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Key Takeaways:
You need to get started using programmatic buying tools, but you’ve never done it before, and you don’t know where to begin. Join the club. We get it. It’s the same reason we haven’t learned to cook for ourselves yet.
Here’s the good news: We’ve got experts at Basis who know the ins and outs of programmatic advertising. All you have to do is ask the right questions. Lucky for you, we’ve asked the basic questions and we’ve come equipped with answers—and, lucky for us, we've been assured repeatedly that there is no such thing as a dumb question.
To start: Programmatic is a very broad term. Simply put, it’s technology that automates digital media buying. This can include automating anything from rate negotiation and campaign set up to optimizations and actualizations. One of the primary buying tools you have at your disposal is a DSP.
A demand side platform (DSP) is an automated ad buying platform, where advertisers and agencies go to purchase digital ad inventory. Examples of ad inventory include banner ads on websites, mobile ads on apps and the mobile web, and in-stream video. DSPs are integrated into multiple ad exchanges.
Popular examples of DSPs include The Trade Desk, Google DV360, Amazon DSP, and Basis DSP.
DSPs use real-time bidding to purchase ad impressions automatically. Here's how the process works:
An SSP is not the same thing as a DSP, but it is similar in concept.
Supply-side platforms, or sell-side platforms (SSPs), facilitate the sale of publisher inventory through an ad exchange. SSPs offer services such as minimum bid requirements in order for the publisher to maximize how much their ad space sells for. The difference is that DSPs are for marketers and SSPs are for publishers. SSPs, like DSPs, are plugged into multiple ad exchanges.
Think of the ad exchange as the "go-between" in the automated buying world. An ad exchange is a digital marketplace that enables advertisers and publishers to buy and sell advertising space via real-time bidding (RTB). Real-time bidding (RTB) is the process of buying and selling ad impressions through instantaneous auctions that occur in milliseconds. The ad exchange announces each impression—with the inventory flowing through DSPs and SSPs—in real time and asks buyers if they are interested in buying said impression and at which price
| Platform | Definition | Who Uses It |
|---|---|---|
| DSP (Demand-Side Platform) | Automated platform for buying digital ad inventory | Advertisers and agencies |
| SSP (Supply-Side Platform) | Platform that helps publishers sell their ad inventory | Publishers |
| Ad Exchange | Digital marketplace where DSPs and SSPs connect to buy and sell ads via real-time bidding | Both buyers and sellers |
In order to understand why DSPs matter, it's important to remember where the need came from and how the ad industry operated before automated buying. Historically, if you were a media buyer at an ad agency, the buying process was facilitated through human beings—it was you (the advertisers), the publishers (website where ad will appear), an audience (the viewer of the ad), and a bunch of spreadsheets and emails going back and forth negotiating prices. This process was complicated, time-consuming, and often error-prone. DSPs allow advertisers and agencies to buy across a lot of sites at the same time—and all of this is done instantly and efficiently, usually before the webpage loads.
There are many DSPs in the programmatic world to choose from. Choosing the right DSP for you depends on a number of factors.
DSP Evaluation Checklist:
Some DSPs come with a full team of experts, offering you everything from full-service to self-service and everything in between. With Basis DSP, you'll start with a three-month platform training program, offering you an overview of programmatic, a walk-through of the interface, and best practices for campaign creation and optimization. Ongoing support is available in the form of a customer success manager and resources to keep you informed—like new feature webinars, best practice guides, and industry-leading research reports.
Learn more about programmatic advertising with Basis.
Sean Duggan and Kristin Battersby from the Basis Candidates & Causes Team host a deep dive into the political audio advertising marketplace heading into the 2026 midterm elections. They share insights and best practices for how to effectively leverage audio—including streaming, podcasting and more—to reach voters and win this November.
Key takeaways:
Commerce media has all the characteristics of a digital advertising channel that every brand is searching for.
What began with retailers has expanded into travel, payments, and other sectors rich in transactional data—empowering advertisers to connect with targeted audiences in relevant moments with personalized messages.
Because commerce media is powered by first-party data, those audiences, moments, and messages are as targeted, relevant, and personalized as possible. A growing number of commerce media platforms also enable a sophisticated omnichannel approach, allowing advertisers to capture audience attention in saturated digital environments.
While non-retail commerce media is still nascent, its swift evolution is opening up new, less-saturated channels for marketers to reach high-intent audiences. In fact, non-retail commerce media is growing even faster than retail media, with ad spend forecast to surpass $100 billion by 2028. It’s a space where innovation—particularly AI-related innovation—is driving rapid expansion.
Considering all this, now is the time for advertising leaders in every sector to get ahead of the curve by understanding the forces driving commerce media’s growth as well as how to leverage the channel strategically.
Marketing teams today are struggling with signal loss, a lack of data readiness, and media fragmentation—all of which make it harder to deliver personalized, timely messages and craft the coordinated omnichannel media strategies that are key to connecting with consumers in today’s crowded digital environment. At the same time, economic volatility is constraining marketing budgets and putting marketing leaders under increased pressure to prove out the value of their investments.
In this environment, commerce media is well-positioned to take on a larger role in marketing budgets. “Commerce media is growing more accessible and attractive to brands outside of CPG and retail as the supply side continues to grow through the collection, organization, and availability of first-party data,” says Jane Frye, VP of Integrated Client Solutions at Basis. And the reliability, accuracy, and abundance of this data make it possible for advertisers to use commerce media for personalization at scale.
There are also increasing opportunities for advertisers to use that high-quality data for audience targeting beyond a commerce media entity’s site or app to create highly personalized omnichannel advertising experiences. Offsite retail media ad spend, which enables advertisers to activate commerce media audiences beyond a retailer’s site or app, is forecast to grow at double the rate of onsite media spend through 2026, and off-platform placements will account for over 63% of display ad spend by 2029.
Even more, commerce media is well-suited for times of economic uncertainty. As a highly measurable channel, it allows marketers to clearly demonstrate ROI. And while commerce media’s early growth was largely driven by performance marketing, it has since evolved into a full-funnel solution that supports brand-building efforts as well.
Ultimately, these strengths make commerce media not just a timely solution for today’s challenges, but also one that’s aligned with the trajectory of digital advertising.
To capitalize on the commerce media opportunity—whether a team is testing and learning on the channel or executing a large-scale strategy—marketing teams must strategize around fragmentation and a lack of measurement standardization, while also prioritizing data readiness and preparing for how the rise of agentic commerce will transform the channel.
The commerce media marketplace is growing increasingly crowded. One way to simplify the space is to limit the number of networks in play. As such, advertisers should carefully evaluate which networks can deliver the most value.
Many new entrants offer access to first-party data but lack the infrastructure to support meaningful advertising outcomes. Marketers should strike a balance between testing emerging platforms with low barriers to entry and investing in more established players with comprehensive ad solutions.
At the same time, there are some meaningful advantages to diversifying spend across a variety of platforms. A diversified strategy is the most effective approach for brand building, says Frye, as channels thrive on the cumulative effect of many small exposures. It also ensures advertisers are not over-relying on a single platform or data source, which mitigates risk and gives teams the flexibility to optimize based on performance.
