Mary Gabrielyan
October 24, 2025
15
minutes read
Marketers don’t need bigger budgets in 2026 so much as smarter ones. This guide shows how to turn goals into measurable actions across search, social, retail media, and CTV, then use AI—carefully governed—to learn faster and compound gains.
Performance marketing has outgrown its PPC roots. It’s now the operating system for growth across B2B and B2C—blending data-driven optimization with brand building, using AI to target precisely, and designing clear paths from first touch to purchase. The scale is real: U.S. digital ad revenue hit $259B in 2024 (+15% YoY), with search at $102.9B and digital video at $62.1B, underscoring how performance tactics fund the mix.
In this guide, you’ll get twelve practical strategies to stretch ROAS—plus the trends that will shape performance marketing beyond 2026. Each one maps to specific metrics, tools, and workflows you can put to work immediately. And with more teams adopting AI in day-to-day marketing, expect faster testing cycles and tighter measurement from the first impression to the final sale.
⚡Every dollar should have a job—and a KPI that tells you if it did the job.
Performance marketing is a results-tied approach where advertisers pay only when a defined action happens—typically a sale, lead, click, app install, or similar outcome. Industry bodies have framed it this way for years: the IAB describes performance campaigns as those built to trigger a specific action, with payment occurring after that action is completed. The Performance Marketing Association uses a similar definition focused on paying for measurable results rather than exposure.
How it differs from brand marketing is straightforward. Brand campaigns prioritize reach and recognition and are often bought on impressions (CPM) or sponsorships; performance campaigns optimize to concrete outcomes and are bought against actions. The IAB’s definition explicitly contrasts outcome-paid performance buys with awareness-driven brand buys that trade on impressions.
The core performance channels span the places you can both target precisely and measure outcomes:
In short, performance marketing centers on accountable spend and measurable outcomes; brand marketing builds mental availability and preference. The two work best together—brand investment raises response rates, while performance investment captures and proves demand.
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At its core, performance marketing is a closed loop. You present an offer to a defined audience, a platform records what happens, and those results feed back into the next decision on who sees what, at what price, and when. That decisioning is increasingly automated. Programmatic exchanges auction each individual impression in milliseconds using the IAB’s OpenRTB protocol, so bids, targeting, and creative selection can change from one impression to the next based on the latest signals.
Measurement sits alongside delivery. Platforms and analytics tools attribute outcomes to ad exposure, then optimization systems use that data to update bids and creatives. Modern buying stacks lean on machine learning techniques—such as multi-armed bandits or related reinforcement-learning approaches—to allocate spend toward higher-performing variants while throttling weaker ones, improving efficiency as the campaign runs.
Privacy requirements have reshaped how data is combined for planning, activation, and measurement. Rather than exchanging raw user-level data, advertisers and media owners increasingly match and analyze it in data clean rooms governed by common principles and privacy-enhancing technologies, as outlined by the IAB Tech Lab.
Finally, proving that media caused incremental results—rather than just appearing near conversions—requires incrementality testing. Lift experiments create exposed vs. holdout groups (or geo regions) and estimate the conversions directly driven by ads. Both Google and Meta document conversion-lift methods to quantify that incremental effect.
Before we get tactical, here’s the bridge from theory to action: you’ve seen how delivery, measurement, and learning form a closed loop. Now translate that loop into decisions you can make each week—anchored in measurable outcomes, privacy-safe data, and experiments that verify cause and effect.
💡 Related reading: What is Real-Time Bidding (RTB)? Definition and importance
These shifts make 2026 a pivotal year for performance tactics in the U.S.:
💡 Read more background: In a cookie-less world: new challenges and opportunities.
3. Automation is now table stakes. Regular use of generative AI surged—McKinsey reports 71% of organizations used gen-AI in at least one function by 2024, with marketing among the most active adopters. The implication for 2026: more algorithmic bidding, creative rotation, and predictive audiences, paired with stronger governance and measurement.
4. Efficiency pressure from the top. Gartner’s 2025 CMO Spend Survey notes continued budget pressure, which heightens the appeal of channels and workflows that can prove incremental revenue and reallocate spend in near-real time. PwC likewise highlights digital advertising—especially streaming—as a key growth engine in the U.S. market.
