Fix leadform attribution: sum PMX + leadform conversions for margin analysis

- Add get_monthly_metrics_all() bulk method to GoogleAdsClient
- Use bulk fetch in first pass instead of N individual API calls
- Pre-compute leadform conversions per course number
- For PMX campaigns with leadform companion, leads_grupo = PMX conv + leadform conv
- fco_pmx_60 now correctly shows 334 leads at 61% margin (was negative)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

google_ads_client.py

@@ -133,6 +133,66 @@ class GoogleAdsClient:
             print(f"  ❌ Error obteniendo métricas mensuales: {e}")
         return result
 
+    def get_monthly_metrics_all(self) -> dict:
+        """
+        Métricas del mes en curso para TODAS las campañas en una sola query.
+        Retorna dict {campaign_id: {cost, conversions, clicks, impressions, ctr,
+                                    status, budget_daily, budget_resource_name, name}}.
+        """
+        ga_service = self.client.get_service("GoogleAdsService")
+        query = """
+            SELECT
+                campaign.id,
+                campaign.name,
+                campaign.status,
+                campaign_budget.amount_micros,
+                campaign_budget.resource_name,
+                metrics.cost_micros,
+                metrics.conversions,
+                metrics.clicks,
+                metrics.impressions
+            FROM campaign
+            WHERE campaign.status != 'REMOVED'
+              AND segments.date DURING THIS_MONTH
+        """
+        raw: dict = {}
+        try:
+            response = ga_service.search(customer_id=self.customer_id, query=query)
+            for row in response:
+                cid = str(row.campaign.id)
+                if cid not in raw:
+                    raw[cid] = {
+                        "name":                 row.campaign.name,
+                        "status":               row.campaign.status.name,
+                        "budget_daily":         row.campaign_budget.amount_micros / 1_000_000,
+                        "budget_resource_name": row.campaign_budget.resource_name,
+                        "cost": 0.0, "conversions": 0.0, "clicks": 0, "impressions": 0,
+                    }
+                m = row.metrics
+                raw[cid]["cost"]        += m.cost_micros / 1_000_000
+                raw[cid]["conversions"] += m.conversions
+                raw[cid]["clicks"]      += m.clicks
+                raw[cid]["impressions"] += m.impressions
+        except GoogleAdsException as e:
+            print(f"  ❌ Error obteniendo métricas mensuales bulk: {e}")
+
+        result = {}
+        for cid, d in raw.items():
+            imp = d["impressions"]
+            result[cid] = {
+                "campaign_id":          cid,
+                "name":                 d["name"],
+                "status":               d["status"],
+                "budget_daily":         round(d["budget_daily"], 2),
+                "budget_resource_name": d["budget_resource_name"],
+                "cost":                 round(d["cost"], 2),
+                "conversions":          d["conversions"],
+                "clicks":               d["clicks"],
+                "impressions":          imp,
+                "ctr":                  round(d["clicks"] / imp * 100, 2) if imp > 0 else 0.0,
+            }
+        return result
+
     def get_campaign_metrics(self, campaign_id: str) -> dict:
         """Métricas del mes en curso para una campaña concreta (acumulado mensual)."""
         ga_service = self.client.get_service("GoogleAdsService")

run.py

@@ -156,6 +156,15 @@ def run():
         if "_leadform" in c["curso"].lower() and _course_num(c["curso"])
     }
 
+    # Precomputar conversiones Google de cada campaña leadform por número de curso
+    leadform_conv_by_course: dict[str, int] = {}
+    for c in campaigns:
+        if "_leadform" in c["curso"].lower():
+            num = _course_num(c["curso"])
+            if num:
+                lf_conv = int(monthly_metrics.get(c["google_campaign_id"], {}).get("conversions", 0))
+                leadform_conv_by_course[num] = leadform_conv_by_course.get(num, 0) + lf_conv
+
     # === PRIMERA PASADA: recopilar datos de todas las campañas ===
     collected = []
     skipped = []
@@ -167,7 +176,7 @@ def run():
         leads, lead_ids = at.get_leads_this_month_gads(cid, campaign["curso"])
         at.update_gacampaignmes_leads_lake(campaign["airtable_id"], lead_ids)
 
-        metrics = gads.get_campaign_metrics(cid)
+        metrics = monthly_metrics.get(cid)
         if not metrics:
             skipped.append(f"[{cid}] {campaign['curso']}")
             continue
@@ -181,13 +190,20 @@ def run():
                 google_status,
             ))
 
-        # Para PMX con companion Search: usar conversiones Google como leads de análisis
         course_num = _course_num(campaign["curso"])
-        is_pmx_with_companion = (
+        is_pmx = "pmx" in campaign["curso"].lower() and "_leadform" not in campaign["curso"].lower()
-            "pmx" in campaign["curso"].lower()
+
-            and course_num in courses_with_both
+        # PMX con companion Search: conversiones Google del PMX (search fluye hacia PMX)
-        )
+        is_pmx_with_companion = is_pmx and course_num in courses_with_both
-        leads_grupo = int(metrics.get("conversions", 0)) if is_pmx_with_companion else leads
+        # PMX con companion Leadform: conv PMX + conv leadform (leads no llegan a Airtable)
+        is_pmx_with_leadform  = is_pmx and course_num in courses_with_leadform
+
+        if is_pmx_with_leadform:
+            leads_grupo = int(metrics.get("conversions", 0)) + leadform_conv_by_course.get(course_num, 0)
+        elif is_pmx_with_companion:
+            leads_grupo = int(metrics.get("conversions", 0))
+        else:
+            leads_grupo = leads
 
         analysis = analyze(campaign, leads_grupo, metrics)
         decision = decide(analysis)
@@ -200,6 +216,7 @@ def run():
             "analysis": analysis,
             "decision": decision,
             "today_metrics": today_metrics.get(cid, {}),
+            "is_pmx_with_leadform": is_pmx_with_leadform,
         })
 
     # Actualizar status en GACampaignMes y Google Ads Campaigns
@@ -293,8 +310,9 @@ def run():
         is_leadform = "_leadform" in campaign["curso"].lower()
         if is_leadform:
             log_text += " | ℹ️ LEADFORM: leads capturados directamente en Google (sin visitar la web) — no llegan a Airtable"
-        elif course_num in courses_with_leadform:
+        elif item.get("is_pmx_with_leadform"):
-            log_text += " | ⚠️ LEADFORM COMPANION: existe una campaña _leadform activa para este curso — parte de las conversiones de Google pueden provenir de leads capturados directamente en Google"
+            lf_conv = leadform_conv_by_course.get(course_num, 0)
+            log_text += f" | ℹ️ LEADFORM COMPANION: {lf_conv} conv leadform sumadas a leads_grupo para este curso"
 
         # Métricas diarias: coste hoy, ingreso (conversiones × PPL) y margen
         coste_hoy   = round(today_m.get("cost", 0), 2)