Overview
The PricingSaaS Intelligence API provides comprehensive pricing data for thousands of B2B SaaS companies. This data helps you understand market trends, competitive positioning, and pricing strategies across the software industry.What is Pricing Intelligence?
Pricing intelligence encompasses structured data about how software companies price their products, including:- Subscription tiers - Free, Starter, Professional, Enterprise plans
- Pricing models - Per-user, per-feature, usage-based, flat-rate
- Feature breakdowns - What features are included in each tier
- Price points - Actual pricing amounts (when publicly available)
- Billing cycles - Monthly, annual, multi-year options
- Free trials - Trial periods and limitations
- Freemium offerings - Free tier capabilities and restrictions
Data Structure
Pricing data is linked to companies in our database. Here’s how the data is organized:Example Pricing Data
Use Cases
Competitive Analysis
Compare your pricing against competitors in your category
Market Research
Identify pricing trends and patterns across industries
Pricing Strategy
Inform your own pricing decisions with market data
Sales Intelligence
Understand prospect’s current tools and pricing
Pricing Models
The API categorizes companies by their primary pricing model:Per-User (Seat-Based)
Per-User (Seat-Based)
Pricing scales with the number of users or seatsExamples: Slack, Figma, NotionTypical structure: $X per user/month
Tiered (Feature-Based)
Tiered (Feature-Based)
Different feature sets at different price pointsExamples: Mailchimp, HubSpot, AirtableTypical structure: Starter, Professional, Enterprise tiers
Usage-Based
Usage-Based
Pay for what you use (API calls, storage, bandwidth)Examples: AWS, Stripe, TwilioTypical structure: $X per 1,000 API calls, requests, etc.
Flat-Rate
Flat-Rate
Single price for unlimited accessExamples: Basecamp, HeyTypical structure: $X/month unlimited
Freemium
Freemium
Free tier with paid upgradesExamples: GitHub, Calendly, LoomTypical structure: Free + paid tiers
Data Freshness
Pricing data is continuously updated through automated web scraping and manual verification.
- Update frequency: Weekly for most companies
- High-priority companies: Daily updates
- Change notifications: Available via webhooks (Enterprise plan)
- Historical data: Track pricing changes over time
Querying Pricing Data
Pricing intelligence is integrated into company data. Use these query patterns:Data Quality
We ensure high-quality pricing data through:1
Automated Collection
Web scrapers continuously monitor company pricing pages
2
Manual Verification
Human reviewers verify and enrich automated data
3
Change Detection
Algorithms detect and flag pricing changes
4
Community Feedback
API users can report inaccuracies
Limitations
- Enterprise pricing: Often not publicly disclosed (“Contact Sales”)
- Custom pricing: Volume discounts and negotiations aren’t reflected
- Regional pricing: Prices may vary by geography
- Currency: Primarily USD, with conversions for other currencies
- Promotional pricing: Temporary discounts may not be captured