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Lucas and Luna scrutinize the messy reality of marketing analytics—where attribution models break, vanity metrics mislead, and campaign data never tells a clean story. Each episode picks a single measurement problem: how last-touch attribution overvalues the final click, why multi-touch models introduce their own biases, or what happens when Facebook and Google report conflicting conversion numbers. Lucas brings the technical rigor—explaining lift studies, incrementality testing, and the statistical pitfalls of small sample sizes—while Luna keeps the conversation tethered to real campaign decisions: budget reallocation, creative testing, and the trade-off between precision and speed. Together they walk through actual brand case studies (from direct-to-consumer startups to enterprise SaaS), showing which metrics mattered, which ones were noise, and how the team eventually reconciled data with strategic judgment. This is not a podcast about marketing automation hacks or growth-hacking gimmicks; it is a podcast for the analyst or manager who stares at a dashboard every morning and needs to know: What is this number actually telling me? And when can I trust it enough to act?
Unknown Host hosts Marketing Analytics with Fexingo: Data, Attribution, and Measuring Campaign Performance.
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 re
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 cu
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 g
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 tr
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 ho
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 ge
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 abou
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 d
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
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
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,
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 Googl
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
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
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
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 causat
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 prod
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 reveal
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 continuo
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 co
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Marketing Analytics with Fexingo: Data, Attribution, and Measuring Campaign Performance is hosted by Unknown Host. The show is categorised under Business and has published 0 episodes.
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