# SafeGraph Financial Model SafeGraph is the definitive data set for physical places - selling raw location/POI data via subscription to enterprises. - Canonical: https://finamodel.com/startups/safegraph - Excel download: https://finamodel.com/startup-models/safegraph.xlsx - Category: Crypto/Web3 - Model type: SaaS ARR / Valuation - Funding round: Series B - Funding: $45M - Founded: 2021 - Geography: U.S. & Canada (primary); aggressive international expansion flagged as next initiative [DECK slide 11]. - Customer: B2B ## About the company SafeGraph sells raw location and points-of-interest data to enterprises. Its data-as-a-service proposition supplies a definitive physical-places dataset for customers building analytics, mapping, and other real-world applications, deliberately focusing on data rather than a software analytics or visualisation layer. The company was growth-stage and primarily served the US and Canada, while identifying international expansion as its next initiative. The research does not provide a fee schedule, so a model should start from enterprise contracts and data-product adoption rather than inventing transaction economics. Forecast enterprise customers, average contract value, data products per customer, usage expansion, renewals, and churn to build subscription revenue. Model data sourcing, validation, licensing, delivery infrastructure, customer support, and sales capacity below gross profit. New logos, expansion, international rollout, data-quality cost, pricing, and net retention are the principal scenario levers. ## What's included - 5-year monthly revenue build with stage-appropriate growth assumptions - Full P&L, headcount plan, and operating-expense schedule - Cash-flow statement, runway, and burn-rate tracking - Valuation via exit multiple with a DCF cross-check - Returns analysis with MOIC and IRR - Unit economics including CAC, LTV, payback, and cohort retention ## Product & value proposition Three data products: - **Core Places** - business listings for 6.8M points of interest (POI). - **Geometry** - building footprints with spatial hierarchy for POI. - **Places Patterns** - foot-traffic insights derived from anonymised mobile devices. Underlying differentiator: "maniacal focus on truth / veracity" - pure data, no analytics or visualisation. Placekey is a free, open universal identifier for physical places that allows customers to join SafeGraph data to third-party datasets; 200M+ places globally. ## Revenue model - Annual recurring subscription (ARR) per customer. - Customer ARR ranges illustrated: $100K–$500K (mid-market) and $500K–$1M (enterprise). - Sold into: Retail & Real Estate, Geospatial, Supply Chain & Logistics, Healthcare. - Self-serve data store and APIs flagged as future channel. - No per-seat or usage pricing disclosed; model implies fixed annual data licence. ## Traction & metrics - 4 customer ARR snapshots: - Customer A (Retail & Real Estate): $500K–$1M ARR - Customer B (Geospatial): $100K–$500K ARR - Customer C (Supply Chain & Logistics): $100K–$500K ARR - Customer D (Healthcare): $500K–$1M ARR - Placekey community: 1,000+ organisations; 7,000 Placekey community members using SafeGraph data. - Slack community: 6,600 members including CDC, Federal Reserve. - 300+ peer-reviewed academic papers written by consortium members in 2020. - White House, Dallas Fed, CDC cited as data users. - Coverage: 6.8M POI, 5,800 major brands, U.S. & Canada; 200M+ places globally via Placekey. - Total ARR, YoY growth rate, customer count, and churn not disclosed. ## Unit economics - LTV to CAC: >4x. - SaaS Magic Number: ~1.0. - Efficiency Score: >1.5. - Gross margin, absolute CAC, LTV, or payback period not disclosed. ## Competition / moat Not explicitly addressed in deck. Implied moats: - Winner-takes-most data network effect (more users → more data → better product → lower price). - Placekey as open standard creates ecosystem lock-in and data-joining infrastructure. - 5,800 