAI poses a brand safety and misinformation risk to marketers and advertisers. GenAI technology is not perfect, and these tools have regularly demonstrated a tendency to produce content that’s, at one end of the spectrum, low-quality and likely ineffective for advertising, and, on the other end of the spectrum, inaccurate or offensive.
Two particular areas of concern include generative AI’s tendency to make up false information (also known as “hallucination” in the AI world) and indications of biases in AI-generated content (due to large language models relying on human inputs and human-generated content, which often contain biases).
These concerns were on full display earlier this year when Google had to suspend the image-generating capabilities of its Gemini chatbot, which is integrated into Google’s advertising tools, after it produced historically inaccurate images—specifically, Gemini created images of “multi-ethnic Nazis and non-white U.S. Founding Fathers”. The controversy demonstrates how developers are still learning how to program these technologies to effectively avoid bias: Gemini was programmed to avoid racial and ethnic bias, which, ironically, backfired when the images in question ended up being inaccurate.
Of course, this doesn’t mean that advertisers should forego the efficiencies offered by GenAI. However, it’s critical that teams understand the risks and put proper safeguards in place to minimize their likelihood.
“If teams are thoughtful in reviewing the outputs, then using AI to repurpose existing creative or develop elements of media assets should be fine,” says Molly Marshall, Client Strategy and Insights Partner at Basis Technologies. “But AI can’t currently replicate the creative process in terms of identifying a strong insight and developing creative that meaningfully relates to a target consumer, so AI-generated creative should complement and iterate upon an existing strategy, not wholly develop it.”
Generative AI has also prompted some additional headaches for brands that have started using AI-powered chatbots to streamline and personalize customer service on their websites. The technology promises to transform the customer service industry; however, upon testing chatbots offered by TurboTax and H&R Block, reports found that the chatbots offered inaccurate information “at least half of the time.”
“Chatbots offer brands a big opportunity to streamline communication with customers, especially as brick-and-mortar stores close and more customer service is going virtual,” says Marshall. “But the potential damage from chatbots that share inaccurate information may outweigh those benefits for some brands.”
Advertisers will also need to prepare for the ways generative AI is infiltrating content across the internet. One report estimates that by 2026, a whopping 90% of online content will be generated by AI.
Generative AI is already making it easier for bad actors to create MFA sites filled with low-quality content, misinformation-filled pages strategically developed around key search terms, and other content that could pose significant risks to brands that run ads alongside it. As a result, advertisers will need to be more deliberate around their ad spend and put new guardrails in place to avoid waste.
Programmatic advertisers, in particular, will need to seek out solutions that help steer their dollars away from MFA sites and other brand unsafe environments. Brands are already spending a reported 15% of their programmatic budgets on made-for-advertising websites (MFAs). Advertisers will need to “react in real-time to block misleading sites and keywords,” says Marshall, and should embrace technological solutions like MFA block lists to help minimize the risk. Agencies and brands may also eventually need to develop teams who work specifically to deal with fake content like misinformation and disinformation, in order to protect their spend: Gartner predicts that by 2027, 80% of marketers will have developed “content authenticity teams” to serve this purpose.
Advertisers will also need to balance their own enthusiasm around AI with a consumer base that isn’t quite so excited. While 77% of advertisers have a positive view of AI, the majority of consumers don’t trust the technology: A 2024 report from the Edelman Trust Institute found that US consumer trust in artificial intelligence has fallen by 15% in the last five years, from 50% to 35%. On a global scale, respondents were nearly two times more likely to say that innovations like AI are “poorly managed” by businesses, NGOs, and governments than they were to say that those innovations were well managed—a sentiment shared across income, generation, and age.
These opinions don’t necessarily mean that advertisers should stop embracing those AI-led tools that work for them—especially considering that AI has effectively driven behind-the-scenes advertising features such as machine learning, algorithmic optimization, bid multipliers, and group budget optimization for some time now.
What it does mean is that leaders need to be cognizant of consumer sentiment toward AI, and to act accordingly. This could include informing consumers about how AI is used in a client or stakeholder’s marketing efforts, via a social media post or a dedicated page on their website. Brands may also opt to disclose when an ad or content is generated by AI. While only about half of ads generated by AI are currently identified as such, adding disclosures can lead to a 47% increase in the appeal of those ads, a 73% increase in the trustworthiness of those ads, and a 96% jump in trust for the brands behind them.
Data privacy is also top of mind for consumers, with 68% of global consumers feeling either somewhat or very concerned about their digital privacy, and 57% agreeing that artificial intelligence is a significant threat to their privacy. Organizations can gain consumers’ trust by offering transparency around how they safeguard their customers’ data, and by prioritizing partnerships with privacy-focused organizations or gaining voluntary certifications like SOC 2 compliance that indicate a commitment to data security and ethical data practices.
Leaders who prioritize this type of transparency can develop stronger, more trust-based relationships with their consumer base—which may provide a key competitive edge in a competitive environment.
Finally, there are a variety of legal concerns advertising leaders must account for as they adopt new AI tools. Artificial intelligence has advanced more quickly than legislators can keep up with it, but there are a variety of regulations that have been introduced in the US and beyond that aim to mitigate the threats posed by AI. At the same time, advertisers must ensure compliance with existing legislation to avoid hefty fines and other legal consequences.
As advertisers grapple with the deprecation of third-party cookies in Chrome and wider issues surrounding signal loss, AI has emerged as a powerful tool for enabling privacy-friendly personalized marketing.
AI can enable lookalike and predictive audiences based on first-party data, and generate a variety of data-based insights to help advertisers better understand their audience and their consumers’ path to purchase. Advertisers are already starting to embrace these tools as a way of making up for the loss of cookies and other factors impacting signal loss.
At the same time, AI technologies can pose some data privacy-related risks. Many AI-powered advertising solutions use personal data to fuel their machine learning algorithms, and depending on the tool itself, there’s some ambiguity around where exactly all that data comes from, where it’s stored, and who can access it. What’s more, some artificial intelligence tools leverage the data they collect to deduce sensitive personal data such as location, health information, and political or religious views.
To ensure the ethical use of consumer data and to protect their businesses from legal consequences, advertising organizations must thoroughly vet any data-focused vendors or tools to ensure their data gathering, processing, analyzing, and storage systems comply with digital advertising regulations—and, of course, ensure their own data systems comply as well. Leaders must also stay on top of new AI- and data privacy-related regulations as they take hold, as this is an area that will likely see a lot of regulatory activity in coming years.
