Audio has long been considered an intimate medium, with a trusted voice delivering a one-to-one experience for listeners. But digital innovation has transformed the way audio is perceived as an entertainment platform, and revolutionized consumers’ daily interactions with it.
Where once the only control audiences had over audio was the ability to change the radio station or pop in a new tape or CD (or LP), digital audio now gives listeners seemingly endless choices—all at the touch of a button or tap of a screen. People today use digital audio to soundtrack their lives, flowing in and out of audio experiences that reflect who they are, what they’re doing, and how they’re feeling in the moment—whether it’s workout time, focus time, party time, bedtime, or downtime.
Perhaps no other channel offers the opportunity for authenticity, connection, and flexibility in the way that audio does. And this, in a nutshell, is why brands are increasingly inserting themselves into the audio conversation. The emergence of audio as a mainstay in media plans, alongside developments within the space (including concepts like sonic branding and voice interactivity, as well as new innovations powered by AI), is a top digital advertising trend to watch as teams look ahead to 2025. But what consumer listening habits can marketers tap into to drive performance? Just how effective are audio ads, really? (Hint: very.) And where exactly are consumers tuning in? (Hint: everywhere.) Here, we’ve compiled a collection of stats that answer all these questions and more, helping advertisers separate the signal from the static noise and craft audio strategies set up to make a buzz.
A perfect storm of circumstance and opportunity is propelling digital audio into the marketing spotlight. Younger generations are drawn to formats like streaming online music and listening to podcasts, likely due to the convenience, personalization, and on-demand access they offer. Brands are embracing the idea of advertising on a cost-effective channel where they can command share of voice, amongst many other benefits. And technology like AI is enhancing the way audiences discover and engage with audio content, making it more seamlessly integrated into daily life and personalized to individual listeners. It’s a medium that has oft been underutilized in advertising—but that’s changing.
Over the last couple of years, few stories in digital media have been more compelling than the rise of the podcast. After a blitz of spending and high-profile acquisitions, the podcast market appears to finally be slowing down, but the podcast advertising market is an entirely different story, with the medium still largely underleveraged and undervalued. Listenership is still consistently rising and technology continues to add more layers of contextual targeting and flexibility to podcast advertising, signaling more opportunities for brands on the horizon.
Cutting through the metaphorical noise has always been a major challenge for brands as they compete to connect with audiences, and that challenge keeps growing as attention spans shrink. In audio advertising, though, marketers have a powerful ally in the battle for engagement—an outlet that can dynamically link ideas and narratives to help create an emotional association between the brand’s message and the listener.
The streaming audio ecosystem is dominated by a few key brands. Spotify is the top dog in the market, one of the most widely used digital products in the US and a powerful presence in broader culture. But the likes of Apple Music, Amazon Music, YouTube, SiriusXM (parent company of Pandora), and iHeartMedia all retain a huge presence in digital audio. Fluctuating economic conditions and price increases at several streaming services over the last several years (including Apple Music, YouTube Premium, and Spotify) are colliding to ease some of the breakneck growth from the past several years.
Additionally, unlike video streaming, there isn’t much incentive for listeners to use—let alone pay for—multiple audio streaming platform subscriptions. The nature of licensing agreements dictates that subscription providers broadly offer the same audio catalog. Their features also overlap significantly (on-demand listening, custom radio, playlist tools, etc.), making it harder to entice audiences to add additional subscriptions for their digital listening.
Across the entire digital advertising ecosystem, AI—and particularly generative AI—has been making waves. More than 87% of marketers believe AI will radically transform digital advertising in the next few years, and its potential in the digital audio space is particularly exciting. Already, this powerful technology is changing how advertisers approach audio ads, allowing for more personalized and dynamic ad experiences. By leveraging AI, brands can craft tailored messages—often in real time—that resonate with individual listeners, enhancing engagement and driving better outcomes across podcast and streaming platforms.
Digital audio is ubiquitous and unique, offering a soundtrack to people’s daily lives through playlists, podcasts, and streaming services. Brands looking to build strong, lasting connections with their audiences have a significant opportunity to meaningfully engage with target audiences in these spaces.
Advertisers already have a plethora of tools at their disposal to help inform and execute strategies that lean into consumer listening habits. And with emerging AI-powered innovations, such as personalized audio ads and dynamic creative optimization, the future of audio advertising is looking even more exciting. If these numbers and emerging innovations are any indication, the audio advertising revolution is only just getting started.
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Want more insights on the power and potential of this channel and how it can impact your media plan? Check out our Audio Advertising Guide.
The digital advertising landscape is undergoing several seismic shifts reshaping how brands reach consumers. As the industry navigates the growing influence of AI as well as the move towards a privacy-first advertising model, digital channels are evolving individually as well. And one of the most important transformations for advertising leaders to understand is taking place in the world of TV and digital video.
Where and how consumers watch TV and video content has grown increasingly fluid, challenging advertisers’ approach to once status-quo TV strategies. At the same time, streaming platforms are evolving, presenting new opportunities for advertisers, but also deepening fragmentation and media complexity.
In this context, forward-thinking marketing teams are no longer translating traditional linear TV strategies into connected TV environments, but rather evolving their digital TV strategies for a consumer base that is video-first and device-agnostic. To do so effectively, it’s critical for advertising leaders to understand video and TV viewership trends, how streaming platforms are changing, and the impact of programmatic CTV.
It’s no secret that screen time has steadily ticked up over the years, with consumers’ near-insatiable desire for video content leading the way. US adults will spend four hours per day with digital video in 2025, accounting for a significant portion of the average person’s leisure time. As consumers diversify their video viewing, time spent with traditional TV environments is trending downward, estimated to average 2 hours and forty-eight minutes in 2025—and almost a quarter of Americans don’t watch any live TV at all. The modern consumer is no longer confined to a single screen or a fixed schedule, as video is available everywhere, at any time.
Digital engagement around the 2024 Summer Olympics is a poignant example of these shifting video viewership habits, as well as a useful case study for advertisers on what the next era of digital video strategy will look like. NBC Universal embraced consumers’ diversified viewing preferences, making Olympics content accessible across all video environments. The opening ceremony was the most streamed live event in Peacock’s history, and viewers watched a whopping 23.5 billion streaming minutes across NBCU digital platforms throughout the games, representing a 40% increase from all previous Olympics combined. That momentum spilled over into social environments, driving a 497% increase in social video viewership compared to the Tokyo Olympics. Even more, brands that advertised during the opening ceremony generated a 320% greater search volume than brands who advertised during the Tokyo opening ceremony.
It's worth noting that consumer video viewing habits weren’t the only contributing factor to these increases in digital engagement compared to the Tokyo Olympics: For example, the Paris Olympics took place in a time zone that was more convenient for US viewers than the Tokyo Games, and wasn’t hampered by mask mandates for athletes or a lack of in-person viewers due to the COVID-10 pandemic like the Tokyo games were.
