The Last-Click Lie
Last-click attribution is the default in most analytics setups. It assigns 100% of conversion credit to the final touchpoint before purchase. This model is simple, easy to implement, and completely misleading. It ignores every touchpoint that built awareness, generated interest, and created trust. It credits the last step in a journey and pretends the previous steps did not matter.
What Last-Click Gets Wrong
Consider a customer journey: they discover a product through a creator's content (awareness), visit the brand website from a search ad (consideration), read reviews on a comparison site (trust building), and finally click a retargeting ad to purchase (conversion). Last-click credits the retargeting ad with 100% of the conversion value. The creator, the search ad, and the review site receive zero credit. Budget allocation follows attribution: the retargeting budget grows, the creator budget shrinks, and the very touchpoints that created the conversion opportunity are defunded.
Multi-Factor Attribution
Sentient OS replaces last-click with multi-factor attribution - a causal model that quantifies the exact contribution of each conversion driver. Price Sensitivity contributes +20% conversion lift. Engagement Quality adds +8%. Match Quality contributes +15%. These are not estimated shares distributed across touchpoints - they are causal weights validated against archetype-level outcome data. The Conversion Modeling module surfaces these factors so teams can allocate budget to the levers that actually drive conversion.
Archetype-Level Attribution
Multi-factor attribution operates at the archetype level, not the aggregate level. "Skeptical Innovators" convert primarily on peer validation and detailed specifications - not on retargeting. "Impulsive Aesthetes" convert on visual quality and initial exposure - not on extended consideration journeys. By understanding attribution per archetype, marketing teams can design channel strategies that match behavioral reality rather than applying a one-size-fits-all attribution model.
Budget Reallocation Based on Causation
When attribution shifts from last-click to multi-factor, budget allocation changes dramatically. Touchpoints that build trust and consideration (content, reviews, peer validation) receive appropriate credit. Touchpoints that merely capture existing intent (retargeting, branded search) are right-sized. The result is a budget that invests in creating demand rather than just harvesting it. Performance Forecasting projects the impact of these reallocation decisions, and Conversion Modeling validates them against actual outcomes.
The Integrity Dimension
Multi-factor attribution must also account for data quality. If engagement metrics are inflated by bot activity, attribution models that include those metrics will misallocate credit. The Integrity Layer filters inorganic signals before they enter the attribution model, ensuring that causal weights reflect genuine human behavior. Without integrity filtering, multi-factor attribution would be more sophisticated than last-click but equally wrong.