RB2B Companies to Contacts

What it does

Not every identified visit comes with a person. Some rows are company-level, and the instinct is to treat those as the low-value remainder of the export.

That gets it backwards. A company that has read eleven pages across three sessions is a stronger signal than a single individual who read one — you just don't yet know who to talk to. This skill closes that gap: it pulls the distinct companies out of your export, ranks them by how much they've actually been reading, then searches for people at each one who match the profile you describe.

When to use it

Use it when account-level intent is the thing you're acting on: an ABM motion, a named-accounts list, or any situation where the buying group matters more than the individual who happened to land on your pricing page.

It's also the right tool when your traffic skews to large organisations, where the person browsing is rarely the person with budget.

How it works

1. Companies are extracted and deduplicated from the export — both the company rows and the employers attached to person rows.
2. They're ranked by RB2B's own engagement figures, all-time page views and recent page count, so the accounts reading most sit at the top.
3. You describe who you're looking for: seniority, department, country, and other filters as needed.
4. Each company is searched for matching people.
5. Those contacts are enriched with business emails, and optionally mobile numbers.

Getting the filters right

The filters are the part worth spending thought on. They're exact-match, which is unforgiving in a specific way: a mistyped value or a department and function that contradict each other doesn't return an approximate answer, it returns nothing — or worse, a confidently wrong list.

Two habits help. Describe the role the way the person's own profile would, not the way your org chart does. And check the result count on a narrow run before widening it, so a filter that silently matches nothing shows up immediately rather than after you've built a sequence around it.

What you get back

A ranked table of company, name, title, seniority, LinkedIn URL, business email with its risk grade, mobile number, and the RB2B visit metrics that put that company where it is in the ranking. The summary covers companies processed, contacts found per company on average, the email enrichment rate, and the risk distribution.

Keeping that visit data next to each contact matters: it's the thing that tells a rep why this account and why now, and it's what makes the first email specific rather than generic.

Before you run it

You need a MoltSets account and the skill installed in Claude, plus an RB2B export that still has its LinkedIn URL column — that column is what every lookup keys off, so exports stripped down to names and emails won't work.

Run it on a small slice first. Twenty or thirty rows is enough to see the hit rate and the risk grades you're getting for your particular audience, and to decide which grades are worth keeping before you point it at a month of traffic.