To help their teams succeed in an increasingly fragmented landscape—both within commerce media and across the broader digital ecosystem—advertising leaders must take steps to reduce the complexity it creates. Tools that reduce manual labor, streamline parts of the campaign process, and unify often-disjointed systems like reporting and billing can help teams operate more efficiently and adapt to new opportunities.
High-quality data is one of commerce media’s most compelling advantages. As the space evolves, marketing teams are finding smart ways to maximize and extend that data. Tools like data clean rooms are opening up new opportunities for data collaboration, with advertisers combining data from commerce media networks, advertising platforms, and publishers with their own first-party data to drive more sophisticated strategies.
To fully capitalize on these opportunities, teams must refine how they collect, organize, store, and activate their data. This is closely tied to the broader challenge of digital advertising fragmentation and resulting tech stack sprawl: When data is siloed across a variety of tools, it becomes difficult to extract meaningful value. With over 50% of agency marketers using eight or more tools to manage client campaigns and 40% using 10 or more tools, unifying data across platforms should be a top priority for marketing teams aiming to succeed not only in commerce media, but across their broader marketing efforts. This is especially true when it comes to harnessing and operationalizing AI: Since AI outputs are only as good as their inputs, marketing teams need access to large volumes of unified, high-quality data to get reliable and differentiated outputs from their AI tools.
Another key consideration for advertisers investing in commerce media is the rise of agentic AI and agentic commerce. Agentic AI’s ability to independently research, compare, and execute purchases on behalf of consumers is poised to change how products are discovered and bought—and, by extension, how commerce media functions as a channel. Marketers who get ahead of this shift will have a meaningful advantage over their competitors.
Consumer interest in AI-assisted shopping is already significant: In late 2024, 71% of US shoppers—and 84% of Gen Z shoppers—expressed interest in using an AI agent to make purchases on their behalf once items hit a target price. Meanwhile, major AI platforms are actively building commerce capabilities that could eventually compete with what retail media has long owned at the lower funnel: Both OpenAI and Perplexity, for example, are building out fully agentic commerce infrastructure. However, OpenAI’s recent scaling back of their plans to integrate checkout directly into ChatGPT suggests that even the most well-resourced AI companies are finding it difficult to own the full purchase journey. Retail media giants, meanwhile, are leaning in on their own agentic bets: Walmart, for example, has introduced Marty, a new agentic capability built to help advertisers manage billing and bidding for their sponsored search campaigns.
As consumers increasingly rely on AI agents to research and buy on their behalf, brands and retailers will need to ensure their products are discoverable and purchasable by those agents in addition to human shoppers. This means auditing websites, product catalogs, and digital assets to verify they’re optimized for AI systems as well as human visitors, including structured data, clean APIs, and metadata-rich content that AI agents can easily parse and act on. Equally important is keeping a pulse on how this space develops, as the agentic commerce space is evolving quickly and the strategies that work today may need to be revisited as new platforms, capabilities, and consumer behaviors emerge.
Commerce media addresses many of the challenges advertisers are grappling with today, offering precision, scale, and omnichannel activation. At the same time, its measurability is a significant advantage at a time when marketers are under increasing pressure to prove performance.
To fully realize the channel’s potential, marketing leaders must take care to invest in the right partners, unify fragmented systems, build robust and streamlined data ecosystems, and prepare for how agentic AI will change the landscape. By taking these steps, teams can unlock the full value of commerce media—not only to meet current challenges, but to set the stage for sustainable growth in the years to come.
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Commerce media isn’t the only space that AI is set to transform: The technology is also poised to reshape how marketers work on a fundamental level. To find out how teams are actually navigating that shift, we surveyed professionals from leading brands and agencies about the tools they're using, where the technology is delivering, and where the gaps remain. Check out AI and the Future of Marketing for all the findings.
For years, advertising in AI-powered environments was limited if not largely nonexistent. But after a flurry of activity over the past few months, that’s no longer the case: Many chatbots and AI-generated search results are now ad-supported (or will be soon), and the pace of change is accelerating.
For advertisers, this means navigating fragmented platforms, limited reporting, and new intent dynamics—all while direct inventory access remains restricted for most. Here’s a look at the current state of AI media advertising, what makes these environments distinct, and where advertisers should focus their attention.
Key Takeaways:
After a slow start (during which OpenAI CEO Sam Altman famously described ads on ChatGPT as a “last resort”), advertising in AI-powered environments has begun to debut across different platforms. And while the timelines have varied across the broader AI ecosystem, the pace has picked up considerably over the past year.
At Google Marketing Live 2025, the company confirmed that paid ad placements would begin appearing within AI Overviews and AI Mode, its AI-powered search experience. Both text-based Search ads and image-forward Shopping ads are now available inside AI-generated summaries on desktop, integrated directly into answers rather than sitting alongside them as separate units.
Microsoft began testing ad formats within Copilot in March 2025, making it one of the earlier chatbot platforms to introduce sponsored placements. And, notably, early insights show that ad relevance metrics in the interface are 25% better than what is seen in traditional search.
In early 2026, OpenAI announced it would begin testing ads within ChatGPT. Placements appear at the bottom of responses—clearly labeled and distinct from the LLM’s organic answer—when a sponsored product or service is deemed “relevant” to the conversation (though there is still uncertainty around what determines this relevance). Early analysis shows ads triggering most frequently on high-intent queries containing modifiers like “best” and “new,” with brands including Best Buy, AT&T, and Expedia among the early participants. The pilot remains restricted to select global brands, with a reported minimum spend commitment of $200,000.
Google has signaled to advertising clients that it is targeting a 2026 rollout for ad placements within Gemini (which is, importantly, a separate initiative from AI Mode and AI Overviews). No formats, pricing structures, or testing timelines have been shared publicly, but with Gemini surpassing 750 million monthly users, the platform represents meaningful scale. And the direct outreach to buyers signals that Google is actively moving to monetize its chatbot, even as the specifics remain undefined.
Anthropic has taken a notably different position on advertising. In February 2026, the company reaffirmed its commitment to Claude remaining ad-free, stating, “There are many good places for advertising. A conversation with Claude is not one of them.” Their reasoning centers on trust: Anthropic’s view is that users shouldn’t have to second-guess whether an AI is genuinely helping them or steering them toward something monetizable. The company says it plans to sustain that model through enterprise contracts and paid subscriptions rather than ad revenue.
Claude aside, the broader picture is a market that is quickly fragmenting. Some AI platforms are moving quickly to monetize through advertising. Others are positioning ad-free experiences as a trust differentiator (at least for now). What’s clear is that AI media environments are no longer a single category. They vary by platform, format, access, audience, and business model. For advertisers, understanding which platforms are ad-supported, which are better suited to organic reach, and how each one fits into a broader media strategy is becoming critical.
Advertising in AI environments introduces a different set of dynamics than traditional search or display, and those distinctions can carry real implications for strategy.
Perhaps the most significant change is the quality of intent. In traditional search, a query signals interest. But in a conversational AI environment, users have often already moved further down the decision path—articulating specific needs and narrowing their options before they ever see an ad.