Another area of legal concern for advertisers relates to the Federal Trade Commission (FTC), which is responsible for safeguarding US consumers from unfair or deceptive advertising practices. Last year, Chairwoman Lina Kahn wrote that the commission is paying special attention to AI’s potential to advance unfair and deceptive advertising practices, stating that “Although these tools are novel, they are not exempt from existing rules, and the F.T.C. will vigorously enforce the laws we are charged with administering, even in this new market.” This sentiment goes along with the FTC’s prior commitment to protecting US consumers from dark patterns, or design techniques that can manipulate consumers into purchasing an item or service or providing personal data (and which can be created and enhanced via AI). On the state level, the Colorado Privacy Act and the California Privacy Rights Act (CPRA) have also outlined regulations around dark patterns in advertising.
Lastly, advertisers need to pay close attention to any ownership- and copyright-related legal concerns around AI-generated content.
While AI-created content currently cannot be copyrighted, the US Copyright Office has initiated an agency-wide investigation to “delve into a wide range of (copyright-related) issues” created by the popularization of GenAI tools. Leaders will need to stay on top of any developments in this area to ensure compliance as more legislators and regulators refine rules around the ownership of AI-generated works.
Overall, advertising leaders must make it a priority to understand how current regulations apply to AI, and to stay on top of new regulations as they take hold. Enlisting a solid legal counsel or team will be key to navigating the complexity of this arena.
By investing the time in advancing their teams’ AI-adjacent knowledge and skillsets now, leaders will set their organizations up for success as the technology becomes increasingly prevalent throughout digital advertising. The sooner advertisers learn how to implement and take advantage of these tools in a discerning and ethical way, the greater their competitive edge will be over those who procrastinate.
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Want to learn more about how advertisers are approaching GenAI? We surveyed over 200 marketing professionals from top agencies, brands, non-profits, and publishers to better understand advertiser sentiments around GenAI, as well as how they’re leveraging GenAI tools in their work. Check out the top takeaways in our report, Generative AI and the Future of Marketing.
What’s new in the realms of paid search and social media? This month, Jess Kaswiner, Director of Social Media Investment, and Nick Tuttle, Director of Search Media Investment, compiled all the latest news, trends, and resources that advertising pros need to know.
THE NEWS: Google recently launched Solutions, a free tool within Google Ads that automates and simplifies campaign management in an accessible and user-friendly way. It comes with several pre-built automation templates for the campaign management process, including Performance Reporting, Anomaly Detection, URL Validation, Budget Optimization, and Negative Keyword Management—all of which can be customized to meet different advertising needs.
THE CONTEXT: As part of this launch, Google announced it will sunset its manual solutions library. This focus on automation comes on the heels of Google’s new AI-powered approach to displaying responsive search ads and its application of Gemini for text and image generation within Performance Max (which has not been hiccup-free). Overall, the company continues to push advertisers towards automated processes across the campaign life cycle, from creative development, to ad placement, to campaign management.
EXPERT POV: Google continues to create new tools to help free up time for paid search managers to analyze data and make strategic decisions. By starting to use the Solutions tools now, search managers can get ahead on campaign management simplification, allowing them to spend more time on optimizations and recommendations that grow paid search accounts and drive business goals. – Nick Tuttle | Director, Search Media Investment
THE NEWS: Performance Max (PMax) campaigns are now available globally through Microsoft Advertising. PMax is an automated campaign type that uses artificial intelligence to create ad assets and automate ad optimization across different Microsoft Advertising formats and channels. The company will soon add more automated features, including brand exclusions (for less inflated performance metrics), search insights reports (for greater visibility into user queries), and video assets (for broader creative distribution) to its PMax campaigns.
THE CONTEXT: This global release follows a closed beta launch in May 2023 that Microsoft deemed successful. Time- and resource-strapped marketers who rely on manual efforts may appreciate PMax campaigns’ automated optimizations, even as some position the campaign type, similarly available through Google, as relinquishing control and decision-making power to artificial intelligence.
EXPERT POV: Rolling out PMax campaigns globally is another instance of Microsoft competing with Google, particularly by relying on AI and algorithms that identify when and where someone is most likely to convert. When it comes to the landscape of search advertising, Google is still far and away the most dominant search engine, but Microsoft integrating ChatGPT into Bing helped increase its market share from 6.35% to 8.07% over the past year. When determining whether PMax may be a valuable, additional layer in your search investment, consider your ideal demographic (as older generations are more likely to use Bing) and your vertical (as certain industries, like healthcare and financial services, attract larger shares of older users). – Nick Tuttle | Director, Search Media Investment
THE NEWS: Reddit is launching a suite of tools, called Reddit Pro, for businesses looking to grow their organic presence on the community-driven platform. Currently in its beta testing phase, Reddit Pro uses AI to help brands identify trending topics and conversations, even allowing them to see when their brand has been mentioned in a subreddit. The suite of features also includes content drafting, scheduling, and reporting tools, as well as the ability to easily turn organic posts into paid advertisements. This is Reddit’s first set of free tools meant to inform businesses’ social media strategies, and the company plans to launch additional features within it later this year.
THE CONTEXT: The Reddit Pro launch came as the company prepared its initial public offering (IPO) at a stock price that valued the company at nearly $6.5 billion. Reddit is likely leveraging this new suite of free tools to entice brands to the platform and turn them into paying advertisers.
EXPERT POV: All eyes are on Reddit as the platform continues to make headlines with news of its successful IPO. Brands looking to connect with a wider audience may want to explore adding this channel to their organic and paid social portfolio. These new Reddit Pro tools—only available to brands that are active on Reddit—grant deeper insight into what Redditors are saying about brands, what aspects of products or businesses are resonating with customers, and which industry topics are trending. For brands not yet using the platform with a u/ (Reddit-speak for “username”) of their own, these new tools may incentivize them to create Reddit profiles and start an “OP” (“original post”) of their own. Pro Tip: Get to know the Reddit lingo! LSHMSFOAIDMT – Jess Kaswiner | Director, Social Media Investment
THE NEWS: TikTok has been under the US political microscope for some time, but now it’s ramping up its own political activity: TikTok users were shown a pop-up message earlier this month, urging them to call members of Congress to voice their opposition to a bill that aims to ban the app in the United States if its parent company, the China-based ByteDance, doesn’t sell it. Congress was quickly flooded with phone calls from TikTok users of all ages; the majority of calls, however, were from children. Since then, anonymous sources say some of the calls have turned threatening and concerning.
