Blueprint

System Data Flow

Entry Point

Process Node

Data Store

Output

Productionv1.0.0

Growth Engine

Marketing

Turns growth from a vague goal into an instrumented system of hypotheses, tests, and compounding learnings.

Logic Breakdown

Normalizes channel inputs, weights outcomes, and recommends the next experiment based on marginal ROI. Event taxonomy designed for clean ingestion (web → CRM → warehouse) with audit-friendly naming conventions.

Architecture Decisions

01Turns growth from a vague goal into an instrumented system of hypotheses, tests, and compounding learnings.
02Normalizes channel inputs, weights outcomes, and recommends the next experiment based on marginal ROI.
03Event taxonomy designed for clean ingestion (web → CRM → warehouse) with audit-friendly naming conventions.

Code Snippet

typescript

growth-engine.ts

type Channel = "Search" | "Social" | "Email" | "Referral";

type Inputs = {
  budget: number;
  cpc: Record<Channel, number>;
  ctr: Record<Channel, number>;
  cr: Record<Channel, number>;
  aov: number;
};

export function simulatePipeline(i: Inputs) {
  const channels: Channel[] = ["Search", "Social", "Email", "Referral"];
  return channels.map((ch) => {
    const clicks = i.budget / i.cpc[ch];
    const landings = clicks * i.ctr[ch];
    const orders = landings * i.cr[ch];
    const revenue = orders * i.aov;
    return { channel: ch, orders, revenue };
  });
}

Key Dependencies

Experiment Design—Core stack component

Attribution—Core stack component

Positioning—Core stack component

Technical Spec

Pillar: Marketing
Primary KPI: Pipeline
Loop Type: Compounding