Marketing Analytics with Fexingo: Data, Attribution, and Measuring Campaign Performance

Lucas and Luna unpack a 2025 study from Adalytics showing that ad blockers suppressed 18% of tracked impressions in a controlled test for a Fortune 500 retailer—yet attribution models still credited those blocked impressions for conversions. They explain why ad-block traffic creates phantom touchpoints, how last-click models overcredit paid search when organic actually drove the sale, and why clean-room data from The Trade Desk is now the gold standard for reconciling delivery logs. A concrete look at the gap between what your dashboard says and what really happened. #AdBlockers #AttributionBlindSpots #Adalytics #Fortune500Retailer #PhantomTouchpoints #LastClickLie #TheTradeDesk #CleanRoomData #DeliveryLogs #Impressions #Conversions #MarketingAnalytics #Podcast #FexingoBusiness #BusinessPodcast #DataReconciliation #PepsiStudy #AttributionModeling Keep every episode free: buymeacoffee.com/fexingo

In this episode of Marketing Analytics with Fexingo, Lucas and Luna dig into a hidden flaw in most attribution models: ad blockers. With an estimated 27% of US internet users running ad blockers in 2026, millions of impressions and clicks go unmeasured, leading to misattributed conversions and skewed channel performance. Lucas explains how ad blockers create a systematic blind spot—especially for display and social campaigns—while search and direct traffic get over-credited. They discuss a real-world case where a mid-market retailer saw display‘s attributed ROI jump 40% after implementing server-side tracking that bypassed ad blockers. Luna pushes back on the assumption that server-side tracking solves everything, noting privacy implications and the tension with Apple’s Intelligent Tracking Prevention. They close by arguing that marketers need to model the gap between observed and actual touchpoints, not just optimize what their tools can see. #AdBlockers #AttributionBlindSpots #ServerSideTracking #MarketingAnalytics #MeasuringCampaignPerformance #DisplayAdvertising #Privacy #AdFraud #DataQuality #MarketingROI #AttributionModeling #AppleITP #ConversionTracking #DigitalMarketing #Business #Marketing #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

In episode 59 of Marketing Analytics with Fexingo, hosts Lucas and Luna unpack a blind spot most attribution models share: platform effects. Lucas explains how ad platforms like Google and Meta optimize delivery based on their own models, creating a feedback loop that inflates performance metrics. He illustrates with a real example from a DTC brand that saw Meta attribute 60% of conversions to its ads, yet a controlled experiment showed only 30% incremental lift. The episode explores how platform bidding algorithms target users already likely to convert, how attribution models double-count overlapping audiences, and why incrementality testing is the only reliable check. Luna challenges Lucas on whether small teams can afford this rigor, and they discuss practical compromises like holdout groups and geo tests. The conversation includes a sincere listener-support pitch for buy me a coffee dot com slash fexingo. No hot takes, just a clear explanation of a structural problem in marketing measurement. #MarketingAnalytics #AttributionModeling #PlatformEffects #IncrementalityTesting #DTCBrand #MetaAds #GoogleAds #MarketingMeasurement #AdWaste #ConversionAttribution #BiddingAlgorithms #DataDrivenMarketing #MarketingROI #BusinessPodcast #FexingoBusiness #PodcastEpisode #MarketingInsights #Analytics Keep every episode free: buymeacoffee.com/fexingo

Episode 58 of Marketing Analytics with Fexingo dives into a hidden attribution flaw: brand search cannibalization. Lucas and Luna use the example of a $50 million e-commerce retailer to show how last-click models attribute conversions to brand search terms that were actually driven by TV or social ads. They walk through a simple incrementality test to reveal true brand search lift, and explain why running geo holdouts for 4-6 weeks can save 15-20% of wasted search spend. The episode ties back to the show's recurring theme: no single-touch attribution model tells the whole story. Tune in for a concrete framework you can apply to your own campaigns starting next week. #Attribution #BrandSearch #SearchCannibalization #IncrementalityTesting #MarketingAnalytics #PPC #PaidSearch #BrandLift #LastClick #MultiTouchAttribution #GeoExperiments #AdWaste #MarketingROI #DigitalMarketing #Ecommerce #FexingoBusiness #BusinessPodcast #Marketing Keep every episode free: buymeacoffee.com/fexingo

In this episode, Lucas and Luna dive into the hidden inefficiencies in digital advertising, using a real-world example from a mid-sized retailer that ran a three-week geo-based incrementality test. They reveal how the test showed that 40% of paid search spend was cannibalizing organic conversions, saving the company $200,000 annually. The discussion covers the mechanics of holdout groups, the pitfalls of last-click attribution, and why most marketers are wasting budget on ads that simply capture existing demand. Perfect for anyone tired of vanity metrics and ready to measure true campaign lift. #IncrementalityTesting #AdWaste #MarketingAnalytics #Attribution #PaidSearch #OrganicConversion #GeoExperiment #HoldoutGroup #MarketingROI #BudgetOptimization #DigitalMarketing #CampaignMeasurement #DataDriven #MarketingScience #RetailMarketing #Business #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna unpack a little-known measurement technique called ghost ads, which lets marketers isolate the true incremental impact of brand campaigns. They walk through how Procter & Gamble used ghost ads to uncover that nearly 30 percent of their digital brand spend was reaching people who would have bought anyway. The hosts explain the mechanics: serving a control group a public-service ad instead of the brand creative, then comparing conversion rates. They also discuss why ghost ads are harder to run on walled gardens like Meta and Amazon, and how the technique exposes inflated attribution numbers. If you work in marketing and want to stop wasting budget on campaigns that look good in a dashboard but don't actually move the needle, this episode is for you. #GhostAds #BrandCampaigns #IncrementalityTesting #ProcterAndGamble #MarketingAttribution #DigitalAdvertising #WalledGardens #Meta #AmazonAds #MarketingAnalytics #CampaignMeasurement #AdEffectiveness #ControlGroups #MarketingROI #FexingoBusiness #BusinessPodcast #Marketing #Analytics Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna dive into why incrementality testing is the only reliable way to measure true ad impact, using Amazon's 2021 shadow-ban experiment and Uber's 2024 geo-testing results as concrete examples. They explain how standard attribution models overcredit channels that merely appear coincident with conversions, while incrementality isolates the actual lift. They walk through the mechanics of a matched-market test, discuss the statistical power needed to detect small effects, and share how a mid-size DTC brand saved $2.3 million annually by cutting non-incremental spend. The episode ends with practical advice on when to invest in incrementality vs. when simpler heuristics suffice. Produced by the Fexingo Business podcast network. #IncrementalityTesting #MarketingAttribution #AdMeasurement #MarketingAnalytics #Amazon #Uber #DTCBrands #MatchedMarketTest #GeoTesting #AdLift #MarketingROI #AttributionModeling #MediaMixModeling #CampaignMeasurement #FexingoBusiness #BusinessPodcast #MarketingPodcast #DataDrivenMarketing Keep every episode free: buymeacoffee.com/fexingo