“I believe that AI-driven answers, regardless of platform, will shorten the research cycle and turn intent into conversion more quickly,” says Lindsay Martin, Group VP of Search Media Investment at Basis. “As a result, click-throughs are more likely to be pre-qualified.”
That pre-qualification impacts landing page strategy. Martin notes that intent-specific landing pages will be critical in these environments to reflect the nuance of the prompt. This is a meaningful departure from the broader match approach that has traditionally anchored search. The prompts that trigger AI ads carry more context than a traditional keyword, and creative built for broad audiences isn’t designed to meet that specificity. Messaging will need to prioritize usefulness, clarity, and context.
Trust is another variable that sets AI environments apart. Recent research finds that 66% of US adults are highly worried about getting inaccurate information from AI tools, and introducing advertising into these environments only deepens that concern, layering a commercial motive onto platforms that users are already approaching with caution.
How platforms plan to handle that transparency gap varies. OpenAI has outlined principles governing how ads will function in ChatGPT, including that ads will not influence responses and that user conversation data will not be shared with advertisers. Google has published documentation on how ads in AI Overviews are triggered: Both the user query and the content of the AIO are considered when serving ads, and placements are currently excluded from sensitive verticals including finance, healthcare, and politics. What that documentation doesn’t address is how users are informed about why a particular ad appeared, or what guardrails exist to ensure the presence of ads doesn’t shape how AIOs are generated in the first place. Whether users accept any of these approaches—or notice the difference—remains to be seen.
“I’m interested in understanding how the different AI platforms’ algorithms determine relevance for advertising and maintain users’ trust,” Martin says. “There isn’t much transparency on that topic yet.”
Lastly, tracking and measurement questions compound both of these challenges. And to date, neither ChatGPT nor Google AI Overviews has provided advertisers with detailed metrics on the success of advertising in these AI-powered environments.
Martin anticipates that attribution capabilities will become more robust over time—showing how AI conversation functions as a conversion assist earlier in the customer journey. For now, reporting remains limited, and the infrastructure to meaningfully capture that influence has yet to become a standard for continued ad optimization.
“If I were a brand,” says Martin, “I would not be comfortable with the high price tag for early advertising without a strong measurement framework in place.”
For most advertisers today, direct access to AI ad environments remains limited. However, there’s still plenty that teams can do to prepare for when inventory becomes more accessible.
On the paid side, the immediate priority should be awareness and readiness. Monitoring how ads are triggered in chatbots (e.g., query types and intent signals) provides a useful foundation before access opens more broadly. And maintaining paid search presence also remains important: Ads appearing alongside AI-generated summaries can deliver brand impressions even without a click, and those impressions still influence decisions.
The more immediate opportunity, however, is organic. Large language models decide which brands to surface, cite, and recommend in their responses, and that process is already happening now, independent of any paid placement. Optimizing for that inclusion, increasingly referred to as generative engine optimization (GEO), means prioritizing structured, factual content, clear product and FAQ pages, and content formatted in ways AI systems can parse and surface reliably.
“If an LLM has no reason to include you in results, you will be left behind,” Martin says.
The intersection of organic and paid strategy in these environments also warrants attention, with Martin noting that GEO is “muddying the waters with how we’ve traditionally differentiated SEO and SEM.” Teams that have treated organic and paid search as separate disciplines will need to think about how those strategies align in environments where the same AI system may determine what it recommends organically and what it surfaces as a sponsored result.
And as the channel continues to mature, AI media advertising will also add new complexity to an already fragmented landscape. Each platform operates on different formats, measurement frameworks, and reporting standards, meaning that teams managing presence across ChatGPT, Google AIOs, and other emerging inventory will be navigating multiple systems simultaneously. That complexity will make it all the more critical for advertisers to seek out platforms that allow them to unify budget, performance, and strategy in one central location—making it easier to respond quickly as inventory expands and the rules continue to evolve.
For advertisers building toward long-term readiness and resilience, staying updated on the latest AI media advertising developments, diversifying measurement frameworks, prioritizing content that AI systems can find and use, and maintaining presence across channels where messaging remains controllable is key. AI search ad spending—spanning both generative AI platforms and AI-powered search summaries—is projected to grow from $2.08 billion in 2026 to $25.93 billion in 2029.
Though the environments driving that growth are still taking shape, advertisers who invest in understanding them now will be better positioned to compete as access widens and the rules become clearer.
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For a deeper look at how AI is reshaping the future of search and what it means for media strategy, check out AI and the Future of Search Engine Marketing.
Key Takeaways:
An omnichannel advertising platform is a centralized technology that connects programmatic, site direct, search, social, and connected TV channels in one interface for unified campaign management and execution. This new breed of technology empowers marketers by simplifying the complexities of modern digital advertising, ultimately consigning the days of multiple single-point solution logins to the past.
Key Benefits of Omnichannel Advertising Platforms:
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Frequent reporting, quick experimentation, effective optimization, flawless execution.
This is the basic blueprint for success for any digital advertising campaign. Of course, there are great nuances to each stage, but this is essentially what a successful advertising strategy in action looks like.
Two decades ago, this cycle was fairly simple to manage. Marketers only had to concern themselves with building a couple of creative iterations, reaching one device, measuring a handful of cost types (for example, CPM or PPC), and utilizing a few tracking methods. However, today’s reality couldn’t be starker. The explosion of digital intermediaries, coupled with the continued emergence of new channels, has irrevocably changed the media landscape—enabling a proliferation of touchpoints and breeding an environment rife with fragmentation.
To combat these challenges, many marketing organizations have simply added more and more single-point solutions to their technology stacks—the theory being that separate, bespoke systems built to master individual channels or specific devices will ultimately drive the best results.
This tactic was once powerful enough to satisfy consumers who wanted nothing more than the basics, like quality service and competitive pricing. But meeting the needs of today’s consumer is a far more demanding proposition. They assume the promotional code they see on Hulu will be valid both on a website and in-store. They believe if they fill up their basket online and close the desktop window, said basket will automatically transfer to the mobile app. They presume an online chat agent will have full knowledge of the complaint they lodged days ago on social media. As such, unified cross-channel experiences and cross-platform mobility are now overtly baseline requirements for brands.
These evolving consumer expectations—driven by tech-savvy millennials and Gen Z—are perennially pushing marketers to improve the seamlessness of their advertising operation. Those that fail to do so will fall behind the curve.
Consider these statistics:
Together, these numbers highlight just how important it is for brands to embrace an omnichannel marketing strategy that works by breaking down silos and putting audiences at the very center of the advertising experience. By doing this, media buyers can get hyper-granular and more precise with their execution, delivering relevant messages that meet individuals right in their moment. Examples of this in practice might include:
The benefits of this approach are both profound and wide-ranging—heightened operational efficiency, improved customer retention, and increased customer lifetime value, to name but a few.
