Meta Ads Lead Gen Analysis

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[Didoo AI] Specialized analysis module for Meta lead generation campaigns. Use when CPL is elevated, lead quality is unclear, or you need to diagnose why leads aren't converting downstream. For general campaign analysis, use meta-ads-analysis.

Install

openclaw skills install @elias-didoo/meta-ads-lead-gen-analysis

Required Credentials

Credential	Where to Get	Used For	OAuth Scope
META_ACCESS_TOKEN	Meta Developer Console → Graph API Explorer → Generate Token	Fetching campaign and form integration data	`ads_read` (read-only)
META_AD_ACCOUNT_ID	Ads Manager URL: `adsmanager.facebook.com/act_XXXXXXXXX`	Identifying which account to query	—

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.

Key Differences from E-commerce Analysis

Metric	E-commerce Benchmark	Lead Gen Benchmark	Why It Differs
LPV Rate	> 70% is healthy	> 50% is healthy	Many leads browse without intent to submit
Form Submit Rate	N/A	> 20% is healthy	Form friction is the primary drop-off point
CPL	Varies by industry	The primary metric	What you're actually paying for
CVR (post-click)	Purchase rate	Lead-to-qualified rate	Meta can't see what happens after form submit
Attribution	1-day or 7-day click	7-day click usually	Longer window for consideration

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?

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:

Go to Meta Events Manager → select your pixel
Check "About CAPI" — status should be green/active
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)

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

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.

Session Context — What This Skill Writes

After completing analysis, store the following in session context:

Key	Description	Example
lp_diagnosis	Funnel stage causing the CPL problem	"Form friction — submit rate 12%, below 20% benchmark"
capi_status	Whether offline leads are being sent to Meta	"Not connected — offline lead data not flowing"
cpl_breakdown	Which stage is the bottleneck	"LPV 65% OK; Form submit 11% is the bottleneck"
recommended_fix_priority	Ranked fix order	"1. CAPI 2. Form fields 3. Audience"

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

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.

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