Episode 54 of Marketing Analytics with Fexingo. Lucas and Luna dive into why incrementality testing—running controlled experiments to measure true causal lift—is the gold standard for marketing ROI. They walk through a real case: how a DTC skincare brand used geo-based incrementality tests to discover that 40% of their Facebook ad conversions would have happened anyway. The hosts contrast this with the limitations of even the best multi-touch or media mix models. Listeners learn the difference between correlation and causation in attribution, and why a simple randomized test is often more reliable than a complex algorithm. The episode includes a brief listener-support moment around the 75% mark. #MarketingAnalytics #IncrementalityTesting #AttributionModel #CausalLift #MarketingROI #GeoExperiments #DTCBrand #FacebookAds #DataDrivenMarketing #Experimentation #CorrelationVsCausation #MarketingMeasurement #FexingoBusiness #BusinessPodcast #MarketingStrategy #PerformanceMarketing #Analytics #PaidMedia Keep every episode free: buymeacoffee.com/fexingo

In Episode 53 of Marketing Analytics with Fexingo, Lucas and Luna delve into why standalone attribution models miss critical saturation effects, using a real-world case of a D2C brand that wasted $2 million on over-served channels. They explain how integrating media mix models (MMM) with attribution reveals diminishing returns and budget reallocation opportunities. Listeners learn about the concept of saturation curves, the pitfalls of linear attribution, and a practical framework to combine MMM and attribution for smarter spend. No fluff—just a concrete example of a brand that cut Facebook spend by 30% and saw overall revenue grow 12%. #MarketingAnalytics #AttributionModeling #MediaMixModeling #MarketingROI #BudgetOptimization #SaturationCurves #D2CMarketing #PaidMedia #FacebookAds #GoogleAds #DataDrivenMarketing #MarketingMeasurement #Incrementality #FexingoBusiness #BusinessPodcast #DigitalMarketing #AdSpend #PerformanceMarketing Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna unpack why even the best multi-touch attribution models can't answer the fundamental question: did the ad cause the sale? Using a real-world case study from a D2C mattress company, they walk through how incrementality testing — comparing a test group exposed to ads against a holdout group — revealed that 40% of attributed conversions would have happened anyway. They discuss the operational challenges (cost, sample size, brand effects) and why incrementality is the closest thing marketing has to a randomized control trial. By the end, listeners understand why incrementality tests should be the foundation, not the afterthought, of any measurement stack. #IncrementalityTesting #MarketingMeasurement #Attribution #D2C #MattressCompany #HoldoutGroup #CampaignROI #MarketingAnalytics #ConversionTracking #AdEffectiveness #BrandAwareness #BaselineConversion #RandomizedControlTrial #MarketingBudget #DataDrivenMarketing #FexingoBusiness #BusinessPodcast #Marketing Keep every episode free: buymeacoffee.com/fexingo

Episode 51 of Marketing Analytics with Fexingo tackles a blind spot in modern attribution: the failure to integrate media mix models with multi-touch attribution. Lucas and Luna explore a real case from a mid-size CPG brand that ran both models in parallel for six months and found a 23% discrepancy in channel ROI estimates. They unpack why siloed models lead to conflicting budget recommendations, how a unified framework reconciles short-term attribution with long-term media effects, and what a 'hybrid' approach looks like in practice. Specific takeaways include the role of adstock decay rates, baseline sales decomposition, and why the CPG brand ultimately shifted 15% of its digital budget back to TV. No fluff, no jargon for its own sake—just a clear explanation of a structural problem that quietly undermines marketing ROI. If you've ever wondered why your attribution dashboard and your media mix model seem to tell different stories, this episode is for you. #MarketingAnalytics #AttributionModeling #MediaMixModeling #MarketingROI #CPGBrand #Adstock #MultiTouchAttribution #BudgetOptimization #DataIntegration #MarketingMeasurement #TVAdvertising #DigitalMarketing #MarketingScience #FexingoBusiness #BusinessPodcast #Marketing #Analytics #CampaignMeasurement Keep every episode free: buymeacoffee.com/fexingo

Episode 50 of Marketing Analytics with Fexingo. Lucas and Luna explore a blind spot in most multi-touch attribution models: they treat each marketing channel as if it has unlimited capacity to drive conversions. Using the case of a DTC skincare brand that saw cost-per-acquisition triple after scaling Facebook spend past a threshold, they explain why saturation points exist, how to detect them using marginal return curves, and what happens when your attribution model assigns credit to an already-saturated channel. They also discuss a practical fix: layering a saturation cap directly into the attribution logic so the model doesn't over-reward spend past the point of diminishing returns. If you manage a media budget or build attribution dashboards, this episode gives you one concrete diagnostic to check this week. #AttributionModels #ChannelSaturation #MarketingAnalytics #DiminishingReturns #FacebookAds #DTCBrands #MarginalROI #MediaMixModeling #AttributionBlindSpots #CostPerAcquisition #SaturationCurves #DigitalMarketing #MarketingROI #DataDrivenMarketing #AnalyticsBestPractices #Business #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Episode 49 of Marketing Analytics with Fexingo digs into a blind spot in most attribution models: paywall and registration-wall data. Lucas and Luna examine how the New York Times uses metered subscription analytics to measure content value far beyond clicks and scroll depth. They discuss why conversion-to-subscription metrics beat engagement proxies, how a paywall changes what you optimize for, and why free-to-paid conversion rate is the single healthiest KPI for premium publishers. The episode features a concrete comparison of walled vs. unwalled content performance and a quick look at how Spotify's freemium funnel parallels the approach. If you're building an attribution model for any business with a gated product or content, this episode offers a practical new metric to layer in. #PaywallAnalytics #ContentAttribution #NewYorkTimes #MeteredPaywall #SubscriptionMetrics #FreemiumFunnel #ConversionRate #ContentROI #MarketingAnalytics #AttributionModel #Spotify #PremiumPublishing #ReaderRevenue #DataDrivenMarketing #Marketing #Business #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Episode 48 of Marketing Analytics with Fexingo. Lucas and Luna dig into a neglected layer of campaign measurement: the data quality score. Most marketers trust their attribution numbers without auditing the raw feed. But one CPG brand found that 23% of their ad interactions were misattributed because of a simple UTM parameter typo. The hosts walk through how to build a data quality scorecard — checking for completeness, consistency, and freshness — and why a 95% score is often the threshold for reliable decision-making. They also discuss how far a little listener support goes at buy me a coffee dot com slash fexingo. #DataQuality #AttributionModel #MarketingAnalytics #UTMParameters #DataFeedAudit #CampaignMeasurement #CPGBrand #DataFreshness #MediaMixModel #MultiTouchAttribution #MarketingROI #DataGovernance #AdTech #AnalyticsScorecard #FexingoBusiness #BusinessPodcast #MarketingPodcast #Episode48 Keep every episode free: buymeacoffee.com/fexingo

