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Igor Ivitskiy

Manchester, United Kingdom

Igor Ivitskiy is a PhD mathematician who applies optimization science to advertising and AI-marketing to find real profit. Known as "The Google Ads Scientist," he brings a mathematical-modeling foundation to high-spend Google and YouTube Ads.
He is ranked #6 in the Top 50 Most Influential PPC Experts 2026 (The PPC Survey) — the only Ukrainian in the global top 10. His research output spans 200+ scientific publications, 3 monographs, and 50+ patents. He is the author of a book on Google advertising published in three languages and a #1 New Release on Amazon US.
Recognized by the UK government as one of 3,000 Exceptional Global Talents, he holds business education from the University of Cambridge (UK) and UC Berkeley's Haas School of Business (US). He is a keynote speaker and conference chair at international scientific and marketing conferences, founder and Chief Scientist of Doctor Ads (UK), and creator of the Profit Forensics methodology and the M.A.T.H. Framework.

Igor Ivitskiy Points
Academic 50
Author 80
Influencer 0
Speaker 5
Entrepreneur 45
Total 180

Points based upon Thinkers360 patent-pending algorithm.

Thought Leader Profile

Portfolio Mix

Company Information

Areas of Expertise

Agentic AI
AI 31.93
Analytics 32.21
Entrepreneurship
Generative AI
Marketing 30.89
Predictive Analytics

Industry Experience

Cross Industry
High Tech & Electronics
Higher Education & Research
Professional Services
Retail

Publications & Experience

20 Article/Blogs
The Heuristic Ceiling: A Performance Bound Effort Cannot Break
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July 06, 2026
Why past a certain point extra effort on a Google Ads account stops producing profit, framed as a mathematical performance bound.

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The Linear-Exponential Gap: Why Ad Decisions Now Outpace Human Reaction
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June 29, 2026
Automated bidding moves at exponential speed while human review stays linear, and what that gap means for advertisers.

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Profit Forensics: From Academic Framework to Diagnostic
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June 22, 2026
The Profit Forensics method for auditing where ad budgets actually leak, moved from theory to a working diagnostic.

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The ROAS Fallacy: Why Average Returns Mislead Scaling
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June 15, 2026
Average ROAS hides the marginal math that actually governs whether scaling adds or destroys profit.

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The Correlation Trap: Pearl's Adjustment Formula for Marketing
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June 08, 2026
Applying causal inference and Pearl's adjustment to separate real ad effects from correlation artifacts.

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Marketing Physics: Treating Ad Markets as Systems
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June 01, 2026
A physicist's-eye view of ad auctions as dynamic systems with measurable limits and forces.

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The GIGO Principle Formalized: Why Data Quality Bounds Results
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May 25, 2026
A formal bound showing how conversion-data quality caps what any optimization can achieve.

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The Black Box Paradox: Optimizing Against an Untrusted Oracle
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May 18, 2026
How to make decisions when the platform's automation is a black box you cannot fully trust.

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Stop Trusting Google's Defaults: A First-Principles Guide
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May 11, 2026
A first-principles walk through the Google Ads defaults that quietly cost advertisers money.

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Beyond the Critical Threshold: When Intuition Stops Working
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May 04, 2026
The account scale past which human intuition breaks and only explicit models keep working.

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Cognitive Hygiene: Pre-Registration and Adversarial Review
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April 27, 2026
Borrowing pre-registration and adversarial review from science to keep marketing decisions honest.

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Cycle Velocity: The Compounding Math of Optimization
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April 20, 2026
Why the speed of your optimization loop compounds and often matters more than any single change.

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The Diffraction Limit of Marketing Measurement
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April 13, 2026
There is a resolution limit below which marketing measurement cannot distinguish signal from noise.

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The Illusion of Precision: Why Modeled Conversions Distort
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April 06, 2026
Modeled conversions look precise and can systematically distort the decisions built on them.

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The M.A.T.H. Framework: A Recursive Loop for Quant Marketing
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March 30, 2026
The M.A.T.H. Framework as a recursive loop for running quantitative marketing under noise.

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Observational Collapse: The Vanishing Conversion Funnel
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March 23, 2026
How privacy changes collapse the observable funnel and what advertisers can still measure.

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Pausing PerformanceMax Rarely Dents Conversions
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March 16, 2026
A data look at what actually happens to total conversions when PerformanceMax is paused.

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The Complete Guide to Google Ads Bid Adjustments
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March 09, 2026
A data-driven guide to device, location, audience and schedule bid adjustments in Google Ads.

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Google Ads Target CPA Bidding: A Data-Driven Analysis
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March 02, 2026
How Target CPA bidding really behaves across accounts and where it lands versus its promise.

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Mastering Google Ads Portfolio Bid Strategies
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February 23, 2026
A definitive guide to portfolio bid strategies and when they help or hurt performance.

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1 Book
19 Google Ads Secrets
Amazon
May 01, 2023

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Tags: AI, Marketing

1 Industry Award
#6, Top 50 Most Influential PPC Experts 2026
The PPC Survey (ppcsurvey.com)
April 01, 2026

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Tags: Marketing

1 Patent
Portfolio of 50+ patents (computational methods, mathematical modeling)
Google Patents / Ukrainian Patent Office
July 01, 2019

Patent Number UA109870U

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Tags: AI

1 PhD Degree
PhD in Mathematical Modeling (Computational Methods)
Igor Sikorsky Kyiv Polytechnic Institute
June 26, 2016

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Tags: AI, Analytics

1 Speaker Award
Europe's Best PPC Case (PPC Caesars Award), Adworld Experience
Adworld Experience
October 02, 2024

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Tags: Marketing

Thinkers360 Credentials

1 Badge

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Igor Ivitskiy


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