We sent 275 cold emails with an AI agent. The telemetry is humbling.

说明与用途

我们用 AI 代理发送了 275 封冷邮件，交付率 91.8%，但没有收到任何真人回复。发现并修复了 em‑dash 编码错误，部署了自托管的聚合跟踪像素，并设定了回复率阈值以决定是否停止该渠道。

问题

Low reply rate from a cold email campaign run by an AI agent.

结果

Delivered 91.8% of 182 verifiable emails; 0 human replies; identified encoding issue; added open tracking; established reply‑rate kill‑gate.

工作流

• 1. Vet business domains and compile one role address per business. 2. Enforce CAN‑SPAM compliance: role sender, postal address, List‑Unsubscribe. 3. Apply hard send‑caps in the sending script (per‑day and per‑month ceilings). 4. Send 275 emails (first touch only). 5. Read provider event store for last five days; re‑verify receipt for 182 emails. 6. Count delivered (167), permanent failures (15), hard bounces (4), replies (0), opt‑outs (0). 7. Identify em‑dash encoding regression causing 550 errors; fix with body linting and suppression. 8. Deploy self‑hosted aggregate‑only tracking pixel for open rates. 9. Set a kill‑gate on 2026‑11‑04 if replies remain below threshold. 10. Publish telemetry and plan for lane cut if needed.

证据

275 countable sends to business domains we researched and vetted by public criteria (no scraped personal emails, no free‑mail, one role address per business, a real suppression list).

来源

delivered (receipt confirmed) 167 — 91.8% (167/182)

来源

replies from real humans 0

来源

Some of the earliest sends were permanently rejected with 550-class errors because of an encoding regression of ours: an em‑dash in the body tripped a receiving filter.

来源