Automation · Sales and quoting

Build a prospect list on WhatsApp from a PhantomBuster Phantom's results

An AI agent checks on WhatsApp what your PhantomBuster Phantom brought in, filters prospects by job title and city and saves the list ready to use.

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How do I build a prospect list from WhatsApp with what my LinkedIn Phantom found?

Tell your Met which Phantom to use and which prospects you want, for example "the managers in Bogotá from this week's search". The Met finds the Phantom by its ID, checks that the last run finished and actually brought rows, tests the filter on your stored leads scoped to that Phantom and tells you how many match with three examples. When you say yes, it saves the dynamic list and checks how many members it ended up with. It does not launch the Phantom or write to anyone: it leaves the list ready for your next step.

What starts it

When someone asks for it

It starts when someone on the sales team writes to the Met on WhatsApp with which Phantom to use and which prospects they want. It does not run in the background: each list is a request.

A manual task: someone on the team runs it with a button, or asks the Met for it in chat.

Who runs it

Sales Met that builds lists in PhantomBuster

Sales team

This is not a named, seeded Met. It is an internal Met with PhantomBuster connected: its work ends when the list is saved with its count checked, not when the prospects are contacted.

Run by the lead qualification Met

Channels: WhatsApp

What you need connected

PhantomBuster Sell and serve

6 steps · 8 tools

The procedure, step by step

Each step shows the tool that runs. They belong to the real connector: if one of them stopped existing, this page would not build.

1
Locate the workspace

The Met checks the connected workspace once: its ID to build links, its time zone and the plan's limits. It reuses them for the rest of the conversation.
- orgs_fetch PhantomBuster
2
Find the Phantom by its ID

The Met looks for the Phantom you named among the workspace's Phantoms. If two share the name, or a deleted one matches, it shows you both with their IDs and asks which one, instead of choosing for you.
- agents_fetch_all PhantomBuster
- agents_fetch_deleted PhantomBuster
3
Check that the last run brought something

The Met checks the status of the last run and reads its result. A run marked as successful can still have produced nothing, so the Met looks at the rows before saying the search worked.
- agents_fetch_output PhantomBuster
- containers_fetch_result_object PhantomBuster
4
Test the filter before saving

The Met turns your request into a filter with your own words, scoped to the leads that Phantom brought, and tests it on your stored leads. It tells you how many match and three names with their job titles. If it gets zero, it checks a sample lead before changing the field.
- org_storage_leads_objects_search PhantomBuster
5
Save the list once you confirm

With your answer, the Met saves the list with a clear name and a description that states the filter in words, including the source Phantom. If a list with the same filter already exists, it suggests using that one instead of creating another.
- org_storage_lists_save PhantomBuster
6
Check how many ended up in the list

The Met reads the saved list's members and tells you the final count. If it does not match the test or comes out as zero, it tells you so the filter gets fixed before a Phantom uses that list.
- org_storage_leads_by_list_listid PhantomBuster

Before you start

What you need ready

The Met solves none of these for you. If one is missing, the automation stops there.

A Phantom that has already run

A Phantom in your workspace, for example a LinkedIn search export, with at least one finished run. This procedure works on its results; it does not launch it.
PhantomBuster connected in Met

In Met, open Connections → PhantomBuster → Connect, sign in and pick the workspace. Saving lists comes switched on; if you prefer the Met to only look, the admin turns that action off.
A WhatsApp line with the Met assigned to the team

The business connects its WhatsApp Business API line and assigns the Met that serves the sales team. The request and the answer happen in that conversation.

The limits

What this automation does NOT solve

Better said here than discovered halfway through the rollout.

It does not contact the prospects. It leaves the list saved; writing to them on LinkedIn, email or WhatsApp is another step, with its own rules and limits.
It does not make up data the Phantom did not bring. If the Phantom does not fill in the job title or the city, the filter cannot use them and the Met tells you.
It does not ask for confirmation in the chat on its own: this procedure shows the count and waits for your answer, but if the save action is on, the real control is that setting.
It does not switch workspaces. If your prospects live in another PhantomBuster workspace, another connection is needed.

FAQ

Questions about this automation

Yes. The list is a saved filter: every new lead from that Phantom that matches the filter joins on its own, without repeating the procedure.

Not in this procedure. Launching is a separate action that acts with your LinkedIn or other network account, and launching too much can restrict that account. That is why it starts switched off: if the admin turns it on, it is best to ask for it explicitly.

Because filtering by date mixes leads from any Phantom that ran that day and leaves out later runs. PhantomBuster recommends scoping the list to the Phantom that feeds it.

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