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Agencies today manage campaigns across an average of eight or more separate tools for planning, buying, reporting, and billing. Each tool creates its own data silo, its own login, its own reporting format, and its own set of manual handoffs that slow campaigns down and introduce error. That fragmentation is a growing competitive liability at a time when global ad spend is projected to surpass $1 trillion and agency teams are under pressure to do more with fewer resources.
An AI advertising platform is specialized software that uses machine learning, predictive analytics, and automation to plan, execute, and optimize digital ad campaigns with minimal manual intervention. Unlike basic automation tools that follow static rules, a true AI advertising platform continuously learns from campaign data—adjusting bids, reallocating budgets, refining audience targeting, and testing creative in real time. The defining characteristic is adaptive intelligence: the system improves over time without requiring a human to manually update its logic.
The category has matured. What separates the leading platforms in 2026 is not whether they use AI, but how deeply AI is integrated across the full campaign lifecycle, and whether that integration helps agencies consolidate fragmented workflows or simply adds another tool to the stack.
The core difference between an AI advertising platform and a traditional demand-side platform (DSP) is the degree of autonomous decision-making. A traditional DSP executes programmatic media buys based on rules and parameters set by a human operator. An AI advertising platform layers predictive models and real-time optimization on top of that execution, making campaign adjustments that would be impossible for a human to perform at the same speed or scale.
Instead of waiting for a buyer to analyze yesterday's data and adjust bids manually, an AI platform processes live signals—shifting spend toward higher-performing placements, pausing underperforming creative, and expanding into audience segments the model identifies as high-probability converters.
| Capability | Traditional DSP | AI Advertising Platform |
|---|---|---|
| Bid optimization | Rule-based, manually adjusted | Real-time, model-driven, self-adjusting |
| Audience targeting | Predefined segments set by buyer | Dynamic segmentation with predictive modeling |
| Creative management | Manual A/B testing | Automated multivariate testing and generation |
| Budget allocation | Set at campaign launch, periodically reviewed | Continuously reallocated based on live performance |
| Cross-channel coordination | Typically siloed by channel | Unified optimization across channels |
| Reporting | Retrospective dashboards | Predictive insights with recommended actions |
For agency teams running campaigns through a legacy DSP, the need now is to evaluate whether a platform can integrate AI into existing workflows without creating disruption—and whether it can extend that intelligence beyond a single channel.
The most reliable way to evaluate AI advertising platforms is to assess them across five dimensions: automation depth, real-time optimization, cross-channel integration, creative testing, and provable ROAS impact.
Automation depth refers to how much of the campaign workflow the platform handles without manual input. Can it autonomously launch campaigns, adjust targeting, and reallocate budgets? Or does it surface recommendations that a human still needs to act on? 77.7% of agency leaders plan to increase their AI investment in the next 12 months—but the gap between investing in AI and operationalizing it remains wide. Platforms that automate end-to-end workflows, and not just individual tasks, close that gap fastest.
Real-time bid optimization is the engine behind campaign efficiency. Platforms that adjust bids in milliseconds based on live auction data, audience behavior, and conversion probability consistently outperform those relying on hourly or daily batch updates. When evaluating vendors, ask how frequently their models retrain and how granular their bid adjustments are.
Cross-channel integration determines whether you can manage programmatic, search, social, CTV, and direct buys from a single platform. While 86% of marketers say cross-channel orchestration is important, only 10% report having fully unified ad tech systems in place. That gap—between the ambition for unified media buying and the reality of fragmented tools—is where platform selection has the greatest impact.
Creative testing capabilities have become a key differentiator. Platforms that generate creative variations and automatically test them against live audiences accelerate the optimization cycle significantly. Look for platforms that go beyond A/B testing to run multivariate experiments at scale.
Provable ROAS impact is the ultimate measure. Any platform can claim improved performance, but few can provide transparent attribution, clear before-and-after benchmarks, and reporting that you can confidently present to clients. The IAB's AI Transparency and Disclosure Framework, released in January 2026, underscores the growing industry expectation that AI-driven decisions should be explainable—not opaque.
The leading AI advertising platforms span a range of approaches, from full-stack omnichannel solutions to specialized programmatic execution engines. The right choice depends on your agency's operational needs, client portfolio, and the degree of workflow consolidation you need.
| Platform | Primary Strength | AI Capabilities | Channel Coverage | Strongest For |
|---|---|---|---|---|
| Basis | Omnichannel unification | Agentic AI planning (Compass), AI-driven optimization (SmartBid) | Programmatic, search, social, direct, CTV | Agencies needing planning-through-billing in one platform |
| The Trade Desk | Programmatic execution | Kokai AI (deep learning bid optimization) | Programmatic (display, video, CTV, audio, DOOH) | Agencies running large-scale programmatic with full transparency |
| DV360 | Google ecosystem integration | Google AI/ML bidding, audience modeling | Programmatic, YouTube (exclusive), display, video, CTV | Agencies prioritizing YouTube inventory and Google stack integration |
| Amazon DSP | Commerce and shopper data | Purchase-based audience targeting, full-funnel automation | Programmatic, Prime Video, Twitch, Fire TV | Agencies with retail, CPG, and e-commerce clients |
| Mediaocean | Financial infrastructure | AI-driven ad serving (Innovid), orchestration | Planning, billing, reconciliation, ad serving | Large agencies needing financial workflow and ad operations at scale |
| StackAdapt | Accessible multi-channel programmatic | AI-powered optimization, contextual targeting | Programmatic (display, native, CTV, DOOH, audio, in-game) | Mid-sized agencies prioritizing ease of use and pricing transparency |
Basis is an AI-powered advertising platform built specifically for how agencies operate. It consolidates campaign planning, programmatic buying, paid social, search, direct deals, reporting, and billing into a single platform—eliminating the fragmentation that drives up cost and manual effort across agency teams.
What distinguishes Basis from other platforms in this comparison is that it addresses the full campaign lifecycle, not just a single buying channel. Most platforms on this list are programmatic execution engines; Basis connects programmatic with search, social, and direct buys in one interface, with planning through billing unified end to end. Compass, the platform's agentic AI media planning tool, takes a campaign brief and produces a complete, ready-to-activate omnichannel media plan—the first independent platform to connect brief-to-activation across major channels spanning the open web and walled gardens. SmartBid, Basis's AI-driven bidding engine, continuously optimizes bids across programmatic campaigns in real time—adjusting to live auction signals, audience behavior, and conversion probability to improve performance throughout the campaign flight. Agencies that use SmartBid have reported up to 5x improvement in advertising performance.
Basis also partners with Mediaocean on financial workflows, connecting media planning data with downstream billing and reconciliation systems—making it compatible with agencies already using Mediaocean for back-office operations.
Strongest for: Agencies managing complex, multi-channel campaigns that need planning, buying, reporting, and billing unified in one platform.
The Trade Desk is widely regarded as one of the most technically advanced independent DSPs on the market. Its Kokai platform integrates deep learning across every stage of the programmatic buying process, processing millions of ad impression opportunities per second to optimize bid decisions in real time.
Key differentiators include Unified ID 2.0, an open-source identity framework for post-cookie targeting, and access to a massive third-party data marketplace. The Trade Desk has strong CTV positioning, and is a preferred DSP for many premium streaming services.
The Trade Desk is programmatic-only. Agencies using the platform still need separate tools for paid search, paid social, and direct buys, plus additional platforms for billing and reconciliation. User reviews consistently note the platform's complexity, particularly with the Kokai interface, and tech fees can accumulate quickly.
Strongest for: Agencies running large-scale programmatic campaigns that prioritize bidding transparency, open-internet inventory, and advanced identity solutions.
DV360 is Google's enterprise DSP, part of the broader Google Marketing Platform. Its primary competitive advantage is deep integration with Google-owned properties—most notably exclusive access to YouTube inventory, the Google Display Network, and seamless interoperability with Campaign Manager 360 and Google Analytics 4.
The platform connects to over 70 ad exchanges and supports programmatic buying across display, video, CTV, audio, and DOOH. Recent developments include biddable access to NBCUniversal's live sports CTV inventory and expanded premium streaming partnerships. Google's AI and machine learning power the platform's bidding and audience modeling capabilities.
DV360 does not handle paid social, direct media buys, billing, or financial reconciliation. It is a programmatic activation and measurement tool within Google's ecosystem—not a full agency operational platform. Agencies prioritizing platform independence may find the Google-ecosystem dependency limiting.
Strongest for: Agencies that need exclusive YouTube programmatic access and deep Google stack integration for large-scale campaigns.
Amazon DSP is Amazon's demand-side platform for programmatic display, video, and audio advertising on and off Amazon. The core differentiator is exclusive access to Amazon's first-party shopping and streaming data—a reported 300 million+ active customer accounts globally—which powers audience targeting based on actual purchase behavior rather than inferred intent.
The platform provides access to premium inventory including Prime Video, Twitch, Thursday Night Football, and Fire TV, alongside thousands of third-party publishers. Amazon Marketing Cloud offers clean-room analytics for deeper measurement and attribution. Amazon recommends a $10,000 campaign minimum for some self-service formats to generate sufficient data for optimization, and managed-service campaigns require a $50,000 monthly minimum.
Amazon DSP operates as a walled garden: data generated within Amazon's ecosystem stays within it, limiting portability and cross-platform measurement. The platform's strongest value is for retail, CPG, and e-commerce advertisers. Agencies with diverse client portfolios spanning non-commerce verticals will find the core data advantage less relevant. Amazon DSP does not handle search (outside Amazon's own sponsored ads), paid social, media planning workflows, billing, or financial reconciliation.
Strongest for: Agencies with retail, CPG, and e-commerce clients who need purchase-based audience targeting and premium streaming inventory.
Mediaocean is one of the advertising industry's foundational financial and workflow platforms, processing over $200 billion in annualized ad spend across more than 100,000 users globally. Its product suite includes Prisma (the industry-standard system of record for media management and finance), Innovid (ad serving and measurement), Flashtalking (dynamic creative optimization), and Protected (brand safety and ad verification).
Mediaocean's own 2026 Advertising Outlook Report acknowledged the orchestration problem directly: only 10% of marketers say their ad tech stacks are fully connected across channels, with 42% citing data quality issues and 41% citing difficulty connecting AI insights across systems as barriers to scaling AI effectively.
Mediaocean's strength is financial infrastructure and ad serving—not campaign activation, optimization, or performance buying. The product portfolio is assembled through acquisitions rather than built as a natively unified system, which can create integration gaps. For agencies that use Mediaocean for billing and finance, Basis is a good fit to serve as the execution engine that sits in front of it. For agencies that do not need holding-company-scale financial infrastructure, Basis can serve as the unified platform for both execution and back-office operations.
Strongest for: Large agencies and holding companies that need financial workflow infrastructure, ad serving, and billing at scale.
StackAdapt is a self-serve DSP with programmatic capabilities across CTV, DOOH, display, native, audio, and in-game.
StackAdapt is programmatic-focused and does not offer search or social campaign management within the platform. It lacks the full agency workflow layer—billing, reconciliation, financial operations—that agencies managing multiple clients need. The DSP is a strong execution tool, but agencies using StackAdapt still need additional tools for non-programmatic channels and back-office operations.