Still, the Paris Games demonstrated that building video strategies to support consumers’ evolved viewing behaviors pays dividends. More specifically, the digital engagement around the Paris Games provides two big takeaways for advertising leaders looking to meet today’s consumers via video.
The first is that today’s TV buys can’t exist in a vacuum. Any investment in CTV must be supported by complementary online and social video placements. CTV may be where a brand’s story begins, but the opportunity to continue the narrative and engage consumers on a deeper level exists within the platforms consumers turn to in search of more content or more information. Advertisers would do well to lean into the unique opportunities presented by each video environment to harness cultural moments, user generated content, and short-form video formats to bring more of their brand or clients to leaned-in audiences.
Secondly, advertising leaders must invest in TV and video in a way that reflects viewership trends. In 2025, consumers will spend one-fifth of their daily media time with CTV, yet advertisers are forecast to allocate just 7.8% of their budgets to the channel. On the other hand, 7.5% of daily media time is spent with Meta’s platforms, but those platforms receive 21.3% of ad spend.
Ultimately, advertisers who adapt their strategies to support the new era of TV and video consumption will have a competitive edge over those who delay adjusting their strategies in tandem with consumer behavior.
While advertisers contend with shifting viewership behaviors more broadly, streaming platforms are experiencing an ongoing evolution of their own to meet the demands of both consumers and advertisers. Observant advertisers will notice two trends shaping this evolution: the pursuit of profitability and the integration of advanced ad tech.
Many streaming platforms have reached a critical juncture where profitability is a pressing concern. As a result, platforms are adopting greater enthusiasm for password-sharing crackdowns (Netflix is already seeing dividends from their efforts in this area, and Disney recently launched a crackdown of their own), rolling out increased subscription costs, and pushing consumers toward ad-supported tiers and bundled offerings. Because of these efforts as well as the larger upward trend of streaming viewership, 54% of the US population will have ad-supported subscriptions in 2025. Compounding this is the growth in FAST viewership, which is projected to grow by 15% each year until 2027.
For advertisers, these changes not only provide more eyeballs to reach, but also individual household account-level data—so marketing teams can be sure they’re targeting their intended consumers, and not their intended consumers’ best friends and family members. As streaming platforms move more users to ad-based subscriptions, advertisers will see CPMs come down as streamers aim to remain competitive. This happened earlier in 2024, when Amazon Prime flooded the market with new ad-supported users, pushing Netflix to drop their CPMs by $10. Advertisers can expect premium inventory to grow more widely accessible thanks to this influx of impressions, and can capitalize on declining costs by leaving space in their budgets for more cost-effective testing opportunities.
As streaming platforms pursue advertising to diversify revenue streams and increase profitability, they’re also prioritizing adtech integrations and partnerships. Netflix, for example, announced it was building out its own adtech platform at the 2024 Upfronts, and other platforms are investing in partnerships with DSPs, measurement providers, clean rooms, alternative identity solutions, and retail media networks to enhance activation, measurement, and targeting capabilities.
As streaming platforms invest more deeply in adtech, advertisers not only have access to more robust opportunities, but these opportunities will be available to a broader range of marketing teams. 70% of the advertisers who supported the 2024 Summer Olympics were new entrants, demonstrating a growing trend toward democratization in premium streaming environments. For advertising leaders, these developments represent a growing opportunity, as premium inventory is made more broadly available in the streaming landscape.
Given the fragmentation and complexity that has become a hallmark of the digital video landscape, it’s no wonder that 75% of CTV inventory is now purchased programmatically. Advertisers are turning to programmatic not only to unify their buying across an increasingly unmanageable volume of platforms, but also to reach their audiences with precision, regardless of where they are.
Meanwhile, economic volatility persists, and marketers are pushed to do more with less. Programmatic advertising provides the tools needed to build sophisticated, yet cost-effective, TV and video strategies. It allows for precise targeting using both third- and first-party data, and supports dynamic ad formats that can adapt to diverse viewing contexts. Programmatic supplies advertisers with the tools needed to reach consumers as they move between various streaming platforms, device screens, and video formats, ensuring a cohesive brand experience.
It’s no wonder the 2024 Upfronts season saw the push toward programmatic grow stronger as buyers demanded that inventory partners prioritize greater access to the addressability, flexibility, and measurement capabilities that are inherent to programmatic. Programmatic demand is rippling across the industry: Advertisers who are increasing CTV spend in 2024 are 61% more likely to purchase those impressions programmatically than those who aren’t increasing CTV spend. Even more, 43% of buyers are pulling budget from linear TV to do so.
As the TV landscape continues to evolve, programmatic provides advertisers with the agility required to keep pace with ongoing changes to capabilities and video consumption habits. However, to make the most of this opportunity, advertising leaders must be wary of rising brand safety and ad fraud threats on CTV, and support their programmatic strategies with safeguards to protect their budgets as well as the reputations of their brand or clients.
Overall, savvy marketers will work with their teams to identify and address areas of underinvestment in programmatic CTV, ensuring they’re taking advantage of the opportunity to activate more sophisticated buys.
Like many other aspects of the advertising industry, the TV and video landscape is undergoing a profound transformation. As traditional boundaries dissolve and new platforms and technologies emerge, forward-thinking advertising leaders must adapt their strategies to stay competitive.
Shifting video consumption habits and a growing volume of ad-supported streamers have placed programmatic advertising at the forefront of this evolution, offering powerful tools for precision targeting, dynamic ad formats, and comprehensive measurement. By embracing these advancements, advertising teams can navigate the complexities of today’s media environment and capitalize on the opportunities presented by the rapidly evolving TV landscape.
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Want to dig deeper into the digital video opportunity? Check out Video Unleashed: The Ultimate Guide to Digital Video Advertising for all the insights and research advertisers need to successfully integrate digital video into their paid media campaigns.
Social media has come a long way since its early days. What once was a space primarily for connecting with friends has morphed into a powerful cultural and economic force, driven by personalized algorithms that shape everything from content recommendations to targeted ads. Social media platforms have evolved into highly sophisticated ecosystems where those personalized algorithms, driven by user data and AI, work together to curate experiences, amplify (and sometimes stifle) voices, and even influence public opinion.
With billions of users spending significant amounts of their time on these platforms, it’s no surprise that social media has become an essential channel for advertisers. Yet as social media—and social media advertising—has grown, so too have concerns about its impact on key issues like users’ online privacy and mental health, especially children and teens. Amidst these concerns, recent regulatory efforts in the United States have intensified, with both lawmakers and platforms taking action to safeguard younger audiences. For advertising leaders, staying ahead of these changes is key to understanding the current state of the industry, as well as how it may evolve in coming years.
