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AI-powered strategic media planning tools are software platforms that analyze client briefs and automatically generate structured media plan drafts, including channel recommendations, budget allocations, and strategic guidance.
These tools address one of the biggest challenges facing agencies today: inefficient planning processes that drain time, create inconsistency across teams, and prevent planners from focusing on strategic work. As AI adoption accelerates across the industry, understanding how these tools work and who benefits most from them matters for teams looking to stay competitive.
Key Takeaways
An AI-powered strategic media planning tool is software that analyzes client briefs and generates a structured media plan draft, including channel recommendations, budget allocations, and tactical suggestions.
This technology works by interpreting natural language from client briefs and matching campaign goals with industry benchmarks and channel-specific insights. Rather than starting from a blank page, planners receive a structured plan they can refine and customize based on client needs as well as their own strategic and creative judgment.
For example, a tool like Compass by Basis reads a client brief, identifies campaign objectives and target audiences, and generates a complete omnichannel media strategy—including prioritized audience segments, competitive context, channel-by-channel budget allocations with visual breakdowns, and campaign flighting—all within a conversational interface inside the platform where campaigns get activated. Planners can refine the strategy through follow-up prompts before building it into client deliverables or moving into activation.
Though powered by many of the same technologies, these tools differ from more general AI assistants or chatbots because they're purpose-built for media planning workflows. They understand advertising terminology, channel dynamics, and how to structure plans that translate directly into campaign execution. Compass, for instance, is built on Basis’ proprietary IMPACT omnichannel framework—a methodology used across thousands of successful media campaigns—rather than relying on generic AI reasoning alone.
According to the IAB State of Data 2025 report:
And, data from Basis’ 2026 Advertising Agency report finds:
This gap highlights where AI adoption has lagged most: operational planning, not creative execution.
Agencies who begin to implement AI toward operational inefficiencies now can gain a strategic edge, freeing up their teams to focus on strategy rather than manual tasks.
AI planning tools follow a structured process to convert briefs into actionable media strategies:
1. Brief Upload and Extraction
The planner uploads a client brief—whether a structured planning document or a simple prompt—and the tool extracts and summarizes key information. This includes campaign objectives, target audiences, budget parameters, KPIs, geographic focus, and timing constraints. In Compass, this extraction step is visible in the interface, so planners can confirm the tool understood the brief correctly before strategy generation begins.
2. Audience Strategy and Prioritization
The tool builds prioritized audience segments based on the brief, going beyond basic demographics. Each segment includes targeting rationale, recommended channels for reaching that audience, and messaging direction. This creates a strategic foundation where audience strategy, channel selection, and messaging are connected from the start.
3. Strategic Framework and Competitive Context
The tool generates a broader strategic framework that includes competitive context, key challenges, and a recommended approach, rather than just a channel list. This strategic layer guides the channel and budget recommendations that follow, grounding them in campaign-specific logic rather than general best practices. The framework also documents the channels the tool evaluated but chose not to recommend, with the reasoning behind each decision. This gives planners a defensible rationale to share with clients, showing that the recommended mix reflects deliberate trade-offs rather than default choices.
4. Channel Mix and Budget Allocation
The tool recommends a channel mix with specific budget allocations, including dollar amounts and percentage breakdowns with rationale for each channel. Visual outputs like budget allocation charts make it easy to see how spend is distributed and share recommendations with stakeholders. The tool can also generate multiple budget scenarios at different investment levels, each with its own channel allocation and rationale. When a client adjusts the budget or asks to see options, planners have ready-made tiers to work from instead of rebuilding the plan each time.
5. Campaign Plan and Flighting
AI maps out campaign flighting with budget allocation by phase, accounting for seasonal moments, tentpole events, and how different channels should ramp up or down throughout the flight. Channel-specific timing guidance ensures the plan reflects real-world campaign dynamics, not just even budget distribution.
6. Measurement and KPI Framework
The tool builds a measurement framework that maps KPIs to each channel’s role in the funnel, complete with relevant benchmarks. Planners get primary and secondary metrics for each channel, along with the business outcome each metric ladders up to. Having these benchmarks built in saves planners from researching performance standards across channels and gives clients a clear view of how success will be measured from the start.
7. Refinement and Strategy Delivery
The strategy generates within a conversational interface where planners can ask follow-up questions, request deeper analysis on specific sections, or adjust recommendations through natural prompts. The result is a complete, structured strategy that planners can refine and use to build client-ready deliverables. Because Compass lives inside the Basis platform, the strategy and eventual campaign activation share the same system, reducing the manual handoffs and reformatting that typically separate planning from execution.
When orchestrated by agentic AI media planning tools, this entire process can happen in minutes. What traditionally required multiple planning sessions, spreadsheet modeling, and cross-referencing past campaigns now generates automatically, giving agency talent more time to focus on strategic refinement and client-specific nuances.
AI media planning tools deliver several concrete benefits that address some of agencies’ most pressing operational challenges:
The time savings from AI planning tools come from automating specific tasks that eat up planners' days.
Take benchmark research. Manually researching industry benchmarks for CPMs, CTRs, and conversion rates across different channels takes significant time. AI tools have this data built in and automatically apply relevant benchmarks based on campaign parameters.
Budget modeling works similarly. Testing different budget scenarios manually requires rebuilding spreadsheets for each variation. AI tools can generate multiple budget allocation models instantly, letting planners compare approaches without manual calculation work.
Channel analysis is another time sink. Evaluating which channels make sense for a specific audience and campaign goal requires cross-referencing multiple data sources. AI planning tools synthesize this analysis automatically, presenting channel recommendations with supporting rationale.
Then there’s plan documentation—formatting decks, documenting strategic rationale, and creating presentation-ready outputs. AI-powered planning tools produce formatted plans that planners can review and refine rather than building from scratch.
With so many manual tasks wrapped up in drafting media plans, time savings derived from using AI-powered planning tools can add up fast. For instance, teams can create media plans 50% faster when using Compass by Basis, and that time savings can then shift to strategic consultation, client communication, or campaign optimization.
Consistency in media planning creates several advantages for agencies:
Standardized Strategic Approach: AI tools encode best practices into their planning logic. Every plan starts from the same strategic foundation: proven frameworks for audience targeting, channel selection, and budget allocation. This doesn't mean every plan looks identical, but it ensures no planner misses critical strategic considerations.
Quality Baseline for Junior Planners: Junior team members can often struggle without senior guidance. AI tools give them access to senior-level strategic thinking, helping them develop better plans while learning. The tool serves as a training resource that improves plan quality across experience levels.
