SafeGraph Data Marketplace Case Study
From 4-Week Sales Cycles to Instant Purchase: Building Self-Service Data Commerce
Overview
SafeGraph is a geospatial-data company that provides high-precision datasets about “places” around the physical world, such as:
- Points of interest (POIs) with attributes – e.g. brands, small businesses, industrial locations, etc.
- Geometry (footprints of places to reduce attribution errors) – e.g. building outlines, area size, spatial relationships, etc. to make sure you know exactly which business is in which footprint.
- Attributes (additional metadata beyond location) – e.g. brand name, category codes like NAICS, open/closed status and other business identifiers
Their mission is to build “the most accurate global places dataset available” and make it accessible.
In keeping with their mission, SafeGraph desired to go to market with a self-serve Data Shop that lets prospective customers preview datasets and buy exactly the records they need, within an easy to use platform.
The Challenge
Long, manual cycles made smaller/research buyers expensive to serve and slowed developers from “interest” to “first successful query.” This led to missed revenue or lengthy support tickets.
SafeGraph needed a low-friction way for buyers to validate fit, purchase precisely what they need, and get data instantly, without AE/SE hand-offs, custom fulfillment, or billing confusion.
Solution
Self-Serve Data Shop
Dataset preview
Curated samples to validate schema/fit pre-purchase
Pay-per-record
QuickBuy only what’s needed
Billing & credits
Statements, transactions, remaining credits, and next-invoice clarity
My Downloads
Order history + secure presigned file delivery
Places API UX
Onboarding cues
“Head to Docs” prompts, create-token CTA, inline microcopy
API portal
Generate/manage tokens, see usage/record counts, and monitor billing
How it works
How it works
Discover → Preview → Purchase → Download.
Customers explore samples, choose a dataset, check out, and retrieve files via presigned URLs, no tickets or waiting. Developers create a token and run test queries immediately, with usage and billing visible in-product.
Why it works
- Product-decision loop mirrors buyer risk: Preview → buy → download
- Developer-first: Tokens + usage + docs live in-product
- Operational guardrails: Transparent credits/billing and formalized APIs reduce internal load
Architecture
Frontend: React for preview, checkout, order history, downloads
Auth: Amazon Cognito (hosted UI)
BFF: Node + GraphQL orchestrating previews, orders, presigned URLs, user updates
Data Services: SafeGraph APIs (Preview, Brand Autocomplete, NAICS → plain-English, Location, Data Orders)
Data & Compute: S3 (packages), RDS (orders), Spark
Messaging: AWS Lambda (data-ready + password resets)
Results (Sales Cycle & Time Saved)
From manual sales to instant checkout
4 weeks → ~5 minutes for self-serve purchases
Time-to-first-value for developers
Token creation + sample queries in one session → activation in minutes, not days
Less internal coordination
- Fewer back-and-forths on quotes, access, credits, and delivery
- Near-zero fulfillment overhead per order (presigned S3 + automated status emails)
Before → After
Access
Email threads & approvals → Sign-in with hosted UI
Evaluation
PDFs/one-offs → In-app curated previews
Pricing
Custom quotes → Transparent pay-per-record
Payment
Invoicing cycles → Card checkout with Stripe
Delivery
Manual file handoffs → Immediate presigned downloads
Activation
“We’ll set you up” → Create token & call API now