@power-seo/analytics - npm Package Compare versions

Comparing version 1.0.4 to 1.0.7

LICENSE

+MIT License
+
+Copyright (c) 2026 CCBD SEO Contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

dist/index.cjs

@@ -1,14 +0,44 @@
-'use strict';
+"use strict";
+var __defProp = Object.defineProperty;
+var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
+var __getOwnPropNames = Object.getOwnPropertyNames;
+var __hasOwnProp = Object.prototype.hasOwnProperty;
+var __export = (target, all) => {
+  for (var name in all)
+    __defProp(target, name, { get: all[name], enumerable: true });
+};
+var __copyProps = (to, from, except, desc) => {
+  if (from && typeof from === "object" || typeof from === "function") {
+    for (let key of __getOwnPropNames(from))
+      if (!__hasOwnProp.call(to, key) && key !== except)
+        __defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });
+  }
+  return to;
+};
+var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);
 
-var core = require('@power-seo/core');
+// src/index.ts
+var index_exports = {};
+__export(index_exports, {
+  analyzeQueryRankings: () => analyzeQueryRankings,
+  analyzeTrend: () => analyzeTrend,
+  buildDashboardData: () => buildDashboardData,
+  buildTrendLines: () => buildTrendLines,
+  correlateScoreAndTraffic: () => correlateScoreAndTraffic,
+  detectAnomalies: () => detectAnomalies,
+  mergeGscWithAudit: () => mergeGscWithAudit,
+  trackPositionChanges: () => trackPositionChanges
+});
+module.exports = __toCommonJS(index_exports);
 
 // src/merge.ts
+var import_core = require("@power-seo/core");
 function mergeGscWithAudit(gscData, auditResults) {
   const auditMap = /* @__PURE__ */ new Map();
   for (const result of auditResults) {
-    auditMap.set(core.normalizeUrl(result.url), result);
+    auditMap.set((0, import_core.normalizeUrl)(result.url), result);
   }
   const gscMap = /* @__PURE__ */ new Map();
   for (const page of gscData) {
-    gscMap.set(core.normalizeUrl(page.url), page);
+    gscMap.set((0, import_core.normalizeUrl)(page.url), page);
   }
@@ -243,12 +273,13 @@ const allUrls = /* @__PURE__ */ new Set([...auditMap.keys(), ...gscMap.keys()]);
 }
-
-exports.analyzeQueryRankings = analyzeQueryRankings;
-exports.analyzeTrend = analyzeTrend;
-exports.buildDashboardData = buildDashboardData;
-exports.buildTrendLines = buildTrendLines;
-exports.correlateScoreAndTraffic = correlateScoreAndTraffic;
-exports.detectAnomalies = detectAnomalies;
-exports.mergeGscWithAudit = mergeGscWithAudit;
-exports.trackPositionChanges = trackPositionChanges;
-//# sourceMappingURL=index.cjs.map
+// Annotate the CommonJS export names for ESM import in node:
+0 && (module.exports = {
+  analyzeQueryRankings,
+  analyzeTrend,
+  buildDashboardData,
+  buildTrendLines,
+  correlateScoreAndTraffic,
+  detectAnomalies,
+  mergeGscWithAudit,
+  trackPositionChanges
+});
 //# sourceMappingURL=index.cjs.map