However, these sizable rewards don’t come easily, and the path leading to them is riddled with complexity. Many companies have attempted to implement an omnichannel strategy, yet few have truly succeeded in constructing a sweeping, unified experience for the consumer. Some don’t even bother initiating the process due to the perception that the effort would demand an unreasonable amount of time and personnel resources, while those that have done so often stumble because of immature implementation methods, competing priorities, slow progress, and spiraling costs. The most significant hurdle, though, is technology: legacy systems designed to run basic single-channel consumer interactions lack the necessary interconnectivity inherent to a true omnichannel experience, which can create massive holes in the ambition for single, holistic campaigns.
The good news for media buyers is that novel solutions are coming onto the market equipped with everything required to nullify all these barriers simultaneously: Omnichannel advertising platforms.
The technology is a game-changer for advertisers.
The omnichannel platform empowers marketers by connecting all the major digital channels—programmatic, site direct, search, social, and connected TV—in one centralized ecosystem, thereby simplifying campaign management and execution. It ultimately consigns the days of multiple single-point solution logins to the past: with omnichannel platforms, marketers can buy programmatic audio inventory, negotiate guaranteed direct page takeovers, and run a series of dynamic carousel ads on Facebook from one interface.
Examples of omnichannel advertising platforms include comprehensive media buying solutions like Basis, as well as enterprise marketing suites from vendors such as Adobe, Salesforce, and MediaMath, which offer varying degrees of unified cross-channel campaign management.
To be clear, this technology should not be confused with omnichannel programmatic platforms that deal solely in the programmatic sphere. An omnichannel advertising platform can do everything those systems can and then some, pulling together all the core components of an omnichannel campaign and adding on top a combination of solutions like workflow automation, integrated reporting, and other AI-powered functionalities built to enhance collaboration and partnership both internally and externally.
| Feature | Omnichannel Advertising Platform | Omnichannel Programmatic Platform |
|---|---|---|
| Channel Coverage | Programmatic, site direct, search, social, and connected TV | Programmatic channels only |
| Buying Methods | Automated and direct/guaranteed buys | Automated/programmatic buys only |
| Additional Features | Workflow automation, integrated reporting, AI-powered functionalities | Primarily focused on programmatic execution |
| Use Case | Full omnichannel campaign management | Programmatic-specific campaign management |
By leveraging this type of all-in-one digital media technology, marketers can gain instant access to every tool they need to power data-based growth and unlock massive time-saving benefits that can transform the way they communicate and engage with consumers.
For marketing organizations large and small, the practice of data consolidation has never been more important. It is the key to building the kind of data-driven culture that’s fundamental to success in a severely fractured industry. Data itself is a dynamic asset, and marketers rely heavily on its accuracy to run effective programs that drive overarching business goals. Unfortunately, many still find themselves perpetually handicapped by incomplete analytics, where siloed data lies scattered in a mix of disparate systems, email chains, Excel spreadsheets, and other communication channels such as Slack or Teams. These limitations are time-sapping and inefficient and make it nearly impossible for marketing organizations to maximize ROI.
With the implementation of an omnichannel platform, marketers can remove such hindrances from their day-to-day by activating a system of record that automatically consolidates, aggregates, and stores campaign data in one centralized hub.
It is a move with two major advantages:
Key Takeaway: Consolidated data eliminates silos, frees teams from manual processes, and enables better collaboration across marketing organizations.
Creative type A resonated well in California but performed poorly in Michigan. Customer Y browses online but always moves to in-app before purchasing. Prospect Z was in a campaign targeting utility buyers but actually purchased a luxury product. Creative type B converts 75% more from Forbes over Yahoo Finance.
When organizations adopt an omnichannel platform equipped with a robust reporting engine, they can give their marketing and media buying teams unprecedented granular visibility at scale. In simple terms, this analytical architecture can surface real-time correlations and customer behaviors that were previously invisible to the naked eye. It automates the process of merging disconnected reports and displays them in dynamic, interactive dashboards that break down media performance on both micro and macro levels.
This type of omnichannel platform can radically change the day-to-day working lives of media buyers and analysts. No more manual data stitching. No more missing spreadsheets. No more guesswork required. Everything automatically unified. With this technology in their arsenal, organizations can essentially do six hugely important things:
The actionable intelligence this reporting engine can provide is startling. It enables campaign optimization on levels that are virtually impossible to reach without it.
Key Takeaway: On-demand multi-dimensional reporting provides real-time, granular visibility that enables unprecedented campaign optimization and data-driven decision making.
A 2021 survey revealed the majority of advertisers use seven platforms in a typical day and nine platforms over the course of a typical ad campaign. The findings are evidence that for all the incredible progress the industry has seen around digital processes and the development of AI-powered support—particularly over the last 10 years—there has been a stark lack of any proportionate upgrade to the technology and procedures designed to help marketers manage it all.
Omnichannel platforms remedy this growing imbalance. By deploying campaigns across all programmatic, site direct, search, social, and connected TV channels from one singular interface, media buyers no longer need to bounce around between multiple disparate systems in order to simply do their job. The real-world implications of these efficiency gains are massive—shortened workflow processes allow marketers to be nimbler with their movement of media weight and can help them adapt digital spend around unplanned events more quickly to improve profit margins. Whether it is uploading new media to a specific channel, iterating on creative within existing assets, altering the segmentation of targeting parameters, or pulling entire omnichannel campaigns from the market, procedures that once took days—or even weeks—now take mere hours.
All of this increases a brand’s ability to keep pace with the forever-changing demands of consumers and deliver impactful advertising that flows freely across channels.
Key Takeaway: Enhanced campaign execution through a single interface dramatically reduces workflow time and enables marketers to respond quickly to market changes.
Today, success with omnichannel marketing is not the daunting, seemingly unachievable aspiration it was. An omnichannel platform makes it all possible by providing marketing organizations with all the functionalities they need to create a customer-centric, journey-focused approach that is now so vital in the fight to win hearts and wallets.
The data shows that the demand for seamless experiences is high and utilizing multiple disconnected single-point solutions simply won’t meet them. It is now up to marketers to evolve with the times and deal with these expectations head on. This all-encompassing technology is the starting point.
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What is an omnichannel advertising platform? An omnichannel advertising platform is a centralized technology that connects programmatic, site direct, search, social, and connected TV channels in one interface for unified campaign management and execution.
What channels do omnichannel advertising platforms support? Omnichannel advertising platforms support programmatic, site direct, search, social, and connected TV channels, allowing marketers to manage all digital advertising from a single interface.
How is an omnichannel advertising platform different from an omnichannel programmatic platform? An omnichannel advertising platform covers all major digital channels including direct buys, while an omnichannel programmatic platform deals solely in programmatic channels and automated buying.
What are the main benefits for media buyers? The main benefits include consolidated data in one hub, on-demand multi-dimensional reporting, enhanced campaign execution from a single interface, and significant time savings through workflow automation.
The rise of AI has put marketers under some serious pressure: Adopt the technology quickly, demonstrate growth and efficiency gains, and stay ahead of a landscape that’s evolving by the day. Easy peasy, right?
Of course, the upside more than justifies the growing pains, with close to two-thirds of marketers reporting that AI has made them moderately-to-significantly more effective over the last year. Still, with new solutions entering the market every day and marketers constantly discovering creative new applications, it’s easy to feel like everyone else is one step ahead.