In this episode, Lucas and Luna dive into the critical but often overlooked practice of data freshness monitoring in marketing attribution. They use the example of a mid-size e-commerce retailer whose attribution model broke because it was relying on stale conversion data. The hosts explain how latency in data pipelines—anywhere from 24 hours to a week—can lead to misallocated budgets and missed windows for campaign optimization. They discuss practical freshness thresholds, the role of data observability tools, and the specific metrics that alert teams to staleness before it distorts reporting. If you've ever wondered why your attribution dashboard seems off on Monday mornings, this episode gives you the framework to spot the rot before it spreads. #DataFreshnessMonitoring #MarketingAttribution #DataQuality #DataObservability #AttributionModeling #MarketingAnalytics #CampaignMeasurement #DataPipeline #MarketingMixModeling #ConversionData #DataLatency #AnalyticsWorkflow #EcommerceAnalytics #DataOps #MarketingROI #BusinessPodcast #FexingoBusiness #MarketingAnalyticsWithFexingo Keep every episode free: buymeacoffee.com/fexingo

Episode 46 of Marketing Analytics with Fexingo tackles a hidden killer of attribution accuracy: stale data. Lucas and Luna walk through a real case from a mid-market e-commerce brand whose last-click model showed email driving 40 percent of revenue — but the data feed was two weeks delayed on web sessions. They explain why data freshness matters more than model sophistication, how to set refresh SLAs, and why a 24-hour lag can inflate channel credit by 30 percent. The hosts also touch on listener-supported funding for the show, noting that a small group of supporters on buy me a coffee dot com slash fexingo keeps the podcast ad-free and independent. If your marketing analytics reports feel off but the math checks out, the problem might be how old your data is. #MarketingAnalytics #AttributionModeling #DataFreshness #LastClickAttribution #DataQuality #MarketingROI #CampaignMeasurement #ETLPipeline #DataLatency #MarketingData #FexingoBusiness #BusinessPodcast #DataDrivenMarketing #AttributionAccuracy #AnalyticsBestPractices #MarketingTechnology #DataFeedMonitoring #PerformanceMarketing Keep every episode free: buymeacoffee.com/fexingo

In this episode of Marketing Analytics with Fexingo, Lucas and Luna dive into a common pitfall in marketing mix modeling: failing to adjust for seasonality. Using the example of a mid-size e-commerce brand that saw a 20% sales lift in Q4 and wrongly attributed it to Facebook ads, they explain how naive models conflate seasonal demand with campaign effectiveness. Lucas walks through a concrete case where a simple additive seasonality factor saved the client $2 million in misallocated budget. They discuss practical ways to incorporate seasonality—through dummy variables, Fourier terms, or external data like retail calendars—and why ignoring it leads to inflated ROAS estimates. The hosts also touch on recent trends in marketing analytics, including Bayesian structural time series and the rise of automated seasonality detection tools. Tune in to learn how to spot seasonality blind spots in your own models and avoid costly attribution errors. #MarketingAnalytics #MarketingMixModeling #Seasonality #Attribution #ROAS #Bayesian #Ecommerce #DataScience #AdSpend #CampaignMeasurement #FexingoBusiness #BusinessPodcast #Marketing #Analytics #MediaMix #LucasAndLuna #Podcast #Episode45 Keep every episode free: buymeacoffee.com/fexingo

Episode 44 of Marketing Analytics with Fexingo dives into a persistent flaw in how most brands measure campaign performance: they treat attribution models as static. Lucas and Luna explain why Bayesian updating — a technique borrowed from data science — can make attribution far more accurate by continuously adjusting credit as new data comes in. They walk through a concrete example: a $2 million retail campaign where a last-click model and a time-decay model gave opposite recommendations, and how a simple Bayesian framework reconciled them. The episode also covers the practical implementation cost (often under $15,000 for a mid-size brand), the risk of overfitting when updating too frequently, and why the biggest barrier is usually organizational — not technical. Listeners learn one actionable principle: any attribution model that doesn't update with new data is already outdated the moment it's deployed. #BayesianUpdating #MarketingAttribution #MarketingAnalytics #DataScience #CampaignMeasurement #AttributionModel #MarketingROI #LastClick #TimeDecay #Incrementality #MarketingMixModel #AttributionModeling #FexingoBusiness #BusinessPodcast #Marketing #DataDrivenMarketing #RetailMarketing #BayesianInference Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna dig into a surprisingly common marketing analytics failure: attribution models that look sophisticated but are built on flawed data feeds. They use a real example from a mid-market DTC brand that spent six months optimizing toward a channel that, according to its own CRM, had never generated a single qualified lead. The episode walks through what a data feed quality audit actually looks like — field-level completeness checks, deduplication logic, timestamp alignment — and why most marketing teams skip it. Listeners learn a concrete protocol: start with the raw event stream before the model, not the model output. The hosts also touch on how this connects to the broader problem of garbage-in-garbage-out in marketing analytics, especially as teams adopt multi-touch models without verifying the underlying data pipeline. No abstract theory — just a practical, actionable walkthrough of one audit that saved a brand over $200,000 annually in misattributed spend. #MarketingAnalytics #AttributionModeling #DataQuality #FeedAudit #MarketingAnalyticsWithFexingo #DTCBrands #MarketingROI #DataPipeline #GarbageInGarbageOut #CampaignMeasurement #AdSpendOptimization #CRMAnalytics #MultiTouchAttribution #MarketingTechnology #BusinessPodcast #FexingoBusiness #Marketing #DataDrivenMarketing Keep every episode free: buymeacoffee.com/fexingo

