Optimal marketing strategy for information products in the presence of network effects: fixed price, seeding, or advance selling?

Abstract This paper investigates a software developer’s optimal marketing strategy in the presence of network effects. We develop a two-period game-theoretic model to compare three common approaches: fixed pricing, uniform seeding, and advance selling. Our central finding reveals a tension between leveraging network effects and avoiding revenue cannibalization. Specifically, a simple fixed pricing strategy is optimal when network effects are weak. As this effect strengthens, strategies that build an early user base, such as seeding (offering free copies) or advance selling (offering pre-launch discounts), become superior. We further show that from the firm’s perspective, advance selling generally dominates seeding, as it more effectively cultivates and capitalizes on the network effect. This corporate preference, however, creates a welfare trade-off: seeding delivers the highest consumer surplus, while advance selling maximizes total social welfare. These findings are robust to the inclusion of consumer valuation uncertainty and strategic behavior.