Scores and ranks influencers for brand partnership fit
Influencer fit scoring

Scores and ranks influencers for brand partnership fit using a multi-dimensional framework covering audience alignment, engagement quality, brand safety, content relevance, and commercial viability for CPG and retail e-commerce…
---
name: influencer-fit-scoring
description: >
Scores and ranks influencers for brand partnership fit using a multi-dimensional framework
covering audience alignment, engagement quality, brand safety, content relevance, and commercial
viability for CPG and retail e-commerce campaigns. Use when evaluating potential influencer
partners, building shortlists, or comparing candidates. Triggers on requests for influencer
evaluation, creator partnerships, influencer scoring, KOL assessment, or ambassador selection.
metadata:
display_name: "Influencer Fit Scoring"
short_description: "Score influencer-brand partnership fit and alignment"
default_prompt: "Score my influencer fit and explain what to improve"
version: "1.0.1"
tags:
- cpg-retail
icon_path: "assets/icon.png"
---Overview
This skill applies a weighted scoring model to evaluate influencer-brand fit across six dimensions: audience alignment, engagement authenticity, content relevance, brand safety, commercial potential, and cost efficiency. It produces a ranked shortlist with composite scores, risk flags, and partnership recommendations tailored to CPG and retail e-commerce objectives.
What you get
- Scored Roster TableAll influencers ranked by composite score with per-dimension breakdowns
- Risk Flag SummaryFlagged influencers with risk type, severity, and recommended action
- Top 10 ShortlistRecommended partners with rationale and suggested partnership tier
- Partnership Structure RecommendationsDeliverables, compensation model, and timeline per tier
- Budget AllocationRecommended spend distribution across influencer tiers
- Competitive IntelligenceNotable competitor influencer partnerships observed
Manual install (npx, ZIP)
npx skills add writer/skills --skill influencer-fit-scoring -g -a claude-codenpx degit writer/skills/skills/influencer-fit-scoring#main ~/.claude/skills/influencer-fit-scoringConnects with Agent Alley MCP · agentalley.io/mcp
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Influencer Fit Scoring
Overview
This skill applies a weighted scoring model to evaluate influencer-brand fit across six dimensions: audience alignment, engagement authenticity, content relevance, brand safety, commercial potential, and cost efficiency. It produces a ranked shortlist with composite scores, risk flags, and partnership recommendations tailored to CPG and retail e-commerce objectives.
When to Use
- Evaluating a list of potential influencer partners for a campaign
- Building a tiered influencer roster (mega, macro, micro, nano)
- Comparing influencer candidates for a specific product launch or promotion
- Assessing existing influencer partnerships for renewal decisions
- Vetting influencers for brand safety and audience authenticity
- Structuring an influencer marketing program from scratch
Required Inputs
| Input | Required | Description |
|---|---|---|
| Influencer Profiles | Yes | Name, handle, platform, follower count, niche/category |
| Brand / Product | Yes | Brand identity, product category, target positioning |
| Campaign Objective | Yes | Awareness, engagement, conversion, content creation, or loyalty |
| Target Audience | Yes | Demographics, interests, geography of desired reach |
| Budget Range | No | Total influencer budget to inform tier recommendations |
| Engagement Metrics | Recommended | Average likes, comments, shares, saves, video views |
| Audience Demographics | Recommended | Follower age, gender, location breakdown (from analytics tools) |
| Past Collaboration Data | No | Previous brand deals, competitor partnerships, performance history |
| Brand Safety Requirements | No | Categories, topics, or associations to avoid |
Methodology
Step 1 — Tier Classification
Categorize each influencer by reach tier:
| Tier | Follower Range | Typical CPG Use Case | Avg. Engagement Rate |
|---|---|---|---|
| Nano | 1K–10K | Authentic advocacy, niche communities | 4%–8% |
| Micro | 10K–100K | Targeted reach, high engagement, UGC | 2%–5% |
| Mid-Tier | 100K–500K | Balanced reach and engagement | 1.5%–3% |
| Macro | 500K–1M | Broad awareness, trend-setting | 1%–2% |
| Mega | 1M+ | Mass awareness, celebrity association | 0.5%–1.5% |
Step 2 — Six-Dimension Scoring Model
Score each influencer on a 0–100 scale across six dimensions:
Dimension 1: Audience Alignment (Weight: 25%)
- Demographic overlap with target audience (age, gender, location)
- Interest category alignment (beauty, food, fitness, parenting, etc.)
