Cross-border acquisition workflows from public signal to reviewed sales action
Hexastruct builds Yingdao RPA, n8n, Feishu robot alerts, Telegram routing, CRM handoff, JS lead records, and human-reviewed follow-up pipelines.
Open pageAI & Acquisition
AI strategy and acquisition engine for global B2B hardware growth
Hexastruct turns public market signals, messy inquiry data, RPA workflows, AI extraction, Feishu alerts, and GTM follow-up into a practical acquisition engine.
Public data crawler automation for global B2B signal monitoring
Hexastruct uses Python, Playwright, Scrapling, browser task queues, source logs, public-page monitoring, and human review to turn scattered market signals into usable lead context.
Open pageData cleaning and extraction that turns messy inquiries into sales-ready records
Hexastruct normalizes names, emails, phone numbers, product categories, countries, duplicate records, RFQ language, urgency signals, and missing fields before scoring and routing.
Open pageGTM strategy that turns inquiry content into follow-up queues and answer-engine visibility
Hexastruct structures inquiry themes, buyer questions, social signals, FAQ content, case pages, follow-up scripts, and AI routing so global buyers understand why they should talk to you.
Open pageLaunch the next stage with Hexastruct
Tell us the product category, current bottleneck, market target, and launch stage. We will map the right build path.
Launch NowGoogle-ready FAQ
Questions buyers ask before they inquire
Why does a B2B hardware company need crawler automation?
Because overseas demand appears across many public sources before it becomes a formal RFQ. Crawler automation monitors those public signals, logs the source, extracts useful fields, and sends only qualified opportunities to human review.
What is data cleaning in a B2B lead-generation workflow?
Data cleaning means normalizing contact fields, product categories, countries, RFQ requirements, duplicate records, missing fields, and spam signals so the sales team can compare leads and respond consistently.
Can Hexastruct connect Yingdao RPA, Playwright, Scrapling, n8n, AI extraction, and Feishu?
Yes. Hexastruct can design the operating logic across public-source monitoring, browser task queues, AI extraction, scoring, JS lead files, Feishu robot alerts, Telegram messages, CRM-ready records, and human review.
Is the crawler workflow only about scraping more data?
No. The useful layer is public-signal monitoring, source logging, field extraction, cleaning, scoring, deduplication, review, and routing. Fewer trustworthy leads are better than a large messy scrape.
How does automation improve SEO and GEO?
Automation reveals repeated buyer questions, product phrases, objections, and category language. Hexastruct turns those signals into crawlable pages, FAQ schema, answer-hub entries, case studies, and llms.txt so Google and AI models can understand the company.
为什么外贸工厂需要数据清洗？
因为询盘、社媒线索、邮件、表格和人工记录经常格式混乱、重复、缺字段。数据清洗可以把这些线索变成统一字段、可评分、可分配、可追踪的销售记录。
影刀 RPA 和爬虫自动化有什么区别？
影刀 RPA 更适合把重复浏览器动作、表格动作和平台操作流程化；爬虫自动化更偏向公开数据监控和字段提取。Hexastruct 会根据场景把二者和 AI 提取、评分、飞书提醒组合起来。
What can a public web crawler monitor for B2B hardware sales?
It can monitor public product pages, supplier listings, crowdfunding launches, visible social posts, keyword results, category pages, and change signals that suggest buyer demand or competitor movement.
What should be defined before building a crawler?
Define source list, legal/public boundaries, target fields, frequency, exclusion rules, deduplication logic, scoring rules, alert destination, and human review process.
Can a crawler feed SEO and GEO content?
Yes. Repeated buyer questions, product terms, objections, and category phrases can become FAQ schema, answer hub entries, service pages, and sales scripts.
Why is data cleaning necessary before AI lead scoring?
AI scoring is unreliable when fields are inconsistent. Clean country, category, contact, source, quantity, urgency, and duplicate status first, then score the record.
Can Hexastruct clean RFQ emails and website inquiries into JS files?
Yes. Website and email inquiries can become structured JS lead records with source page, contact fields, category, summary, score, missing fields, and recommended next action.
数据清洗和 CRM 有什么关系？
CRM 只负责存储和管理，如果进入 CRM 的数据本身混乱，销售还是会浪费时间。数据清洗是在进入 CRM 或飞书提醒之前，把字段、重复项、评分和下一步动作整理清楚。
What should be inside a Feishu lead alert?
A good Feishu alert should include source URL, buyer or company clue, product category, summary, lead score, missing fields, suggested next action, owner, and follow-up reminder.
Can AI lead workflows avoid low-quality automated outreach?
Yes. Hexastruct uses deduplication, scoring, negative-signal filters, and human review before outreach so the workflow supports quality sales work instead of blind mass messaging.
How does a lead workflow help Google and AI search visibility?
The workflow reveals what buyers repeatedly ask. Those questions can be rewritten into FAQ schema, service pages, answer hub pages, case pages, and llms.txt entries for GEO and SEO.