Joanna Drews

Advanced measurement is moving from a “nice to have” to a requirement for brands that want to prove how marketing drives real business outcomes.✅ Nowhere is this more visible than in Retail Media Networks. RMNs like Instacart give brands access to closed-loop performance data tied to actual purchases. That data is powerful, but it also raises an important question for marketing leaders: How do we validate results beyond platform-reported metrics and understand true incremental impact? This is why third-party measurement is becoming a critical part of the RMN conversation. Circana has emerged as a leading independent measurement partner for retail media performance, including Instacart. By combining retailer point-of-sale data with broader market and category intelligence, Circana helps brands understand not just what sold, but what actually changed because of advertising. https://lnkd.in/gp4CghWf For food and beverage brands, this matters because RMN performance rarely exists in isolation. Retail media influences household penetration, repeat rates, brand switching, and category growth, not just attributed sales within a single platform. Third-party measurement helps separate signal from noise by providing a consistent view across retailers, channels, and time. The broader industry trend is clear. As RMN budgets grow, marketers are being asked to answer harder questions around incrementality, brand impact, and long-term growth. Platform dashboards alone are no longer enough. At Effective, we see advanced media performance reporting as a layered system. Platform data shows what happened. Third-party measurement helps explain why it happened and whether it was truly incremental. Together, they create a clearer connection between media investment and business results. This is how performance reporting evolves from tracking activity to proving impact. Jeff O'Shaughnessy Joelle Kaplan #MarketingMeasurement #RetailMedia #MediaPerformance #Incrementality #F&B #MarketingEffectiveness

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Today is a huge milestone for our company. We're happy to announce the release of Agile Mix Modeling™ - a first of its kind, full-funnel media measurement solution that leverages advance machine learning models to measure all media - including offline channels and walled gardens. Read the exclusive article from Digiday that explains how our clients Sierra Nevada Brewing Co. and GE Lighting, a Savant company were able to boost ROI and incremental revenue by getting performance insights in a matter of days, not months. Cheers!

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Impression-level AI is powerful only if the data inputs are clean and the incentives are aligned. Moving intelligence upstream doesn’t eliminate opacity by default. If agentic systems are making micro-decisions in milliseconds, transparency and governance become even more critical especially as AI-driven optimization increasingly determines pricing, prioritization, and access. There’s also a structural implication. When optimization lives at the impression layer, differentiation shifts from bulk inventory to signal quality and predictive modeling. The competitive edge is who can predict value most accurately at the micro level.

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CMOs demand guaranteed delivery, lowest CPMs, strategic flexibility, and outcome-based pricing. Physics says you can't have all four simultaneously. Principal media delivers three of them. The question is which three matter most. Forrester's new principal media report from the inimitable Jay Pattisall is very much worth a read, and it's going to trigger the predictable debate. Critics will argue agencies are creating conflicts. Evangelists will tout cost savings. Both will miss the strategic reality: CMOs facing compression don't have the luxury of perfect markets. I've watched boards push CMOs for guaranteed outcomes while slashing budgets. In that environment, academic arguments about strategic flexibility mean nothing. The anti-principal media argument assumes unlimited client patience, perfect information, and rational markets. Reality looks different. Reality is: your board wants cost certainty so they can model P&L without media volatility. Reality is: your CFO wants guaranteed delivery so you're not scrambling for Super Bowl inventory in scatter markets. Reality is: your CEO wants outcome-based pricing that ties media spend to business results. Principal media trades strategic flexibility for the three things boards actually care about: cost certainty, delivery guarantee, and outcome alignment. The Forrester report shows 80% of marketers are interested in principal media advantages. That's not because CMOs are naive about conflicts of interest. It's because they're making rational trade-offs under real constraints. The criticism of principal media comes from people who've never faced the impossible triangle. They can afford to optimize for strategic flexibility because they're not accountable for the P&L impact when media costs spike or inventory disappears. Yes, principal media requires transparency. Yes, it needs contractual controls and performance accountability. Yes, clients should cap how much spend flows through principal arrangements. But the mechanism itself? It's agencies finally building inventory positions that enable the outcome-based pricing we've demanded for years. I'm a big supporter as, for two decades, I've watched CMOs demand that agencies move from billing hours to pricing on outcomes. "Put skin in the game," they said. "Share the risk." Now agencies are doing exactly that with principal media, and the industry is calling it a conflict of interest. We can't have it both ways. Forrester predicts principal media will grow to one-third of billings by 2026. Read their report, then decide which three variables matter most for your business. https://lnkd.in/eKHg5qmk #PrincipalMedia #MediaBuying #CMO #MarketingLeadership #MarketingStrategy

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Personalization isn’t about channels or platforms. It’s about giving customers what they actually want. In this episode of Here’s the Deal, I share the marketer’s checklist for data activation, from unifying your data to optimizing campaigns in real time.