Reduced Errors: Manual planning risks introducing errors such as calculation mistakes, overlooked channels, and misallocated budgets. AI tools eliminate these mechanical errors, catching issues before plans reach clients. This improves client trust and reduces the costly back-and-forth of fixing mistakes.
Scalable Quality Control: As agencies grow, maintaining consistent plan quality becomes harder. AI tools scale that quality automatically—the hundredth plan generated gets the same strategic rigor as the first.
These consistency benefits matter even more when you consider the tech stack complexity most agencies face. More than one-third (36.8%) of agencies now juggle 10+ tools in their tech stack—up dramatically from 17.3% in 2024—and managing that many disconnected systems can create inconsistency. When AI planning tools integrate into unified platforms where planning connects directly to activation, consistency extends beyond plan creation into execution. The fewer handoffs between systems, the fewer opportunities for plans to get lost in translation.
One concern about AI tools is the "black box" problem, i.e., a lack of visibility or understanding around how the AI reaches its recommendations. But well-designed AI planning tools address this through transparency features, providing rationale into their reasoning as well as ample opportunities for human interaction, iteration, and oversight.
IAB research finds that 51% of brands worry they don't have enough transparency about how agency partners use AI. Transparent AI tools that clearly show their work help address this concern: Agencies can demonstrate their value and provide visibility into their strategic process.
The key difference between manual and AI-powered media planning is how planner time is allocated: manual planning prioritizes mechanics, while AI planning prioritizes strategy.
| Aspect | Manual Media Planning | AI-Powered Media Planning |
| Speed of Drafting Initial Plan | Hours to days per campaign | Minutes per campaign |
| Benchmark Research | Manual lookup across multiple sources | Automatic application of relevant benchmarks |
| Consistency | Varies by planner experience and approach | Standardized strategic framework across all plans |
| Budget Modeling | Manual spreadsheet work for each scenario | Instant generation of multiple allocation models |
| Junior Planner Support | Depends on senior availability for guidance | Built-in access to senior-level strategic thinking |
| Measurement Setup | Research benchmarks and build KPI framework manually | KPI framework with channel-level benchmarks generated automatically |
| Error Rate | Higher risk of calculation and oversight errors | Reduced mechanical errors |
| Time Allocation | More time on mechanics, less on strategy | More time on strategy, less on mechanics |
| Scalability | Requires adding planners to handle more volume | Same team handles increased planning volume |
| Knowledge Transfer | Lost when team members leave | Captured in the tool |
| Planning-to-Activation Handoff | Manual export, reformatting, and rebuilding in activation platform | Strategy built inside the same platform where campaigns get activated |
Using AI-powered media planning tools doesn’t mean replacing planners. Rather, it allows planners more time to scale their work effectively and efficiently, while simultaneously providing them with more time to focus on the deep, strategic work best completed by humans. Manual planning forces planners to focus on mechanical tasks. AI planning shifts that time to strategic consultation, creative collaboration, and client relationship building.
This shift matters because 54.0% of agencies report more strained client relationships compared to two years ago. When planners spend less time on administrative work, they have more capacity for the client-facing strategic work that strengthens relationships.
AI-powered media planning tools are best suited for agencies and brands managing planning complexity, scale, or constrained resources.
Agencies managing multiple clients across various industries handle significant planning volume. AI tools help these agencies scale planning operations without proportionally scaling headcount, improving profitability while maintaining quality. They're particularly valuable when agencies need to pitch new business quickly or accommodate compressed timelines.
Organizations adding junior planners benefit from AI tools that give newer team members strategic scaffolding. Instead of requiring constant senior oversight, junior planners can produce quality work more independently while learning planning fundamentals.
Any agency where inefficient processes or disconnected systems create operational friction will benefit from AI planning tools. Given that 48.9% of agency leaders cite inefficient processes as their top challenge, this includes a significant portion of the industry.
AI planning tools deliver the most value when integrated into platforms where planning connects directly to activation. When the same system that generates the plan also executes it, data flows seamlessly—no manual transfers, no disconnected spreadsheets, no reconciliation work. This integration addresses the silos/disconnected systems problem that 40.4% of agencies identify as a major challenge.
The ideal scenario combines AI-powered planning with all-channel activation capabilities and AI that extends across the entire media buying process, from brief to activation to optimization. When these capabilities exist within a single platform rather than requiring multiple point solutions, agencies avoid the tech stack bloat that creates new inefficiencies (or accentuates existing ones).
Agencies looking to adopt AI-powered media planning tools should follow a structured approach:
Document how much time planning currently takes and where bottlenecks exist. Identify which parts of the planning process consume the most time and which would benefit most from automation. This assessment creates a baseline for measuring improvement.
Don't add another disconnected tool to an already complex tech stack. Look for AI planning capabilities that integrate with existing systems or exist within unified platforms. The planning tool should connect seamlessly to wherever campaigns get activated—whether that's programmatic buying, publisher-direct placements, or search and social platforms (or ideally, a platform that combines all of these in one).
Test AI planning on a small set of campaigns before rolling out across all clients. Choose campaigns that represent typical planning challenges, such as finding the right mix of channels, moderating complexity, and meeting realistic timelines. This pilot phase helps teams learn the tool and build confidence before scaling.
Invest in training so planners understand what the tool can do and how to refine its outputs effectively. Focus on explaining the logic behind recommendations so planners can make informed decisions about when to accept, modify, or override AI suggestions.
Create clear workflows for how AI-generated plans get reviewed and approved. Define who validates outputs, what criteria determine plan quality, and how feedback gets incorporated to improve future plans. This process maintains quality control while scaling efficiency.
Track metrics that matter: planning time per campaign, error rates, client feedback on plan quality, and planner satisfaction. These measurements justify the investment and identify areas for continued optimization.
Once the pilot proves successful, expand AI planning to additional teams and client accounts. Gradual rollout allows for learning and refinement without disrupting operations.
The investment priority is clear in the data: 77.7% of agency leaders plan to increase AI investment in the next 12 months, with automation tools tied for the second priority at 44.7%. Agencies moving quickly on AI planning implementation gain competitive advantage while others wait.
Basis Compass is purpose-built to solve the operational challenges agencies cite most: inefficient processes and disconnected systems. Here’s what sets it apart:
Compass gives agency employees back the time they need to do the strategic and creative work that clients are seeking, while automating the spreadsheet juggling that drains valuable hours from every week.