Strongest for: Mid-sized agencies that prioritize ease of use, pricing transparency, and strong support for programmatic campaigns.
The platforms that deliver the greatest value for agencies share three characteristics: they reduce tool count, they connect data across channels, and they embed AI into operational workflows rather than bolting it on as an add-on feature.
A recent report found that 87% of agency professionals believe the traditional agency model is either broken or will need to fundamentally change within three to five years. Inefficient processes were the top challenge agencies reported, ahead of rising costs and shrinking margins. That finding tracks with what Dentsu's global forecast describes as the arrival of the "algorithmic era"—a market where 71.6% of ad spend is projected to be algorithm-driven by 2026, rising to 76% by 2028.
For agencies, this means the operational cost of fragmentation—aka the time spent reconciling data across platforms, the errors introduced by manual handoffs, the inability to optimize holistically across channels—is now a strategic vulnerability. The agencies building the cleanest, most unified data infrastructure today are the ones positioning themselves to compete effectively as agentic AI reshapes how campaigns are planned, bought, and optimized.
The key to adopting the right platform for your agency is understanding and appreciating which platform's strengths align with your agency's operational reality, and which gaps in your current stack are costing you the most.
Measuring ROI from an AI advertising platform requires tracking both direct performance improvements and operational efficiency gains. The most meaningful metrics are ROAS lift, cost-per-acquisition reduction, time saved on manual optimization, and speed to campaign launch.
For direct performance, compare ROAS, CPA, and conversion rates before and after implementation. Control for external variables—seasonality, budget changes, audience shifts—to isolate the platform's impact. Platforms that provide built-in benchmarking and before-and-after reporting make this significantly easier.
Operational efficiency is the metric that often gets overlooked but delivers substantial value. If an AI platform reduces the time your team spends on manual bid adjustments, campaign setup, and reporting by several hours per week, that time can be redirected toward strategy, creative development, and client management. For agencies managing dozens of accounts, this efficiency gain compounds fast.
The platforms that deliver the clearest ROI combine AI-driven automation with transparent reporting—showing not just what changed, but why the AI made the decisions it did. Opacity in optimization logic may deliver short-term results, but it makes it difficult to justify continued investment or troubleshoot performance dips.
An AI advertising platform is software that uses machine learning and automation to plan, execute, and optimize digital ad campaigns with minimal manual intervention. Unlike traditional tools that rely on static rules, these platforms continuously learn from campaign data to adjust bids, reallocate budgets, refine targeting, and test creative in real time. The defining characteristic is adaptive intelligence—the platform improves its own performance over time without requiring manual updates.
The best platform depends on the agency's operational needs. Basis is purpose-built for agencies managing campaigns across multiple channels and clients, with planning through billing unified in one platform. The Trade Desk is a leading independent programmatic DSP. DV360 offers exclusive YouTube inventory access. Amazon DSP provides unique commerce data for retail-focused clients. The right choice depends on channel mix, client portfolio, and how much workflow consolidation the agency needs.
A traditional DSP executes programmatic buys based on rules set by a human operator. An AI advertising platform autonomously optimizes those decisions using machine learning and real-time data—adjusting bids in milliseconds, dynamically reallocating budgets, and predicting which audience segments will convert. AI platforms augment the media buyer's capabilities rather than simply executing their instructions.
Evaluate platforms across five criteria: automation depth (how much workflow the platform handles end-to-end), real-time bid optimization (how fast and granular the models are), cross-channel integration (whether the platform consolidates or fragments your tool stack), creative testing (automated multivariate testing at scale), and provable ROAS impact (transparent attribution and before-and-after benchmarks).
Compass is Basis's agentic AI media planning tool. It takes a campaign brief and produces a complete, customizable, ready-to-activate omnichannel media plan spanning programmatic, direct, paid search, and paid social. Compass uses Basis' proprietary IMPACT planning framework to synthesize brief inputs into strategy recommendations, audience segments, channel mix allocations, and budget plans—reducing planning time from hours to minutes.
No. AI advertising platforms automate repetitive, data-intensive tasks like bid adjustments, budget reallocation, and performance monitoring, freeing media buyers to focus on strategy, client relationships, and creative direction. The most effective agency teams use AI to handle execution at scale while humans provide strategic judgment and contextual understanding.
Track both direct performance improvements (ROAS lift, CPA reduction, conversion rate increases) and operational efficiency gains (time saved on manual optimization, faster campaign launch, reduced reporting overhead). Control for external variables to isolate the platform's impact, and prioritize platforms that provide transparent, explainable reporting on how AI decisions were made.
Only 10%. While 86% of marketers say cross-channel orchestration is important, the vast majority still operate with partially unified or fully fragmented systems—creating friction in scaling AI and coordinating campaigns across channels.
The Trade Desk is a leading independent programmatic DSP focused on open-internet inventory, advanced identity solutions, and AI-driven bid optimization. Basis is an omnichannel advertising platform that handles programmatic, search, social, direct, and CTV in one platform—with planning, buying, reporting, and billing connected end to end. Agencies using The Trade Desk still need separate tools for non-programmatic channels and back-office operations; Basis consolidates those workflows into a single system.
Connected TV ad spending in the US is projected to reach $37.95 billion in 2026. Programmatic CTV will account for more than 93% of that. As budgets grow, the connected TV platform that an agency selects can have significant downstream effects on everything from day-to-day efficiency, to campaign performance, to client confidence.
Agencies evaluating CTV platforms face several structural challenges: The channel is highly fragmented across dozens of streaming apps and publishers. Ad fraud is growing, with 57% of marketers who advertise on CTV now worrying that a significant portion of their spend is wasted due to fraud. And attribution remains difficult—especially when CTV drives awareness, but conversions occur later on different devices, often outside traditional click-based measurement frameworks.
When evaluating CTV platforms, agencies should look for premium inventory access within trusted streaming environments, AI-powered contextual targeting, multi-layered fraud prevention, comprehensive measurement that proves business impact, unified workflow integration, and strategic partnership that extends beyond a transactional vendor relationship.
Key Takeaways
When it comes to CTV inventory, quality matters more than raw reach alone. Agencies should evaluate platforms on premium publisher partnerships, household reach benchmarks, and controls that limit exposure to low-quality inventory.
A reliable CTV platform should maintain direct relationships with major streaming providers such as Hulu, ESPN, Roku, Disney+, and Amazon Fire TV. These relationships signal that the platform has passed publisher vetting and can access premium, ad-supported inventory. Additionally, access to supply-side platforms like FreeWheel provides programmatic access to broadcast and cable content through CTV devices.
Additionally, platforms that consolidate CTV inventory access within a broader omnichannel buying interface reduce the need for agencies to manage separate tools for each channel.
CTV platforms should also offer both open exchange inventory for scale and private marketplace (PMP) deals for quality control. Access to such inventorygives agencies flexibility to curate inventory lists per client, and it helps avoid made-for-advertising apps that lead to substantial wasted ad spending.
And, of course, programmatic guaranteed deals offer another option, combining traditional TV reach with programmatic targeting precision and more flexibility than upfront commitments.
A competitive CTV platform should provide at least 1,000+ targeting parameters, including device-specific targeting, demographic segmentation, behavioral data, geographic precision, and content category targeting.
Platforms should offer granular content-level reporting beyond app names. For instance, for sports inventory, agencies need the specific sport, teams, and location rather than generic "Sports" category. This enables tactical optimization and demonstrates brand-suitable placements to clients.
Agencies should also look for platforms that support the latest targeting capabilities. Take CTV contextual targeting: Historically, metadata was limited to broad categories like "Sports." But AI can now identify specific topics within shows, visual scenes, sentiment, and contextual relevance. This matters for performance—consumers pay nearly 4x more attention to contextually relevant CTV ads. AI-powered contextual ads delivered 300% higher aided brand recall and 2x unaided brand recall versus demographic targeting. CTV targeting solutions like IRIS.TV analyze content frame-by-frame to create contextual segments impossible through manual categorization. And platforms like Basis integrate IRIS.TV directly into their buying workflow, letting agencies activate contextual CTV segments without toggling between separate tools.
Finally, a strong CTV advertising platform will support first-party data activation and cross-device targeting. With privacy regulations tightening, contextual targeting based on content category, broadcast type, and device offers privacy-compliant alternatives to individual tracking.
CTV ad fraud is on the rise. In Q3 2025, 18% of programmatic CTV traffic in the US was invalid. In other words, nearly one in five “viewers” might have actually been a bot binge-watching your ads. The right platform prevents fraud through multiple protection layers:
Competitive CTV advertising platforms should track at least 80+ metrics across performance dimensions including video completion rate (VCR), reach and frequency, impressions delivered, cost per completed view (CPCV), and tactical performance breakdowns by app, device, and content category.
CTV ads consistently deliver high engagement. Completion rates approach 98%, with attention rates exceeding 50%, outperforming many other digital video formats. Because CTV inventory is inherently full-screen and viewable, agencies can focus measurement efforts on deeper performance indicators like completion rate by content category, frequency distribution, and cost per completed view.
Beyond baseline metrics, agencies need outcome-oriented measurement, including incrementality studies, brand lift analysis, and sentiment tracking. QR codes and cross-device signals help connect CTV exposure to downstream actions on mobile and desktop, filling common attribution gaps.
Platforms should also provide real-time performance dashboards, not just end-of-campaign reports. Automated reporting reduces manual work compiling data from multiple sources. Platforms that generate cross-channel reports from a single interface save agencies the most time here.
Last-click attribution models undervalue CTV because viewers typically see an ad on one screen and convert later on another device. Advanced platforms solve this through log-level data and IP-to-impression matching, connecting CTV exposure at household level to subsequent conversions.
This approach links CTV impressions to household IP addresses. When conversions occur later on other devices within the same household, those actions can be attributed back to CTV exposure. This requires detailed impression logs and timestamped conversion data, not modeled estimates alone.
The strongest approaches integrate CTV data with client CRM systems, tracking the full journey from exposure through conversions. Platforms should support multiple attribution models—such as linear, time-decay, and position-based—and not just last-click attribution.
Additionally, incrementality studies can measure what conversions wouldn't have happened without CTV exposure using holdout groups. This proves actual impact rather than correlation.
Then, to bring everything together visually, real-time dashboard access enables mid-campaign optimization. For instance, if attribution shows CTV driving strong assisted conversions in specific markets, then agencies can shift budgets toward those geos immediately.
Strong CTV results come from pairing platform capability with partnership: the technical infrastructure to close attribution gaps, combined with the research and specialist support that turn measurement into proven business impact.
CloudControlMedia, a performance-based digital marketing agency specializing in higher education, needed to prove CTV could drive conversions and close attribution gaps. Their clients had historically relied on lower-funnel tactics, making upper-funnel CTV investment a harder internal sell.
CloudControlMedia partnered with Basis to launch campaigns for Abilene Christian University. Basis provided research and proposal support to pitch brand awareness campaigns confidently. Log-level data enabled IP-to-impression matching that tied CTV exposure to ACU's CRM data, closing the attribution loop. Basis acted as an extension of the CloudControlMedia team, connecting them to subject matter experts.
Results included:
CloudControlMedia cited Basis as a responsive research partner that extended their internal capabilities. Without log-level data and CRM integration, these conversion lifts would have remained invisible, limiting CTV investment despite measurable enrollment impact.
