foco
← All Tools
Ra
Marketing AnalyticsAttribution Modeling

Rabbit

Multi-touch attribution that shows which marketing channels actually drive conversions.

A full-stack attribution platform with a React dashboard and FastAPI backend. Upload touchpoint data, run five attribution models, and get confidence-scored results with business insights.

Status

Active

Built With

ReactTypeScriptFastAPIPythonpandasscikit-learnMaterial UIRechartsDocker

Source

GitHub →

What it does

Features

01

5 Attribution Models

Linear, Time Decay, First Touch, Last Touch, and Position-Based models to compare how credit is distributed across channels.

02

Adaptive Identity Resolution

Automatically selects the best method (customer ID, session+email, email-only, or aggregate) to link touchpoints across devices.

03

Confidence Scoring

Statistical confidence for every result, including data quality metrics, model fit, and channel-level scores.

04

Journey Analysis & Insights

Reconstructs customer journeys, identifies top conversion paths, and generates actionable business recommendations.

Who is this for?

Rabbit is built for marketing data analysts, marketing technology managers, and agency teams who need to understand which channels actually contribute to conversions — not just which ones touched the customer last.

If you've ever argued over whether paid search or email deserves credit for a conversion, and wished you had data to back it up, this platform gives you five different models to compare.

The Problem

Most teams have no clear picture of how their marketing channels work together:

  • Last-click attribution is the default — most analytics tools give all credit to the final touchpoint, ignoring everything that came before it.
  • Touchpoint data is fragmented — customer interactions are spread across platforms with no unified view of the journey.
  • No confidence metrics — even when attribution numbers exist, there's no way to know how reliable they are.
  • Limited model options — teams are stuck with one model and can't compare how different approaches change the story.

How It Works

Upload your touchpoint data, pick a model, and get results in three steps:

  1. Upload data — import touchpoint data as CSV, JSON, or Parquet files with customer IDs, timestamps, channels, and conversion flags
  2. Select an attribution model — choose from Linear, Time Decay, First Touch, Last Touch, or Position-Based attribution
  3. Get results — view confidence-scored attribution results with data quality metrics, channel breakdowns, and actionable business insights

Use Cases

Campaign Performance Analysis

Run multiple attribution models side by side to see how credit shifts between channels. Identify which channels consistently contribute to conversions regardless of the model used.

Budget Reallocation

Use attribution results to find over- and under-invested channels. Shift budget toward channels with high attributed conversions and strong confidence scores.

Cross-Channel Attribution

Map the full customer journey across paid, organic, email, and direct channels. See how channels interact and which combinations drive the highest conversion rates.

Long-Cycle B2B Attribution

Handle extended sales cycles where conversions happen weeks or months after first contact. Adaptive identity resolution links touchpoints across sessions and devices to reconstruct the full journey.

Get started with Rabbit

Check out the source code, try it yourself, or reach out if you want this kind of tooling built for your measurement stack.