====== Why refunds should be attributed to traffic source ====== ===== The attribution blind spot ===== Most marketers attribute sales to traffic sources. Few attribute refunds the same way. Sales are celebrated. Refunds are absorbed. This imbalance distorts decision-making. CBSplit was built to connect refunds back to their origin. ===== Sales attribution without refund attribution is incomplete ===== Traffic sources are typically evaluated by: * Conversion rate * EPC * Cost per acquisition * Initial ROAS Refunds are often tracked separately, at the offer or account level. Without linking refunds to traffic, profitability appears inflated. CBSplit ties refunds to the same segmentation used for sales. ===== Not all traffic produces equal customer quality ===== Different traffic sources generate different buyer behavior. Some sources produce: * High-intent customers * Clear expectation alignment * Stable subscription behavior Others produce: * Impulse buyers * Misaligned expectations * Higher refund likelihood Without refund attribution, these differences remain hidden. ===== Refund clusters reveal traffic intent problems ===== Refund spikes often cluster around: * Specific ad angles * Certain geographies * Particular traffic networks * Aggressive messaging styles If refunds are not attributed, these clusters are invisible. CBSplit isolates refund behavior by source and segment. ===== Refund-adjusted ROAS changes scaling decisions ===== A traffic source may look profitable on gross revenue. After refund attribution, it may show: * Thin margins * Negative net ROAS * Increased processor risk * Lower lifetime value Scaling based on gross performance leads to silent erosion. CBSplit recalculates profitability using refund-adjusted revenue. ===== Refund attribution protects processor health ===== Processor thresholds depend on: * Refund ratios * Chargeback frequency * Traffic quality stability If one source drives disproportionate refunds, risk accumulates. Attributing refunds to traffic allows: * Controlled scaling * Targeted optimization * Risk containment CBSplit integrates refund signals into traffic evaluation. ===== Blended reporting hides refund impact ===== Aggregated dashboards smooth over: * Source-level variance * Cohort-based dissatisfaction * Timing differences * Refund clustering patterns Blended metrics protect weak sources from scrutiny. CBSplit preserves segmentation to expose weak links. ===== Profitability depends on net revenue, not gross sales ===== True performance measurement requires: * Sales attribution * Refund attribution * Rebill tracking * Cohort-based LTV Traffic evaluation without refund attribution is structurally incomplete. CBSplit completes the attribution loop.