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AIDevGTMAIDevGTM/gtm-cofounder/skills/15-know-if-its-working/SKILL.md

know-if-its-working

Skill334 starsChanged 3 months agoMITView on GitHub

Measure GTM with the metrics that matter (net developer retention, DREAM funnel) instead of vanity numbers. Use when the user has dashboards full of stars and pageviews but can't tell if go-to-market is working, or is optimizing acquisition over a leaky bucket.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Don't over-trust last-touch.

    line 47
  2. Distinctive:

    Add a "how did you hear about us?" free-text field.

    line 48
  3. Distinctive:

    If your numbers are telling a story you can't read, get a human to look with you.

    line 77

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Know if it's working

The only early metric that matters is net developer retention. Without it, you're not running a funnel; you're running a colander.

Use this when: you're tracking GitHub stars and pageviews and still can't answer "is GTM working?", or you're pouring effort into acquisition while new users quietly churn.

The core idea

Acquisition is worthless if users don't come back. Prove retention first; only then does spending on acquisition make sense. Most early founders optimize the top of the funnel while the bottom leaks. Fix that order.

Framework: net developer retention (Frankl)

Of all the developers who first used the product in Month 1, how many used it in Month 2? Month 3?

  • Hold it above 100% (meaning existing cohorts grow through internal referral/expansion).
  • Below solid retention, do not focus on acquisition: you're filling a leaky bucket.
  • This single cohort question tells you more than every vanity chart combined.

Framework: the DREAM metrics (Frankl)

Measure one honest number per stage, not pageviews, not stars.

StageThe metric that counts
Discoveryunique human visitors / month
Researchnewsletter subs + community joins + follows
Evaluationfree-tier signups / downloads / active free users
Activationmonthly active users · frequency · session depth
Membershipcommunity members actively posting & answering

The gate before all of it, the weekend test: can a new developer get to first value over a weekend from docs + Stack Overflow, no support call? Time-to-value target: < 1 hour ideal, 1 day max. If Evaluation/Activation fails here, no channel work will save you.

Growth benchmarks (non-ARR, Frankl)

  • Pre-seed: ~30% month-over-month user growth
  • Post-Series-A: ~10% MoM
  • First $1M ARR: within 12 months is good, 9 is excellent

Framework: attribution philosophy (Czakon)

Developer marketing is hard to attribute and that's normal. A dev sees your HN post, reads a tutorial, lurks for two months, then signs up direct.

  • Don't over-trust last-touch; it will tell you "direct/organic" and hide the real work.
  • Add a "how did you hear about us?" free-text field. Self-reported attribution beats a broken model.
  • Judge channels on trend and directional signal, not spurious precision.

Decision tree: what to fix first

Is month-2 cohort retention healthy (users come back)?
├─ NO  → STOP optimizing acquisition. Fix Evaluation/Activation (the weekend test, time-to-value).
└─ YES → is a channel reliably producing retained users?
         ├─ YES → pour more in (and only now consider paid to amplify).
         └─ NO  → go back to first-50-users; find the channel before scaling spend.

Mistakes that look reasonable

  • Vanity metrics: stars, pageviews, impressions. They feel like progress and predict nothing.
  • Acquisition over a leaky bucket: buying users who never return.
  • Demanding clean attribution: chasing a perfect model instead of acting on directional signal.
  • Ignoring the weekend test: a beautiful funnel that dies at first-value.

Your next 30 minutes

  • Compute one number: of the devs who first used it 8 weeks ago, what % used it in the last 2 weeks?
  • Pick one honest metric per DREAM stage; delete the vanity charts from your dashboard.
  • Time yourself doing your own onboarding cold. Over an hour? That's your #1 GTM problem.
  • Add a "how did you hear about us?" field to signup this week.

Built from real dev-tool GTM experience, with frameworks from Adam Frankl (The Developer-Facing Startup) and Jakub Czakon (markepear.dev). If your numbers are telling a story you can't read, get a human to look with you. Reach out to me on LinkedIn.

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