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Andrew Perpetua — เรียนรู้เกี่ยวกับ Facebook Ads
Andrew Perpetua และ Facebook Ads
Andrew Perpetua เป็นผู้เชี่ยวชาญ Facebook Ads เคยทำงานที่ Meta ดูแล Ads Products มีประสบการณ์มากกว่า 10 ปี Performance Marketing แชร์ความรู้ผ่าน Blog และ Social Media
เนื้อหาเกี่ยวข้อง — ทำความเข้าใจ Gain คืออะไร — ทุกสิ่งที่ต้องรู้ในปี 2026
แนวคิดหลักของ Andrew Perpetua คือใช้ Data-driven Approach ทดสอบ Creative อย่างเป็นระบบ ให้ Algorithm ทำงาน ไม่ Over-optimize ด้วยมือ
แนะนำเพิ่มเติม — อ่านเพิ่มเติมที่ SiamCafeBook
เนื้อหาเกี่ยวข้อง — WordPress WooCommerce Shift Left Security —
เนื้อหาเกี่ยวข้อง — บทความที่เกี่ยวข้อง: Python Click CLI Container Orchestration
Campaign Structure และ Setup
# === Facebook Ads Campaign Structure ===
# ใช้ Facebook Marketing API (Python SDK)
# pip install facebook-business
# campaign_structure.py
from dataclasses import dataclass, field
from typing import List, Dict, Optional
from enum import Enum
class CampaignObjective(Enum):
CONVERSIONS = "OUTCOME_SALES"
LEADS = "OUTCOME_LEADS"
TRAFFIC = "OUTCOME_TRAFFIC"
AWARENESS = "OUTCOME_AWARENESS"
ENGAGEMENT = "OUTCOME_ENGAGEMENT"
class BidStrategy(Enum):
LOWEST_COST = "LOWEST_COST_WITHOUT_CAP"
COST_CAP = "COST_CAP"
BID_CAP = "BID_CAP"
ROAS_TARGET = "MINIMUM_ROAS"
@dataclass
class AdCreative:
name: str
headline: str
description: str
cta: str # SHOP_NOW, LEARN_MORE, SIGN_UP
image_url: Optional[str] = None
video_url: Optional[str] = None
format: str = "single_image" # single_image, video, carousel
@dataclass
class AdSetConfig:
name: str
targeting: Dict
budget_daily: float
optimization_goal: str # CONVERSIONS, LANDING_PAGE_VIEWS, LINK_CLICKS
bid_strategy: BidStrategy = BidStrategy.LOWEST_COST
creatives: List[AdCreative] = field(default_factory=list)
@dataclass
class CampaignConfig:
name: str
objective: CampaignObjective
budget_daily: float
use_cbo: bool = True # Campaign Budget Optimization
ad_sets: List[AdSetConfig] = field(default_factory=list)
class FacebookAdsManager:
"""Facebook Ads Campaign Manager"""
def __init__(self, account_id, access_token):
self.account_id = account_id
self.token = access_token
def create_campaign(self, config: CampaignConfig):
"""สร้าง Campaign"""
# Facebook Marketing API call
# campaign = AdAccount(account_id).create_campaign(params={
# 'name': config.name,
# 'objective': config.objective.value,
# 'special_ad_categories': [],
# 'campaign_budget_optimization': config.use_cbo,
# 'daily_budget': int(config.budget_daily * 100),
# 'bid_strategy': 'LOWEST_COST_WITHOUT_CAP',
# })
print(f"Campaign: {config.name}")
print(f" Objective: {config.objective.value}")
print(f" Budget: /day")
print(f" CBO: {config.use_cbo}")
return config
def create_targeting(self, countries, age_min=18, age_max=65,
genders=None, interests=None, lookalike=None):
"""สร้าง Targeting"""
targeting = {
"geo_locations": {"countries": countries},
"age_min": age_min,
"age_max": age_max,
}
if genders:
targeting["genders"] = genders
if interests:
targeting["flexible_spec"] = [{"interests": interests}]
if lookalike:
targeting["custom_audiences"] = [{"id": lookalike}]
return targeting
# ตัวอย่าง Campaign Structure
manager = FacebookAdsManager("act_123456", "token")
# Broad Targeting Campaign
broad = CampaignConfig(
name="[CBO] Broad - Conversions",
objective=CampaignObjective.CONVERSIONS,
budget_daily=50.0,
use_cbo=True,
ad_sets=[
AdSetConfig(
name="Broad 25-55 TH",
targeting={"countries": ["TH"], "age_min": 25, "age_max": 55},