THE CONTEXT: Less than a week later, the US House of Representatives passed the bill, 352 to 65 in favor of a nationwide TikTok ban if the app isn’t sold, driven by concerns over the data security of US TikTok users. The bill’s future in the Senate is unclear, but President Biden has said he would sign the bill if Congress passes it.
EXPERT POV: While a ban on TikTok in US markets could have significant implications for brands already active on the platform—especially those leveraging it for influencer marketing and e-commerce sales—daily active usage is not showing any signs of slowing. The recent developments around TikTok highlight a continuing concern with and focus on data privacy in the digital advertising space. Taking a step back from TikTok specifically, this situation underscores the importance of diversification in media planning. In the short term, however, Committee and House votes are the beginning, not the end, of a long process. – Jess Kaswiner | Director, Social Media Investment
THE NEWS: Pinterest’s recent campaign, “The P is for Performance,” touts the platform’s full-funnel approach to advertising, including lower-funnel case studies that show as much as a 28% increase in conversions and up to a 96% increase in traffic for its advertisers. Pinterest’s performance products include mobile deep links and direct links, making it easier for users to convert, plus shopping ads for greater inspiration and Pinterest API for Conversions for higher reporting visibility.
THE CONTEXT: In years past, Pinterest’s ethos of being a place for discovery has appealed to advertisers seeking upper-funnel awareness for their brands. With this campaign, Pinterest seeks to broaden its draw for advertisers who may only think of it as an upper-funnel platform. The campaign launched shortly after Pinterest released its Q4 2023 earnings, highlighting 12% revenue growth compared to the same period in 2022 and its 11% increase in global monthly active users.
EXPERT POV: Pinterest has thrived as one of the first social platforms to sit in a space that blends paid search and social channels. It’s no surprise that as a historically well-established traffic driver, Pinterest has now set its sights on also fiercely competing in lower-funnel effectiveness. Recent product releases have proven to be fairly low-lift activations for advertisers, particularly in the retail, e-commerce, travel, and professional services industries. Brands can significantly cut down the path to conversion by leveraging Pinterest to display product information, prices, and descriptions directly to their audiences’ feeds via shopping ads and simplify the consumer journey by tapping into direct links. – Jenny Lewis | Director, Social Media Investment
THE NEWS: Online sales for Cyber Week 2023 were up 7.8% year-over-year, with e-commerce sales totaling $12.4 billion on Cyber Monday. Paid digital marketing was a big driver of that growth, and advertisers are relying more on automated platforms to enhance efficiencies and expedite the scaling of campaigns. On the other hand, with advancements in automation and AI, invalid traffic has become more and more sophisticated over the past three years. One advertiser explained that tackling invalid traffic led to “more stable and predictable growth across our most important paid media channels.”
THE CONTEXT: 22% of ad spend in 2023 (or $84 billion out of a total $382 billion) was lost due to ad fraud. However, $23 billion of that amount would be recoverable with fraud mitigation platforms in place. Given that political advertising for the US presidential election will drive up ad costs at the start of the holiday season, driving efficiencies by leveraging the right technologies will be especially key for advertisers this year.
EXPERT POV: Ad networks aren’t incentivized to crack down on the increased bot traffic we’re seeing due to AI advances and the corresponding ease with which bad actors can create bots. So, the onus is on the marketer to stay alert for signs of high levels of bot traffic. These include high bounce rates and traffic spikes without corresponding conversion increases. Consider ways to block or limit these, like captchas, using conversion-based goals with machine learning bidding, and optimizing landing page content to be very specific to the intended conversion. — Jesse Foley | VP, Search Media Investment
THE NEWS: The IAB’s new comprehensive consumer privacy study found that nearly 80% of consumers would prefer to get more ads in exchange for not having to pay for websites and apps, and that 90% prefer personalized ads, but that nearly half feel websites and apps aren’t clear enough about how their data is used.
THE CONTEXT: With Google planning to fully deprecate third-party cookies in its Chrome browser by the end of this year, and signal loss across the industry as a result of data privacy concerns, figuring out how to use consumer data in ethical, transparent ways to serve personalized ads to consumers is a must for digital advertisers.
EXPERT POV: The fact that most consumers would rather receive more ads to retain their free access to websites and apps means that advertisers’ digital media investments are well-positioned to reach consumers who find them valuable. Advertisers should take a “test and learn” approach to understand which channels work best given their KPIs and to remain flexible and fluid with budget allocations based on results. —Laura Kubiesa | VP, Social Media Investment
THE NEWS: Google’s responsive search ads rely on artificial intelligence to combine headlines and descriptions based on consumer behavior and predicted outcomes. New AI-powered features allow Google to decide when an ad should display only one headline versus two, with the second headline appearing at the beginning of the ad’s description section. Google can now also supplement or override an advertiser’s manual assets—like images, sitelinks, callouts, and structured snippets—with its own AI-generated assets if it feels doing so will help an ad’s performance.
THE CONTEXT: AI’s influence on ad placement and creative continues to grow. Search Engine Land weighed the pros and cons of Google’s update, noting that while it may serve to drive engagement and performance, it also means that advertisers are surrendering more control to Google. At the same time, artificial intelligence tools often don’t perform with 100% accuracy—and as this is a newer feature, advertisers have no benchmark for how much accuracy these specific features can provide.
EXPERT POV: With the increased focus and adoption of AI capabilities in digital media, it’s no surprise Google continues to roll out these features within their campaign types and ad formats. As the industry continues to trend in this direction, getting left behind means being unable to capitalize on the reported improved performance of these AI-powered features. However, many advertisers need to maintain control over the images and copy that run within their ads, so turning off the auto-assets feature within Google Ads may be the better option. Advertisers who aren’t comfortable giving up control can still take advantage of some of the latest updates by testing the new campaign-level headlines and descriptions and scheduling them to run during certain time frames, which can help manage time-sensitive promotional copy. — Alyssa Theo | VP, Search Media Solutions
THE NEWS: AI and automation within Meta's ad products, such as its Advantage suite, helped fuel 24% year-over-year growth for Meta's ad business in Q4 2023. The social giant also shared advertiser success stories that included increased revenue and improved performance metrics for brands’ campaigns when they employed Meta’s AI ad tools. Meta plans to expand its generative AI features, including text and image variations, to further enhance advertising capabilities.
