Sets up pre-launch tracking for product launches with UTM parameters, analytics events, baselines, and dashboards; runs post-launch retros using KPIs and benchmarks.
From launch-skillsnpx claudepluginhub amplitude/builder-skills --plugin launch-skillsThis skill uses the workspace's default tool permissions.
Provides UI/UX resources: 50+ styles, color palettes, font pairings, guidelines, charts for web/mobile across React, Next.js, Vue, Svelte, Tailwind, React Native, Flutter. Aids planning, building, reviewing interfaces.
Fetches up-to-date documentation from Context7 for libraries and frameworks like React, Next.js, Prisma. Use for setup questions, API references, and code examples.
Calculates TAM/SAM/SOM using top-down, bottom-up, and value theory methodologies for market sizing, revenue estimation, and startup validation.
This skill covers how to measure product launches — what to set up before launch day, what to track during, and how to evaluate results afterward. Without consistent measurement, launches are guesswork. With it, each launch informs the next.
Measurement starts before launch day. Setting up tracking the day of the launch means you miss the first-wave data when traffic is highest.
UTM parameters track where traffic comes from. Use a consistent naming scheme across all launches so you can compare over time.
utm_source = the platform (twitter, linkedin, email, producthunt, hackernews)
utm_medium = the channel type (social, email, paid, referral)
utm_campaign = the launch name (feature-name-launch, v2-launch, etc.)
utm_content = the specific asset (tweet-thread, announcement-email, blog-post)
Example URLs:
?utm_source=twitter&utm_medium=social&utm_campaign=realtime-api-launch&utm_content=launch-tweet?utm_source=email&utm_medium=email&utm_campaign=realtime-api-launch&utm_content=announcement-email?utm_source=producthunt&utm_medium=referral&utm_campaign=realtime-api-launch&utm_content=ph-listingRules:
Before launch, verify these analytics events exist and fire correctly:
| Event | Description |
|---|---|
landing_page_view | Landing page loaded with UTM params captured |
signup_started | User begins registration |
signup_completed | Account created |
first_action | First meaningful product action (varies by product) |
cta_click | Each CTA button clicked (with label) |
blog_post_view | Launch blog post loaded |
email_open | Launch email opened (from email platform) |
email_click | Link clicked in launch email |
If these events don't exist and you don't have time to add them before launch, at minimum use UTMs to measure traffic and signups from whatever analytics platform you already have.
What "success" looks like depends on launch tier. Don't compare a Tier 3 changelog tweet to a Tier 1 product launch.
| Metric | What it measures | Where to track |
|---|---|---|
| New signups (day 1, week 1) | Direct acquisition impact | Product analytics |
| Landing page visitors | Reach of the announcement | Web analytics |
| Landing page → signup conversion rate | Page effectiveness | Web analytics |
| Email open rate | List engagement | Email platform |
| Email click rate | Email copy effectiveness | Email platform |
| Social impressions + engagements | Awareness | Native platform analytics |
| Press mentions | PR reach | Manual + Google Alerts |
| Backlinks generated | SEO impact | Ahrefs, Search Console |
| Product Hunt rank (if applicable) | PH-specific reach | Product Hunt |
| Metric | What it measures |
|---|---|
| New signups from launch traffic | Acquisition |
| Feature adoption rate (existing users) | Activation |
| Blog post views | Content reach |
| Social engagement rate | Resonance |
| Email open + click rate | List engagement |
| Metric | What it measures |
|---|---|
| Changelog views | Awareness among existing users |
| Social post engagement | Reach |
These are rough benchmarks for a B2B/developer tool with an established audience. Use them to calibrate expectations, not as hard targets.
| Metric | Weak | Solid | Strong |
|---|---|---|---|
| Email open rate (existing list) | < 20% | 30-40% | > 50% |
| Email click rate | < 2% | 4-8% | > 10% |
| Landing page → signup CVR | < 2% | 5-10% | > 15% |
| Twitter launch tweet impressions (10K followers) | < 5K | 10-30K | > 50K |
| HN front page (if hit) | — | 200-500 visits | 2,000+ visits |
| Product Hunt (featured) | < 100 upvotes | 200-500 | 500+ |
| Tier 1 launch: week-1 signups | < 100 | 200-1,000 | 1,000+ |
These vary enormously by audience size, product category, and launch quality. Treat them as directional.
On launch day, watch metrics in near real-time for the first 4-6 hours. This is when you can still adjust (reshare a post, send a follow-up tweet, extend a limited offer).
What to watch:
Don't do:
Run the retro within 5-7 days of launch, when the data is fresh. For Tier 1, schedule this during launch prep. For Tier 2, a Slack thread async works.
Before the retro, gather:
The retro should produce exactly two things:
Document in a shared place (Notion, Linear, Confluence) so it accumulates over launches. The value compounds: after 10 launches, you have a quantitative model of what works for your product and audience.
Track every launch in a single spreadsheet or database:
| Launch | Date | Tier | Top channel | Signups (D1) | Signups (W1) | Email open rate | Notes |
|---|
After 5+ launches, patterns emerge:
This history is your most valuable launch asset. It makes future launch planning faster and more accurate than any external benchmark.