budget_daily=0,
optimization_goal="CONVERSIONS",
creatives=[
AdCreative("Image Ad 1", "สินค้าลดราคา 50%", "ช้อปเลย", "SHOP_NOW",
format="single_image"),
AdCreative("Video Ad 1", "รีวิวสินค้ายอดนิยม", "ดูเลย", "SHOP_NOW",
format="video"),
],
),
],
)
manager.create_campaign(broad)
print(f" Ad Sets: {len(broad.ad_sets)}")
for adset in broad.ad_sets:
print(f" {adset.name}: {len(adset.creatives)} creatives")Performance Optimization
# ads_optimizer.py — Facebook Ads Performance Optimization
import random
from dataclasses import dataclass
from typing import List, Dict
from datetime import datetime, timedelta
@dataclass
class AdMetrics:
ad_name: str
impressions: int
clicks: int
conversions: int
spend: float
revenue: float
@property
def ctr(self):
return self.clicks / self.impressions * 100 if self.impressions > 0 else 0
@property
def cpc(self):
return self.spend / self.clicks if self.clicks > 0 else 0
@property
def cpa(self):
return self.spend / self.conversions if self.conversions > 0 else 0
@property
def roas(self):
return self.revenue / self.spend if self.spend > 0 else 0
class AdsOptimizer:
"""Facebook Ads Optimization Engine"""
def __init__(self):
self.ads: List[AdMetrics] = []
self.rules: List[Dict] = []
def add_ad(self, metrics: AdMetrics):
self.ads.append(metrics)
def add_rule(self, name, metric, operator, threshold, action):
self.rules.append({
"name": name, "metric": metric,
"operator": operator, "threshold": threshold,
"action": action,
})
def evaluate_rules(self):
"""ประเมิน Optimization Rules"""
print(f"\n{'='*55}")
print(f"Ads Optimization Report")
print(f"{'='*55}")
actions = []
for ad in self.ads:
for rule in self.rules:
value = getattr(ad, rule["metric"], None)
if value is None:
continue
triggered = False
if rule["operator"] == ">" and value > rule["threshold"]:
triggered = True
elif rule["operator"] == "<" and value < rule["threshold"]:
triggered = True
if triggered:
actions.append({
"ad": ad.ad_name,
"rule": rule["name"],
"value": value,
"action": rule["action"],
})
if actions:
print(f"\n Actions ({len(actions)}):")
for a in actions:
print(f" {a['ad']}: {a['rule']} "
f"(value={a['value']:.2f}) -> {a['action']}")
else:
print(f"\n No actions needed")
def performance_report(self):
"""Performance Report"""
print(f"\n Ad Performance:")
total_spend = sum(a.spend for a in self.ads)
total_revenue = sum(a.revenue for a in self.ads)
for ad in sorted(self.ads, key=lambda a: a.roas, reverse=True):
print(f" {ad.ad_name:<25} "
f"ROAS:{ad.roas:.1f}x "
f"CPA: "
f"CTR:{ad.ctr:.1f}% "
f"Conv:{ad.conversions}")
print(f"\n Total: Spend= "
f"Revenue= "
f"ROAS={total_revenue/total_spend:.1f}x" if total_spend > 0 else "")
# ตัวอย่าง
optimizer = AdsOptimizer()
ads = [
AdMetrics("Image Ad - Product A", 50000, 1200, 45, 300, 2700),
AdMetrics("Video Ad - Review", 80000, 2400, 72, 500, 5400),
AdMetrics("Carousel - Collection", 30000, 600, 15, 200, 900),
AdMetrics("UGC Video - Testimonial", 60000, 1800, 90, 400, 6300),
AdMetrics("Static - Discount 50%", 40000, 800, 8, 250, 400),
]
for ad in ads:
optimizer.add_ad(ad)
# Optimization Rules
optimizer.add_rule("High CPA", "cpa", ">", 20, "Pause or reduce budget")
optimizer.add_rule("Low ROAS", "roas", "<", 2.0, "Review creative/targeting")
optimizer.add_rule("Low CTR", "ctr", "<", 1.0, "Refresh creative")
optimizer.performance_report()
optimizer.evaluate_rules()Creative Testing Framework
# creative_testing.py — A/B Testing Framework สำหรับ Ad Creatives
from dataclasses import dataclass