The shift to AI-powered media planning represents an opportunity to amplify human judgment, while reducing the manual tasks that slow teams down. These tools handle the mechanical work that drains time and creates inconsistency, giving planners capacity to focus on strategy, creativity, and client relationships. For agencies facing increasing complexity, tighter timelines, and pressure to do more with the same resources, AI planning tools offer a practical path forward.
The agencies that integrate these capabilities thoughtfully, particularly within unified platforms that connect planning directly to activation, will differentiate themselves through both efficiency and quality. They'll respond to briefs faster, produce more consistent work, and give planners more time for the strategic thinking that clients value most.
What is an AI-powered strategic media planning tool?
An AI-powered media planning tool is software that analyzes client briefs and automatically generates a structured media plan draft, including channel recommendations, budget allocations, and tactical suggestions. Planners can then refine and customize this draft based on client needs and their own strategic judgment.
Do AI media planning tools replace human media planners?
No, human oversight remains essential throughout the process. The typical workflow is AI generates a draft, then the planner reviews, refines, and approves it, keeping strategic decision-making with the planner while automating mechanical tasks.
How much time can AI planning tools save agencies?
Manual media planning can take hours or days, while AI tools can reduce this to minutes. Teams using Compass by Basis, for example, create media plans 50% faster than with manual processes.
Are AI-generated media plans transparent?
Well-designed tools avoid functioning as a black box by showing their reasoning behind each recommendation. Platforms like Compass explain the rationale for channel and budget decisions and let planners see which data sources informed them.
Can AI tools generate multiple budget scenarios?
Yes, AI planning tools can instantly generate multiple budget allocation models at different investment levels, each with its own rationale. This lets planners present clients with options without rebuilding the plan from scratch each time.
What data do AI media planning tools use to build strategies?
They combine campaign objectives and parameters from a client brief with industry benchmarks, performance data, and proprietary frameworks. Compass, for instance, is built on Basis's IMPACT omnichannel campaign framework, a methodology used across thousands of successful media campaigns.
How does AI media planning improve consistency across agency teams?
AI tools encode best practices into their planning logic, so every plan starts from the same strategic foundation regardless of which planner builds it. This gives junior planners access to senior-level strategic thinking while reducing calculation and oversight errors.
Why does connecting media planning to activation matter?
When planning tools integrate into the same platform used for activation, data flows seamlessly without manual transfers or reformatting. Compass lives inside the Basis platform, allowing planners to move from a brief to an active campaign without switching systems.
Who benefits most from AI-powered media planning tools?
Mid-to-large agencies managing high planning volume, teams with growing numbers of junior planners, and organizations facing inefficient processes or disconnected tech stacks see the most benefit. These tools are most valuable for teams using unified advertising platforms where planning connects directly to activation.
How is Compass by Basis different from a general AI chatbot?
Compass is purpose-built for media planning workflows rather than relying on generic AI reasoning, using Basis's proprietary IMPACT framework alongside industry benchmarks. It operates within the same platform where agencies activate and manage campaigns, so plans move directly into execution without manual handoffs.
Key Takeaways:
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Remember when researching a purchase meant toggling between about 20 different tabs on your laptop? You’d run a string of keyword searches on Google, scroll through the results, open tabs for all the promising-sounding options, and review. Your collection of tabs might exist for days, weeks, or even months, growing and shrinking along with your research until you finally felt informed enough to pull the trigger (or until your browser decided to stage an intervention and crash).
Now think about the last item you bought. Maybe you asked ChatGPT for product recommendations and made a purchase after reviewing them. Or perhaps an AI summary at the top of a Google search compared three options for you, and you picked one without having to do any additional research. Sound familiar?
The path that moves a person from “I might need this” to “I bought it” looks almost nothing like it did a decade ago, or even three years ago. It’s fragmented, nonlinear, and increasingly shaped by algorithms and AI. For advertisers, that shift changes what it looks like—and the underlying technology it requires—to reach consumers effectively in key moments of influence.
Not long ago, the customer journey was relatively straightforward. A customer became aware of a product, considered and evaluated it, and finally made their decision and completed the purchase. Advertising mapped neatly onto that path. A billboard or TV spot built awareness, while a well-placed search or display ad nudged a shopper toward a decision. Advertisers could reasonably predict where a customer was headed and meet them there.
Today’s journey looks quite different: It bends, loops, scatters across channels, and rarely starts or ends where advertisers expect.
Discovery now happens everywhere, all the time. Most shoppers say they discover new products at least once a week, and that discovery is spread across TikTok FYPs, Instagram feeds, AI summaries, retail apps, and beyond. This discovery also often happens across multiple devices at the same time, with the majority of media consumers across every generation saying they now browse the internet or use apps on their phones while watching TV. With content so readily available, advertisers are competing for attention that is splintered across screens and digital spaces. That makes showing up intentionally and consistently across channels even more important.
The research phase has changed as well, evolving into a multi-touch, multi-channel endeavor. Consumers now research a product three or more times before buying, and nearly a quarter research five times or more. They also turn to a variety of sources for their research: online reviews and listicles, social media, recommendations from family and friends, in-store visits, search engines, AI, and beyond. For advertisers, that scatter makes presence across channels less of a “nice-to-have” and more of a requirement, since there’s no longer a single place where decisions get made.
Purchase has also grown more unpredictable. More than 30% of shoppers say they research online but buy in-store, a pattern that makes attribution especially difficult. When someone discovers a product through a TikTok creator but buys it at Walmart, connecting that sale to the original touchpoint—or any other touchpoints along the way—is a real challenge for advertisers trying to understand what’s working. Without a connected view of those touchpoints, advertisers risk crediting the wrong channel and misallocating their next dollar.
In addition to the rising complexity of digital media, AI is also playing a major role in the evolution of the customer journey. Among people who use AI to shop, it now ranks as the second most influential shopping source—trailing only behind search engines and outranking retailer sites, apps, and recommendations from family and friends.
And adoption is climbing quickly. AI now plays a role in 86% of shoppers’ retail journeys. Nearly half of AI shoppers use it most or every time they shop, with 80% saying they anticipate relying on it more moving forward. People who use AI for shopping are also finding real value in the tool: 81% say AI makes the job easier, 77% say it makes them more confident in their decisions, and nearly 90% report it helps them find products they wouldn’t have known about otherwise.