Episode 42 of Marketing Analytics with Fexingo. Lucas and Luna unpack the single biggest blind spot in modern marketing measurement: budget cannibalization from channels that look effective in your attribution model but are actually stealing conversions from other touchpoints. Using a concrete example from a fictional DTC brand called 'Bloom & Spruce', they walk through how a last-click model can credit a retargeting display ad for a sale that was already guaranteed by an earlier email campaign — and how that misattribution can inflate retargeting spend by 40% while the email channel gets starved. They then explain why multi-touch models don't automatically fix the problem and what a simple 'what-if' scenario analysis can reveal about where your budget is actually going. No abstract theory here — the hosts simulate the math in real time, showing listeners exactly how to spot cannibalization in their own dashboards. They also touch on a listener question about whether view-through attribution makes the problem worse. Recorded June 10, 2026. #AttributionModel #BudgetCannibalization #LastClickAttribution #MultiTouchAttribution #ViewThroughAttribution #MarketingAnalytics #MarketingMeasurement #DTCBrand #DigitalMarketing #AdSpendOptimization #ConversionTracking #EmailMarketing #Retargeting #BloomAndSpruce #FexingoBusiness #BusinessPodcast #Marketing #DataDrivenMarketing Keep every episode free: buymeacoffee.com/fexingo

In episode 41 of Marketing Analytics with Fexingo, Lucas and Luna unpack why traditional marketing mix models fall short when data is sparse or campaigns change fast. They walk through a concrete example: a mid-size consumer goods brand that wasted $2 million on TV ads because its frequentist model couldn't handle seasonality shifts. Lucas explains how a Bayesian framework — updating probabilities as new data comes in — helped the brand reallocate 30 percent of its budget to digital within six weeks. Luna questions whether Bayesian methods are too complex for most marketing teams, and Lucas shares a practical compromise: start with weakly informative priors and a simple four-variable model. They also touch on the rising use of Bayesian hierarchical models for multi-market brands. No math PhD required — just a smarter way to update your marketing strategy week by week. #MarketingMixModel #BayesianStatistics #FrequentistStatistics #AdBudgetOptimization #MediaMixModeling #MarketingROI #AttributionModeling #DataDrivenMarketing #MarketingAnalytics #CampaignMeasurement #TVAdvertising #DigitalMarketing #Seasonality #MarketingBudget #HierarchicalModeling #MarketingScience #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Episode 40 digs into a blind spot in multi-touch attribution models: how they systematically undervalue early-funnel content like blog posts and educational videos. Lucas and Luna examine a case from a B2B SaaS company that ran a six-month experiment comparing last-click vs. multi-touch attribution for its content program. The result? Multi-touch credited the final demo request to the email sequence, but the actual decision path started with a blog post three months earlier—a touch that the model weighted at just 5 percent. The hosts walk through the specific decay curves and position-based weighting that cause this distortion, and discuss when to use time-decay models as a corrective. Listeners learn why content marketers should run their own attribution experiments rather than blindly trusting platform defaults. #MultiTouchAttribution #ContentMarketingROI #MarketingAnalytics #AttributionModeling #B2BSaaS #TimeDecayModel #PositionBasedWeighting #TouchpointWeighting #MarketingMeasurement #ContentAttribution #LastClickVsMultiTouch #FunnelAnalysis #AttributionBias #ROIMeasurement #MarketingExperimentation #FexingoBusiness #BusinessPodcast #Marketing Keep every episode free: buymeacoffee.com/fexingo

Episode 39 of Marketing Analytics with Fexingo. Lucas and Luna unpack the growing role of data clean rooms in marketing attribution. Using the 2025 privacy changes to Apple's SKAdNetwork and Google's Privacy Sandbox as a backdrop, they walk through how a clean room lets advertisers join first-party data with a publisher's data without sharing raw user IDs. They cite a case where a major retailer ran a clean-room attribution study and found that display ads drove 12 percent more incremental store visits than last-click models had shown. The hosts also explore the tension between privacy compliance and measurement accuracy, and how the rise of clean rooms is reshaping the vendor landscape. No hype, just the mechanics and the trade-offs. #MarketingAnalytics #DataCleanRoom #Attribution #PrivacySandbox #SKAdNetwork #FirstPartyData #AdMeasurement #Incrementality #Privacy #RetailMedia #DisplayAds #StoreVisits #MarketingROI #AdTech #DataPrivacy #FexingoBusiness #BusinessPodcast #Marketing Keep every episode free: buymeacoffee.com/fexingo

Episode 38 of Marketing Analytics with Fexingo. Lucas and Luna dig into geo-based incrementality testing — why running controlled experiments across geographic regions is the gold standard for measuring true ad lift. They break down a real example: how a national quick-service chain used city-level test-and-control markets to isolate the impact of a new digital campaign, uncovering that their multi-touch attribution model had overstated mobile display ROI by 40 percent. They explain the minimum viable setup: at least 20 matched DMAs, a 70-30 split, and four to six weeks of runtime. They also discuss common pitfalls like competitive spillover and seasonality bias. No clickbait, just practical analytics for marketers who want to stop guessing and start measuring. #GeoExperiments #IncrementalityTesting #MarketingAnalytics #Attribution #AdLift #TestAndControl #DMA #QuickServiceChain #MobileDisplay #ROI #MarketingMeasurement #DataDriven #CampaignMeasurement #FexingoBusiness #BusinessPodcast #Marketing #Analytics #ExperimentDesign Keep every episode free: buymeacoffee.com/fexingo

