u/Impressive_System481

Once we have a contact, they get pushed into our CRM automatically. No manual entry.
The structure is straightforward: companies position at the top, contacts belong to companies, inquiries belong to contacts, and each inquiry can have multiple product lines attached. Clean hierarchy, easy to query.
Before anything gets created, the system checks for duplicates. If the company already exists, it updates the record. If the contact already exists at the same company, same thing. This matters more than it sounds — without it, you end up with a messy database fast.
Every new contact lands with a lifecycle tag: "not yet contacted." That single field is what drives everything downstream — outreach timing, follow-up sequences, escalation to the sales team.

Once we have a target company, the agent goes back to LinkedIn to find the right contact. It pulls name, job title, LinkedIn profile, and email where available. Email is the harder part — LinkedIn doesn't surface it directly, so we're supplementing with other methods where we can.
Everything then gets pushed into Twenty, self-hosted.
The data model has a clear hierarchy: Company → Person → Inquiry → Product Demand. A company can have multiple contacts, a contact can generate multiple inquiries over time, and each inquiry can contain multiple product demands.
On import, the agent creates the company record first, then the contact, and links them. Before creating anything, it checks for duplicates — if the company URL or LinkedIn already exists, it updates rather than creates. Same logic for contacts: same name at the same company means update, not duplicate.
Each contact gets a lifecycle field on import, set to "Tier 3— Not Contacted." That's the starting point for everything that comes after.

In our industry the right person is usually a procurement or sourcing manager. Finding them manually on LinkedIn takes time — you're searching, scrolling, checking job titles, deciding if it's worth reaching out.
We automated this part. Looking at the most recent week of data — roughly half of connection requests are being accepted, and the majority of contacts landing in our pipeline are in procurement or sourcing roles, which is exactly what we're targeting.
Not a huge sample size yet, but the signal is decent. The job title matching seems to be working.

Starting from the top of the funnel.
Our market is narrow — manufacturers who use specific industrial raw materials, mostly in Europe and parts of Asia. There's no clean list you can just buy. So the first problem was: how do you systematically find these companies at scale?
We built a search layer using an expanded keyword library tied to our product categories and target industries. It runs automatically and flags companies that match our criteria.
Right now about 60% of what it surfaces are genuinely worth pursuing. The rest look plausible but don't actually fit.
For a niche B2B business, 60% felt like a reasonable starting point. We're still improving it.and once we have a list of companies, how do we find the right person to talk to inside them.  

Starting from the beginning of the pipeline.
Our industry is niche — refractory raw materials. The buyer pool is small and scattered across Europe and parts of Asia. Generic lead tools don't work well here, so we had to build our own search logic.
The approach: start with a small set of core keywords based on our products and target industries, then expand them into a broader library. The agent runs searches based on this library and pulls matching companies.
Current result: around 60% of matched companies are genuinely qualified leads. Not perfect, but good enough to keep the pipeline moving.
Still refining the keyword logic. The other 40% is mostly companies that look right on the surface but don't actually buy what we sell.

We’re part of a company that exports industrial raw materials to manufacturers in Europe and Asia, and we’ve been doing this for over 20 years.

About a month ago, we started building an automated system to support parts of this process. It’s not intended as a product or a shift in business direction

The main issue is that tasks like identifying qualified buyers, writing personalized outreach, and managing follow-ups are handled manually by the sales team. While this approach is effective, it takes a significant amount of time and doesn’t scale easily.