AI also tends to expand the path to purchase rather than shortening it. After an AI interaction, shoppers tend to add more steps to their customer journey, often in an effort to validate their choice before buying. Though AI certainly does streamline some stages of the path to purchase, it also adds steps that weren’t there before. And each of those new steps is another opportunity for advertisers to connect with shoppers on their way to making a decision.
Zero-click search is reshaping the journey further. As AI summaries and chatbot responses answer questions directly in the results, fewer users click through to a brand’s site at all. That doesn’t mean those impressions stop mattering, however: Ads appearing alongside AI-generated summaries still influence decisions, even without a click. It does mean advertisers have to rethink how they measure influence and where they show up, since a growing share of discovery and decision-making now happens inside environments where AI shapes what consumers see, hear, and trust about a brand.
Adapting to how the customer journey has evolved starts with recognizing and accepting the complexity of it. CTV, retail media, short-form video, AI chatbots, AI search summaries, and more are all live, simultaneous touchpoints, each with its own signals and rules. Advertisers who try to manage each in isolation will likely struggle to keep up. The teams adapting best treat these channels as one connected system, planning and buying across them together rather than each in isolation.
Accomplishing this depends on a few capabilities. One is real-time visibility and reporting. When AI tools can compress discovery, evaluation, and purchase into minutes, advertisers need to see what’s resonating as it happens (not days later in a reconciled report) so they can move budget toward what’s working during key moments of impact.
That kind of visibility is hard to come by when data stays fragmented. Nearly half of agency marketers use eight or more tools to manage campaigns, and more than a third manage 10 or more. Even more, fewer than one in five industry professionals describe their first-party data as extensive and well-structured. This leaves teams to piece together the path to purchase from incomplete inputs across systems that weren’t necessarily built to talk to each other.
Speed is another key capability, in both execution and planning. Shoppers today move through different steps quickly and across channels, which means bid strategies, creative, budget allocation, and the media plans behind them all need to keep pace. Automated, AI-powered optimization that makes continuous, goal-aligned adjustments, powered by live performance signals, can be the difference between capitalizing on the channels where target audiences are spending time and missing those opportunities entirely. That same speed matters earlier in the campaign process, too. Considering how dynamic the customer journey is today, teams that can build and adjust media plans quickly—rather than rebuilding them manually each quarter—stay aligned with how consumers actually behave. AI-powered tools are increasingly helping compress that planning work so agency talent can focus on strategy over manual setup.
Taken together, these capabilities underscore what adapting to the modern customer journey requires: A strategy built around how consumers behave today, and the infrastructure to execute it.
In a journey this fragmented and fast-moving, the infrastructure beneath a team’s advertising workflows matters as much as the strategy on top of it. But not all infrastructure is created equal, and “unified” can mean different things in practice.
Real visibility across channels means little if teams must continually switch between tools to access data, billing, and reconciliation systems. Real-time optimization falls short if the platform powering it can’t handle the complexity of true omnichannel work. For example, a platform that unifies programmatic but treats search, social, and site direct buys as afterthoughts isn’t unified in the way that advertisers need to adapt to the complexity of the 2026 customer journey.
The advertisers best positioned for navigating it are the ones working from a single, unified platform that connects programmatic, search, social, and CTV, supported by infrastructure stable enough to make agile, cross-channel activation reliable at scale.
In 2026, the customer journey is fragmented, nonlinear, and shaped by AI at every turn. To reach people in moments of meaningful impact, advertisers need visibility across channels, the speed to act on what they see, and the connected infrastructure to make both possible.
The days of the tidy linear funnel and the slow, self-directed path to purchase aren’t coming back. Today’s customer journey calls for a different kind of toolkit, one well-suited for media fragmentation, AI, and the speed at which today’s consumers move. The advertisers who invest now in unified, real-time infrastructure—the kind that brings every channel into a single view and acts on customer signals as they happen—will be the ones who keep pace as the journey keeps changing.
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Looking for more information on how to adapt your media planning for the modern customer journey? Check out Beyond the Funnel: A Better Way to Plan Media.
Key Takeaways:
Brand safety and suitability look very different today than they did just a few years ago, and most advertisers’ strategies haven’t kept up with the new pace.
Online spaces increasingly characterized by harmful and polarizing content, the proliferation of AI-generated media, reduced platform moderation, and the growing complexity of digital advertising have combined to raise the brand risk profile for advertisers.
Closing that gap requires a mindset shift from leaders. Instead of treating brand safety as a box to check once campaigns are live, brand safety and suitability must be approached as a strategic consideration built into media planning from the start.
The brand safety and suitability environment has evolved considerably in recent years. The open web has grown more volatile, with offensive language, controversial content, and hate speech on the rise. Just between 2024 and 2025, the share of offensive content online rose by 72%. Considering that 64% of global consumers say the genre of content surrounding an ad influences how they perceive it, the increasing hostility of online spaces creates significant content adjacency issues for advertisers.
The emergence of generative AI and subsequent proliferation of AI-generated content online has exacerbated such concerns. A 2025 Basis study found that a full 100% of marketers and advertisers agree that AI presents a brand safety and misinformation risk, and 53% of media experts in the US cite advertisements’ proximity to gen AI content as a top media challenge this year.
Social media has grown particularly contentious, especially as major social platforms have rolled back their content moderation policies in recent years. Close to two-thirds of marketers running campaigns on social feel concerned about the brand suitability of those ad placements.
April Weeks, Chief Media Officer at Basis, says the combination of these and other factors has raised the stakes for brand safety and suitability. “The risk has increased,” says Weeks, “and to adapt, advertisers must treat brand safety and suitability as brand-specific governance issues that are integrated into the media plan.”
Beyond content adjacency issues, wasted spend is a major concern when it comes to programmatic investments.
The ANA’s latest Programmatic Transparency Benchmark found a considerable gap in how effectively advertisers convert their spend into working media. Higher-performing advertisers directed 54% of their programmatic investments toward impressions that were measurable, viewable, and free of invalid traffic and made-for-advertising (MFA) content. Lower-performing advertisers converted just 32.1%—in other words, more than two-thirds of their spend was wasted.
The platforms marketing teams use for programmatic advertising have a considerable impact on how effectively they’re able to direct their spend. For example, platforms that prioritize supply path optimization (SPO)—offering supply chain visibility, neutral buy-side transparency, and brand safety controls built into the buying process—help advertisers convert more spend into quality placements.
“The best DSPs clean up the supply chain before an advertiser even bids—vetting publishers, filtering out bots, and removing invalid traffic up front,” notes Lindsey Freed, SVP of Media Investment at Basis.
