Customer Lifetime Value – Segflow Documentation

What is the CLV Analysis?

Customer Lifetime Value Analysis is in development and coming soon

The Customer Lifetime Value (CLV) Analysis estimates the total economic value a customer or cohort will generate over time. Inside a Board, CLV is computed from the connections you’ve made between acquisition sources, cohorts, usage/retention metrics, and revenue metrics, so the results reflect your real system, not a generic spreadsheet.

This analysis helps you decide how much to invest to acquire and retain different segments, which channels deserve more budget, and which early behaviors predict high value.

What You Need to Get Started

Outcome metric for value – A revenue or value metric (e.g., MRR, ARPU, Net Revenue) connected on your Board
Cohorts or segments – Cohort definitions (e.g., signup month, channel, plan) linked to your metrics
Retention/engagement signals – Metrics that represent ongoing usage or churn risk
Historical data (preferably 6–12+ months) – Enough time to observe repeat value and decay

The analysis runs within your Board and uses your connections (e.g., Channel → Cohort → Usage → Revenue) as the causal scaffold.

What You’ll Get Back

Predicted LTV by cohort/segment – Forward-looking value with confidence ranges
Payback and LTV:CAC – Time-to-recover acquisition cost and value-to-cost ratios by channel/segment
Early predictor insights – Leading behaviors that correlate with high LTV (e.g., activation milestones)
Retention-adjusted scenarios – “What if retention improves by X%?” and the resulting LTV lift
Prioritisation guidance – Which segments to acquire, retain, or upsell first

How the Analysis Works

Step 1: Define Value & Cohorts in Your Board

Choose your value metric and connect cohorts/segments and channels to it. These Board connections become the analytical backbone.

Step 2: Establish Baselines

Compute historical revenue per customer over time and retention curves for each cohort/segment to form a business-as-usual baseline.

Step 3: Estimate Lifetime Value

Project future value by combining retention survival (likelihood a customer remains active) with expected monetisation (ARPU/expansion). Results are produced per cohort/segment with confidence ranges.

Step 4: Quantify Payback & LTV:CAC

Where CAC is connected on the Board (e.g., via Marketing Mix), calculate payback period and LTV:CAC by channel/segment.

Step 5: Surface Early Predictors

Identify early behaviors (activation milestones, usage frequency) that correlate with high LTV to guide onboarding and lifecycle interventions.

Step 6: Scenario & Sensitivity

Run “what-if” scenarios (improve D30 retention, increase expansion rate) and see the projected LTV impact.

How to Interpret the Results

CLV Analysis provides a directional, risk-aware estimate of value:

Better cohort/revenue data → stronger estimates
Stable retention patterns → more reliable projections
Clear Board connections → more actionable insights

Keep in mind:

Not all value is perfectly attributable; confidence ranges reflect uncertainty
Segment LTV can shift with pricing, product, or macro changes
Use CLV as an investment compass, not a deterministic forecast

When to Use the CLV Analysis

Ideal for:

Acquisition budgeting – Decide maximum CAC by channel/segment
Retention & lifecycle strategy – Focus on cohorts with the biggest LTV lift from small retention gains
Pricing & packaging – Understand which plans/segments sustain higher lifetime value
Revenue planning – Build forecasts grounded in retention-adjusted value

Less suitable for:

Very sparse revenue histories or rapidly changing business models
Situations requiring exact, auditable per-user accounting (use finance systems)

Getting the Best Results

Connect the Right Nodes in Your Board

Link channels → cohorts → usage/retention → revenue
Include CAC where possible for LTV:CAC and payback

Start with Clean, Sufficient History

Aim for 6–12+ months of data per key segment
Validate revenue metric definitions and seasonality

Validate and Iterate

Compare projected vs. realised value each cycle
Re-segment if outliers dominate a cohort
Use scenario tests to guide experiments (e.g., onboarding improvements)

Summary

The CLV Analysis turns your Board’s connected data into a value lens: who to acquire, how much to invest, where retention pays off, and which early behaviors predict long-term return. Use it to make confident, segment-aware investment decisions that balance growth with durability.