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Orbit Financial Model

Orbit is a SaaS platform that ingests signals from developer communities (GitHub, Slack, Twitter, Discourse, etc.) and structures them using the proprietary "Orbit Model." The model classifies community members by two axes:

• Love: measure of a member's activity level in the community
• Reach: measure of a member's sphere of influence

Members are segmented into four orbit levels (1 = most engaged Ambassadors → 4 = passive Observers). The platform then surfaces recommended actions (reply on GitHub, tweet shoutout, send personal email) directly inside the product, automating community engagement workflows.

Key differentiator: the Orbit Model is open source (github.com/orbit-love/orbit-model, 180 stars, 13 contributors as of deck date) which drives bottom-up awareness and product-led adoption. The commercial platform adds analytics, reporting, and action execution on top of the free model.

All traction shown is for the Orbit Model open source project and Orbit's own community (their dog-fooding instance), not for paying customers:

• Orbit Model GitHub repo: 180 stars, 22 watchers, 13 contributors
• One customer community (API Evangelist's dashboard, Aug 2019 – Aug 2020):
• Total members: 644
• Orbit 1 (Ambassadors): 24; Orbit 2: 72; Orbit 3: 110; Orbit 4 (Observers): 328
• Orbit's own community dashboard (Feb 1 – Aug 31, 2020):
• Total members: 821
• Orbit 1: 63; Orbit 2: 75; Orbit 3: 393; Orbit 4: 267
• Activities tracked by type: GitHub (issues, PRs), Twitter mentions, Slack, events, signups - weekly activity volume rising from ~5–10/week in Feb 2020 to ~80+/week by Aug 2020
• No ARR, MRR, paying customer count, or revenue figures in deck.

• Deck positions existing CRMs as the incumbent workaround - citing a16z's Martin Casado tweet calling CRMs "an ill fit" for community-led growth
• Cultural problem framed: enterprise sales teams doing outbound (LinkedIn spam) on developer communities is actively counterproductive
• Moat claimed: open-source Orbit Model drives bottom-up adoption and word-of-mouth; brand equity with DevRel community
• No named direct competitors listed.

Team:

• Patrick Woods, CEO - Director of Customer Success at FigureEight & Keen IO; Partner at DeveloperMode
• Josh Dzielak, CTO - DevRel Lead at Algolia; VP Engineering at Keen IO; Partner at DeveloperMode
• Backed by Heavybit Industries and Harrison Metal (accelerator/early-stage investors implied)

Advisors:

• James Tamplin (CEO & Founder, Firebase)
• Sam Ramji (CSO, DataStax; former Head of DevRel, Google)
• Aghi Marietti (CEO & Founder, Kong)
• Andrew Miklas (CTO & Founder, PagerDuty)
• Kyle Wild (CEO & Founder, Keen IO)
• James Governor (Co-founder, RedMonk)

Ask:

• "Thoughtful partners" - no dollar amount specified
• Use of funds: scale product & engineering; onboard new customers; category evangelism; refine pricing and packaging

• Archetype + why: SaaS ARR model (bottom-up PLG motion). Revenue is subscription-based SaaS targeting DevRel/community teams. Growth is product-led (open-source model → platform trial → paid conversion), making a seats/workspaces ARR model most appropriate. No marketplace or transactional layer evident.

• Forecast horizon & granularity: 3 years monthly (Month 1–36), then annual summary. Early stage with no revenue yet means Year 1 is largely pre-revenue / early customer ramp; monthly granularity matters for cash runway and hiring pacing.

• Key drivers & assumptions:
• New logos per month (customer count ramp): starts at 2–5/month in Month 1, scaling to 20–30/month by Month 24 as PLG flywheel builds; rationale: pre-revenue stage, small team
• Average ACV: $6,000–$18,000/year (community tools typically $500–$1,500/month for SMB DevRel teams); no pricing in deck
• Seats or workspaces per customer: 1–3 seats per DevRel/community team; rationale: small buyer persona
• Free-to-paid conversion rate: 3–8%; rationale: PLG open-source → paid, typical for developer tools
• Monthly churn: 1.5–2.5%; rationale: DevRel budget is discretionary and smaller companies may churn
• Gross margin: 70–80%; rationale: pure SaaS, likely AWS-hosted, minimal COGS
• Headcount plan: 8–12 FTEs post-raise (engineering-heavy, 1–2 AEs, 1 DevRel); salaries drive OpEx
• CAC: $2,000–$5,000 (PLG-assisted, low-touch sales); no data in deck
• LTV: derived from ACV / churn; at 2% monthly churn, avg customer life ~50 months → LTV/CAC likely 8–15x at scale
• S&M as % revenue: 40–60% in early years, declining as PLG matures
• R&D as % revenue: 35–50% in early years (engineering-first company)
• G&A: 15–25% in early years

• Scenarios (Base / Bull / Bear - which variables flex):
• Base: 3–5 new logos/month at launch, 5% free-to-paid conversion, $10k ACV, 2% monthly churn
• Bull: Orbit Model open-source virality accelerates; 10–15 logos/month by Month 12, ACV lifts to $15k as enterprise buyers enter, churn drops to 1%
• Bear: Pricing/packaging takes longer to finalize (deck acknowledges this); slow logo growth (1–2/month), ACV $6k, churn 3%

• Required sheets / outputs:

1. Assumptions dashboard (all drivers in one place)
2. Customer cohort model (monthly new logos, cumulative ARR by cohort, churn waterfall)
3. P&L (Revenue, COGS, Gross Profit, S&M, R&D, G&A, EBITDA)
4. Headcount plan (by function, fully-loaded cost)
5. Cash flow & runway (monthly burn, cash balance, months of runway)
6. ARR bridge (new ARR, expansion, churn, net new ARR)
7. Unit economics summary (CAC, LTV, LTV/CAC, payback period)
8. Scenario toggle (Base / Bull / Bear)