George is the VP of Growth & Demand @ Ramp

Philosophy: Growth as Science

• Growth = Science: Playbooks do not really work. Come in with a blank slate —> form a hypothesis —> run experiments. Most marketers just apply what they already know; growth is about discovering what works for your company.
• Mindset: Think like a scientist. It's about experimental design, measurement, and rigor.
• Velocity > Perfection: The default bias should be to run more things faster, rather than one thing perfectly.
  • The Tradeoff: A sloppy experiment that 3x's a conversion rate to hit a quarterly number is a valid short-term choice. You can go back and optimize for rigor later to understand why it worked. Velocity and rigor are dials you turn based on the time horizon.

Portfolio Approach

• Treat growth like a VC portfolio. You need a mix of bets, and the allocation should be an intentional conversation with leadership.
  • Long-Term (Big Swings): High-risk, high-reward. The huge step-changes. Most will fail.
  • Short-Term (Incremental Gains): High-confidence, low-impact. The 2-5% improvements that help you hit this quarter's number.
• When a Bet Works —> Go for Saturation: This is a key mistake startups make. Don't just double or triple spend. Push the channel to its asymptote as fast as possible. Find the point where the response curve decays. Most companies scale winning channels too slowly.

• Finding Alpha: Iterate + Experiment!
  1. Do what's new: Things no one else knows about because the channel is new (e.g., being the first B2B brand on TikTok).
  2. Do what's contrarian: Things everyone is convinced will not work (Direct Mail, which became a huge channel for him).

Mental Models

• Pre-mortems & Post-mortems:
  • The value of a post-mortem is tied to the quality of the pre-mortem.
  • Pre-mortem Process: Part of the initial experiment design. The goal is to assess what may cause your strategy to fail. Not just 3-4 big risks, but the "million things" that could go wrong. Assign probabilities to each.
  • The Real Learning —> Unpredicted Failures: A post-mortem is most valuable when an experiment fails for a reason you didn't anticipate.
    • Why? A predicted failure just confirms your model of the world was correct. You don't learn much. An unpredicted failure reveals a flaw in your fundamental assumptions.
    • Figure out what went wrong and then apply the lesson to all future experiments.
  • Key Post-mortem Question: "Did we learn something that can be generalized to other parts of the business?"