Most marketers still rely on last-click attribution, but it systematically undervalues upper-funnel channels. In this episode, Lucas and Luna break down a real-world case from a $200 million DTC brand that switched from last-click to a Bayesian marketing mix model. They explain why the switch revealed that TV and podcasts were driving 40% of incremental revenue — not the 8% last-click showed — and walk through the three biggest mistakes companies make when adopting MMM. If you've ever wondered why your attribution dashboard doesn't match your P&L, this episode gives you the concrete reasons and a practical framework for fixing it. #MarketingMixModeling #LastClickAttribution #DTCBrands #MarketingAnalytics #Incrementality #BayesianStatistics #TVAdvertising #PodcastAds #Attribution #MarketingROI #DataDrivenMarketing #MediaMixModel #Business #Finance #Marketing #FexingoBusiness #BusinessPodcast #Analytics Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna dig into the viewability metric that the entire digital ad industry relies on — and why it's often misleading. Using a real example from a $2 million programmatic campaign run by a midsize retailer, Lucas explains how the Interactive Advertising Bureau's standard of 50% pixels for 1 second can declare an ad 'viewable' even when no human is paying attention. They explore research from Google showing that only 8% of viewable display ads actually get seen by a human for more than a second, and discuss the gap between viewability and attention. Luna challenges whether viewability is still useful at all, and they land on the practical fix: layering eye-tracking based attention metrics or using 'active viewability' thresholds. The episode includes a donation segment tied to the show being ad-free, supported by listeners at buy me a coffee dot com slash fexingo. #AdViewability #Viewability #AttentionMetrics #ProgrammaticAdvertising #DigitalMarketing #IABStandards #GoogleResearch #DisplayAds #MarketingAnalytics #AdEffectiveness #Attribution #CampaignMeasurement #AdFraud #BrandSafety #EyeTracking #ActiveViewability #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Episode 35 of Marketing Analytics with Fexingo dives into the underappreciated power of ad frequency caps. Lucas and Luna explore how setting the right frequency limit can dramatically improve campaign ROI, reduce ad fatigue, and prevent brand harm. They walk through real data from a 2025 e-commerce case where capping frequency at three impressions per user per week lifted conversion rates by 18 percent while cutting wasted spend by 22 percent. They also discuss how frequency caps interact with attribution models, why overexposure can inflate last-click credit, and practical tips for setting frequency limits across channels like social, display, and video. If you've ever wondered why showing an ad too often can backfire, this episode has the numbers and strategy you need. #AdFrequencyCaps #MarketingAnalytics #CampaignROI #AdFatigue #FrequencyManagement #AttributionModels #DigitalAdvertising #MediaPlanning #ConversionOptimization #WastedAdSpend #EcommerceMarketing #SocialMediaAds #DisplayAdvertising #VideoAdvertising #BrandSafety #DataDrivenMarketing #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Episode 34 of Marketing Analytics with Fexingo dives into a common but dangerous pitfall: multi-touch attribution models that look sophisticated but actually misallocate credit and inflate ROI. Lucas and Luna unpack a real-world example from a DTC brand that saw a 40% discrepancy between its attribution model and a simple holdout test. They explain why last-click models often outperform MTA in volatile channels, how to sanity-check your model with incrementality data, and why attributing fractional credit to every touch can make your P&L look better than it really is. If you're a marketer, analyst, or founder relying on attribution to make budget decisions, this episode gives you the questions to ask before you trust the numbers. #MultiTouchAttribution #MarketingAnalytics #P&L #AttributionModel #LastClick #IncrementalityTesting #HoldoutTest #DTC #MarketingROI #DataDriven #FractionalCredit #CampaignPerformance #Business #Marketing #FexingoBusiness #BusinessPodcast #MarketingPodcast #Analytics Keep every episode free: buymeacoffee.com/fexingo

In this episode, Lucas and Luna dive into how multi-touch attribution directly affects a company's profit and loss statement. They explore a real case from a mid-size e-commerce brand that shifted from last-click to a custom weighted attribution model, resulting in a 15% increase in return on ad spend over six months. The hosts break down why attribution is more than just a reporting tool—it's a financial lever. Lucas explains the concept of diminishing returns on channel spend and how proper attribution reveals which channels are truly driving incremental profit. Luna challenges the notion that all attribution models are equally valid, pointing out that many overlook offline influence and customer journey complexity. They discuss the importance of aligning attribution with unit economics and how even a simple model can beat no model at all. The episode hits on the practical trade-offs between accuracy and simplicity, and why marketers should think like CFOs. Listeners walk away with a concrete understanding of how attribution decisions ripple through the P&L, and a framework for evaluating their own approach. #MarketingAnalytics #MultiTouchAttribution #MarketingROI #ProfitAndLoss #AttributionModeling #LastClick #IncrementalProfit #UnitEconomics #EcommerceMarketing #AdSpendOptimization #DataDrivenMarketing #MarketingFinance #ChannelAttribution #MarketingMeasurement #BusinessPodcast #FexingoBusiness #AttributionWins #MarketingTechnology Keep every episode free: buymeacoffee.com/fexingo

Episode 32 of Marketing Analytics with Fexingo dives into a foundational flaw in many attribution models: the lack of a true control group. Lucas and Luna examine how Unilever's 2023 ice cream campaign in Brazil used a geo-based holdout to prove that their digital spend drove only 12% incremental lift, not the 35% their last-click model claimed. They walk through the mechanics of matched-market experiments, the minimum sample size for statistical significance, and why a control group is the only way to separate correlation from causation. If you've ever wondered why your attribution dashboard shows a high ROAS but your revenue flatlines, this episode gives you the diagnostic tools to find the gap. Listeners learn one concrete number: a properly designed control group can cut attributed conversions by 20 to 50 percent on average, revealing which channels actually move the needle. #MarketingAnalytics #Attribution #ControlGroup #Incrementality #Unilever #GeoHoldout #CausalInference #A_BTesting #MarketingROI #LastClick #DataDriven #CampaignMeasurement #HoldingOut #StatisticallySignificant #Marketing #BusinessPodcast #FexingoBusiness #AttributionModel Keep every episode free: buymeacoffee.com/fexingo

