Form and campaign teardown: which ads bring real buyers

The problem this solves

LinkedIn lead campaigns get judged by cost per lead, and cost per lead is a number that lies politely. A campaign that fills forms with students, job seekers, and the perpetually curious posts a beautiful CPL; the campaign quietly reaching directors at right-sized companies posts an ugly one. Judged on the metric everyone reports, the wrong campaign wins the next budget round, and the pipeline downstream keeps starving while the dashboard celebrates.

The information needed to judge properly exists on both sides of a join almost nobody performs. The ad account knows which campaign and which form produced every lead; the lead itself carries a company, a title, and answers that reveal fit. Joining them means pulling every lead with its source attribution, resolving each company, and scoring the result - per lead, per week. Done by hand it is an afternoon in spreadsheets, so it happens once a quarter if ever, and reallocation decisions run on CPL in between.

This mission performs the join on demand. It pulls the window's leads with their source campaigns and forms, enriches and scores every lead against your ICP, and renders the verdict per campaign: who brings buyers, who brings noise, and where the money should move.

How the mission runs

1. Pull leads with their attribution. The Lead Sync connection returns every form submission in the window with its source form and campaign attached - first-party data from your own ad account, complete rather than sampled.
2. Enrich and score each lead. Every lead's company is resolved and enriched with firmographics, and the lead is scored against your ICP: right industry, right size, right seniority, form answers that signal a real evaluation. The scoring reasoning is kept per lead.
3. Aggregate by campaign and form. Scores roll up to the units you can act on: each campaign and each form gets a quality mix - what share of its leads are ICP-fit, marginal, or noise - alongside its volume and spend.
4. Rank on cost per qualified lead. The metric that should have been the default all along: spend divided by fit leads only. Campaigns re-rank, sometimes dramatically - the cheap-CPL noise machine falls, the expensive-looking buyer magnet rises.
5. Deliver the verdict and the file. A CSV lands with every lead, its score, and its source, and the summary names the reallocation call: which campaigns earn more budget, which need new targeting, and which forms attract the wrong crowd.

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

A campaign-level quality teardown: every lead in the window scored and attributed, quality mix and cost per qualified lead per campaign and per form, a full CSV of the evidence, and a concrete reallocation recommendation ranked by the money it moves.

Make it yours

• Run it weekly as a standing schedule so the quality mix becomes a trend line rather than a quarterly surprise.
• Split the analysis by form question set - the form often shapes lead quality as much as the targeting does.
• Chain it with the optimize-to-quality playbook, so the same scoring that judges campaigns also feeds LinkedIn only qualified conversions.

Frequently asked questions

Go deeper

• Budget allocation by evidence: splits that trace to data
• AI advertising operations: the complete guide
• Lead routing and scoring that reflect reality