Podbit · BiggerPockets Real Estate Podcast
The 1% rule originated 15 years ago and virtually no market in America averages it today. What matters for investors is a rent-to-price ratio in the 0.6–1% range, which signals you can find deals worth underwriting — not that every average property will cash flow.
Where this was said
At 6:37 · chapter starts 5:00
Before naming his pick, Henry Washington walks through his market selection framework, a five-factor checklist covering price growth, population growth, job growth, rent growth, and income growth over both 1-year and 5-year windows. The goal: find places people want to live that also have jobs for them. Richmond, Virginia clears every bar. [1] — Henry Washington "Richmond, Virginia added 56,000 residents in four years and hosts major employers like Capital One (13,000 employees) and VCU. With a $364,…" 05:00 With a $364,000 median home price and $2,100 median rent, the numbers suggest deals are findable on-market — and great deals off-market. The city has added 56,000 new residents in four years, driven by employers including Capital One (13,000 workers) and VCU's hospital system. The billion-dollar Diamond District mixed-use redevelopment adds further evidence that the city is building roots. Henry sums it up as a market where you'll work for the deal but will be rewarded with both cash flow and appreciation.
Richmond, Virginia added 56,000 residents in four years and hosts major employers like Capital One (13,000 employees) and VCU. With a $364,000 median home price and $2,100 median rent, the numbers work for buy-and-hold investors willing to hunt for deals.
Richmond, Virginia has a median home price of $364,000 and a median rent of $2,100, offering solid rent-to-price dynamics.
SiteGPT attracted over 1 million visitors and $500K in total revenue without spending a cent on paid marketing. The secret: engineering as marketing — building free tools that rank on Google.
Bhanu quit his first job after just 8 months, moved back to his parents' house to cut costs, and started building. One product sold for $250K; the next hit $10K MRR in its first month.
90% of SiteGPT's Google search traffic comes not from the main product but from ~50 free tools Bhanu built. Each tool targets a low-competition keyword and funnels users back to the paid product.
50,000 monthly visitors become 200 leads, 60 trials, and roughly 15–24 new customers per month at ~$100 average revenue each. Add a $1,700–$1,800 LTV and you have a very healthy SaaS.
Start with a blank Ahrefs search, layer in keyword filters (include term, KD < 10, volume > 1,000), list candidates in Notion, design a CTA linking to your main product, then score by volume, difficulty, build effort, and product relevance. That's the whole playbook.
Marketing feels painful for most builders. Engineering as marketing flips the script: instead of writing cold emails or blog posts, you build things — and those things rank on Google forever.
Don't spend months perfecting before launch. Ship the core feature, get real users, and let their feedback dictate the product roadmap. Premature polish is a trap.
SiteGPT launched and hit $10,000 MRR within its first month. That momentum was so overwhelming that Bhanu sold his existing SaaS, Feather, for $250,000 to free up all his time.
PropGPT launched with 20 downloads a day and strong influencer marketing but hit a ceiling at $1,000–$2,000 MRR. High download numbers masked a critical flaw: almost nobody stuck around after the free trial ended.
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