3 roads to driving more revenue out of your digital device

April 12, 2018 Shawn Oreschnick, Logic PD

In the new OEM economy, information is king. We’ve written previously about how OEMs can maximize their natural advantage as device creator by carefully exploring, testing, and exploiting information opportunities created by their digital device’s data – but OEMs can only take full advantage of these opportunities if they select the go-to-market strategy for their smart device that meets their customers’ needs. 

The three main monetization strategies we’ll discuss here are the pay-up-front, pay-as-you-go, and pay-for-information business models. Exploring the pros and cons of these strategies will help clarify which would work best for your company, depending on the relationships between your company and its clients/customers, and how much your company knows about how end users use your smart device.

1. The pay-up-front model

In this least complicated model, the primary vehicle of value creation is the device itself. The OEM’s customers pay one price (or an annual fee) into which the OEM must price the embedded value of ongoing service costs—which may include access to data generated by the device. The big benefit to OEMs here is that they receive the revenue up-front in one large sum, regardless of actual usage of the device or amount of services requested by customers.

Of course, the biggest worry for OEMs who choose this approach is that customers will request a disproportionately high level of services relative to the revenue they provide the OEM. Variable costs related to providing services can easily exceed initial estimates if the price clients pay is set too low. Too many “high-maintenance” customers can make the task of getting enough product into the market to reach critical mass—the point at which there is enough data that info buyers would find useful, thus creating the desired info-level revenue stream–a difficult one.

OEMs can mitigate this threat and constrain service costs by including an option for “surge fees” as needed within the contracts they enter into with customers. This is similar to how cellular companies often charge customers for exceeding their individual allotment of data in a given period.

This option makes the most sense for OEMs that sell into a supply chain or through a multi-step distribution model and lack easy access to end customers via their current distribution methods. The pay-up-front model represents the simplest, most straightforward monetization method for OEMs to get their device in the hands of end consumers and ultimately gain a better understanding of how they use it.

2. The pay-as-you-go model

Under this model, revenues are earned primarily through the ongoing services provided to the client, usually through a periodic subscription. Access to databases of device-generated information would certainly fit within the category of services an OEM could choose to price into their subscription model.

Pay-as-you-go uses the opposite approach from the pay-up-front model; here, the initial product cost is embedded into the monthly service fee. Some OEMs prefer this model because it creates an ongoing revenue stream that is more reliable and an easier "sell" than the one-time payment or annual fee from the pay-up-front model. Research has shown that pay-as-you-go customers are less likely to opt out of their plan at the end of the year than those who sign up via the pay-up-front approach.

OEMs that rely on this model ideally want their clients to use a “mild-to-moderate” amount of service per period. Those that fall too far on either end of the usage continuum pose risks—those who use too little of the service may not find it valuable and those who use too much may strain customer service resources. OEMs can combat these problems by utilizing AI to help detect underutilization and intervene early to help customers feel like they receive sufficient bang for their buck. OEMs can use the same techniques to reduce customer service expenses.

This model is attractive for OEMs that are accustomed to selling service packages and warranties. Companies with experience in providing aftermarket services may already possess the blueprint to make the necessary additions to their customer service and IT infrastructures. This could allow them to offer other potential revenue-generating services—like access to device information databases—to their customers. Once the bones of the system are in place, OEMs can then strategize how to build even more robust, sticky, and data-centric annuity revenue streams.

3. The pay-for-information model

In this model, revenue is generated directly from the sale of data rather than the purchase of a device or subscription fees. OEMs use this approach when they give away the device and the ongoing service, but charge for access to the data generated by the device. Because of the near-infinite number of data access plans and packages an OEM can generate, this model allows them to create geometrically larger value completely disconnected from the costs to create it.

The primary drawback to this approach is the burden the OEM must bear in proving out the value of the information to potential customers before these customers are willing to pay for it. Customers cannot see the value of the information before they actually get it, at times forcing OEMs to “give it away” initially, potentially creating a delay to any earnings.

OEMs can overcome this dilemma by bundling their device with the sale of coordinating products or accessories. The OEM may not specifically charge the customer for their device, but they can recover some margin in the overall sale prior to any information purchases.

This model likely appeals to OEMs with an add-on IoT product that represents a low percentage of the overall bill of materials for the customer solution. It helps if the OEM is established enough to afford giving the device away. If the OEM is willing to give the pay-for-information model enough leash to get up and running and prove its worth to a healthy base of customers, they will have created a new, constantly refreshing revenue stream at nearly 100% margin.

What about combining models?

OEMs can combine these strategies and offset risks, but consideration must be given to the customer’s point of view. Are customers’ risks being mitigated, or just the OEM’s? Most buyers tend to dislike complexity. OEMs should choose a model and stick with it until your company’s product lines or information sophistication evolve in a way that necessitates a move to a different model.

Shawn Oreschnick is Director of Analytics and Research Services at Logic PD

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