dist/index.cjs.map

@@ -1,1 +0,1 @@
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============================================================================\n// @power-seo/analytics — Merge GSC + Audit Data\n// ============================================================================\n\nimport { normalizeUrl } from '@power-seo/core';\nimport type { GscPageData, PageInsight, AuditCategory, CategoryResult } from './types.js';\n\ninterface AuditData {\n  url: string;\n  score: number;\n  categories: Record<AuditCategory, CategoryResult>;\n  recommendations: string[];\n}\n\nexport function mergeGscWithAudit(\n  gscData: GscPageData[],\n  auditResults: AuditData[],\n): PageInsight[] {\n  const auditMap = new Map<string, AuditData>();\n  for (const result of auditResults) {\n    auditMap.set(normalizeUrl(result.url), result);\n  }\n\n  const gscMap = new Map<string, GscPageData>();\n  for (const page of gscData) {\n    gscMap.set(normalizeUrl(page.url), page);\n  }\n\n  const allUrls = new Set([...auditMap.keys(), ...gscMap.keys()]);\n  const insights: PageInsight[] = [];\n\n  for (const url of allUrls) {\n    const gsc = gscMap.get(url);\n    const audit = auditMap.get(url);\n    const opportunities: string[] = [];\n\n    if (gsc && audit) {\n      if (gsc.clicks > 50 && audit.score < 70) {\n        opportunities.push(\n          `High-traffic page (${gsc.clicks} clicks) with low audit score (${audit.score}). Fixing issues could significantly boost organic performance.`,\n        );\n      }\n      if (gsc.position > 10 && gsc.impressions > 100) {\n        opportunities.push(\n          `Page has ${gsc.impressions} impressions at position ${gsc.position.toFixed(1)}. Improving to page 1 could unlock significant traffic.`,\n        );\n      }\n      if (audit.recommendations.length > 0) {\n        opportunities.push(...audit.recommendations.slice(0, 3));\n      }\n    } else if (gsc && !audit) {\n      opportunities.push(\n        'Page receives search traffic but has not been audited. Run an audit to identify improvement opportunities.',\n      );\n    } else if (!gsc && audit) {\n      if (audit.score < 50) {\n        opportunities.push(\n          `Page has a low audit score (${audit.score}) and no search traffic. Consider improving or removing the page.`,\n        );\n      }\n    }\n\n    insights.push({\n      url,\n      gscMetrics: gsc\n        ? { clicks: gsc.clicks, impressions: gsc.impressions, ctr: gsc.ctr, position: gsc.position }\n        : undefined,\n      auditScore: audit?.score,\n      auditCategories: audit?.categories,\n      opportunities,\n    });\n  }\n\n  return insights;\n}\n\nexport function correlateScoreAndTraffic(insights: PageInsight[]): {\n  correlation: number;\n  topOpportunities: PageInsight[];\n} {\n  const paired = insights.filter((i) => i.gscMetrics && i.auditScore !== undefined);\n\n  if (paired.length < 2) {\n    return { correlation: 0, topOpportunities: [] };\n  }\n\n  const scores = paired.map((i) => i.auditScore!);\n  const clicks = paired.map((i) => i.gscMetrics!.clicks);\n\n  const n = scores.length;\n  const meanScore = scores.reduce((a, b) => a + b, 0) / n;\n  const meanClicks = clicks.reduce((a, b) => a + b, 0) / n;\n\n  let numerator = 0;\n  let denomScore = 0;\n  let denomClicks = 0;\n\n  for (let i = 0; i < n; i++) {\n    const diffScore = (scores[i] ?? 0) - meanScore;\n    const diffClicks = (clicks[i] ?? 0) - meanClicks;\n    numerator += diffScore * diffClicks;\n    denomScore += diffScore * diffScore;\n    denomClicks += diffClicks * diffClicks;\n  }\n\n  const denominator = Math.sqrt(denomScore * denomClicks);\n  const correlation = denominator === 0 ? 0 : numerator / denominator;\n\n  // Top opportunities: high traffic, low score\n  const topOpportunities = [...paired]\n    .filter((i) => i.gscMetrics!.clicks > 0)\n    .sort((a, b) => {\n      const scoreA = a.gscMetrics!.clicks / (a.auditScore! || 1);\n      const scoreB = b.gscMetrics!.clicks / (b.auditScore! || 1);\n      return scoreB - scoreA;\n    })\n    .slice(0, 10);\n\n  return { correlation: Math.round(correlation * 1000) / 1000, topOpportunities };\n}\n","// ============================================================================\n// @power-seo/analytics — Trend Analysis\n// ============================================================================\n\nimport type { TrendPoint, TrendDirection, TrendAnalysis, AuditSnapshot } from './types.js';\n\nexport function analyzeTrend(points: TrendPoint[], metric = 'value'): TrendAnalysis {\n  if (points.length === 0) {\n    return { metric, trend: 'stable', change: 0, points: [] };\n  }\n\n  if (points.length === 1) {\n    return { metric, trend: 'stable', change: 0, points };\n  }\n\n  // Linear regression for slope\n  const n = points.length;\n  const xs = points.map((_, i) => i);\n  const ys = points.map((p) => p.value);\n\n  const meanX = xs.reduce((a, b) => a + b, 0) / n;\n  const meanY = ys.reduce((a, b) => a + b, 0) / n;\n\n  let numerator = 0;\n  let denominator = 0;\n  for (let i = 0; i < n; i++) {\n    const xi = xs[i] ?? 0;\n    const yi = ys[i] ?? 0;\n    numerator += (xi - meanX) * (yi - meanY);\n    denominator += (xi - meanX) * (xi - meanX);\n  }\n\n  const slope = denominator === 0 ? 0 : numerator / denominator;\n\n  // Percentage change first→last\n  const first = points[0]!.value;\n  const last = points[points.length - 1]!.value;\n  const change = first === 0 ? 0 : Math.round(((last - first) / Math.abs(first)) * 10000) / 100;\n\n  // Classify trend based on slope relative to mean\n  const threshold = Math.abs(meanY) * 0.02; // 2% of mean\n  let trend: TrendDirection;\n  if (slope > threshold) {\n    trend = 'improving';\n  } else if (slope < -threshold) {\n    trend = 'declining';\n  } else {\n    trend = 'stable';\n  }\n\n  return { metric, trend, change, points };\n}\n\nexport function buildTrendLines(snapshots: AuditSnapshot[]): Record<string, TrendAnalysis> {\n  if (snapshots.length === 0) {\n    return {};\n  }\n\n  // Sort by date\n  const sorted = [...snapshots].sort((a, b) => a.date.localeCompare(b.date));\n\n  // Overall score trend\n  const overallPoints: TrendPoint[] = sorted.map((s) => ({ date: s.date, value: s.score }));\n  const result: Record<string, TrendAnalysis> = {\n    overall: analyzeTrend(overallPoints, 'overall'),\n  };\n\n  // Per-category trends\n  const categories = Object.keys(sorted[0]!.categories) as Array<\n    keyof (typeof sorted)[0]['categories']\n  >;\n  for (const category of categories) {\n    const categoryPoints: TrendPoint[] = sorted.map((s) => ({\n      date: s.date,\n      value: s.categories[category],\n    }));\n    result[category] = analyzeTrend(categoryPoints, category);\n  }\n\n  return result;\n}\n\nexport function detectAnomalies(points: TrendPoint[], threshold = 2): TrendPoint[] {\n  if (points.length < 3) {\n    return [];\n  }\n\n  const values = points.map((p) => p.value);\n  const mean = values.reduce((a, b) => a + b, 0) / values.length;\n  const variance = values.reduce((sum, v) => sum + (v - mean) ** 2, 0) / values.length;\n  const stdDev = Math.sqrt(variance);\n\n  if (stdDev === 0) {\n    return [];\n  }\n\n  return points.filter((p) => Math.abs(p.value - mean) > threshold * stdDev);\n}\n","// ============================================================================\n// @power-seo/analytics — Query Ranking Analysis\n// ============================================================================\n\nimport type { GscQueryData, RankingAnalysis, RankingBucket, PositionChange } from './types.js';\n\nconst BUCKET_RANGES = [\n  { range: '1-3', min: 1, max: 3 },\n  { range: '4-10', min: 4, max: 10 },\n  { range: '11-20', min: 11, max: 20 },\n  { range: '21-100', min: 21, max: 100 },\n];\n\nexport function analyzeQueryRankings(queries: GscQueryData[]): RankingAnalysis {\n  if (queries.length === 0) {\n    return {\n      totalQueries: 0,\n      buckets: BUCKET_RANGES.map((r) => ({ range: r.range, count: 0, queries: [] })),\n      strikingDistance: [],\n    };\n  }\n\n  const buckets: RankingBucket[] = BUCKET_RANGES.map((range) => {\n    const matching = queries.filter((q) => q.position >= range.min && q.position <= range.max);\n    return {\n      range: range.range,\n      count: matching.length,\n      queries: matching,\n    };\n  });\n\n  // Striking distance: position 4-20, sorted by impressions descending\n  const strikingDistance = queries\n    .filter((q) => q.position >= 4 && q.position <= 20)\n    .sort((a, b) => b.impressions - a.impressions);\n\n  return {\n    totalQueries: queries.length,\n    buckets,\n    strikingDistance,\n  };\n}\n\nexport function trackPositionChanges(\n  current: GscQueryData[],\n  previous: GscQueryData[],\n): PositionChange[] {\n  if (current.length === 0 && previous.length === 0) {\n    return [];\n  }\n\n  const prevMap = new Map<string, GscQueryData>();\n  for (const q of previous) {\n    prevMap.set(q.query, q);\n  }\n\n  const changes: PositionChange[] = [];\n\n  for (const curr of current) {\n    const prev = prevMap.get(curr.query);\n    if (prev) {\n      changes.push({\n        query: curr.query,\n        previousPosition: prev.position,\n        currentPosition: curr.position,\n        change: prev.position - curr.position, // positive = improvement\n        impressionChange: curr.impressions - prev.impressions,\n      });\n    }\n  }\n\n  return changes;\n}\n","// ============================================================================\n// @power-seo/analytics — Dashboard Data Builder\n// ============================================================================\n\nimport type { DashboardInput, DashboardData, DashboardOverview } from './types.js';\nimport { buildTrendLines } from './trends.js';\n\nexport function buildDashboardData(input: DashboardInput): DashboardData {\n  const { gscPages = [], gscQueries = [], auditResults = [], auditHistory = [] } = input;\n\n  // Overview metrics\n  const totalClicks = gscPages.reduce((sum, p) => sum + p.clicks, 0);\n  const totalImpressions = gscPages.reduce((sum, p) => sum + p.impressions, 0);\n  const averageCtr =\n    gscPages.length > 0\n      ? Math.round((gscPages.reduce((sum, p) => sum + p.ctr, 0) / gscPages.length) * 10000) / 10000\n      : 0;\n  const averagePosition =\n    gscPages.length > 0\n      ? Math.round((gscPages.reduce((sum, p) => sum + p.position, 0) / gscPages.length) * 10) / 10\n      : 0;\n  const averageAuditScore =\n    auditResults.length > 0\n      ? Math.round(auditResults.reduce((sum, r) => sum + r.score, 0) / auditResults.length)\n      : 0;\n  const totalPages = Math.max(gscPages.length, auditResults.length);\n\n  const overview: DashboardOverview = {\n    totalClicks,\n    totalImpressions,\n    averageCtr,\n    averagePosition,\n    averageAuditScore,\n    totalPages,\n  };\n\n  // Top pages by clicks\n  const topPages = [...gscPages].sort((a, b) => b.clicks - a.clicks).slice(0, 10);\n\n  // Top queries by clicks\n  const topQueries = [...gscQueries].sort((a, b) => b.clicks - a.clicks).slice(0, 10);\n\n  // Trend lines from audit history\n  const trendLines = buildTrendLines(auditHistory);\n\n  // Collect issues from audit results\n  const issues: string[] = [];\n  for (const result of auditResults) {\n    issues.push(...result.recommendations);\n  }\n  // Deduplicate and limit\n  const uniqueIssues = [...new Set(issues)].slice(0, 20);\n\n  return {\n    overview,\n    topPages,\n    topQueries,\n    trendLines,\n    issues: uniqueIssues,\n  };\n}\n"]}