To that end, here’s a look at where the industry actually stands, and how marketers are finding real value in the technology.
Recent research offers a useful baseline for understanding how AI has taken hold across the marketing industry. Nearly all marketing and advertising professionals (95%) report using generative or agentic AI at least once a month, and a third use it every day. When it comes to what marketers are actually doing with AI tools, the top use cases are ideation and brainstorming, research, and drafting content and creative. ChatGPT dominates as the go-to platform, with Gemini and Copilot rounding out the top three.
On the organizational side, nearly two-thirds of marketers (65.7%) say their companies pay for or subscribe to premium AI tools. However, adoption of more sophisticated, custom in-house solutions remains limited, with nearly half (47.1%) reporting that their organizations don't use any at this time.
Beyond adopting custom tools and achieving the data readiness necessary to fuel those tools, the creative use of AI is increasingly what separates high-performing marketing teams from the rest. Below, Basis experts share a variety of ways they're finding value in the technology across their roles.
“I’ve found AI very useful as a partner to expedite tasks related to writing and communication. A few examples:
Robert Kurtz | Business Outcomes Partner
“I used Copilot to run a basic regression model for performance forecasting based on historical spending and online conversion data. Copilot helped organize and clean the data set, ran the analysis, and summarized findings so that I could interpret and contextualize the data outputs. This was a cool way to expedite data analysis so that I could focus on interpreting the numbers.”
Lauren Johnson | Effectiveness Lead
“One of our clients was receiving some negative responses online after running new, bold creative executions. They asked us for support in what we could see online from a brand sentiment perspective, but we couldn’t find much using our social listening platform. So, we took a handful of social media posts and asked Copilot to summarize sentiment and themes. The tool helped us to quickly understand audience sentiment on social media based on 15 social posts with 600+ comments.”
Emily Zelenz | VP, Integrated Client Solutions
“I’ve found AI particularly useful for keeping up with what competitors are doing in market. One of our clients has a long list of competitors, so I built a prompt that can look for new competitor creative launched within specific time periods. It makes competitive updates in the QBR much more streamlined—previous to this, I’d have to look at each brand one by one in an ad tracking tool and see if any looked new.
On a similar note, I've also given Copilot a list of competitors in a category and asked for a SWOT analysis of each. Individually curated research would be a lot more in-depth and likely more interesting—but leveraging Copilot gave a quick overview in just 2 minutes. That quick intel is a great starting point, and then it's up to us to identify where we need to dive deeper.”
Molly Marshall | Strategic Business Outcomes Partner
“I work with a lot of pharma clients, and the drugs and diseases we look at are often very complicated. I use a custom GPT for disease and drug research that:
I use the output as a starting point for my own understanding, then ask targeted follow-up questions and cross-check key points until I’m confident in the fundamentals and feel comfortable having an educated conversation with my clients.”
Ryan Sperry | VP, Integrated Client Solutions
“I’ve experimented with using generative AI to pressure test ideas. I'll ask it to poke holes in an argument or tell me why a certain idea is 'bad.' While I don't always agree with what it comes up with, it's a great way to stress-test my thinking. This is a particularly good use case for leveraging AI as a brainstorming partner on the media strategy side.”
Kelly Boyle | SVP, Strategic Business Outcomes
“One of our clients partnered with a vendor that develops synthetic personas representing key target audiences. The initial output included detailed audience profiles covering demographics, psychographics, media consumption behaviors, and trust metrics.
We are currently in the process of validating those findings against syndicated sources such as GWI and IPSOS, and the early review indicates strong directional alignment.
One area we are exploring as a next step is using these personas to inform creative message testing, in addition to broader audience strategy and planning. We are still in the early stages of evaluating how this could be applied most effectively, but the results so far are both promising and exciting.”
Jackie Etter-Krause | Sr Integrated Client Solutions Director
My team played around with AI to help us determine the best radius targeting for one of our multi-location clients. Copilot analyzed factors like population density, traffic patterns, bridge/toll road barriers, etc., and helped us determine the appropriate radius as well as some exclusions to implement within Meta & Google.”
Marykate Dougherty | VP, Integrated Client Solutions
These use cases are just a snapshot of the ways marketers are finding value in AI, and the list is only growing. Whether pressure testing a media strategy, navigating a PR crisis, or getting up to speed in an unfamiliar vertical, AI has proven itself as a capable and versatile partner across a variety of marketing functions.
Not every application needs to be groundbreaking—some of the most impactful uses are the ones that simply save time, surface better insights, or help advertisers show up more prepared for a client conversation. As the technology continues to evolve, marketers who are actively experimenting today will be best positioned to scale what works tomorrow.
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For more insights on how marketing teams are using AI, we asked professionals from leading brands and agencies about which tools they’re using, where the technology is driving results, and where the challenges still lie. Check out the 2025 AI and the Future of Marketing Report for an inside look at what's actually working.
Political advertising has never been a simple undertaking. It demands strategic precision, creative discipline, and the ability to move quickly in an environment where the rules, the platforms, and the electorate itself seem to shift by the day. The 2026 US midterm elections promise all of that and more, and they’re arriving at a moment when the political advertising landscape has been fundamentally reshaped by the rapid evolution of connected TV, the maturation of streaming audio, the rise of AI-assisted creative and optimization tools, and deep uncertainty around redistricting, candidate turnover, and an increasingly fragmented media environment.
This guide is designed to help political advertisers—including campaigns, causes, consultants, and agencies—navigate what lies ahead. Whether you're managing a statewide senate race, running a closely contested congressional district, or promoting a ballot measure campaign, the insights here are designed to be actionable, practical, and grounded in the realities of the 2026 election cycle.
Key Takeaways for Political Advertising in 2026
With control of both the House and the Senate up for grabs, the 2026 elections are expected to be the most expensive midterm cycle in US history. Political ad spending for the year is projected to hit $10.8 billion, a 20%+ increase over the last midterms held in 2022.
The backdrop for this fall’s elections is unusually complex. Beyond the anticipated referendum on an unpopular president, a wave of congressional retirements—early estimates suggest approximately 10% of sitting members may not seek reelection—is creating an unusually large number of open-seat races where neither candidate enters with the name recognition and voter relationships of an established incumbent. At the same time, redistricting proceedings are underway in several key states, including California, Missouri, North Carolina, Ohio, Texas, and Utah, with the potential to redraw competitive boundaries heading into the cycle.
The implications for political advertisers are significant. Open-seat races typically require heavier investment in early awareness and fundraising, since candidates cannot rely on existing voter relationships to carry their message. And in races where redistricting has created entirely new districts, voters may find themselves represented by a candidate they have never heard of, making name recognition advertising even more critical in the early campaign phase.
"I think everything's up for grabs," says Jackie Huelbig McLaughlin, VP of Candidates & Causes at Basis.
Watch List: Redistricting is underway in California, Missouri, North Carolina, Ohio, Texas, and Utah. Campaigns in these states should plan for a shifting competitive landscape and prioritize early awareness investment.
