AdTech Marketing Case Studies: 15 Proven Campaigns

Written by: Aaron Rovner, Founder, Saas Hero | Last updated: September 6, 2026

Key Takeaways

• Adtech marketing uses software to automate ad buying, targeting, and measurement across programmatic, CTV, social, and search, tying impressions to revenue.
• The 15 case studies show that infrastructure efficiency, such as 84% ad-server reduction and 63% faster activation, drives ROI alongside ROAS and CPM.
• Privacy-first, cookieless strategies often outperform cookie-based targeting, with documented lifts up to 97% in brand visitation and 72% lower eCPM.
• Board-ready measurement tracks pipeline ROAS, CAC payback, and incrementality instead of form fills, so adtech investments map directly to revenue.

What Is AdTech Marketing?

Adtech marketing uses software to automate ad buying, targeting, and measurement across programmatic display, CTV, social, and search. It includes demand-side platforms (DSPs), supply-side platforms (SSPs), data management platforms, identity resolution, and creative automation. Traditional digital marketing relies on manual placement decisions and broad audience definitions. Adtech relies on real-time bidding, algorithmic decisioning, and data pipelines that connect impression delivery to downstream revenue signals.

How AdTech Marketing Differs From Traditional Digital Marketing

Traditional digital marketing case studies focus on messaging changes, creative refreshes, and channel mix shifts. Adtech case studies focus on technical infrastructure, data plumbing, and system efficiency. The QBurst telecom DOOH platform case study illustrates this distinction. The headline results were a 63% reduction in campaign activation time and 99.7% uptime across 16,000+ edge devices. Those metrics rarely appear in a traditional marketing case study.

Real-time bidding, programmatic buying, and identity resolution in a cookieless world are the mechanics that separate adtech from manual ad buying. When 67% of developers use ad blockers and 34.9% of US browsers block third-party cookies by default, the infrastructure layer of an adtech campaign determines whether accurate measurement is possible.

Key Metrics in AdTech Case Studies

Adtech metrics measure system efficiency and incrementality, not only conversion volume. The primary metrics used across the case studies in this guide are defined below.

For campaigns with long sales cycles, pipeline ROAS, calculated as (pipeline generated × average close rate × average deal size) ÷ channel investment, is more defensible than closed-revenue ROAS when reporting to a CFO or board.

15 AdTech Case Studies by Category

Each case study follows a consistent structure: Challenge, Solution, Results, and Key Takeaway. All figures are sourced and dated.

Programmatic CTV Case Studies

Case Study 1: Virgin Atlantic — 9.2x ROAS on CTV and Search

• Challenge: Drive more revenue from the same media budget and test whether AI-driven Performance Max could deliver incremental revenue more efficiently than incumbent search campaigns.
• Solution: Consolidated activity into a single Microsoft Advertising Performance Max campaign with destinations separated at the asset group level.
• Results: The campaign delivered a 9.2x ROAS (£9.20 per £1 spent). A 70% lower CPC and 87% higher conversion rate vs. UK generic Search drove this efficiency. This performance translated into 729 bookings at a 7.36% CTR.
• Key Takeaway: Automation combined with structured asset groups outperforms manual campaign proliferation.

Case Study 2: Unieuro — CTV Lift Study in Italy

• Challenge: Become the first brand in Italy to test CTV lift measurement during Black Friday 2025.
• Solution: Ran Microsoft Advertising Premium Streaming with 10-, 15-, and 20-second creatives across Samsung, LG, Rakuten, and Pluto.
• Results: The campaign drove a 53% increase in brand searches and a 294% lift in relevant generic searches. It also produced a 76% increase in visits to conversion pages, with CPM 40% lower than expected and a 95%+ video completion rate.
• Key Takeaway: CTV success depends on measuring post-exposure search behavior, not only direct response.

Case Study 3: Cambio Roasters — CTV-to-Display Remarketing

• Challenge: Drive ecommerce growth for a family-owned coffee brand against a 40% revenue growth target.
• Solution: Deployed a CTV-to-display remarketing strategy executed by Skai and Grain Group via Amazon Advertising.
• Results: The remarketing campaigns produced 85% revenue growth vs. the 40% target. Conquesting campaigns saw a 74% conversion increase, with a 14% ROAS lift and a 20% decrease in cost per conversion across 53 million combined impressions.
• Key Takeaway: CTV amplifies the performance of lower-funnel channels when connected to remarketing.

