Who the budget reachesWeekly + monthly

Targeting vs who actually buys

Compares who each campaign paid to reach with the people on your deals, and moves budget toward the profiles that buy.

Runs with
  • LinkedIn Ads export
  • DemandSense (optional)
  • CRM export
You need
Campaign Manager demographics export plus CRM deals. Or the DemandSense MCP.
You get
Spend vs pipeline per buyer profile, changes per campaign and an exclusion list that's safe to apply.

What you get

Who you pay to reach, against who buys. With the titles to exclude and the calls to approve

  • The monthly review: What each ad set paid to reach, graded on-target, adjacent or off-target
  • Spend against pipeline: Each buyer profile’s share of spend next to its share of pipeline
  • Titles safe to exclude: Off-target titles to drop as a 30-day test, and the ones to keep for now
  • Recommendations to decide: Eight calls, each with the number that confirms it

Get it

Paste one prompt. It reads your exports and changes nothing

Your exports
Load the Targeting vs who actually buys scenario from https://github.com/demandsense-labs/linkedin-ads-skills/tree/main/monthly-targeting-review and run it on the exports I’ve attached.
DemandSense
Load the Targeting vs who actually buys scenario from https://github.com/demandsense-labs/linkedin-ads-skills/tree/main/monthly-targeting-review and run it on my DemandSense workspace. Pull the data through the connector rather than asking me for exports.

Rather not paste it? Install it instead

Add it to Claude Code once and call it by name on any export

Claude Code
/plugin install linkedin-ads-skills --marketplace demandsense-labs/linkedin-ads-skills

Read the source on GitHub Skill folder on GitHub

How it runs

6 steps, in order. Each one applies a rule of the Standard, and stops the run when the data can’t carry it

  1. Monthly

    Job title audit

    Who each campaign paid to reach, graded against that campaign's own targeting.

  2. Read the deal side

    The buying-committee list is the base, titles on deal contacts are evidence (they're often patchy).

  3. Group deals by profile

    Pipeline created, win rate, deal size.

  4. Spend against pipeline

    Compare each profile's share of spend with its share of pipeline. Flag profiles that get too much budget, too little, or never convert.

  5. Recommend

    Targeting, exclusion and budget changes per campaign. Before cutting a title, check whether it sits in an account showing buying signals.

  6. Weekly

    Light check

    Is new spend leaking to off-target titles?

Hi there, here is myskill

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