THE CONTEXT: Meta, along with every other social platform, is placing a high level of priority on building out further automation and AI solutions that work in tandem with their advertising algorithms to drive strong results for customers while making the lives of marketers easier.
EXPERT POV: In the face of ongoing question marks with Meta’s advertising platform (e.g. third-party cookie deprecation, ATT impacts, and data privacy regulations), capitalizing on AI and automation solutions integrated into the platform is an effective way to manage media campaigns efficiently, expand existing audience targeting to reach engaged new users, and create a high volume of ad iterations for easier creative testing. — Erik Chellberg | VP, Social Media Investment
THE NEWS: Pinterest has begun rolling out an integration that allows ads to show on Pinterest via Google’s Ad Manager. The integration will make it so that when Pinterest users come across a Google ad, they’ll be sent to the advertiser’s website to finalize their transaction. This partnership will not only broaden the reach of advertisers using Google Ads but will allow them to engage an active, high-value consumer base.
THE CONTEXT: Pinterest’s stock dipped almost 28% in early February, but bounced back after this Google deal was announced.
EXPERT POV: For those advertisers looking to generate discovery, this new inventory source could be very beneficial. Google is rolling out this new option over the next several quarters, and it will be available within Google’s Ad Manager. As of now, Basis Technologies is waiting to see how this inventory performs to inform future recommendations. — Robert Kurtz | Group VP, Search Media Solutions
THE NEWS: TikTok's Marketing Science team partnered with IPG's MAGNA Media Trials to conduct a study of digital video through the lens of TikTok’s impact on its advertisers. Contents of the report include TikTok’s positive effect on brand sentiment and consumer experience, higher engagement with skippable vs. non-skippable video ads, how contextual content adjacency increases ad view time, and the details of TikTok Pulse, a feature that guarantees ad placement next to top-performing organic content.
THE CONTEXT: TikTok has faced several hurdles in the past few years, not the least of which being several countries and US states implementing full or partial bans of the platform. And although TikTok’s growth is slowing, it still led 2023’s list of app downloads and consumer spending.
EXPERT POV: Advertisers are right to prioritize TikTok, given the time users spend on the app per day, averaging 53.8 minutes, and the platform’s abundance of out-of-the-box and accessible ad products, betas, incentives, and platform support. — Alana Putterman, Group VP, Social Media Investment
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Since OpenAI first introduced ChatGPT back in November of 2022, consumers and advertisers alike have wondered how AI-powered chatbots will change their lives.
In the months that followed, ChatGPT grew to 100 million monthly users faster than any other consumer application in history, Microsoft introduced its own GPT 4-powered app—Copilot—while also integrating it into Microsoft 365, and Google moved swiftly to roll out its own AI-powered chatbot, Gemini.
Amidst this frantic flurry of innovation, it’s growing increasingly likely that generative AI will soon revolutionize the search landscape. In fact, Gartner has predicted that by 2026, traditional search engine volume will drop by 25% as a result of chatbot-like applications.
But given the uncertainty around exactly how search will transform in the coming years, what can advertisers do now to prepare? Leaders can get ahead of the coming changes by adopting test and learn strategies that set their teams up for success and give them a competitive edge going into the AI-driven future.
Though generative AI seems to be everywhere just a year-plus after its public debut, the good news for search advertisers is that they will likely have a bit of time to prepare before any drastic changes to their media planning takes hold. Even as more consumers adopt tools like ChatGPT, Copilot, and Google’s generative AI-powered SGE over the next few years, they’ll mostly use those solutions for synthesizing complex information, while Google Search will remain the method of choice for simpler searches.
In the longer-term future, consumer adoption of generative AI-powered chatbots for search will increase, with competition increasing as more companies develop AI tools. We’ve seen this a bit already: After rolling out Copilot last year, Microsoft’s US search ad revenues were forecast to grow over three times faster than Google’s YoY, and the company’s share of the nonretail search market is projected to reach almost 9% by 2025. There are also a number of startups in the space, and if OpenAI or Apple create their own search engines—or partner with another company to create one—that could significantly disrupt market shares. With this increased competition, consumer use of AI for search will likely grow increasingly fragmented.
No matter what the competitive landscape looks like a few years down the line, we are likely to see lower volume across traditional search engines. Instead of going to Google Search, consumers will turn to chatbots or interact with voice-powered AI assistants like Amazon’s Alexa, Google Assistant, and Apple’s Siri in a way that is more search engine-like. As far as advertising opportunities, these AI-powered solutions will be backed by many of the same players who are currently in the search space, and those companies will undoubtedly integrate opportunities for marketing engagement within the tools.
The big takeaway? While we’ll eventually see a decline in the use of traditional search engines, we’ll likely also see a net positive engagement with generative AI-powered search engine-like queries.
This shift to chatbot-driven search may also lead to a meaningful decline in organic website traffic. One recent forecast estimated that Google’s Search Generative Experience (SGE) could reduce organic search traffic to publishers’ sites by anywhere from 20% to 60%.
Google has already steered users in that direction over the past five-to-10 years, with developments like its Quick Answers feature (which pulls content meant to answer a searcher’s question and displays it above other search results). Quick Answers can oftentimes eliminate the need for searchers to actually click into one of those search results—which makes sense, as users want to get their questions answered promptly and accurately, and Google wants to keep people in the Google ecosphere.
Generative AI-powered search engines and chatbots may increasingly have a similar ability to answer questions within their own environment, reducing the need to drive users to a website. For instance, consumers may be able to buy products directly through a chatbot without ever needing to go to the brand or retailer’s website (similar to how shoppable ad formats on Instagram and TikTok help fuel in-platform social commerce). Or, alternatively, you might be able to make a reservation via a chatbot without ever opening the OpenTable or Resy app (similar to how those apps’ APIs let you book a table directly from a restaurant’s website).
This shift bears striking similarities to how Facebook shifted its algorithm several years ago, giving preference to organic posts from brands that were also serving paid ads on the platform. Search engines will likely end up operating in a very similar way: Services like Google and Bing will still have organic listings, but they’re going to be trumped by these conversations that consumers are having with chatbots, and it’s going to be harder to get exposure in those conversations if you aren’t leveraging advertising opportunities in those spaces.