Across these CTV examples, a pattern emerges. CTV drives measurable lift in search, remarketing, and direct response when brands measure post-exposure behavior and connect upper-funnel impressions to lower-funnel outcomes.

DSP Optimization, Creative Automation, and Supply-Side Case Studies

Case Study 4: A+E Global Media — Pod-Level Auctions

• Challenge: Reduce operational complexity and unlock greater value from premium streaming inventory.
• Solution: Shifted from slot-level to pod-level auctions using Index Exchange’s OpenRTB 2.6 implementation.
• Results: The change delivered an 84% reduction in ad-server requests and a 39% average increase in impressions and 19% average increase in ad spend for podded vs. unpodded supply.
• Key Takeaway: Infrastructure efficiency functions as a core adtech KPI.

Case Study 5: PubMatic and Dentsu — CTV Contextual Precision

• Challenge: Reach B2B decision-makers in the financial professional services sector with privacy-focused targeting.
• Solution: Used the PubMatic SSP integrated with Cocie AI’s contextual targeting technology, analyzing content themes and viewing behaviors in real time.
• Results: The campaign achieved 72% lower eCPM vs. other CTV partners and drove 5% of total landing-page visits.
• Key Takeaway: Premium inventory combined with contextual precision delivers cost efficiency and quality engagement.

Case Study 6: PubMatic and Agence 79 — Programmatic Video Curation

• Challenge: Improve click efficiency for a leading retail client in France.
• Solution: Activated PubMatic’s advanced curation solutions via Havas Media Network subsidiary Agence 79.
• Results: Curated inventory delivered a 5x higher CTR vs. the open market.
• Key Takeaway: Curated supply consistently outperforms open marketplaces on click efficiency.

Case Study 7: SEGA — Creative Automation at Scale

• Challenge: Scale creative production across seven international markets while improving performance efficiency for direct-response campaigns.
• Solution: Implemented Bannerflow’s creative automation plus Social Dynamic Ads, dynamically populating local currencies, age ratings, and product features at serve time.
• Results: The program produced a 44% reduction in CPM and a 14% reduction in CPC. Production time dropped by two-thirds, from three weeks to one week.
• Key Takeaway: Dynamic creative automation enables personalization at scale without proportional production cost.

Together, these cases show how smarter supply, curated inventory, and automated creative workflows compound performance gains across both buy and sell sides.

Identity and Cookieless Solutions

Case Study 8: UNICEF — Cookieless SORT Technology

• Challenge: Boost awareness of UNICEF’s overseas support in Ukraine without third-party cookies.
• Solution: Used Perion’s SORT technology with cookieless clustering based on in-the-moment behaviors and multi-format ad placements.
• Results: The campaign delivered a 2x lift in page grabber visitation vs. third-party targeting and a 97% lift in brand visitation rate. It also produced a 75% lift in page grabber interactions vs. contextual targeting.
• Key Takeaway: Cookieless solutions can outperform cookie-based targeting across key engagement metrics.

Case Study 9: Owl Labs — Cookieless Product Launch

• Challenge: Launch a new video conferencing product with brand awareness and interactive engagement at scale across browsers where cookie-based targeting has limited reach.
• Solution: Activated Perion’s SORT cookieless technology with high-impact ad units, including full-screen canvas ads and animated banners.
• Results: The campaign achieved a 77% lift in bottom adhesion CPR and a 21.5% lift in interaction rate vs. cookie-based targeting.
• Key Takeaway: Privacy-first targeting reaches and engages audiences that cookies miss.

Case Study 10: Lily’s Kitchen — Cookieless Brand Campaign

• Challenge: Reach pet owners at scale without media pixels or cookies while maintaining brand safety and ethical credentials.
• Solution: Journey Further used trusted cookieless data sets (TGI), publisher first-party data, contextual targeting, and attention-based optimization across programmatic DSPs, Spotify, CTV, and Netflix.
• Results: The campaign drove an 18% increase in recall and favourability, 23% increase in purchase intent, and 8% increase in unprompted brand awareness.
• Key Takeaway: Attention metrics can stand in for conversion pixels in cookieless environments.

