SIGNAL

by DATACRAFT

Discover What Really Drives Your Results

Uncover hidden causal relationships in your time series data.
Know exactly which activities today predict outcomes tomorrow.

Causal Relationship Discovery

Signal analyzes your time series data to calculate R-values between activities—revealing which past actions have the strongest correlation to future outcomes.

Lag Analysis

Discover optimal timing: Does ad spend drive conversions in 3 days? 7 days? We calculate the exact lag time.

R-Value Strength

Measure correlation strength from -1 to +1. Know which activities have the most predictive power.

Leading Indicators

Identify metrics that predict future performance, giving you early warning and optimization opportunities.

Correlation Matrix

Visualize R-values between all your metrics. See which activities correlate with outcomes at a glance.

Example: Email clicks → Leads (R = 0.96)

Time-Delayed Effects

Calculate optimal lag times between cause and effect across 0-30 day windows.

Example: Ad spend → Conversions (5-day lag)

Predictive Signals

Discover which activities serve as reliable early indicators of future performance.

Example: Social shares predict traffic 2 days ahead

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How Signal's R-Value Analysis Works

We compute Pearson correlation coefficients (R-values) between your time series to reveal cause-and-effect relationships.

Upload Time Series Data

Provide CSV files with timestamps and metrics (e.g., ad spend, social engagement, conversions, revenue). Signal automatically parses and caches data in high-performance Parquet format.

Calculate R-Values

We compute correlations between all metric pairs, testing lags from 0-30 days. Discover that today's activity X has an R-value of 0.85 with tomorrow's outcome Y.

Identify Optimal Lags

For each relationship, we find the time delay that maximizes R-value strength. Example: "Paid media spend on Monday → Peak conversions on Friday (4-day optimal lag, R = 0.72)"

Visualize & Act

Interactive heatmaps, lag plots, and leading indicator dashboards make insights actionable. Know exactly which activities to amplify and when to expect results.

Real-World Example

Marketing Campaign Analysis: Upload 90 days of paid media, social metrics, and conversion data.

  • Discovered: Social shares have R = 0.68 with web traffic (2-day lead time)
  • Discovered: Ad clicks correlate with conversions at R = 0.78 (5-day optimal lag)
  • Action: Plan conversion tracking 5 days after ad campaigns; use social metrics as early warning

All correlations include p-values to ensure statistical significance. Only actionable relationships are highlighted.

Why Signal's Approach Is Different

  • Causal, not just correlative: Lagged analysis reveals what causes what
  • Automated lag optimization: Finds exact timing between activities and outcomes
  • Statistical rigor: P-values ensure relationships aren't random
  • Leading indicators: Predict future performance before it happens
  • Intelligent caching: Parquet format means 10-100x faster analysis
  • Multi-source merging: Combine datasets across channels automatically
  • Visual clarity: SVG graphs cached for instant insights
  • Marketing-optimized: Built for multi-channel attribution and ROI

Try Signal with Real Data

Log in with a test account to explore pre-loaded marketing campaigns with discovered R-value relationships.

Username: sarah_analytics
Username: mike_campaigns
Username: jessica_strategy

Password for all test accounts: signal2025

Signal by Datacraft — Where X activity meets Y outcome

Discover the R-values that drive your business