Bottom line: performance marketing fits the moment because it’s measurable, privacy-aware, and built to follow consumer attention into retail media and streaming while AI accelerates optimization.
💡 For additional context on media mix shifts feeding into 2026, see Media trends 2025.
This section turns the plan into action. We’ll outline four core plays to set your foundation—each with concrete moves and a metric to watch. Every point relies on sources you can check.
Performance programs are accountable to defined outcomes (purchases, qualified leads, installs). Industry guidance frames performance as paying after a specific action is completed, in contrast to impression-based buying for awareness. That accountability makes clear goals and message-match essential, because bidding, targeting, and creative are tuned to those outcomes.
What to do:
Brand and performance aren’t rivals. Brand investment raises mental availability and trust, which improves conversion rates and lowers acquisition costs; activation captures that demand. Empirical work from the IPA shows long-term brand building and short-term activation work in tandem, with guidance on balancing the two. McKinsey similarly reports that applying performance rigor to branding can deliver efficiency gains up to 30% and incremental top-line growth up to 10% without increasing the budget.
⚡ Attention is a leading indicator; conversion is the receipt. Track both.
What to do:
Modern buying platforms apply machine learning to audience expansion, bidding, and creative selection. As AI reshapes search and social delivery, spend is shifting toward AI-driven placements; eMarketer data projects U.S. AI-driven search ad spend rising from ~1% of search in 2025 to 13.6% by 2029, reflecting rapid adoption of AI-assisted targeting and optimization.
⚡ Let algorithms explore, but make humans accountable for the guardrails.
What to do:
💡 For a deeper overview, see What Is AI Targeted Advertising and Why It’s Changing Everything and explore Elevate for AI-enabled planning and optimization.
Customers don’t progress in a straight line. They bounce between social, search, email, retail media, and streaming before purchase. When orchestration works across channels, value rises: a well-cited retail study of 46,000 shoppers found that customers using four or more channels spent 9% more in-store than single-channel shoppers, with similar uplifts online.
⚡ Journeys beat channels: design sequences, not silos.
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What to do:
Retail media networks (RMNs) combine retailer first-party data with on-site and off-site ad inventory, then close the loop with sales attribution. Connected TV (CTV) extends this precision into streaming environments, where impressions are bought programmatically and tied back to site visits, leads, or sales through deterministic or modeled attribution.
As mentioned, eMarketer projects continued U.S. retail media expansion into 2026, including billions in incremental search spend, while CTV is on track to command roughly one-third of total U.S. TV ad spend. These shifts put outcome measurement at the center of what used to be “upper-funnel” channels.
⚡ Retail + CTV is a full-funnel handshake—reach on the big screen, receipts in the retailer.
What to do:
💡 For CTV buying/measurement fundamentals, see Connected TV advertising.
💡 For foundations and trends, see What Is a Retail Media Network: Definition, Trends, Insights.
Ad platforms can deliver qualified traffic, but conversion happens on your page. Benchmarks suggest “average” landing-page conversion rates cluster in the mid-single digits across industries, which means layout, copy, forms, proof points, and speed have outsized influence on ROI.
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CRO is a compounding lever: small gains at each micro-step (view → add to cart → checkout start → purchase) multiply. Think of the funnel as a chain of percentages. If each step improves a little—more product views turn into adds to cart, more carts turn into checkouts, more checkouts become purchases—those small lifts multiply across the journey. A 10% gain at three steps isn’t just 10% better overall; it compounds into a much larger increase in completed orders.
Recent analyses of hundreds of millions of visits put median landing-page conversion around 6–7%, highlighting the headroom available with disciplined testing. Unbounce
⚡ Speed is a feature. A fast page is often the cheapest way to lift ROAS.
What to do:
Mobile now drives the majority of browsing and a large slice of commerce, yet checkout friction remains high. Independent UX research finds the typical U.S. checkout exposes far more form elements than necessary and that a material share of shoppers abandon solely because the process feels long or complicated. Simplifying fields, enabling wallets, and reducing steps reliably recovers revenue.
⚡ On mobile, every extra field is a tax on intent—collect only what you can’t ship without.
What to do:
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Video commands attention and increasingly connects to conversion. Shoppable video blends content and commerce; agencies already view it as the next frontier for retail media. Livestream shopping continues to evolve in the U.S., with social platforms and retailers testing formats that compress discovery and purchase into a single session. When interactive elements—polls, quizzes, overlays—invite participation, completion and click-through rates typically rise.