Across UNICEF, Owl Labs, and Lily’s Kitchen, privacy-first and cookieless approaches consistently match or beat cookie-based tactics on engagement, cost, and brand lift.

Mobile App Monetization and Measurement

Case Study 11: Streaming Platform — Secure Multi-Party Computation

• Challenge: Measure a brand awareness campaign without sharing subscriber lists or revealing which users saw the ad, while meeting GDPR and CCPA requirements.
• Solution: Implemented a secure multi-party computation (MPC) protocol with a major social network, enabling joint measurement without exposing individual records.
• Results: The collaboration generated 127,000 incremental trial sign-ups with a 34% conversion rate to paid subscriptions. Performance was strongest among the 25-to-34 demographic and remained fully GDPR and CCPA compliant.
• Key Takeaway: Privacy-enhancing technologies enable robust measurement without data exposure.

Case Study 12: Swiss Bank — Data Clean Room Lookalikes

• Challenge: Build lookalike audiences without third-party cookies for a regulated financial institution.
• Solution: Used the Decentriq data clean room for privacy-safe lookalike audience targeting.
• Results: The bank saw a 129% increase in CTR and a 57% increase in page view rate, along with a 44% decrease in cost per page view vs. standard campaigns.
• Key Takeaway: Clean rooms unlock first-party data for targeting while protecting individual records.

Professional Services and B2B CTV

Case Study 13: Westridge Counsel — CTV for Professional Services

• Challenge: Generate incremental qualified inquiries for a regional estate and tax planning firm with a long sales cycle, without reallocating from existing channels.
• Solution: Ran a six-month CTV campaign via Adwave at $2,200 per month with a vanity URL conversion event, intake form attribution question, and pre/post baseline measurement.
• Results: The program produced 49 net incremental inquiries, a 53% lift over baseline. Of those, 41% converted to consultations and 56% converted to retained clients, yielding a first-year ROAS of about 3.3x and a projected lifetime ROAS of about 24x.
• Key Takeaway: Baseline measurement captures CTV impact that direct attribution misses.

Case Study 14: Patriot Auto Group — CTV for Local Brand Building

• Challenge: Expand brand recognition beyond a 10-mile radius and reduce dependence on rising third-party lead costs.
• Solution: Launched a CTV campaign via Adwave targeting adults 25–64 within 30 miles, with creative rotated every 4–6 weeks from November 2025 to February 2026.
• Results: The dealership saw a 34% increase in showroom visits and a 41% increase in branded searches. Cost per vehicle sold dropped 28%, and CTV delivered a 2.8x ROAS.
• Key Takeaway: CTV awareness spend lifts the performance of downstream channels such as search and in-store traffic.

Case Study 15: Telecom DOOH Platform — Operational AdTech at Scale

• Challenge: Replace fragmented workflows, manual campaign execution, and inconsistent analytics across 16,000+ edge devices for a leading US telecom’s DOOH network.
• Solution: Deployed QBurst’s cloud-native microservices platform on AWS, unifying DOOH and in-vehicle media under a single intelligent adtech platform with real-time telemetry.
• Results: The platform delivered a 63% reduction in campaign activation time and a 45% boost in ad engagement via contextual targeting. It maintained 99.7% uptime across 16,000+ devices.
• Key Takeaway: Operational metrics such as uptime, activation time, and system efficiency belong beside media metrics in adtech reporting.

Taken together, these 15 campaigns show three consistent themes. Infrastructure efficiency produces measurable ROI, privacy-first targeting outperforms cookie-based approaches, and CTV compounds the impact of lower-funnel channels when measurement connects the full journey.

Schedule a Strategy Call to see how SaaSHero applies these adtech principles to B2B paid media programs while optimizing against CRM revenue data.

Privacy-First and Cookieless Strategies: What the Data Shows

The case studies above demonstrate that privacy-first strategies frequently outperform cookie-based tactics on cost and engagement. UNICEF’s cookieless SORT campaign delivered a 97% lift in brand visitation, and Owl Labs saw a 21.5% lift in interaction rate versus cookie-based targeting. Lily’s Kitchen achieved double-digit gains in recall and purchase intent without pixels or cookies. These outcomes align with broader industry data. Contextual advertising now delivers CTRs within 5–8% of behavioral targeting, and server-side tracking recovers 15–30% of lost conversion signals. ID-less audiences such as iOS and Safari users deliver lower CPMs, lower cost per acquisition, and higher average order value compared to cookie-addressable audiences, even when absolute conversion volumes are lower. CRM audiences built from first-party data deliver a 3.4x ROAS lift over interest-based targeting.