+{"version":3,"sources":["../src/index.ts","../src/merge.ts","../src/trends.ts","../src/rankings.ts","../src/dashboard.ts"],"sourcesContent":["// @power-seo/analytics — Public API\n// ----------------------------------------------------------------------------\n\nexport { mergeGscWithAudit, correlateScoreAndTraffic } from './merge.js';\nexport { analyzeTrend, buildTrendLines, detectAnomalies } from './trends.js';\nexport { analyzeQueryRankings, trackPositionChanges } from './rankings.js';\nexport { buildDashboardData } from './dashboard.js';\n\nexport type {\n  GscPageData,\n  GscQueryData,\n  AuditSnapshot,\n  TrendPoint,\n  TrendDirection,\n  TrendAnalysis,\n  PageInsight,\n  RankingBucket,\n  RankingAnalysis,\n  PositionChange,\n  DashboardInput,\n  DashboardOverview,\n  DashboardData,\n  AuditCategory,\n  CategoryResult,\n  PageAuditResult,\n} from './types.js';\n","// @power-seo/analytics — Merge GSC + Audit Data\n// ----------------------------------------------------------------------------\n\nimport { normalizeUrl } from '@power-seo/core';\nimport type { GscPageData, PageInsight, AuditCategory, CategoryResult } from './types.js';\n\ninterface AuditData {\n  url: string;\n  score: number;\n  categories: Record<AuditCategory, CategoryResult>;\n  recommendations: string[];\n}\n\nexport function mergeGscWithAudit(\n  gscData: GscPageData[],\n  auditResults: AuditData[],\n): PageInsight[] {\n  const auditMap = new Map<string, AuditData>();\n  for (const result of auditResults) {\n    auditMap.set(normalizeUrl(result.url), result);\n  }\n\n  const gscMap = new Map<string, GscPageData>();\n  for (const page of gscData) {\n    gscMap.set(normalizeUrl(page.url), page);\n  }\n\n  const allUrls = new Set([...auditMap.keys(), ...gscMap.keys()]);\n  const insights: PageInsight[] = [];\n\n  for (const url of allUrls) {\n    const gsc = gscMap.get(url);\n    const audit = auditMap.get(url);\n    const opportunities: string[] = [];\n\n    if (gsc && audit) {\n      if (gsc.clicks > 50 && audit.score < 70) {\n        opportunities.push(\n          `High-traffic page (${gsc.clicks} clicks) with low audit score (${audit.score}). Fixing issues could significantly boost organic performance.`,\n        );\n      }\n      if (gsc.position > 10 && gsc.impressions > 100) {\n        opportunities.push(\n          `Page has ${gsc.impressions} impressions at position ${gsc.position.toFixed(1)}. Improving to page 1 could unlock significant traffic.`,\n        );\n      }\n      if (audit.recommendations.length > 0) {\n        opportunities.push(...audit.recommendations.slice(0, 3));\n      }\n    } else if (gsc && !audit) {\n      opportunities.push(\n        'Page receives search traffic but has not been audited. Run an audit to identify improvement opportunities.',\n      );\n    } else if (!gsc && audit) {\n      if (audit.score < 50) {\n        opportunities.push(\n          `Page has a low audit score (${audit.score}) and no search traffic. Consider improving or removing the page.`,\n        );\n      }\n    }\n\n    insights.push({\n      url,\n      gscMetrics: gsc\n        ? { clicks: gsc.clicks, impressions: gsc.impressions, ctr: gsc.ctr, position: gsc.position }\n        : undefined,\n      auditScore: audit?.score,\n      auditCategories: audit?.categories,\n      opportunities,\n    });\n  }\n\n  return insights;\n}\n\nexport function correlateScoreAndTraffic(insights: PageInsight[]): {\n  correlation: number;\n  topOpportunities: PageInsight[];\n} {\n  const paired = insights.filter((i) => i.gscMetrics && i.auditScore !== undefined);\n\n  if (paired.length < 2) {\n    return { correlation: 0, topOpportunities: [] };\n  }\n\n  const scores = paired.map((i) => i.auditScore!);\n  const clicks = paired.map((i) => i.gscMetrics!.clicks);\n\n  const n = scores.length;\n  const meanScore = scores.reduce((a, b) => a + b, 0) / n;\n  const meanClicks = clicks.reduce((a, b) => a + b, 0) / n;\n\n  let numerator = 0;\n  let denomScore = 0;\n  let denomClicks = 0;\n\n  for (let i = 0; i < n; i++) {\n    const diffScore = (scores[i] ?? 0) - meanScore;\n    const diffClicks = (clicks[i] ?? 0) - meanClicks;\n    numerator += diffScore * diffClicks;\n    denomScore += diffScore * diffScore;\n    denomClicks += diffClicks * diffClicks;\n  }\n\n  const denominator = Math.sqrt(denomScore * denomClicks);\n  const correlation = denominator === 0 ? 0 : numerator / denominator;\n\n  // Top opportunities: high traffic, low score\n  const topOpportunities = [...paired]\n    .filter((i) => i.gscMetrics!.clicks > 0)\n    .sort((a, b) => {\n      const scoreA = a.gscMetrics!.clicks / (a.auditScore! || 1);\n      const scoreB = b.gscMetrics!.clicks / (b.auditScore! || 1);\n      return scoreB - scoreA;\n    })\n    .slice(0, 10);\n\n  return { correlation: Math.round(correlation * 1000) / 1000, topOpportunities };\n}\n","// @power-seo/analytics — Trend Analysis\n// ----------------------------------------------------------------------------\n\nimport type { TrendPoint, TrendDirection, TrendAnalysis, AuditSnapshot } from './types.js';\n\nexport function analyzeTrend(points: TrendPoint[], metric = 'value'): TrendAnalysis {\n  if (points.length === 0) {\n    return { metric, trend: 'stable', change: 0, points: [] };\n  }\n\n  if (points.length === 1) {\n    return { metric, trend: 'stable', change: 0, points };\n  }\n\n  // Linear regression for slope\n  const n = points.length;\n  const xs = points.map((_, i) => i);\n  const ys = points.map((p) => p.value);\n\n  const meanX = xs.reduce((a, b) => a + b, 0) / n;\n  const meanY = ys.reduce((a, b) => a + b, 0) / n;\n\n  let numerator = 0;\n  let denominator = 0;\n  for (let i = 0; i < n; i++) {\n    const xi = xs[i] ?? 0;\n    const yi = ys[i] ?? 0;\n    numerator += (xi - meanX) * (yi - meanY);\n    denominator += (xi - meanX) * (xi - meanX);\n  }\n\n  const slope = denominator === 0 ? 0 : numerator / denominator;\n\n  // Percentage change first→last\n  const first = points[0]!.value;\n  const last = points[points.length - 1]!.value;\n  const change = first === 0 ? 0 : Math.round(((last - first) / Math.abs(first)) * 10000) / 100;\n\n  // Classify trend based on slope relative to mean\n  const threshold = Math.abs(meanY) * 0.02; // 2% of mean\n  let trend: TrendDirection;\n  if (slope > threshold) {\n    trend = 'improving';\n  } else if (slope < -threshold) {\n    trend = 'declining';\n  } else {\n    trend = 'stable';\n  }\n\n  return { metric, trend, change, points };\n}\n\nexport function buildTrendLines(snapshots: AuditSnapshot[]): Record<string, TrendAnalysis> {\n  if (snapshots.length === 0) {\n    return {};\n  }\n\n  // Sort by date\n  const sorted = [...snapshots].sort((a, b) => a.date.localeCompare(b.date));\n\n  // Overall score trend\n  const overallPoints: TrendPoint[] = sorted.map((s) => ({ date: s.date, value: s.score }));\n  const result: Record<string, TrendAnalysis> = {\n    overall: analyzeTrend(overallPoints, 'overall'),\n  };\n\n  // Per-category trends\n  const categories = Object.keys(sorted[0]!.categories) as Array<\n    keyof (typeof sorted)[0]['categories']\n  >;\n  for (const category of categories) {\n    const categoryPoints: TrendPoint[] = sorted.map((s) => ({\n      date: s.date,\n      value: s.categories[category],\n    }));\n    result[category] = analyzeTrend(categoryPoints, category);\n  }\n\n  return result;\n}\n\nexport function detectAnomalies(points: TrendPoint[], threshold = 2): TrendPoint[] {\n  if (points.length < 3) {\n    return [];\n  }\n\n  const values = points.map((p) => p.value);\n  const mean = values.reduce((a, b) => a + b, 0) / values.length;\n  const variance = values.reduce((sum, v) => sum + (v - mean) ** 2, 0) / values.length;\n  const stdDev = Math.sqrt(variance);\n\n  if (stdDev === 0) {\n    return [];\n  }\n\n  return points.filter((p) => Math.abs(p.value - mean) > threshold * stdDev);\n}\n","// @power-seo/analytics — Query Ranking Analysis\n// ----------------------------------------------------------------------------\n\nimport type { GscQueryData, RankingAnalysis, RankingBucket, PositionChange } from './types.js';\n\nconst BUCKET_RANGES = [\n  { range: '1-3', min: 1, max: 3 },\n  { range: '4-10', min: 4, max: 10 },\n  { range: '11-20', min: 11, max: 20 },\n  { range: '21-100', min: 21, max: 100 },\n];\n\nexport function analyzeQueryRankings(queries: GscQueryData[]): RankingAnalysis {\n  if (queries.length === 0) {\n    return {\n      totalQueries: 0,\n      buckets: BUCKET_RANGES.map((r) => ({ range: r.range, count: 0, queries: [] })),\n      strikingDistance: [],\n    };\n  }\n\n  const buckets: RankingBucket[] = BUCKET_RANGES.map((range) => {\n    const matching = queries.filter((q) => q.position >= range.min && q.position <= range.max);\n    return {\n      range: range.range,\n      count: matching.length,\n      queries: matching,\n    };\n  });\n\n  // Striking distance: position 4-20, sorted by impressions descending\n  const strikingDistance = queries\n    .filter((q) => q.position >= 4 && q.position <= 20)\n    .sort((a, b) => b.impressions - a.impressions);\n\n  return {\n    totalQueries: queries.length,\n    buckets,\n    strikingDistance,\n  };\n}\n\nexport function trackPositionChanges(\n  current: GscQueryData[],\n  previous: GscQueryData[],\n): PositionChange[] {\n  if (current.length === 0 && previous.length === 0) {\n    return [];\n  }\n\n  const prevMap = new Map<string, GscQueryData>();\n  for (const q of previous) {\n    prevMap.set(q.query, q);\n  }\n\n  const changes: PositionChange[] = [];\n\n  for (const curr of current) {\n    const prev = prevMap.get(curr.query);\n    if (prev) {\n      changes.push({\n        query: curr.query,\n        previousPosition: prev.position,\n        currentPosition: curr.position,\n        change: prev.position - curr.position, // positive = improvement\n        impressionChange: curr.impressions - prev.impressions,\n      });\n    }\n  }\n\n  return changes;\n}\n","// @power-seo/analytics — Dashboard Data Builder\n// ----------------------------------------------------------------------------\n\nimport type { DashboardInput, DashboardData, DashboardOverview } from './types.js';\nimport { buildTrendLines } from './trends.js';\n\nexport function buildDashboardData(input: DashboardInput): DashboardData {\n  const { gscPages = [], gscQueries = [], auditResults = [], auditHistory = [] } = input;\n\n  // Overview metrics\n  const totalClicks = gscPages.reduce((sum, p) => sum + p.clicks, 0);\n  const totalImpressions = gscPages.reduce((sum, p) => sum + p.impressions, 0);\n  const averageCtr =\n    gscPages.length > 0\n      ? Math.round((gscPages.reduce((sum, p) => sum + p.ctr, 0) / gscPages.length) * 10000) / 10000\n      : 0;\n  const averagePosition =\n    gscPages.length > 0\n      ? Math.round((gscPages.reduce((sum, p) => sum + p.position, 0) / gscPages.length) * 10) / 10\n      : 0;\n  const averageAuditScore =\n    auditResults.length > 0\n      ? Math.round(auditResults.reduce((sum, r) => sum + r.score, 0) / auditResults.length)\n      : 0;\n  const totalPages = Math.max(gscPages.length, auditResults.length);\n\n  const overview: DashboardOverview = {\n    totalClicks,\n    totalImpressions,\n    averageCtr,\n    averagePosition,\n    averageAuditScore,\n    totalPages,\n  };\n\n  // Top pages by clicks\n  const topPages = [...gscPages].sort((a, b) => b.clicks - a.clicks).slice(0, 10);\n\n  // Top queries by clicks\n  const topQueries = [...gscQueries].sort((a, b) => b.clicks - a.clicks).slice(0, 10);\n\n  // Trend lines from audit history\n  const trendLines = buildTrendLines(auditHistory);\n\n  // Collect issues from audit results\n  const issues: string[] = [];\n  for (const result of auditResults) {\n    issues.push(...result.recommendations);\n  }\n  // Deduplicate and limit\n  const uniqueIssues = [...new Set(issues)].slice(0, 20);\n\n  return {\n    overview,\n    topPages,\n    topQueries,\n    trendLines,\n    issues: uniqueIssues,\n  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dist/index.js

