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====== Why front-end winners often fail at scale ======

===== The early victory illusion =====

Front-end tests often produce clear winners.

Higher conversion rate.
Better EPC.
Lower CPA.

Traffic is shifted.
Budgets increase.
Confidence rises.

Then performance degrades.

CBSplit was built to explain why front-end winners frequently collapse at scale.

===== Front-end wins are measured under limited pressure =====

Early tests operate under:

  
  * Controlled traffic volume
  * Narrow targeting
  * Stable ad costs
  * Limited cohort exposure

At scale, conditions change:

  
  * Traffic expands into colder audiences
  * Acquisition costs fluctuate
  * Platform algorithms shift
  * Payment systems face higher load

Front-end metrics do not account for this stress.

===== Aggressive tactics scale poorly =====

Front-end winners often rely on:

  
  * Urgency-heavy copy
  * Scarcity framing
  * Emotional triggers
  * High-pressure upsells

These tactics convert well in small samples.

At scale, they can increase:

  
  * Refund rates
  * Customer dissatisfaction
  * Support burden
  * Processor scrutiny

CBSplit evaluates durability before declaring a scalable winner.

===== Refund patterns magnify with volume =====

A small refund percentage may seem manageable at low volume.

When scaled:

  
  * Refund counts grow rapidly
  * Refund ratios become visible
  * Chargeback exposure increases
  * Net revenue shrinks

Front-end tests rarely run long enough to see this compounding effect.

CBSplit tracks refund-adjusted performance.

===== Rebill behavior changes at scale =====

Subscription funnels often:

  
  * Attract high-intent users early
  * Expand into broader audiences when scaled

Broader audiences may show:

  
  * Higher churn
  * Lower rebill survival
  * Shorter customer lifecycles

Front-end winners that ignore rebill durability fail under expansion.

CBSplit measures cohort stability before scaling.

===== Traffic quality shifts with expansion =====

Scaling often requires:

  
  * New geographies
  * Additional traffic sources
  * Broader targeting
  * Creative variation

Front-end performance under narrow targeting does not guarantee stability under diverse traffic.

CBSplit segments performance by traffic source and cohort.

===== Operational stress reveals hidden fragility =====

At higher volume:

  
  * Payment systems face more retries
  * Customer support load increases
  * Refund processing accelerates
  * Platform scrutiny intensifies

Front-end winners rarely account for operational resilience.

CBSplit incorporates operational stability into evaluation.

===== Scaling magnifies small weaknesses =====

Minor structural issues at low volume become major risks at high volume.

Examples include:

  
  * Slight billing confusion
  * Subtle expectation mismatch
  * Small refund clusters
  * Retry-dependent approvals

These weaknesses compound under scale.

CBSplit identifies structural fragility early.