In the early days of social media, the landscape was akin to a “wild west” of digital communication: Platforms were growing and changing rapidly, and both users and advertisers operated with significant freedom and minimal oversight. But as social media’s influence has grown, so too has the need for regulation—particularly given the proliferation of mis- and disinformation on social media sites and the technological advancements that make these platforms both highly personalized and addictive for users.
Many of regulators’ concerns are focused on children and teens, because while social media is used across generations, it is especially popular among young people: US teenagers spend an average of 4.8 hours per day on social media platforms, and US children averaged two hours per day on TikTok and over an hour per day on Instagram in 2023.
Social media’s impacts on youth mental health make the need for regulation especially critical: Adolescents who spend more than three hours per day on social media are twice as likely to encounter mental health problems like anxiety and depression, and half of 13-to-17-year-olds say that social media makes them feel lonely or isolated. Earlier this year, the US Surgeon General released an advisory exploring the negative impacts of social media on youth mental health, and published a piece in the New York Times calling for a warning label on social media platforms (akin to the labels found on tobacco products).
Given both social media’s popularity among young users and its potential to create negative health impacts, regulatory bodies are increasingly focusing on protective measures for younger audiences. These regulations impact how data is collected and used, restrict certain types of ad targeting and content, and attempt to safeguard young social media users’ mental health and wellbeing. For advertisers, this shift means adapting to a more structured environment, but also offers an opportunity to engage with audiences more responsibly.
In July 2024, the Federal Trade Commission (FTC) took action against the social media platform NGL: ask me anything, banning its parent company and founders from offering their app to anyone under the age of 18. The FTC, along with the Los Angeles District Attorney’s Office, says the app unfairly and actively targeted children and teens to encourage sign ups, misrepresented the safeguards in place for filtering out harmful content, and used deceptive practices to lure young users into paying for subscriptions,
This represents the first time the FTC has ever banned minors from such a platform, but isn’t the first time the agency has tried to take action against a social media giant: In 2023, they proposed banning Meta from monetizing children and teens’ data. Though it is yet to be seen whether their groundbreaking decision on NGL: ask me anything will set a precedent for similar cases, it marks a significant shift in regulatory actions.
In late July 2024, the US Senate took decisive action to protect children’s safety online, overwhelmingly passing the Children and Teens’ Online Privacy Protection Act (COPPA 2.0) and the Kids Online Safety Act (KOSA). COPPA 2.0 prevents companies from collecting personal data from children under the age of 17 without consent, bans targeted advertising to children and teens, and makes it easy for parents to eliminate their children’s online personal information. KOSA, on the other hand, focuses primarily on social media platforms, requiring that they protect minors’ information, “disable addictive product features,” and make it easier for minors to opt out of personalized algorithms.
Despite garnering bipartisan support in the Senate, this legislation has yet to pass the House. However, the strong momentum behind these bills indicates a growing consensus on the need for enhanced protections for young internet users.
Beyond this federal-level action, many individual states are taking social media regulation into their own hands.
In 2023, several states passed legislation requiring age verification and parental consent for minors to access social media platforms. And in September 2024, a Texas law came into effect that creates requirements for social media platforms and other digital services providers aimed at protecting minors. Under this law, social media providers must clearly disclose how they use algorithms when sharing information and content with minors, create parental tools that allow them to supervise minors’ use of the platform, limit the collection and use of minors’ personal information, and more.
Additionally, New York recently passed two measures, The Stop Addictive Feeds Exploitation Act (SAFE Act) and the New York Child Data Protection Act, which significantly limit how social media companies can interact with minors. The SAFE Act prevents social media platforms from using algorithmic (and highly addictive) feeds on young users’ accounts, and the New York Child Data Protection Act restricts websites from collecting, using, sharing, or selling minors’ personal data, unless informed consent is given or it is crucial for the operation of the site.
Though most of these protective measures have come directly from leaders and regulators, some social media platforms are taking proactive steps to protect young audiences. TikTok, in the face of an impending ban in the US, recently announced they are restricting ad targeting for users under the age of 18. Other platforms like Facebook and Instagram already restrict certain types of targeting for teenage users, such as targeting by gender, locations smaller than cities, or interests, behaviors, and demographics.
This burst of regulatory action around social media isn’t happening in a vacuum: It’s part of a larger trend of regulators cracking down on the digital advertising industry. In recent years, the industry has faced heightened regulatory scrutiny, with significant developments in data privacy laws, as well as antitrust lawsuits against tech giants like Google and other types of new legislation aimed at protecting consumers.
Of course, advertisers must work with their legal teams to ensure compliance with regulations that apply to them, such as COPPA 2.0. But it’s also important for advertising leaders to keep track of new regulations focused specifically on social media platforms and providers. In understanding the sentiment and goals that guide these regulations, leaders will gain a valuable outlook on how social media advertising may develop in the coming years, as well as how the industry is evolving more generally when it comes to consumer safety, choice, and privacy.
The social media advertising landscape is changing, driven by a surge in regulation aimed at enhancing the safety and privacy of young internet users. Both federal and state-level actions underscore the increasing demand that social media platforms protect the minors who use their applications. This shift is not only transforming how such platforms operate, but also reshaping social media advertising more broadly.
For advertisers, understanding the changing regulatory landscape is essential to navigating the current social media advertising environment. As the social media regulatory framework continues to develop, advertising leaders who stay informed and agile will be better equipped to maintain compliance and understand the trajectory of how the digital advertising industry will develop and change in the coming years.
The story of signal loss in digital advertising has been a long and winding one, with several plot twists (we’re looking at you, Google). In the wake of the search giant’s monopolist’s latest announcement that it will not, in fact, deprecate third-party cookies in Chrome—instead planning to provide users with an “informed choice” experience—now is likely a particularly confusing time for many brands as they strive to understand the landscape of signal loss and what it means for their campaigns.
As most media agencies likely understand, signal loss will continue to increase despite Google’s U-turn, as a majority of Chrome users are expected to opt-out of a cookied browser experience. And, of course, these forthcoming changes aren’t the only source of signal loss: Digital advertisers have already lost targeting and tracking capabilities for Firefox and Safari users, faced further losses as a result of Apple’s App Tracking Transparency, and contended with a wave of privacy-minded digital advertising regulation.
As the advertising industry moves towards a more privacy-first model, it is critical for media agencies to coach and educate their clients to set them up for success. Maintaining proactive and transparent communication, working to optimize clients’ systems for collecting and executing on first-party data, and helping them adjust to new systems for cookieless measurement should be key aspects of any media agency’s plans.
When educating clients about signal loss, agency teams should prioritize proactive, transparent communication. In maintaining as much transparency as possible around how their team plans to address signal loss, agencies can ensure that clients maintain their desired levels of understanding and control over their media buys. And by communicating proactively about changes that will impact clients’ ability to target and measure their campaigns, agencies can ensure their clients aren’t caught off guard when more signals are lost and begin to impact performance.