@@ -1,4 +0,3 @@
-import { normalizeUrl } from '@power-seo/core';
-
 // src/merge.ts
+import { normalizeUrl } from "@power-seo/core";
 function mergeGscWithAudit(gscData, auditResults) {
@@ -241,5 +240,12 @@ const auditMap = /* @__PURE__ */ new Map();
 }
-
-export { analyzeQueryRankings, analyzeTrend, buildDashboardData, buildTrendLines, correlateScoreAndTraffic, detectAnomalies, mergeGscWithAudit, trackPositionChanges };
-//# sourceMappingURL=index.js.map
+export {
+  analyzeQueryRankings,
+  analyzeTrend,
+  buildDashboardData,
+  buildTrendLines,
+  correlateScoreAndTraffic,
+  detectAnomalies,
+  mergeGscWithAudit,
+  trackPositionChanges
+};
 //# sourceMappingURL=index.js.map

dist/index.js.map

@@ -1,1 +0,1 @@
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============================================================================\n// @power-seo/analytics — Merge GSC + Audit Data\n// ============================================================================\n\nimport { normalizeUrl } from '@power-seo/core';\nimport type { GscPageData, PageInsight, AuditCategory, CategoryResult } from './types.js';\n\ninterface AuditData {\n  url: string;\n  score: number;\n  categories: Record<AuditCategory, CategoryResult>;\n  recommendations: string[];\n}\n\nexport function mergeGscWithAudit(\n  gscData: GscPageData[],\n  auditResults: AuditData[],\n): PageInsight[] {\n  const auditMap = new Map<string, AuditData>();\n  for (const result of auditResults) {\n    auditMap.set(normalizeUrl(result.url), result);\n  }\n\n  const gscMap = new Map<string, GscPageData>();\n  for (const page of gscData) {\n    gscMap.set(normalizeUrl(page.url), page);\n  }\n\n  const allUrls = new Set([...auditMap.keys(), ...gscMap.keys()]);\n  const insights: PageInsight[] = [];\n\n  for (const url of allUrls) {\n    const gsc = gscMap.get(url);\n    const audit = auditMap.get(url);\n    const opportunities: string[] = [];\n\n    if (gsc && audit) {\n      if (gsc.clicks > 50 && audit.score < 70) {\n        opportunities.push(\n          `High-traffic page (${gsc.clicks} clicks) with low audit score (${audit.score}). Fixing issues could significantly boost organic performance.`,\n        );\n      }\n      if (gsc.position > 10 && gsc.impressions > 100) {\n        opportunities.push(\n          `Page has ${gsc.impressions} impressions at position ${gsc.position.toFixed(1)}. Improving to page 1 could unlock significant traffic.`,\n        );\n      }\n      if (audit.recommendations.length > 0) {\n        opportunities.push(...audit.recommendations.slice(0, 3));\n      }\n    } else if (gsc && !audit) {\n      opportunities.push(\n        'Page receives search traffic but has not been audited. Run an audit to identify improvement opportunities.',\n      );\n    } else if (!gsc && audit) {\n      if (audit.score < 50) {\n        opportunities.push(\n          `Page has a low audit score (${audit.score}) and no search traffic. Consider improving or removing the page.`,\n        );\n      }\n    }\n\n    insights.push({\n      url,\n      gscMetrics: gsc\n        ? { clicks: gsc.clicks, impressions: gsc.impressions, ctr: gsc.ctr, position: gsc.position }\n        : undefined,\n      auditScore: audit?.score,\n      auditCategories: audit?.categories,\n      opportunities,\n    });\n  }\n\n  return insights;\n}\n\nexport function correlateScoreAndTraffic(insights: PageInsight[]): {\n  correlation: number;\n  topOpportunities: PageInsight[];\n} {\n  const paired = insights.filter((i) => i.gscMetrics && i.auditScore !== undefined);\n\n  if (paired.length < 2) {\n    return { correlation: 0, topOpportunities: [] };\n  }\n\n  const scores = paired.map((i) => i.auditScore!);\n  const clicks = paired.map((i) => i.gscMetrics!.clicks);\n\n  const n = scores.length;\n  const meanScore = scores.reduce((a, b) => a + b, 0) / n;\n  const meanClicks = clicks.reduce((a, b) => a + b, 0) / n;\n\n  let numerator = 0;\n  let denomScore = 0;\n  let denomClicks = 0;\n\n  for (let i = 0; i < n; i++) {\n    const diffScore = (scores[i] ?? 0) - meanScore;\n    const diffClicks = (clicks[i] ?? 0) - meanClicks;\n    numerator += diffScore * diffClicks;\n    denomScore += diffScore * diffScore;\n    denomClicks += diffClicks * diffClicks;\n  }\n\n  const denominator = Math.sqrt(denomScore * denomClicks);\n  const correlation = denominator === 0 ? 0 : numerator / denominator;\n\n  // Top opportunities: high traffic, low score\n  const topOpportunities = [...paired]\n    .filter((i) => i.gscMetrics!.clicks > 0)\n    .sort((a, b) => {\n      const scoreA = a.gscMetrics!.clicks / (a.auditScore! || 1);\n      const scoreB = b.gscMetrics!.clicks / (b.auditScore! || 1);\n      return scoreB - scoreA;\n    })\n    .slice(0, 10);\n\n  return { correlation: Math.round(correlation * 1000) / 1000, topOpportunities };\n}\n","// ============================================================================\n// @power-seo/analytics — Trend Analysis\n// ============================================================================\n\nimport type { TrendPoint, TrendDirection, TrendAnalysis, AuditSnapshot } from './types.js';\n\nexport function analyzeTrend(points: TrendPoint[], metric = 'value'): TrendAnalysis {\n  if (points.length === 0) {\n    return { metric, trend: 'stable', change: 0, points: [] };\n  }\n\n  if (points.length === 1) {\n    return { metric, trend: 'stable', change: 0, points };\n  }\n\n  // Linear regression for slope\n  const n = points.length;\n  const xs = points.map((_, i) => i);\n  const ys = points.map((p) => p.value);\n\n  const meanX = xs.reduce((a, b) => a + b, 0) / n;\n  const meanY = ys.reduce((a, b) => a + b, 0) / n;\n\n  let numerator = 0;\n  let denominator = 0;\n  for (let i = 0; i < n; i++) {\n    const xi = xs[i] ?? 0;\n    const yi = ys[i] ?? 0;\n    numerator += (xi - meanX) * (yi - meanY);\n    denominator += (xi - meanX) * (xi - meanX);\n  }\n\n  const slope = denominator === 0 ? 0 : numerator / denominator;\n\n  // Percentage change first→last\n  const first = points[0]!.value;\n  const last = points[points.length - 1]!.value;\n  const change = first === 0 ? 