Quality Score Optimization

# Quality Score Optimization

Part of [Agent Skills™](https://github.com/itallstartedwithaidea/agent-skills) by [googleadsagent.ai™](https://googleadsagent.ai)

## Description

The Quality Score Optimization skill provides a systematic framework for diagnosing, tracking, and improving Quality Score across every keyword in a Google Ads account. Quality Score is Google's 1-10 rating of the overall relevance and quality of your keywords, ads, and landing pages. It directly impacts ad rank, cost-per-click, and whether your ads show at all. A one-point Quality Score improvement can reduce CPCs by 10-15%.

The skill decomposes Quality Score into its three sub-components — Expected Click-Through Rate (eCTR), Ad Relevance, and Landing Page Experience — and provides targeted improvement strategies for each. It goes beyond the current snapshot by tracking historical Quality Score trends at the keyword level, identifying score degradation patterns, and correlating changes with account modifications. This longitudinal analysis reveals the root causes behind score fluctuations.

The optimization engine prioritizes improvement efforts by weighting keywords by spend volume. A Quality Score improvement on a keyword consuming $1,000/day has far greater impact than the same improvement on a $5/day keyword. The skill generates impact-ranked improvement plans, estimates CPC savings, and tracks improvement progress against benchmarks specific to each industry vertical.

## Use When

- User asks about "Quality Score" or "QS optimization"
- User mentions "high CPCs" that may relate to quality issues
- User wants to "improve ad rank" without increasing bids
- User asks about "expected CTR", "ad relevance", or "landing page experience"
- User mentions "below average" quality components
- User wants to "reduce cost per click" through quality improvements
- User asks "why aren't my ads showing" (may be QS related)
- User wants to "track Quality Score changes over time"

## Architecture

```mermaid
flowchart TD
    A[Google Ads API:\nKeyword Quality Data] --> B[QS Data Extraction]

    B --> C[Current QS Snapshot]
    B --> D[Historical QS Tracking]
    B --> E[Sub-Component Breakdown]

    E --> F[Expected CTR Analysis]
    E --> G[Ad Relevance Analysis]
    E --> H[Landing Page Experience Analysis]

    F --> I[CTR Improvement Engine]
    I --> I1[Ad Copy Testing]
    I --> I2[Ad Extension Optimization]
    I --> I3[Audience Refinement]

    G --> J[Relevance Improvement Engine]
    J --> J1[Keyword-Ad Alignment]
    J --> J2[Ad Group Restructuring]
    J --> J3[DKI Opportunities]

    H --> K[Landing Page Improvement Engine]
    K --> K1[Page Speed Optimization]
    K --> K2[Content Relevance Matching]
    K --> K3[Mobile Experience Audit]

    I1 --> L[Spend-Weighted Priority Ranker]
    I2 --> L
    I3 --> L
    J1 --> L
    J2 --> L
    J3 --> L
    K1 --> L
    K2 --> L
    K3 --> L

    L --> M[QS Improvement Plan]
    M --> N[Estimated CPC Savings]
    M --> O[Implementation Roadmap]
    M --> P[Progress Tracking Dashboard]
```

## Implementation

Quality Score extraction and analysis engine:

```javascript
async function analyzeQualityScores(customerId) {
  const keywordData = await getKeywordQualityData(customerId);

  const analysis = keywordData.map(kw => ({
    keyword: kw.text,
    matchType: kw.matchType,
    qualityScore: kw.qualityScore,
    expectedCtr: kw.expectedCtr,
    adRelevance: kw.adRelevance,
    landingPageExperience: kw.landingPageExperience,
    monthlySpend: kw.costMicros / 1_000_000,
    impressions: kw.impressions,
    weightedImpact: calculateWeightedImpact(kw)
  }));

  return {
    distribution: buildQSDistribution(analysis),
    bottomKeywords: analysis.filter(kw => kw.qualityScore <= 5)