Successfully addressing brand suitability, brand safety, and programmatic waste in today’s media environment requires marketing leaders to think about these issues differently than they have in the past.
“Historically, brand safety meant not showing up next to negative content,” says Dan Wilson, GVP of Integrated Client Solutions at Basis. “Today, it's about safeguarding your brand's integrity: considering where your ads are placed, the quality of the surrounding content, and what's suitable for your brand, audience, message, and moment in the customer journey.”
Legacy brand safety approaches were characterized by post-campaign verification, a reliance on platforms to manage risk, and blunt controls like broad keyword blocks or genre-level content blocking. As the complexity of the digital media environment has grown, Weeks says that advertisers must take on more responsibility, taking the time to craft nuanced brand safety and suitability strategies that are engrained into the planning process.
Leading advertisers are now incorporating pre-bid tools alongside post-bid verification, adding solutions to block MFAs and other low-quality websites, and accounting for channel- and platform-specific risks. Social listening, for example, has become essential given the polarization of content on social platforms.
Content adjacency approaches are also becoming more nuanced. The most successful advertisers are moving away from binary “safe vs. unsafe” thinking, and towards more granular, context-specific approaches. Rather than applying a blanket block on all news content, for instance, advertisers can use inclusion lists of trusted publishers paired with contextual targeting to ensure ads appear alongside news the brand is comfortable with, and within trusted editorial environments. “It’s about approaching it from a lens that isn’t black and white,” says Wilson.
Technology is evolving to support advertisers in these more granular approaches. For example, newer solutions can go beyond keyword matching, using contextual and semantic analysis to assess whether content is actually suitable and incorporating real-time signals to reduce waste.
Ultimately, success depends on leaders shifting their mindset, considering brand safety and suitability in the planning phase, and addressing them through a nuanced, multi-pronged approach.
Crafting a brand safety strategy suited to the complexity of today's media landscape takes real investment. Auditing legacy approaches, building channel-specific controls, and evolving workflows and tech stacks all take time. For leaders willing to invest that time, however, the potential returns are significant.
"The opportunity amongst the complexity is there," says Wilson. "The question is, will advertisers take the time to find it?"
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For a deeper look at how supply path optimization supports stronger brand safety outcomes, check out The Case for Supply Path Optimization as Strategic Priority.
The local branch of a marketing & advertising agency holding company based in San José, Costa Rica wanted to compare Basis’ campaign efficiency—specifically with time and cost savings—against working with separate media owners.
To do so, they used Basis to boost brand awareness and visibility for two leading client brands in the beverage industry to their target consumers.
Basis implemented a strategic, data-driven digital out-of-home (DOOH) campaign that included:
Basis delivered a data-driven DOOH campaign in Costa Rica that simplified execution, reached 665k users, and proved the platform’s power to reduce costs and maximize efficiency.
The results:
Strategic Virtual Roadmap
Basis designed a journey roadmap of high-traffic zones and pinpointed 13 key screens that aligned with target audience’s mobility patterns, maximizing reach with the right audience at the right time.
Precise Activation with PMPs
Basis used three distinct private marketplace deals for precise targeting and scheduling across a combination of indoor and outdoor screens.
Centralized Execution Across Media Vendors
Basis enabled seamless coordination and exact time scheduling across multiple vendors, reducing complexity and boosting efficiency.
Integrated Post-Campaign Reporting
Paired with a measurement provider, Basis provided a detailed report that covered campaign performance metrics and qualitative audience data like consumer demographics and device type.
For most agencies, the DSP is where media plans turn into live campaigns, which makes it one of the more consequential platform decisions a team can make. Choose well, and planning, buying, and reporting move faster across every account. Choose poorly, and the platform adds friction to campaigns it was supposed to accelerate.
The best DSP for agencies depends on your agency's size, client volume, and channel mix. Platforms like Basis, The Trade Desk, DV360, Amazon DSP, Viant, and Simpli.fi each serve different agency profiles, from independent boutiques managing a handful of accounts to mid-market teams running programmatic, search, social, and direct buys across dozens of verticals. The right demand side platform reduces operational complexity, improves reporting transparency, and scales with your client roster rather than against it.
That decision carries more weight every year. Programmatic now accounts for roughly 91% of US digital display ad spend, so the platform an agency uses to access it shapes a growing share of the work. At the same time, tool sprawl is climbing: Basis' 2026 Advertising Agency Report found that more than one-third of full-service and media agencies now manage 10 or more adtech tools, more than double the share two years ago, with inefficient processes (44.1%) and siloed systems (40.4%) ranking as their top operational challenges. The DSP you choose either adds to that burden or helps remove it.
This guide compares leading demand side platforms by agency type, walks through the evaluation criteria that matter most, and helps you build a case for the right investment.
The right DSP for your agency is the one that matches your team's workflow, your clients' channel requirements, and your growth trajectory. There is no universal "best" platform. A platform that excels for a holding-company network may create friction for an independent shop, and vice versa.
Start by identifying where you fall across three dimensions:
Once you map your agency against these dimensions, the field narrows quickly. A boutique with five clients and a display-heavy media mix has different requirements than a mid-market shop running full-funnel campaigns across 30 accounts. For a deeper look at the criteria that should guide your evaluation, this guide to choosing the right omnichannel DSP covers the decision in more detail.
Agencies should evaluate DSPs across six core dimensions: inventory breadth, multi-client account management, campaign optimization, reporting transparency, onboarding support, and pricing model clarity.
Inventory breadth determines where your ads can run. The strongest programmatic platforms for agencies offer access to premium display, video, native, audio, CTV, and digital out-of-home inventory through direct publisher integrations, private marketplaces, and the open exchange. This matters more as budgets shift to streaming: US CTV ad spend is on pace to reach about $38 billion in 2026, up nearly 15% year over year, so inventory access increasingly means streaming reach. Brand safety and ad fraud protection are also part of this evaluation. (For a detailed look at how leading DSPs handle both, see this comparison of DSPs for ad fraud protection and brand safety.)
Multi-client account management is where many DSPs fall short for agencies. You need hierarchical account structures that let you manage budgets, audiences, and creative assets at the client level without cross-contamination. Platforms designed for single-advertiser use often require workarounds that slow your team down.
Campaign optimization should go beyond basic bid adjustments. Look for algorithmic optimization across KPIs, automated budget pacing, and the ability to shift spend across tactics in real time. With AI now used at more than 99% of agencies, the question is no longer whether a platform applies AI but how much routine optimization it removes from your team's plate.