0 : Math.round(((last - first) / Math.abs(first)) * 10000) / 100;\n\n  // Classify trend based on slope relative to mean\n  const threshold = Math.abs(meanY) * 0.02; // 2% of mean\n  let trend: TrendDirection;\n  if (slope > threshold) {\n    trend = 'improving';\n  } else if (slope < -threshold) {\n    trend = 'declining';\n  } else {\n    trend = 'stable';\n  }\n\n  return { metric, trend, change, points };\n}\n\nexport function buildTrendLines(snapshots: AuditSnapshot[]): Record<string, TrendAnalysis> {\n  if (snapshots.length === 0) {\n    return {};\n  }\n\n  // Sort by date\n  const sorted = [...snapshots].sort((a, b) => a.date.localeCompare(b.date));\n\n  // Overall score trend\n  const overallPoints: TrendPoint[] = sorted.map((s) => ({ date: s.date, value: s.score }));\n  const result: Record<string, TrendAnalysis> = {\n    overall: analyzeTrend(overallPoints, 'overall'),\n  };\n\n  // Per-category trends\n  const categories = Object.keys(sorted[0]!.categories) as Array<\n    keyof (typeof sorted)[0]['categories']\n  >;\n  for (const category of categories) {\n    const categoryPoints: TrendPoint[] = sorted.map((s) => ({\n      date: s.date,\n      value: s.categories[category],\n    }));\n    result[category] = analyzeTrend(categoryPoints, category);\n  }\n\n  return result;\n}\n\nexport function detectAnomalies(points: TrendPoint[], threshold = 2): TrendPoint[] {\n  if (points.length < 3) {\n    return [];\n  }\n\n  const values = points.map((p) => p.value);\n  const mean = values.reduce((a, b) => a + b, 0) / values.length;\n  const variance = values.reduce((sum, v) => sum + (v - mean) ** 2, 0) / values.length;\n  const stdDev = Math.sqrt(variance);\n\n  if (stdDev === 0) {\n    return [];\n  }\n\n  return points.filter((p) => Math.abs(p.value - mean) > threshold * stdDev);\n}\n","// ============================================================================\n// @power-seo/analytics — Query Ranking Analysis\n// ============================================================================\n\nimport type { GscQueryData, RankingAnalysis, RankingBucket, PositionChange } from './types.js';\n\nconst BUCKET_RANGES = [\n  { range: '1-3', min: 1, max: 3 },\n  { range: '4-10', min: 4, max: 10 },\n  { range: '11-20', min: 11, max: 20 },\n  { range: '21-100', min: 21, max: 100 },\n];\n\nexport function analyzeQueryRankings(queries: GscQueryData[]): RankingAnalysis {\n  if (queries.length === 0) {\n    return {\n      totalQueries: 0,\n      buckets: BUCKET_RANGES.map((r) => ({ range: r.range, count: 0, queries: [] })),\n      strikingDistance: [],\n    };\n  }\n\n  const buckets: RankingBucket[] = BUCKET_RANGES.map((range) => {\n    const matching = queries.filter((q) => q.position >= range.min && q.position <= range.max);\n    return {\n      range: range.range,\n      count: matching.length,\n      queries: matching,\n    };\n  });\n\n  // Striking distance: position 4-20, sorted by impressions descending\n  const strikingDistance = queries\n    .filter((q) => q.position >= 4 && q.position <= 20)\n    .sort((a, b) => b.impressions - a.impressions);\n\n  return {\n    totalQueries: queries.length,\n    buckets,\n    strikingDistance,\n  };\n}\n\nexport function trackPositionChanges(\n  current: GscQueryData[],\n  previous: GscQueryData[],\n): PositionChange[] {\n  if (current.length === 0 && previous.length === 0) {\n    return [];\n  }\n\n  const prevMap = new Map<string, GscQueryData>();\n  for (const q of previous) {\n    prevMap.set(q.query, q);\n  }\n\n  const changes: PositionChange[] = [];\n\n  for (const curr of current) {\n    const prev = prevMap.get(curr.query);\n    if (prev) {\n      changes.push({\n        query: curr.query,\n        previousPosition: prev.position,\n        currentPosition: curr.position,\n        change: prev.position - curr.position, // positive = improvement\n        impressionChange: curr.impressions - prev.impressions,\n      });\n    }\n  }\n\n  return changes;\n}\n","// ============================================================================\n// @power-seo/analytics — Dashboard Data Builder\n// ============================================================================\n\nimport type { DashboardInput, DashboardData, DashboardOverview } from './types.js';\nimport { buildTrendLines } from './trends.js';\n\nexport function buildDashboardData(input: DashboardInput): DashboardData {\n  const { gscPages = [], gscQueries = [], auditResults = [], auditHistory = [] } = input;\n\n  // Overview metrics\n  const totalClicks = gscPages.reduce((sum, p) => sum + p.clicks, 0);\n  const totalImpressions = gscPages.reduce((sum, p) => sum + p.impressions, 0);\n  const averageCtr =\n    gscPages.length > 0\n      ? Math.round((gscPages.reduce((sum, p) => sum + p.ctr, 0) / gscPages.length) * 10000) / 10000\n      : 0;\n  const averagePosition =\n    gscPages.length > 0\n      ? Math.round((gscPages.reduce((sum, p) => sum + p.position, 0) / gscPages.length) * 10) / 10\n      : 0;\n  const averageAuditScore =\n    auditResults.length > 0\n      ? Math.round(auditResults.reduce((sum, r) => sum + r.score, 0) / auditResults.length)\n      : 0;\n  const totalPages = Math.max(gscPages.length, auditResults.length);\n\n  const overview: DashboardOverview = {\n    totalClicks,\n    totalImpressions,\n    averageCtr,\n    averagePosition,\n    averageAuditScore,\n    totalPages,\n  };\n\n  // Top pages by clicks\n  const topPages = [...gscPages].sort((a, b) => b.clicks - a.clicks).slice(0, 10);\n\n  // Top queries by clicks\n  const topQueries = [...gscQueries].sort((a, b) => b.clicks - a.clicks).slice(0, 10);\n\n  // Trend lines from audit history\n  const trendLines = buildTrendLines(auditHistory);\n\n  // Collect issues from audit results\n  const issues: string[] = [];\n  for (const result of auditResults) {\n    issues.push(...result.recommendations);\n  }\n  // Deduplicate and limit\n  const uniqueIssues = [...new Set(issues)].slice(0, 20);\n\n  return {\n    overview,\n    topPages,\n    topQueries,\n    trendLines,\n    issues: uniqueIssues,\n  };\n}\n"]}
+{"version":3,"sources":["../src/merge.ts","../src/trends.ts","../src/rankings.ts","../src/dashboard.ts"],"sourcesContent":["// @power-seo/analytics — Merge GSC + Audit Data\n// ----------------------------------------------------------------------------\n\nimport { normalizeUrl } from '@power-seo/core';\nimport type { GscPageData, PageInsight, AuditCategory, CategoryResult } from './types.js';\n\ninterface AuditData {\n  url: string;\n  score: number;\n  categories: Record<AuditCategory, CategoryResult>;\n  recommendations: string[];\n}\n\nexport function mergeGscWithAudit(\n  gscData: GscPageData[],\n  auditResults: AuditData[],\n): PageInsight[] {\n  const auditMap = new Map<string, AuditData>();\n  for (const result of auditResults) {\n    auditMap.set(normalizeUrl(result.url), result);\n  }\n\n  const gscMap = new Map<string, GscPageData>();\n  for (const page of gscData) {\n    gscMap.set(normalizeUrl(page.url), page);\n  }\n\n  const allUrls = new Set([...auditMap.keys(), ...gscMap.keys()]);\n  const insights: PageInsight[] = [];\n\n  for (const url of allUrls) {\n    const gsc = gscMap.get(url);\n    const audit = auditMap.get(url);\n    const opportunities: string[] = [];\n\n    if (gsc && audit) {\n      if (gsc.clicks > 50 && audit.score < 70) {\n        opportunities.push(\n          `High-traffic page (${gsc.clicks} clicks) with low audit score (${audit.score}). Fixing issues could significantly boost organic performance.`,\n        );\n      }\n      if (gsc.position > 10 && gsc.impressions > 100) {\n        opportunities.push(\n          `Page has ${gsc.impressions} impressions at position ${gsc.position.toFixed(1)}. Improving to page 1 could unlock significant traffic.`,\n        );\n      }\n      if (audit.recommendations.length > 0) {\n        opportunities.push(...audit.recommendations.slice(0, 3));\n      }\n    } else if (gsc && !audit) {\n      opportunities.push(\n        'Page receives search traffic but has not been audited. Run an audit to identify improvement opportunities.',\n      );\n    } else if (!gsc && audit) {\n      if (audit.score < 50) {\n        opportunities.push(\n          `Page has a low audit score (${audit.score}) and no search traffic. Consider improving or removing the page.