The structural shift toward privacy-first marketing remains permanent regardless of Google’s cookie decisions. Safari and Firefox blocked third-party cookies years ago, meaning approximately 40% of US web traffic was already cookieless before Chrome’s phased changes. Brands with mature first-party data strategies saw an average 35% improvement in measurement accuracy during the transition to privacy-compliant tracking architectures, based on Digimau’s client work since 2023. Marketers who invest in first-party data, contextual intelligence, and privacy-enhancing technologies now gain a durable performance advantage.

How to Build Your Own AdTech Case Study

The Challenge-Solution-Results format used throughout this guide applies directly to your own reporting. To build a board-ready adtech case study from your campaigns, track the following elements.

• Primary conversions: Sales-qualified leads, opportunities created, and closed revenue, rather than raw form fills.
• Secondary conversions: Content downloads and webinar registrations, tracked but excluded from bidding optimization.
• Incrementality: Geo holdouts or matched-market tests that isolate causal lift from correlation.
• Viewability and completion rate: Metrics that confirm ads were seen, not just served.
• Pipeline created: Ad spend connected to CRM-recorded pipeline using lifecycle stage events.
• CAC payback: Results expressed in months to recover acquisition cost, matching CFO expectations.
• LTV:CAC ratio: A ratio above 3:1 as the standard threshold for a healthy SaaS acquisition channel.

Present results in language that reconciles with finance. Board-ready measurement reconciles to finance, documents assumptions, carries an audit trail, links to decisions, and has a governance owner. Pipeline coverage and CAC payback, rather than impressions or MQLs, are the metrics that withstand CFO scrutiny. To capture results like the case studies in this guide, structure your own measurement and storytelling around these same principles.

Common Pitfalls in AdTech Marketing

Failed adtech implementations tend to share a small set of recurring mistakes. Each pitfall below includes a diagnostic question to help you spot the issue in your current program.

• Over-reliance on last-click attribution. In a six-to-nine-month B2B sales cycle, last-click credits the branded search that happened after the decision was made, which defunds the channels that created demand. Diagnostic: What did this channel actually cause, versus merely touch?
• Ignoring viewability. An ad that was never seen cannot influence a buyer. 72% of ad buyers now prioritize cross-platform measurement that connects activation to business results. Diagnostic: Were my ads even seen?
• Failing to test incrementality. 82% of marketers are not fully confident in their attribution data. Incrementality testing provides the only reliable way to measure causation rather than correlation. Diagnostic: What would happen if I turned this channel off?
• Neglecting creative fatigue. SEGA cut production time by two-thirds specifically to enable faster creative iteration and avoid fatigue. Diagnostic: When was the last time I refreshed creative?
• Optimizing to form fills instead of revenue. An algorithm trained on form fills finds the people most likely to submit forms, such as students, competitors, and job seekers, rather than buyers. Diagnostic: Are we optimizing campaigns around CRM data or just form submissions?

These pitfalls compound when left unaddressed. Teams that correct attribution, viewability, incrementality, creative cadence, and optimization targets usually see rapid improvements in both efficiency and revenue impact.

Why SaaSHero Is the Recommended Partner

SaaSHero serves as the outsourced inbound growth team for B2B companies, with one team owning strategy and execution across paid media, creative, landing pages, and reporting. The team optimizes everything against CRM revenue data rather than form-fill counts. The firm has managed over $60M in lifetime ad spend across 100+ B2B companies, holds Google Premier Partner status (top 3% of agencies), and ranks #20 of approximately 6,000 agencies on G2.

The SaaSHero approach operationalizes what the strongest adtech case studies demonstrate. The team feeds algorithms high-quality signals, owns the post-click experience, and measures against pipeline instead of lead volume. TripMaster generated $504,758 in net new ARR with a 650% ROAS from paid search. TestGorilla achieved an 80-day CAC payback period while adding more than 5,000 new customers. Playvox reduced cost per lead by 10x while increasing lead volume by 163%.

