What Topics and Frameworks Does Avinash Kaushik Cover on kaushik.net?

kaushik.net is Avinash Kaushik's blog, Occam's Razor, covering marketing, analytics, strategy, measurement, experimentation, and AI. It is written for practitioners who want practical frameworks rather than news summaries — the kind of material you read when you need to decide what to measure, how to structure a test, or how to argue for better analytics practice inside an organization. The site organizes its work into four recurring areas: Analytics, Marketing Models & Frameworks, Strategic Thinking, and Leadership.

Analytics: making data actionable

The analytics content centers on turning raw reporting into decisions. Recurring themes include actionable web analytics, digital analytics, key performance indicators, and the difference between statistical certainty and actually answering a business question.

A representative post, "Google's Statistics: Heads They Win, Tails You Lose," examines Google Brand Lift and Conversion Lift studies. The argument is that both rely on the same underlying idea of statistical certainty, but certainty is not the same thing as answering the question you care about. That distinction — measurement confidence versus decision relevance — runs through much of the analytics writing.

Another post, "Google Analytics 2026: Unlocking New Features, Analysis," reviews a cluster of features Google Analytics released over the prior year that extend its ability to support higher-altitude analysis. If your question is "what should I actually do with GA beyond surface reporting," this is the category to start in.

Marketing models and frameworks

This section covers digital marketing, search engine marketing, and brand marketing, usually through a named model you can apply directly.

• Answer Engine Optimization (AEO) — framed as a "Loss Recovery Growth Model." The premise: as search behavior shifts from keyword queries to resolution questions typed into answer engines, sites will lose traffic and revenue unless they adapt. Useful if you are trying to forecast or offset declining search referrals.
• Google Ads Maturity Model — an "AI Ready?" assessment of where an organization sits on the Google Ads platform, with the pointed analogy that using the platform poorly is like insisting on horses when fuel-efficient long-range motorcycles exist.
• Sports Marketing Measurement Playbook — incrementality, measurement, and KPIs, motivated by the observation that nearly all of the top 50 US telecasts last year were connected to sports.
• High-Impact Marketing: Rock Creative Pre-Testing — brand marketing and brand measurement, written as a dialogue about the gap between what a brand thinks its advertising communicates and what it actually does.

Strategic thinking and experimentation

Strategy posts sit alongside a strong thread on controlled experiments and incrementality. "Robust Experimentation and Testing | Reasons for Failure!" targets readers already exposed to testing methodology and walks through why experiments break down in practice. The pairing matters: the strategy content tends to assume you have a measurement capability, and the experimentation content assumes you have a decision worth testing.

Leadership and analytics team practice

The leadership category addresses how analytics functions succeed or fail inside organizations. "Scapegoating Analysts | Recognizing & Preventing A Bad Idea" is aimed at analysts and analytics leaders, covering how to spot and prevent a pattern where analysts absorb blame for outcomes they did not control. This is organizational advice rather than technical instruction.

How to decide whether it fits your problem

The blog is a good fit if you want frameworks and opinionated arguments you can adapt to your own context. It is a weaker fit if you need step-by-step tool documentation, current pricing or platform parameters, or vendor-neutral how-to instructions — the posts are written as analysis and argument, not as manuals. Browse the "All Articles" index by category to confirm coverage before committing time to a specific question.