Lauren Johnson, Client Strategy and Effectiveness Lead at Basis Technologies, says that specificity should be a key aspect of these conversations. “The more precise we can get with how specific aspects of signal loss impact a specific client in their specific campaign,” Johnson says, “the more successful we’ll be in evolving the ways that our clients think so that they’ll be set up for success.”
Johnson recommends that agency leaders ensure their team members are prepared to come to each client and say, “These are the exact ways in which we’ve lost and are losing signals. Here’s exactly how that signal loss is impacting targeting and measurement in this specific buy. And here are the new approaches we’d like to test for targeting and measuring this campaign.’”
To provide this type of communication consistently across an agency’s clients, leaders can create a signal loss POV—a document that lays out the agency’s stance on and approach to signal loss—and share it out with their team. This helps to ensure that everyone, including more junior-level employees, can speak effectively to an agency’s signal loss plan.
Strong communication (or even overcommunication) and re-iteration of this information will be key to effectively educating clients over time. In keeping brands fully informed, agencies can build trust with clients and support client retention during a particularly tumultuous time for both agency-client relations and the advertising industry as a whole.
As advertisers know well, first-party data is currently the best replacement for third-party data: Not only is it privacy-friendly, but it also provides a high degree of precision in understanding an audience. As such, helping clients better collect, unify, organize, and execute on their first-party data must continue to be a top priority for media agencies.
“Often, the biggest struggles for brands when it comes to first-party data are (1) the ability to scale it for activation, and (2) understanding the value it brings to other aspects of campaign planning,” says Kelly Boyle, Group VP of Client Strategy and Insights at Basis Technologies.
Agencies are well positioned to help their clients address these problems—for example, by proposing a media plan with an objective of collecting first-party data. The best approaches here will vary by industry: A restaurant brand, for instance, might focus on collecting first-party data via loyalty programs and reservation systems, whereas a B2B brand might focus on collecting it by encouraging prospects to fill out a form to access a piece of relevant content, such as a report or whitepaper.
Agencies can also support their clients with the critical task of unifying their first-party data. This means taking stock of the various places where a clients’ first-party data is stored—many brands’ first-party data is spread across a variety of different platforms and third-party vendors—and educating them about how solutions like CRMs and CDPs can help to centralize, standardize, and execute on that data. For example, agencies could use a CDP storing a brand’s first-party data to gain a view of their consumers’ buying journey and better understand what tactics and touchpoints are most effective at leading to conversions. Then, in the planning stage, they can heavy-up spending on those tactics and touchpoints to increase conversions.
Boyle notes that first-party data can also help to inform campaign planning, which is growing increasingly important as advertisers lose signals. “Signal loss increases the importance of strategy, planning, and upfront research,” says Boyle. “If we’re less able to go after our audience based on cookies and other lost signals, then we must have a better understanding of the client’s core audience—what they care about, how they behave, etc.—in the planning stage, and use that to inform our campaigns.”
When unified and organized properly, first-party data can provide advertisers with valuable consumer information that they can use in the planning stage to craft more strategic campaigns.
Finally, media agencies must help their clients transition away from the current status quo of third-party cookie-based measurement and attribution solutions. A big part of this task will be resetting expectations with those proactive, transparent communications plans: Clients are used to being able to easily pull detailed, cookie-based reports, but as signal loss intensifies, the ways advertisers measure their campaigns will look significantly different.
In addition to setting new expectations around measurement, agencies must help their clients adjust to a new, more privacy-friendly measurement stack. This means aligning all the different data sources that can help tell a client’s business story amidst signal loss, such as the client’s sales data, first-party data, brand lift studies, cookieless multi-touch attribution tools, and any other kinds of measurement tools or partners that a client or agency has access to. Of course, agencies can continue to place third-party pixels for clients where they can, but as signal loss increases, that pixel data won’t be able to tell a holistic story about what a brand’s campaign investment is doing for them. As such, advertisers should complement pixel data with other, cookieless measurement solutions, and proactively communicate to their clients about what these solutions offer.
What alternative measurement approaches might media agencies want to explore with their clients? For one, marketing mix modeling (MMM) is making a resurgence. While MMMs used to be major undertakings that could often only be done on an annual basis, there are many new players in the space offering solutions that are more turnkey. Going into 2024, more than half of US brands and agencies reported that they would be somewhat or significantly more focused on MMM this year.
Attention metrics are another KPI that forward-looking marketers are integrating into their measurement approaches. “Research shows that attention drives brand outcomes,” says Boyle. “Understanding the strengths of media placements in capturing attention and measuring that impact on short- and long-term metrics gives marketers another lever to guide marketing decisions.” Given the benefits they offer, it makes sense that just under half of US brands and agencies say they will be somewhat or significantly more focused on attention metrics in 2024.
Lastly, agencies should make ongoing testing a core competency. This means proactively building thoughtful learning agendas that help prioritize key areas where testing supports both client and agency curiosities about performance, as well as designing appropriate experiments that support those learning goals. “At Basis, we aim to group our tests around learning topics that range from audience to attention,” says Johnson. “With these foundations in place, we prioritize channel-specific tests for audience learnings, creative findings, ad quality, and so on. Testing is powerful tool for agencies to arm their clients with critical data points for how their media investment supports their business.”
It is especially important to begin testing now (if you haven’t already), as advertisers will have fewer and fewer signals to test with moving forward. Johnson recommends that advertising teams ask themselves, “How can we implement testing to understand incrementality now, so that when we lose even more signals, we can expect that incrementality is happening—because we’ve tested and proven it—even if we don't see it in our key metrics from our ad server?”
Overall, the onus is on agencies to bring those new measurement solutions to their clients and to begin testing and learning with them as soon as possible. Marketers can approach these conversations by asking their clients, “Have you thought about [X measurement solution]?” or by telling them that they have a new solution they’d like to explore on the client’s behalf. Agencies must also strengthen their own cookieless measurement stacks so that they can provide the best and most holistic approaches possible as signal loss increases.
With many signals already lost and more to come once Google makes its planned changes in Chrome, the time for agencies to set new expectations and help prepare their clients for increased signal loss is now.
As privacy regulations tighten and cookie-based data dwindles, agencies that prioritize proactive and transparent client communication and education, and coach their clients on how to optimize their first-party data and measurement stacks for a world with significantly fewer cookie-based signals, will be best prepared for what lies ahead. It is a critical time for agencies to serve as strategic advisors to their clients—and those who do it right will see the added benefit of increased client trust and retention.
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Of course, signal loss isn’t the only challenge facing media agencies: Financial pressures, media fragmentation, and inefficient processes are just a few of the other factors pushing agencies to evolve. To learn more about how marketing professionals from agencies across the US feel about the problems and opportunities shaping their present and their future, check out our 2024 Advertising Agency Report.