In our work with leaders at agencies and brands, we’re seeing an equal amount of fear and excitement around how AI will change not only the search landscape, but digital advertising as a whole. There’s a lot of trepidation around AI’s impact on brand safety, but it’s been complimented by a lot of underlying excitement around what these tools can empower advertisers to do—particularly the way they allow advertisers to swiftly and efficiently produce, edit, and switch out assets based on their needs.
While some leaders are actively preparing for the coming changes, we are also seeing a lot of folks who are very hesitant to adopt any generative AI solutions. In some respects, that hesitancy makes sense, given the many unknowns around how the landscape will develop. At the same time, to best set their companies up for future success, advertisers do need to lean into these AI-driven advertising opportunities now, at least to some degree. Marketing and advertising leaders who are more quick to learn and test new AI-powered tools will develop generative AI-adjacent skill sets earlier than their AI-averse peers, giving those early adopters a competitive edge in the years that follow.
How should advertising leaders guide their teams towards the future of search advertising? Here are our recommendations:
AI-powered targeting is probably the most developed AI feature that advertisers can test and learn on right now. This involves relying on Google or Meta or Bing’s AI technologies to target certain people who are potentially in market for your product. The tactic is becoming even more important in the context of signal loss, because it offers advertisers a privacy-friendly way to reach targeted audiences. These are opportunities brands and agencies should be exploring right now—you don’t want your team to still be using manual keywords and manual CPCs right up until the point where they’re no longer an option.
Then, of course, there’s generative AI, which is the shiny new toy of the moment. It’s all very exciting, but it can also be a bit scary for teams to adopt because it means relying heavily on a machine to create the right message for your audience. The consistency, quality, and accuracy offered by these GenAI features is definitely a worthy concern. It’s important to remember that artificial intelligence tools do have biases, because they’re programmed by people, who have biases, and they learn from gigantic pools of content and data, some of which is inevitably biased. We saw some of these fears play out recently, with Google suspending its Gemini chatbot’s ability to generate images of people after an online uproar when some Gemini-generated images were historically inaccurate.
Advertisers can and should test and learn on these tools, but it’s critical to put guardrails in place. By adopting a strong quality control system, advertisers can experiment with these tools and benefit from the efficiencies they offer while protecting themselves from brand safety risks and avoiding low-quality creative.
Google’s Performance Max (PMax) is, perhaps, the most exciting AI-driven advertising opportunity on the market today. Think of it as Google’s proof of concept that AI and machine learning can drive advertising results for conversion-focused campaigns across all assets and a variety of channels, combining them all into a single campaign type.
Within PMax, Google is slowly rolling out the ability to create ads using generative AI tools. For instance, an advertiser can upload a picture of their product and tell PMax to generate an image of that product on a beach at sunset. PMax will then spit out four variations of that basic image for use in an ensuing campaign. There are some enormous time- and cost-efficiency benefits to this: Advertisers can cut thousands of dollars that would typically be spent on production and go to market much more quickly. Advertisers can even download that asset and use it on other channels for greater creative continuity.
We don’t yet know what advertising opportunities will look like on chatbot-driven search engines, so at this point, it’s all speculation, but it’s important for advertisers to stay up to date on developments in this area so that they know when those opportunities come to market.
One other way advertisers can prepare is to optimize their content for Google’s Quick Answers. A Google-powered chatbot is likely to pull content from the same places it’s pulling those answers, so from an early adopter standpoint, this is a great area for SEM marketers to prioritize.
Once of the greatest benefits that AI offers advertisers is its ability to quickly process and analyze huge sums of data. As the technology develops, more and more data-related insights will become more widely available, and businesses will need the infrastructure and the know-how to use those insights effectively.
Data-driven cultures value and use data to inform their decisions, investing time, energy, and money into employees, processes, and tools that help them to do so effectively. For leaders, this could mean levelling up a team’s processes relating to data quality and consolidation, having them perform an audit of all the different sources from which they collect data (ex. social media, website analytics, customer surveys, etc.) and expanding upon that list, or investing in a CDP to better capitalize on first-party data in a cookieless world.
By investing in AI-powered tools, data-facing teams will be able to generate new insights, improve accuracy, and automate tasks. And because they’ll be using AI for data-related tasks, teams will likely grow increasingly comfortable with these kinds of tools, which will make it easier for organizations to leverage additional AI-powered solutions as they emerge.
Advertising leaders should also pay attention to prospective employees’ AI-related skills when hiring new team members and prioritize upskilling current team members. This could be anything (and everything) from hiring more data scientists to providing employees with free learning opportunities focused on using AI to improve SEM campaigns. Again, the more leaders invest in their team’s AI abilities now, the quicker those teams will be able to adapt as new technological developments come down the line.
Lastly, leaders should aim to stay on top of news related to how search engines are changing, keep abreast of what new AI-driven advertising opportunities are available, and pay attention to what successes and failures their peers are having with artificial intelligence tools.
In particular, stay attuned to the potential challenges and pitfalls posed by artificial intelligence. Generative AI, most of all, comes with several significant risk factors. A hallucinating AI chatbot, for example, can make up fake “facts” and generate misinformation that can be difficult for content moderation tools to spot, and the resulting content can represent a threat to brand safety. (It’s also the reason 82% of US B2C marketing execs have expressed concern over marketing their brands during this year’s presidential election cycle). In fact, Gartner has predicted that by 2027, 80% of marketers will have (and need) dedicated “content authenticity teams” to combat AI-generated misinformation.
There are also many unanswered questions related to AI-generated content and copyright infringement—from the legality of chatbots being trained on unlicensed content, to questions around who owns AI-generated media, with the US Copyright Office ruling in 2023 that works containing materials created by AI cannot be copyrighted. In the short term, be sure to keep an eye on how the regulatory landscape develops. While we can’t predict how governments will legislate the use of these technologies, it’s all but certain that they will eventually take regulatory action, and staying abreast of those developments will be critical.
It’s a lot to keep track of, but these are the things advertisers need to be doing now to ensure they’re at the forefront of the industry and to feel confident that they’re providing their clients and stakeholders with the best possible recommendations.
The quickly developing search landscape asks a lot of marketing and advertising leaders. Advertisers will need to get comfortable with being uncomfortable in the coming years as AI moves us towards an uncertain future. Teams that test and learn early will have a leg up on those who are more hesitant to dive into the AI-driven future of search engine marketing.
