PM hiring is signal-starved: recruiters skim for roadmap scope, metric ownership, and cross-functional delta. Launch CV turns your wins into the exact language they screen for — quantified, baselined, ATS-clean.
PM keyword library — pre-loaded
+ 120 more across B2B, B2C, marketplace, and platform PM tracks.
Four dimensions of PM impact
Every AI-generated PM bullet contains all four. Senior reviewers scan for them in the first six seconds.
Team size, surface area, customer segment, dollar value of owned product line.
Activation, retention, conversion, NPS, revenue, latency — whichever you moved.
Before → after. Percentage and absolute. Annualized when honest.
vs. control, vs. prior quarter, vs. industry benchmark.
3 real rewrites
Before
“led product team”
After · AI rewrite
Owned PM workstream for 3 squads (8 engineers, 2 designers) shipping the activation funnel rebuild — moved D7 activation from 31% → 48%.
Before
“did user research”
After · AI rewrite
Ran 24 generative interviews + a 9-segment cluster analysis across 1,200 NPS responses — reframed our ICP, killed 2 planned features, accelerated 1.
Before
“worked on pricing”
After · AI rewrite
Led pricing experiment moving Starter from $19 → $9/mo with a Lifetime tier — net-new MRR up 38%, conversion-to-paid up 2.4×, churn flat.
Sections built for PMs
Named launches with scope, segment, and outcome. Public ones link out.
A/B tests, scope, lift, statistical significance. Failures honestly noted.
User interviews, surveys, JTBD studies — quantified by reach and decisions changed.
C-suite reviews owned, cross-functional partnerships, board updates if applicable.
Public-speaking, blog posts, podcast appearances, internal RFCs cited externally.
MBA, Reforge, Lenny's, PMC — issued and verified-link-included where possible.