- Audience income level proxy (based on content, brand affinities)
- Geographic concentration in target markets
Score = (Demo Match % × 0.4) + (Interest Match % × 0.3) + (Geo Match % × 0.3) × 100
Dimension 2: Engagement Quality (Weight: 20%)
- Engagement rate vs. tier benchmark (above/at/below average)
- Comment quality ratio: meaningful comments ÷ total comments
- Saves and shares ratio (high-intent signals)
- Follower growth trajectory (organic vs. spike patterns)
Score = (ER Percentile × 0.4) + (Comment Quality × 0.3) + (Save/Share Ratio × 0.2) + (Growth Health × 0.1) × 100
Dimension 3: Content Relevance (Weight: 20%)
- Content category alignment with brand/product
- Content production quality (visual, audio, editing)
- Content format match with campaign needs (Reels, long-form, Stories, etc.)
- Organic product integration naturalness (does the creator authentically use similar products?)
Dimension 4: Brand Safety (Weight: 15%)
- Controversial content history scan (political, offensive, polarizing)
- Competitor partnership conflicts (exclusivity concerns)
- FTC compliance history (proper #ad disclosure)
- Audience bot/fake follower percentage (flag if >15%)
- Content tone alignment with brand values
Score = 100 - (Controversy Penalty + Competitor Conflict Penalty + Compliance Risk Penalty + Bot Penalty)
Dimension 5: Commercial Viability (Weight: 10%)
- Previous sponsored content performance (vs. organic benchmarks)
- Product-tagging and link-in-bio utilization (shoppability)
- Track record of driving measurable actions (site traffic, sales, codes redeemed)
- Professional responsiveness and reliability (if data available)
Dimension 6: Cost Efficiency (Weight: 10%)
- Estimated CPM: (Influencer Fee ÷ Estimated Impressions) × 1,000
- Estimated CPE: Influencer Fee ÷ Estimated Engagements
- Benchmarked against tier and platform norms
| Platform | Tier | CPM Benchmark | CPE Benchmark |
|---|---|---|---|
| Micro | $8–$15 | $0.15–$0.40 | |
| Macro | $12–$25 | $0.30–$0.80 | |
| TikTok | Micro | $5–$12 | $0.05–$0.20 |
| TikTok | Macro | $10–$20 | $0.10–$0.35 |
| YouTube | Micro | $15–$30 | $0.25–$0.60 |
| YouTube | Macro | $20–$40 | $0.40–$1.00 |
Step 3 — Composite Score Calculation
Composite Score = (Audience × 0.25) + (Engagement × 0.20) + (Content × 0.20)
+ (Safety × 0.15) + (Commercial × 0.10) + (Cost × 0.10)
Adjust weights based on campaign objective:
- Awareness campaigns: Increase Audience Alignment to 30%, reduce Cost Efficiency to 5%
- Conversion campaigns: Increase Commercial Viability to 20%, reduce Content Relevance to 15%
- Content creation campaigns: Increase Content Relevance to 30%, reduce Audience Alignment to 15%
Step 4 — Risk Flag Assessment
Flag influencers with critical risk indicators:
| Risk Flag | Trigger | Severity |
|---|---|---|
| 🔴 Bot Audience | >20% fake/bot followers | Disqualifying |
| 🔴 Competitor Exclusive | Active deal with direct competitor | Disqualifying |
| 🟡 Controversy History | Past 12 months controversial content | Review Required |
| 🟡 Engagement Anomaly | ER >3× tier average (potential manipulation) | Investigate |
| 🟡 Audience Mismatch | <40% demo overlap with target | Low Priority |
| 🟢 Rate Premium | CPM >2× benchmark | Negotiate |
Step 5 — Shortlist & Tier Recommendation
Rank influencers by composite score and organize into partnership tiers:
- Tier A — Anchor Partners (Top 10%): Long-term ambassadorships, exclusive deals, co-creation
- Tier B — Campaign Partners (Top 11–30%): Campaign-specific collaborations, multi-post packages
- Tier C — Amplification Partners (Top 31–60%): One-off posts, product seeding, affiliate programs
- Below Threshold (Bottom 40%): Not recommended; document reasons
Output Specification
- Scored Roster Table: All influencers ranked by composite score with per-dimension breakdowns
- Risk Flag Summary: Flagged influencers with risk type, severity, and recommended action
- Top 10 Shortlist: Recommended partners with rationale and suggested partnership tier
- Partnership Structure Recommendations: Deliverables, compensation model, and timeline per tier
- Budget Allocation: Recommended spend distribution across influencer tiers
- Competitive Intelligence: Notable competitor influencer partnerships observed
Examples
Input: "Score these 15 food bloggers for our organic snack brand launch on Instagram. Target audience is health-conscious millennials in the US. Budget $50K."