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Synthetic data can be exciting: it can help brands understand niche audiences faster, simulate scenarios, and extend human insight where real data is scarce. But let’s be clear, its power is conditional. Synthetic data is only as good as the human data behind it. Poor training or biased inputs can mislead marketers and erode trust. Used well, synthetic data lets marketers: ✅ Understand niche groups faster ✅ Test scenarios that traditional research can’t scale to ✅ Make decisions with more confidence The opportunity is real, but so is the risk. Start small, validate carefully, and remember: synthetic data should augment human expertise, not replace it. #SyntheticData #AI #MarketingStrategy

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Composable CDPs sit on top of existing data clouds to preserve customer 360 and activate real-time data. Here's why this architecture wins. The data is clear: 60% of organizations are investing in composable enterprise technology within the next three years. Traditional monolithic CDPs are being squeezed out—and for good reason. I had this exact conversation with the Head of MarTech for a Financial Services organization this week! Three architectural advantages driving this shift: 🔧 API-First Design: Seamless integration between components and third-party tools means your data infrastructure adapts to your business, not the other way around. ⚡ Vendor Agnosticism: Organizations aren't locked into single vendors, allowing flexibility in choosing best tools for each task. No more vendor lock-in limiting your growth. 📊 Performance + Cost: Composable solutions connect directly to the data layer, leveraging pre-built modules while enabling custom AI and ML solutions. This is exactly why our platform integrations with Snowflake, Salesforce, and Treasure Data, etc. are built on composable principles. When your CDP becomes the customer experience engine—not just a data repository—you unlock real-time personalization at scale. The question isn't whether to go composable. It's whether your current architecture can compete with organizations that already have. What's your experience with composable vs. traditional CDP architectures? https://bit.ly/4egYVyG #ComposableCDP #DataArchitecture #MarTech #CustomerData #DataStrategy Merkle

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Is AI coming for UX research? Angel Tang, UX Researcher at Merkle, weighs in on how AI transforms the field—and what it can’t replicate. Watch this insight-packed Fast Currents clip:

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If 80% of leaders say commerce complexity has outpaced their ability to manage it, at least they see the challenge ahead. It’s the 20% who haven’t even seen it coming that concern me most.

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CMOs Are More Focused On Growing Revenue Than Brand Awareness https://lnkd.in/g8jyVmuY Chief marketing officers are increasingly prioritizing direct revenue outcomes over traditional brand awareness efforts, influenced by economic pressures, performance measurement demands, and AI‑enabled tracking. This shift reflects a need for more measurable impact on business performance, with revenue growth becoming a leading strategic metric for modern marketing leaders. #CMOInsights #RevenueGrowth #MarketingStrategy #BrandVsPerformance #BusinessImpact #DataDrivenMarketing

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Excited to share that Aperiam has invested in Bedrock Platform. Obvious statement of the century: programmatic advertising has a complexity problem. The infrastructure that was built to give media buyers control has, over time, done the opposite. Burying teams under layers of operational overhead, legacy tooling, and opaque supply chains. Bedrock is built on a simple but powerful thesis: what if you stripped away the bloat and rebuilt the stack around what actually matters... precision, transparency, and speed to execution. Their platform combines AI-driven campaign automation with curated, premium inventory across video, CTV, DOOH, and audio, and aims to be flexible and get smarter over time. Plus, the team (Shane, Austin, Ryan, James) has deep roots in the infrastructure layer of ad tech and understands the plumbing better than almost anyone. We believe the next generation of programmatic will be leaner, faster and AI-first. Bedrock is building that.

