Pricing Strategy and Innovation Incentives for Security Software: Theory and Evidence

We develop an analytical model that presents optimal pricing strategies for a multi-product software firm selling consumer security software. Our model highlights two aspects unique to this kind of software. The first is a supply-side effect that alters its cost structure due to the nonnegligible costs of providing security updates and patches to minimize vulnerabilities and prevent security breaches. The second is a demand-side pooling effect which accrues from the fact that customers often get free substitutes for components of security software suites. In contrast with prior results on information goods, our model predicts the optimality of mixed bundling as a pricing strategy for security software vendors. The absence of these two effects leads to the optimality of pure bundling, which is consistent with past work. Another central finding of our model is that, contrary to what is commonly believed about information goods industries, the unique economics of security software actually lead to a positive relationship between bundling and innovation: the use of mixed bundling can increase a firm’s incentives to develop more secure software. Our analytical model leads to many empirical predictions about the magnitude of marginal costs, the percentage discount on bundles relative to component prices and the relative demand of the bundle with respect to the demand for components. We test these propositions using a unique dataset on security software demand and pricing that we have collected from Amazon.com and find strong support for our theoretical results. Finally, we also contribute by developing and using a novel methodology based on inferring price-cost marks ups and demand elasticities, and we use it to empirically establish the optimality of mixed bundling by firms engaging in consumer security software.