The political benefits of redistricting will ultimately be state-dependent, and predictions around competitiveness in those districts will be somewhat difficult to make until primaries clarify the field. Either way, campaigns in affected states should not assume that historical spending patterns or targeting approaches will translate to the new map. Early investment in audience research and media planning will pay dividends later.
Additionally, the retirement wave, in particular, is likely to make primaries more competitive across the board. Candidates who might have had a clear path in a race against a known incumbent now face crowded fields where early advertising, grassroots organizing, and digital presence can be decisive. For campaigns with limited budgets, this means making hard choices about where to allocate early dollars—and recognizing that earned media, organic social, and community presence may play an outsized role in building momentum before paid media becomes the primary vehicle.
Every election cycle teaches the industry something new, and 2024 was no exception. Among the most instructive contrasts of the last presidential race was the divergence in how the Trump and Harris campaigns approached their paid digital advertising in the campaign's final stretch. The Trump campaign, hamstrung by budgetary restrictions, was highly selective with their media buys: If they knew a voter was already in their corner, that voter simply wasn't seeing their ads. The Harris campaign, meanwhile, was “throwing spaghetti against the wall,” says Huelbig McLaughlin—having entered the race late and operating under time pressure, they took a broader approach, running significantly more volume across more audiences in the hopes that something would connect.
In 2026, knowing your audience before you spend will be key to maximizing political advertising budgets. Heading into a midterm cycle—where the margin for error is increasingly narrow—campaigns cannot afford to waste impressions on voters who are already committed. “The goal,” says Huelbig McLaughlin, “should be to stretch the dollars in a very mindful way" through disciplined targeting and a thoughtful media mix.
This philosophy will define the most competitive 2026 races. Campaigns that invest early in understanding their voter base—who needs persuasion, who needs activation, and who is already a lost cause—will be the ones best positioned to allocate their media dollars efficiently when spending peaks in October and November.
The fundamental rhythm of the political advertising spending cycle has not changed: awareness and fundraising in the early months, a building cadence through the summer, and then an all-out sprint from Labor Day through Election Day. Basis data from the 2024 election found that 48% of digital ad budgets were spent in the final 30 days before Election Day, with nearly half of that concentrated in the final 10 days of the campaign.
Early in the cycle—through primaries and into the summer—the goal is awareness: getting the candidate's name and core message in front of as broad an audience as possible. Then, as Election Day approaches, the objective shifts to precision: Identifying the specific persuadable voters who haven't committed, reaching them with the right frequency, and getting out the vote. These two objectives require different channel strategies, different targeting approaches, and different creative executions.
In 2026, the dynamics of that late-cycle sprint will be shaped by two intersecting factors: the aforementioned volume of competitive races created by redistricting and retirements, and the growing supply of premium CTV inventory. In races where multiple well-funded campaigns are all racing to reach the same undecided voters in the final weeks, the premium on reserving inventory early cannot be overstated.
Budget Strategy and Timing Tips:
Political advertisers have long operated in a more constrained targeting environment than their commercial counterparts. But some restrictions on audience targeting for election ads on platforms like Google and Meta, coupled with state-by-state regulatory variations, can make audience strategy an increasingly complex, jurisdiction-specific exercise.
In this environment, geopolitical targeting has become an increasingly important tool. Basis data from the 2022 midterms showed that nearly 20% of political programmatic ads used geopolitical targeting to reach voters in specific districts—with 51% using congressional district targeting and 32% using state senate district targeting. With third-party cookie deprecation having largely reshaped the programmatic targeting landscape, these geography-based approaches have only grown more prominent in the last four years.
Beyond geotargeting, identifying ways to more precisely reach undecided voters remains the political targeting holy grail: Who are they, where do they live, what do they watch, what are their passions? In districts where redistricting has created new competitive dynamics—and where an anticipated referendum on an increasingly-unpopular president has loomed over many races—this kind of audience intelligence work is especially valuable, as the old assumptions about which precincts are reliably red or blue may no longer apply.
Automatic Content Recognition (ACR) data from smart TV manufacturers, combined with programmatic targeting capabilities on CTV platforms, offers one of the most compelling answers to this challenge. Campaigns can now reach households based on their actual viewing behavior—not inferred demographic proxies—and serve political messages in contextually appropriate environments at the moment those households are most engaged.
Speaking of which…
Connected television (CTV) has been the hottest digital channel of the past several election cycles, and 2026 will be no different. While broadcast television will remain the single largest channel for political ad spend at $5.3 billion, CTV is projected to rank second at $2.48 billion—and, tellingly, is the only segment expected to show meaningful growth. For political advertisers who have already internalized the case for CTV, the challenge is now to invest more effectively given an increasingly crowded and complex inventory landscape.
The fundamental appeal of CTV has always been its ability to deliver the emotional and persuasive power of television-style video with the precision targeting capabilities of digital. And with the number of cord-cutters and “cord-nevers” growing by the year, campaigns must approach CTV as a distinct and valuable channel to complement their linear efforts, as the audiences for each TV-consumption method are increasingly divergent.
There is now a sizable subset of undecided and swing voters who are only reachable via connected TV. This audience of individuals who are not watching broadcast or cable skews younger, and is generally associated with urban and higher-income audiences. But audiences of all kinds are making the switch from cable to connected TV, making it increasingly critical to an array of midterm races in competitive districts.
Case in point: “My parents and in-laws in their 70s all cut the cord this year and are relying entirely on YouTube TV or Hulu TV,” says Huelbig McLaughlin. “The cord-cutting age is going up."
Key Data Point: $2.48 billion: Forecast CTV political ad spend in 2026—the only digital channel projected to grow this year. (Source: AdImpact)
In recent election cycles, the gap between demand for political CTV advertising and the available supply constrained campaigns' ability to fully exploit the channel—particularly in premium environments.
Fortunately for CTV-hungry political advertisers, that gap is narrowing rapidly, and 2026 is poised to be the first US election where CTV inventory meets the market’s needs.
More and more streaming platforms and publishers are now accepting (if not outright welcoming) political and advocacy advertising. The shift is fueled, in part, by the proliferation of smart TV apps that come pre-loaded on devices from manufacturers like LG, Samsung, and Vizio. These OEM (original equipment manufacturer) platforms operate their own owned-and-operated channels—including free ad-supported streaming TV (FAST) channels—and are opening up significant new inventory.
Additionally, companies like Disney have opened up valuable inventory across many of its platforms, such as Hulu and ESPN—a particularly notable development for campaigns targeting sports-adjacent audiences—to go along with growing opportunities across DIRECTV, HBO Max, Paramount, and other premium providers.
Live sports inventory, in particular, have increasingly migrated to streaming platforms and offer particularly high value, with the FIFA World Cup, NFL, college football, MLB, and other major sports events providing exactly the kind of broad, engaged audience that campaigns are always eager to reach.
But the streaming story goes beyond mere supply: ACR data generated by smart TVs is making targeting dramatically more sophisticated, with tens of millions of Americans having opted in to sharing data about what is displayed on their screens. This creates rich household-level viewing data that advertisers can use to reach audiences based on the content they actually consume—whether that’s live sports, their favorite shows, or even specific streaming services.
