Addressing Transparency Challenges in Programmatic Advertising

You can’t be the player and the referee. It’s common sense. Yet, the ad tech ecosystem is built on vendors trying to do exactly that. The landscape is riddled with intentional conflicts of interest designed to obscure margins and create dependency. We see this playing out in two ways: 1. The "Grading Your Own Homework" Problem. A media platform (think Meta, Google, but also many, many others) delivers the ads and also provides the performance data. You pay them for inventory (how much?? We don’t really know), and they are the only ones telling you how well the campaign worked. They tell you their own performance. How do you verify this? You can’t. 🤨 We see platforms pitch "performance" solutions directly to brands every day. They control the inventory access. They control the attribution data. They report record-breaking results quarter after quarter. Business is always booming when you grade your own exams. When the vendor controls the ruler, the measurements will always look favorable to the vendor. You are forced to trust that their internal metrics are accurate rather than engineered to encourage you to spend more. 2. The Transparency Trap. We see this with aggregators who bundle service fees and media costs into one opaque number. Sometimes called "programmatic managed service”. You have no way of knowing how much of your dollar actually went to working media versus how much went into their pocket as an undisclosed markup. These vendors often attempt to manage split loyalties. They sell wholesale inventory to agencies while simultaneously pitching clients directly. They use the intelligence gained from one side to undercut the other. They cannot balance these commitments without compromising the integrity of one. Will they choose you (the client) or their own bottom line? Again..🤔 So what can you do? Stop accepting ambiguity. You must distinguish between service and inventory. Ask your partners three questions today: • Who is your client? Is the client me, or am I actually the product? If it’s a free service, you’re the product being sold! • How do you make your money? Is the model a transparent, flat managed service fee, or are you making an unknown margin? • Do you use third-party measurement? Or am I just trusting your internal numbers? What are the truly independent verification options? If a potential partner is vague, evasive, or claims that information is proprietary, you already have your answer.

This morning, AdExchanger published an insightful piece highlighting a critical challenge in the Connected TV space—premium publishers increasingly bundling their streaming inventory in opaque ways that limit advertiser visibility. Rather than providing app and show-level transparency within the bid stream—where it can be actioned—advertisers are often left with fragmented, one-off reports that offer little opportunity for strategic optimization. By adopting these black-box models, publishers are inadvertently undermining their own value. Their most significant asset—the premium content they produce—is being devalued when advertisers cannot effectively align their investments with the programming that resonates most with their audiences. The reality is that advertisers are willing to pay higher CPMs for impressions with full content transparency because it allows them to make more informed decisions and, ultimately, drive better performance. This principle has long been the foundation of linear TV, where show-level buying had created a thriving, demand-driven ecosystem rooted in transparency and accountability. At Rain the Growth Agency, we’ve seen firsthand how transparency fuels success in CTV. By leveraging show & channel level data and aligning our digital buying strategies with the programming that has proven effective in our clients’ linear campaigns, we’re driving significant performance gains. And are willing to pay higher cpms than we otherwise might. We’re working with partners like Spectrum Reach, Samsung Ads, fuboTV Network & DIRECTV which provide the transparency needed at the show & network level to make data-driven investment decisions that maximize ROI through our custom algorithms & buying strategies. A notable example is Alexander Groysman at Spectrum Reach, who has led the charge in developing one of the most comprehensive and well-structured content metadata sets in the industry. His work has set a new standard for transparency, enabling advertisers to better understand performance at a granular level and optimize their spend accordingly. As streaming networks attempt to replicate the playbook of tech companies, they risk overlooking a crucial difference: they are not technology companies. They lack the same product offerings, incentives, and advertiser appeal that drive digital platforms’ success. In chasing the tech model, they may ultimately lose what has always differentiated them—high-quality, trusted content that brands are eager to invest in when they can do so with confidence and clarity. Publishers who prioritize transparency stand to gain the most, while those who don't risk leaving money on the table and eroding advertiser trust. It’s time to rethink the approach before it’s too late. Link to article in comments.

