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Use casesData for subscriptions podcast - Episode #6
Subscriptions and Usage Monetization
Guest
Olivier Bussenot
Head of BD at DigitalRoute
Guest
Olivier Bussenot
Head of BD at DigitalRoute
Episode description
Rather than selling products outright, manufacturers are moving to servitization and outcome-based billing models. To support this transformation, businesses need granular visibility of how both physical products and digital services are performing and being used by the customer.
In this episode, our host Behdad Banian is joined by Olivier Bussenot, Business Development Director at DigitalRoute, to discuss what goes into getting the data right for outcome-based billing models.
Highlights
Today, companies monetize data in more ways than you can imagine. That’s not only what you have on your phone, or what you’re watching on Netflix. It could be something very different and applied in wide-use cases.
For example, one of the ways Google monetizes data is by aggregating and delivering anonymous data from millions of cars on the road each daily. This data can be sold on to both traffic authorities and traffic report apps.
Beyond traffic and road conditions, sensors on cars also collect data on variables such as weather conditions, which can then be used by forecasting platforms, for example.
We can notice a trend in the B2B market, especially with companies dealing with manufacturing or companies that deal with heavy machinery. These companies rely on data for predictive maintenance (PdM).
To implement preventive and predictive patience, OEMs need to collect data across several points, including sensor integrated in a piece of machinery.
With the ability monitor the real-time condition of components, wear parts and consumables within the machine, the maintenance engineer knows when to service a machine, what needs to be changed, and what exactly to service.
I see this increasing in the market because in these types of businesses when one machine breaks down, it affects the whole production line. This is why the world is tilting towards outcome-based pricing. We are not there yet, but we see a lot of companies plugging into this.
Outcome-based service is the future of data monetization in general. The goal is to match the perceived value of a product or service by a customer.
It’s about how much the customer is ready to pay for a service when it’s intangible and most times, this is difficult. But if implemented well, it unlocks endless opportunities in businesses.
The best way to approach this usability with customers is to have the correct unit of measurement, which as be as simple as tracking kilowatts of electricity consumed.
When it comes to more sophisticated metrics, like tracking usage of a fleet of devices in the field, you’re dealing with a much high number of data points and metrics in real time.
Monetization of service usage data can involve the aggregation of multiple metrics. Because of the level of granularity required, this makes monetization much more complex,
You could get away with a simpler use cases. But to get to that holy grail, you need a more robust level of data aggregation and granularity.
There are no specific needs for software. This is good news, because companies can make quick wins with data monetization if they employ the right software and technology.
Businesses running with one-time or flat-fee payments may find it difficult to monetize data. For companies like this, the first step is to tilt toward a usage-based pricing model.
Companies that already offering service-based or subscription-based models have easier entry points. First, is to have raw data which could come from data lakes or your API platform.
In between, you need to aggregate the data and the more you aggregate and crosscheck with different data sources, the more business value you can target.
At the exit of the pipeline just before the data is inserted into the monetization engine, we can decide the level requested by the customer.
Before monetization, data needs to be safe, certified, and robust. It needs to be connected to the right systems and with our business rules, we can implement processes for data transport.
For over 25 years, DigitalRoute has been managing these complex systems, and we’re ready for the ever-growing volume of data generated by digital service offerings in complex partner ecosystems.
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