In the context of today’s quickly evolving advertising landscape, agencies must keep pace with the rapid growth of digital media and adtech to meet their clients' needs. Brands are demanding deeper insights and expertise around which platforms to invest in, how to leverage first-party data for greater impact, and more.
In this episode, John Lods, CEO of the agency Arm Candy, shares his thoughts on navigating these complexities. Together with host Noor Naseer, Lods explores how agencies can stay ahead of the curve, evaluate new technologies, and offer meaningful, data-driven advice that sets their clients up for success.
It’s nearly impossible for marketers to get through a day without encountering a conversation, article, or social post about AI—how it can help businesses drive revenue, how governments may regulate its use, how it might transform the search landscape, its environmental impact, and more. Most advertisers feel the technology will revolutionize our industry, with a 2024 Basis survey finding that 87.9% of marketers believe AI will radically transform digital advertising in the next three to five years. However, the newness of generative AI, the risks associated with it, and the influx of AI-driven applications and tools flooding the market can make crafting an adoption strategy a daunting task.
Indeed, the prominence of AI in today’s marketing conversations is in part due to advertising leaders' thirst for guidance on how to effectively adopt the technology, particularly when it comes to paid solutions. Most brands and agencies recognize the significant potential for cost and time efficiencies offered by AI, and that early adoption may provide a competitive edge and drive success for their businesses as the industry transforms. However, they’re also wary of the risks associated with AI—particularly generative AI—as well as the trend of AI-washing, and know they must select paid solutions with care.
The tension between this desire to adopt and uncertainty around how to adopt is evident in the current rates of industry use and investment. While an overwhelming 92% of US advertising agencies are currently using generative AI, exceeding the general business population, only 44% of marketers and advertisers say their employers currently pay for generative AI tools.
These statistics demonstrate that the industry is in a transition period, with many marketing teams using free solutions like ChatGPT as well as older AI-driven technologies that have already been integrated into their work (such as programmatic advertising), but still figuring out how to navigate the adoption of newer paid AI solutions. To make informed investment decisions about these types of solutions, marketing leaders must understand AI’s risks as well as how their peers are approaching paid AI tools.
Marketing teams who have yet to invest in paid AI solutions seem to have some common concerns about the technology, mostly stemming from its risks.
A 2023 Gartner survey found that concerns around inaccuracies and bias in AI-driven software and AI-generated content were the top reasons marketing leaders were hesitant to onboard new AI solutions, along with concerns around relying too heavily on the emerging technology. Marketers are also concerned with how AI-generated content will land with consumers: 60.3% of industry professionals feel that consumers will find a brand less authentic if its marketing and advertising efforts include AI-generated content.
Many of these concerns intensified over the past year as advertisers witnessed controversies related to AI-generated content making headlines. Early in 2024, advertisers saw the risks of bias and inaccuracies in AI-generated content play out when Google had to take its Gemini AI tool offline after it portrayed white historical figures, such as the US Founding Fathers and German soldiers from the Nazi era, as people of color. Ironically, the tool generated the content because of safeguards Google developers put in place to reduce bias, which inadvertently resulted in offensive inaccuracies. And in June, advertisers saw how Toys“R”Us’ AI-generated commercial was met with both backlash from creatives and a drop in consumer sentiment. These well-publicized controversies have likely made many advertisers a bit more wary of genAI’s content creation abilities.
Considering the very real risks associated with AI, it’s critical for marketing leaders to understand what safeguards they can implement to mitigate liabilities associated with any AI tools they consider adopting. For example: Human staff should always review all AI-generated content for bias and inaccuracies before it goes live, legal teams should review any AI solutions under consideration for possible data privacy and security threats before they’re onboarded, and some brands may even choose to forego releasing fully AI-generated advertisements given developments like the consumer response to the Toys“R”Us commercial.
To a majority of marketing teams, AI’s risks still appear to be outweighed by its alluring potential benefits, and budgets are increasingly making room for new paid AI solutions. But with so many new tools and applications on the market, how are advertising leaders prioritizing those tools in which they feel confident enough in to invest?
One August 2023 survey found that data analysis was most commonly listed as a focus for the next 12 months for US and Canadian CMOs, followed by strategy, creative, and content development for media use and audience targeting and segmentation. Digital marketing teams have already benefited from AI’s data analysis capabilities for many years, as it drives programmatic advertising and programmatic optimization tactics like bid shading and machine learning optimization. And AI tools that can assist in the organization and synthesis of first-party data for audience targeting and segmentation are helping advertisers grapple with signal loss and the shift towards a privacy-first advertising model.
Marketing teams are also investing in AI to increase efficiency and streamline workflows. Sixty-one percent of industry professionals say their organization has invested in technology to automate or streamline processes in the past year, and 66% say their organization plans to invest in the technology in the coming year. While not all these tools are AI-driven, AI is opening many new opportunities for workflow automation and streamlining. For example, marketing teams are leveraging AI copilots that work alongside their tech stacks to streamline operations, as well as advertising platforms equipped with digital advertising automation features that simplify various aspects of the campaign process.
Because the technology is so new, most marketing teams are still in the process of optimizing their generative AI usage and investments. And they’re not alone: Only 11% of global companies across industries are using generative AI at scale.
More than 90% of marketers and advertisers say they use generative AI as part of their digital marketing efforts, primarily leveraging the technology to ideate/brainstorm and to draft content/creative, as well as for research and optimization purposes. While AI-led ideation and brainstorming are relatively risk-free, using genAI to draft content and creative comes with distinct risks, and marketers should ensure they are setting up fact checking and quality control systems to avoid AI-generated bias and inaccuracies in their marketing content.
Additionally, though unpaid tools are the most popular, many marketers are recognizing that premium tools offer can more than their free counterpoints. As marketers continue to explore and expand their use of generative AI, balancing its potential benefits with careful management of risks will be crucial for maximizing effectiveness and achieving strategic goals.
Ultimately, while most marketing teams are still working through their approach to newer, paid AI tools, they are readily embracing free tools like ChatGPT. Due to the risks associated with AI, marketing teams will want to invest meaningful time and effort in evaluating which paid solutions will drive the most success for their teams, and what protections they must put in place to use them safely. This will require a significant time and energy investment up-front—but doing so may well help organizations to get ahead of their competitors in the long run.
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Want to learn more about how advertisers are approaching AI, as well as how they’re thinking and feeling about an AI-driven future? Get all the latest insights in our report, AI and the Future of Marketing.
As AI revolutionizes how advertisers work, media agencies are adopting the technology to drive revenue amidst slashed client budgets and shrinking margins.
Agency leaders overwhelmingly feel that AI will have a significant and positive impact on the advertising industry, with 82.4% believing that AI will be the most influential trend to shape digital advertising in the next ten years. At the same time, media agencies have a bit of a leg up when it comes to familiarity with AI, given that they’ve relied on the technology for longer than many other players in the industry via programmatic advertising (and programmatic optimization tactics like bid shading and machine learning optimization.)