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Consumer app revenue is set to outpace gaming by 2026… but the monetization trends in this space matter for everyone. If I were building or marketing an app in entertainment, fintech, utilities or gaming, I’d 100% give this a read for some ideas to make extra $. My colleague Lya Krzyzanowski dives into key insights from 159B+ impressions on Liftoff’s Vungle Exchange: rewarded ads, high-value markets, and non-disruptive placements that drive revenue and retention. Check it out #AdTech #AppMonetization #ConsumerApps #GamingApps #Liftoff #GrowthStrategy

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See how agencies are shrinking time-to-insight from hours to minutes and delivering trusted outputs with full traceability. 👉 Watch this quick demo of Domino Data Lab Document Intelligence's power to transform mission-critical records, policies, reports and multi-modal data into auditable, operational insights at speed. 🎥 https://gag.gl/MfxQ0b

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Just read Quad’s piece on how in-store retail media networks (RMNs) are doing more than just “ads in aisles.” They’re becoming strategic conversion tools. Here are some of the key take-aways - with a twist of how this applies to what we do here at The Customer Club: ✅ Standout points & what they mean 1. “Address shoppers when they’re in the buying mood.” The notion: when your consumer is already in-store, with intent, you get a moment of truth. 👉 For us: this reinforces that SMS + digital offer moments / gamification (we do) should align with when the shopper is in the path-to-purchase. It’s not just push messaging — it’s timely and contextual. 2. “Strengthen brand visibility and loyalty.” The data: ~31.5% of shoppers will immediately buy a new product they just learned about in store. 👉 For CPG brands using our platform: digital offers / gamification + retail media can work hand-in-hand. 3. “Create flexible, fast-to-market campaigns.” Very relevant: in-store digital signage + RMNs allow shorter lead times and responsive activations. 👉 For our SaaS offering: we want to emphasize our agility to CPG marketers — from campaign launch to distribution using SMS + QR + retail-media integration. 4. “Influence impulse purchases.” ~70% of US shoppers report making unplanned purchases to some degree. 👉 Real opportunity: brands often focus only on “planned purchase” funnels. This shows that the in-store moment (supported by endemic advertising) offers incremental upside. For The Customer Club: SMS-triggered offers and gamification can catch that unplanned moment and could be a differentiator. 5. “Drive incremental store revenue.” An academic study found in-store displays, when optimally placed, increase store revenue by ~11%. 👉 Big number. Our CPG clients can link digital offer activations + in-store RMN ads -> the conversation moves from “drive awareness” to “drive measurable ROI” — something CFOs care about. https://lnkd.in/gizq6Rkq

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Personalization isn’t about channels or platforms. It’s about giving customers what they actually want. In this episode of Here’s the Deal, Daniella Harkins shares the marketer’s checklist for data activation, from unifying your data to optimizing campaigns in real time.

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MMM Analysts are often brilliant with data and statistics, but they can miss the nuances of how media is actually planned, bought, and optimized in the real world. On the other side, media planners and marketers understand channels and tactics deeply but may not have the data fluency to connect those decisions back to econometric models. The truth is, you cannot do great MMM without appreciating both sides. Media is not just another input in a dataset. How a channel is planned, the way budgets are phased, the impact of flighting, or the difference between GRPs and impressions - all of these details matter in how we build models and interpret results. Without that context, you risk building a technically sound model that doesn’t actually reflect the market reality. That’s when stakeholders lose trust, and the insights don’t stick. This is why, in building the MMM Academy, I wanted media to have its rightful place. We don’t just talk about regressions, lag curves, or variance explained. We connect those concepts to real media practices: - How campaigns are phased and why that affects model specification - The difference between always-on and burst strategies, and how they show up in the data - What planners look for when deciding budget allocation across channels - How new formats like retail media and connected TV should be thought of in an MMM framework For analysts, this means you’re not just crunching numbers, you’re learning how media decisions are actually made. For marketers and planners, it means you’re seeing how those decisions translate into measurable outcomes. At the MMM Academy, we believe that bridging this gap is essential. Because the best MMM analysts are not just statisticians - they’re also informed partners to marketers, able to interpret results in the language of media and business. That’s when the work moves from being a model on a slide to becoming a tool for confident, real-world decision-making. Learn more about our course here: https://lnkd.in/efYu7KtC

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CMO’s and agencies are so enamored with bottom-funnel targeting tactics that they totally lost the ability to move people effectively—their judgement is out of balance with real needs today. The targeting down funnel ‘disease’ gives marketers a feeling that they aren’t being wasteful but so much is showing they aren’t being effective either. “This ….reveals …a fundamental mismatch. Respondents are applying bottom-of-funnel tactics to what they've identified as top-of-funnel brand building objectives.”

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