/**
 * Amazon Benchmark Tool — Configuration Data
 * Revenue/Budget/Growth maps, industry thresholds, WKFYR matrix
 */
(function () {
  'use strict';

  window.BenchmarkApp = window.BenchmarkApp || {};

  // Slug → numeric midpoint maps
  window.BenchmarkApp.REVENUE_MAP = {
    '0-10k': 5000,
    '10k-25k': 17500,
    '25k-50k': 37500,
    '50k-100k': 75000,
    '100k-300k': 200000,
    '300k-500k': 400000,
    '500k-1m': 750000,
    '1m-5m': 3000000,
    '5m-10m': 7500000,
    '10m-50m': 30000000,
    '50m+': 75000000
  };

  window.BenchmarkApp.BUDGET_MAP = {
    '0-5k': 2500,
    '5k-10k': 7500,
    '10k-25k': 17500,
    '25k-50k': 37500,
    '50k-100k': 75000,
    '100k-1m': 550000,
    '1m+': 1500000
  };

  window.BenchmarkApp.GROWTH_MAP = {
    'negative': -5,
    '0-10': 5,
    '10-25': 17.5,
    '25-50': 37.5,
    '50-100': 75,
    '100+': 150
  };

  // Human-readable labels for dropdown slugs
  window.BenchmarkApp.REVENUE_LABELS = {
    '0-10k': '$0 – $10K',
    '10k-25k': '$10K – $25K',
    '25k-50k': '$25K – $50K',
    '50k-100k': '$50K – $100K',
    '100k-300k': '$100K – $300K',
    '300k-500k': '$300K – $500K',
    '500k-1m': '$500K – $1M',
    '1m-5m': '$1M – $5M',
    '5m-10m': '$5M – $10M',
    '10m-50m': '$10M – $50M',
    '50m+': '$50M+'
  };

  window.BenchmarkApp.BUDGET_LABELS = {
    '0-5k': '$0 – $5K',
    '5k-10k': '$5K – $10K',
    '10k-25k': '$10K – $25K',
    '25k-50k': '$25K – $50K',
    '50k-100k': '$50K – $100K',
    '100k-1m': '$100K – $1M',
    '1m+': '$1M+'
  };

  window.BenchmarkApp.GROWTH_LABELS = {
    'negative': 'Negative',
    '0-10': '0 – 10%',
    '10-25': '10 – 25%',
    '25-50': '25 – 50%',
    '50-100': '50 – 100%',
    '100+': '100%+'
  };

  // Industry display names
  window.BenchmarkApp.INDUSTRY_LABELS = {
    pet: 'Pet',
    fashion: 'Fashion',
    wellness: 'Health & Wellness'
  };

  // 9 sub-tier thresholds per industry (index 0 = A+, 8 = C-)
  window.BenchmarkApp.THRESHOLDS = {
    pet: {
      revenue: [300000000, 100000000, 50000000, 10000000, 5000000, 1000000, 500000, 10000, 0],
      asins:   [400, 400, 150, 150, 150, 150, 100, 50, 0],
      budget:  [30000000, 10000000, 1000000, 500000, 100000, 50000, 10000, 5000, 0],
      growth:  [10, 10, 10, 3, 3, 3, 0, 0, -999],
      labels:  ['A+', 'A', 'A-', 'B+', 'B', 'B-', 'C+', 'C', 'C-']
    },
    fashion: {
      revenue: [400000000, 200000000, 100000000, 50000000, 10000000, 1000000, 500000, 10000, 0],
      asins:   [1200, 1000, 1000, 500, 250, 100, 50, 10, 0],
      budget:  [40000000, 20000000, 1000000, 500000, 100000, 50000, 10000, 5000, 0],
      growth:  [8, 8, 8, 2, 2, 2, 0, 0, -999],
      labels:  ['A+', 'A', 'A-', 'B+', 'B', 'B-', 'C+', 'C', 'C-']
    },
    wellness: {
      revenue: [200000000, 100000000, 50000000, 10000000, 5000000, 1000000, 500000, 10000, 0],
      asins:   [500, 200, 200, 200, 150, 150, 100, 50, 0],
      budget:  [20000000, 10000000, 1000000, 500000, 100000, 50000, 10000, 5000, 0],
      growth:  [10, 10, 10, 4, 4, 4, 0, 0, -999],
      labels:  ['A+', 'A', 'A-', 'B+', 'B', 'B-', 'C+', 'C', 'C-']
    }
  };

  // WKFYR scoring matrix: [metricName][tierLetter] → lever contributions
  window.BenchmarkApp.WKFYR_MATRIX = {
    revenue: {
      C: { ppc: 0.25, listing: 0.25, seo: 0.10, account: 0.05 },
      B: { ppc: 0.15, listing: 0.15, seo: 0.15, account: 0.10 },
      A: { ppc: 0.05, listing: 0.05, seo: 0.25, account: 0.25 }
    },
    budget: {
      C: { ppc: 0.25, listing: 0.10, seo: 0.05, account: 0.05 },
      B: { ppc: 0.20, listing: 0.15, seo: 0.10, account: 0.05 },
      A: { ppc: 0.10, listing: 0.10, seo: 0.15, account: 0.15 }
    },
    asins: {
      C: { ppc: 0.05, listing: 0.25, seo: 0.05, account: 0.15 },
      B: { ppc: 0.05, listing: 0.15, seo: 0.10, account: 0.10 },
      A: { ppc: 0.05, listing: 0.05, seo: 0.15, account: 0.05 }
    },
    growth: {
      C: { ppc: 0.20, listing: 0.15, seo: 0.10, account: 0.05 },
      B: { ppc: 0.10, listing: 0.10, seo: 0.15, account: 0.10 },
      A: { ppc: 0.05, listing: 0.05, seo: 0.05, account: 0.05 }
    }
  };

  // Lever descriptions per overall tier
  window.BenchmarkApp.LEVER_DESCRIPTIONS = {
    ppc: {
      A: 'Optimize ROAS across existing campaigns, explore DSP and video ads',
      B: 'Scale winning campaigns, expand keyword coverage, test new ad types',
      C: 'Launch foundational Sponsored Products campaigns, set up auto + manual targeting'
    },
    listing: {
      A: 'Enhance A+ Content, optimize Brand Story, maintain competitive positioning',
      B: 'Full listing overhaul — titles, bullets, images, A+ Content for top ASINs',
      C: 'Build listings from scratch — keyword-rich titles, benefit-driven bullets, quality images'
    },
    seo: {
      A: 'Fine-tune backend keywords, monitor ranking shifts, defend category positions',
      B: 'Expand backend keyword strategy, optimize indexing across catalog',
      C: 'Complete SEO overhaul — keyword research, backend optimization, category node fixes'
    },
    account: {
      A: 'Catalog strategy & expansion, international growth, brand registry optimization',
      B: 'Inventory health improvement, account health monitoring, FBA optimization',
      C: 'Basic account setup — Brand Registry, FBA enrollment, policy compliance'
    }
  };

  // Lever display config
  window.BenchmarkApp.LEVER_CONFIG = {
    ppc:     { label: 'PPC Ads',              color: '#FF5223' },
    listing: { label: 'Listing Optimization',  color: '#4CAF50' },
    seo:     { label: 'SEO Optimization',      color: '#2196F3' },
    account: { label: 'Account Management',    color: '#9C27B0' }
  };
})();