Output: Ranked roster with composite scores. Top 5 micro-influencers (25K–80K followers) score highest due to strong audience alignment (82% health/wellness interest match) and above-average engagement. Two macro influencers flagged for competitor conflict (active partnerships with competing snack brands). Budget allocation: 60% micro (8 creators), 30% mid-tier (3 creators), 10% content licensing.
Input: "Evaluate these 8 TikTok creators for our Gen Z skincare line. We need high conversion potential."
Output: Scoring with Commercial Viability weighted at 20%. Top 3 creators identified with proven affiliate sales history, active TikTok Shop integration, and product-review content style. Two creators flagged for engagement anomalies suggesting potential bot activity. Recommended: 3-creator program with affiliate commission structure + flat fee hybrid.
Guidelines
- Always verify engagement authenticity — inflated metrics waste budget and distort ROI
- Weight dimensions differently based on campaign objective; one size does not fit all
- For CPG, prioritize creators who show organic product usage in their content (not just paid posts)
- Consider content repurposing rights in partnership structure (whitelisting, paid amplification)
- Evaluate audience overlap between shortlisted creators to avoid redundant reach
- For regulated CPG categories (food, supplements), verify creator compliance with FTC/FDA guidelines
- Nano and micro creators typically deliver 3–5× the engagement rate of macro at lower CPMs
- Always check for audience geographic concentration — a US brand needs US-majority audiences
- Recommend a mix of tiers: anchors for credibility, micro for engagement and conversion
Validation Checklist
- All six scoring dimensions are evaluated with documented rationale
- Composite scores use appropriate objective-based weight adjustments
- Risk flags are assigned and disqualifying risks result in removal
- Shortlist includes clear tier assignments with partnership recommendations
- Cost efficiency benchmarks are platform- and tier-specific
- Audience overlap analysis is performed across shortlisted creators
- Budget allocation is realistic and sums to provided budget
- FTC/compliance considerations are addressed for regulated categories
| 1 | |
| 2 | name influencer-fit-scoring |
| 3 | description > |
| 4 | Scores and ranks influencers for brand partnership fit using a multi-dimensional framework |
| 5 | covering audience alignment, engagement quality, brand safety, content relevance, and commercial |
| 6 | viability for CPG and retail e-commerce campaigns. Use when evaluating potential influencer |
| 7 | partners, building shortlists, or comparing candidates. Triggers on requests for influencer |
| 8 | evaluation, creator partnerships, influencer scoring, KOL assessment, or ambassador selection. |
| 9 | |
| 10 | metadata |
| 11 | display_name "Influencer Fit Scoring" |
| 12 | short_description "Score influencer-brand partnership fit and alignment" |
| 13 | default_prompt "Score my influencer fit and explain what to improve" |
| 14 | version "1.0.1" |
| 15 | tags |
| 16 | - cpg-retail |
| 17 | icon_path "assets/icon.png" |
| 18 | |
| 19 | |
| 20 | # Influencer Fit Scoring |
| 21 | |
| 22 | ## Overview |
| 23 | |
| 24 | This skill applies a weighted scoring model to evaluate influencer-brand fit across six dimensions: audience alignment, engagement authenticity, content relevance, brand safety, commercial potential, and cost efficiency. It produces a ranked shortlist with composite scores, risk flags, and partnership recommendations tailored to CPG and retail e-commerce objectives. |