Campaigns that want to maximize their CTV presence in 2026 should plan to use a mix of buying approaches rather than relying on any single method. Programmatic open exchange, private marketplace deals, and programmatic guaranteed each offer different tradeoffs in terms of pricing, inventory access, and targeting precision. As demand surges in October and inventory tightens dramatically in competitive markets, campaigns that have locked in favorable PMP or programmatic guaranteed pricing in advance will have a significant edge over those relying solely on the open exchange.
In most congressional districts, sufficient inventory exists—but only if campaigns plan strategically and secure access before peak season.
Key Takeaways
Campaigns looking to make the most of CTV advertising opportunities should:
If CTV has been the marquee channel story of recent cycles, streaming audio is shaping up to be one of the defining new opportunities of 2026. Audio represented just 1% of political ad spend in the 2022 midterms and 3% during the 2024 election season (most of which was radio) despite the average voter spending 21.2% of their total media time consuming audio, representing a significant underexplored opportunity.
With workers having increasingly returned to offices (and their accompanying commutes) in recent years, audio consumption is rising in kind. The medium is uniquely well-positioned to reach voters during screen-free moments: In the car, on a commute, during a workout, while cleaning the house. Podcast listenership, in particular, has demonstrated itself increasingly resonant across key voter demographics, delivering outsized political impact. And with programmatic buying now available even for broadcast radio inventory, the barriers that once made audio difficult to activate at scale have largely been removed.
While targeted podcast advertising at scale remains somewhat nascent, the streaming audio opportunity through platforms like Spotify and iHeart is very real—and growing. Basis’ Jaime Vasil (Group VP, Candidates & Causes) anticipates meaningful growth in streaming audio political spend this cycle, and campaigns that are early movers in the channel stand to benefit from both lower CPMs and less competitive inventory than they will find in CTV.
Beyond inventory, the emergence of streaming audio reflects a key shift in the ways media consumption has changed in the past several years. Voters have moved from passively consuming programming at a specific, scheduled time (and on a specific, dedicated channel) to actively constructing their own media environments across an array of mediums—combining on-demand streaming services with live sports, podcasts, social video, and background audio throughout the day. Effective political advertising in 2026 will need to follow voters into all of those environments rather than waiting for them to find you.
“People are now curating and consuming their own personalized entertainment menus across different channels and different timeframes,” says Huelbig McLaughlin. “And as political advertisers, we’re going to have to crack that.”
One of the more nuanced conversations in political advertising heading into 2026 concerns the relationship between paid media and organic digital content—and, specifically, whether the viral social media success stories of recent cycles are broadly replicable for candidates in smaller or less urban markets.
The impetus for the discussion, of course, is newly elected New York City mayor Zohran Mamdani, whose authentic, personality-driven TikTok and Instagram content generated outsized organic reach among younger voters. The appeal is obvious: Organic content costs relatively little, can generate significant reach, and communicates a kind of authenticity that traditional political advertising often struggles to replicate.
The question, then, is whether the “Mamdani effect” will grow and influence campaigns this midterm cycle?
While the content itself is undeniably fresh and engaging, Vasil offers an important caution: "It's sometimes more about the candidate than the tactics." Mamdani was a young candidate living in Queens, genuinely relatable to the digital-native voters he was trying to reach. The same approach deployed by a candidate in a rural congressional district—or by any candidate who lacks the natural charisma or cultural fluency to pull it off—is unlikely to produce the same results. Trump's social media dominance, for example, was built on 25+ years of name recognition accumulated through television and business ventures—something that’s not exactly replicable for most candidates.
That said, authentic organic social content will likely become increasingly important for candidates seeking to connect with voters under 55. The key word there is "authentic," as voters—particularly younger ones—are highly attuned to content that feels manufactured or performative. The opportunity is real, but campaigns should resist the temptation to force organic content that doesn't fit the candidate's actual personality and voice.
The practical strategic implication is for campaigns to use organic social to establish their voice, generate earned media, and raise early awareness and funds—particularly for less-known candidates in the primary phase—while investing those raised funds into disciplined paid media as the general election approaches.
When it comes to creative, far too many campaigns still embrace an outdated mindset: Developing a polished 30-second television spot, then repurposing it across digital channels without thinking through adaptation, context, or modern attention spans.
But in the current media environment, that approach is no longer fit for purpose. Or, as Huelbig McLaughlin puts it succinctly: "People need to stop creating ads for linear TV and thinking that they translate directly to digital."
The fundamental challenge is attention. Whether a voter is watching CTV, scrolling through social content, or listening to a podcast, they are in an inherently different cognitive mode than a traditional broadcast television viewer. Attention spans are shorter, and the threshold for capturing interest is higher. A 30-second ad that might work perfectly in the context of an evening news broadcast may fail to register on a streaming platform where the viewer can skip, mute, or simply look away.
Effective creative in 2026 will require campaigns to develop platform-adapted versions of their messaging: the 30-second anchor spot for broadcast and premium CTV, a 15-second cut optimized for digital video, and a six-second bumper designed to work as a pure impression. The good news is that AI-assisted creative tools are making this kind of versioning more accessible and less expensive than it has ever been.
The greatest looming constraint here, of course, is budget. A campaign with $50,000 in media budget, for instance, is going to approach creative testing very differently than one with $500,000 a month. But even resource-constrained campaigns can benefit from a few guiding principles: Lead with the most important message in the first three seconds, design for sound-off viewing on social, and ensure that every creative asset has a clear and singular call to action.
Political Advertising Creative Best Practices:
Artificial intelligence has become impossible to ignore in any conversation about marketing, and political advertising is no exception. But there is a significant gap between the hype around AI and the practical reality of what it can actually do well for political campaigns, and understanding that distinction is essential for campaigns trying to make smart decisions about where to invest in AI capabilities.
The areas where AI creates the most tangible value for political advertisers in 2026 generally fall into two broad categories: campaign optimization and creative development.
On the optimization side, AI-powered bidding and campaign management tools offer real efficiency and ROAS gains for campaigns managing complex multi-channel buys. AI can process far more data signals than any human media buyer, adjusting bids and allocations in near-real-time based on performance data. For campaigns running programmatic CTV, audio, display, native, search, and/or social simultaneously, this kind of automated optimization can meaningfully improve performance without requiring additional headcount.
On the creative side, AI is becoming a reliable tool for creative testing and iteration. The ability to quickly generate multiple versions of ad copy, test different message framings with focus groups or panel research, and identify which creative elements are resonating—at a speed and cost that would have been prohibitive even a few years ago—is a real competitive advantage. "Using AI for creative testing is going to add meaningful efficiency and effectiveness gains," says Vasil.
Of course, the risks of AI in political advertising are also quite real, and campaigns should approach the technology with appropriate care.
Perhaps the most significant concern is AI-generated content that misleads voters—whether through deepfakes, manipulated audio, or fabricated quotes attributed to real candidates and officials. This concern, sadly, is no longer hypothetical: The technology required to produce convincing deepfake content is now widely accessible, and bad actors will almost certainly use it in the 2026 cycle.
