Pricing · Analytical model of software pricing and consumer learning
Economics of Free Under Perpetual Licensing: Implications for the Software Industry
Information Systems Research · 2014
Summary
The preferred strategy depends on customer beliefs about functionality, cross-module synergies, word-of-mouth effects, and the number of periods.
For your marketing
Possible founder application
A software-specific framework for distinguishing free trials, free plans, and seeding. Use it to clarify the mechanism you expect before designing an experiment, not as a universal recommendation.
Reported result
What the study found
The preferred strategy depends on customer beliefs about functionality, cross-module synergies, word-of-mouth effects, and the number of periods. Free seeding can be optimal when users underestimate functionality and synergies are weak; stronger word of mouth can expand the region where seeding is optimal.
Research question
What the authors investigated
When should software firms use free seeding or feature-limited freemium under perpetual licensing?
Design
Two-period analytical consumer-valuation learning model comparing feature-limited freemium, uniform seeding, and charge-for-everything strategies.
Sample and setting
Theory paper focused on software business models; no empirical sample.
Scope and transfer
Limitations to keep in view
Results are conditional on assumptions of the two-period model and perpetual-license context; they do not establish how subscriptions or modern SaaS freemium perform empirically.
Research sources
INFORMS publisher abstract and author-hosted PDF retrieved with Firecrawl; profile identifies theoretical results rather than empirical evidence.