The storyHow they got there
Steven Goh launched Proxycurl (under Nubela) around 2018 from Singapore, funded by crypto profits and prior side projects. The product was simple: a reliable API to extract LinkedIn data at scale. Every sales and marketing team wanted this solved — LinkedIn's own API was locked, and scraping at scale kept breaking.
The first ten customers came from LinkedIn API banned-tool refugees: people posting in r/datasets and r/webscraping looking for alternatives. The cold email approach was deliberately abandoned — Steven didn't want sales calls. The first hundred came from programmatic SEO: thousands of comparison and use-case pages generated at scale.
At maturity, the channel mix: programmatic SEO with pages targeting "find email of [role]" and "LinkedIn API alternatives" (~55%), developer content and tutorials on Medium and dev.to (~20%), word-of-mouth among data engineers and sales-ops teams (~15%), and G2/Capterra category pages (~10%).
Unit economics: CAC around $100–200 from mostly organic traffic, ARPU around $200–500/month on usage-based pricing, LTV around $3–5K with low churn because the API gets integrated directly into customer pipelines. The strict no-sales-calls policy under $50K ARR kept margins high and the team lean. Docs ARE the marketing site for developer APIs.
Channel MixWhere the growth actually came from
Most case studies hand-wave channels. Here's the rough allocation — not in dollars spent, but in users acquired — across the routes that actually mattered.