Meanwhile, on the compliance side of the equation, platform policies around AI disclosure are moving quickly. Google already requires political advertisers to disclose any use of AI in their ads, and similar requirements are likely to proliferate across platforms. Meta does the same, albeit in only certain circumstances. And a UChicago Harris/AP-NORC Poll found that voters strongly prefer that political ads disclose any use of AI, a finding that should help curb any temptations to omit disclosures even where they are not yet required.
The regulatory approach to AI usage in political advertising remains somewhat of a moving target, but the directional trend points toward greater transparency, more required disclosures, and tighter platform enforcement. Campaigns that build disclosure compliance into their workflow now will be better positioned as requirements evolve.
Misinformation and disinformation have had a prominent presence in every recent election cycle, but AI is changing its character.
The same tools that make it easier to test creative messages and generate ad variations can also be used to produce misleading content at scale and speed that would have been impossible just a few years ago. With trust in news sources and political information already eroding, the 2026 cycle will require campaigns to actively work to build and maintain credibility with voters who are increasingly skeptical of everything they see.
In an environment where voters are increasingly questioning what is real and making personal decisions about what constitutes “fact” vs. “opinion,” campaigns need to demonstrate their authenticity through more than just advertising. Being visible in communities, having candidates with verifiable records and clear commitments, and using paid media to amplify genuine moments rather than manufactured ones can help create foundations of trust that advertising can subsequently reinforce and build upon.
Additionally, brand safety tools from verified partners remain essential for ensuring that campaign ads are not serving alongside misinformation and disinformation, or appearing in contexts that could damage the campaign's credibility. Tools from providers like Comscore and Peer39 offer contextual controls that should be standard practice for any political media buy.
But importantly, campaigns cannot count on technology alone to handle the disinformation problem on their behalf. Trust and safety teams at major tech companies have been substantially reduced in recent years, and while platforms continue to invest in automated content moderation, the volume and sophistication of AI-generated misinformation and disinformation is growing faster than defensive capabilities. Political advertisers need their own mitigation strategies—including clear messaging frameworks, rapid response protocols, and media buys designed to maintain a commanding share of voice in competitive markets—to better protect themselves against disinformation’s most prevalent risks.
Historically, dating back to 2016 and the Cambridge Analytica scandal that rocked Facebook, the regulatory environment for political advertising has consistently trended toward increasing restrictions, with platforms tightening rules around what creative they will accept, narrowing targeting options, and expanding disclosure requirements. In 2026, however, the picture is decidedly more mixed, with some meaningful new inventory openings debuting alongside continued compliance complexity.
On the positive side for political advertisers: Publishers are opening up more and more inventory to political and advocacy advertising, drawn to the category’s astronomic ad spending and sensing an opportunity to tap into a lucrative new revenue stream—particularly during this projected record-setting midterm cycle.
At the same time, many digital publishers have added newly-rigorous vetting and disclosure requirements. Advertiser verification, signed disclaimer forms, and detailed record-keeping are becoming standard, following the model that has long been standard practice across linear television.
Political advertisers will want to seek out partners with built-in compliance infrastructure and workflows, allowing platforms to capture the information needed for regulatory disclosure in a systematic, automated way that alleviates compliance concerns and streamlines media buys. Otherwise, campaigns that cannot demonstrate clean, documented compliance with platform policies and applicable state regulations risk having their ads pulled at the worst possible moment.
The 2026 midterms will be contested on a fundamentally different media landscape than any previous cycle. The combination of cord-cutting acceleration, CTV inventory expansion, streaming audio's growing political presence, AI-driven creative and optimization tools, redistricting uncertainty, and an unusually large cohort of first-time and open-seat candidates creates both significant challenges and significant opportunities for political advertisers.
The campaigns that succeed will be those that approach the cycle with intellectual humility, strategic discipline, and a willingness to learn from the latest data. And don't make assumptions about what worked in 2022 or 2024, either: The audience has changed, the platforms have changed, and the competitive map has changed along with them. Start early, invest in better understanding your voter universe, lock in premium inventory before the crunch, build for the screens and devices your voters are actually using, treat creative as a strategic asset rather than an afterthought, and seek out experienced advertising and technology partners to support you in your goals.
Explore how Latcha + Associates integrated Basis DSP into their platform as their programmatic buying arm for a Fortune 500 automotive leader, deploying 40,000+ campaigns with 56,000 tags across 385+ dealerships in less than a week.
Latcha + Associates is a Michigan-based, full-service digital agency that specializes in brand strategy, creative development, UX, and relationship management.
While they had pitched and built a marketing platform for dealerships, Latcha + Associates realized it needed a DSP that offers spend control, data-driven automation, and scalability. After securing a leading luxury automotive client, they faced a new hurdle: managing complex media execution alongside 385+ dealerships while maintaining spend control, leveraging individual first-party data sets, and automating processes—all without adding complexity to their existing system.
In 2024, Latcha + Associates partnered with Basis to integrate Basis DSP via API into their proprietary platform and optimize its design for their new Fortune 500 client’s dealership needs. Basis’ Platform Ops team provided technical consulting, referred partner contacts, and clear documentation to ensure a seamless build.
Basis’ automation flexibilities enabled Latcha + Associates to automate the campaign development process across the dealerships, reducing manual and repetitive work for 40,000+ campaigns. The client can customize and personalize how they’d like to set up the DSP within their platform, giving them more control over what each dealer can access. In addition, Basis’ two-way integration with Google Campaign Manager (GCM) allowed them to seamlessly use and push information from GCM to Basis DSP.
Alongside the platform build project, Basis’ Customer Success team provided educational resources, including a presentation to Latcha + Associates’ client, to highlight what was possible within Basis DSP. To support faster adoption, Basis delivered tailored education—including a Programmatic 101 session for Latcha’s client—and supplied dealer-friendly resources.
In early 2025, Latcha + Associates launched a pilot run of 7,500 display campaigns across 25 dealerships, followed by a rapid rollout to 370+ dealers in which Basis expedited QA for more than 56,000 tags during this phase. To date, Latcha + Associates has successfully launched and deployed 40,000+ campaigns and plans to expand into streaming audio, connected TV, and digital video for their leading automotive client.
Since onboarding Basis DSP, Latcha + Associates' clients have seen greater success across their multi-channel campaigns, including:
“Basis DSP has been a breeze to use. Given the number of campaigns we’re building, it could get overwhelming, but its ease of use has made running these campaigns much more manageable."
- Senior Digital Media Planner, Latcha + Associates
Yousef Kattan, Founder and CEO of Truth Marketing, joins this episode of Adtech Unfiltered for a candid conversation about the state of measurement and attribution. From the myth of last-click to the limits of a so-called “single source of truth,” Yousef explores how the industry is evolving—and what it will take to get measurement right.
Together with host Noor Naseer, Kattan unpacks privacy regulation, AI-driven modeling, MTA’s future, and the growing responsibility agencies have to educate clients. As imperfect data, platform discrepancies, and CFO scrutiny intensify, this episode offers a timely conversation on strengthening measurement strategy.