SEO Dimensions and AI-Assisted Predictive Scoring for Digital Business Sales Performance in Indonesia - Muchtadin Muchtadin; Michael Surya Gunawan; Dwi Safarina; Kamal Arif Al-Farouqi (Pandawan Sejahtera Indonesia, 2026)
The intensification of digital commerce competition has elevated Search Engine Optimization (SEO) into a strategically important yet empirically underexplored determinant of sales performance, particularly within Indonesia’s rapidly expanding e-commerce ecosystem, where organic search drives over 64% of commercial platform traffic. This study examines the influence of three core SEO dimensions on page optimization, off-page optimization, and technical SEO on digital business sales performance, measured through website traffic growth, customer conversion rates, and revenue improvement. A quantitative explanatory design was applied using primary data from structured question naires administered to 120 digital business owners and e-commerce managers in Indonesia, cross-validated with secondary Google Analytics records over a twelve-month observation window. Multiple linear regression was conducted after validity, reliability, normality, multicollinearity, and heteroscedasticity tests. An AI-assisted Predictive SEO Performance Scoring (PSPS) model was also developed as a weighted composite function based on standardized regression coefficients to simulate performance trajectories across three SEO deployment scenarios. All three SEO dimensions showed statistically significant positive effects on sales performance (p < 0.05), with on-page SEO recording the strongest coefficient (β = 0.342), followed by technical SEO (β = 0.318) and off-page SEO (β = 0.291). The model explained 68% of performance variance (R2 = 0.68). PSPS scenario analysis showed that comprehensive SEO adoption produced an 83.5% relative performance improvement over minimal deployment. These findings position SEO as a core strategic investment aligned with Indonesia’s Making Indonesia 4.0 agenda and SDGs 8, 9, and 10.