The job advertising industry is fundamentally inefficient: full of hidden markups, faulty processes, and little accountability. Let me explain: At its core, this is a marketplace. You’ve got: > Buyers: employers spending heavily to find relevant talent > Suppliers: job boards, aggregators, and anyone with access to candidates The marketplace should stay neutral, optimize for employer outcomes, and reward high-performing suppliers. That’s the theory. Now let’s look at other “programmatic” job ad platforms. They’re glorified job distributors. Here are the problems. 1. Lack of transparency in spend They tell employers: We’ll manage your media budget for a 7.5–10% fee. That should ideally be the only markup. However, suppliers offer platforms 10-15% commissions to incentivize spend. (I’m glad this is not a state secret anymore.) So the platform profits from both sides: buyers & suppliers. The system can favor suppliers who pay higher commissions, without disclosing them to employers. Budgets are funneled through a blind exchange (black box) with hidden markups of 50–60%. Spend looks efficient, but a large chunk disappears into undisclosed markups & incentives. 2. Lack of transparency Most platforms don’t show you which specific source led to a hire. If you can’t see source-to-hire, you’re flying blind. 3. Broken application processes 93-97% of candidates who start a job application don’t complete it, because of long forms & bad user experience. 4. Wrong locations & confusing job titles Employers post a job in one location, but talent live somewhere else. Also, some job titles make no sense. So many candidates never even see the right jobs! 5. Wrong numbers The numbers you are seeing in your reports are wrong! When candidates don’t accept cookies, they don’t get attributed to the right campaigns. We started Joveo to solve the inefficiency in our ecosystem. Here’s how. 1. Our platform is built to be, in reality, neutral & agnostic. We don’t let supplier commissions influence the media buying decision process. Our AI doesn’t even see them. We optimize for employers’ outcomes: candidate quality, speed & budget efficiency. 2. We’re transparent. We show every source & every hire, with full transparency. 3. We’re independent. We’re not owned by a job board. Our only incentive is to do what’s right for the employer. 4. We fix inefficiency. We built our own job application optimization tech to fix drop-offs. Jobs are shown in the right locations based on commute distances. AI rewrites job titles & descriptions to include top-searched keywords, so job seekers can easily find them. We enable employers to re-engage their talent pools, so they’re not paying to re-acquire candidates they already have. 5. We’re accountable. See it to believe it. Run a trial next to anyone out there, and let the results speak for themselves. We’re about 20-25% more efficient right out of the gate, even before we start optimizing!

The Association of National Advertisers' latest Programmatic Transparency Benchmark, in collaboration with TAG TrustNet, delivers a sobering reality check for our industry: programmatic waste has surged 34% in just two years, now reaching $26.8 billion. - For every dollar invested, fewer flow into actual working media. - In Q2 2025, 37.8% of spend was inefficient, with transaction costs alone eating up over 25%. - The True Ad Spend Index dropped from 41 in Q1 to just 37 in Q2. - Even TrueCPM shows a persistent gap of 36.5%. Why this matters: The invisible has been made visible. And with this visibility comes responsibility. 1. Action over vanity metrics: #CTR isn’t always the KPI to optimize. Run campaign performance analyses and define what really drives your business. 2. Connect audiences to actions: measurement that ties both together will have the highest odds of success. 3. Leverage real-time dashboards: they’ve already helped reduce inefficiency in Made for Advertising (#MFA) sites from 2.3% in 2023 to just 0.8%. Similar gains are within reach in #CTV and Private Market Places fighting #counterfeitads and other fraudulent traffic. The bigger picture: This isn’t just about saving wasted dollars. It’s about building sustainable growth. Brand-safe premium inventory made transparent will increasingly become the currency of trust between advertisers, agencies, and platforms. Transparency is your competitive edge. Always in-tune, navigating with curiosity and Zeal. MediaPost Joe Mandese #adtech #pmp #programmatic #trustinmedia #transparency

