惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

月光博客
月光博客
人人都是产品经理
人人都是产品经理
博客园 - 聂微东
WordPress大学
WordPress大学
S
SegmentFault 最新的问题
博客园 - Franky
V
V2EX
Y
Y Combinator Blog
Google DeepMind News
Google DeepMind News
J
Java Code Geeks
T
The Blog of Author Tim Ferriss
罗磊的独立博客
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Jina AI
Jina AI
博客园 - 叶小钗
F
Fortinet All Blogs
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
A
About on SuperTechFans
M
MIT News - Artificial intelligence
云风的 BLOG
云风的 BLOG
Last Week in AI
Last Week in AI
D
Docker
博客园 - 【当耐特】
阮一峰的网络日志
阮一峰的网络日志

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
25–35% of our best customers were aging out of retargetin...
강해수 · 2026-06-17 · via DEV Community

강해수

A frequency cap failure on a $40K/mo account eventually traced back to a 7-day retargeting window that was quietly excluding the highest-value buyers in our entire funnel.

After frequency started climbing despite caps looking correct on paper, I pulled 90 days of raw pixel events — first site visit to purchase, for every converter, no modeling — through a Cloudflare Workers pipeline into D1 so I could query without sampling. The distribution killed the assumption the whole account was built on: only 35–40% of converters closed within 7 days of first touch. Another 25–30% converted between day 8 and day 21. The remaining 25–35% came back somewhere between day 22 and day 45. A default 7-day window was functionally running zero retargeting pressure on roughly 60% of the people who would eventually buy.

The part that stings: the longest-lag cohort had 20–30% higher AOV than the sub-7-day cohort. These were customers researching higher-ticket SKUs (₩80,000–₩150,000 skincare sets), doing ingredient comparisons, waiting on payday. Not weak intent — longer consideration cycles. The account's ROAS had looked acceptable for months because we were efficiently converting fast movers and completely ignoring slow movers. The 7-day default exists because Meta's aggregate data across all verticals skews toward impulse and replenishment. Our category doesn't.

The fix was restructuring retargeting into three sequential tiers: days 1–7 (viewed product, no ATC) with urgency-light creative, days 8–21 (viewed or ATC, no purchase) with benefit-depth and comparison angles, and days 22–45 (ATC or initiate checkout, no purchase) with direct offers and friction reduction. Each tier runs as its own ad set with separate frequency caps, and tiers exclude each other to prevent overlap. About 30% of retargeting budget shifted out of the 1–7 day tier. Blended retargeting ROAS lifted 30–50% within three weeks, and the frequency problem resolved on its own — larger pools, better distribution.

One caveat worth knowing upfront: if you're under ~500 site visits per day, the 22–45 day tier will sit under 1,000 people and Meta's delivery gets erratic. Collapse tiers 2 and 3 into a single 8–45 day window rather than running three underfueled ad sets.

I wrote up the full breakdown — including how I now instrument purchase lag as a standing monthly metric rather than a one-time audit, and what signals indicate your window structure needs re-calibration — over on themedilog.com.

Full post →