Reporting transparency matters for both internal decisions and client communication. Your DSP should provide granular, exportable reporting with clear visibility into costs, margins, and performance by tactic, channel, and audience segment. If you need to rebuild reports outside the platform, that is a red flag.
Onboarding support is especially critical for agencies switching platforms or adopting programmatic for the first time. Structured onboarding, dedicated success managers, and ongoing training reduce time-to-value and protect campaign performance during the transition.
Pricing model clarity separates platforms you can trust from those that obscure costs. Understand whether a DSP charges on a CPM basis, a percentage of spend, a flat SaaS fee, or some combination. Hidden fees can erode your margins and make it harder to forecast profitability for your clients.
If you want a refresher on how these platforms work, this DSP fundamentals guide covers the essentials.
The leading demand side platforms popular with agencies in 2026 each have distinct strengths. The right fit depends on your agency's profile, so the comparison below is organized by use case rather than a single ranking.
| Platform | Core strength | Best for |
| Basis | Unified planning, buying, optimization, reporting, and billing across programmatic, search, social, and direct | Agencies that want to consolidate their full workflow in one platform, plus expansive programmatic inventory, supply path transparency, and award-winning service |
| The Trade Desk | Enterprise-grade programmatic scale | Large, tech-savvy programmatic teams with substantial budgets |
| DV360 | Deep Google ecosystem integration and YouTube access | Google-centric campaigns that lean on GA4 and CM360 |
| Amazon DSP | Purchase-intent targeting built on Amazon shopping data | Commerce and retail clients with high spend |
| Viant | CTV reach and people-based, cookieless identity | Programmatic teams prioritizing streaming and AI-driven execution |
| Simpli.fi | Localized and multi-location programmatic at scale | Agencies with franchise, local, or multi-location clients |
| Platform | Programmatic | Paid search | Paid social | Direct buys | Billing & reconciliation | CTV | Entry point |
| Basis | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | Lower threshold |
| The Trade Desk | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | ~$10K+/mo |
| DV360 | ✓ | Limited¹ | ✗ | ✗ | ✗ | ✓ | GMP contract (~$50K+/mo) |
| Amazon DSP | ✓ | ✗² | ✗ | ✗ | ✗ | ✓ | $10K rec. self-serve / $50K managed |
| Viant | ✓ | ✗ | ✗ | ✗ | ✗ | ✓ | Self-serve & managed |
| Simpli.fi | ✓ | ✗ | Partial³ | ✗ | Separate⁴ | ✓ | Self-serve & managed |
¹ DV360's search functionality is limited; agencies typically run paid search through Google Ads separately. ² Amazon's search ads run through its own sponsored-ads console, separate from Amazon DSP. ³ Simpli.fi reaches social inventory programmatically but is not a paid-social campaign-management tool. ⁴ Simpli.fi offers agency workflow and billing through its separate Advantage and Core Media product line, not a natively unified platform.
The best DSPs for agencies in 2026 include Basis, The Trade Desk, DV360, Amazon DSP, Viant, and Simpli.fi, and the right choice depends less on raw programmatic horsepower than on how much of the agency workflow a platform can absorb. A team running programmatic across a handful of large accounts, for instance, has different needs than a shop reconciling dozens of clients across channels. With that in mind, the sections below will evaluate each platform on channel coverage, workflow depth, and the agency profile it fits best.
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 manual effort across agency teams.
Here is 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. 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 has produced measurable gains, with some agencies reporting up to a 5x improvement in advertising performance. For agencies managing high client volume across verticals, that combination of consolidation and performance is what separates Basis from point solutions that address only one stage 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 to activating to optimizing to reporting to billing—across both the open web and walled gardens.
The Trade Desk has built a strong reputation for enterprise-grade programmatic buying. Its bidding capabilities, access to a large third-party data marketplace, and strong connected TV inventory make it a credible choice for sophisticated, large-scale programmatic programs.
That sophistication, however, comes with a steep learning curve, and its formidable monthly minimums make it best suited to agencies with dedicated programmatic expertise and clients with substantial budgets. The Trade Desk is also programmatic-only. It does not handle paid search, paid social, or direct buys, so agencies still need separate tools for non-programmatic channels and a separate system for billing and reconciliation.
The Trade Desk is strongest for: Large agencies running high-volume programmatic programs with dedicated ad tech resources and clients whose media mix is weighted toward programmatic.
DV360 (Google Display & Video 360), part of the broader Google Marketing Platform, offers programmatic buying with detailed attribution and tight integration across Google's ecosystem, including exclusive YouTube inventory, the Google Display Network, Campaign Manager 360, and Google Analytics 4. For advertisers running Google-heavy campaigns, that interoperability is hard to match.
The tradeoffs, however, are significant. DV360 is not available as a self-serve product: Access requires a Google Marketing Platform contract with practical minimum spend thresholds, and its utility diminishes outside Google-owned environments. Search functionality is limited, and the platform does not handle paid social, direct buys, billing, or financial reconciliation. For agencies whose clients need omnichannel reach beyond Google, DV360 addresses only part of the buying workflow.
DV360 is strongest for: Agencies running Google-heavy, attribution-focused campaigns, particularly teams with in-house analytics expertise already operating within the Google stack.
Amazon DSP gives agencies access to something few platforms can replicate: targeting built on Amazon's proprietary shopping, browsing, and streaming data. Purchase-intent signals derived from Amazon's retail ecosystem offer uniquely powerful audience targeting based on actual purchase behavior rather than inferred intent, alongside premium inventory across Prime Video, Twitch, Thursday Night Football, and Fire TV.
The tradeoff is cost and scope. Self-service access carries no hard minimum, though Amazon recommends roughly a $10,000 campaign budget for some formats to generate enough data for optimization, while managed service requires a minimum commitment of around $50,000 per month. The platform's core advantage is strongest for retail, CPG, and e-commerce clients; agencies serving other verticals will find it less relevant. Amazon DSP also operates as a walled garden and does not handle paid search, paid social, direct buys, media planning workflows, billing, or reconciliation.
Amazon DSP is strongest for: Agencies with commerce-focused clients that can put Amazon's shopper data and premium streaming inventory to work.
Viant is an AI-powered, CTV-focused programmatic DSP whose central differentiator is its Household ID, a deterministic, people-based identity solution built for cookieless, cross-device targeting and measurement. The platform pairs solid connected TV and video inventory with autonomous campaign features, including a product that handles setup, optimization, and management with limited manual intervention.
