Meta Ads Lead Gen Analysis

Required Credentials

When to Use

When running lead generation campaigns and standard e-commerce analysis logic doesn't apply. Specifically for:

• CPL is higher than expected or target
• Lead volume is healthy but conversion rate to closed deals is low (quality problem)
• LPV rate looks fine but form submit rate is unknown
• CAPI may not be sending offline lead data back to Meta
• Not sure if the problem is the ad, the audience, or the form itself

Lead gen has fundamentally different metrics than e-commerce — standard CVR and LPV benchmarks don't apply. Use this skill instead of applying e-commerce logic to lead gen campaigns.

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Key Differences from E-commerce Analysis

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Step 1: Gather Lead Gen Specific Data

Pull these metrics at the campaign and adset level:

• Spend, impressions, CTR
• LPV Rate (Landing Page View rate = landing page views / link clicks)
• Form Submit Rate (if available — requires CAPI or form integration)
• CPL (cost per lead)
• Frequency
• Lead volume vs. prior period

Also ask the user:

• What does a "good lead" look like for their business?
• What's their lead-to-close rate historically?
• Are they using CAPI to send offline lead data back to Meta?

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Step 2: CAPI Verification — Critical for Lead Gen

Without CAPI sending offline lead data back to Meta:

• Meta is optimizing for form submissions, not qualified leads
• CPL shown may be "form submit cost" not "actual lead cost"
• The algorithm can't learn which leads actually convert

How to verify CAPI is connected:

1. Go to Meta Events Manager → select your pixel
2. Check "About CAPI" — status should be green/​active
3. Ask: are offline leads (calls, CRM-qualified leads) being sent back via CAPI?

If CAPI is NOT connected for offline leads:

• This is a priority fix — it will lower CPL over 2–3 weeks
• Recommend a CRM integration or Zapier/​Make workflow
• Or use Meta's Lead Forms (form submission = conversion automatically tracked)

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Step 3: Audience Targeting Analysis for Lead Gen

Cold Audiences (Interest-Based Targeting)

• Interest targeting works for cold audiences
• Frequency builds fast — limit budget to avoid rapid fatigue
• Test narrower interest layers (2–3 stacked interests, not broad categories)

Custom Audiences (Retargeting and Lookalikes)

• Website visitors (pixel): typically highest conversion rate
• Email lists (matched audiences): strong for existing customer re-engagement
• Lookalikes (LAL): based on converter audiences, quality depends on seed list quality
• Test LAL layers 1–3% first — wider LAL = lower quality but more volume

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Step 4: Format Output

Lead Gen Health Summary:

• Spend / CPL / Lead Volume
• LPV Rate vs. benchmark (> 50% healthy for lead gen)
• Form Submit Rate (if available)
• CAPI Status (connected / not connected)

SECTION 1: CAPI Gap (if applicable)

State whether offline lead data is being sent to Meta. Impact: algorithm is optimizing for quantity, not quality.

SECTION 2: Audience Diagnosis

Diagnose targeting based on frequency and CPL — is the audience too broad or well-matched?

SECTION 3: Funnel Stage

Identify the CPL bottleneck stage:

• LPV < 50% → Ad-to-Form disconnect
• LPV ≥ 50% but low leads → Form friction (check form fields)
• LPV and CVR OK but CPL high → Audience mismatch or CAPI not connected

LP Landing Page diagnosis: The full LP disconnect diagnostic (Step 4a–4d) lives in meta-ads-recommendation → Step 4. This skill identifies the funnel stage; recommendation prescribes the fix.

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Session Context — What This Skill Writes

After completing analysis, store the following in session context:

meta-ads-recommendation reads these keys to produce the lead gen action plan.

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Key Collision Resolution

⚠️ Key priority: meta-ads-analysis writes lp_diagnosis_general; this skill writes lp_diagnosis (the lead-gen-specific version). meta-ads-recommendation is configured to prefer lp_diagnosis when available — so running both skills in sequence does NOT cause overwriting. The two keys coexist.

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Rules

• Apply lead gen benchmarks, not e-commerce benchmarks
• Always verify CAPI status before diagnosing CPL issues — missing CAPI is the most common cause of misleading CPL data
• Do not recommend creative changes if form friction is the bottleneck
• Do not recommend audience changes if LPV rate indicates a page problem
• This is analysis only — recommendations route to meta-ads-recommendation