The fee structure uses a flat retainer indexed to total monthly ad spend. The model avoids a percentage-of-spend fee or per-channel charges. Adding a channel, shifting budget, or testing a new platform carries no fee consequence, so channel-mix decisions rest on evidence alone.

Talk With SaaSHero About Your AdTech Roadmap and explore how to apply these principles to your own B2B programs.

Frequently Asked Questions

What Is AdTech Marketing?

Adtech marketing uses technology to automate and improve digital advertising buying, targeting, and measurement across programmatic display, CTV, social, and search. It encompasses demand-side platforms, supply-side platforms, data management platforms, identity resolution, and creative automation. The defining characteristic is that decisions about which inventory to buy, at what price, and for which audience occur algorithmically in real time rather than manually in advance.

How Do I Measure AdTech ROI?

Measure performance against CRM outcomes such as pipeline created, CAC payback, and closed revenue instead of form fills. A standard approach separates primary conversions, like sales-qualified leads and opportunities, from secondary conversions, like content downloads and webinar registrations. Use only primary conversions for bidding optimization and push lifecycle stage events back into the ad platforms so the algorithm learns from qualified outcomes. Use incrementality testing, including geo holdouts or matched-market experiments, to validate causal lift instead of relying on attribution models alone. For sales cycles longer than 90 days, report pipeline ROAS rather than closed-revenue ROAS to reduce lag in board reporting.

What Are the Best AdTech Case Studies?

The strongest adtech case studies combine hard metrics with documented methodology. The five highest-impact examples in this guide are Virgin Atlantic, SEGA, A+E Global Media, UNICEF, and Cambio Roasters. Each one documents the challenge, the technical solution, and the specific metrics used to evaluate success, so stakeholders can understand both what happened and why.

How Do AdTech Case Studies Differ From Digital Marketing Case Studies?

Traditional digital marketing case studies document messaging changes, creative refreshes, and channel mix decisions. Adtech case studies document technical infrastructure, data plumbing, and system efficiency. Results in adtech case studies frequently include operational metrics such as ad-server request reduction, campaign activation time, system uptime, and bid response latency that never appear in a conventional marketing case study. The challenge section of an adtech case study often describes fragmented data pipelines or legacy platform architecture alongside targeting or messaging problems.

What Metrics Matter in AdTech?

The metrics that matter depend on the campaign objective and funnel stage. For awareness campaigns, focus on reach, frequency, video completion rate, and brand lift. For consideration, emphasize engagement rate, site visits after exposure, and attention scores. For conversion, prioritize cost per acquisition, ROAS, and incremental sales lift. Across all stages, viewability confirms that ads were seen rather than merely served, and incrementality testing validates that the campaign caused the outcome rather than coinciding with it. For B2B programs specifically, CAC payback and pipeline-to-spend ratio are the metrics that withstand board scrutiny.

What Is Cookieless Advertising?

Cookieless advertising refers to targeting and measurement that do not rely on third-party cookies, the cross-site identifiers that, as noted earlier, Safari and Firefox have blocked for years and that Chrome has been phasing out. Cookieless strategies include first-party data activation, such as uploading CRM lists to ad platforms via Customer Match, contextual targeting based on page content, identity solutions like hashed email-based identifiers, data clean rooms for privacy-safe data matching, and privacy-enhancing technologies such as secure multi-party computation. The case studies in this guide show that cookieless approaches frequently outperform cookie-based targeting on engagement and cost efficiency metrics.

How Do I Choose an AdTech Partner?

Evaluate adtech partners on four criteria. First, CRM-data optimization, where the partner connects ad platform bidding to CRM lifecycle events rather than form fills. Second, full-funnel ownership, where the partner owns the post-click experience, including landing pages, conversion tracking, and creative, not just the ad account. Third, in-house creative, because creative produced by the same team running the media enables faster iteration and tighter message-to-audience alignment. Fourth, fee structure, where a flat retainer indexed to total ad spend, rather than a percentage of spend or a per-channel charge, removes the financial incentive to maintain a suboptimal channel mix. Ask any prospective partner directly what the ad platform is trained on and how the fee structure aligns with your performance goals.