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Jia Huang

Data & Analytics at Signal · San Francisco, CA

I joined Airbnb's data science team in 2016, two years before the IPO push really started. My first project was building the causal inference framework for their pricing experiments — the system that determines whether a change in pricing actually caused a change in bookings, or whether it was just correlated with something else (seasonality, a marketing campaign, a competitor's outage).

That work taught me the most important lesson of my career: most companies don't have a data problem. They have a decision problem. They collect terabytes of data and then make decisions based on intuition, politics, or whatever the highest-paid person in the room thinks. The data exists. The connection between data and decisions doesn't.

After three years at Airbnb, I moved to Amplitude as Head of Data Science. Amplitude is in the business of helping companies understand user behavior, and working there gave me a front-row seat to how 2,000+ product teams actually use analytics. The uncomfortable truth: most teams look at dashboards. Very few teams run experiments. Almost none have a systematic framework for connecting analytics to product decisions. They have the data. They have the tools. They don't have the practice.

The gap between "having data" and "being data-driven" is enormous, and it's mostly an organizational problem, not a technical one. The companies that are genuinely data-driven — Airbnb, Spotify, Booking.com — built decision frameworks first and analytics infrastructure second. Everyone else did it backwards and wonders why their $2 million data platform hasn't changed how anyone makes decisions.

I left Amplitude in 2024 to consult and write. My consulting work focuses on helping growth-stage companies build experimentation programs. My writing focuses on the same theme from a different angle: what does it actually look like when data drives product decisions, and why is it so rare?

I live in San Francisco with my husband and our daughter. I play competitive chess online (rating ~2100), which my colleagues think explains my personality but actually just explains my insomnia.

Experience

Articles by Jia Huang (12)

The 11 Prompts Every AI Coding Agent Still Fails in 2026 (Reproducible Benchmark)Claude Code, GPT-Codex, Gemini Coder, and Cursor Agent all sail past surface-level benchmarks but consistently fail on 11 specific prompts. Each failu · May 20, 2026Schema Markup Is Dying. Entity Context Is the New Currency.Ten years of schema.org evangelism produced a generation of marketers who treat structured data as the AEO answer. The truth in 2026 is uncomfortable: · May 20, 2026The CMO's AEO Dashboard: 7 Metrics That Actually Belong in a Board DeckShare of voice and organic traffic are legacy metrics. The seven AEO metrics that boards are starting to ask for — and the dashboards that surface the · May 25, 2026AI Shopping Agents: The New Distribution Layer for Comparison-Driven CategoriesSynthetic content has crossed 60% of new web pages by some measurements. The detection arms race, the platform downgrades, and the EEAT signals that n · May 25, 2026AEO Contribution Margin: A CFO Framework for Defending the Budget When Cuts HitCorrelation between AEO investment and pipeline is easy to claim and impossible to defend in a CFO review. Geo-holdouts, content-cohort holdouts, and · May 25, 2026Government Buyers Use ChatGPT to Shortlist Vendors. FedRAMP Vendors Are Ready.Operation AI Comply, the FCC's political-ad AI disclosure order, NIST AI RMF 1.1, and the Colorado AI Act are converging into the first real federal-p · May 26, 2026Anthropic's $1.5B Wall Street Venture Reveals a New Enterprise Distribution PlaybookTop-quartile SaaS products get users to first value in 5–9 days. The median is 18–24 days. That 14-day gap is worth 35 to 45 retention points at month · May 30, 2026The Amodei Doctrine: Why Anthropic's Regulatory Reversal Is the Most Important AI Policy Move of 2026Across 500+ SaaS products, 62% of signups never experience core product value. AI-native onboarding is delivering 3.2x activation improvement. Here is · Jun 13, 2026The Team Activation Gap: Why B2B SaaS Products That Onboard Teams Retain at 1.7x the RateConventional PM wisdom says 80% of your roadmap should chase new customers. Top-quartile expansion SaaS companies have inverted this — and the NDR gap · Jun 21, 2026The AI Leader-Laggard Divide: Why 74% of Enterprise AI Gains Flow to 20% of CompaniesGartner projects over 40% of agentic AI projects will be canceled by 2027. Analysis of enterprise deployments reveals five failure patterns—and the PM · Jun 30, 2026AI Overviews Hit 48% of Google Queries. Here's the GEO Playbook That AdaptsOpenAI's three-tier model family — Sol, Terra, Luna — makes inference speed a first-class pricing variable for the first time. Here's the enterprise r · Jul 11, 2026Anthropic Found a Hidden Workspace Inside Claude. Here's Why Enterprise Buyers Should Care.New benchmarks from a16z and Mixpanel reveal a fundamental tension in AI monetization—and the activation playbook for the teams solving it. · Jul 21, 2026