Website: https://causalmma.com API Base URL: https://api.causalmma.com
Professional-grade marketing attribution powered by causal inference. Go beyond correlation—prove which channels actually cause conversions.
Scientific marketing attribution that reveals true cause-and-effect relationships in customer journeys using 8 verified causal inference methods from economics and medicine. 60-75% more affordable than competitors like Windsor.ai, Northbeam, and Rockerbox.
- 🔬 8 Scientific Causal Inference Methods: Doubly Robust Estimation, Propensity Score Matching, Instrumental Variables, Shapley Values, PC Algorithm, and more
- 📊 7 Attribution Models: Data-driven (AI-powered), Shapley, Propensity Score, Instrumental Variables, Time Decay, Position-based, Linear
- ⚡ Fast Processing: 4-32ms average response time for real-time optimization
- 🤖 AI Agent Integration: Works with OpenAI GPT-4, Anthropic Claude, LangChain
- 💰 Transparent Pricing: Starting at $149/month (60-75% cheaper than competitors)
- 🔒 Local SDK Available: 100% local processing for maximum data privacy and offline use
- Best for: Most users who want zero infrastructure costs
- Pricing: $149-$799/month
- Setup: Instant—just get an API key
- Documentation: API Docs | Quick Start | Code Examples
- Best for: Organizations with existing AI infrastructure, strict data privacy requirements, or massive datasets (10M+ rows)
- Pricing: Custom (typically $1,500-$8,000/month depending on deployment)
- Benefits: 100% local processing, no data leaves your servers, 15-30x faster for large datasets, offline/air-gapped deployment
- Documentation: SDK Docs
curl -X POST https://api.causalmma.com/api/v1/attribution \
-H "X-API-Key: YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"touchpoints": [
{
"customer_id": "c1",
"timestamp": "2025-01-01T10:00:00",
"channel": "email",
"conversion": 0
},
{
"customer_id": "c1",
"timestamp": "2025-01-01T12:00:00",
"channel": "paid_search",
"conversion": 1,
"conversion_value": 100
}
],
"attribution_model": "data_driven"
}'pip install causalmma-clientfrom causalmma_client import LocalEngine
import pandas as pd
engine = LocalEngine(
api_key="ca_live_YOUR_API_KEY",
control_plane_url="https://ops.causalmma.com"
)
df = pd.DataFrame([
{"customer_id": "c1", "timestamp": "2025-01-01T10:00:00", "channel": "email", "conversion": 0, "ad_exposure": 1},
{"customer_id": "c1", "timestamp": "2025-01-01T12:00:00", "channel": "paid_search", "conversion": 1, "conversion_value": 100, "ad_exposure": 1}
])
result = engine.analyze(df=df, model="data_driven", treatment="ad_exposure", outcome="conversion")
print(result)- 📘 API Reference - Complete API documentation
- 🔧 SDK Documentation - Local SDK installation and usage
- 🚀 Quick Start Guide - Get started in 5 minutes
- 💻 Code Examples - Examples in Python, JavaScript, PHP, Ruby, R
- 💰 Pricing - Simple, transparent pricing
| Model | Description | Best For |
|---|---|---|
data_driven |
AI-powered causal inference with doubly robust estimation | Most accurate results |
shapley |
Game-theoretic fair credit distribution | Provably fair attribution |
propensity_score |
Propensity score matching | Comparing similar customers |
instrumental_variables |
Two-stage least squares | Handling unmeasured confounding |
time_decay |
Recency-weighted attribution | Recent touchpoints matter more |
position |
First & last touch emphasized | Awareness + conversion focus |
linear |
Equal credit to all touchpoints | Baseline comparison |
- Email: cm-contact@infinidatum.net
- Website: https://causalmma.com
- API Base: https://api.causalmma.com
- GitHub: https://github.com/rdmurugan/causallm
- Starter: $149/month - 10K API requests, 100 req/min
- Professional: $399/month - 50K API requests, 500 req/min (Most Popular)
- Business: $799/month - 100K API requests, 1000 req/min
- Enterprise: Custom - Unlimited requests, Local SDK option, Custom SLAs
All plans include:
- 14-day free trial (no credit card required)
- All attribution models
- Statistical confidence intervals
- Complete documentation
- Email support
- ✅ True Causation, Not Correlation: 8 verified causal inference methods vs. correlation-based tracking
- ✅ Statistical Certainty: Every result includes p-values, confidence intervals, and standard errors
- ✅ Fast & Production-Ready: 4-32ms response time for real-time optimization
- ✅ Academically Grounded: Methods from peer-reviewed economics and medical research
- ✅ 60-75% More Affordable: $149-$799/month vs. $20K-$100K+/year for competitors
- ✅ Developer-Friendly: Simple REST API, integrates in under 10 minutes