As we approach 2026, choosing the right programmatic advertising platforms is no longer a nice-to-have; it’s a strategic essential. Marketing and advertising are now driven by automation, intelligence, and personalization. At the core of this evolution are programmatic advertising platforms (also referred to as demand-side platforms), which use intelligent data and analytics to make sure the right messaging reaches the right audience at the best moment.
With video, connected TV (CTV), retail media, and AI bidding all surging forward, marketers need clarity on what separates the best from the rest. In this guide, we’ll examine our top 5 programmatic advertising platforms for 2025, how to choose the best fit, and how these platforms can help your organization scale a revenue-first growth model.
What to evaluate before you pick a DSP (get ROI faster)
Before you dive into platform features and vendor demos, consider key factors to determine the best demand-side platform (DSP) for your organization. Frame your decision around these five core pillars:
- AI-Driven Bidding & Optimization: How smart is the DSP at bidding in real time toward revenue (not just clicks)?
- Audience & Data Capabilities: Can you onboard first-party data, build lookalikes, and leverage contextual and retail signals?
Reporting, Measurement & Cross-Channel Reach: Does the DSP give you integrated reporting, incrementality testing, and multi-touch attribution across desktop, mobile, video, and CTV? - Privacy, Identity & Brand Safety: With the cookie trail disappearing, how strong is the identity layer, and how safe is the inventory?
- Workflow, Integrations & Total Cost of Ownership: How easy is it to integrate the DSP into your stack (CRM/CDP/tagging/analytics), and how transparent are the fees?
In the U.S., digital ad revenue hit approximately $259 billion in 2024, a 15 % increase YoY. Selecting the wrong platform can result in wasted budget, unclear results, and missed growth opportunities.
When selecting a DSP, focus on goals like pipeline, qualified opportunities, and targeted reach, especially across CTV/video and mid-funnel ABM. Avoid common mistakes, including choosing a platform based on flashy UI, ignoring hidden platform fees or locked-in ecosystems, or building your campaigns in silos.
AI-driven bidding and optimization
Smart bidding is on the rise and is more essential than ever for growth. Today’s programmatic ecosystem demands platforms that support both standard automated bid strategies and custom bidding logic.
Standard bidding relies on built-in algorithms that automatically optimize toward goals like conversions or CPA, while custom bidding lets advertisers feed in their own business signals (such as lead quality or lifetime value) to drive smarter spend decisions. Both operate within real-time bidding (RTB) auctions, where DSPs compete in milliseconds for each impression, enabling AI to continuously adjust bids based on audience, context, and predicted performance.
The Google Display & Video 360 (DV360) platform supports automated strategies and custom models to optimize conversions. With CTV inventory expected to grow 13.8% in 2025, the pressure on bidding efficiency is even greater.
Start by defining a value-based bid model that prioritizes high-propensity accounts, set a CPM ceiling to control costs, and then use automated bidding tools to optimize toward the high-value segment.
Audience strategy and data access
In the post-cookie world, who you reach and how you reach them matters just as much as where. With continued digital growth, enterprises should focus on first-party data onboarding, lookalike audiences, propensity modeling, contextual targeting, and retail and commerce signals (for brands with e-commerce or trade channels).
DSPs leverage targeting engines, which sift through massive amounts of data to construct user profiles and create targeted audience segments, often with AI scoring components to create better transparency. The more audience data you provide the DSP, the better you’ll be able to tie audience behavior to meaningful signals. For example, The Trade Desk (TTD) offers Audience Unlimited, which uses AI scoring for third-party data, creating more refreshed data.
Cross-channel measurement and reporting
Media investment without measurement is guesswork. A robust measurement stack in programmatic advertising requires platform-level reporting and cross-channel views, as well as incrementality and uplift testing (not just last-click), and path-to-conversion analysis across display, video, mobile, and CTV.
With digital video on the rise, leverage this medium to promote a cross-channel lift on your search and display efforts. For example, integrate DV360 analytics with your GA4 to attribute view-through from CTV to site visits and pipeline engagements.
To get the most out of your measurement, incorporate multi-touch attribution and avoid defaulting to last-click, which can skew spend and dilute insight.
Top platforms you should consider
DSPs have quickly become the go-to solutions for enterprises looking to automate and optimize ad buying across different channels. The following five DSPs are leading the pack for B2B marketers heading into 2026.
Google Display & Video 360 (DV360)
Display & Video 360 (DV360) is a comprehensive programmatic advertising solution created by Google. DV360 works with businesses of all sizes, but excels particularly with large B2B advertisers seeking integrated display, video, YouTube, and CTV reach, along with advanced optimization.
