The problem this solves
LinkedIn is where B2B budgets go to pay for precision they rarely use. The targeting is capable of remarkable specificity - exact companies, exact roles - but feeding it requires a matched audience file most teams never build. So campaigns fall back to firmographic proxies: industry, size, seniority. The ads reach people who look like buyers on paper, and the budget spreads across a market where only a sliver is in motion right now.
The file stays unbuilt because assembling it is genuinely tedious: identifying which companies are actively researching your category, finding the actual marketing leaders inside them, and formatting both lists to LinkedIn's exacting CSV schemas - where a malformed column silently tanks match rates. Each step lives in a different tool. Meanwhile the highest-leverage audience available, companies demonstrably in-market this month, goes untargeted while the generic campaign burns through the quarter.
How the mission runs
- Surface in-market companies. Intent Data identifies companies currently showing buying signals on your category - active research behavior rather than static firmographic fit. The audience starts from who is in motion now instead of who matches a profile.
- Find the marketing leaders inside them. Email Finder resolves the people layer: the marketing decision-makers at each in-market company, with the identifiers LinkedIn contact matching needs. The company list gains the human targets your ads should actually reach.
- Format both CSVs to LinkedIn's schema. The CSV tool builds two files - company targeting and contact targeting - matched exactly to LinkedIn Ads upload formats: correct columns, headers, and encodings. The formatting details that silently break match rates are handled once, correctly.
- Save to Drive with a targeting note. Both CSVs land in Google Drive alongside a short note: audience size, how the companies were qualified, and the recommended campaign use for each file. Whoever runs your LinkedIn account uploads from Drive when ready.
The prompt
This is the exact objective the agent receives. Swap the obvious placeholders for your own domain, segment or channel and run it as-is from the console, Slack, or the API.
What comes back
Two upload-ready CSVs in Google Drive - a company list of accounts showing active buying intent on your category, and a contact list of their marketing leaders - formatted precisely for LinkedIn Ads matched audience uploads, with a note covering audience size and qualification logic. Your next LinkedIn campaign targets companies that are demonstrably in-market instead of a demographic approximation of them.
Make it yours
- Change the persona: build the contact layer around revenue or operations leaders when your buyer sits outside marketing.
- Tier the audience: split companies into hot and warm intent files so bids and creative can differ by urgency.
- Refresh monthly: intent decays fast, so a standing rerun keeps the matched audience tracking who is in-market now.
Frequently asked questions
Does the mission upload the audience and launch ads?
The playbook ends at Drive: files built, formatted, and documented, with the upload into LinkedIn remaining your action. Audience creation and campaign writes are the kind of account changes that wait for explicit human approval, while everything up to that point runs free.
How current is the intent signal?
It reflects recent research behavior at the time the mission runs, which is exactly why the audience beats static lists - and why it ages. Treat the file as a snapshot of who is in motion now, and rerun on a cadence so the audience keeps pace with the market.
What match rate should I expect on LinkedIn?
Match rates vary with list size and how well identifiers resolve, and no honest tool promises a number. The mission maximizes your odds by getting the schema exactly right and enriching contacts with the fields LinkedIn matches on, and the targeting note flags any thin spots in the list.