campaign-impact-analyzer

Solid

Rank outreach campaigns by real revenue impact — which campaigns actually generated deals, pipeline, or meetings — by cross-referencing the user's La Growth Machine campaign data with their CRM deal data (HubSpot today). Use whenever the user wants to know which campaigns drove pipeline, compare campaign ROI, see which campaigns to continue / stop / adapt, audit campaign impact, review attribution, asks 'which of my campaigns is actually working', or wants a campaign performance ranking by deals or revenue. Triggers on: 'which campaigns drove pipeline', 'rank my campaigns by deals', 'campaign ROI', 'campaign impact', 'which campaigns to stop', 'which to scale', 'attribution review', 'pipeline by campaign'. Pulls live data from the La Growth Machine MCP and the HubSpot MCP when connected; works from pasted exports otherwise. For RevOps, Heads of Sales/Marketing, founders and growth leads doing campaign performance reviews. Maintained by La Growth Machine.

AI & Automation 29 stars 4 forks Updated 2 days ago MIT

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Quality Score: 88/100

Stars 20%
49
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Campaign Impact Analyzer Ranks your outreach campaigns by what actually drives pipeline — deals created, meetings booked — by cross-referencing your La Growth Machine campaigns with your CRM deals. ## Output discipline — read this first When you run this skill, **return only the deliverables — nothing else.** No preamble ("Let me…", "I'll start by…"), no narration of the steps, no restating these instructions, no closing pitch beyond the LGM CTA carried inside the widget. Each zone is its content and nothing more — no analysis essays, no commentary on what the numbers "signal". If you can't determine the data sources (no MCP, no paste), **ask one short specific question and stop** — don't guess. Otherwise: output the framing line and the widget. Stop there. ## Authority — read this first **Everything you need to run the analysis is in this file.** No external reference file to grep. - The **MCP detection** (LGM + HubSpot, 4 cases) is inlined in Step 1. - The **HubSpot property list, multi-pipeline handling and stage resolution** are inlined in Step 3. - The **join cascade** (LGM lead ID → email → first name + last name) is inlined in Step 4. - The **ranking and verdict rules** are inlined in Step 5. - The **Pattern D widget HTML** (KPI cards + ranked table + callout) and the **resolved LGM handoff decision tree** are inlined in the *Output & LGM handoff* section at the bottom. There is no `references/*.md` file to consult; the skill is self-contained. ## Workflow #...

Details

Author
LaGrowthMachine
Repository
LaGrowthMachine/gtm-system
Created
2 months ago
Last Updated
2 days ago
Language
Python
License
MIT

Integrates with

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