While programmatic offers speed and scale, it also comes with complexities, from data gaps to transparency issues, that marketers must learn to manage. Here are a few key challenges we encounter and how we handle them: 1. Brand Safety & Ad Fraud Ads running in the wrong environment or facing invalid traffic can harm brand reputation and waste budget. How we handle it: We use advanced brand safety and suitability tools combined with pre-bid filters from trusted third-party verification platforms. Supply Path Optimization (SPO) ensures our campaigns only access high-quality, transparent inventory, minimizing risk and maximizing value. 2. Data Privacy & Compliance Evolving regulations like GDPR, CCPA, and now the global push towards privacy-first approaches mean we must be vigilant in handling user data responsibly. How we handle it: We adopt privacy-first strategies, work with compliant vendors, and integrate consent management platforms to ensure full regulatory adherence without compromising campaign effectiveness. 3. Measurement & Attribution Cross-device behavior, walled gardens, and cookie deprecation make accurate performance measurement more complex than ever. How we handle it: We’re adapting by prioritizing first-party data strategies, enhancing server-side tracking implementations, and moving beyond traditional attribution models. Where possible, we use data-driven or modeled attribution and complement it with incrementality testing and platform-based lift studies to better understand true campaign impact. 4. Technology Complexity & Integration Programmatic involves multiple platforms, DSPs, SSPs, data providers, and more, creating a complex ecosystem to manage efficiently. How we handle it: We streamline workflows using automation tools, develop standardized processes, and maintain close collaboration between teams and technology partners to reduce errors and boost campaign agility. Despite these challenges, programmatic advertising’s benefits far outweigh the hurdles, especially when you turn challenges into opportunities with the right strategies and tools. At the end of the day, programmatic isn’t just about technology or data; it’s about how we adapt, innovate, and stay vigilant to drive brand growth safely and effectively. #ProgrammaticAdvertising #BrandSafety #DataPrivacy #AdTech #MarketingChallenges #DigitalMarketing

If you are running programmatic Ads for B2B - Read this My client was facing significant challenges with programmatic advertising for B2B services and software. Despite extensive use of digital channels like Google Display Network, Google Paid Search, LinkedIn, and Bing Paid Search—which show clear user engagement and click-through conversions—programmatic ads result in high bounce rates close to 99%, with little to no real user engagement or conversions. ➡️ Possible Causes: ◾ Bot Traffic: A high volume of traffic from identical IP addresses, with uniform engagement patterns, suggests bot activity. ◾ Ineffective Targeting: Cookie-based targeting in programmatic platforms may not accurately reach intended audiences. ◾ Misalignment of Metrics: Traditional engagement metrics (click-through rate, time on site, etc.) may not effectively measure the impact of programmatic ads, which some liken to billboard advertising. ➡️Solution: ✔️ Scroll Tracking: We use tools like Google Tag Manager (GTM) to implement scroll tracking, firing a pixel once a visitor scrolls through a significant portion of the page (e.g., 50%). This provides a better indicator of engagement beyond mere page views. ✔️View-Through Conversions: Shift focus to view-through conversions, which track if users who saw your ad but didn’t immediately click on it, convert later. This acknowledges the billboard-like nature of programmatic ads. (In this case, we can also consider metrics like brand recall and search lift, which reflect the indirect benefits of visibility and brand exposure.) ✔️Report Suspicions: Address the suspected bot activity by reporting it to your Demand-Side Platform (DSP) or Account-Based Marketing (ABM) platform provider. Request investigations and refunds for fraudulent activity. ✔️Use Advanced Filters: Implement IP blocking and more sophisticated fraud detection measures to improve the quality of traffic. ✔️Cross-Channel Retargeting: Use insights from more successful channels to retarget engaged users through programmatic ads. ✔️Unified Analytics: Analyze data across all platforms to better understand user paths and optimize ad strategies accordingly. ➡️ Results: ◾ Better Traffic Quality ◾ More Realistic Goals ◾ Higher ROI P.S. Programmatic ads are great for boosting brand awareness, even if they don't always get direct clicks. By adjusting your strategy and expectations, you can maximize their effectiveness and see better results.