Most marketing teams still judge ad performance by last-click attribution — and they're overpaying by billions. In this episode, Lucas and Luna break down why incrementality testing is the only reliable way to measure true ad lift, using a real case from a major retailer that ran a geo-level experiment and discovered 40% of its digital spend was wasted. They explain the difference between 'was this ad seen?' and 'did this ad cause a sale?' — and why brands like Procter & Gamble have already shifted billions into incrementality-based measurement. If your marketing analytics stack doesn't include a holdout group, this episode is your wake-up call. #IncrementalityTesting #MarketingAnalytics #AdSpend #Attribution #LiftMeasurement #GeoTesting #HoldoutGroups #DigitalMarketing #ROI #PPC #MediaMix #ProcterAndGamble #MarketingMeasurement #DataDrivenMarketing #AdFraud #MarketingROI #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna dig into a 2026 meta-analysis of 147 brand lift studies that found creative quality accounts for nearly 60 percent of ad effectiveness — double the contribution of targeting precision. They walk through how Unilever ran a controlled experiment pitting two different creatives against identical audience segments and got a 3X lift difference, then discuss why most marketing analytics teams still allocate 80 percent of their optimization budget to audience selection rather than creative testing. The episode covers practical ways to bake creative testing into media mix models and why platforms like Meta are now offering Creative Lift APIs. If you have ever wondered why your perfectly targeted campaign underperformed, this one is for you. #AdCreative #BrandLift #MarketingAnalytics #CreativeTesting #Unilever #MediaMixModeling #Attribution #CampaignOptimization #Meta #Incrementality #DigitalMarketing #AdEffectiveness #MarketingROI #Business #FexingoBusiness #BusinessPodcast #Podcast #Marketing Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna explore how marketing analytics teams routinely confuse correlation with causation—and why it costs millions in wasted ad spend. They unpack a 2025 experiment from a mid-size e-commerce brand that ran a geo-lift test on its highest-performing Facebook ads. The ads looked brilliant in the attribution dashboard: 12x return on ad spend. But the geo test revealed the campaign drove zero incremental revenue; buyers were converting anyway through organic search. The hosts explain why attribution models blind you to counterfactual reality, the difference between incremental and absolute lift, and how a simple holdout structure can save your budget. They also discuss what happens when machine learning optimization algorithms optimize for spurious correlations. This is episode 29 of Marketing Analytics with Fexingo: Data, Attribution, and Measuring Campaign Performance. #MarketingAnalytics #CorrelationVsCausation #GeoTesting #Incrementality #AttributionFailure #AdSpendWaste #HoldoutGroups #Counterfactual #CausalInference #FacebookAds #Ecommerce #MachineLearningBias #ROIMyth #AttributionModel #LiftTest #Business #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Episode 28 of Marketing Analytics with Fexingo. Lucas and Luna dive into a common headache: what happens when your multi-touch attribution model and your marketing mix model give you completely contradictory answers about which channel drove a sale. They walk through a real case—a mid-size e-commerce brand that saw a 30% gap between MTA and MMM on paid search—and discuss why this isn't a bug but a feature of the two methodologies. The hosts explain how different data sources, time horizons, and assumptions create the conflict, and why the smartest teams learn to triangulate rather than pick a winner. They also share a practical framework: use MTA for tactical optimization within channels, and MMM for strategic budget allocation across channels. Expect numbers, channel details, and a healthy dose of humility about what models can and can't tell you. #MarketingAnalytics #Attribution #MediaMixModel #MultiTouchAttribution #PaidSearch #Ecommerce #DataScience #Measurement #CampaignPerformance #MarketingROI #ChannelOptimization #BudgetAllocation #MarketingStrategy #FexingoBusiness #BusinessPodcast #Marketing #Analytics #Podcast Keep every episode free: buymeacoffee.com/fexingo

Episode 27 of Marketing Analytics with Fexingo. Lucas and Luna dive into survival analysis — a technique borrowed from medical research — and why it outperforms traditional lead scoring for B2B sales cycles. They break down a real example: a SaaS company that used Kaplan-Meier curves to discover that leads who attended a demo within 7 days had a 34% higher conversion probability than those who waited longer. The hosts explain how hazard functions and censored data reveal which marketing touches actually accelerate deals, and why most CRM-based lead scoring models miss the timing dimension entirely. #SurvivalAnalysis #LeadScoring #B2BMarketing #KaplanMeier #HazardFunction #CensoredData #MarketingAnalytics #ConversionRate #SaaS #CRM #MarketingMeasurement #Attribution #DataScience #FexingoBusiness #BusinessPodcast #Marketing #Analytics #LeadConversion Keep every episode free: buymeacoffee.com/fexingo

In this episode, Lucas and Luna explore why cross-validation is a missing ingredient in many marketing attribution and media mix models. They walk through a concrete example: a DTC brand that trusted its default model's ROAS estimates, only to discover the model overfit to a noisy holiday period. When the brand ran a simple k-fold cross-validation, it found the model's predictions were 30% less reliable than advertised. The hosts explain how cross-validation works, why it's rarely used in marketing analytics, and how it can prevent budget misallocations. They also touch on the trade-off between model complexity and generalizability, and why a model that looks great on training data can fail in the real world. No math overload — just a practical case for making models robust before betting the marketing budget on them. #CrossValidation #MarketingModels #Attribution #MediaMixModeling #ROAS #DataScience #MarketingAnalytics #FexingoBusiness #BusinessPodcast #DTCBrand #ModelValidation #Overfitting #KfoldValidation #MarketingROI #CampaignMeasurement #DataDrivenMarketing #MarketingOptimization #AnalyticsBestPractices Keep every episode free: buymeacoffee.com/fexingo

Episode 25 of Marketing Analytics with Fexingo dives into incrementality testing — the gold standard for measuring whether an ad actually causes a sale or just captures one that would have happened anyway. Lucas and Luna walk through a real 2025 case from a DTC apparel brand that ran a geo-based incrementality test across Facebook, Google, and TV. They explain why last-click and even multi-touch models overstate performance by 30-50%, how randomized control groups work in practice, and why major advertisers like Procter & Gamble and Uber have pushed incrementality from academic curiosity to boardroom necessity. No jargon, no fluff — just a clear breakdown of what incrementality is, when it's worth the cost, and why your attribution model is probably lying to you. #IncrementalityTesting #MarketingAnalytics #AdAttribution #Measurement #DTCBrands #ProcterAndGamble #Uber #FacebookAds #GoogleAds #TVAdvertising #GeoTesting #HoldoutGroups #MarketingROI #AttributionLies #FexingoBusiness #BusinessPodcast #Marketing #DataDriven Keep every episode free: buymeacoffee.com/fexingo