| 25 | |
| 26 | ## When to Use |
| 27 | |
| 28 | Evaluating a list of potential influencer partners for a campaign |
| 29 | Building a tiered influencer roster (mega, macro, micro, nano) |
| 30 | Comparing influencer candidates for a specific product launch or promotion |
| 31 | Assessing existing influencer partnerships for renewal decisions |
| 32 | Vetting influencers for brand safety and audience authenticity |
| 33 | Structuring an influencer marketing program from scratch |
| 34 | |
| 35 | ## Required Inputs |
| 36 | |
| 37 | | Input | Required | Description | |
| 38 | |---|---|---| |
| 39 | | Influencer Profiles | Yes | Name, handle, platform, follower count, niche/category | |
| 40 | | Brand / Product | Yes | Brand identity, product category, target positioning | |
| 41 | | Campaign Objective | Yes | Awareness, engagement, conversion, content creation, or loyalty | |
| 42 | | Target Audience | Yes | Demographics, interests, geography of desired reach | |
| 43 | | Budget Range | No | Total influencer budget to inform tier recommendations | |
| 44 | | Engagement Metrics | Recommended | Average likes, comments, shares, saves, video views | |
| 45 | | Audience Demographics | Recommended | Follower age, gender, location breakdown (from analytics tools) | |
| 46 | | Past Collaboration Data | No | Previous brand deals, competitor partnerships, performance history | |
| 47 | | Brand Safety Requirements | No | Categories, topics, or associations to avoid | |
| 48 | |
| 49 | ## Methodology |
| 50 | |
| 51 | ### Step 1 — Tier Classification |
| 52 | |
| 53 | Categorize each influencer by reach tier: |
| 54 | |
| 55 | | Tier | Follower Range | Typical CPG Use Case | Avg. Engagement Rate | |
| 56 | |---|---|---|---| |
| 57 | | Nano | 1K–10K | Authentic advocacy, niche communities | 4%–8% | |
| 58 | | Micro | 10K–100K | Targeted reach, high engagement, UGC | 2%–5% | |
| 59 | | Mid-Tier | 100K–500K | Balanced reach and engagement | 1.5%–3% | |
| 60 | | Macro | 500K–1M | Broad awareness, trend-setting | 1%–2% | |
| 61 | | Mega | 1M+ | Mass awareness, celebrity association | 0.5%–1.5% | |
| 62 | |
| 63 | ### Step 2 — Six-Dimension Scoring Model |
| 64 | |
| 65 | Score each influencer on a 0–100 scale across six dimensions: |
| 66 | |
| 67 | **Dimension 1: Audience Alignment (Weight: 25%)** |
| 68 | Demographic overlap with target audience (age, gender, location) |
| 69 | Interest category alignment (beauty, food, fitness, parenting, etc.) |
| 70 | Audience income level proxy (based on content, brand affinities) |
| 71 | Geographic concentration in target markets |
| 72 | |
| 73 | |
| 74 | Score = (Demo Match % × 0.4) + (Interest Match % × 0.3) + (Geo Match % × 0.3) × 100 |
| 75 | |
| 76 | |
| 77 | **Dimension 2: Engagement Quality (Weight: 20%)** |
| 78 | Engagement rate vs. tier benchmark (above/at/below average) |
| 79 | Comment quality ratio: meaningful comments ÷ total comments |
| 80 | Saves and shares ratio (high-intent signals) |
| 81 | Follower growth trajectory (organic vs. spike patterns) |
| 82 | |
| 83 | |
| 84 | Score = (ER Percentile × 0.4) + (Comment Quality × 0.3) + (Save/Share Ratio × 0.2) + (Growth Health × 0.1) × 100 |
| 85 | |
| 86 | |
| 87 | **Dimension 3: Content Relevance (Weight: 20%)** |
| 88 | Content category alignment with brand/product |
| 89 | Content production quality (visual, audio, editing) |
| 90 | Content format match with campaign needs (Reels, long-form, Stories, etc.) |