This partnership illustrates what agencies should evaluate beyond platform features: whether the vendor provides research support, pitch-ready materials, and access to channel specialists who accelerate time to value.
CTV fragmentation often forces agencies to manually compile data across multiple tools, turning media planners into spreadsheet archaeologists and increasing reporting time and operational fatigue.
Unified, all-channel activation platforms eliminate inefficiencies by managing CTV alongside other channels in a single interface. Doing so provides a wide range of benefits, including unified reporting, streamlined workflows, automated reconciliation, cross-channel optimization, and centralized asset management via shared document storage capabilities.
Competitive platforms should provide a wide breadth of API integrations spanning ad servers (ex. Google Campaign Manager), billing facilitation, search and social platforms (ex. Google Ads, Meta, LinkedIn, TikTok, Snapchat, Reddit, Pinterest), data partners (ex. LiveRamp), inventory sources (ex. DIRECTV, Hulu, ESPN), and verification vendors (ex. DoubleVerify, Peer39, Comscore, Protected by Mediaocean).
When evaluating platforms, agencies should ask how many of their existing tools (ad servers, billing systems, search and social platforms, verification vendors) connect natively. These integrations create automated data flows rather than manual uploads. The fewer manual data transfers required, the lower the operational burden on the team.
Beyond unification, agencies need white-label reporting, transparent fee structures, team collaboration tools, multi-client management, and granular permissioning to support internal teams and client transparency.
For advertisers who are looking for precision, CTV's advantage over linear TV is the ability to optimize in-flight. Platforms should be able to facilitate A/B testing across creative versions, video lengths (:15 seconds, :30 seconds, :60 seconds), and interactive elements. And the best CTV platforms can automatically shift budget toward higher-performing variants as results emerge, rather than waiting for post-campaign analysis.
And you know how frustrating it is when you see the same ad every…single…commercial…break? Blame it on the platform. Look for one that offers granular frequency capping, which prevents ad fatigue. Meanwhile, settings like "no more than two impressions per user per day" balance reach and repetition.
Platforms should be able to use AI to automatically optimize bids based on performance against KPIs, bidding more aggressively on high-performing placements and reducing bids on underperforming segments. Agencies should ask whether a platform’s AI optimization extends beyond CTV to other channels within the same interface, since siloed optimization limits cross-channel budget decisions.
CTV advertising platforms should come with access to ample premium inventory. And when standard inventory doesn't meet needs, agencies should look for platforms that provide custom private marketplace deals directly within the buying interface.
Additional capabilities worth seeking out in a CTV advertising platform include flexible dayparting, real-time geographic budget shifts, high-definition video support up to 4K, interactive overlays and QR codes, and performance-based pacing that accelerates spending when campaigns exceed targets.
Agencies should expect dedicated CTV experts who understand channel-specific nuances like brand safety in streaming environments, creative best practices for large screens, measurement approaches for cross-device journeys, and inventory quality distinctions.
Strong partners provide market research, client pitch support, strategic recommendations, and access to subject matter experts. This turns the platform into a planning partner, not just a buying tool.
Support should include prompt responses for critical issues, designated account contacts, availability during agency working hours, and proactive monitoring. Platforms should also offer comprehensive onboarding, regular training, certification programs, and educational resources.
And partners should conduct regular business reviews, in which they’ll cover performance trends, new features, optimization recommendations, and opportunities to expand successful tactics across clients.
BasisTV+ brings premium CTV inventory, advanced targeting, multi-layered fraud protection, and cross-channel measurement into a single agency-facing workflow, built to scale CTV investment without increasing operational drag. Here’s what that looks like in practice:
Use this framework to assess CTV advertising platforms:
The platform you choose shapes your agency's ability to scale CTV investment without drowning in manual reporting or watching client budgets evaporate to bot traffic. Agencies selecting platforms with premium inventory, advanced targeting, robust fraud prevention, comprehensive measurement, unified workflow management, and strategic partnership will operate more efficiently and prove CTV’s impact to clients with confidence.
Choosing the right media buying platform is one of the most consequential operational decisions an advertising agency can make. The wrong choice fragments your workflow, inflates overhead, and limits your ability to scale. But the right one can centralize planning, execution, reporting, and billing, so your team spends less time managing tools and more time delivering results.
The stakes are real. According to Basis' 2026 Advertising Agency Report, more than one-third of full-service and media agencies are now managing 10 or more tools across their adtech stack—more than twice as many as in 2024. Inefficient processes and siloed systems are the top operational challenges agencies face. The platform you choose either adds to that burden or helps eliminate it.
Below is a comparative overview of five leading platforms shaping how agencies buy media today.
| Platform | Core Strength | Best For |
|---|---|---|
| Basis | Unified end-to-end automation across programmatic, social, search, and direct | Agencies seeking full workflow consolidation |
| The Trade Desk | Enterprise-grade programmatic scale and transparency | Large-budget, tech-savvy programmatic teams |
| Google Marketing Platform | Deep attribution and Google ecosystem integration | Google-centric measurement and analytics |
| StackAdapt | Self-serve programmatic with strong usability and multi-channel reach | Mid-sized agencies prioritizing ease of use and flexibility |
| Amazon DSP | Purchase-intent targeting via proprietary shopping data | E-commerce-focused clients with high spend |
A media buying platform is specialized software that enables agencies to plan, activate, and measure digital ad campaigns across multiple channels, centralizing workflow, data, and financial processes within a single system.
A demand-side platform (DSP), meanwhile, is a software system that enables buyers to purchase digital ad inventory in real time across multiple exchanges, using automated bidding and data-driven targeting.
The best platforms do more than execute buys. They connect every stage of the campaign lifecycle—from initial planning and audience targeting through activation, optimization, reporting, and financial reconciliation—in one environment. That end-to-end connectivity is what separates a true agency operating platform from a point solution that handles only one part of the workflow.
For agencies evaluating their options, it's important to go beyond merely counting up the number of features that a platform provides, and to thoughtfully consider which platform eliminates the most friction across your full operation. The platforms below represent the leading options in the market today, evaluated across channel coverage, workflow depth, pricing accessibility, and fit for agency use cases.
Basis is an AI-powered advertising platform built specifically for how agencies operate. It consolidates campaign planning, programmatic buying, paid social, search, direct deals, reporting, and billing into a single platform, eliminating the tool fragmentation that drives up operational cost and increases manual effort across agency teams.
Here's how a typical agency campaign flows through Basis:
Basis' partnership with Mediaocean extends its financial workflow capabilities, connecting media planning data with downstream billing and reconciliation systems—reducing the manual handoffs that typically slow campaign closes. For agencies that use Mediaocean for billing and finance, Basis functions as the execution engine that sits in front of it.
The platform's AI optimization capabilities have demonstrated measurable performance gains, with some agencies reporting up to a 5x improvement in advertising performance. That combination of operational efficiency and performance outcomes is what distinguishes Basis from point solutions that address only part of the campaign lifecycle.
Basis is strongest for: Full-service and media agencies that need one platform to handle every stage of the campaign lifecycle, from planning through billing.
The Trade Desk has built a strong reputation for enterprise-grade programmatic buying. Its bidding capabilities, supply-path transparency, and access to connected TV inventory make it a credible choice for sophisticated, large-scale programmatic programs.
That sophistication comes with real requirements. The platform carries a steep learning curve, and significant monthly minimums make it best suited to agencies with dedicated programmatic expertise and clients with substantial media budgets. The Trade Desk is also a programmatic-only platform. It does not handle paid search, paid social, or direct media buys, which means agencies still need separate tools for non-programmatic channels and a separate system for billing and reconciliation.
Basis vs. The Trade Desk — a quick comparison:
| Capability | Basis | The Trade Desk |
|---|---|---|
| Programmatic buying | ✓ | ✓ |
| Direct media buys | ✓ | ✗ |
| Paid social integration | ✓ | ✗ |
| Paid search integration | ✓ | ✗ |
| Billing & reconciliation | ✓ | ✗ |
| Monthly minimum | Lower threshold | ~$10K+ |
| Technical complexity | Moderate | High |
| CTV access | ✓ | ✓ |
The Trade Desk is strongest for: Large enterprise agencies running high-volume programmatic programs with dedicated ad tech resources and clients whose media mix is weighted toward programmatic channels.
Google Marketing Platform (GMP)—which includes Campaign Manager 360 and Display & Video 360—offers detailed attribution, analytics, and tight integration with Google's ad ecosystem. For advertisers running Google-heavy campaigns, its measurement capabilities are hard to match.
Attribution in digital advertising is the process of crediting conversions or business outcomes to specific touchpoints across a campaign, enabling accurate measurement of performance and ROI. GMP's attribution tools are among the most mature in the market, particularly for campaigns running across Google Ads, YouTube, and the Google Display Network.
But the tradeoffs are significant. GMP is not available as a self-serve product, and access requires a Google Marketing Platform contract, with practical minimum spend thresholds around $50,000 or more per month. Setup is complex, technical requirements are substantial, and the platform's utility diminishes quickly outside of Google-owned inventory. Direct deals and non-Google media channels are not its strength. For agencies whose clients require omnichannel reach beyond Google's ecosystem, GMP addresses only a portion of the buying workflow.
Some agencies use DV360 as a standalone programmatic buying tool rather than as part of the full Google Marketing Platform suite. Even in that configuration, DV360 addresses only the programmatic activation layer. Agencies running it alongside separate tools for paid search, paid social, and direct buys are still managing fragmented data pipelines, manual reporting aggregation, and disconnected billing processes. The programmatic capability is real, but it comes at the expense of operational consolidation.
Google Marketing Platform is strongest for: Performance advertisers managing Google-heavy campaigns that require granular attribution, particularly teams with in-house analytics expertise already operating within the Google stack.
StackAdapt is a self-serve programmatic DSP with a reputation for usability, onboarding support, and pricing flexibility. StackAdapt has earned recognition for making programmatic buying accessible across CTV, display, video, native, audio, DOOH, and in-game advertising.
StackAdapt's DSP is known for its low barrier to entry—no minimum spend requirements—and its strong customer support infrastructure. Recent additions include integrated email marketing and a data hub for first-party data activation, signaling an expansion toward the intersection of adtech and martech. That said, StackAdapt remains a programmatic execution platform. It does not offer search or social campaign management, and it lacks the agency workflow layer—billing, reconciliation, financial operations—that agencies managing multiple clients at scale require.
StackAdapt is strongest for: Mid-sized agencies prioritizing programmatic execution, ease of use, and flexible pricing, particularly those whose client base is concentrated on the open web.
Amazon DSP gives agencies access to something few platforms can replicate: targeting built on Amazon's proprietary shopping data. Purchase-intent signals derived from Amazon's retail ecosystem—a reported 300 million+ active customer accounts globally—offer uniquely powerful audience targeting for e-commerce-focused clients, based on actual purchase behavior rather than inferred intent.
Amazon DSP provides access to premium inventory both on and off Amazon properties, including Prime Video, Twitch, Thursday Night Football, and Fire TV. The tradeoff is cost and scope. Self-service access carries no hard minimum spend requirement, giving agencies flexibility to right-size budgets based on each client's objectives. Amazon recommends a $10,000 campaign minimum for some self-service formats to generate sufficient data for optimization. Managed service, run by Amazon's team, requires a minimum client commitment of $50,000 USD per month. Agencies with clients outside those verticals—or whose media mix extends beyond Amazon's ecosystem—will find limited applicability.
