Optimizes SaaS conversion funnels by mapping steps, identifying drop-offs, simplifying signups and pricing pages, reducing friction, and using social proof and A/B testing.
npx claudepluginhub whawkinsiv/solo-founder-superpowers --plugin solo-founder-superpowersThis skill uses the workspace's default tool permissions.
Every page has one job. If you can't name it, the page is broken. This skill helps you find where users drop off and fix it.
Provides Ktor server patterns for routing DSL, plugins (auth, CORS, serialization), Koin DI, WebSockets, services, and testApplication testing.
Conducts multi-source web research with firecrawl and exa MCPs: searches, scrapes pages, synthesizes cited reports. For deep dives, competitive analysis, tech evaluations, or due diligence.
Provides demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation for multi-location retailers managing 300-800 SKUs.
Every page has one job. If you can't name it, the page is broken. This skill helps you find where users drop off and fix it.
Before optimizing, find where users actually drop off.
Typical SaaS funnel:
Landing page visit → Signup page viewed → Account created →
Onboarding started → Key action completed → Returned next week →
Upgrade page viewed → Subscription created
Tell AI:
Analyze our conversion funnel:
- Pull the number of users at each step: [list your funnel steps]
- Calculate the drop-off % between each step
- Identify the step with the biggest drop-off — that's our priority
- Show results in a table: Step | Users | Drop-off %
If you don't have analytics yet: Set them up first (see analytics-instrumentation skill). In the meantime, track manually: count signups, count activations, count paying customers. Even rough numbers reveal the biggest leak.
For the biggest drop-off, evaluate the page/flow using this framework:
Tell AI:
Simplify our signup flow:
- Reduce to email + password (or email-only with magic link)
- Add Google Sign-In as the most prominent option
- After signup, redirect directly to onboarding (not "check your email")
- Defer all profile questions (name, company, role) to later
Tell AI:
Optimize our pricing page:
- Highlight the recommended tier with a visual badge ("Most Popular")
- Default to annual pricing (show monthly as toggle)
- Add a comparison table showing features by tier
- Add FAQ section below pricing addressing common objections
- Add social proof near the CTA: "[X] teams already use [Product]"
Tell AI:
Improve trial-to-paid conversion:
- Show usage meters on the dashboard: "X of Y [resource] used"
- When user hits 80% of a limit, show a gentle prompt: "You're growing! Upgrade for unlimited [resource]"
- 3 days before trial ends, show banner: "Your trial ends [date]. Keep everything by upgrading."
- After trial ends, downgrade features but keep their data intact
Tell AI:
Convert our [signup/onboarding] form to multi-step:
- Step 1: The easiest, most engaging question
- Step 2: The information we need to deliver value
- Step 3: Account details (email, password)
- Add progress indicator ("Step 2 of 3")
- Validate inline on blur with green checkmarks
- Use appropriate input types (email, tel, number) for mobile keyboards
| Trigger | How to Use It |
|---|---|
| Loss aversion | "Your free trial ends in 3 days" > "Upgrade now" |
| Social proof | "4,200 teams signed up this month" |
| Anchoring | Show the "before" (manual, slow) vs. "after" (with your product) |
| Commitment/consistency | Small yes → big yes. Free tool → signup → paid. |
| Scarcity (use honestly) | "3 spots left in this cohort" (only if true) |
Tell AI:
Add social proof and behavioral triggers to our [signup/pricing/landing] page:
- Add a live counter or recent activity: "[X] teams signed up this month"
- Add testimonial quotes near the CTA
- Add trust badges near payment forms (SSL, money-back guarantee)
- Frame the CTA as low-commitment: "Start free — no credit card required"
You don't need complex testing infrastructure. Here's the bootstrapped founder approach:
Tell AI:
Set up a simple A/B test:
- Create a feature flag that splits users 50/50
- Variant A: [current version]
- Variant B: [proposed change]
- Track [conversion event] for both variants
- Run until we have 100+ users per variant (or 2 weeks, whichever is longer)
- Show me the conversion rate for each variant
Rule: Don't peek at results daily and stop early. Set a duration and stick to it.
| Metric | What It Tells You |
|---|---|
| Signup rate (visitor → account) | Is your landing page compelling? |
| Activation rate (account → key action) | Is your onboarding working? |
| Trial-to-paid conversion | Is your product delivering enough value? |
| Time to value | How fast do users reach "aha"? |
| Expansion revenue triggers | What behavior precedes upgrades? |
| Mistake | Fix |
|---|---|
| Optimizing low-traffic pages | Focus on your highest-traffic funnel step |
| A/B testing button colors | Test headlines, CTAs, and page structure instead |
| Adding more fields "for data" | Every field costs conversions. Defer to later. |
| Ignoring mobile | 50%+ of traffic is mobile. Test there first. |
| Complex testing tools at small scale | Feature flags are enough until 1,000+ users/week |