As AI develops at a rapid pace, there are an ever-expanding number of ways agencies can employ the technology to save time and increase efficiency. To make the most of AI for driving revenue and staying competitive, media agencies may want to pay particular attention to AI-powered opportunities supporting campaign planning and optimization.
One of AI’s most meaningful impacts on marketing is its ability to organize and analyze huge amounts of data in a fraction of the time it would take for a human to do so. This AI-powered capability has already revolutionized the media buying space, most notably through the advent of programmatic advertising. Today, AI is growing increasingly effective at pulling insights from audience and historical campaign data to help marketing teams craft more impactful campaign strategies. And generative AI is opening new possibilities for supporting and accelerating the campaign planning process, with 6.4% of marketers reporting that they use generative AI for tasks related to media buying strategy, and a flurry of new tools emerging that look to expand that number significantly.
AI-driven social listening, for example, is becoming table stakes for marketers. Manually sifting through social media to gain insights on the top concerns of consumers looking for a certain type of product takes hours—but AI-powered social listening tools can get it done in a matter of minutes. Using these tools, advertisers can easily track their competitors online as well as quickly generate clear insights into consumer sentiments, preferences, and trends. They can then use those insights in the planning process to ensure their campaigns are attuned to both competitor activity and consumer sentiment and behavior. For example, Fulham Football Club uses social listening to gain a more segmented and nuanced understanding of their fanbase according to their online activity, which opens up opportunities to target those segments with personalized messaging. This heightened attunement to their audience helps Fulham spend more efficiently, which in turn drives revenue.
Moreover, these types of tools aren’t exclusive to social—AI listening tools can pull data from search touchpoints and synthesize data from consumer reviews as well.
Beyond customer listening, media agencies and their technology partners are finding more and more ways to refine campaign planning processes using AI’s data synthesis capabilities. For example, some advertising platforms can employ AI to synthesize data from all the campaigns that run within them, and provide advertisers with insights into performance benchmarks and budget distribution trends amongst marketing teams working in the same vertical. AI can also accelerate the forecasting process, enabling advertisers to predict available inventory based on specific criteria and implement new strategies using the precise targeting parameters from their forecasts.
Media agencies are also mitigating signal loss by using technologies like CDPs equipped with AI to quickly gather, standardize, and leverage consumer data to pull audience insights and track the customer journey to plan their campaigns more strategically as well.
Overall, leveraging AI to implement audience and competitor insights in the planning process can help media agencies save time and craft data-driven strategies that are finely attuned to their target audiences’ needs and preferences as well as market trends, helping them better drive ROAS and deliver revenue for their clients.
AI-powered campaign optimization has been around for a while, but new innovations in this area offer media agencies a variety of ways to allocate campaign assets and budgets more effectively. In fact, AI is moving the advertising industry closer to a world where teams will spend very little time on manual campaign optimization, freeing them up for more strategic and fulfilling tasks.
Tools like bid shading and group budget optimization, which automatically make campaign adjustments to improve win rates and drive increased ROAS, have begun this process and are growing more widely adopted. As AI continues to progress, more tools such as these are expected to emerge and help advertisers drive revenue by allocating their dollars towards the tactics, channels, and properties where they’re most impactful.
Major adtech partners are also rolling out offerings that include AI-driven campaign optimization features, such as Google’s Performance Max and Meta’s Advantage+. However, these walled-garden offerings don’t come without trade-offs—the most significant one being the transparency media buyers are used to. While it’s important for advertisers to test and learn on these tools, media teams must assess whether they are actually accomplishing their goals, rather than setting and forgetting their campaigns.
Dynamic creative optimization (DCO) is another developing area that’s helping media teams save time and spend more effectively, allowing media teams to serve high volumes of diverse creative that’s personalized to specific audience segments, which makes it more likely for ads to resonate with more consumers. One Jack in the Box campaign, for example, used DCO to generate 135 different ad variations and saw a whopping 85% increase in CTR compared to the campaign’s benchmark.
DCO not only reduces time spent on manual creative optimizations, but also provides media teams with extensive insights on how all those creative variations perform, allowing them to tweak their strategies based on those learnings. The speed and efficiency with which AI can process and analyze data, and generate new content based on its findings, will doubtless enhance creative optimization technologies moving forward: Creative optimization was marketers’ third-most popular response when asked what part of the digital marketing process they expect to be most impacted by AI.
These are just a few of the many ways in which AI is helping advertisers to automate and speed up the campaign optimization process, and there are plenty more coming down the line as the technology advances. When used effectively (and carefully monitored by human teams), these tools hold tremendous promise for increasing efficiency and personalization—and thus for driving revenue for media agencies and their clients.
With over half of marketing leaders believing that AI will make marketers significantly more efficient at their jobs within the next three-to-five years, AI-driven workflow automation is another major area of opportunity for media agencies.
Indeed, all the AI-driven campaign planning and optimization functionality detailed above can help contribute to overall workflow automation, in that they automate parts of the campaign process and reduce manual workloads for marketing teams. But there are other applications as well: For example, some agencies are turning to AI copilots to automate their workflows. AI-driven copilots are LLMs that are integrated into existing tools and platforms and collaborate with the marketers using them. They improve efficiency and accelerate specific workflows, such as by detecting inconsistencies across different media formats.
By adopting AI-driven tools throughout the campaign life cycle that automate manual tasks, advertising leaders can streamline their workflows and save time. This is an application that’s been of interest to marketing organizations for some time already, with 61% of marketers reporting that their organization has invested in technology to automate or streamline processes in the past year. And adoption is set to increase, with 66% of marketers saying their organizations have plans to invest in this kind of technology within the next year.
In an era where media fragmentation, signal loss, high turnover rates, and many other factors are making agency work more difficult for marketing professionals, AI’s ability to automate manual tasks and streamline workflows is one of its major benefits for media agencies looking to save time, drive efficiency, and increase revenue.
Media agencies have a unique opportunity to leverage AI to drive revenue and enhance efficiency, at a time when such results are critically needed across the agency landscape. AI-powered planning and optimization tools are two areas that offer particularly strong benefits.
Additionally, the AI-driven campaign planning and optimization functionality detailed above can pair with workflow automation technology to help drive wider agency efficiency, reducing manual workloads for teams across the organization.
In exploring and integrating these types of AI into their operations, media agencies can open new avenues for growth and innovation, and position themselves at the forefront of an increasingly AI-driven industry.
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Curious to learn more about how advertisers are navigating AI adoption? Get all the latest insights in our report, AI and the Future of Marketing.
It’s been less than two years since OpenAI introduced the public to ChatGPT and officially ushered in the generative AI era, and the technology has quickly become the hottest topic in all of marketing.