| 91 | Organic product integration naturalness (does the creator authentically use similar products?) |
| 92 | |
| 93 | **Dimension 4: Brand Safety (Weight: 15%)** |
| 94 | Controversial content history scan (political, offensive, polarizing) |
| 95 | Competitor partnership conflicts (exclusivity concerns) |
| 96 | FTC compliance history (proper #ad disclosure) |
| 97 | Audience bot/fake follower percentage (flag if >15%) |
| 98 | Content tone alignment with brand values |
| 99 | |
| 100 | |
| 101 | Score = 100 - (Controversy Penalty + Competitor Conflict Penalty + Compliance Risk Penalty + Bot Penalty) |
| 102 | |
| 103 | |
| 104 | **Dimension 5: Commercial Viability (Weight: 10%)** |
| 105 | Previous sponsored content performance (vs. organic benchmarks) |
| 106 | Product-tagging and link-in-bio utilization (shoppability) |
| 107 | Track record of driving measurable actions (site traffic, sales, codes redeemed) |
| 108 | Professional responsiveness and reliability (if data available) |
| 109 | |
| 110 | **Dimension 6: Cost Efficiency (Weight: 10%)** |
| 111 | Estimated CPM: (Influencer Fee ÷ Estimated Impressions) × 1,000 |
| 112 | Estimated CPE: Influencer Fee ÷ Estimated Engagements |
| 113 | Benchmarked against tier and platform norms |
| 114 | |
| 115 | | Platform | Tier | CPM Benchmark | CPE Benchmark | |
| 116 | |---|---|---|---| |
| 117 | | Instagram | Micro | $8–$15 | $0.15–$0.40 | |
| 118 | | Instagram | Macro | $12–$25 | $0.30–$0.80 | |
| 119 | | TikTok | Micro | $5–$12 | $0.05–$0.20 | |
| 120 | | TikTok | Macro | $10–$20 | $0.10–$0.35 | |
| 121 | | YouTube | Micro | $15–$30 | $0.25–$0.60 | |
| 122 | | YouTube | Macro | $20–$40 | $0.40–$1.00 | |
| 123 | |
| 124 | ### Step 3 — Composite Score Calculation |
| 125 | |
| 126 | |
| 127 | Composite Score = (Audience × 0.25) + (Engagement × 0.20) + (Content × 0.20) |
| 128 | + (Safety × 0.15) + (Commercial × 0.10) + (Cost × 0.10) |
| 129 | |
| 130 | |
| 131 | Adjust weights based on campaign objective: |
| 132 | **Awareness campaigns**: Increase Audience Alignment to 30%, reduce Cost Efficiency to 5% |
| 133 | **Conversion campaigns**: Increase Commercial Viability to 20%, reduce Content Relevance to 15% |
| 134 | **Content creation campaigns**: Increase Content Relevance to 30%, reduce Audience Alignment to 15% |
| 135 | |
| 136 | ### Step 4 — Risk Flag Assessment |
| 137 | |
| 138 | Flag influencers with critical risk indicators: |
| 139 | |
| 140 | | Risk Flag | Trigger | Severity | |
| 141 | |---|---|---| |
| 142 | | 🔴 Bot Audience | >20% fake/bot followers | Disqualifying | |
| 143 | | 🔴 Competitor Exclusive | Active deal with direct competitor | Disqualifying | |
| 144 | | 🟡 Controversy History | Past 12 months controversial content | Review Required | |
| 145 | | 🟡 Engagement Anomaly | ER >3× tier average (potential manipulation) | Investigate | |
| 146 | | 🟡 Audience Mismatch | <40% demo overlap with target | Low Priority | |
| 147 | | 🟢 Rate Premium | CPM >2× benchmark | Negotiate | |
| 148 | |
| 149 | ### Step 5 — Shortlist & Tier Recommendation |
| 150 | |
| 151 | Rank influencers by composite score and organize into partnership tiers: |
| 152 | |
| 153 | **Tier A — Anchor Partners** (Top 10%): Long-term ambassadorships, exclusive deals, co-creation |
| 154 | **Tier B — Campaign Partners** (Top 11–30%): Campaign-specific collaborations, multi-post packages |
| 155 | **Tier C — Amplification Partners** (Top 31–60%): One-off posts, product seeding, affiliate programs |
| 156 | **Below Threshold** (Bottom 40%): Not recommended; document reasons |
| 157 | |
| 158 | ## Output Specification |