For agencies, the constraints mirror other programmatic-only platforms. Viant does not offer search, social, or direct buying, and it carries no agency workflow, billing, or financial operations layer. Its interface and advanced features can present a learning curve, and the autonomous approach, while innovative, reduces hands-on trader control, which some teams prefer to keep.
Viant is strongest for: Programmatic teams that prioritize CTV reach and people-based identity and are comfortable leaning on automated execution.
Simpli.fi is a programmatic platform with a clear specialty in localized and hyperlocal advertising, including geo-fencing, geo-conversion tracking, and multi-location campaign management at scale across CTV, display, video, native, and audio.
However, users flag a complex interface and a learning curve for new teams. Additionally, Simpli.fi's strength is concentrated in local and multi-location use cases, so agencies with national or non-local clients may find its core value proposition less applicable.
Simpli.fi is strongest for: Smaller agencies serving local, multi-location clients that need hyperlocal targeting at scale.
The strongest platforms automate routine optimization and surface reporting that scales across clients, so teams spend their time on strategy rather than manual adjustments.
Campaign optimization in modern DSPs goes well beyond setting a bid and walking away. Leading platforms use machine learning to adjust bids in real time, shift budget across tactics and channels as results come in, and pace spend to avoid over- or under-delivery, all aimed at the outcomes clients care about. Reporting is where that quality becomes visible to clients: The best platforms offer dashboards configurable per client, scheduled report delivery, transparent cost breakdowns that separate media from platform fees, and cross-channel views that show how programmatic, search, social, and direct buys perform together.
The deeper divide is structural. Most of the platforms above handle one slice of the workflow well. A programmatic DSP executes programmatic buys, but with most demand side platforms, agencies still need to run separate tools for search, social, direct deals, and the back-office work of billing and reconciliation. Each added tool is another login, another data silo, and another manual handoff, which is why tool sprawl tracks so closely with the inefficiency and siloed-system challenges agencies report. The platforms that stand apart are the ones that reduce the number of systems an agency has to operate, not add to it. That unified model is where Basis, in particular, is built to compete—and it is increasingly what cross-channel, AI-driven optimization depends on, since connected data is the input those systems need to work.
Independent DSPs operate without ties to a specific holding company or media conglomerate, giving agencies more flexibility in how they buy media and where they allocate spend. Holding-company-affiliated platforms may offer preferential pricing or bundled services, but they can also limit access to competitive inventory or lock teams into a single ecosystem.
For independent and boutique agencies, this distinction matters. If your agency is not part of a major network, you need a DSP that offers transparent pricing, open marketplace access, and support that does not assume you have a 50-person ad ops team. The best independent DSPs provide the same caliber of technology, inventory access, and optimization available to large networks, without enterprise-level minimums.
Third-party agencies evaluating DSPs should pay close attention to contract terms. Some platforms require long-term commitments or minimum monthly spend that can be prohibitive for smaller shops; others offer flexible models that scale with the business. The broader question is how the DSP fits the full tech stack alongside your ad server, data tools, and campaign management. For a wider view, see how top advertising agency platforms for media buying compare.
Building a business case for a new DSP requires framing the investment in terms leadership cares about: operational efficiency, margin improvement, and client retention.
Basis unifies programmatic, direct, search, social, and connected TV buying in a single platform, giving agencies one place to plan, execute, optimize, and report across every digital channel.
For agencies managing high client volume, Basis provides the multi-client account structures, automated reporting, and cross-channel visibility that reduce operational complexity. For independent agencies competing with larger networks, it offers enterprise-grade technology paired with dedicated onboarding, training through AdTech Academy, and ongoing support from a dedicated Success Manager.
Explore Basis DSP to see how it fits your agency's needs.
What is the best DSP for agencies? The best DSP for agencies depends on client volume, channel mix, and team experience. Agencies that want planning, programmatic, search, social, direct buys, and billing in one place tend to favor a unified platform like Basis, while teams focused purely on programmatic scale may prefer The Trade Desk or DV360. Map your requirements first, then match them to the platform that removes the most friction across your full operation.
What is a DSP and how do agencies use it for programmatic advertising? A DSP, or demand side platform, is software that lets advertisers and agencies buy digital ad inventory programmatically through automated, real-time auctions. Agencies use DSPs to plan, execute, and optimize campaigns across display, video, native, CTV, and audio from a single interface. The DSP automates bidding, applies audience targeting, and reports on performance, letting agencies manage media buying at scale across multiple clients.
Which leading demand side platforms are popular with agencies in 2026? Leading demand side platforms used by agencies in 2026 include Basis, The Trade Desk, DV360, Amazon DSP, Viant, and Simpli.fi. Each serves a different profile: Basis unifies programmatic, search, social, CTV and direct buys with planning, billing; The Trade Desk and Viant focus on programmatic scale and CTV; DV360 integrates with the Google ecosystem; Amazon DSP brings shopper-data targeting; and Simpli.fi specializes in localized, multi-location campaigns.
What is the best DSP for independent agencies? The best DSP for an independent agency offers transparent pricing, open marketplace access, flexible contract terms, and strong onboarding support without enterprise-level minimums. Independent shops should prioritize platforms like Basis that deliver the same technology and inventory access as large networks while providing hands-on support, since they rarely have large in-house ad ops teams.
Which DSP is best for agencies managing high client volume across verticals? Agencies managing high client volume across verticals need hierarchical multi-client account structures, per-client reporting, and broad channel coverage in one system. A unified platform that handles programmatic, search, social, and direct buys, along with billing and reconciliation, reduces the manual handoffs and data silos that multiply as account counts grow.
What DSPs offer the best customer support and onboarding? Agencies adopting or switching platforms should prioritize structured onboarding, dedicated success managers, and ongoing training, all of which reduce time-to-value and protect performance during a transition. Basis pairs its platform with a services organization that provides consulting, onboarding, and training through AdTech Academy, along with a dedicated Success Manager for ongoing support.
What is the difference between a managed-service DSP and a self-serve DSP for agencies? A self-serve DSP gives your team direct control over setup, optimization, and reporting, which suits agencies with experienced programmatic traders. A managed-service DSP provides hands-on support from the platform's team, handling some or all execution on your behalf. Many platforms offer both, letting agencies choose the level of support that matches their team's capabilities and workload.
Can small or independent agencies access the same DSP technology as large agency networks? Yes. Many leading DSPs offer independent agencies the same technology, inventory access, and optimization they provide to large networks. The key is to evaluate pricing minimums, contract flexibility, and onboarding support, since some platforms require enterprise-level spend commitments while others offer flexible models built for independent teams.
