Using Information Networks to Discover and Execute Marketing Brand Alliances: A Data-Driven Framework for Actionable Insights

Marketing brand alliances are consumer-facing collaborations in which brands are jointly presented through shared offerings or campaigns. Despite their widespread use, the systematic discovery and evaluation of such opportunities remains challenging because managers must screen vast combinatoric candidates to identify the few truly promising alliance opportunities. This study proposes brand alliance network exploitation (BANE), a sociotechnical framework that leverages information networks derived from digital user traces for market-wide, ex ante alliance opportunity discovery with execution guidance. BANE integrates off-line brand attributes, online consumer comention signals, and network embeddings to predict alliance opportunities; validates predictions through consumer and brand manager surveys; qualifies positive, nonmaterialized opportunities through the BANE matrix; and generates marketing mix execution guidance. Temporal holdout testing demonstrates that BANE predicts future alliances from preannouncement signals, and stakeholder surveys show that BANE-identified opportunities are perceived as significantly more promising than controls. For brand managers, BANE offers a scalable, data-driven alternative to survey-based alliance search for partner selection, portfolio-level collaboration strategy, and campaign execution. For investors, agencies, and consultancies, BANE provides systematic and timely signals of emerging alliances and evolving brand connections across industries.