`,\n        );\n      }\n    }\n\n    insights.push({\n      url,\n      gscMetrics: gsc\n        ? { clicks: gsc.clicks, impressions: gsc.impressions, ctr: gsc.ctr, position: gsc.position }\n        : undefined,\n      auditScore: audit?.score,\n      auditCategories: audit?.categories,\n      opportunities,\n    });\n  }\n\n  return insights;\n}\n\nexport function correlateScoreAndTraffic(insights: PageInsight[]): {\n  correlation: number;\n  topOpportunities: PageInsight[];\n} {\n  const paired = insights.filter((i) => i.gscMetrics && i.auditScore !== undefined);\n\n  if (paired.length < 2) {\n    return { correlation: 0, topOpportunities: [] };\n  }\n\n  const scores = paired.map((i) => i.auditScore!);\n  const clicks = paired.map((i) => i.gscMetrics!.clicks);\n\n  const n = scores.length;\n  const meanScore = scores.reduce((a, b) => a + b, 0) / n;\n  const meanClicks = clicks.reduce((a, b) => a + b, 0) / n;\n\n  let numerator = 0;\n  let denomScore = 0;\n  let denomClicks = 0;\n\n  for (let i = 0; i < n; i++) {\n    const diffScore = (scores[i] ?? 0) - meanScore;\n    const diffClicks = (clicks[i] ?? 0) - meanClicks;\n    numerator += diffScore * diffClicks;\n    denomScore += diffScore * diffScore;\n    denomClicks += diffClicks * diffClicks;\n  }\n\n  const denominator = Math.sqrt(denomScore * denomClicks);\n  const correlation = denominator === 0 ? 0 : numerator / denominator;\n\n  // Top opportunities: high traffic, low score\n  const topOpportunities = [...paired]\n    .filter((i) => i.gscMetrics!.clicks > 0)\n    .sort((a, b) => {\n      const scoreA = a.gscMetrics!.clicks / (a.auditScore! || 1);\n      const scoreB = b.gscMetrics!.clicks / (b.auditScore! || 1);\n      return scoreB - scoreA;\n    })\n    .slice(0, 10);\n\n  return { correlation: Math.round(correlation * 1000) / 1000, topOpportunities };\n}\n","// @power-seo/analytics — Trend Analysis\n// ----------------------------------------------------------------------------\n\nimport type { TrendPoint, TrendDirection, TrendAnalysis, AuditSnapshot } from './types.js';\n\nexport function analyzeTrend(points: TrendPoint[], metric = 'value'): TrendAnalysis {\n  if (points.length === 0) {\n    return { metric, trend: 'stable', change: 0, points: [] };\n  }\n\n  if (points.length === 1) {\n    return { metric, trend: 'stable', change: 0, points };\n  }\n\n  // Linear regression for slope\n  const n = points.length;\n  const xs = points.map((_, i) => i);\n  const ys = points.map((p) => p.value);\n\n  const meanX = xs.reduce((a, b) => a + b, 0) / n;\n  const meanY = ys.reduce((a, b) => a + b, 0) / n;\n\n  let numerator = 0;\n  let denominator = 0;\n  for (let i = 0; i < n; i++) {\n    const xi = xs[i] ?? 0;\n    const yi = ys[i] ?? 0;\n    numerator += (xi - meanX) * (yi - meanY);\n    denominator += (xi - meanX) * (xi - meanX);\n  }\n\n  const slope = denominator === 0 ? 0 : numerator / denominator;\n\n  // Percentage change first→last\n  const first = points[0]!.value;\n  const last = points[points.length - 1]!.value;\n  const change = first === 0 ? 0 : Math.round(((last - first) / Math.abs(first)) * 10000) / 100;\n\n  // Classify trend based on slope relative to mean\n  const threshold = Math.abs(meanY) * 0.02; // 2% of mean\n  let trend: TrendDirection;\n  if (slope > threshold) {\n    trend = 'improving';\n  } else if (slope < -threshold) {\n    trend = 'declining';\n  } else {\n    trend = 'stable';\n  }\n\n  return { metric, trend, change, points };\n}\n\nexport function buildTrendLines(snapshots: AuditSnapshot[]): Record<string, TrendAnalysis> {\n  if (snapshots.length === 0) {\n    return {};\n  }\n\n  // Sort by date\n  const sorted = [...snapshots].sort((a, b) => a.date.localeCompare(b.date));\n\n  // Overall score trend\n  const overallPoints: TrendPoint[] = sorted.map((s) => ({ date: s.date, value: s.score }));\n  const result: Record<string, TrendAnalysis> = {\n    overall: analyzeTrend(overallPoints, 'overall'),\n  };\n\n  // Per-category trends\n  const categories = Object.keys(sorted[0]!.categories) as Array<\n    keyof (typeof sorted)[0]['categories']\n  >;\n  for (const category of categories) {\n    const categoryPoints: TrendPoint[] = sorted.map((s) => ({\n      date: s.date,\n      value: s.categories[category],\n    }));\n    result[category] = analyzeTrend(categoryPoints, category);\n  }\n\n  return result;\n}\n\nexport function detectAnomalies(points: TrendPoint[], threshold = 2): TrendPoint[] {\n  if (points.length < 3) {\n    return [];\n  }\n\n  const values = points.map((p) => p.value);\n  const mean = values.reduce((a, b) => a + b, 0) / values.length;\n  const variance = values.reduce((sum, v) => sum + (v - mean) ** 2, 0) / values.length;\n  const stdDev = Math.sqrt(variance);\n\n  if (stdDev === 0) {\n    return [];\n  }\n\n  return points.filter((p) => Math.abs(p.value - mean) > threshold * stdDev);\n}\n","// @power-seo/analytics — Query Ranking Analysis\n// ----------------------------------------------------------------------------\n\nimport type { GscQueryData, RankingAnalysis, RankingBucket, PositionChange } from './types.js';\n\nconst BUCKET_RANGES = [\n  { range: '1-3', min: 1, max: 3 },\n  { range: '4-10', min: 4, max: 10 },\n  { range: '11-20', min: 11, max: 20 },\n  { range: '21-100', min: 21, max: 100 },\n];\n\nexport function analyzeQueryRankings(queries: GscQueryData[]): RankingAnalysis {\n  if (queries.length === 0) {\n    return {\n      totalQueries: 0,\n      buckets: BUCKET_RANGES.map((r) => ({ range: r.range, count: 0, queries: [] })),\n      strikingDistance: [],\n    };\n  }\n\n  const buckets: RankingBucket[] = BUCKET_RANGES.map((range) => {\n    const matching = queries.filter((q) => q.position >= range.min && q.position <= range.max);\n    return {\n      range: range.range,\n      count: matching.length,\n      queries: matching,\n    };\n  });\n\n  // Striking distance: position 4-20, sorted by impressions descending\n  const strikingDistance = queries\n    .filter((q) => q.position >= 4 && q.position <= 20)\n    .sort((a, b) => b.impressions - a.impressions);\n\n  return {\n    totalQueries: queries.length,\n    buckets,\n    strikingDistance,\n  };\n}\n\nexport function trackPositionChanges(\n  current: GscQueryData[],\n  previous: GscQueryData[],\n): PositionChange[] {\n  if (current.length === 0 && previous.length === 0) {\n    return [];\n  }\n\n  const prevMap = new Map<string, GscQueryData>();\n  for (const q of previous) {\n    prevMap.set(q.query, q);\n  }\n\n  const changes: PositionChange[] = [];\n\n  for (const curr of current) {\n    const prev = prevMap.get(curr.query);\n    if (prev) {\n      changes.push({\n        query: curr.query,\n        previousPosition: prev.position,\n        currentPosition: curr.position,\n        change: prev.position - curr.position, // positive = improvement\n        impressionChange: curr.impressions - prev.impressions,\n      });\n    }\n  }\n\n  return changes;\n}\n","// @power-seo/analytics — Dashboard Data