Agencies and in-house teams have rushed to begin using new AI solutions in pursuit of greater efficiency, deeper insights, and creative inspiration, while adtech and martech companies have eagerly promoted their own AI capabilities in the hopes of cashing in on the buzz.
Amidst this flurry of excitement and activity around AI’s potential, marketers and advertisers have begun facing a steady increase in pressure to demonstrate the impact of these new tools. Is AI, in fact, driving new levels of efficiency and facilitating stronger work? Are industry professionals still as excited about this still-emerging tech as they were a year ago, during its relative infancy? Do its many much-touted upsides outweigh a laundry list of potential risk factors? And how much of this AI hype cycle is just that: hype?
For this report, we surveyed marketing and advertising professionals from top agencies, brands, and publishers to see how marketers are using and feel about AI today, and to explore how the technology is poised to shape the industry going forward.
Findings include:
Throughout programmatic advertising history, brands have often entrusted its execution to agencies and trading desks. But today, in a world of high consumer expectations and constantly shifting market dynamics, many brands are searching for an alternative to the traditional brand-agency model as they look to gain greater transparency into their media buys, more holistic control over their data, and greater assurance of compliance with privacy regulations.
The result: programmatic in-housing.
Numerous heavy hitters have already brought elements of their programmatic operations in-house, including Marriott, Colgate-Palmolive, Procter & Gamble, Coca-Cola, Bayer, Wayfair, American Express, Unilever, Anheuser-Busch, Netflix, Target, Deutsche Telekom, and Ally Financial. Now, as those groundbreaking programs mature and their outcomes come into view, more brand advertising leaders are peering over with interest and beginning to question whether they, too, should take some—or total—control of their own programmatic business.
With many different levels of programmatic in-housing available, as well as a variety of potential benefits and challenges, leaders must carefully consider which—if any—in-housing option is best for their brand and team. Whether opting for full control, a hybrid approach, or a path to self-service, choosing the right in-housing model can significantly impact both campaign performance and operational efficiency.
The first adopters of in-house programmatic media buying were mostly digital natives like Netflix and Target—brands boasting rich, voluminous first-party data that gave them a head start on the process. Over time, though, the types of companies in-housing have become more diversified. And, they have done so with varying degrees of success.
Those who tried and failed often did so because they underestimated the logistical hurdles involved and became too fixated on the stereotype that in-housing is an all-or-nothing play—just look at Vodafone or Prudential. But this idea of agency versus in-house programmatic as a dichotomy is outdated, as it doesn’t suit the needs of modern brands. As marketing leaders learn more about the intricacies behind this digital transformation, a whole range of in-house programmatic manifestations are emerging, with brands and agencies breaking new ground and creating new operational frameworks as their relationships evolve. Indeed, in-housing programmatic is far from a death knell for agencies—brands still lean heavily on their external partners, and agency investments still command more than 20% of total marketing budgets. Understanding market logistics and maximizing technology-driven optimization opportunities requires as much critical insight as possible, and agencies remain ideally positioned to provide that guidance.
When it comes to programmatic in-housing, one thing is clear: Where we were five years ago looks very different from today, and where we are today will look very different five years from now.
While it is difficult to neatly classify the numerous variations of in-housing—especially considering all the factors involved—here are four of the most common arrangements:
This is the quintessential in-housing set-up, where an adtech stack sits within a brand organization in tandem with media strategy, ad operations, data management, and campaign stewardship. An in-house operation that looks like this is still relatively uncommon, given the major commitment of time, resources, and internal talent marketing organizations need to launch, maintain, and refine it.
However, despite the complexities involved, the popularity of programmatic in-housing is rising, and brands are building relationships with the technology platforms and the talent they need for in-housing to succeed. Case in point: 66% of brands say they have contracts with technology providers like DSPs or verification partners, and two-thirds also say they have “hands on keyboards” doing the actual work.
For brands going down this route, the classic approach involves forming an internal agency-style trading desk and equipping them with a demand side platform (DSP). Going all-in can be a monumental task, but with the right preparation, planning, and implementation, the returns are significant. Pharmaceuticals giant Bayer, which first began developing their in-housing operations back in 2017, was reportedly able to reduce its programmatic buying costs by over $10 million in just the first six weeks. The company has also pointed to a number of additional in-housing related benefits, including ownership of their tech stacks, data, and dashboards.
Bayer’s success presents a microcosm of the upsides that come from in-housing programmatic. Transparency is a major one: With data privacy at the front and center of public consciousness, it is paramount that brands know exactly what their advertising is doing.
Despite progress over the last few years, many agencies still fall short on providing real visibility into the digital ad buying process. This lack of transparency, combined with increased control and potential cost savings, drives many brand leaders to pursue in-housing. Indeed, gaining access to unfiltered campaign performance data empowers brands to do a host of valuable things, including:
The fact that Bayer was able to save $10+ million almost immediately after in-housing its programmatic is more the exception than the rule. Brands often see cost benefits over time as they save on agency fees, including fixed rates, platform costs, and media expenses. Internal programmatic teams can concentrate solely on maximizing profitability for their brand. In contrast, agency partners balance this goal with their own revenue needs and margin requirements. Going all-in on in-housing removes these additional layers, potentially streamlining the path to increased profitability.
Then there is the matter of cost efficiencies through better campaign execution. The switch in-house ultimately enables brands to invest in—and nurture—talent within their marketing organization. While outsourced staffing solutions can provide some great results, they may not be able to optimize the consumer journey with the same granularity as an in-house staffer who knows the brand through and through.
Now, there may be many upsides to in-housing, but brand leaders should not underestimate the organizational, technological, and cultural challenges involved in this digital transformation.
For starters, programmatic in-housing takes time. Ideally, the transition should be a well-researched, deliberate journey with calculated investment in the right resources and tech over a period of many months, if not years. From the outset, those leading the change need to ensure they involve a wide range of internal stakeholders from all corners of their organization, including finance, legal, product, and IT. All these teams will have either a direct or indirect influence on the program’s success, so it is important to listen to their input on the process and get their buy-in before proceeding. What are the security implications, for example, from an IT perspective? How much budget is available for the required tools? How are privacy regulations going to be respected? What are the data challenges from a CRM standpoint? A multitude of questions must be answered, so the more support earned from across the organization, the better.
In sum, programmatic in-housing is not something you can just do on a whim, and it is critical to set the expectation internally that transformational results are unlikely to arrive immediately. Brands accustomed to focusing on short-to-medium term initiatives and goals must learn to adapt to protracted, longer-term processes and a new way of working if they want to successfully in-house programmatic.
Of course, most marketing leaders are thinking hard about how to wrangle more out of their advertising dollars, and many are concluding that they need outside help and guidance to do so successfully. At the same time, many media agencies are adopting new structures—reorganizing in a way that makes it easier to offer on-demand services and step into a more advisory role for clients that seek to in-house some of their programmatic budgets. It is a development that makes sense for both parties: Agencies have extensive experience in what works and what doesn’t in the programmatic sphere—not to mention the tools necessary for executing on programmatic media buys—and clients need to tap into those resources as they bring some of that operational activity inside their own walls.
