# Warehouse-AI Email Drip -- Cold Outreach Sequence **Product:** Warehouse-AI **ICP:** Warehouse operations managers, 3PL coordinators, distribution center directors at companies running 50-500 person warehouse floors **Voice:** Floor-direct, data-confident, zero-fluff **Palette signal:** Ops black / forklift amber / steel mist **Sequence length:** 5 emails over 14 days --- ## Email 1 -- Day 1 (Cold open) **Subject:** Your pick-pack error rate after midnight Hi [Name], Most warehouse ops teams I talk to have a number they track on paper and a number they actually believe. Usually two different numbers. Warehouse-AI pulls your WMS data, your exception logs, and your shift notes into one place and surfaces the gaps before they become chargebacks. No new hardware. No rip-and-replace. Works alongside your existing TMS or WMS in a day. Worth 15 minutes this week? -- [Sender] --- ## Email 2 -- Day 3 (Proof point) **Subject:** 340 mis-picks in 30 days -- found in 4 hours Hi [Name], A distribution center in Memphis had a recurring short-ship problem on one SKU family. Their team had been chasing it manually for three weeks. Warehouse-AI cross-referenced their receiving logs against pick confirmations and pinned it to a single slotting conflict introduced during a layout change. Four hours to find. One afternoon to fix. Chargebacks dropped 60% the following month. If your floor has patterns you know exist but cannot isolate, that is exactly what we built this for. Reply and I will show you what it looks like on a floor similar to yours. -- [Sender] --- ## Email 3 -- Day 7 (Objection disarm) **Subject:** Re: "we already have a dashboard" Hi [Name], Most warehouses do. The dashboard shows you what happened. Warehouse-AI tells you why it happened and which shift, which lane, which carrier pairing made it worse. The difference is the question it answers. A dashboard answers "what is the number." We answer "what changed, where, and when did it start." If your team is already drowning in data but still guessing at root cause, that is the gap we close. Happy to run a 20-minute live demo using publicly available benchmark data from your vertical so you can see the output before committing any of your own. Interested? -- [Sender] --- ## Email 4 -- Day 10 (Stakes framing) **Subject:** Chargeback season is 90 days out Hi [Name], For most distribution operations, Q3 prep starts now. Carrier compliance windows tighten, retail routing guides get updated, and whatever process gaps exist on your floor get amplified by volume. Warehouse-AI runs a floor diagnostic in about 48 hours -- no integration required for the initial pass, just a data export your team already generates. Output is a prioritized list of operational risks ranked by chargeback exposure and fix complexity. Teams that run the diagnostic in May or June tend to enter peak season with a cleaner floor and fewer surprises. Want to schedule the diagnostic before your team locks Q3 priorities? -- [Sender] --- ## Email 5 -- Day 14 (Clean exit) **Subject:** Closing the loop Hi [Name], I have sent a few notes about Warehouse-AI and have not heard back -- which usually means either the timing is off or this is not the right problem for your team right now. Either answer is fine. If the timing is wrong, I am happy to reconnect in Q4. If it is not the right fit, just say the word and I will stop reaching out. If there is a specific issue on your floor -- pick accuracy, slotting efficiency, shift handoff gaps, carrier compliance -- and you want a second opinion, I am glad to spend 20 minutes looking at it with you, no pitch attached. Either way, thank you for your time. -- [Sender] --- ## Usage notes - Replace [Name] and [Sender] before sending - Email 2 can be personalized with a vertical-specific proof point if one is available - Email 3 is best used when a prospect has replied with a "we already have tools" objection - Email 4 should be timed to actual seasonal reality -- adjust the Q3 framing if sending outside April-June - Email 5 is a permission-based close; always end sequences with a clean exit rather than a hard ask