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While we’re on the topic of getting comfortable with major shifts in the advertising landscape: Want to find out how your peers are adapting to signal loss and the cookieless future? We surveyed over 200 marketing professionals across agencies, brands, and publishers to find out how prepared they feel for the loss of third-party cookies, what alternative targeting and attribution solutions they’re adopting, and more. Read all about it in Identity vs. Privacy: Digital Advertising in a Cookieless World.
When it comes to US voter sentiment, there is a clear generational divide that extends across feelings on hot-button political issues, local vs. national political involvement, optimism about the upcoming election season, and the overall state of the country.
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In 2020, many leaders committed to advancing diversity, equity, and inclusion (DEI) at their organizations in response to the movement for racial justice set in motion by the murder of George Floyd by Minneapolis police. Four years later, some those commitments appear to be wavering, with forecasts estimating that organizational DEI investments will fall by 13% in 2024 compared to 2022. In the advertising sector specifically, recent layoffs at Google and Meta resulted in downsized DEI programs, and investment in diverse-owned media companies has slowed.
It seems that for many companies, amidst continuing economic uncertainty and in the lack of acute public pressure such as that felt in the wake of Floyd’s murder, DEI has been relegated to a “non-mission critical” investment.
Despite these trends, much of the advertising industry remains committed to advancing diversity, equity, inclusion, and accessibility, and there is ample opportunity for continued prioritization and growth of DEI efforts.
To further explore how leaders can make meaningful strides toward DEI at their organizations, we sat down with Lois Castillo, Head of Diversity, Equity, and Inclusion at Basis Technologies. Lois, a veteran of both DEI and advertising work, recently wrapped up Basis Technologies’ first virtual IDEA (inclusion, diversity, equity, and accessibility) summit, an event aimed at integrating IDEA principles more deeply into Basis’ organizational culture. Below, she shares what companies can be doing better in their DEI work, how DEI leaders can anchor themselves amidst the complexity of that work, and how the IDEA summit served to advance Basis’ DEI-focused goals.
Lois Castillo: First, the obvious answer: Not doing it.
By this point, leaders should understand that DEI is not just an ethical imperative, or good for business, but something organizations can’t survive without. The world is a diverse place that’s only getting more diverse, and if companies don’t reflect that increased diversity, they’re just not going to make it. When businesses don’t change with the times, they perish—for example, look at what happened to Blockbuster’s once streaming TV became the norm. The same thing goes for leaders: If you’re not doing your own work and development around DEI and bringing that into your organization, you’re not going to be leading for much longer.
When it comes to companies taking action, a common mistake I notice is treating DEI as solely the responsibility of HR. While fostering diversity, equity, and inclusion among employees is crucial, that’s just one aspect of the work. Companies that fail to make a real impact are likely fixating solely on this aspect instead of adopting a holistic approach that extends beyond their own workforce.
My team takes a three-pronged approach, addressing DEI in the following areas:
Additionally, I think it’s worth noting that companies that don’t include accessibility in their DEI work are missing the mark. To be truly inclusive of diverse team members, we need to work towards an accessible workplace—one that considers the spectrum of ability and neurodiversity and works to ensure that everyone on those spectrums can succeed.
LC: Well, I start with transparency and honesty—I don’t pretend I know everything. But I love people, and I’m curious about people, and I’m committed to constantly learning about the issues that people experience so that I can better address them in my work.
It’s true that all the axes of diversity among us can get overwhelming if you start to think about it, and that there’s a lot of work that must be done to address those axes individually. At the same time, there are ways we can address all of them at once, like creating shared language and behaviors for interacting with each other in the workplace that are rooted in respect and accountability—for example, calling someone in instead of calling them out when they make a mistake.
This isn’t easy work, that’s for sure. It’s not for the faint of heart. But that doesn’t mean you give up!
LC: First, let me break down what the summit looked like. We organized a variety of sessions, each with an expert speaker who shared stories and insights based on a specific aspect of inclusion, diversity, equity, and accessibility (IDEA). We had sessions on topics including how ageism shows up the workplace, how to foster inclusive environments for neurodivergent folks, and what great allyship looks like in practice. In addition to presentations from our experts, the sessions provided space for dialogue, where our employees could share personal experiences, ask questions, and engage with each other.
One of my main goals behind the event was to help move our culture forward by grounding everyone in the same language and knowledge. There are so many people with so many different life experiences at our company, and I wanted us to get grounded around the complexity and the multifaceted nature of diversity, equity, and inclusion. I think when people hear the word “diversity,” they’re often thinking of gender and race. But we’re diverse in so many ways, and they all intersect. So, advancing our people’s knowledge and vocabulary of those differences was a big part of the event.
LC: I hope people walked away with curiosity about all the different ways people exist in the world, and with actionable tools that can help them in their own learning journeys around inclusion, diversity, equity, and accessibility. Many of the topics at this specific event were geared around self, encouraging people to investigate their own experiences. I hope the sessions inspired people to get curious about their own experiences of difference in the world, as well as their triggers, blind spots, and biases. It’s important to get curious about yourself, because that will more than likely translate into curiosity about others’ experiences.
I think my favorite part of the summit was just watching the chats in these sessions and seeing all the engagement and the different questions and contributions people had. I loved seeing how participants felt free and safe enough to share their vulnerability. It’s really meaningful to see presentations and conversations resonating with people, and to see them feel secure enough to bring their personal lives and experiences into conversations with their colleagues.
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Learn more about Basis Technologies’ commitment to diversity, equity, inclusion, and accessibility here.
Artificial intelligence is transforming the world of social media advertising—and fast. But when it comes to a channel where backlash can be particularly swift and unforgiving, just how fast should brands adopt these new technologies?
Social advertisers are seeing a boom in AI-powered advertising tools, and teams are facing increased pressure to embrace them to harness the speed and efficiency they promise. At the same time, some of these tools—particularly those powered by generative AI—have come accompanied by new concerns around both quality and brand safety, as the race to bring new AI solutions to market has resulted in many of them feeling like they’re still works in progress.
Advertisers worry about the quality of AI-generated ads, given events like Google’s recent suspension of its Gemini AI chatbot’s ability to create images of people after it generated historically inaccurate images. And a recent study found that only 38% of consumers have a positive view of AI, calling into question how AI-generated ads will be received.