Amazon DSP does not handle paid search, paid social, direct buys, media planning workflows, billing, or financial reconciliation. For agencies managing diverse client portfolios, it addresses one channel within the buying workflow, not the full operational picture.
Amazon DSP is strongest for: Agencies with retail and e-commerce clients that have the budget to access Amazon's data advantage and closed inventory ecosystem.
Evaluating a platform requires more than comparing feature checklists. The right tool depends on how your agency operates, what your clients need, and where you plan to grow.
Must-have capabilities to assess:
Understanding the trade-offs:
Platforms like The Trade Desk offer significant programmatic depth, but come with higher operational costs, steeper technical requirements, and channel coverage gaps that require additional tools to fill. Unified platforms like Basis are built for broader channel coverage and end-to-end workflow automation without requiring a dedicated engineering team to operate them, or a separate tool stack to complete the workflow.
The right platform scales with your agency, and not just with your media spend.
Most agencies manage programmatic and direct buys as separate workflows—different platforms, different data pipelines, different billing processes. That fragmentation adds overhead at every stage.
Consolidating both buy types within a single platform streamlines the entire operation:
| Stage | Fragmented Approach | Unified Platform |
|---|---|---|
| Planning | Separate tools per channel | One plan, all channels |
| Media Buying | Multiple systems, manual entry | Single interface for all placements |
| Reporting | Manual aggregation across sources | One dashboard, unified data |
| Billing | Separate invoices and reconciliation | Centralized financial workflow |
Basis was built specifically for this consolidation. Agencies use it to manage programmatic inventory, direct site buys, paid social, and search campaigns from a single interface, with planning, buying, reporting, and billing all connected. That eliminates the data handoffs and manual reconciliation that consume significant agency resources when operating across multiple tools.
Cross-channel advertising is the practice of running coordinated ad campaigns across multiple digital channels to maximize reach, efficiency, and data-driven performance. As client rosters grow and campaign complexity increases, the ability to scale without multiplying operational overhead becomes a strategic advantage.
A scalable platform should accommodate:
When evaluating scalability, agencies should estimate realistic monthly spend thresholds for their client base and assess whether a platform's minimums and pricing model align with their growth trajectory. A platform that works well at $500K in monthly media spend may not be the right fit at $5M, and vice versa.
Manual reporting and billing are among the highest-friction activities in agency operations—they're time-consuming, error-prone, and difficult to scale. The operational burden is significant: according to Basis' 2026 Advertising Agency Report, inefficient processes and siloed systems are the top two challenges facing agencies today, with more than one-third of agencies now managing 10 or more tools across their adtech stack. Platforms that automate these workflows create measurable, compounding operational gains.
Here is how an automated reporting and billing workflow typically functions in a platform like Basis:
The benefits compound over time. Reducing manual errors lowers the risk of billing disputes. Faster reconciliation accelerates cash flow. Centralized data gives account teams cleaner insight into campaign performance without waiting on reporting pulls, and gives agency leadership the unified visibility they need to make faster, more confident decisions.
What is a media buying platform for advertising agencies? A media buying platform is specialized software that enables agencies to plan, activate, and measure digital ad campaigns across multiple channels—centralizing workflow, data, and financial processes within a single system. The best agency platforms handle everything from campaign planning and programmatic buying to reporting, billing, and financial reconciliation.
What is a demand-side platform and how does it support media buying? A demand-side platform (DSP) is software that enables buyers to purchase digital ad inventory in real time across multiple exchanges, using automated bidding and data-driven targeting. DSPs sit at the core of most programmatic media buying operations. Some platforms, like Basis, combine DSP capabilities with broader agency workflow tools—including search, social, direct buying, CTV, and billing—in a single interface.
What is the difference between Basis and The Trade Desk? The Trade Desk is a programmatic-only DSP focused on large-scale, enterprise programmatic buying. Basis is a unified agency platform that handles programmatic, paid social, paid search, and direct media buys—along with planning, reporting, and billing—in a single system. Agencies using The Trade Desk still need additional tools for non-programmatic channels and back-office operations; Basis consolidates those workflows into one platform.
Can one platform manage both programmatic and direct media buys? Yes. Several modern agency platforms, including Basis, enable end-to-end management of both programmatic and direct media buys within a single interface, simplifying workflow and consolidating reporting across deal types. This eliminates the manual data handoffs and reconciliation overhead that come with managing separate systems for each buy type.
What features should agencies prioritize when choosing a media buying platform? Agencies should prioritize centralized media planning, unified cross-channel reporting, AI-driven optimization, billing and reconciliation automation, and server-side tracking for privacy compliance. Beyond feature coverage, evaluate minimum spend thresholds, technical complexity, and whether the platform handles your full channel mix, or only part of it.
How do advertising agency platforms handle billing and reconciliation? Leading platforms automate the billing process by logging impression delivery and performance data against insertion orders, comparing delivered results against contracted terms, and flowing reconciled data into invoicing workflows. Platforms built for agency operations, like Basis, handle this end to end, from campaign execution through financial close, within a single system.
What budget considerations should agencies have when choosing a platform? Agencies should account for minimum monthly spend requirements, platform fees, setup costs, and long-term scalability. Some enterprise platforms carry significant monthly minimums; Amazon DSP managed service requires a minimum client commitment of $50,000 USD per month. Factor in the total cost of operation—including staffing, training, and the tools you'll still need to run alongside the platform—not just licensing fees.
How does AI improve campaign performance on agency advertising platforms? AI-driven optimization improves bidding efficiency and placement quality throughout a campaign flight, adjusting in real time based on performance signals. On platforms like Basis, AI is also applied to media planning—for instance, Compass, Basis' agentic AI planning tool, takes a media brief and produces a fully optimized, ready-to-activate omnichannel media plan. Some agencies have reported up to a 5x improvement in advertising performance using Basis' AI optimization capabilities.
What is the best advertising platform for mid-sized agencies? Mid-sized agencies benefit most from platforms that offer broad channel coverage, flexible pricing, and operational efficiency without requiring a dedicated engineering team. Basis and StackAdapt both serve this market well—Basis for agencies that need full workflow consolidation from planning through billing, StackAdapt for agencies prioritizing programmatic execution with strong usability and no minimum spend requirements.
Political advertisers evaluating platforms for the 2026 midterms should prioritize six capabilities: omnichannel activation across CTV, programmatic, audio, social, and search; CTV inventory access with pre-negotiated deals; geopolitical targeting at the congressional district and state legislative level; rapid activation workflows that compress planning-to-launch timelines; built-in compliance and brand safety tools; and AI-powered planning and optimization that preserves human strategic control.
Political ad spending for the 2026 midterms is projected to reach $10.8 billion, making this the most expensive midterm cycle in US history. That total represents a 20%-plus increase over the 2022 midterms and comes within striking distance of the $11.2 billion spent during the 2024 presidential cycle.
The forces driving that spending are significant. Control of both chambers of Congress is up for grabs. A record wave of congressional retirements is creating open-seat races where neither candidate enters with the advantages of incumbency. Redistricting is underway in several key states, including California, Missouri, North Carolina, Ohio, Texas, and Utah. With more competitive races, more open seats, and more uncertainty than any recent midterm, campaigns that cannot move quickly from planning to activation risk falling behind before the general election even begins.
For political advertisers managing campaigns across CTV, programmatic display, streaming audio, social, and search, the platform you choose determines whether your team can move at the speed this cycle demands or gets buried in manual execution during the final sprint. This guide covers what political advertisers should prioritize when evaluating advertising platforms for the 2026 midterms.
Key Takeaways
Political advertising operates under constraints that intensify every platform decision. The timeline is fixed, as Election Day does not move. The spending cadence is compressed: Basis data from the 2024 election cycle shows 48% of digital ad budgets ran in the final 30 days, with nearly half of that concentrated in the last 10 days. As such, the margin for error is narrow. A pacing miscalculation or delayed campaign launch in late October cannot be corrected in November.
These constraints shape the platform evaluation criteria that follow. Each section addresses a capability that matters in any advertising context but becomes especially high-stakes when the deadline is immovable, the budget is front-loaded, and there is no second attempt.
Political advertising in 2026 spans a wide channel list. CTV is projected to account for 23% of total political ad spend, the only channel forecast to experience growth during this cycle. Streaming audio is emerging as a breakout opportunity, reaching voters during screen-free moments that CTV and display miss entirely. Social platforms remain essential for fundraising and persuasion. And programmatic display and video continue to serve awareness and retargeting roles across the funnel.
The operational question is whether your platform can activate across all of these channels from a single workflow or whether your team needs to rebuild campaigns in separate interfaces for each.
Platforms that handle programmatic, direct publisher buying, search, social, and CTV in one system eliminate the manual handoffs that slow campaign launches and create inconsistency across channels.
For political campaigns specifically, channel coverage should include access to CTV inventory across platforms that accept political ads (Hulu, ESPN, Roku, YouTube, DIRECTV), programmatic audio through streaming and podcast platforms, and social activation through Meta, Google, TikTok, and Snapchat. Platforms that also support programmatic terrestrial radio through partnerships like iHeart expand reach into a format that political advertisers have historically underinvested in. Digital out-of-home (DOOH) is another channel worth evaluating, particularly for reaching voters in transit, at events, and in public spaces where screen-based media doesn't reach.
What to ask:
The spending cadence of political advertising creates unique operational demands. Basis data from the 2024 election found that 48% of digital ad budgets ran in the final 30 days, with nearly half of that concentrated in the last 10 days.
That compression means platforms need to support rapid campaign activation, real-time budget pacing, and mid-flight optimization under sustained time pressure.
Specific capabilities to evaluate:
Political targeting operates under platform-specific restrictions and state-by-state regulatory variations. Restrictions on audience targeting for election ads on platforms like Google and Meta, combined with state-by-state regulatory variations, make audience strategy a jurisdiction-specific exercise.
Geopolitical targeting has become an increasingly important tool in this environment. Basis data from the 2022 midterms showed that nearly 20% of political programmatic ads used geopolitical targeting, with 51% targeting by congressional district and 32% by state senate district. With redistricting underway in multiple states, the ability to target by updated district boundaries is essential.
Beyond geography, platforms should support integrations with major voter data providers, including L2, TargetSmart, i360, Tunnl, and Aristotle. Direct integrations with identity resolution providers like LiveRamp allow campaigns to upload, match, and activate voter file data quickly rather than waiting days for manual onboarding. Platforms with additional data partnerships—such as Foursquare for location intelligence, CivicScience for attitudinal data, and Adastra for identity resolution—give campaigns more options for building precise audience segments.
Automatic Content Recognition (ACR) data from smart TV manufacturers adds another layer of targeting precision. Campaigns can reach households based on actual viewing behavior, not inferred demographic proxies, and serve political messages in contextually appropriate streaming environments. Cross-device and household-level targeting further extends this capability, allowing campaigns to expand reach beyond individual devices to entire households.
What to ask:
CTV is the only media channel projected to see increased political spending over the 2024 presidential cycle, with $2.5 billion in CTV political ad spend expected in 2026. For political advertisers, CTV access is as much about securing inventory at favorable pricing as it is about reach: CPMs surge as Election Day approaches, and campaigns that wait until October pay a steep premium.