brand relationships and 6.8M POI scale creates high replication cost. - Named competitors: not named. ## Team & funding ask / use of funds **Team**: - Auren Hoffman - CEO (previously LiveRamp) - Felix Cheung - VP Engineering (previously Uber, Microsoft) - Lauren Spiegel - VP Product (previously Scality) - Jason Cook - VP Sales & Customer Success (previously Radius) - Nicole Berger - VP Operations (previously Slyce, SIG) - Evan Barry - VP Marketing (previously Raken, Branch) - Karissa Paddie - VP Corporate Strategy (previously Bolt) - Ross Epstein - VP New Projects (previously Sendbloom, LinkedIn) - Jonathan Wolf - VP Partnerships (previously Envestnet, Bazaarvoice) --- ## Recommended financial model - **Archetype + why**: DaaS / B2B subscription ARR model. Revenue is pure annual data licence subscription; unit economics language (LTV/CAC, Magic Number, Efficiency Score) confirms SaaS-adjacent metrics. No marketplace or transactional GMV. Close to enterprise SaaS but with DaaS nuances (data refresh costs vs. hosting, no seat-based pricing). - **Forecast horizon & granularity**: 3 years (2021–2023), monthly for Year 1 then quarterly for Years 2–3. Given COVID-era tailwinds and international expansion plan, monthly granularity in Year 1 captures ramp dynamics. - **Key drivers & assumptions**: - Starting customer count: ~20–50 paying enterprise customers; deck shows 4 illustrative logos but references broad industry coverage - estimate conservative; no disclosed number. - Blended ACV (annual contract value): ~$300K based on midpoints of disclosed ARR bands ($100K–$1M range, two buckets); weight toward mid-market given product stage. - New logo adds per quarter: 3–6 net new logos in Year 1, scaling to 8–12/quarter by Year 3 as self-serve channel opens. - Net revenue retention (NRR): 110–120%; DaaS businesses with diverse use cases typically expand as customers add more products/geographies; Placekey ecosystem increases stickiness. - Gross margin: 70–80%; data businesses have high gross margins once data is collected; mobile data ingestion + cleaning costs are the primary COGS. - LTV/CAC >4x; implies payback <3 years at assumed ACV and gross margin. - SaaS Magic Number ~1.0; implies S&M spend ~= incremental ARR - use as constraint/check on S&M budget. - Efficiency Score >1.5; use as forecast sanity check (ARR added / (S&M + R&D spend)). - International expansion: begins Year 2, contributing 10–15% of new logos by Year 3. - Placekey community conversion rate to paid: 2–5% of 7,000 community members convert annually; drives a freemium-to-paid funnel in model. - **Scenarios (Base / Bull / Bear - which variables flex)**: - Bear: ACV stays flat, NRR = 105%, new logo adds 2–3/quarter, no international contribution. - Base: ACV grows modestly, NRR = 115%, new logos per assumptions above, self-serve channel adds ~10% of new ARR by Year 3. - Bull: ACV expands via upsell to $400K+, NRR = 125%, acquisition of complementary data companies adds inorganic ARR, international = 20% of new ARR by Year 3. - **Required sheets / outputs**: 1. Assumptions - all drivers with scenario toggle (Base/Bull/Bear via CHOOSE). 2. ARR Bridge - opening ARR, new ARR, expansion ARR, churn ARR, closing ARR per period. 3. Revenue & Gross Profit - ARR → recognised revenue (assume annual prepay = ARR), COGS, gross margin. 4. Unit Economics - CAC by cohort, LTV, payback, Magic Number, Efficiency Score (to tie back to deck). 5. P&L - Revenue, GM, S&M, R&D, G&A, EBITDA. 6. Headcount - by function, drives S&M and R&D opex. 7. Cash & Runway - if raise not disclosed, show cash burn and implied runway at various funding levels. 8. Dashboard - ARR growth, NRR, Magic Number, Efficiency Score, LTV/CAC. ## Frequently asked questions ### Is the SafeGraph financial model free? Yes. The SafeGraph model is a free Excel download with live formulas. ### Can I change the assumptions? Yes. The workbook is editable and its live formulas recalculate when assumptions change.