====== Why refunds lag behind campaign decisions ======

===== The timing mismatch =====

Campaign decisions are made quickly.

Budgets are increased.
Traffic is scaled.
Offers are duplicated.
Variants are declared winners.

Refunds move slowly.

This mismatch creates distorted decision-making.

CBSplit was built to correct this imbalance.

===== Campaign metrics are immediate =====

Most campaign dashboards show:

  
  * Clicks
  * Conversions
  * Revenue
  * ROAS

These update in near real time.

They create urgency.
They encourage fast action.

Refund data does not move at the same speed.

===== Refunds arrive after experience, not purchase =====

Refunds are triggered by:

  
  * Product dissatisfaction
  * Billing confusion
  * Fulfillment issues
  * Post-purchase regret

These signals require time.

Refunds often appear:

  
  * Days later
  * After support contact
  * After subscription rebill
  * After reflection

By then, campaign decisions have already been made.

===== Scaling amplifies delayed risk =====

When early metrics look strong, teams:

  
  * Increase ad spend
  * Open new traffic sources
  * Expand to new geographies
  * Duplicate funnel structures

If refund behavior is unhealthy, scaling multiplies exposure.

Refund signals lag behind this expansion.

CBSplit measures refund-adjusted revenue, not just gross performance.

===== Refund clusters distort later performance =====

Refunds often cluster around:

  
  * Specific traffic segments
  * Certain messaging angles
  * Aggressive upsell flows
  * Retry-heavy payment paths

These clusters may not be visible during early scaling.

CBSplit isolates refund behavior by segment before scale accelerates it.

===== Decision velocity exceeds outcome velocity =====

Modern marketing operates at high speed.

Outcome signals move at natural speed.

The faster decisions move, the wider the gap becomes.

CBSplit slows evaluation just enough to preserve accuracy.

===== Lag hides true profitability =====

A campaign may look profitable today.

After refunds settle:

  
  * Net revenue declines
  * Processor risk increases
  * LTV projections shrink
  * Scaling thresholds shift

Campaign momentum masks this erosion.

CBSplit recalculates performance after refund resolution.

===== Refund lag creates false confidence =====

When refund signals are delayed:

  
  * Early wins feel validated
  * Teams overcommit resources
  * Risk accumulates silently

By the time refunds are visible, damage has already spread.

CBSplit integrates refund timelines into performance evaluation.