The CTV inventory ecosystem for political advertising has expanded significantly. Disney has opened inventory across Hulu and ESPN. OEM platforms from LG, Samsung, and Vizio operate their own FAST channels with growing political inventory. DIRECTV, HBO Max, Paramount, and other premium providers are accepting political and advocacy advertising in increasing volumes. Peacock, Tubi, Sling, Discovery+, Pluto TV, and fuboTV have also entered the political CTV market, giving campaigns a broader set of inventory sources than any previous cycle.
But not all CTV inventory is created equal. Platforms that accept political ads (Hulu, Roku, YouTube, ESPN) will see the sharpest CPM increases as Election Day approaches. Basis data from 2024 showed that programmatic video CPMs nearly doubled the election cycle average in November and had already increased 50%+ above average in October.
The platform evaluation question is whether your advertising platform gives you the inventory relationships and buying mechanisms to lock in favorable pricing before that surge hits.
Buying mechanisms to evaluate:
Measurement capabilities matter here too. Platforms that integrate cross-channel reach measurement—comparing digital campaign performance to linear TV—help campaigns quantify incremental reach and optimize budget allocation between CTV and traditional broadcast. Basis integrates Comscore Campaign Ratings for Advanced Reach Measurement, enabling campaigns to measure cross-channel reach, frequency, and incrementality from a single platform.
Live sports inventory deserves special attention in 2026. The FIFA World Cup (June-July), NFL, and college football season overlap directly with general election spending. Political advertisers increasingly use live sports as a targeting proxy, reaching voters in specific states and DMAs based on the games they watch. Platforms with strong sports-adjacent CTV inventory access will have a meaningful advantage. BasisTV+ provides access to CTV/OTT, addressable, and live sports and events inventory, reaching 93% of US smart TV households with 1,000+ advanced TV targeting parameters and 80+ trackable metrics.
AI-generated political content, including deepfakes, adds a new layer of brand safety complexity in 2026. Deepfake political ads are already running in midterm campaigns. There is no federal law governing AI use in political advertising, and while 26 states have enacted some form of deepfake disclosure legislation, enforcement remains limited.
At the same time, platform policies around AI disclosure are evolving quickly. Google requires political advertisers to disclose any use of AI in their ads. Meta requires disclosure in certain circumstances. The directional trend points toward greater transparency requirements.
Political advertisers need platforms that build compliance into the workflow rather than bolting it on as a separate step. Specific capabilities to look for:
Political advertising clients range from well-funded Senate campaigns with experienced media buyers to first-time candidates and ballot measure committees running their first digital campaign. The platform should accommodate both.
For experienced political media teams, self-serve access with full control over targeting, bidding, and optimization is essential. For campaigns that need additional support, managed service options that handle execution while preserving strategic control offer a middle ground.
The Basis Candidates & Causes practice has served political advertisers for two decades, offering service tiers from fully self-serve to fully managed execution. The team includes more than 40 political subject matter experts who understand the compliance, timing, and operational nuances that distinguish political media buying from commercial campaigns. In the 2024 cycle, the team supported more than 1,400 state and local campaigns, managing over $130 million in political ad spend across video, display, native, audio, and text ads.
This flexibility matters because political campaigns don't all operate the same way. A statewide Senate race and a state legislative campaign have very different team structures, budgets, and execution needs. The right platform adapts to those differences rather than forcing a one-size-fits-all approach.
Audio represented just 3% of political ad spend during the 2024 election season, despite the average voter spending 21.2% of their total media time consuming audio content. That gap is a meaningful opportunity for political campaigns willing to move early.
Streaming audio reaches voters in screen-free moments: during commutes, workouts, and household tasks. With workers returning to offices and commutes increasing, audio consumption is rising. Podcast listenership has demonstrated increasing resonance across key voter demographics. And with programmatic buying now available even for broadcast radio inventory, the barriers that once made audio difficult to activate at scale have been largely removed.
Campaigns that are early movers in streaming audio stand to benefit from lower CPMs and less competitive inventory than they will find in CTV, particularly during the October-November sprint when CTV pricing spikes.
Platforms should support programmatic audio activation through streaming services like Spotify and iHeart, ideally within the same workflow used for CTV, display, and social. Campaigns that can add audio to their channel mix without logging into a separate tool or rebuilding targeting from scratch will capture this opportunity more efficiently. Exclusive inventory partnerships add further value. Basis provides access to DAX (Digital Ad Exchange) inventory reaching over 20% of total US audio consumers across leading streaming and podcast platforms, with 60,000+ podcasts and 350+ terrestrial US radio stations, plus a multicultural network for reaching Spanish-speaking voters.
The operational demands of political advertising compress the workflow challenges agencies already know well into a much shorter timeline. Basis data shows that agencies using its automation platform save an average of 51 hours per campaign—equivalent to roughly 6.5 work days—and approximately $8,925 per campaign in efficiency gains. In political advertising, where the window for peak spending narrows to weeks, those saved hours translate directly into competitive advantage.
Automation delivers measurable time savings across five areas that consistently drain political campaign time:
Campaign setup and trafficking. Building campaigns across CTV, display, audio, social, and search typically requires logging into separate platforms and manually configuring each. Automated platforms let planners build campaigns once and traffic them to all channels simultaneously, eliminating redundant data entry and the consistency errors that come from rebuilding campaigns in interfaces that were never designed to talk to each other.
Budget pacing. When 48% of your budget runs in the final 30 days, real-time pacing visibility isn't a convenience feature — it's a necessity. Automated pacing tracks spend across all channels from a single view and adjusts delivery rates to hit flight date targets without daily manual check-ins across disconnected tools.
Performance monitoring. Cross-channel dashboards that consolidate CTV, display, audio, social, and search metrics into a single view let teams identify optimization opportunities faster. In the final sprint, the ability to spot an underperforming tactic and reallocate budget in hours rather than days can determine whether you reach persuadable voters before Election Day.
Reporting. Pulling final reporting from multiple platforms and consolidating it into client-ready formats is one of the most time-consuming tasks in the campaign lifecycle. Automated reporting with customizable templates eliminates manual exports and spreadsheet merging.
Billing reconciliation. Managing billing across multiple delivery sources creates additional operational burden, particularly for campaigns with FEC reporting requirements. Platforms with billing integrations and automated reconciliation streamline a task that otherwise consumes hours per campaign.
AI adds measurable value to political advertising in two areas: pre-activation planning and campaign optimization.
On the optimization side, AI-powered bidding 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 CTV, audio, display, and social simultaneously, automated optimization improves performance without requiring additional headcount. Basis' SmartBid technology processes dozens of performance signals throughout the day to make continuous, goal-aligned adjustments across the full media mix. In testing, SmartBid has delivered a 133% increase in return on ad spend (ROAS).
On the planning side, tools like Compass by Basis represent a shift in how campaigns can approach pre-activation workflows. Compass generates media strategies by synthesizing uploaded campaign briefs, analyzing market data, and utilizing Basis' proprietary omnichannel IMPACT framework. The output includes a proposed media strategy, channel mix recommendations, targeting recommendations with named audience personas, and a presentation deck. Agency teams can then refine the strategy through a back-and-forth conversation with the Compass agent before plans flow directly into campaign activation. Every recommendation includes clear reasoning, so teams can see what's driving each allocation and adjust the strategy as needed.
For political advertisers managing multiple races simultaneously, or for consultancies handling campaigns across several states, this kind of planning acceleration can be the difference between launching on time and falling behind.
That said, AI should augment strategic judgment, not replace it. The strongest platforms automate mechanical tasks and surface recommendations while preserving full human control over strategic decisions. Political campaigns that differentiate through audience insight, creative strategy, and local market expertise need platforms that enhance those capabilities rather than attempting to automate them away.
The following checklist summarizes the platform capabilities political advertisers should evaluate for the 2026 midterm cycle.
Channel coverage. Does the platform support CTV, programmatic display and video, streaming audio, DOOH, social (Meta, Google, TikTok, Snapchat), search, and direct publisher buying from a single workflow?
CTV inventory access. Which premium publishers are accessible? How many PMPs are pre-approved for political? Does the platform support programmatic guaranteed buying? Does it offer cross-channel reach measurement against linear TV?
Political targeting. Does the platform support congressional district, state legislative district, DMA, and hyperlocal targeting? Which voter data providers integrate directly? How fast is voter file activation? Does the platform support cross-device and household-level targeting?
Activation speed. Can the platform move from brief to live campaign across channels in hours? Does planning connect directly to activation without manual reformatting?
Pacing and optimization. Does the platform provide real-time cross-channel pacing? Can budget be shifted between channels mid-flight from a single interface? Does the platform offer AI-powered bidding that optimizes across the full media mix?
Brand safety and compliance. Does the platform include DAA Political Ad Icon support, rapid creative review, contextual controls, and verification partner integrations? Does it include fraud prevention tools?
Streaming audio. Does the platform support programmatic audio alongside CTV and display within the same workflow?
AI capabilities. Does the platform offer AI-powered optimization and planning tools? Do those tools preserve human control over strategic decisions? Do AI recommendations include transparent reasoning?
Service flexibility. Can the platform scale from self-serve to fully managed execution based on campaign needs?
Political expertise. Does the platform provider have a dedicated political advertising practice with experience across election cycles?
Basis has served political advertisers for two decades, supporting thousands of campaigns, independent expenditure committees, and issue advocacy advertisers since 2006. In the 2024 cycle alone, the Candidates & Causes team supported more than 1,400 state and local campaigns, managing over $130 million in political ad spend. The platform aligns with the evaluation criteria outlined above:
The 2026 midterms will test every political advertiser's ability to move fast, spend efficiently, and reach the right voters across a fragmented media environment. The platform you choose determines whether your team spends the final 30 days executing strategy or wrestling with disconnected tools.
What makes political advertising platform requirements different from commercial media buying?
Political advertising operates on a fixed deadline with no flexibility. Election Day does not move, and the spending cadence compresses heavily into the final weeks. Platforms need to support rapid activation, real-time pacing under extreme time pressure, political-specific targeting (congressional districts, voter file data), compliance tools for political ad disclosure, and inventory relationships with publishers that accept political advertising.
How early should political campaigns lock in CTV inventory?
Early—ideally before September. Programmatic video CPMs in 2024 nearly doubled the election cycle average in November and increased 50%+ in October. Campaigns that secure PMP deals and programmatic guaranteed pricing before September will have a significant cost advantage over those relying solely on open exchange buying during peak season.
Can smaller campaigns benefit from the same platforms used by major races?
Yes. Platforms with flexible service tiers accommodate campaigns at different scales. Self-serve access gives experienced political media buyers full control, while managed service options support campaigns with smaller teams or less programmatic experience. The operational efficiency gains from automation — faster campaign setup, unified reporting, automated pacing — benefit campaigns regardless of budget size.
How should political advertisers think about streaming audio in their media mix?
Audio represented just 3% of political ad spend in 2024 despite voters spending over 21% of their media time with audio content. That gap means lower CPMs and less competitive inventory compared to CTV, particularly during the October-November sprint. Campaigns that activate streaming audio through the same platform used for CTV and display can add the channel without additional operational overhead.