from typing import List
import random
import math
@dataclass
class CreativeVariant:
name: str
format: str # image, video, carousel
hook: str
impressions: int = 0
conversions: int = 0
spend: float = 0
@property
def cvr(self):
return self.conversions / self.impressions if self.impressions > 0 else 0
class CreativeTestingFramework:
"""Creative Testing Framework ตามแนวคิด Andrew Perpetua"""
def __init__(self):
self.variants: List[CreativeVariant] = []
self.min_impressions = 1000 # Minimum สำหรับ Statistical Significance
def add_variant(self, variant: CreativeVariant):
self.variants.append(variant)
def is_significant(self, v1: CreativeVariant, v2: CreativeVariant):
"""ตรวจสอบ Statistical Significance"""
if v1.impressions < self.min_impressions or v2.impressions < self.min_impressions:
return False, "Need more data"
p1 = v1.cvr
p2 = v2.cvr
n1 = v1.impressions
n2 = v2.impressions
if p1 == 0 and p2 == 0:
return False, "No conversions"
p_pool = (v1.conversions + v2.conversions) / (n1 + n2)
if p_pool == 0 or p_pool == 1:
return False, "Cannot calculate"
se = math.sqrt(p_pool * (1 - p_pool) * (1/n1 + 1/n2))
if se == 0:
return False, "SE is zero"
z = abs(p1 - p2) / se
return z > 1.96, f"z={z:.2f} (need >1.96)"
def testing_report(self):
"""Creative Testing Report"""
print(f"\n{'='*55}")
print(f"Creative Testing Report")
print(f"{'='*55}")
# Sort by CVR
sorted_variants = sorted(self.variants, key=lambda v: v.cvr, reverse=True)
winner = sorted_variants[0] if sorted_variants else None
for v in sorted_variants:
is_winner = " *WINNER*" if v == winner else ""
print(f" {v.name:<30} "
f"CVR:{v.cvr*100:.2f}% "
f"Conv:{v.conversions} "
f"Imp:{v.impressions:,}{is_winner}")
# Statistical Significance
if len(sorted_variants) >= 2:
sig, msg = self.is_significant(sorted_variants[0], sorted_variants[1])
print(f"\n Significance: {'YES' if sig else 'NO'} ({msg})")
# Recommendations
print(f"\n Testing Framework (Andrew Perpetua):")
print(f" 1. ทดสอบ 3-5 Creatives ต่อ Ad Set")
print(f" 2. รอ 1,000+ Impressions ก่อนตัดสินใจ")
print(f" 3. ดู CVR ไม่ใช่แค่ CTR")
print(f" 4. Winner takes all — Scale winner, kill losers")
print(f" 5. ทดสอบ Creative ใหม่ทุก 2 สัปดาห์")
# ตัวอย่าง
framework = CreativeTestingFramework()
variants = [
CreativeVariant("UGC Video - Unboxing", "video", "ลองเปิดกล่อง!", 15000, 120, 300),
CreativeVariant("Studio Photo - Product", "image", "สินค้าขายดี", 12000, 72, 240),
CreativeVariant("Carousel - Features", "carousel", "5 เหตุผลที่ต้องมี", 10000, 50, 200),
CreativeVariant("Meme Style - Humor", "image", "เมื่อเพื่อนเห็นของ", 8000, 40, 160),
CreativeVariant("Before/After", "image", "ก่อน vs หลัง", 11000, 88, 220),
]
for v in variants:
framework.add_variant(v)
framework.testing_report()เคล็ดลับจาก Andrew Perpetua
- Broad Targeting: ให้ Algorithm หา Audience เอง อย่า Narrow มากเกินไป
- CBO: ใช้ Campaign Budget Optimization ให้ Facebook จัดสรร Budget อัตโนมัติ
- Creative First: Creative สำคัญที่สุด ทดสอบหลาย Format (Video, Image, UGC)
- ROAS Focus: วัดผลด้วย ROAS ไม่ใช่แค่ CTR หรือ CPC
- Scale Gradually: เพิ่ม Budget 20% ต่อสัปดาห์ อย่าเพิ่มทีเดียวมาก
- Advantage+: ใช้ Advantage+ Shopping Campaigns สำหรับ E-commerce
Andrew Perpetua คือใคร
ผู้เชี่ยวชาญ Facebook Ads Digital Marketing เคยทำงานที่ Meta Product Marketing Manager ดูแล Ads Products ประสบการณ์ 10+ ปี Performance Marketing แชร์ความรู้ Blog Social Media
แนะนำเพิ่มเติม — คอร์สเทรด Forex ที่ iCafeForex
เนื้อหาเกี่ยวข้อง — PagerDuty Incident Machine Learning Pipeline
