Add leadform campaign detection and log notes for attribution discrepancies

- Detect courses with _leadform companion campaigns before first pass
- Add ℹ️ LEADFORM note in Log for campaigns that use Google's native lead form (leads bypass the website and don't reach Airtable)
- Add ⚠️ LEADFORM COMPANION note for sibling campaigns of the same course (explains conversion count discrepancy)
- Also moves _course_num and courses_with_both detection to pre-pass (before first loop) so PMX analysis uses correct leads_grupo

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Jose Manuel 2026-04-25 16:32:38 +02:00
parent 9edd74b9ad
commit 369bca604e

86
run.py
View File

@ -125,6 +125,32 @@ def run():
print(f"{len(campaigns)} campañas con actividad este mes")
print("→ Analizando...\n")
# Detección anticipada de cursos con Search Y PMX simultáneos
def _course_num(name: str) -> str | None:
m = re.search(r'fco_(?:search|pmx)_(\d+)', name, re.IGNORECASE)
return m.group(1) if m else None
course_types_pre: dict[str, set] = {}
for c in campaigns:
num = _course_num(c["curso"])
if num:
course_types_pre.setdefault(num, set())
if "pmx" in c["curso"].lower():
course_types_pre[num].add("pmx")
elif "search" in c["curso"].lower():
course_types_pre[num].add("search")
courses_with_both = {
num for num, types in course_types_pre.items()
if "pmx" in types and "search" in types
}
# Detección anticipada de cursos con campaña _leadform activa
courses_with_leadform = {
_course_num(c["curso"])
for c in campaigns
if "_leadform" in c["curso"].lower() and _course_num(c["curso"])
}
# === PRIMERA PASADA: recopilar datos de todas las campañas ===
collected = []
skipped = []
@ -150,12 +176,21 @@ def run():
google_status,
))
analysis = analyze(campaign, leads, metrics)
# Para PMX con companion Search: usar conversiones Google como leads de análisis
course_num = _course_num(campaign["curso"])
is_pmx_with_companion = (
"pmx" in campaign["curso"].lower()
and course_num in courses_with_both
)
leads_grupo = int(metrics.get("conversions", 0)) if is_pmx_with_companion else leads
analysis = analyze(campaign, leads_grupo, metrics)
decision = decide(analysis)
collected.append({
"campaign": campaign,
"leads": leads,
"leads_grupo": leads_grupo,
"metrics": metrics,
"analysis": analysis,
"decision": decision,
@ -174,23 +209,6 @@ def run():
# Ordenar: 0=críticas → 1=no críticas → 2=mantener
collected.sort(key=_priority)
# Detectar cursos con campaña Search Y PMX simultáneas (posible reatribución PMX)
def _course_num(name: str) -> str | None:
m = re.search(r'fco_(?:search|pmx)_(\d+)', name, re.IGNORECASE)
return m.group(1) if m else None
course_types: dict[str, set] = {}
for item in collected:
name = item["campaign"]["curso"]
num = _course_num(name)
if num:
course_types.setdefault(num, set())
if "pmx" in name.lower():
course_types[num].add("pmx")
elif "search" in name.lower():
course_types[num].add("search")
courses_with_both = {num for num, types in course_types.items() if "pmx" in types and "search" in types}
# === SEGUNDA PASADA: imprimir en orden + aplicar decisiones ===
resumen = []
advice_updates = [] # (gcm_record_id, consejo, criticidad) para batch update final
@ -258,6 +276,13 @@ def run():
if "search" in campaign["curso"].lower() and course_num in courses_with_both:
log_text += " | ⚠️ PMX ATTRIBUTION: campaña Search con companion PMX activo — parte de las conversiones de Google pueden estar reatribuidas a la campaña PMX"
# Nota leadform: los leads se capturan en Google sin pasar por la web
is_leadform = "_leadform" in campaign["curso"].lower()
if is_leadform:
log_text += " | LEADFORM: leads capturados directamente en Google (sin visitar la web) — no llegan a Airtable"
elif course_num in courses_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"
advice_updates.append((
campaign["airtable_id"],
decision.get("consejo", ""),
@ -286,26 +311,15 @@ def run():
print(" ✓ Consejos y criticidad guardados.")
# Snapshot diario: ConvLeadsLakeMesFinal + ConvLeadsLakeMesGrupo
# Para PMX con Search companion del mismo curso, Grupo = leads del Search
course_search_leads = {
_course_num(item["campaign"]["curso"]): item["leads"]
for item in collected
if "search" in item["campaign"]["curso"].lower()
and _course_num(item["campaign"]["curso"])
}
final_leads_data = []
for item in collected:
name = item["campaign"]["curso"]
num = _course_num(name)
if num and "pmx" in name.lower() and num in courses_with_both:
grupo = course_search_leads.get(num, item["leads"])
else:
grupo = item["leads"]
final_leads_data.append({
# PMX con companion Search → Grupo = conversiones Google (ya calculado en leads_grupo)
final_leads_data = [
{
"airtable_id": item["campaign"]["airtable_id"],
"conv_leads_lake_mes": item["leads"],
"conv_leads_lake_mes_grupo": grupo,
})
"conv_leads_lake_mes_grupo": item["leads_grupo"],
}
for item in collected
]
if final_leads_data:
print(f"→ Actualizando ConvLeadsLakeMesFinal ({len(final_leads_data)} registros)...")
at.batch_update_gacampaignmes_final_leads(final_leads_data)