What to do:
Dynamic creative optimization (DCO) assembles ads from modular components—headlines, images/video, CTAs, product feeds—in real time. Platforms test combinations against audience signals and placements, then automatically bias delivery toward the variants that convert best. Standards from IAB enable dynamic components to be rendered and tracked consistently across ad servers, while platform features such as Meta’s Advantage+ Creative and Dynamic Creative automate the asset-mixing and learning loop.
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⚡ DCO wins by volume and relevance: more shots on goal, aimed better.
What to do:
💡 If you need a primer on content-level personalization, see What Is Dynamic Content Personalization (And Why It Drives Conversions).
Influencer and affiliate programs become true performance channels when compensation shifts from flat fees to outcome-based models (CPA, revenue share). Creators distribute trackable links or codes; conversions are attributed and paid on incremental sales. Recent U.S. shopping data underscores the impact: Adobe Analytics found that influencers and other affiliate marketers drove about 20% of Cyber Monday e-commerce revenue in 2024, and affiliate-linked products were 6× more likely to convert than non-affiliate content.
⚡ Creators earn their keep when they’re paid on outcomes, not promises.
What to do:
Instead of static A/B tests that split traffic 50/50 until significance, algorithmic approaches (multi-armed bandits and related reinforcement-learning methods) continuously reallocate impressions toward higher-performing variants while still exploring new options. In advertising, the “arms” can be creatives, bids, audiences, or landing-page versions; the system learns which combinations maximize conversions or revenue under budget constraints. Academic work and industry papers document bandits applied to bidding and portfolio optimization for search and programmatic campaigns.
What to do:
No single method answers every question. A modern measurement stack triangulates:
On the plumbing side, customer data platforms (CDPs) unify first-party data and activate it across channels; surveys and market analyses show rapid CDP adoption and growth as marketers prepare for AI and privacy-first activation.
⚡ Test for causality. If it doesn’t move the holdout, it didn’t move the business.
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What to do:
💡 For a deeper overview, see MarTech: Complete Guide to Marketing Technology in 2026 and 15 Digital Marketing Metrics & KPIs to Measure Performance.
The next moves aren’t just extensions of today’s playbook—they change how campaigns are built, delivered, and measured. What follows are near-term shifts worth piloting now so you’re ready when they scale. Start small, define clear success criteria, and graduate winners into your always-on mix.
Generative models now produce copy, images, and video variants at scale, and they plug directly into ad platforms’ optimization loops (dynamic creative, automated placements).
Adoption isn’t fringe: 63% of marketers say they’re already using generative AI, and AI-driven referrals to websites in the U.S. grew more than 10× between July 2024 and February 2025—evidence that gen-AI content is feeding real traffic, not just hype.
What to do. Build a modular asset library (headlines, visuals, CTAs) and use human-in-the-loop review to ship many variants, then let platform algorithms concentrate spend on winners.
💡 For governance and workflow ideas, see GenAI in creative & media strategy.
Third-party cookies are no longer the default fuel for targeting and measurement. Google’s Privacy Sandbox team paused a hard deprecation and shifted toward user choice and expanded protections (e.g., IP Protection coming to Chrome’s Incognito mode), while continuing to invest in privacy-preserving APIs and clean-room workflows. The direction is clear: consented first-party data, on-device signals, and experiments to validate incremental impact.
What to do. Prioritize first-party data capture, server-side conversion APIs, and clean-room partnerships with major platforms and retailers; standardize lift testing so you can prove causality as identifiers fragment.
Retail media networks (RMNs) are moving from on-site search/display to full-funnel buying with off-site inventory, CTV tie-ins, and self-serve tools—functionally DSPs powered by retailer first-party data.
Digiday reports RMNs pushing off-site and streaming integrations, with Amazon Marketing Cloud often serving as the “glue” between prospecting and conversion. Walmart Connect’s DSP, built with The Trade Desk, illustrates the model at scale.
What to do. Treat RMNs as cross-channel systems: plan prospecting (CTV/open web) and conversion (retailer on-site/search) together, and read closed-loop sales plus incrementality, not ROAS alone.