Earlier in my career, I helped build an ad-exchange with RTB. And one thing people underestimate is how brutal that world is. Ads aren’t a line of text. Ads are infrastructure. Without pixels, conversion tracking, attribution, remarketing, standard CPC/CPM economics, fraud checks, solid advertiser–publisher balancing… nothing works. Technically, if you miss the latency budget (often <50ms end-to-end) you simply lose every bids. That’s why the current idea of "just blend ads into LLM answers" is… interesting and massively under-appreciated. It requires a lot of backend machinery to become even remotely useful. One major issue is that influence inside the answer becomes invisible. A model can quietly avoid certain topics, soften negatives about a sponsor, or reframe something as "best practice" (look Google SERP). Most jurisdictions legally require visual ad labeling. But ads blended into conversation make labeling almost impossible for users to detect. Not only text but code (using a specific SDK or using a certain cloud provider) and generated images/videos (adding luxury items in the foreground or branded products in the background). In voice mode, micro-nudges toward a product mid-explanation start to sound like Black Mirror (S7E1 - Common People). Free users will definitely enjoy hidden affiliate links, commissions, and commercial recommendations disguised as "helpful" (maybe it's already the case). The economics are unclear. Adtech is low-margin, inference is expensive and slow, and ROI only appears when ads actually convert. But if LLMs move to agentic buying, i.e. recommending a product and executing the purchase in-chat, the model switches from CPC/CPM to CPE/CPO (paying per engagement / order). The attribution becomes end-to-end: impression → suggestion → conversion, which is the graal! To trust LLMs, we'll need transparency by design: logs of sponsored insertions, clear visual labeling, attested outputs that guarantee the reasoning wasn't shaped by something outside the LLM own intelligence.

There’s a lot of noise right now around ad tech transparency, platform fees, and agency audits. None of this is new, but what is new is the level of attention and (finally) action behind it. Behind all of this are the economic issues that have persisted in the space for a long time. Money in advertising flows in one direction: Advertisers → Publishers. Any platform, feature, or “value‑add” in between is a cost to the advertiser. To better understand the fees in legacy ad buy flows, here is a simplified (but realistic) flow: - Agency fee: 10–15% - DSP fees: - Platform: 10–15% - Audience activation: $0.35–$2.50 CPM - Fraud prevention: $0.15–$0.55 CPM - SSP fee: 10–20% So before a bid ever reaches a publisher auction through these legacy flows, a meaningful portion of its value is already gone. These fees don’t just affect efficiency; they directly determine which auctions you win and the quality of inventory you access. A $10 DSP bid can become a $5 bid or less by the time it hits the publisher auction, which is the only auction that matters. Now layer in incrementality. Despite the buzz, many systems still rely on last-touch attribution, arbitrary conversion windows, and fragmented, probabilistic identity matching. These systems aren’t designed to prove lift; they’re designed to assign credit. The result is reported performance without true revenue uplift. And that’s the uncomfortable truth: A significant portion of advertising spend still isn’t truly incremental. So when agencies and brands push for transparency, it’s about two table‑stakes questions: - How much of my dollar actually reaches the publisher auction? - Can I clearly prove net revenue or sales uplift from what I bought? This is why I was drawn to Mastercard Commerce Media. When attribution and incrementality are solved upfront, you can stop debating inputs and start optimizing for what actually matters: efficient media, real lift, and measurable growth. #adtech