Builder\n// ----------------------------------------------------------------------------\n\nimport type { DashboardInput, DashboardData, DashboardOverview } from './types.js';\nimport { buildTrendLines } from './trends.js';\n\nexport function buildDashboardData(input: DashboardInput): DashboardData {\n  const { gscPages = [], gscQueries = [], auditResults = [], auditHistory = [] } = input;\n\n  // Overview metrics\n  const totalClicks = gscPages.reduce((sum, p) => sum + p.clicks, 0);\n  const totalImpressions = gscPages.reduce((sum, p) => sum + p.impressions, 0);\n  const averageCtr =\n    gscPages.length > 0\n      ? Math.round((gscPages.reduce((sum, p) => sum + p.ctr, 0) / gscPages.length) * 10000) / 10000\n      : 0;\n  const averagePosition =\n    gscPages.length > 0\n      ? Math.round((gscPages.reduce((sum, p) => sum + p.position, 0) / gscPages.length) * 10) / 10\n      : 0;\n  const averageAuditScore =\n    auditResults.length > 0\n      ? Math.round(auditResults.reduce((sum, r) => sum + r.score, 0) / auditResults.length)\n      : 0;\n  const totalPages = Math.max(gscPages.length, auditResults.length);\n\n  const overview: DashboardOverview = {\n    totalClicks,\n    totalImpressions,\n    averageCtr,\n    averagePosition,\n    averageAuditScore,\n    totalPages,\n  };\n\n  // Top pages by clicks\n  const topPages = [...gscPages].sort((a, b) => b.clicks - a.clicks).slice(0, 10);\n\n  // Top queries by clicks\n  const topQueries = [...gscQueries].sort((a, b) => b.clicks - a.clicks).slice(0, 10);\n\n  // Trend lines from audit history\n  const trendLines = buildTrendLines(auditHistory);\n\n  // Collect issues from audit results\n  const issues: string[] = [];\n  for (const result of auditResults) {\n    issues.push(...result.recommendations);\n  }\n  // Deduplicate and limit\n  const uniqueIssues = [...new Set(issues)].slice(0, 20);\n\n  return {\n    overview,\n    topPages,\n    topQueries,\n    trendLines,\n    issues: uniqueIssues,\n  };\n}\n"],"mappings":";AAGA,SAAS,oBAAoB;AAUtB,SAAS,kBACd,SACA,cACe;AACf,QAAM,WAAW,oBAAI,IAAuB;AAC5C,aAAW,UAAU,cAAc;AACjC,aAAS,IAAI,aAAa,OAAO,GAAG,GAAG,MAAM;AAAA,EAC/C;AAEA,QAAM,SAAS,oBAAI,IAAyB;AAC5C,aAAW,QAAQ,SAAS;AAC1B,WAAO,IAAI,aAAa,KAAK,GAAG,GAAG,IAAI;AAAA,EACzC;AAEA,QAAM,UAAU,oBAAI,IAAI,CAAC,GAAG,SAAS,KAAK,GAAG,GAAG,OAAO,KAAK,CAAC,CAAC;AAC9D,QAAM,WAA0B,CAAC;AAEjC,aAAW,OAAO,SAAS;AACzB,UAAM,MAAM,OAAO,IAAI,GAAG;AAC1B,UAAM,QAAQ,SAAS,IAAI,GAAG;AAC9B,UAAM,gBAA0B,CAAC;AAEjC,QAAI,OAAO,OAAO;AAChB,UAAI,IAAI,SAAS,MAAM,MAAM,QAAQ,IAAI;AACvC,sBAAc;AAAA,UACZ,sBAAsB,IAAI,MAAM,kCAAkC,MAAM,KAAK;AAAA,QAC/E;AAAA,MACF;AACA,UAAI,IAAI,WAAW,MAAM,IAAI,cAAc,KAAK;AAC9C,sBAAc;AAAA,UACZ,YAAY,IAAI,WAAW,4BAA4B,IAAI,SAAS,QAAQ,CAAC,CAAC;AAAA,QAChF;AAAA,MACF;AACA,UAAI,MAAM,gBAAgB,SAAS,GAAG;AACpC,sBAAc,KAAK,GAAG,MAAM,gBAAgB,MAAM,GAAG,CAAC,CAAC;AAAA,MACzD;AAAA,IACF,WAAW,OAAO,CAAC,OAAO;AACxB,oBAAc;AAAA,QACZ;AAAA,MACF;AAAA,IACF,WAAW,CAAC,OAAO,OAAO;AACxB,UAAI,MAAM,QAAQ,IAAI;AACpB,sBAAc;AAAA,UACZ,+BAA+B,MAAM,KAAK;AAAA,QAC5C;AAAA,MACF;AAAA,IACF;AAEA,aAAS,KAAK;AAAA,MACZ;AAAA,MACA,YAAY,MACR,EAAE,QAAQ,IAAI,QAAQ,aAAa,IAAI,aAAa,KAAK,IAAI,KAAK,UAAU,IAAI,SAAS,IACzF;AAAA,MACJ,YAAY,OAAO;AAAA,MACnB,iBAAiB,OAAO;AAAA,MACxB;AAAA,IACF,CAAC;AAAA,EACH;AAEA,SAAO;AACT;AAEO,SAAS,yBAAyB,UAGvC;AACA,QAAM,SAAS,SAAS,OAAO,CAAC,MAAM,EAAE,cAAc,EAAE,eAAe,MAAS;AAEhF,MAAI,OAAO,SAAS,GAAG;AACrB,WAAO,EAAE,aAAa,GAAG,kBAAkB,CAAC,EAAE;AAAA,EAChD;AAEA,QAAM,SAAS,OAAO,IAAI,CAAC,MAAM,EAAE,UAAW;AAC9C,QAAM,SAAS,OAAO,IAAI,CAAC,MAAM,EAAE,WAAY,MAAM;AAErD,QAAM,IAAI,OAAO;AACjB,QAAM,YAAY,OAAO,OAAO,CAAC,GAAG,MAAM,IAAI,GAAG,CAAC,IAAI;AACtD,QAAM,aAAa,OAAO,OAAO,CAAC,GAAG,MAAM,IAAI,GAAG,CAAC,IAAI;AAEvD,MAAI,YAAY;AAChB,MAAI,aAAa;AACjB,MAAI,cAAc;AAElB,WAAS,IAAI,GAAG,IAAI,GAAG,KAAK;AAC1B,UAAM,aAAa,OAAO,CAAC,KAAK,KAAK;AACrC,UAAM,cAAc,OAAO,CAAC,KAAK,KAAK;AACtC,iBAAa,YAAY;AACzB,kBAAc,YAAY;AAC1B,mBAAe,aAAa;AAAA,EAC9B;AAEA,QAAM,cAAc,KAAK,KAAK,aAAa,WAAW;AACtD,QAAM,cAAc,gBAAgB,IAAI,IAAI,YAAY;AAGxD,QAAM,mBAAmB,CAAC,GAAG,MAAM,EAChC,OAAO,CAAC,MAAM,EAAE,WAAY,SAAS,CAAC,EACtC,KAAK,CAAC,GAAG,MAAM;AACd,UAAM,SAAS,EAAE,WAAY,UAAU,EAAE,cAAe;AACxD,UAAM,SAAS,EAAE,WAAY,UAAU,EAAE,cAAe;AACxD,WAAO,SAAS;AAAA,EAClB,CAAC,EACA,MAAM,GAAG,EAAE;AAEd,SAAO,EAAE,aAAa,KAAK,MAAM,cAAc,GAAI,IAAI,KAAM,iBAAiB;AAChF;;;ACjHO,SAAS,aAAa,QAAsB,SAAS,SAAwB;AAClF,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,EAAE,QAAQ,OAAO,UAAU,QAAQ,GAAG,QAAQ,CAAC,EAAE;AAAA,EAC1D;AAEA,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,EAAE,QAAQ,OAAO,UAAU,QAAQ,GAAG,OAAO;AAAA,EACtD;AAGA,QAAM,IAAI,OAAO;AACjB,QAAM,KAAK,OAAO,IAAI,CAAC,GAAG,MAAM,CAAC;AACjC,QAAM,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,KAAK;AAEpC,QAAM,QAAQ,GAAG,OAAO,CAAC,GAAG,MAAM,IAAI,GAAG,CAAC,IAAI;AAC9C,QAAM,QAAQ,GAAG,OAAO,CAAC,GAAG,MAAM,IAAI,GAAG,CAAC,IAAI;AAE9C,MAAI,YAAY;AAChB,MAAI,cAAc;AAClB,WAAS,IAAI,GAAG,IAAI,GAAG,KAAK;AAC1B,UAAM,KAAK,GAAG,CAAC,KAAK;AACpB,UAAM,KAAK,GAAG,CAAC,KAAK;AACpB,kBAAc,KAAK,UAAU,KAAK;AAClC,oBAAgB,KAAK,UAAU,KAAK;AAAA,EACtC;AAEA,QAAM,QAAQ,gBAAgB,IAAI,IAAI,YAAY;AAGlD,QAAM,QAAQ,OAAO,CAAC,EAAG;AACzB,QAAM,OAAO,OAAO,OAAO,SAAS,CAAC,EAAG;AACxC,QAAM,SAAS,UAAU,IAAI,IAAI,KAAK,OAAQ,OAAO,SAAS,KAAK,IAAI,KAAK,IAAK,GAAK,IAAI;AAG1F,QAAM,YAAY,KAAK,IAAI,KAAK,IAAI;AACpC,MAAI;AACJ,MAAI,QAAQ,WAAW;AACrB,YAAQ;AAAA,EACV,WAAW,QAAQ,CAAC,WAAW;AAC7B,YAAQ;AAAA,EACV,OAAO;AACL,YAAQ;AAAA,EACV;AAEA,SAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO;AACzC;AAEO,SAAS,gBAAgB,WAA2D;AACzF,MAAI,UAAU,WAAW,GAAG;AAC1B,WAAO,CAAC;AAAA,EACV;AAGA,QAAM,SAAS,CAAC,GAAG,SAAS,EAAE,KAAK,CAAC,GAAG,MAAM,EAAE,KAAK,cAAc,EAAE,IAAI,CAAC;AAGzE,QAAM,gBAA8B,OAAO,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,MAAM,OAAO,EAAE,MAAM,EAAE;AACxF,QAAM,SAAwC;AAAA,IAC5C,SAAS,aAAa,eAAe,SAAS;AAAA,EAChD;AAGA,QAAM,aAAa,OAAO,KAAK,OAAO,CAAC,EAAG,UAAU;AAGpD,aAAW,YAAY,YAAY;AACjC,UAAM,iBAA+B,OAAO,IAAI,CAAC,OAAO;AAAA,MACtD,MAAM,EAAE;AAAA,MACR,OAAO,EAAE,WAAW,QAAQ;AAAA,IAC9B,EAAE;AACF,WAAO,QAAQ,IAAI,aAAa,gBAAgB,QAAQ;AAAA,EAC1D;AAEA,SAAO;AACT;AAEO,SAAS,gBAAgB,QAAsB,YAAY,GAAiB;AACjF,MAAI,OAAO,SAAS,GAAG;AACrB,WAAO,CAAC;AAAA,EACV;AAEA,QAAM,SAAS,OAAO,IAAI,CAAC,MAAM,EAAE,KAAK;AACxC,QAAM,OAAO,OAAO,OAAO,CAAC,GAAG,MAAM,IAAI,GAAG,CAAC,IAAI,OAAO;AACxD,QAAM,WAAW,OAAO,OAAO,CAAC,KAAK,MAAM,OAAO,IAAI,SAAS,GAAG,CAAC,IAAI,OAAO;AAC9E,QAAM,SAAS,KAAK,KAAK,QAAQ;AAEjC,MAAI,WAAW,GAAG;AAChB,WAAO,CAAC;AAAA,EACV;AAEA,SAAO,OAAO,OAAO,CAAC,MAAM,KAAK,IAAI,EAAE,QAAQ,IAAI,IAAI,YAAY,MAAM;AAC3E;;;AC3FA,IAAM,gBAAgB;AAAA,EACpB,EAAE,OAAO,OAAO,KAAK,GAAG,KAAK,EAAE;AAAA,EAC/B,EAAE,OAAO,QAAQ,KAAK,GAAG,KAAK,GAAG;AAAA,EACjC,EAAE,OAAO,SAAS,KAAK,IAAI,KAAK,GAAG;AAAA,EACnC,EAAE,OAAO,UAAU,KAAK,IAAI,KAAK,IAAI;AACvC;AAEO,SAAS,qBAAqB,SAA0C;AAC7E,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO;AAAA,MACL,cAAc;AAAA,MACd,SAAS,cAAc,IAAI,CAAC,OAAO,EAAE,OAAO,EAAE,OAAO,OAAO,GAAG,SAAS,CAAC,EAAE,EAAE;AAAA,MAC7E,kBAAkB,CAAC;AAAA,IACrB;AAAA,EACF;AAEA,QAAM,UAA2B,cAAc,IAAI,CAAC,UAAU;AAC5D,UAAM,WAAW,QAAQ,OAAO,CAAC,MAAM,EAAE,YAAY,MAAM,OAAO,EAAE,YAAY,MAAM,GAAG;AACzF,WAAO;AAAA,MACL,OAAO,MAAM;AAAA,MACb,OAAO,SAAS;AAAA,MAChB,SAAS;AAAA,IACX;AAAA,EACF,CAAC;AAGD,QAAM,mBAAmB,QACtB,OAAO,CAAC,MAAM,EAAE,YAAY,KAAK,EAAE,YAAY,EAAE,EACjD,KAAK,CAAC,GAAG,MAAM,EAAE,cAAc,EAAE,WAAW;AAE/C,SAAO;AAAA,IACL,cAAc,QAAQ;AAAA,IACtB;AAAA,IACA;AAAA,EACF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package.json