A healthy dose of skepticism is, well, healthy. But these concerns, while well-founded, don’t mean advertisers should avoid testing and learning with AI-powered tools that fit their goals. There are a variety of ways advertisers can begin adopting these technologies to tap into their benefits while maintaining caution around things like brand safety. As automation- and AI-led solutions become the new normal in digital advertising, it’s critical that teams start developing their skill sets and increasing their familiarity with these tools to ensure they can use them with confidence and enjoy the increased efficiencies they provide.
AI has already started to change how advertisers target audiences on social media. Many platforms—including Meta, TikTok, and LinkedIn—are beginning to pull back on the number of manual controls they’re giving advertisers to connect with target audiences. Instead, they’re moving advertisers towards AI-powered tools that identify the most appropriate target audiences for their campaigns. For instance, Meta’s Advantage+ Targeting feature automatically identifies targetable audiences based on factors like performance data, consumers’ interactions with other ads in the same vertical, and the content consumers are looking at across Instagram, Messenger, and Facebook.
In some ways, this is a very exciting development. We’re seeing solid results from our own use of these tools, so the numbers are speaking for themselves. On the other hand, it’s a bit nerve-wracking: Advertisers aren’t used to letting platforms take the wheel like this, and if you have a very specific target audience in mind—and you're spending an enormous amount of money trying to reach them—you want to know that you're serving ads to the right people. The shift toward AI-powered audience targeting may end up creating yet another black box to baffle and frustrate advertisers desperate for transparency.
However, this is the direction these platforms are going in, which means we’ll eventually reach a point where advertisers won’t be able to revert to those very specific, manual settings they’d grown accustomed to. Because of this, it’s critical for advertisers to at least begin testing and learning with these tools to grow more comfortable with this shift.
Of course, having AI handle the targeting doesn’t mean advertisers should just set and forget these campaigns. It’s critical to review performance data and assess whether the AI-powered tools are actually accomplishing their goals. For example, if an advertiser is running a lead gen ad, and Facebook is recommending some fairly broad targeting settings, is that actually driving quality leads? Maybe… or maybe not. In this new, AI-driven social world, advertisers will need to carefully assess and adjust their strategies accordingly.
Social platforms are also empowering advertisers to create assets like copy, images, and entire ads via AI. There are a number of significant benefits to these tools, the biggest being simplicity, speed, and ease of launch. This type of built-in efficiency could radically transform how advertisers develop and scale their social campaigns. Advertisers can generate and test new creative variants across different audience segments for more fine-tuned campaigns, or even experiment with entirely different creative approaches to see which resonates more strongly with consumers.
However, efficiency without effectiveness is ultimately inadequate, and many advertisers have real concerns around this shift towards AI-generated content. Without sufficient quality control and campaign monitoring, advertisers using AI-generated ads run the risk of wasting money on ineffective creative—or, worse yet, garnering some serious backlash from consumers.
There’s also some concern that we’re going to get to the point where most (if not all) of the ads on social are generated by AI, and we may well hit a point where consumers don't want to see AI-generated assets, but will instead desire something that feels a little more authentic. Considering this, advertisers should start to think about how they can strike a balance and find the right opportunities to use these tools, but not necessarily allow them to dictate all their social media advertising and messaging efforts.
Social listening is an increasingly key advertising tool, providing insights that can significantly impact a brand’s strategic approach. Manual social listening can be time-consuming and tiresome, but new AI-powered social listening tools can review and process huge amounts of data and sentiment and automatically pull out the top takeaways for advertisers’ immediate use. For instance: What are the top concerns of consumers in a certain category? What does overall sentiment look like? And why is it negative or positive?
Comparatively speaking, these AI-powered social listening tools are also a safe and impactful way for social teams to leverage AI, as they aren’t generating anything that is subsequently going out to consumers. As a result, this is a solution that’s seeing a high rate of adoption: In Q4 2023, social listening was the third-most popular use of AI (after chatbots and copy generation) among brands and retailers, with 40% saying they use AI-powered social listening tools.
All in all, social listening offers even the most AI-averse advertisers a low-risk, high-reward avenue for harnessing the power of AI.
The best ways to leverage AI-powered tools for social media advertising will differ from agency to agency and brand to brand: Some are ready and willing to go all-in on generative AI, for instance, while others may approach adoption at a slower pace. Whatever pace you choose, the important thing is to test and learn in some way on tools that fall into each of these three categories. The future of social advertising is AI-driven, and advertisers who don’t start getting comfortable with these technologies will lack a competitive edge as these solutions grow more commonplace and become more advanced in the coming years.
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Curious about how your peers feel about generative AI, which GenAI advertising tools they’re leveraging, and how often they’re using them? We surveyed over 200 marketing professionals from top agencies, brands, non-profits, and publishers to get a pulse check on the industry’s sentiment towards and use of GenAI. Read all about it in our report, Generative AI and the Future of Marketing.
It was early 2020 when Google first announced plans to deprecate third-party cookies in its Chrome browser. Now, several years and numerous delays later, those once-distant plans are coming to fruition: Cookies were turned off for 1% of users as of early 2024, and they appear set to be deprecated for all users by the end of the year.
Google is by no means early to the party when it comes to taking a stance against the legacy identifier, considering that Mozilla’s Firefox started limiting cookies back in 2013 and Apple’s Safari followed suit in 2017. But given that Chrome currently accounts for more than 66% of the global browser share, Google’s move will have the biggest impact on advertisers.
In the years since Google’s initial announcement, the digital advertising industry has been aflutter with conversations around alternative targeting solutions for a cookieless world—from contextual targeting, to geotargeting and location-based targeting, to collecting and maximizing first-party data, to tools like Google’s Privacy Sandbox.
But targeting isn’t the only thing that will be transformed by cookie deprecation. A recent survey found there are two key challenges that are top-of-mind for advertising professionals as we head into a cookieless world: Targeting and measurement/attribution. As the digital advertising industry stands on the precipice of cookie loss, the conversation is expanding to include more comprehensive solutions around not only targeting, but measurement as well.
Since the advent of the third-party ad server, marketers have grown used to empirical metrics housed within reporting modules: They knew exactly how many view-through conversions they were getting and the (relatively) precise path to conversion, and they could easily measure ad frequency. This was all enabled by third-party cookies, which tracked a user’s experience as they navigated the digital space.