In this episode, Lucas and Luna dive into the practical use of holdout groups to validate multi-touch attribution models. Using a real-world case from a mid-market e-commerce brand that ran a six-month geo holdout test, they explore how withholding a portion of the market from advertising reveals true incrementality. Lucas explains why most attribution models overstate performance by 30-50% and how holdout groups expose the gap. The conversation covers experimental design, statistical power, common pitfalls like selection bias, and when holdout testing beats MMM or lift studies. Luna challenges the cost and ROI of running holdouts, and they discuss how even small brands can implement them at low cost. The episode closes with a forward-looking question about whether holdout groups will become standard for budget allocation. #HoldoutGroups #MarketingAttribution #Incrementality #MultiTouchAttribution #AdEffectiveness #ExperimentalDesign #GeoHoldout #StatisticalPower #MarketingROI #MarketingAnalytics #CampaignMeasurement #ABTesting #MediaMixModeling #BrandLift #MarketingScience #Ecommerce #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

In this episode, Lucas and Luna dive into the difference between incrementality testing and correlation-based attribution. Lucas explains how the rise of privacy changes — like Apple's App Tracking Transparency and Google's deprecation of third-party cookies — has made traditional last-click and multi-touch models unreliable. He shares a concrete example from a DTC brand that ran a geo-based incrementality test and discovered that their Facebook ads were actually not driving incremental sales. Luna pushes back on the cost and complexity of these tests, and Lucas walks through how a simple holdout group design can work for a $5 million ad budget. They discuss why more sophisticated advertisers are moving toward controlled experiments, and how even small brands can use matched-market tests or ghost-ads methodology. The episode closes with a forward-looking question about whether agency business models can survive when clients demand proof of incrementality. #IncrementalityTesting #MarketingAttribution #AdEffectiveness #PrivacyChanges #GeoBasedTesting #HoldoutGroups #GhostAds #ControlledExperiments #DTCAdvertising #FacebookAds #AppTrackingTransparency #CookieDeprecation #MarketingAnalytics #Marketing #Business #FexingoBusiness #BusinessPodcast #DataDrivenMarketing Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna explore the hidden interactions between marketing channels that standard attribution models miss. Using a real example from a direct-to-consumer brand that ran TV and paid search simultaneously, they show how media mix models can reveal that search was stealing credit from TV, and how adjusting the budget allocation boosted overall ROAS by 18%. They discuss why simple additive models fail, how Bayesian priors help with sparse data, and why the synergy effect is often larger than the direct effect. The episode also touches on how Amazon and Procter & Gamble use these insights to optimize cross-channel budgets. Perfect for marketers who want to move beyond last-click and understand the true interplay of their campaigns. #MediaMixModeling #ChannelSynergies #MarketingAttribution #CrossChannelMarketing #BayesianStatistics #MarketingAnalytics #DTCBrands #PaidSearch #TVAdvertising #BudgetOptimization #ROAS #MarketingROI #AdEffectiveness #MarketingScience #AttributionModeling #BusinessPodcast #FexingoBusiness #Marketing Keep every episode free: buymeacoffee.com/fexingo

Episode 21 of Marketing Analytics with Fexingo digs into why ignoring last year’s data can break your media mix model. Lucas and Luna explore a 2024 case from a mid-sized DTC brand—let’s call it FreshStep—that ran a full MMM without a 2023 baseline. The result? It over-credited social video by 22% and under-credited search by 15%, leading to a $340,000 misallocation in Q1 2025 alone. They walk through how Bayesian priors from prior-year data would have caught the error, why many teams skip this step, and what it means for your 2026 planning cycle. Packed with real numbers and a clear takeaway: your model is only as good as the history you feed it. Perfect for marketers, analysts, and anyone building or buying attribution tools. #MarketingAnalytics #MediaMixModel #MMM #BayesianStatistics #PriorYearBaseline #Attribution #DTCBrand #MarketingBudget #AdSpend #SocialVideo #SearchMarketing #DataScience #MarketingROI #CampaignMeasurement #2026Marketing #MarketingPodcast #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

In this episode, Lucas and Luna challenge the obsession with direct response attribution for podcast advertising. They examine a case study from a DTC mattress company that ran 12 weeks of podcast ads and found zero last-click conversions but a 14% lift in branded search and a 9-point increase in purchase intent according to a brand lift study. They discuss why podcast ads operate more like traditional broadcast media than digital display, how brand lift studies measure true ad effectiveness, and why relying solely on attribution codes or promo codes can lead to false negatives. The conversation covers the methodology of brand lift studies with holdout groups, the problem of survey fatigue, and how to combine lift studies with incrementality tests for a complete picture. By the end, listeners understand why brand lift studies are essential for any channel where the impact is delayed, emotional, or indirect, and how to design one that produces reliable results. #MarketingAnalytics #BrandLiftStudies #PodcastAdvertising #Attribution #DTC #DirectResponse #MarketingMeasurement #Incrementality #HoldoutGroups #BrandedSearch #PurchaseIntent #MediaMixModeling #SurveyMethodology #PodcastMarketing #AdEffectiveness #Marketing #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Episode 19 of Marketing Analytics with Fexingo. Lucas and Luna break down how brand lift studies work, why they're the gold standard for measuring ad effectiveness, and how companies like Netflix use them to prove causation, not just correlation. They walk through a real 2025 case where a CPG brand ran a geo-based brand lift test on a new snack launch, revealing a 12% lift in purchase intent that their click-based attribution model had completely missed. The hosts discuss survey design, control vs. exposed groups, and how to avoid common pitfalls like survey fatigue and priming bias. Plus: why brand lift studies are becoming essential as third-party cookies fade and walled gardens tighten. A focused, practical episode for marketers who need to justify brand spend with actual data. #BrandLift #AdEffectiveness #MarketingAnalytics #Attribution #Netflix #CPG #GeoTest #SurveyDesign #Causation #ControlGroup #ExposedGroup #PurchaseIntent #ThirdPartyCookies #WalledGardens #Marketing #Business #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Episode 18 of Marketing Analytics with Fexingo dives into the critical but often overlooked step of calibrating media mix models against real-world experiments. Lucas and Luna explore why even sophisticated MMMs can produce misleading results without calibration, using the example of a DTC brand that ran a geo lift test only to discover their model had over-allocated 25% of budget to paid search. They discuss common calibration methods—geo lifts, on-off tests, and incrementality experiments—and explain why calibration isn't a one-time fix but a continuous process. If you're using MMM to guide budget decisions, this episode will help you spot when your model is lying to you. #MediaMixModeling #MarketingAnalytics #Calibration #GeoLiftTest #Incrementality #BudgetAllocation #DTCBrand #PaidSearch #MarketingROI #DataScience #Attribution #Experimentation #MarketingStrategy #Business #Marketing #FexingoBusiness #BusinessPodcast #LucasAndLuna Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna dig into geo lift testing — the overlooked sibling of incrementality measurement. Using a real 2024 case from a national quick-service chain, they explain why splitting test and control by geography reveals true ad effectiveness that user-level attribution misses. You'll learn how geo experiments solve the 'leaky bucket' problem of digital attribution, why Facebook and Google can't run them for you, and what it takes to design a valid geo test. Plus: the hosts discuss why the chain's national TV campaign looked like a failure in last-click but drove a measurable 4.3 percent store-visit lift in test DMAs. No jargon, no fluff — just the concrete mechanics of geo lift and why it's becoming a must-have tool for marketing analytics teams. #GeoLift #Incrementality #MarketingAnalytics #Attribution #MarketingMixModeling #AdEffectiveness #QuickServiceRestaurant #TVAdvertising #DigitalAds #FacebookAds #GoogleAds #StoreVisits #DMA #ExperimentDesign #Counterfactual #BudgetOptimization #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Episode 16 of Marketing Analytics with Fexingo digs into Amazon's unique approach to marketing mix modeling. While most brands treat MMM as a top-down budget allocation tool applied annually, Amazon runs it as a continuous, channel-level optimization loop — updating models weekly and feeding results directly into programmatic bidding algorithms. Lucas and Luna break down the structural reasons behind this difference: Amazon's closed-loop attribution from ad impression to purchase, its ability to isolate incremental sales through controlled experiments, and the sheer scale of data that makes granular MMM viable. They walk through a concrete example of how a mid-market brand tried to replicate Amazon's approach and why it backfired — because their data wasn't granular enough and their business had too many offline sales. The episode closes with a practical rule of thumb: if you can't measure at least 80 percent of your conversions in a deterministic way, don't bother with weekly MMM updates. This is a fresh take on a classic marketing analytics model, grounded in the reality of how the world's biggest advertiser actually operates. #MarketingAnalytics #MarketingMixModeling #Amazon #AdvertisingStrategy #DataDrivenMarketing #Attribution #Incrementality #BudgetOptimization #ClosedLoopAttribution #ProgrammaticBidding #RetailMedia #EcommerceMarketing #Business #FexingoBusiness #BusinessPodcast #LucasAndLuna #Analytics #DigitalMarketing Keep every episode free: buymeacoffee.com/fexingo