 {
   "name": "@power-seo/analytics",
-  "version": "1.0.4",
+  "version": "1.0.7",
   "description": "Analytics data processing: merge GSC data with audit results, trend analysis, ranking insights",
@@ -20,18 +20,8 @@ "license": "MIT",
   ],
-  "scripts": {
-    "build": "tsup",
-    "dev": "tsup --watch",
-    "test": "vitest run",
-    "test:watch": "vitest",
-    "typecheck": "tsc --noEmit",
-    "lint": "eslint src/",
-    "lint:fix": "eslint src/ --fix",
-    "clean": "rimraf dist"
-  },
   "dependencies": {
-    "@power-seo/core": "workspace:*",
-    "@power-seo/audit": "workspace:*"
+    "@power-seo/core": "1.0.3",
+    "@power-seo/audit": "1.0.7"
   },
   "devDependencies": {
-    "rimraf": "^6.0.0",
+    "rimraf": "^6.1.3",
     "tsup": "^8.3.0",
@@ -59,3 +49,21 @@ "typescript": "^5.7.0",
     "access": "public"
+  },
+  "bugs": {
+    "url": "https://github.com/CyberCraftBD/power-seo/issues"
+  },
+  "homepage": "https://github.com/CyberCraftBD/power-seo/tree/main/packages/analytics#readme",
+  "funding": {
+    "type": "github",
+    "url": "https://github.com/sponsors/cybercraftbd"
+  },
+  "scripts": {
+    "build": "tsup",
+    "dev": "tsup --watch",
+    "test": "vitest run",
+    "test:watch": "vitest",
+    "typecheck": "tsc --noEmit",
+    "lint": "eslint src/",
+    "lint:fix": "eslint src/ --fix",
+    "clean": "rimraf dist"
   }
-}
+}

Fixed alerts

No bug tracker

Maintenance

Package does not have a linked bug tracker in package.json.

Found 1 instance in 1 package

No website

Quality

Package does not have a website.

Found 1 instance in 1 package

Improved metrics

Number of package files

9

12.5%

Lines of code

633

6.75%

Number of low maintenance alerts

0

-100%

Number of low quality alerts

0

-100%

Worsened metrics

Total package byte prevSize

88857

-5.53%

Dependency changes

• + Added

  @power-seo/audit@1.0.7
  (transitive)

• + Added

  @power-seo/content-analysis@1.0.8
  (transitive)

• + Added

  @power-seo/readability@1.0.7
  (transitive)

• + Added

  @power-seo/schema@1.0.8
  (transitive)

• Updated

  @power-seo/audit@1.0.7

• Updated

  @power-seo/core@1.0.3