Where can I compare trusted DSP platforms for digital campaigns? You can compare DSPs using the at-a-glance and channel-coverage tables in this guide, which evaluate Basis, The Trade Desk, DV360, Amazon DSP, Viant, and Simpli.fi across channel support, billing, CTV access, and entry point. Score each platform against your own client volume, channel mix, and team experience to identify the strongest fit.
How much does it cost to run a DSP campaign through an agency? DSP campaign costs vary by pricing model, media spend, and the channels you activate. Common structures include a percentage of media spend, CPM-based fees, or a flat SaaS subscription, and some platforms combine them. Beyond platform cost, factor in creative production, data fees for audience targeting, and any managed-service charges. Request a transparent fee breakdown from each DSP you evaluate so you can forecast client margins accurately.
Meadows at Mystic Lake is an award-winning public golf course that offers a unique, challenging, and scenic golf experience. They are a full-service golfing destination enhanced by nearby food and entertainment venues.
Mid-flight, Meadows at Mystic Lake’s CTV campaign was delivering at just 17.4% of target. With budget on the line and the flight window closing, the team needed a fast answer.
The issue: Brand protection costs were consuming campaign budget at $1.60 CPM, restricting delivery and preventing the campaign from serving at full capacity across tactics.
Using Basis, the team switched to Protected by Mediaocean. Brand protection costs dropped from $1.60 to $0.10 CPM, a 94% reduction, and the impact on delivery was immediate.
Within one week, the campaign reversed its course. It went from 17.4% pacing to ahead of target, serving across all tactics at full spend.
To manage the recovery, the team added budget across tactics, then pulled daily budgets back once full delivery was confirmed, staying on target without overspending.
During the same period, the team activated a new content targeting tactic through Basis, delivering an $18.94 CPM—the lowest of the campaign.
“When we identified brand protection as the issue, we made the switch to Protected by Mediaocean and didn’t look back. The campaign recovered faster than expected, and we talked away with a new brand protection set we can use across all campaigns.” - Senior Integrated Media Specialist
Marketers are measuring more than ever, but confidence in campaign decisions is still lagging. What’s the disconnect?
Join Basis Effectiveness Lead Lauren Johnson and VP of Media Innovations + Technology Noor Naseer for a candid look at what separates real campaign effectiveness from measurement for measurement’s sake. They unpack what’s moving the needle in measurement in 2026, where most teams get stuck, and how to turn the data you already have into clear next steps.
You’ll walk away with:
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 advertising 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.
For agencies buying CTV at scale, BasisTV+ is built to bring clarity and efficiency. It reaches 93% of US smart TV households and unifies CTV with programmatic, search, social, and direct media in a single interface, allowing teams to grow CTV investment without adding tools, manual reporting, or operational drag.
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 advertising 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 ad platforms should also offer both open exchange inventory for scale and private marketplace (PMP) deals for quality control. Access to such inventory gives 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 advertising 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:
The CTV platforms with the most detailed reporting combine real-time dashboards, log-level data, and trackable metrics in a single interface alongside all other digital channels. 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.
The strongest platforms measure CTV alongside programmatic, search, social, and display in a single interface, then connect exposure to conversions across devices using log-level data and IP-to-impression matching. That unified view is what makes cross-channel measurement possible: Rather than evaluating CTV in isolation, agencies see how it works with every other channel to drive outcomes.
This is important because last-click attribution models undervalue CTV, since viewers typically see an ad on one screen and convert later on another device. Advanced platforms solve this by connecting CTV exposure at the household level to subsequent conversions (instead of crediting only the final click) using log-level data and IP-to-impression matching.
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.
What is the best platform for agencies buying CTV at scale?
The best platform for buying CTV at scale combines premium inventory reach with unified workflow management, so agencies can grow investment without adding tools or manual work. BasisTV+ reaches 93% of US smart TV households and manages CTV alongside programmatic, search, social, and direct media in one interface. That consolidation lets agencies scale CTV efficiently while proving its impact to clients.
Which CTV advertising platforms offer the most detailed reporting and analytics?
The most detailed platforms pair real-time dashboards and log-level data with 80+ trackable metrics and white-label, cross-channel reporting. BasisTV+ delivers this with automated reporting, eliminating the manual work of compiling data from multiple sources. This gives agencies the granularity to optimize mid-campaign and report with confidence.
Which trusted CTV platforms integrate with programmatic buying tools?
Trusted CTV platforms integrate natively with programmatic exchanges, DSP functionality, ad servers, billing systems, data partners, and verification vendors. BasisTV+ offers 170+ API integrations, including trusted partners such as DoubleVerify, Peer39, Comscore, Protected by Mediaocean, LiveRamp, and FreeWheel. These native connections create automated data flows instead of manual uploads.
Which platforms offer cross-channel measurement that includes CTV?
Platforms that measure CTV alongside programmatic, search, social, and display in a single interface offer true cross-channel measurement. BasisTV+ connects CTV exposure to conversions across devices using log-level data and IP-to-impression matching, rather than crediting only the last click. This shows how CTV works with every other channel to drive outcomes.
How do I choose the best connected TV advertising platform this year?
Evaluate platforms across key criteria: inventory quality, targeting depth, brand safety, measurement, integration, and support. Prioritize premium inventory access, AI-powered contextual targeting, multi-layered fraud prevention, cross-device attribution, unified workflow integration, and strategic partnership beyond a transactional vendor relationship. The platform you choose shapes your agency's ability to scale CTV without drowning in manual reporting or losing budget to bot traffic.
What CTV advertising platforms offer cross-device retargeting?
Platforms that support cross-device retargeting use household-level identity resolution to re-engage CTV-exposed viewers on their mobile and desktop devices. This turns CTV from a standalone awareness tactic into a connected, full-funnel strategy. BasisTV+ supports cross-device targeting directly within the buying workflow, so agencies can extend CTV exposure into retargeting without a separate tool.
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 also has a leading independent DSP that is built into the platform, extensive partnerships with data and inventory providers, and an array of integrations with leading publishers and platforms including ad servers (Google Campaign Manager), billing systems (Advantage and Freewheel), and search and social APIs (Google Ads, Bing, Meta, LinkedIn, TikTok, Snapchat, Reddit, Pinterest).
Lastly, Basis has an award-winning customer service team that is known to partner closely with users to ensure their success across onboarding, education, and campaign execution.
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 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.