LinkedIn Ads Deep Analysis

Process

1. Collect LinkedIn Ads data (Campaign Manager export, Insight Tag status)
2. Read ads/references/linkedin-audit.md for full 25-check audit
3. Read ads/references/benchmarks.md for LinkedIn-specific benchmarks
4. Read ads/references/scoring-system.md for weighted scoring
5. Evaluate all applicable checks as PASS, WARNING, or FAIL
6. Calculate LinkedIn Ads Health Score (0-100)
7. Generate findings report with action plan

What to Analyze

Technical Setup (25% weight)

• Insight Tag installed and firing on all pages (L01)
• Conversions API (CAPI) active — launched 2025 (L02)
• Conversion events configured for full funnel
• Revenue attribution tracking enabled

Audience Targeting (25% weight)

• Job title targeting uses specific titles, not just functions (L03)
• Company size filtering matches ICP (L04)
• Seniority level appropriate for offer (L05)
• Matched Audiences active: retargeting + contact lists (L06)
• ABM company lists uploaded (up to 300,000 companies) (L07)
• Audience expansion OFF for precision campaigns, ON for scale (L08)
• Predictive audiences tested — replaced Lookalikes Feb 2024 (L09)

Creative Quality (20% weight)

• Thought Leader Ads active, ≥30% budget allocation for B2B (L10)
• Ad format diversity: ≥2 formats tested (L11)
• Video ads tested (L12)
• Creative refresh every 4-6 weeks (L13)

Lead Gen & Performance (15% weight)

• Lead Gen Form ≤5 fields (13% CVR benchmark) (L14)
• Lead Gen Form synced to CRM in real-time (L15)
• Campaign objective matches funnel stage (L18)
• A/B testing active: creative or audience (L19)
• Message ad frequency ≤1 per 30-45 days (L20)

Bidding & Budget (15% weight)

• Bid strategy: CPS for Messages, Max Delivery for Content (L16)
• Daily budget ≥$50 for Sponsored Content (L17)
• CTR ≥0.44% for Sponsored Content (L21)
• CPC within benchmark: $5-7 average, senior $6.40+ (L22)
• Lead-to-opportunity rate tracked, not just CPL (L23)
• Attribution: 30-day click / 7-day view configured (L24)
• Demographics report reviewed monthly (L25)

Thought Leader Ads (TLA) Assessment

Thought Leader Ads use employee/executive personal posts as sponsored content:

• CPC typically $2.29-$4.14 vs $13.23 for standard Sponsored Content
• CTR typically 2-3x higher than corporate-branded ads
• Best for: B2B thought leadership, brand awareness, engagement

Evaluate:

• Are TLAs being used? (If not, HIGH priority recommendation)
• Are they getting ≥30% of total LinkedIn budget?
• Are the right employees selected (industry credibility, active posters)?
• Is post content authentic and valuable (not salesy)?

ABM Strategy Assessment

For B2B Enterprise accounts:

• Company list uploaded and segmented by tier (Tier 1, 2, 3)
• Custom content per tier (personalized messaging)
• Account penetration tracking (contacts reached per target account)
• Integration with CRM/ABM platform (Demandbase, 6sense, etc.)

LinkedIn Context

Setting	Value
Minimum audience size	500 (for ads to run)
Lead Gen Form CVR benchmark	13%
TLA CPC range	$2.29-$4.14
Standard SC CPC	$13.23 average
Hierarchy rename	Oct 2025 (Campaign Group → Campaign → Ad)
Predictive Audiences	Replaced Lookalikes Feb 2024

Key Thresholds

Metric	Pass	Warning	Fail
CTR (Sponsored Content)	≥0.44%	0.30-0.44%	<0.30%
CPC (average)	≤$7.00	$7-10	>$10.00
Lead Gen CVR	≥10%	5-10%	<5%
Message frequency	≤1/30 days	1/15-30 days	>1/15 days
TLA budget share	≥30%	15-30%	<15%

Output

LinkedIn Ads Health Score

LinkedIn Ads Health Score: XX/100 (Grade: X)

Technical Setup:   XX/100  ████████░░  (25%)
Audience:          XX/100  ██████████  (25%)
Creative:          XX/100  ███████░░░  (20%)
Lead Gen:          XX/100  █████░░░░░  (15%)
Budget & Bidding:  XX/100  ████████░░  (15%)

Deliverables

• LINKEDIN-ADS-REPORT.md — Full 25-check findings with pass/warning/fail
• TLA adoption roadmap (if not using)
• ABM strategy recommendations (for B2B)
• Lead Gen Form optimization priorities
• Quick Wins sorted by impact

HYROS Cross-Reference (Optional)

When output/hyros_data.json is available, enrich this analysis with independent attribution data:

1. Check if output/hyros_data.json exists (run fetch_hyros_data.py if not)
2. Read HYROS data and extract LinkedIn attribution from attribution.platform_attribution.linkedin
3. Compare LinkedIn-reported leads/conversions vs HYROS attribution
4. Flag LinkedIn over-reporting (common for B2B with long sales cycles)
5. Use HYROS to track full lead-to-close attribution that LinkedIn can't see

Metric	LinkedIn-Reported	HYROS-Attributed	Variance
Conversions	X	Y	Z%
Revenue	$X	$Y	Z%
ROAS	X.Xx	Y.Yx	Z%

LinkedIn typically over-reports by 15-30% due to long B2B sales cycles and view-through attribution. HYROS is especially valuable for B2B where the full lead → MQL → SQL → close path spans weeks or months.

If HYROS data is NOT available, skip this section entirely.