Episode 15 of Marketing Analytics with Fexingo tackles the problem of sparse data in marketing attribution. Lucas and Luna explore how a Bayesian prior — starting with a baseline assumption — can stabilize models when conversion events are rare. They walk through a concrete example: a B2B SaaS company with a long sales cycle and only a handful of closed-won deals per quarter. The hosts explain how a non-informative prior acts as a smoothing mechanism, preventing overfitting and making multi-touch attribution models more reliable. They also discuss the practical trade-off — how a strong prior can mask real changes in channel performance. The episode includes a brief, organic mention of listener support via buymeacoffee.com/fexingo. No fluff, just a focused look at a statistical concept that directly improves campaign measurement. #BayesianStatistics #MarketingAttribution #DataScience #MarketingAnalytics #B2BSaaS #ConversionModeling #PriorDistribution #SparseData #MultiTouchAttribution #CampaignMeasurement #Probability #LongSalesCycle #StatisticalModeling #FexingoBusiness #BusinessPodcast #Marketing #Analytics #Podcast Keep every episode free: buymeacoffee.com/fexingo

Episode 14 of Marketing Analytics with Fexingo digs into a blind spot most attribution models miss: interaction effects between marketing channels. Lucas and Luna explore a real-world example where a brand's paid search ads only worked because of a podcast campaign running at the same time — and how a marketing mix model with interaction terms caught what last-click and multi-touch attribution completely missed. They walk through the math behind interaction effects (with clear, non-technical language), discuss what happens when you optimize channels independently, and explain why leading marketers now build 'synergy budgets' rather than siloed channel budgets. Specific references include a 2025 case from a mid-market DTC brand that shifted 30% of its budget after a mix model revealed a 2.4x multiplier between display and email. Recorded May 27, 2026. #MarketingAnalytics #Attribution #MarketingMixModel #MMM #ChannelInteractions #SynergyEffects #PaidSearch #PodcastAdvertising #DisplayAdvertising #EmailMarketing #DataDrivenMarketing #BudgetOptimization #ROI #DTCBrands #MarketingROI #FexingoBusiness #BusinessPodcast #Marketing Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna explore why traditional attribution models—even multi-touch—fail to answer the most critical question in marketing analytics: what would have happened if you hadn't run that campaign at all? They dive into the concept of counterfactual reasoning, using concrete examples from e-commerce and B2B SaaS. Lucas explains how companies like Amazon and Booking.com use holdout groups and synthetic control methods to isolate true campaign incrementality. The episode breaks down the difference between correlation and causation in marketing data, and why relying on attribution alone can lead to budget misallocation. Listeners learn one practical framework for building counterfactual tests into their own measurement stack—without needing a PhD in statistics. Perfect for marketers and analysts tired of attribution models that overcredit channels and underdeliver insights. #MarketingAnalytics #AttributionModeling #Counterfactuals #IncrementalityTesting #MarketingMeasurement #CampaignAnalytics #DataDrivenMarketing #CausalInference #HoldoutGroups #SyntheticControl #Amazon #BookingCom #B2BSaaS #EcommerceAnalytics #ROIMeasurement #Business #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo

Lucas and Luna explain why holdout groups—control groups that receive zero ad exposure—are the missing piece in most marketing attribution setups. They walk through a real example from a DTC skincare brand that ran a six-week geo-holdout test and discovered its Facebook campaigns were actually cannibalizing organic sales. The episode covers how holdout groups differ from incrementality testing, the minimum sample sizes required for statistical significance, and why most brands refuse to run them because they 'can't afford to not spend.' Listeners learn one concrete method to validate their attribution numbers without waiting for a full marketing mix model rebuild. #MarketingAnalytics #Attribution #HoldoutGroups #Incrementality #GeoTesting #AdEffectiveness #Measurement #DTC #FacebookAds #MarketingROI #DataDrivenMarketing #CampaignMeasurement #StatisticalSignificance #ControlGroup #MarketingScience #FexingoBusiness #BusinessPodcast #Marketing Keep every episode free: buymeacoffee.com/fexingo