Analytics PipelineAI Workflow

“Run `npx radzor@latest add event-tracker user-segmentation ab-test funnel-report csv-export` to install 5 Radzor components. Then read components/radzor/event-tracker/radzor.manifest.json, components/radzor/user-segmentation/radzor.manifest.json, components/radzor/ab-test/radzor.manifest.json, components/radzor/funnel-report/radzor.manifest.json, components/radzor/csv-export/radzor.manifest.json and each component's llm/integration.md. Wire them together to track user events, segment users by behavior, run A/B tests with variant assignment, analyze conversion funnels, and export reports to CSV. A complete product analytics stack. Use the manifest's inputs (check envVar for required environment variables), outputs (check fields for object shapes), composability (check mapField for field extraction), and actions — don't invent custom interfaces.”

Paste this into Claude Code, Cursor, Windsurf, or any AI coding agent.

// npx radzor@latest add event-tracker user-segmentation ab-test funnel-report csv-export
import { EventTracker }     from "./components/radzor/event-tracker"
import { UserSegmentation } from "./components/radzor/user-segmentation"
import { ABTest }           from "./components/radzor/ab-test"
import { FunnelReporter }   from "./components/radzor/funnel-report"
import { CsvExport }        from "./components/radzor/csv-export"

const tracker = new EventTracker({
  endpoint: process.env.ANALYTICS_ENDPOINT!,
  batchSize: 50,
  flushIntervalMs: 10_000,
})

const segments = new UserSegmentation({})
segments.defineSegment("power-users", "Users with 10+ sessions", [
  { field: "sessionCount", operator: "gte", value: 10 },
])
segments.defineSegment("new-users", "Users signed up in last 7 days", [
  { field: "daysSinceSignup", operator: "lte", value: 7 },
])

const ab = new ABTest({ salt: "my-secret-salt" })
ab.createExperiment("new-checkout", ["control", "variant-a", "variant-b"])

const funnel = new FunnelReporter({ funnelId: "checkout", steps: ["view_product", "add_to_cart", "begin_checkout", "purchase"] })

const csv = new CsvExport({ delimiter: "," })

// --- Usage in your app ---
async function trackUserAction(userId: string, action: string, attrs: Record<string, unknown>) {
  // Track the event
  tracker.track(action, { userId, ...attrs })

  // Evaluate user segment
  const { segments: userSegments } = segments.evaluate(userId, attrs)

  // Get A/B test variant
  const { variant } = ab.getVariant("new-checkout", userId)

  // Record funnel step
  if (["view_product", "add_to_cart", "begin_checkout", "purchase"].includes(action)) {
    funnel.recordStep(userId, action)

    // Track conversion for A/B test on purchase
    if (action === "purchase") {
      ab.trackConversion("new-checkout", userId, (attrs.amount as number) ?? 0)
    }
  }

  return { userSegments, variant }
}

// --- Generate reports ---
function exportReports() {
  const funnelData = funnel.getReport()
  const abResults = ab.getResults("new-checkout")

  // Export funnel report
  const funnelCsv = csv.generate(funnelData.steps.map(s => ({
    step: s.name,
    users: s.count,
    conversionRate: s.conversionRate,
    dropoff: s.dropoff,
  })))

  // Export A/B test results
  const abCsv = csv.generate(Object.entries(abResults.variants).map(([name, data]) => ({
    variant: name,
    participants: data.participants,
    conversions: data.conversions,
    conversionRate: data.conversionRate,
    revenue: data.totalValue,
  })))

  return { funnelCsv, abCsv }
}