Deriving Matching Strategies from User Search Heterogeneity: The Case of Meta-Platforms

Digital platform ecosystems act as unprecedented matchmakers in two-sided markets. Given continued criticism conceiving users merely by base size to increase network effects, which neglects their demand heterogeneities as a source of value creation and capture for platforms, we position user search preferences as key determinants of a platform’s matching strategy and investigate their impact on complement attention. We test our theory on matching depth for search specificity and matching breadth for search intention, analyzing a rich dataset on the fashion product category from a leading meta-platform. While we find empirical support for higher search specificity increasing complement attention and search intentions of users closest geared towards a purchase negatively impacting complement attention when paired with a broad or brand-led portfolio, we find no empirical support for a focused or product-led portfolio increasing complement attention for users closest geared towards a purchase. We contribute to platform research at the nexus of user heterogeneities, governance, and coopetition.