This, in essence, is what the hybrid in-housing model is all about: An in-house marketing team tees up the overarching strategy before consulting with an agency on how to deliver it in the market. Sometimes, this will lead to the agency assuming the day-to-day responsibilities of implementing the plan and pulling the levers, and other times it will lead to the advertiser doing the work with their own platform under the agency’s direction.
The latter scenario is the one that more brands are pursuing, as it ultimately merges many of the best aspects of both in-housing and outsourcing. With hybrid in-housing, brands can:
An Association of National Advertisers study frames the hybrid in-housing trend in numerical terms, finding that, in 2023, only 32% of marketers had in-house programmatic capabilities, and just 17% of the remaining respondents were considering adding those capabilities within the next year. This highlights just how important agencies remain to brands. Programmatic advertising can be a complex venture, and there are still many marketing organizations that struggle to identify the right systems to help them better engage their audiences. The hybrid option alleviates that pressure and empowers brands to take whatever baby steps they want.
Option number three: fully outsourcing, a route that many brands still prefer despite the myriad benefits that in-housing offers. It represents a great option for those who don’t have the resources to build an internal programmatic team and all the costs that come with it—think upfront licensing fees, salaries, training, etc.
From a brand perspective, the main drawbacks to contracting out all aspects of programmatic advertising are the lack of control they will enjoy over their consumer data and the limited transparency they will get into media performance. To address this, however, some agencies are recalibrating with a dynamic that is helping them win more programmatic business: the holding company model solution. Indeed, a growing number of agency pitches today feature purpose-built services supported by their holding company’s dedicated data and analytics divisions. It is a move designed to negate the potential for brand-agency conflicts, with these specialty customer intelligence orgs brought into the equation to fuel better communications planning and extract deeper insights into the brand’s marketing efficacy. It is a symbol of how some agencies are responding to the moment and the mood of the industry, becoming nimbler and reengineering their capabilities to stay attractive to brands.
One key area where agencies retain an upper hand in the in-housing/outsourcing calculation is talent. Managing and optimizing programmatic media is a complex art, and advertisers considering independence from agencies will need a glut of staff additions to ensure they are doing things right—a programmatic manager, a data analyst, and a DSP operator, to name but a few.
The problem facing brand-side HR departments today is actually filling these positions—the labor market in this field is desperately tight, job titles are evolving, and, to make matters tougher, the available talent often take opportunities at agencies over brands because they can offer better career progression, opportunities to diversify, and ongoing learning. Within the four walls of a brand, those things can be difficult to come by, considering there is only one program to service and (most likely) fewer opportunities to influence overall strategy.
No player in the programmatic space can expect to be successful without the right people doing the bidding, so this talent shortage is a pressing concern for brands, often leaving them with no choice but to look to external partners.
Likely a concept that many marketing leaders may not even be familiar with, the path to self-service model is aimed at brands that desire greater control over specialized programmatic functions but may be kept in check by internal resource limitations.
The premise is simple: Marketing organizations tap dedicated in-housing consultants to onboard new technology at a pace that makes sense for their evolving business. Then, as the client gets more comfortable with each aspect of the programmatic ecosystem, the consultants introduce more capabilities and training modules to nurture in-house teams to the point where they can manage everything independently. This is an option that may suit small- to medium-sized teams who have been wary of in-housing programmatic media buying because they felt it too complex and/or tedious for them to manage alone. But with the proper training and strategists on standby, teams can maintain internal operations with far greater ease.
Here is what a typical path to self-service might look like over six months:
This path to self-service blueprint can ultimately help brand leaders ensure their systems, campaigns, and data consolidation practices are set up effectively from the outset, allowing their teams to mitigate many of the issues that can bring in-housing plans grinding to a halt.
From platforms to people to processes and everything in between, with so many factors to weigh when considering in-housing programmatic ad buying, where does one start? Here are a few considerations for marketing leaders looking into in-housing, whether they’re at the RFP stage or just the “I was thinking about…” step:
1. Evaluate “why” this is important to your organization. Is your organization looking to cut costs? Hit a business objective? Gain more operational control? Identifying your in-housing “why” will allow you to understand your needs, wants, limitations, and what you’re trying to change. It also creates space for a feasibility check and an objective session to help move from problem to solution.
2. Understand the landscape. Nearly a decade ago, in-housing came into vogue thanks to tactics like RTB. However, during the height of the COVID-19 pandemic, long-term contracts and full-time employees became more of a burden as businesses just tried to survive. If you do consider in-housing, it’s important to consider it in context of the larger marketing and economic landscapes to ensure that now is the right time to take the first steps.
3. Review your readiness. When it comes to technology, are you comfortable vetting new options to streamline how you use your existing tech stack? In terms of people, are you well-positioned to add, retain, or replace talent? As far as strategy, how does your first-party data look? How confident are you in making real-time optimizations to live campaigns? Answering these critical questions can uncover your gaps as well as highlight opportunities for process and personnel improvements.
4. Bring in the right stakeholders. As noted earlier, organizations that wish to bring their programmatic adtech stacks in-house—even if an agency might still operate and manage it—should invite HR, IT, CRM specialists, finance, legal, and product to early conversations, as any of these people may have direct or indirect influence on, or use of, the tools at hand.
5. Bite off only what you can chew. Even though it may save money in the long run, in-housing programmatic can be an expensive venture: It takes time, it takes energy, it can be costly, and it can be disruptive to the status quo for many organizations. Taking it on in small chunks can help match a company’s tolerance level for each of those considerations, whether that be in the form of a hybrid model or a path to self-service.
Bringing programmatic media buying in-house is a significant undertaking. The whole operation must be built on a foundation of organized data, deliberate processes, capable tools, and skillful talent. As programmatic’s prominence rises and privacy continues to be at the forefront for consumers and regulators alike, more marketing leaders may want to in-house their programmatic advertising… But, all too often, they don’t know where to begin.
The good news that is a host of options exist, from going all-in, to a hybrid approach where brands and agencies share responsibilities, to full outsourcing, to going down a path to self-service. Overall, in-housing has many benefits, the biggest being the ability to obtain greater transparency into media buys and secure more holistic control over data, not to mention the possibility of significant long-term cost savings. And either way, agencies still have an important role to play in the media buying ecosystem—whether as valued partners or as critical consultants.
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If you’re starting to think about making changes to your organization’s programmatic advertising strategy and are looking for some guidance, our Programmatic Readiness Quiz can help! In just three minutes, you’ll discover whether outsourcing, hybrid, or in-house programmatic ad buying is the best path for achieving your team's goals.
