RE

RealFriend Financial Model

• Conversational AI assistant ("Luke") available 24/7 via chat that searches, filters, and schedules apartment viewings on behalf of users.
• Hybrid AI: bot handles search and scheduling; human hand-off implied ("hybrid AI real estate assistant").
• User flow: onboarding via chat → natural-language preference capture → proactive listing suggestions → in-app showing scheduling → post-visit follow-up with alternatives.
• Longer-term vision: expand beyond real estate to loans, jobs, cars - AI advisor for all major financial decisions.

• US real estate commissions pool: $100B
• Referral fees sub-pool (25% of commissions): $10B
• US millennials = 40% of home buyers
• Tel Aviv rental market: ~50K apartments rented per year
• No formal TAM/SAM/SOM breakdown or sourced market-size methodology in deck.

• Single revenue line: 25% referral fee from real estate agents on successful closings.
• No subscription, SaaS, or advertising revenue mentioned.
• No pricing per transaction stated explicitly; implied that agent pays 25% of their commission to Realfriend on each deal closed.
• Channel: direct-to-consumer acquisition (word-of-mouth referenced for Tel Aviv growth) → agents pay referral on conversion.

• Tel Aviv: Launched 2018; 53,800 engaged users in 2019; "quickly became market leader in rentals market"; grew word-of-mouth only.
• New York: Beta launched March 2019; 2,500 Monthly Active Users (as of Feb 2020).
• Engagement growth: 25% month-over-month growth in engagement (NYC).
• Retention / satisfaction: >60% of users would be "very disappointed" if service disappeared (Sean Ellis test).
• NPS: NYC = 40 (after 1 year); Tel Aviv = 65 (after 2 years). Benchmarked vs. Zillow (-8), AI assistants (30–40), Tesla/Apple/Airbnb (65+).
• No revenue figures, no transaction volume, no closed-deal counts disclosed.

• Zillow positioned as an inferior alternative (NPS -8 vs. Realfriend's 40–65).
• AI assistants (Hey Google, Amazon Alexa) cited as benchmark (NPS 30–40).
• Moat framing: trust/brand ("world class trusted brand"), conversational relationship depth ("Your mom introduces him"), word-of-mouth organic growth.
• No formal competitive landscape slide.

• Two co-founders: Luke (NYC) and Dooron (Tel Aviv).
• Background: working together 15 years, served in IDF special forces, launched multiple businesses together.
• No funding ask amount, valuation, or use-of-funds breakdown disclosed in deck.

• Archetype + why: Marketplace / referral-fee revenue model with user-funnel P&L. Realfriend earns a 25% cut of agent commissions on closed deals; the core model should track users → conversations → referrals → closed transactions → referral revenue. Closest archetype is a marketplace/lead-gen model, not SaaS (no subscription revenue) and not a 3-statement operating forecast at this stage given the early traction.

• Forecast horizon & granularity: 3-year monthly model (2020–2022), consolidating NYC and Tel Aviv as two separate market tracks that roll up to a combined P&L.

• Key drivers & assumptions:

*Demand / user growth*

• NYC MAU at model start: 2,500
• NYC MoM engagement growth: 25% - will taper: use 25% in H1 2020, declining to 8% by end of year 2 as market saturates
• Tel Aviv engaged users 2019: 53,800 - model as ~4,500/month average active (53.8K/12); MoM growth 5% given mature market
• New market expansion (e.g. LA, Chicago): 1 new city per year from 2021 onward, ramping like NYC beta curve with 6-month lag

*Conversion funnel*

• User-to-referral conversion (users who successfully close a deal via Realfriend): 3%–5% per cohort-month, consistent with consumer real estate search intent
• Average US rental deal commission: ~$2,000–$3,000 (one month's rent as broker fee in NYC); sale deal commission: 2.5%–3% of median NYC price (~$750K) = ~$19K–22K per sale
• Realfriend take: 25% of agent commission
• Mix: 80% rentals / 20% sales to start; shift to 60/40 over 3 years as brand builds

*Revenue per closed deal*

• Rental referral revenue per deal: $500–$750 (25% of one-month broker fee)
• Sale referral revenue per deal: $4,750–$5,500 (25% of ~2.5% commission on ~$750K median)

*Costs*

• Headcount: 6 FTEs at start (2 founders + 4 engineers/ops); scaling to 20 by end of year 2
• AI/infra costs: $5K/month at 2,500 MAU, scaling linearly with users
• Sales/partnerships (agent network): 1 BD hire per city per year
• No inventory, no balance sheet complexity - asset-light

• Scenarios (Base / Bull / Bear - which variables flex):
• Base: 25% MoM NYC user growth tapers to 8% by Y2; 3% conversion; 80/20 rental-sale mix
• Bull: Growth sustains at 20% MoM through Y1; 5% conversion; faster city expansion (2 new cities in 2021)
• Bear: Growth slows to 10% MoM by Q3 2020 (COVID impact plausible given Feb 2020 deck date); 2% conversion; no new city until 2022

• Required sheets / outputs:

1. Assumptions & toggles (centralized)
2. User funnel (MAU by city → referrals generated → closings)
3. Revenue build (rental referrals + sale referrals by city, monthly)
4. OpEx build (headcount plan, infra, marketing)
5. P&L summary (gross revenue, gross margin, EBITDA)
6. Cash runway (monthly burn vs. funding; key for seed raise)
7. Scenario comparison table (Base / Bull / Bear on revenue and runway)