How Kyle Fowler built $42k/month passive income with two no-code card scanner apps

Executive overview

Two niche app store apps — Cardstock and Scanamon — generate $41k MRR with no VC funding. The growth came in two phases: years of passive income from App Store Optimization, then a deliberate shift to TikTok when rankings dropped.

The core insight: owning a high-value keyword in an underserved niche can produce years of passive revenue — but you need a second channel before you lose that ranking.

Origin and early growth

• Built Cardstock in 2019 to solve his own problem: no app existed to scan and value baseball cards
• Validated the idea with a Reddit post before building; a DM from a stranger prompted him to finish it
• Launched at $4.99 flat on the App Store; 12 paid downloads on day one from a single Reddit post
• Switching from paid download to a freemium subscription model was the single biggest revenue jump ever
• Pricing settled at $5/month, $50/year, $99 lifetime

ASO: the passive income engine

• Spent one to two weeks researching keywords on Sensor Tower; focused on "baseball card scanner" and "find value for baseball cards"
• Held the number one App Store ranking for those keywords for two to three years with zero ad spend
• Was generating ~$9–10k MRR passively throughout college from search alone
• Lost rankings in May 2024 — the forcing function to find a second channel
• Key advice: use Sensor Tower free trial, brainstorm a keyword list, rank by search volume, put the best ones in your title

TikTok: cracking the format

• Hired a friend (Jacob) from Wendy's with no content experience; early videos got ~20 likes
• Iterated until finding a repeatable format: show a desirable card for 3–5 seconds, scan it with the app in hand, reveal the value
• The goal of every video is the "what's the app?" comment — not brand awareness
• Added the app logo inside the scanner UI to associate the brand without a call-to-action
• Key principle: control as many variables as possible so the format is repeatable and testable

Scaling with Noise

• Used Noise (a UGC/slideshow distribution platform) to scale to 9,000+ posts in a month for ~$2,600 (~$1 CPM)
• Creators pull from a pre-built Google Drive of hook images and captions; Noise handles payouts
• Bulk posting at low CPM converts even without viral posts — sheer volume drives download volume
• Noise dashboard shows which hooks and images outperform, enabling continuous iteration
• Slideshows work because the format is fully controllable: hook, image sequence, and caption are all pre-set

Scanamon and the second app

• Built Scanamon (Pokémon card scanner) as a natural extension using existing framework and AI dev tools
• Launched with the TikTok slideshow format already proven from Cardstock
• Currently at ~$9k MRR; the same scaling playbook applied from day one
• Created a separate creator account with an AI-generated profile to broaden audience appeal

Philosophy on growth channels and learning

• Believes most channels work — the question is which one you can execute well enough
• Bootstrap constraint forced him to learn before hiring, which made him a better evaluator of agencies and talent
• Learning process: ask trusted network contacts first, then dig into specialised communities (Twitter, Discord), then use AI/search for specifics
• The willingness to just do the thing and iterate is the differentiator, not access to secret tactics