What role does AI play in political advertising platforms?
AI delivers value in two areas: campaign optimization (automated bidding, pacing, and budget allocation based on real-time performance data) and pre-activation planning (generating media strategies and channel mix recommendations from campaign briefs). The strongest platforms use AI to accelerate mechanical tasks while preserving human control over strategic decisions like audience definition, budget allocation, and creative messaging.
What is geopolitical targeting in political advertising?
Geopolitical targeting allows political advertisers to serve ads based on political boundaries—congressional districts, state legislative districts, DMAs, ZIP codes, and other jurisdiction-level geographies—rather than relying solely on demographic or behavioral audience segments. This capability is especially important during redistricting cycles, when district boundaries shift and campaigns need to reach voters within updated lines. During the 2022 midterms, Basis data showed that nearly 20% of political programmatic ads used geopolitical targeting, with 51% of those targeting by congressional district and 32% by state senate district. For the 2026 cycle, with redistricting underway in states including California, Missouri, North Carolina, Ohio, Texas, and Utah, platforms that support targeting by updated district boundaries give campaigns a structural advantage in reaching the right voters.
How do political advertisers measure CTV performance against linear TV?
Cross-channel reach measurement tools allow campaigns to compare digital and CTV performance against linear TV, quantifying incremental reach, co-viewing lift, and frequency differences. In one statewide campaign measured through Basis' integration with Comscore Campaign Ratings, digital channels delivered 4.5 million incremental viewers who were unreachable through linear TV alone, with CTV delivering 5x lower ad frequency than linear and a 44% lift from CTV co-viewing. These metrics help campaigns optimize budget allocation between CTV and traditional broadcast based on actual reach data rather than estimates.
Key Takeaways
Picture this: The weekend is finally here, it’s game time, and you’ve got your homemade nachos all set to go (your secret ingredient: home-pickled jalapenos!). You plop down on the couch, crack open your first beer, turn on the big screen and...shoot. Where’s the game? Didn’t you read something about Amazon securing the rights for this season? No wait, that was Peacock...or was it Apple TV+? ESPN+? Maybe TBS? Or TNT? One of the Ts? Fox? CBS? Hulu? YouTube TV? Is this one of the games on Netflix? Why can’t you find it?! Was there ever even a game today? THE NACHOS ARE GETTING COLD!
Tuning in to live sports used to be so simple. And we’re not even talking about 50+ years ago, when that meant “going to the game” or “turning on the radio” for 95% of your live sports consumption. As recently as the 2000s, when it came to sports broadcasts, there were the major networks, ESPN, an occasional game on one of the Turner channels, and that pretty much was it.
Today, sports leagues are scattering their broadcast rights around like digital Johnny Appleseeds, adding to an already-complex CTV and streaming video environment and creating new challenges for advertisers and consumers alike. This fragmentation is reshaping sports advertising as we know it—forcing brands to rethink where (and how) they run sports ads to reach today’s fans. The clear reason for this shift? Money—big money. US sports TV and streaming rights are forecast to reach $32.8 billion in 2026 and are forecast to surpass $36 billion in 2030. All this has taken place in the face of (or, perhaps, helped fuel) cord cutting that drives essential revenue away from traditional broadcasters and into the pockets of streaming services.
In light of these dramatic shifts, how can digital advertisers effectively reach and connect with sports fans? And is navigating the disparate live sports landscape worth all the trouble? (Spoiler alert: yes, yes it is!) Read on to learn all about it.
The biggest shift in sports advertising over the past several years is where games actually air, and that change is reshaping every advertiser’s media plan.
First off, let’s look at some of those new (or, at least, new-ish) sports broadcast partnerships, an area that’s seen some significant departures from the “old normal” in recent years:
The fact that so many major American sports entities have granted exclusive broadcast rights to streaming platforms marks a significant shift in the industry. And with digital live sports viewership surpassing linear TV in 2023—a gap that’s only widened since—it’s clear that the streaming-first revolution in sports broadcasting has arrived.
Just as meaningful is the price those companies paid for their live sports streaming rights: $200 million per year from Disney, Amazon Prime Video, and NBCUniversal for WNBA games; $5 billion over the next ten years from Netflix for the WWE “Raw” programming; $1 billion per year from Amazon for their weekly regular season NFL matchup; a reported $2+ billion per year from Google for Sunday Ticket; and $150 million from Netflix for its two Christmas day NFL games in 2024.
To make up for these kinds of skyrocketing costs, linear broadcasters and streaming video platforms alike are turning to two main revenue sources: subscription price hikes and—you guessed it!—advertising. So, without further ado, let’s take a look at how (and why) advertisers can make the most of this evolving landscape.
Live sports advertising offers brands a rare combination of guaranteed reach, deeply engaged audiences, and rich targeting opportunities—making sports ads some of the most valuable placements in any media plan.
Roughly two-thirds of Americans are sports fans. And people who watch sports aren’t going to catch a replay of the game once it hits Netflix in a few months—they’re going to watch it live. This is a valuable “guaranteed” audience upon which platforms and advertisers alike can place outsized value compared to other broadcasts (no wonder sports tend to dominate lists of the most-watched US broadcasts year after year). When brands want to ensure they are meeting a large, built-in audience all at once, there are few opportunities quite like live sports.
Which is not to say that brands can’t benefit from advertising against other sports content, such as highlights, clips, and replays (more on this in a bit!). Those often represent prime contextual advertising opportunities, whether via contextual partners like Comscore and DoubleVerify, or with specific publishers such as the AP, Gannett, or (of course) ESPN.
On the more local level, no matter what embarrassment, scandal, or years-long losing streak might afflict their favorite team, fans tend to “root root root for the home team” through thick and thin. For advertisers that want to geotarget, sporting events often post remarkable ratings in specific markets—and fan loyalty can translate to brand loyalty. No wonder organizations of all kinds pay out top dollars to be the official beer, official pizza, official bank, official cryptocurrency platform, or even official HR/payroll provider of your hometown team.
Another key factor that’s fueling sports viewership? Sports betting, which has gone from being largely prohibited under federal law (except in Nevada) before 2018 to being all over American sports coverage today. After the Supreme Court struck down the federal ban that year, individual states began legalizing it, and total consumer spending on sports betting has since skyrocketed—surpassing $100 billion for the first time in 2023, and expected to exceed $235 billion in 2028.
This growing excitement around sports betting is delivering new, passionate audiences to live sports, with over a fifth of US adults reporting that they have personally engaged with sports betting within the last year. And if someone is spending money on the game, they’re a whole lot more likely to tune in, with 85% of sports bettors saying it makes them more interested in watching the games.
As for where and how they’re watching...
Nearly 165 million Americans regularly watch live sports—almost 50% of the total population. Perhaps even more notably, more than 122 million of those viewers currently tune in on digital devices, and that number is projected to rise to 141 million by 2029. Yep: Just like the rest of the video world, the future of live sports advertising is digital.
Of course, as is the case with that larger digital video environment, the increasingly disparate nature of sports broadcast agreements (even in light of new offerings like ESPN’s new direct-to-consumer streaming service) is only adding to the complexity and fragmentation that mark the digital video and CTV space. Among avid sports fans, 69% feel it’s a hassle to navigate multiple providers to watch the same sport and 59% feel it’s gotten more difficult to find what they want to watch, and you can only imagine how frustrating that must be when the start of the game is rapidly approaching (and your nachos are getting cold...) And for advertisers, the evolution from a few reliable live sports hubs to numerous broadcasters across multiple channels can mean added complexity in campaigns targeting these audiences. So as streaming becomes the norm for live sports, advertisers and viewers alike are adapting to some growing pains.
That said, to their credit, the big tech companies that have waded into the live sports streaming wars are taking crucial steps toward optimizing benefits for advertisers. Prime Video, now a major home for NBA coverage, has rolled out interactive tools like “key moments,” advanced stats, and personalized bet tracking for NBA broadcasts. Meanwhile, NBCUniversal and Walmart launched integrated shoppable experiences across both linear and streaming sports inventory in late 2024, bringing retail media into live broadcasts. On the measurement front, Nielsen’s Big Data + Panel tool now includes live sports as a core category, and leagues are pushing for streaming platforms to share first-party metrics to support accurate ad pricing.
Even the more traditional homes of live sports have readily embraced the potential of streaming those events for maximum impact. NBC's presentation of Super Bowl LX in February 2026 drew 125.6 million viewers across NBC, Peacock, Telemundo, NBC Sports Digital, and NFL+—making it the second most-watched Super Bowl ever, behind only the prior year's Super Bowl LIX (127.7 million viewers). The fact that both records now factor in streaming and digital audiences alongside linear underscores how integral those platforms have become to live sports measurement. And annual events like the Masters golf championship and NCAA men’s basketball tournament have long had authorized (and ad-filled) streams as part of their overall broadcast packages. As viewers increasingly flock to OTT and CTV for their live sports consumption, brands will have new ways to personalize and target these consumers as part of their cross-channel marketing strategies.
Digital marketing in sports now extends well beyond traditional in-game commercials. Brands are building sports-focused campaigns that span social media, athlete partnerships, branded content within sports podcasts, contextual ads around highlights and recaps, and programmatic placements on sports news sites and apps.
Sports fans spend significant time on digital platforms throughout the week, not just during games—and they respond well to content that speaks to their fandom. For advertisers, that creates year-round opportunities to stay top-of-mind with a passionate audience, well beyond the few hours a game is live.
Speaking of which...
The digital evolution of live sports broadcasts goes beyond individual devices.
More and more fans are watching the game on digital platforms, particularly bigger screens like CTV. Sports viewership on YouTube’s connected TV app grew by 30% in 2024—a clear signal that connected TV (CTV) has become a major player in sports advertising.
But the real secret weapon for advertisers may be resting in your pocket (or your hand) right now: smartphones. Sports broadcasts present a unique cross-platform marketing opportunity, with viewers often using second screens to look up players and team statistics, use social media to engage with others, watch other games on a separate device, place bets, and more—all while watching live sports at home.
This multi-device behavior creates valuable targeting opportunities that extend well beyond game time. Sports fans are a widely targetable audience segment through private marketplaces (PMPs) like Tapjoy, and they can be further segmented via top data providers like Alliant (golf), eXelate (NBA), and Cuebiq (NHL). These tools help advertisers continue to market to viewers even after the game clock hits 0:00. Put it all together, and sports programming offers a powerful way to consistently reach and remarket to specific target audiences across multiple devices.
Beyond retargeting viewers across devices during and immediately after games, there’s also a significant opportunity to build upon the momentum of live sports and continue the conversation long after the final whistle. Sports fans are often ideal audiences for marketers as they are deeply engaged when it comes to their favorite teams. Considering the fact that 41% of fans are already locked into their favorite pro sports team by the age of 12 (and 62% by the age of 17), it’s clear that sports fans are an active, impassioned audience ripe for engagement. By leaning into this passion and connecting with these fans within relevant content related to their favorite teams, marketers can further deepen brand loyalty and drive meaningful engagement.
Whether by running ads alongside clips and replays, within sports shows, or even alongside social media content, advertisers have ever-expanding opportunities to engage with sports fans beyond live events themselves—and perhaps even to persuade more viewers to tune into live games. The power of such placements is underscored by deals like the 2024 NBA and Warner Bros. Discovery agreement which includes the studio show Inside the NBA, as well as other NBA content like Bleacher Report and House of Highlights, a social media network that distributes sports clips and content.