As Google turns off third-party cookies for its users, advertisers are losing the cookie-fueled reports that they’ve relied on for years. Without them, advertising teams must reconsider how they both assess campaign performance and tell those performance stories to either clients or teams. And given that 30 million Chrome users have already had cookies turned off, the time to make that shift is now.
Among the industry leaders we work with, the ones who are adapting more quickly than their peers are those who understand how their buying decisions, audience strategies, and performance expectations need to shift, and are actively working to change how they communicate performance stories to their clients and teams.
For instance, cookie-based reports used to allow advertising teams to say, “This person saw my ad on this channel, they saw a retargeted ad X days later on this other channel, and then they purchased this product after X amount of time.” Now, without cookie-based data, teams will need to get comfortable telling stories that sound more like, “We invested X amount on this channel, X amount on this channel, and X amount on this channel. Though we can’t track conversions on the individual user level like we used to, we see that sales went up by X amount based on business data, that search terms peaked on this day, and that social engagement grew as well. Using various data sets, we can infer that those ads played a part in driving awareness, consideration, and, eventually, conversion.” Teams can also leverage data they gain from modelling to make projections about performance based on media spend, as well as cookieless conversion attribution to measure post-click conversions in a privacy-friendly way.
Just like with cookieless targeting, there isn’t a silver bullet solution out there that’s going to make measurement as precise as it was with third-party cookies—and advertisers should approach any claims that a certain solution can do so with a healthy amount of skepticism.
Instead of hoping for a fix-all solution, teams across the industry will need to experiment and try out different measurement tools to determine what works best for them in a cookieless world. It’s OK to not have a single path forward, and it’s OK to try different approaches—but it’s not OK to just keep waiting. In this new landscape, it’s about being comfortable with experimentation and adaptable to performance.
Tools like cookieless conversion attribution that rely on click strings or Google’s Privacy Sandbox reporting can give advertising teams some insights on conversions for anonymized groups of users in a privacy-friendly way. Strategies like media mix modeling—which rely on statistical analyses of media spending rather than individual user information—are another solution digital advertising teams might consider as they rethink measurement. Teams that get comfortable with modeling out what to expect from performance vs. having hard figures to rely upon will have an edge once third-party cookies are completely gone. Other tools like brand perception studies and audience panels can also prove useful when it comes to post-cookie storytelling. And if teams haven’t started optimizing their first-party data processes? Considering that first-party data is useful for both targeting and attribution, it’s a strategy that’s critical to invest in.
Leaders should also recognize that this new way of measuring is far more resource intensive, and that they won’t be able to have a digital media associate pull a comprehensive report to send to clients or stakeholders like they could when third-party cookies were around. In a cookieless world, there will be far more people—and a far greater level of skill—involved. Leaders who start to plan for this now will be well-positioned once cookies have been fully deprecated.
Whether industry professionals choose to grapple with it now or later, Google’s third-party cookie deprecation will change measurement across the digital advertising ecosystem. Leaders who work with their teams to reapproach how they communicate campaign performance, and to experiment with alternative measurement solutions, will set themselves up for success as the cookieless future becomes the cookieless present.
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Interested in how your peers are adapting to signal loss and preparing for the cookieless future? Basis Technologies surveyed over 200 marketing and advertising professionals across agencies, brands, non-profits, and publishers to find out how ready they feel for a world without cookies, what cookieless solutions they’re implementing, and more. Dig into the findings in our report, Identity vs. Privacy: Digital Advertising in a Cookieless World.
Earlier this month, droves of marketers and advertisers descended on Austin, Texas to soak in the sights and insights of SXSW 2024. Here are three insights from the notebooks of Basis’ Media Innovations & Technology team to help marketers keep 2024 moving in the right direction.
Podcasting increasingly stands as a contender in advertisers’ paid media strategies. That’s thanks to its unique ability to meet consumers where they are and building trust and affinity not just for podcasters, but for the brands that support them.
Despite the proven performance benefits, podcasting remains an under-invested channel for most brands. For marketers that are evaluating how to add podcast placements into media buys, start by forming a crawl, walk, run strategy approach. Messaging style is critical—after all, podcasting is, at its core, storytelling. Ad content should take on this same style to meet consumers in a mindset they’re already in. Brands should also cross-pollinate paid messaging into complementary channels like Instagram and TikTok to extend their presence, discover new audiences, and maximize their investment.
AI and machine learning will continue to improve podcasting’s capabilities—from content analysis, to niche audience segments, to creating content for advertisers and podcast producers.
Finally, advertisers should keep an eye on AI to potentially be applied as a measurement solution.
Data is the ultimate commodity in a cookieless world—particularly when it comes to effectively understanding and reaching audiences. One form of data that doesn’t get enough recognition in its ability to transform advertisers’ paid media strategies is causal data. At its heart, causal data is focused on measuring a brand’s ability to shift audience perceptions and beliefs about that brand.
Advertisers who want to leverage the power of causal data will need to get up close and personal with their audiences. This requires dedicated, qualitative audience research to understand who your audience is and what they care about—not just the tropes that have been created about them. Understanding the emotional drivers behind consumers’ decisions and perceptions of a brand can bridge data and art, transforming insight into creative messaging that resonates on a deeper level.
When it comes to measuring causal data outcomes, advertisers need to get curious and ask their audiences questions that dig into cause and effect. For example: “How did you feel about a brand before?” and “What touchpoints or communications led you to change your mind?”
Accessing the power of causal data involves a hands-on effort from advertisers, but the outcomes are invaluable, especially as consumers are increasingly loyal to the brands who can prove they truly understand who consumers are and what they need or care about.
The past few years have seen a continual churn of emerging technologies, hitting the scene with a healthy dose of hype. Marketers have been enchanted by the newness and novelty of these technologies (partially thanks to the brain’s novelty center), causing them to put discernment on the back burner.
However, hype and innovation often diverge, meaning marketers will need to override that novelty center to effectively evaluate new technologies based on the intrinsic value they present to a brand on an individual basis.
Marketers who ask questions of hyped-up solutions will be poised for successful deciphering of hype from reality. Consider questions like, “What value does this present to my organization?” “Is there an actual product available to us for use?” “What resources (personnel, investment, time) will be required?” And “What are the outcomes we can expect from using this solution?”
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Not able to make it to this year’s SXSW? Watch Noor Naseer’s session on navigating hype in advertising on demand and download the slides today.