[ FIELD NOTES ]
Field Notes for Selling Into Factories
For industrial-goods reps, SaaS BD and supply-chain finance advisors — the people whose customers are factories. We write about how to find the right factory accounts, how to read their capacity and procurement rhythm, and how to turn lists into closed deals — every piece reverse-engineered from real deals, not training-company scripts.
The Costliest Waste in a Sales List: Calling a "Fake Factory"
Lesson 3 taught you how to build a list; Lesson 4 tells you what traps are hiding inside it. Traders, stall traders, first- and second-tier re-order middlemen, out-of-town sales offices, and shuttered shell companies — these five types of 'fake factories' eat up more than 30% of your dialing time. This lesson breaks down the identification signals and gives you an 8-question self-check for 'Is this actually a real factory?'
— Gongchangku Editorial
How to Build a Factory Call List You Should Work Today
The previous lesson covered factory tiering — but where does the list come from? This lesson gives you a 5-step filtering funnel from ICP to an executable list: translate your Ideal Customer Profile into filter criteria, combine dimensions to shrink the pool, deduplicate, score and rank by tier, and set daily quotas. Tianxia Gongchang outputs a structured list at step two, so sales reps receive a call-ready list — not raw data.
— Gongchangku Editorial
Not Every Factory Is Worth Calling — Tiering Factory Customers into S/A/B/C
Calling through a list of 600 factories with no prioritization burns 250,000 yuan in sales cost — yet the S- and A-tier customers actually worth deep investment account for only 18% of the list. This article provides a 5-dimension scoring sheet to help industrial salespeople rank the list before making a single call, concentrating resources on the factories most likely to close.
— Gongchangku Editorial
Work Out Which Factories to Sell To — The Ideal Customer Profile for Industrial Sales
The most common waste in industrial sales is spending an entire quarter calling through a vague list filtered by 'business scope: machinery/manufacturing.' This article uses the product-backward method to condense a fuzzy 'target factory' into a single filterable Ideal Customer Profile in three steps, and shows how to use Tianxia Gongchang to validate how many factories nationwide actually match the profile — so you can judge whether the market is worth entering.
— Gongchangku Editorial
Finding Factories That Are Already Implementing ERP/MES — Which of 3 Digital Transformation Signals Fires First
For salespeople selling industrial SaaS, data platforms, or IT implementation services: how do you find factories whose digital transformation budgets have already been approved? This article puts three signal types to the test — government digital transformation showcase lists, IT hiring signals, and factories' own procurement tender announcements — and explains how Tianxia Gongchang locks those signals back to scale-matched genuine factory entities.
— Gongchangku Editorial
Factories That Just Raised — 3 Tools to Capture the Funding Window
For sales teams in supply-chain finance, high-end industrial equipment, and IPO advisory, the best prospect is a factory that just received fresh capital. This article field-tests three tools — Tianyancha's funding alerts, ITjuzi, and Cninfo's IPO prospectus database — and shows how to pair them with Tianxia Gongchang to verify that a funded target is a genuine factory, then deliver a step-by-step workflow for turning a funding announcement into a ready-to-visit lead list.
— Gongchangku Editorial
Reverse-Lookup a Factory from the Owner's Douyin Account — 4 Social Prospecting Tools Tested
Factory owners are increasingly building personal brands on Maimai, Douyin, and WeChat Channels. The accounts behind those profiles are real procurement windows. This article puts four social tools — Maimai, Douyin enterprise accounts, WeChat Channels, and WeCom — through a structured five-dimension test, and shows how pairing them with Tianxia Gongchang's reverse-lookup turns an owner's handle into a verified factory entity.
— Gongchangku Editorial
Targeting Factories That Are Losing Export Volume and Opening Domestic Stores — A Hands-On Test of the Customs Data + 1688 + Tianxia Gongchang Trio
Trade friction and softening overseas demand have forced a wave of export-oriented factories into an export-to-domestic pivot. They urgently need domestic channels, brand services, and domestic SaaS. This article tests customs volume-drop signals, 1688 new-store scanning, and the Tianxia Gongchang trio — delivering a practical, actionable method for identifying factories in the middle of an export-to-domestic pivot.
— Gongchangku Editorial