In addition to using ad placements within gameday-adjacent content, brands and marketers can also harness the power of sports by working with athlete influencers. Take, for instance, rugby star and Olympian Ilona Maher. She rose to fame not only for her powerful presence and performance on the field, but also for her active presence on social media—where she now has over five million followers on Instagram and works with major brands like Barbie and Maybelline. Additionally, many athletes have also started their own podcasts (like Angel Reese’s “Unapologetically Angel” and the Kelce brothers’ “New Heights”), offering brands the opportunity to place high-impact ads that connect with fans within their shows.
Sports offer brands a unique opportunity to connect with deeply passionate and engaged audiences, both during and outside of the game. By leveraging gameday-adjacent content and collaborating with athlete influencers, brands and marketers can tap into the enthusiasm of sports fans to build stronger connections, deepen brand loyalty, and drive meaningful engagement across a variety of platforms.
Sporting events are a fixture of American culture. From Super Bowl Sunday every winter to the WNBA Finals every summer, live sports are a reliable way to bring people together in front of their TVs, laptops, and other streaming devices to catch the action (and, of course, the commercials). And even as the way fans consume their sports continues to evolve hand-in-hand with the rest of the video realm, advertisers will look to live sports as a pillar of their omnichannel marketing strategies. In short: It’s a home run opportunity for brands to hit their goals, assist in the revenue-driving process, and score some big wins.
(And yes, there were seven sports puns in that last sentence. Touchdown.)
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The role of CTV in live sports advertising is expected to dramatically increase in the years ahead. Check out our CTV advertising guide for tips on everything from CTV campaign best practices, to safeguards against CTV ad fraud, to effective targeting tactics, and much, much more.
Key Takeaways:
Marketing teams have moved quickly to adopt AI. But when it comes to delivering measurable returns on those investments, most organizations are still finding their footing.
For the second consecutive year, agency leaders named AI as their top investment priority, with more than three-quarters planning to increase their AI spend over the next 12 months. However, only about 29% of organizations across sectors say they can dependably measure ROI on their AI initiatives, and CEOs report that just 25% of their AI initiatives have delivered expected ROI.
Right now, the gap between investment and demonstrated impact is significant. Closing it requires a deliberate approach to how tools are selected, how a strong foundation is built before implementation, and how their impact gets translated into stories that resonate with stakeholders.
Getting real returns on AI starts well before a tool is ever deployed. Key steps include:
With a proliferation of AI solutions crowding the market, tool selection has become an increasingly consequential decision. According to Lauren Johnson, Effectiveness Lead at Basis, a deep understanding of how an AI tool works is the starting point for evaluating whether it will deliver meaningful results.
"If we are going to ask AI to help us evaluate datasets, we need to understand how it's executing that task," says Johnson. "What are its outputs based on? What historical data is it drawing from? Marketers need to understand how their tools work in order to assess whether they'll be able to drive the impact they're looking for."
Given the state of the market, deep evaluation is critical: Gartner has warned that many vendors are engaging in “agent washing,” or positioning existing products as agentic AI without adding genuine agentic functionality. Of the thousands of vendors pitching themselves as agentic AI providers, Gartner estimates only around 130 actually deliver on that promise.
A deeper understanding of how AI tools work also makes the case for seeking out specialized solutions over generic ones. Out-of-the-box AI solutions have strengths when used strategically, but specialized tools trained on large volumes of relevant industry data tend to produce more precise and differentiated outputs. An AI media planning tool trained specifically on advertising performance data, for example, can generate cross-channel recommendations grounded in real campaign outcomes—something a general-purpose model isn't equipped to do.
Data quality is a make-or-break factor for AI performance, but most marketing organizations aren't yet where they need to be. Only 21.4% of industry professionals describe first-party data as “foundational” to their organization's AI initiatives, and roughly one-third say first-party data plays little-to-no role in their current AI use at all. Half of leaders also say their businesses don’t have the technical or data stack readiness to support AI agent deployment.
Without clean, unified, accessible data, AI tools produce outputs that are generic at best and misleading at worst—neither of which supports the kind of differentiated results that justify continued investment. Leaders must treat data readiness as a strategic prerequisite. That involves:
Finally, understanding the impact of AI investments requires knowing exactly what success looks like before deployment. “Just like with anything in our world,” says Johnson, “assessing effectiveness starts with setting a goal for what you want the tool to do for you.” If saving time on a specific workflow is the goal, for instance, measure how long that workflow takes today and define a clear target for how much AI should reduce it.
Currently, only 40% of marketing professionals are using or planning to use defined KPIs specifically for their AI solutions. Crafting a phased roadmap for AI adoption, with concrete milestones and tool-specific performance targets, gives teams both a framework for evaluating impact and the foundation for communicating that impact to stakeholders.
How marketing teams use and communicate about their AI investments is just as important as laying the groundwork for them to succeed. The teams best positioned to demonstrate impact tend to:
To achieve maximum value from AI tools, humans must consistently scrutinize what they produce. The technology can provide weak or inaccurate outputs if trained on low-quality data, and of course, there’s the matter of hallucinations: One study found that close to half of marketers spot inaccuracies in AI outputs several times a week.
“AI tools are not going to tell you when they're wrong,” notes Johnson. “Teams need to continually push back against and stress-test AI outputs in order to get real value.”
Leaders should nurture a team culture where pushing back on AI outputs is both expected and encouraged. When that standard is set by leadership and integrated into how teams operate on a daily basis, it drives higher-quality AI usage across the board. Teams that operationalize this approach are better positioned to extract demonstrable value from their AI investments over time.
Proving AI’s value to stakeholders is a significant challenge for marketing teams in 2026. In fact, only 41% of marketers can confidently prove out the ROI of their AI investments, down from 49% in 2025.
This is where the goals and KPIs set during the planning phase become essential. Tracking performance against those benchmarks over time—whether that’s hours saved on a specific task, improvement in campaign performance, or lift in a business outcome—gives teams the evidence they need to make a credible case for AI’s impact.
Beyond quantifying AI’s impact, marketing leaders must strategize around using that evidence to craft compelling narratives for stakeholders. For one thing, while AI can (and should) drive meaningful improvements in speed and cost, leaders should focus more on how their AI investments contribute to business outcomes. AI efficiency gains can be significant and are worth including in these stories, but positioning AI’s value primarily around efficiency risks reinforcing the perception of marketing as a cost center rather than a strategic growth driver.
Connecting investments to business outcomes is also what tends to land with senior decision-makers. The most resonant executive narratives tie major investment asks to concrete business drivers that connect marketing’s AI investments to the revenue and business outcomes that sales and finance leaders care about.
Another key to making those narratives credible is grounding them in a deep understanding of the tools themselves. “Executives want to hear that we're using AI, but they also want to know that it's grounded in real data,” says Johnson. “They want to know what’s powering these tools and that they can trust the outputs.”
That deep understanding is part of what makes an AI narrative credible at the executive level. Leaders who build expertise in how their tools work, what data powers them, and how that functionality is advancing business goals will be poised to earn sustained buy-in.
The ability to drive and demonstrate ROI on AI tools is quickly becoming one of the clearest dividing lines between marketing teams that lead and those that fall behind. Getting there requires a deliberate approach at every stage: selecting tools with a deep understanding of how they work, fueling them with the data infrastructure they need to perform, and translating their impact into narratives that resonate with stakeholders.
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Want more insights on how marketing teams are approaching AI? Our AI and the Future of Marketing report synthesizes findings from a proprietary survey of professionals across leading brands and agencies, covering adoption trends, workforce shifts, and the biggest barriers teams are still working through.
As 2026 progresses, brands are taking a harder look at their agency relationships.
A full 85% of US B2C marketing executives plan to review their media agencies this year. That level of reevaluation reflects a broader shift in what brands want from their agency partners, and what they’re no longer willing to accept.
Agencies are feeling this pressure. Some 65.3% of agency professionals have had clients move work in-house within the last year, and 87.3% say the traditional agency model is broken or heading in that direction. This leaves brands in a difficult position. As the industry transforms, they’re evaluating agency partners against rising expectations—sharper AI judgment, leaner operations, clearer business storytelling—while agencies are still evolving to meet them. In this context, asking the right questions can separate partners built for where the industry is going from those still operating on where it’s been.
Below are five questions worth asking before signing a contract, renewing one, or kicking off a review:
First, brands should start with the structural questions nobody wants to open a pitch with: Who owns the data? Who owns the tech stack? What gets packed up and sent with the brand if the relationship ends, and what stays behind?
This matters more in 2026 than it did even two years ago. The share of full-service and media agencies managing eight or more tools has more than doubled since 2024 (from 22.1% to 46.7%), with more than a third now juggling 10 or more tools. Every additional tool is another place where a brand’s data, historical insights, and optimization learnings can live with the agency rather than with the brand itself. When the agency changes, the brand often has to start from scratch.
The agencies worth partnering with in 2026 are comfortable with portability and clear about ownership. They can articulate exactly what a brand owns, where that data sits, and how it would transfer in a transition. Better still, they’re open to operating inside a brand’s owned media infrastructure rather than requiring the brand to operate inside theirs. When the tools, the data, and the vendor relationships belong to the brand, a roster change doesn’t mean starting over.
As a practical first step, brands can ask for a consultative audit of how an agency’s stack maps to their own. They can explore where it complements, where it duplicates, and what a brand should own directly to protect long-term flexibility, regardless of who handles execution. That distinction signals whether an agency is confident competing on the quality of its strategy and service rather than the stickiness of its tooling.
Asking whether an agency uses AI no longer yields much signal—it’s used at more than 99% of agencies today, with nearly 60% of professionals using it daily. The sharper questions get at how agencies are using the technology, and where they are deciding not to apply it.
Strong answers to these questions will be specific. An agency should be able to name the workflows where AI is adding real value, those where it’s being tested with clear guardrails, and the places where the team has consciously held back. Brands should also expect a clear answer on how an agency protects sensitive data inside AI tools. A vague answer—or worse, a reflexive “AI everything”—is a red flag. AI tools can produce strategies that sound authoritative but aren’t rooted in reality: predictions built on extrapolated data, synthesized “case studies” that don’t reflect actual market outcomes, audience insights the tool inferred rather than verified, etc. When an agency builds recommendations on that kind of output without pressure-testing it, the brand ends up paying the cost.
A stronger approach sounds thoughtful and curious. Take AI-powered search as an example. Some platforms are monetizing chat-based search in ways that could eventually open powerful new audience and targeting opportunities. But right now, the data is a black box and the measurement is thin. An agency that says, “We’re watching this closely. Here’s what we want to see before we recommend it, and here’s how we’ll know when it’s ready,” is showing exactly the kind of judgment a brand is paying for. An agency that says, “Let’s just run ads there and see what happens,” is not.
The same principle applies as agencies adopt agentic AI. A partner that’s using agents to streamline planning cycles or improve reporting, for example, should be able to walk through what the agent is doing, where the underlying logic is coming from, what the human is still doing, and why that split makes sense.
