Statistical Model

Survival Analysis (Cox Proportional Hazards)

Understand how long outcomes take—not just whether they happen.

Survival Analysis answers a question that most funnels completely ignore: “When will this convert—or churn—if it happens at all?”

The Problem This Model Solves

Most marketing and growth analysis treats outcomes as binary: Converted vs not converted.

What gets ignored is Time, Probability over time, and Risk acceleration. This causes misjudged funnel efficiency, premature channel abandonment, and overconfidence in short-term performance.

Questions This Model Answers

"How long does conversion usually take?"

"When is churn risk highest?"

"Which channels accelerate or delay conversion?"

"Where does the funnel decay over time?"

"Are we confusing “slow” with “bad”?"

How the Model Thinks (Without the Math)

Survival Analysis treats outcomes as events that may happen later, or may never happen at all.

Instead of asking: “Did this user convert?”, it asks: “What is the probability this user converts by time T?”

Key ideas: Hazard rate (risk at a given moment) and Survival curve (probability of not concerning yet). Think of it as: “Funnels with a clock attached.”

Core Business Use Cases

1Time-to-Conversion Analysis

The Problem

Channels look weak because conversions are slow.

What It Reveals

Expected conversion timelines by channel.

Decision Enabled

Judge channels on patience, not impatience.

2Funnel Decay Diagnosis

The Problem

Drop-offs aren’t evenly distributed.

What It Reveals

Where abandonment risk spikes.

Decision Enabled

Fix the right stage, not the loudest one.

3Churn Risk Forecasting

The Problem

Churn is noticed after it happens.

What It Reveals

Rising hazard rates before churn.

Decision Enabled

Intervene before revenue disappears.

4Retention vs Acquisition ROI

The Problem

Retention feels cheaper but slower.

What It Reveals

Long-term payoff curves.

Decision Enabled

Balance fast acquisition with durable retention.

5B2B & High-Consideration Journeys

The Problem

Long sales cycles break attribution.

What It Reveals

Conversion probability over months.

Decision Enabled

Fund demand creation without waiting for deals.

Powered by SpendSignal

How We Use This Model

SpendSignal uses Survival Analysis to bring time intelligence into ROI.

Specifically:

  • Channel-level time-to-value curves
  • Churn hazard alerts
  • Funnel-stage prioritization
  • Inputs to Cash Velocity and Retention ROI modules

This stops teams from asking “Why hasn’t this converted yet?” and starts asking “Is this converting as expected?”

Example Output

Instead of “Conversion rate = 3%”, you see:

  • 20% convert within 7 days
  • 45% within 30 days
  • Hazard spike at day 14

The decision insight: "This channel is slow—but reliable."

Works Best When

  • Journeys span days to months
  • Churn matters more than clicks
  • Time is a critical cost

Be Cautious When

  • Outcomes are instantaneous
  • Data lacks timestamps
  • You need aggregate-only analysis

Frequently Asked Questions

Is this only for subscriptions?

No. Any delayed outcome benefits.

Does it require user-level tracking?

Ideally yes—but aggregated event cohorts can still work.

Is this predictive?

It’s probabilistic, not deterministic—which is safer.

Stop Guessing. Start Knowing.

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