Deeper Diligence

Daypart

Headlines move markets. Claims move businesses. We investigate both. Every episode breaks down the evidence behind the biggest stories in AI, advertising, ecommerce, and digital media, showing what can be verified, what can’t, and what everyone else missed.

Episodes

  1. 2d ago

    Understanding Attribution and Ad Fraud in 2026 with Dr. Fou

    Episode Notes Bogdan and co-host Digital Chatvertising interview Dr. Augustine Fou of Fou Analytics, a longtime digital marketer and ad-fraud researcher (ex‑McKinsey, American Express, Interpublic, Omnicom; PhD MIT), on why pixel attribution dominates because it’s easy and bundled with platforms, yet is oversimplistic and easily gamed. Fou explains better validation via holdout/“turn‑off” experiments (citing eBay’s paid-search test) to measure incremental impact using traffic and sales velocity, and recommends repeating on/off cycles for causal evidence. The discussion covers fraud seasonality spikes around budget deadlines (Q4, month/quarter ends) and in movie and political spending, how programmatic exchanges enabled fraud via fake sites and low-value apps, and why AI mainly lowers barriers rather than creating a new fraud wave. He details attribution gaming (e.g., footfall credit via mass device exposure) and advises reconciling platform-attributed conversions against real sales. Fou argues for evidence-based verification and transparent supporting data, contrasting legacy verification approaches, and offers common-sense ways to spot MFA sites. 00:00 Welcome and Introductions 01:27 Why Pixel Attribution Wins 04:25 Beyond Pixels Holdout Tests 07:01 Budget Pressure and Incrementality 08:57 Fraud Seasonality in Q4 11:51 Who Are the Bad Guys 16:24 Old Fraud Still Thrives 18:05 AI and Modern Fraud Tricks 20:01 How Attribution Gets Gamed 25:17 DIY Truth Checks for Nontechnical Teams 28:58 Turn Off Experiment Playbook 30:19 Verify Traffic and Vendor Claims 37:04 Spotting MFA Sites Fast 40:04 Wrap Up and Where to Reach Dr Fou This podcast is powered by Pinecast.

  2. Aug 3

    Decoding Attribution: A Deep Dive with Eric Tilbury

    Episode Notes In this episode of Deeper Diligence, Digital_Chadvertising and guest Eric Tilbury (VP of Programmatic & Solutions Engineering at Inuvo) break down how ad attribution works and why it often fails. They explain user-ID and pixel-based attribution, including view-through vs click-through conversions, and discuss alternative approaches like media mix modeling and incrementality testing (e.g., geo lift). The conversation covers how privacy changes (like Safari blocking third-party trackers) and cross-device behavior make deterministic attribution fragile, while black-box platforms and incentives to hit low CPA/ROAS can distort results. They discuss common gaming and fraud tactics such as ID bridging, affiliate and click manipulation, and bottom-funnel retargeting that captures outsized credit, leading to budget misallocation. Practical advice includes defining measurement strategy first, testing vendors, building in-house measurement protocols, and using transparency and independent verification to evaluate ad tech. 00:00 Welcome and Guest Intro 01:51 What Attribution Means 03:27 View Through vs Click Through 04:16 Pixels and Tracking Basics 05:43 Other Attribution Methods 07:50 When Attribution Breaks 08:59 Incrementality and MMM 11:50 Why Deterministic Misleads 14:39 Easy Button Incentives 18:42 Privacy and ID Limits 22:17 ID Bridging and Fraud 28:08 Retargeting Reality Check 31:42 CFO and Investor Playbook 33:36 Transparency and Vetting 35:26 Future of Measurement 37:03 Wrap Up and Where to Find Eric This podcast is powered by Pinecast.

  3. Jul 23

    The Google's Gamble: Liability and Control in AI-Driven Advertising

    Jeromy, Bogdan and Lee discuss Google integrating AI more deeply into its ad campaign workflow while changing terms so advertisers are liable for AI-generated mistakes, arguing Google gains control without responsibility and predicting potential lawsuits and backlash, especially from professional advertisers. They explore why Google may be pushing this, including internal incentives to grow YouTube advertiser counts, and argue better measurement tools for incremental lift would drive adoption more sustainably. The conversation shifts to an Australian dock workers’ union demanding a 28-hour workweek as automation and AI increase productivity, questioning whether claimed gains are real and where they actually occur. They then cover a Texas Tribune investigation into Texas data centers using permitting tactics for turbines and diesel generators, noting emissions tied to gas plants serving data centers and debating hype versus reality of build-outs. Finally, they discuss Apple reportedly considering acquiring Prism ML to run a compressed 27B-parameter model locally on iPhones, emphasizing privacy and potential market shifts if Apple executes. 00:00 Welcome and Introductions 01:08 Google Ads AI Liability 06:27 Why Google Pushes YouTube 09:20 Measuring CTV Lift Properly 12:09 Australia 28 Hour Workweek 13:14 AI Productivity Reality Check 21:28 Texas Data Centers Emissions 27:59 North Korea Linux Tangent 30:42 Apple Local AI Comeback 37:00 Wrap Up and Subscribe This podcast is powered by Pinecast.

  4. Jul 15

    Inside the Phia Affiliate Fraud Scandal: An Interview with Ben Edelman

    Episode Notes Ben Edelman on Phia’s Alleged Forced Clicks: How Shopping Plugins Commit Affiliate Fraud In a Deeper Diligence guest episode, ad-fraud researcher Ben Edelman discusses his investigation into Phia and the Bloomberg coverage alleging affiliate fraud through “forced clicks” and standdown-rule violations. Edelman explains the three-step affiliate marketing bargain (show link, user clicks, user buys) and how forced clicks skip the user click by using Phia’s iOS plugin to open an invisible tab that loads an affiliate link and closes it, positioning Phia as “last click” for commission—often costing merchants, and sometimes other affiliates like review publishers. He also describes standdown rules requiring shopping plugins to stay out of the way when another affiliate referred the user, and says Phia tracked competitor affiliate links yet did not stand down. Edelman questions Phia’s claim this behavior was a bug, cites past cases including eBay prosecutions and Honey-related evidence, and argues enforcement can deter fraud. 00:00 Welcome and Guest Intro 01:14 Ben Edelman Background 01:40 Why Phia Drew Attention 03:18 Cookie Stuffing vs Forced Clicks 04:14 Affiliate Marketing Basics 07:21 Networks and Incentives 09:40 Phia Forced Clicks Explained 12:34 Stand Down Rules Violations 14:31 Real World Harm Examples 17:09 Bug Claim and Intent 21:27 Past Major Fraud Cases 23:27 Honey Investigation Lessons 24:55 Stopping Fraud Systemically 27:02 Future Misconduct and Wrap Up 28:11 Closing Thanks and Contact This podcast is powered by Pinecast.

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Headlines move markets. Claims move businesses. We investigate both. Every episode breaks down the evidence behind the biggest stories in AI, advertising, ecommerce, and digital media, showing what can be verified, what can’t, and what everyone else missed.