Similar questions apply to how AI is used for ad creation. The IAB acknowledged the industry’s concerns around this use case in early 2026 with its first AI Transparency and Disclosure Framework, citing a widening gap between how advertising executives think consumers feel about AI-generated ads and how those consumers actually feel. Brands should expect their agency partners to have a specific, current point of view on that gap, and for them to be able to explain the strategy behind their approach to using AI for creative generation. Clarity on these questions can help brands discern a meaningful AI strategy from something any agency could offer.
Transparency is a word nearly every agency uses. What it actually delivers in practice is where brands often find a gap. Some 88.3% of agency professionals say the digital advertising industry needs more of it, which is both encouraging and telling: The people closest to the work know there’s a gap worth closing.
Transparency doesn’t just mean a brand gets a dashboard. Dashboards show a brand what happened—real transparency explains the “why” behind what happened. Why was budget shifted between channels last week? Why was a particular audience deprioritized? Why did the team recommend pausing a tactic that was still performing? The “why” is where trust gets built, and it’s what brands should expect from their partners.
Transparency also shows up in how agencies handle pricing. The traditional structures—commission, FTE, billable hours—were built around the time-intensive, often-manual labor AI is now compressing or automating. The agencies adapting fastest are moving toward pricing tied to outputs and outcomes rather than hours, an evolution brands evaluating partners should welcome. Brands should expect the upside of that shift: clear fee structures, visibility into what’s a pass-through cost versus a markup, and flexibility on the pricing model itself, whether that’s project-based, IO-based, a clean percentage of media, or something custom to the engagement. Agencies that treat their pricing as a black box tend to treat a lot of other things that way too.
Over half of agency professionals (54.0%) say their client relationships are more strained today than they were two years ago. Much of that friction traces back to a storytelling gap. Agencies often speak in impressions, clicks, and conversion rates. Brands, on the other hand, answer to CFOs, boards, and a CMO role that has been reshaped in recent years to tie every dollar back to measurable business return.
The capability gap brands should explore with agency partners is the ability to connect campaign performance to business outcomes. In other words, they should look for agencies who can move from “We drove a 12% lift in CTR” to “We drove a 12% lift in CTR, and here’s how that shaped pipeline. Here’s what it suggests about audience intent, and here’s what we’d recommend next based on the business context you’ve shared with us.” That kind of translation and storytelling is the work agencies increasingly have to own, as connecting the dots between media activity and business impact is where real value gets created.
The agencies positioned to do this work well tend to have one thing in common: They’ve invested in connected infrastructure that pulls their work together across channels, so their teams aren’t spending the majority of their time stitching together data from disconnected tools. When the foundation is sound, human attention can shift to interpretation and strategy, which is where brands are actually trying to buy value in the first place.
Though a simple question, it’s a meaningful one. The top performing agencies in 2026 are proactive partners. They bring POVs on industry shifts before the brand has to chase them down. They flag emerging channels with a clear stance on whether they’re worth testing and why. They raise risks early, even if those risks might reduce their own scope of work.
A reactive relationship is one a brand has to manage, whereas a proactive one is one a brand can lean on. The difference shows up in small moments, like whether a weekly check-in brings new ideas to the table or just rehashes last week’s performance. But those small moments add up. Over a year, they can be the difference between an agency acting as a vendor and one acting as an extension of the brand’s own team.
The strongest version of this dynamic feels less like a brand managing an agency and more like a brand working with a trusted partner who’s actively looking out for its bottom line.
Brands are investing in digital advertising to drive business impact, and agencies too often deliver activity instead. Closing that gap, between what’s happening in a campaign and what it means for the business, is the real work of partnership in 2026.
The industry is in the middle of a structural reset. Revenue models are under pressure, AI is redefining what agency labor actually looks like, and brands have more options for how to get the work done. The brands that come out of this period with the strongest partnerships will be the ones asking the sharpest questions and holding out for agencies whose answers line up with how their business runs.
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Interested in a deeper look at what’s reshaping the agency business in 2026, including how agencies are thinking about AI, tech stack consolidation, and the future of their revenue models? Explore the 2026 Advertising Agency Report.
CTV is on track to account for more than half of all digital political ad dollars in 2026, but buying premium inventory effectively is getting harder. In this session of Basis’ 2026 Political Advertising Bootcamp, members of our Candidates & Causes team are joined by two seasoned political media practitioners for a candid, expert-level discussion on how to navigate the CTV landscape heading into the fall.
Watch now to learn what it actually takes to run CTV that delivers for political clients.
You’ll Learn:
Key Takeaways:
That streaming TV advertising playbook you relied on last year? It’s already outdated. Between shifting viewer behavior, emerging platforms, and growing concerns about inventory quality, the video ecosystem is changing fast.
By 2030, connected TV will capture more than 40% of global TV ad investment, reflecting a fundamental shift in how audiences consume video content. Today, however, linear TV still offers mass reach—which means advertisers must strategize around extracting maximum value now while planning for continued viewership declines. Meanwhile, the rise of social video, growing concerns about inventory quality, and complexities around addressability are reshaping what it means to run a successful video campaigns.
For advertisers building video strategies this year, understanding the nuances of this changing landscape is critical. Read on for six insights to guide your TV and CTV planning in 2026:
With nearly seven in 10 advertisers planning to increase their CTV spend in 2026, the industry’s commitment to CTV is continuing to accelerate. However, there's still an increasingly wide gap between ad spend and viewership: In 2027, there will be a 14-point gap between the percent of time US adults spend with CTV per day and the percent CTV ad spend makes up of total US ad spending.
CTV's advantages make this gap notable. The channel combines television's high-impact storytelling with digital precision targeting, superior completion rates, and direct attribution to consumer actions. In fact, three-quarters of American CTV owners prefer targeted ads to enhance their viewing experience, and more than one in five viewers have used their CTV devices to complete a purchase after seeing an ad. Add to this the emergence of new CTV ad formats and expanding inventory options, and it's clear that advertisers who match their spend to viewership now stand to gain significant competitive advantage before the market catches up.
But don’t write off linear TV just yet: While connected TV continues its steady climb, traditional television still delivers the kind of mass reach that many campaigns need, particularly those focused on driving brand awareness.
And no, this isn’t just your grandparents watching Jeopardy (or you watching Jeopardy, if Jeopardy is your thing!). Audiences across all age groups still tune in to traditional broadcasts, though younger generations are doing so less frequently than their older counterparts.
However, linear TV’s reach is eroding as more viewers shift to streaming alternatives: In 2026, CTV offers access to 15% more of the US population than linear. Advertisers must ensure their linear and CTV strategies complement each other in the short term, while planning for linear’s decline and the continued rise of CTV and social video.
This might look like running broad awareness campaigns on linear TV during high-profile events like live sports, then using CTV to extend reach to cord-cutters and younger viewers who don't watch traditional TV. Or, it could look like managing CTV campaigns with a platform that offers Open Addressable Ready (OAR) capabilities, which enable consistent, addressable campaigns across both linear and streaming using unified audience data and measurement. Advertisers should also allocate budget dynamically—shifting spend to CTV as linear reach declines, while maintaining traditional TV presence where it remains cost-effective.
Ultimately, success in streaming TV advertising lies in treating linear and CTV as complementary tools in a holistic video strategy that evolves alongside viewer behavior.
The boundaries between TV and social media are dissolving faster than audiences can scroll to the next video in their TikTok feed. This is especially true among younger audiences, with nearly 80% of young people aged 10-24 reporting that they watch movies or TV shows on social platforms.
Sports content, in particular, is driving social video engagement (as well as live CTV engagement): Between 2020 and 2024, the percentage of Americans who reported they watched live sports games on social media platforms in the last month grew by 34%.
Following these viewership trends, US advertisers invested more than $10 billion more in social video than in linear TV in 2025.
Recent spending trends show social video and CTV budgets are climbing while linear investments decline: In 2025, CTV and social video dominated the priority list for video advertising budgets, setting the stage for continued growth in 2026.
The living room TV? Still relevant. But today, it’s far from the only screen that matters for reaching video-watching audiences.
In 2026, buying inventory from a recognizable streaming service doesn’t guarantee your ads will appear in brand-safe, high-quality environments. As the streaming ecosystem has matured, the term “premium” has been applied so broadly that it’s lost much of its meaning. Spoiler alert: Slapping a well-known logo on an ad buy doesn’t automatically make it premium.
Much of what advertisers purchase on major platforms runs within long-tail apps, user-generated content channels, or bundled placements that offer minimal transparency. As a result, 15% of streaming TV ad spend is wasted in low-quality environments rather than premium streaming content.
Considering this, it’s critical that advertisers demand transparency from their CTV providers. Just as important is implementing quality controls when buying CTV inventory to ensure spend isn’t wasted on low-quality placements—for example, by checking in on campaigns midstream to make sure ads are showing up where intended. Overlaying ACR (automatic content recognition) data into CTV buys can also help by offering more precise visibility into placements, verifying exactly what content appeared on-screen when your ad ran.
Ultimately, premium placement in streaming comes from verification and control, not brand recognition alone.
While video strategies of the past focused on specific channels and distribution methods, the video strategies of the future will focus on following engaged audiences wherever they’re consuming content, regardless of the screen.
This means treating CTV, social video, and linear TV as complementary tools in a unified strategy rather than competing channels. Advertisers must align their content objectives with inventory-specific tactics across platforms. Broad awareness campaigns might justify run-of-content purchases, but performance-focused initiatives demand curated placements and app-level visibility.
The shift from channel-first to audience-first planning is showing up in how advertisers choose their partners: 66% of media buyers cite audience personalization capabilities as the most important factor when choosing video ad partners.
Marketing teams are implementing this audience-first approach by leveraging CTV targeting parameters including behavioral and demographic segmentation as well as content-level contextual targeting to connect with viewers in high-quality environments—then extending those learnings across social video and other channels. AI-powered, all-channel platforms can help with this by automatically applying these learnings to optimize buys across channels.
Streaming TV’s promise of precise, addressable advertising faces a critical data quality challenge. Many platforms claim they can offer addressability, but the accuracy varies significantly based on the kind (and quality) of data powering it.
IP-based targeting, which many platforms rely on, suffers from significant accuracy problems. IP-to-postal linkages are correct just 13% of the time on average, while IP-to-email connections hit the mark only 16% of the time. Yes, that means they’re wrong a whopping 87% and 84% of the time, respectively! These error rates undermine the targeting precision that makes addressable TV attractive in the first place.
As the addressability landscape develops, advertisers must understand what kind of addressability the platforms they invest in offer. To accomplish this, teams should ask their CTV partners specific questions: What data sources power your targeting capabilities? How accurate is your addressability, and how do you measure it? Do you primarily use deterministic data or probabilistic data? Platforms that can’t answer these questions transparently may not offer the precision they promise. And to enhance precision, advertisers should layer first-party and deterministic data—which offer the highest level of targeting accuracy—into their buys.
Today’s streaming landscape offers tremendous opportunities for advertisers willing to navigate its complexities. Success requires moving beyond assumptions about premium inventory, channel effectiveness, and targeting precision, and crafting strategies grounded in audience behavior, content quality, and data transparency.
Six Key Takeaways:
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Want to dive deeper into what’s shaping the future of advertising? Check out Rewinding to Fast Forward: The 2026 Digital Advertising Trends Report for more insights into how the media landscape is evolving and what it means for your marketing strategy.