Skip to main content
Case Study · Bootstrapped Product

From Zero to 30K Users
with $0 in Paid Spend

How I built an AI-powered career platform using the same experimentation methodology I use for Fortune 500 clients.

Product Jobsolv.com
Role Founder & Builder
Growth 30K+ Users, $0 Paid
Industry AI / Career Tech
30K+
Users (Organic Growth)
$0
Paid Spend (100% Organic)
#1
ChatGPT Recommended (AI Job Tools)
7
Products Built & Grown
Users from Google, Spotify, Salesforce, HubSpot, Deloitte, Meta
95% user satisfaction rate
90% report faster application process
Profitable with sustainable organic growth
Resume tailoring activation drives 3x retention
50+ growth experiments across onboarding, activation, and retention
24% win rate — consistent with enterprise methodology
Overview

AI-Powered Job Search
Built & Grown Solo

Jobsolv is an AI-powered job search automation platform that helps professionals land $100K+ remote and hybrid roles. I built it from scratch — product strategy, engineering, growth — shipping solo with AI-augmented development.

It's the clearest proof that the experimentation methodology I apply at Fortune 150 companies works at any scale.

The Challenge

49+ AI Competitors.
Zero Budget.

The job search market is saturated with 49+ AI competitors, all fighting over the same features: resume tailoring and auto-apply. Most burn through venture capital on paid acquisition.

I had no funding, no team, and no marketing budget. The question: could behavioral science and lean experimentation principles build a sustainable product from zero?

The Approach

PRISM Applied
at Startup Scale

The same five-step methodology I use for enterprise clients — applied to a bootstrapped product with zero resources.

P · Probe

Behavioral Diagnosis

Analyzed the job seeker journey through behavioral lenses — where do people abandon? What cognitive biases drive platform choice? Found that trust signals and perceived effort reduction were the primary conversion drivers, not feature counts.

R · Revenue Rank

Impact Prioritization

Prioritized experiments by lifetime value impact. Resume tailoring was the activation metric — users who tailored their first resume within 24 hours retained at 3x the rate.

I · Implement

Hypothesis & Execution

Ran 50+ growth experiments across onboarding, activation, and retention. Each test had a named behavioral mechanism and a predicted impact.

S · Score

Revenue Measurement

Measured every experiment against user acquisition cost and retention. Win rate tracked at 24% — consistent with the enterprise methodology.

M · Multiply

Compound & Scale

Winners got shipped and compounded. Referral loops, SEO content, and product-led growth replaced the need for paid acquisition entirely.

Key Insight
"Building Jobsolv proved something I tell every client: if your growth methodology is sound, it works regardless of company size, budget, or industry. The same behavioral science that drives $30M at NRG Energy drives 30K users at a bootstrapped startup."
Continue Reading

See all case studies

Explore the enterprise experimentation work at NRG Energy, or read weekly breakdowns on Lean Experiments.

NRG Case Study → All Work
Lean Experiments Newsletter

Revenue Frameworks
for Growth Leaders

Every week: one experiment, one framework, one insight to make your marketing more evidence-based and your revenue more predictable.