DV360 supports cross-channel media planning, various ad formats, audience management, and custom bidding model support. DV360 offers powerful tools and integrations for reaching audiences and optimizing ad campaigns, providing a seamless experience for advertisers, especially when signals from GA4 are mature. Using DV360, brands can run video and display ads, setting CPM ceilings and transitioning to custom bidding once GA4 signals mature to drive 15-25% CPA improvement over 60-90 days.
The Trade Desk (Koa AI)
The Trade Desk (Koa AI) is an open-web digital advertising platform that supports a diverse range of ad formats, including CTV, display, mobile, social media, and programmatic audio. The platform offers insights, automation, and optimization for B2B firms needing ABM-style reach across display, video, CTV, and household-level targeting.
Some of the platform’s most impressive features are “Audience Unlimited,” which allows AI to score third-party audience segments, and sophisticated AI bidding with Koa. Other features include full-funnel attribution, real-time customized reporting, customer support, and traffic monitoring, making it suitable for experienced advertisers and marketers new to programmatic advertising. Another notable feature was the release of Unified ID 2.0 (UID2), which provides holistic targeting and measurement (replacing third-party cookies) with a focus on privacy.Using TTD, marketers can create campaigns that span CTV and display, using value-based bidding to prioritize high-intent households and measure the cost per incremental visit and post-exposure site lift. Be sure to provide multiple creatives in your campaigns so the AI has more data to analyze.
Amazon DSP (Performance+ / Brand+)
Amazon DSP allows advertisers to buy display, video, and audio ads both on and off Amazon’s channels and networks. Amazon DSP offers deep first-party shopper data from across the Amazon ecosystem, including Prime Video, Fire TV, Twitch, Amazon.com, Whole Foods, and Amazon smart devices, making it especially suited for eCommerce and retail advertisers looking to tie ad impressions directly to purchase behavior with programmatic reach and predictive AI models.
In one recent case study, Amazon’s Performance+ mode delivered +176% ROAS, a 50% reduction in cost per acquisition (CPA), and +66% YOY growth in sales (results may vary by segment). Teams can utilize Amazon DSP for CTV prospecting and off-Amazon display retargeting, leveraging the Amazon Ad Tag for attribution, and then tracking ROAS, page views, and new-to-brand percentages.
Additional leaders to evaluate
While the three DSPs mentioned above are strong contenders for large enterprises, these alternatives may be a better fit for enterprises concerned about ease of use and setup.
StackAdapt
StackAdapt is a self-serve DSP that relies heavily on third-party data providers and contextual targeting. While it offers tools like page-level keyword targeting and predictive modeling, it lacks access to consumer data tied to a specific commerce ecosystem. For advertisers who want to target based on behavior or closed-loop purchase signals, this can be a limitation.
StackAdapt is a good fit for mid-market B2B marketers with limited advertising budgets, seeking a platform that offers ease of use, cross-channel display and video, a focus on email marketing, and account-based marketing support. In 2025, StackAdapt launched “Ivy,” an in-platform AI assistant designed to provide campaign suggestions and optimization, enabling marketers to make faster, more informed decisions.
Basis DSP (Basis Technologies)
Basis Technologies is an omnichannel DSP that automates purchasing digital ad inventory across display, video, native, audio, and CTV. Basis DSP is an ideal fit for complex enterprises that demand centralized operations and granular data capabilities with a heavy emphasis on private marketplace (PMP) advertising.
Basis DSP combines centralized workflow automation, programmatic-guaranteed support, and the ability to plan, negotiate, and track custom PMP offerings across thousands of premium publishers, all within a single platform. The PMP deal library within Basis allows enterprises to easily curate and test premium deals. Enterprise B2B marketers can use Basis DSP to centralize the procurement of premium deals (PMP/PG), automate launch cycles, and significantly reduce time-to-market.
Checklist: Evaluate programmatic advertising platforms with rigor
Here’s a copy-and-paste checklist for evaluating the best programmatic advertising platform for your organization.
- AI Bidding: The platform supports custom/automated bidding, bidding toward revenue-based signals.
What good looks like: Custom bid algorithm or script access and a minimum 2-week learning window. - Audience/Data: Onboard first-party CRM data, create lookalikes, contextual segments, and retail signals.
What good looks like: Segment builds that outperform baseline by ≥20%. - Reporting/Measurement: Unified cross-channel reporting, incrementality tests supported, path-to-conversion visible.