| 159 | |
| 160 | **Scored Roster Table**: All influencers ranked by composite score with per-dimension breakdowns |
| 161 | **Risk Flag Summary**: Flagged influencers with risk type, severity, and recommended action |
| 162 | **Top 10 Shortlist**: Recommended partners with rationale and suggested partnership tier |
| 163 | **Partnership Structure Recommendations**: Deliverables, compensation model, and timeline per tier |
| 164 | **Budget Allocation**: Recommended spend distribution across influencer tiers |
| 165 | **Competitive Intelligence**: Notable competitor influencer partnerships observed |
| 166 | |
| 167 | ## Examples |
| 168 | |
| 169 | **Input**: "Score these 15 food bloggers for our organic snack brand launch on Instagram. Target audience is health-conscious millennials in the US. Budget $50K." |
| 170 | |
| 171 | **Output**: Ranked roster with composite scores. Top 5 micro-influencers (25K–80K followers) score highest due to strong audience alignment (82% health/wellness interest match) and above-average engagement. Two macro influencers flagged for competitor conflict (active partnerships with competing snack brands). Budget allocation: 60% micro (8 creators), 30% mid-tier (3 creators), 10% content licensing. |
| 172 | |
| 173 | **Input**: "Evaluate these 8 TikTok creators for our Gen Z skincare line. We need high conversion potential." |
| 174 | |
| 175 | **Output**: Scoring with Commercial Viability weighted at 20%. Top 3 creators identified with proven affiliate sales history, active TikTok Shop integration, and product-review content style. Two creators flagged for engagement anomalies suggesting potential bot activity. Recommended: 3-creator program with affiliate commission structure + flat fee hybrid. |
| 176 | |
| 177 | ## Guidelines |
| 178 | |
| 179 | Always verify engagement authenticity — inflated metrics waste budget and distort ROI |
| 180 | Weight dimensions differently based on campaign objective; one size does not fit all |
| 181 | For CPG, prioritize creators who show organic product usage in their content (not just paid posts) |
| 182 | Consider content repurposing rights in partnership structure (whitelisting, paid amplification) |
| 183 | Evaluate audience overlap between shortlisted creators to avoid redundant reach |
| 184 | For regulated CPG categories (food, supplements), verify creator compliance with FTC/FDA guidelines |
| 185 | Nano and micro creators typically deliver 3–5× the engagement rate of macro at lower CPMs |
| 186 | Always check for audience geographic concentration — a US brand needs US-majority audiences |
| 187 | Recommend a mix of tiers: anchors for credibility, micro for engagement and conversion |
| 188 | |
| 189 | ## Validation Checklist |
| 190 | |
| 191 | [ ] All six scoring dimensions are evaluated with documented rationale |
| 192 | [ ] Composite scores use appropriate objective-based weight adjustments |
| 193 | [ ] Risk flags are assigned and disqualifying risks result in removal |
| 194 | [ ] Shortlist includes clear tier assignments with partnership recommendations |
| 195 | [ ] Cost efficiency benchmarks are platform- and tier-specific |
| 196 | [ ] Audience overlap analysis is performed across shortlisted creators |
| 197 | [ ] Budget allocation is realistic and sums to provided budget |
| 198 | [ ] FTC/compliance considerations are addressed for regulated categories |
| 199 |
Details
- License
- Apache-2.0
- Stars on the repo
- ★ 7
- Checked
- Source
- writer/skills ↗
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