AR and VR are shifting from novelty to shoppable utility. eMarketer projects that a majority of U.S. AR users will shop with AR starting in 2025, and forecasts show AR shoppers representing a meaningful slice of the population even as standalone app usage lags—most access happens via social platforms.
Recent hardware moves (e.g., Meta’s AR glasses announcements) suggest more mainstream touchpoints ahead.
What to do. Start with mobile/social AR: virtual try-ons, 3D product demos, and shoppable overlays. Define success metrics up front (view-through, add-to-cart from AR, assisted conversion) so pilots can graduate into always-on formats.
Attention aims to quantify whether an ad was actually seen and processed, going beyond viewability.
Adoption is rising: eMarketer reported 47% of buy-side decision-makers expected to focus more on attention in 2024.
Outcome studies show why—Adelaide’s 2025 guide (52 case studies) found campaigns optimized to its AU metric averaged 41% higher brand lift and 55% stronger lower-funnel impact; IAS/Lumen report similarly ties high-attention impressions to significantly higher conversion rates and lower CPA.
What to do. Add attention to planning and reporting: pick a vendor (e.g., Adelaide, DoubleVerify, IAS), set AU/attention targets per placement, and track the delta in brand lift and sales against your historical benchmarks.
Performance marketing in 2026 is measurable, adaptive, and increasingly AI-driven. You set outcomes first, instrument the journey end to end, and let algorithms explore while you verify what’s truly incremental. The highest returns come when performance and brand work together: brand investment builds preference and trust; performance capture turns that demand into revenue through clear goals, disciplined testing, and tight measurement.
If you take one thing forward, make it this: treat every tactic as part of a connected system. Use privacy-safe data to reach real people, run routine lift experiments to separate correlation from causation, and keep your stack integrated so insights move quickly from reporting to action. That’s how you compound small gains into durable growth.
If you’re ready to operationalize this approach, reach out to AI Digital. We help teams stand up outcome-led programs with a DSP-agnostic Open Garden model, AI-enhanced managed service, premium Smart Supply selection, and the Elevate platform for planning and real-time optimization—combining transparency, custom KPI optimization, and human expertise so budgets work harder across CTV, retail media, social, search, and the open web.
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Inefficiency
Description
Use case
Description of use case
Examples of companies using AI
Ease of implementation
Impact
Audience segmentation and insights
Identify and categorize audience groups based on behaviors, preferences, and characteristics
Automated ad campaigns
Automate ad creation, placement, and optimization across various platforms
Brand sentiment tracking
Monitor and analyze public opinion about a brand across multiple channels in real time
Campaign strategy optimization
Analyze data to predict optimal campaign approaches, channels, and timing
Content strategy
Generate content ideas, predict performance, and optimize distribution strategies
Personalization strategy development
Create tailored messaging and experiences for consumers at scale
A plan for achieving specific, measurable outcomes (sales, leads, installs) using channels that can target precisely and prove results. It defines goals and guardrails (e.g., CPA, ROAS), selects the right mix of search, social, retail media, CTV, affiliate/partners, and influencer, then tests and optimizes continuously based on real data.
Core: conversion rate, cost per acquisition (CPA), return on ad spend (ROAS), customer acquisition cost (CAC), and customer lifetime value (LTV). Supporting: click-through rate (CTR), add-to-cart rate or lead quality score, attention or in-view time (where available), incrementality lift, and payback period/mer.
Triangulate. Use marketing mix modeling (MMM) for budget allocation over time, multi-touch attribution (MTA) for day-to-day optimization when signals allow, and incrementality tests (geo or audience holdouts) to prove causal impact. Track both outcome KPIs (revenue, LTV, ROAS/CPA) and quality indicators (lead acceptance, repeat purchase rate).
Brand builds memory, trust, and preference; performance captures and proves demand. Strong brand signals raise conversion rates and lower acquisition costs, while performance programs turn that advantage into measurable revenue—and provide feedback that sharpens future brand work.
A performance marketing strategy sets the direction: the goals you’ll pursue, the audiences to prioritize, the channels’ roles across the funnel, and how you’ll measure success. A performance marketing plan turns that strategy into execution: budgets, flight dates, creative assets, targeting settings, tests, and the week-to-week actions you’ll take to hit the goals.
