Virtual Data Rooms as market institutions

VDRs function as intermediaries between multiple parties, providing a means for them to share sensitive data, without the costs associated with creating a physical (or digital) shared workspace for each side to exchange information. Thus, VDRs create value by providing a method for reducing the costs of searching, verifying, enforcing, and sharing data in the context of transactions.

The VDR market has several pricing models that vary considerably in terms of how they reflect the economic benefits created for transaction participants, and therefore, the way they create incentives for participants in the VDR market to maximise the allocative efficiency (i.e., optimal transaction size) and economic welfare (i.e., net price vs. user value) of their participation in the VDR market, and thus, for the market as a whole.

The five pricing models

There are five distinct models of VDR pricing that exist in the market today. Each model has a different set of allocative efficiency implications, buyer welfare implications, and market participation incentives.

Per-page pricing is the most traditional form of VDR pricing, as it is based on the physical data room model. In other words, a user pays for each piece of data that they send to their counterparty, based on the volume of data that is sent. There are many disadvantages to this pricing structure in the cloud environment. Given that the marginal cost of storing and securing additional pages approaches zero in the cloud environment, the relationship between the per-page price of a piece of data and the underlying cost of storing and securing that data is essentially non-existent. Instead, the per-page pricing structure continues to generate substantial revenue for VDR providers and imposes higher and more variable costs on their customers, particularly in instances of data-intensive transactions that create uncertainty for users about how many pages they will send. Thus, the per-page pricing model creates deadweight losses for users where participants are forced out of optimal behaviour related to document sharing, or where users are unable to afford to participate in these types of transactions.

Usage-based pricing uses storage consumption to measure how much the user is being billed for VDR services as opposed to the number of pages sent. This metric is more justifiable in the context of cloud economics; however, like per-page pricing, usage-based pricing continues to have a volume-sensitivity that becomes less and less relevant as a user builds out their VDR (i.e., they create more and more data to store in their VDR). Additionally, the shift away from pure usage-based models by the SaaS industry (e.g., over 40% of providers are now using hybrid models) indicates that the industry has recognised that the misalignment between the two creates significant reductions in customer value over time.

The per-user pricing model has completely separated revenue from volume of data and instead aligns revenue based on the number of access points to the VDR, which will be the same for lower-volume and higher-volume per-user usage scenarios. For organisations that are operating in lean environments and are using their VDR to manage large and complex sets of data, this is a more efficient pricing model; however, its efficiency starts to fail when transactions grow to include dozens or even hundreds of counterparties. In these cases, the per-user pricing model increases the cost of a transaction as it scales up in size, thereby discouraging optimal participation (i.e., users have been priced out of optimal behaviour). This scenario is an example of market failure due to a misalignment of the pricing structure and the intended purpose of VDRs.

Flat-rate pricing is designed to solve the scaling issues of both per-page and per-user pricing models. Flat-rate pricing resolves these scaling issues by giving users a flat rate for access to all data stored in the VDR, regardless of how much data they send or who they send it to. Flat-rate pricing, however, charges the same price to all users regardless of consumption; therefore, VDR providers cannot price-discriminate between users with dissimilar usage profiles. The resulting pricing structure is generally characterised by higher prices for lower-volume users and lower prices for higher-volume users, thereby resulting in underutilisation by lower-volume users and cross-subsidisation by higher-volume users. Thus, the trend away from flat-rate pricing by VDR providers is telling, as they are now using increasingly sophisticated tools to segment demand.

The tiered subscription pricing model addresses all of the above inefficiencies and has, as a result, become the expected dominant pricing model for virtual data room (VDR) services.

Tiered pricing and price discrimination

A tiered pricing model is a well-established example of second degree price discrimination whereby firms allow customers to self-select from various quality-differentiated product bundles rather than directly observing their willingness-to-pay. Although there are theoretically ambiguous implications for average total welfare, empirical data is distinctly positive — buyers who are priced out of VDR services under a flat-fee or per-page pricing model are now able to participate in the market via lower-tier pricing. Thus, providers are able to capture a larger proportion of total consumer surplus across a diverse group of customers and don't incur the administrative burden associated with first-degree price discrimination.

Evidence suggesting lower customer churn rates under tiered pricing models compared with flat-rate alternatives supports this conclusion: tiered pricing models improve the alignment of the consumption of a particular product with the value derived from consuming the product, thereby reducing the logical basis for customers to switch providers. The implication of this is not simply a commercial observation; it provides evidence that overall economic efficiency within the market has improved.

The role of asymmetric information

Buyer decision-making regarding pricing is constrained by extreme asymmetric information. Providers possess extensive knowledge as to how the pricing structures behave under various usage conditions, while the vast majority of buyers lack sufficient transactional history to assist them in forecasting how costs will change over contracts. This asymmetric information is not incidental; per-page pricing structures and usage-based pricing structures both intentionally take advantage of the information asymmetry and derive revenue from costs that buyers are unable to predict at the time of contracting.

The gradual convergence of the market onto tiered subscriptions can also be viewed as a signalling equilibrium: tiered, clear pricing structures reduce adverse selection to the extent that buyers can make credible, pre-purchase estimates of their total costs. Providers who offer tiered pricing provide credible confirmation that their pricing structure does not rely on buyer miscalculation; a reputation-based system which supports long-term stability in the market.

Structural Implications

Within the traditional four transaction types (vendor due diligence, post-merger integration, capital raise transactions, and major restructurings), the use of tiered subscription pricing consistently achieves the highest level of predictability for cost, efficiency of access and scalability. The continued use of per-page and usage-based pricing in certain segments of the market is better explained by buyer inertia and the advantages that longer-established providers hold over less experienced buyers. As buyers become more sophisticated and comparative data on pricing becomes more readily available, it is expected that the continued convergence of the market to tiered subscription pricing will be the overall equilibrium outcome.