Principal media usage grew 11% last year - yet nearly half of advertisers still have no formal governance around it. That should worry CMOs. The Association of National Advertisers (ANA) has just updated its highly influential report, “The Acceleration of Principal Media", highlighting both rising adoption (+11% YoY) and growing advertiser awareness (96% being very or somewhat familiar). Although there are ethical concerns around principal media, my personal view is that it can be beneficial for brands, provided all parties clearly understand why partners are being recommended and how money is being made. Principal media can unlock: 💸 Greater cost efficiency and buying power 🏆 Access to inventory that might otherwise be unavailable 💡 Opportunities to participate in larger or more strategic deals However, this only works if agencies are transparent about why specific media inventory is being recommended, and the commercial implications of selection for both advertiser and agency. According to the ANA's new report, “The Continued Acceleration of Principal Media”, lack of transparency remains the single greatest concern for advertisers, cited by 90% of respondents. What is perhaps more concerning is that governance guardrails remain limited. Nearly half of advertisers report having no formal guidelines in place to manage the use of principal media. Advertisers need to address this immediately. Key actions for advertisers should include: 1️⃣ Establishment of formal governance structures and approval workflows (i.e. no blanket approvals) 2️⃣ Locking in strong contractual protections, with explicit terms covering principal media (e.g. transparency auditing, data rights) 3️⃣ Requirements for full transparency in how principal media is used in planning, partner selection and performance reporting 4️⃣ Demand a clear business case for principal media (including comparisons with alternative buying routes), validated by procurement or an independent third party 5️⃣ Maintain financial discipline - track spend, set caps and monitor allocations through ongoing auditing 6️⃣ Manage risk and strategic alignment by ensuring brand safety and campaign fit, and only deploying principal media where it demonstrably adds value For marketers, governance and agency commercial design matter now more than ever. If this is something you’re currently navigating, I’d be happy to share perspectives, or discuss the governance challenges I’m seeing across the industry. Feel free to get in touch. #media #digitalmedia #planning #strategy #marketing #marketingstrategy #advertising Overline Goodway Group Paul Frampton-Calero ⚡️ Fiona Davis Nick King Jeremy Hines

Mastering Supply Path Optimization (SPO) in Programmatic Advertising: A Step-by-Step Strategy In the fast-evolving world of programmatic advertising, efficiency and transparency are paramount. Supply Path Optimization (SPO) has emerged as a critical tactic for advertisers aiming to reduce ad fraud, streamline transactions, and boost return on investment (ROI). By refining the route between demand-side platforms (DSPs) and supply-side platforms (SSPs), SPO eliminates wasteful intermediaries and ensures ad spend reaches high-quality inventory. Here’s a step-by-step strategy to implement SPO in your programmatic campaigns effectively. Step 1: Define Your Objectives Start by clarifying what you want SPO to achieve—whether it’s cutting costs, improving transparency, or reducing fraud. For example, if your goal is to combat fraud, prioritize verified publishers and minimize resold inventory. Establish key performance indicators (KPIs) like cost-per-mille (CPM) reduction, viewability rates, or fraud incidence to measure success. Clear objectives align your team and technology toward tangible outcomes. Step 2: Audit Your Supply ChainExpected output: Assess your current supply paths using DSP and SSP reporting tools. Platforms like The Trade Desk or PubMatic provide detailed logs of bid requests, wins, and impressions. Identify inefficiencies—such as excessive hops between intermediaries or duplicated inventory—and map out the supply chain. Look for patterns like high CPMs from low-quality sources or discrepancies in impression counts, which signal fraud or waste. Step 3: Select Trusted Partners Narrow your SSP partnerships to a curated list of reliable, transparent providers. Favor SSPs like Magnite or PubMatic that offer direct publisher relationships and fraud-detection tools. Negotiate private marketplace (PMP) deals to secure premium inventory, bypassing crowded open exchanges. Fewer, high-quality connections reduce complexity and enhance control. Step 4: Implement and Test Configure your DSP to prioritize optimized paths based on your audit findings. Use bid filters to exclude low-performing sources and allocate budget to tested partners. Run A/B tests comparing SPO-optimized campaigns against baseline setups to measure improvements in ROI, fraud rates, and delivery efficiency. Adjust bids and rules in real time based on performance data. Step 5: Monitor and Refine Continuously track results using analytics dashboards. Leverage tools like Unified ID 2.0 for better transparency and attribution. Regularly review publisher performance and prune underperformers. As market dynamics shift, adapt your SPO strategy to maintain gains. By following these steps, advertisers can transform their programmatic campaigns into lean, fraud-resistant operations. SPO isn’t a one-time fix—it’s an ongoing commitment to smarter spending and stronger results.