What good looks like: The platform can run geo- or randomized tests and presents lift metrics. - Privacy/Identity & Brand Safety: Uses durable identifiers, brand-safety controls, and frequency caps.
What good looks like: support and integration with brand safety vendors. - Workflow/Integrations: Native integrations with analytics, CRM, and tag management; transparent fee structure.
What good looks like: API access, data fee transparency, and a pilot program available. - Service/Support & Commercial Terms: Clear SLA, pilot terms, transparent data/tech charges.
What good looks like: Pilot of at least 3 months, defined target ROAS/CPA, no hidden mark-ups.
To streamline the setup process, consider support from a team that specializes in programmatic advertising.
Common pitfalls to avoid when scoring DSPs
When scoring a DSP for your organization, avoid emphasizing flashy UI while overlooking data and infrastructure. Validate the measurement framework and incrementality upfront, and be cautious of hidden integration or setup costs, as well as other unanticipated program fees.
Operationalizing your programmatic stack (people, process, and tools)
Establishing a high-functioning programmatic practice within your organization within 30–60 days requires being organized upfront. Map out clear roles, processes, and tools to ensure the process goes smoothly.
Roles and handoffs
Standing up a successful programmatic advertising practice depends on clear ownership and tight collaboration between teams. Traders manage bids, deal setup, and pacing; Marketing Ops owns tagging, data ingestion, and audience sync between CDP and CRM; Analytics handles attribution modeling, uplift testing, and dashboards; Creative develops assets and variants across display, video, and CTV; and RevOps/Pipeline Mapping connects campaign results to business revenue.
Maintain a cadence of scheduled flight launches, midweek optimizations, and weekly reviews to track performance, refresh creative, and keep all teams aligned on progress.
Data and integration plan
A seamless data and integration plan underpins every high-performing DSP setup. Start by implementing robust conversion tagging—whether Floodlight or GA4 for DV360, the Amazon Ad Tag for Amazon DSP, or standard site pixels for other platforms. Sync CRM audiences directly into the DSP to power first-party targeting and suppression. Establish a consent framework that aligns with GDPR, CCPA, and emerging U.S. state privacy laws.
Ensure APIs connect analytics, DSP, and CDP systems so data flows freely between platforms, then define retention and suppression logic to exclude current customers or existing opportunities. Together, these elements provide a clean, compliant, and measurable foundation for optimization.
Optimization cadence and guardrails
To ensure success with your DSP setup, allow a minimum of 2 weeks for learning before implementing any significant bid/budget changes. Adjust bids/budgets twice per week after the learning phase. And create guardrails, including CPM caps, frequency caps, placement exclusions, and brand safety. Execute a creative refresh every 4-6 weeks (especially for CTV/video) so optimization continues.
Proving ROI and scaling what works (measurement blueprint)
You’ve chosen your DSP and set it up; now it’s time to track what’s working (and what’s not). Here is your blueprint for quantifying impact and making decisions within 90 days.
Attribution and incrementality
Run geo splits or randomized audience splits to isolate programmatic impact. Define primary KPI (pipeline or qualified opportunities) and secondary KPIs (site visits, demo requests). To determine Incremental Lift, subtract the Control Conversion Rate from the Exposed Conversion Rate, then divide by the Control Conversion Rate; a statistically significant lift target should have 90 to 95 percent confidence.
Budget allocation and pacing
Leverage platform auto-budget allocation to shift spend into high-performing lines (e.g., DV360 auto-budget tool) and budget decisions to marginal CPA/ROAS. If you have a multi-quarter plan, layer in MMM (marketing mix modelling) to complement the short-term optimizations.
Testing roadmap
A structured testing roadmap is crucial for staying ahead of performance shifts. Each quarter, plan multivariate tests that experiment with different formats, messages, and lengths to determine what resonates best. Compare contextual versus audience-based reach to determine which strategy delivers higher qualified engagement.
Evaluate the performance of PMP or programmatic-guaranteed deals against open-exchange inventory to balance scale and control, and dedicate at least one quarterly test to CTV-first pilots. These iterative experiments will reveal which levers drive meaningful pipeline lift and justify scaling spend.
Now it’s time to build your programmatic stack, optimize fast, and scale with confidence with the right DSP for your organization. If you’re ready to transform your programmatic efforts from a cost center into a growth engine, let’s talk. Book a programmatic audit and pilot plan with our programmatic advertising team.
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Alex Faubel
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