Unlocking vehicle data and creating value for both the vehicle manufacturer and driver


Martin Moravek
Solutions Architect

Giving drivers greater control over their car’s data to decide whether to share it with 3rd parties in return for a share of the revenues generated from its sale could help vehicle manufacturers overcome their existing challenges to monetize vehicle data.

More data awareness among customers

In recent years there have been several major company scandals related to data that have had a damaging effect on their respective brands. Here’s just a select few examples — Facebook and their well publicised Cambridge Analytica data scandal (where millions of users’ data was harvested without their consent and used for political advertising), and Avast, who had to shut down their $180M company Jumpshot that offered analytics based on secretly collected Avast users’ data. This has resulted in an evolution of citizens’ attitudes, who have become more sensitive towards how their data is handled, while awareness amongst citizens that data has a high value is also rising. 

Car manufacturers are in an increasingly challenging situation

Like many major enterprises, such as those in banking where PSD2 and Open Banking has recently been introduced, vehicle manufacturers (OEMs) are also under increasing pressure to open up the data collected by their vehicles. Privacy challenges like those mentioned above create a feeling of risk surrounding data in general, and pose challenges about how to open up this data in a legally compliant way that doesn’t also give away a competitive advantage. OEMs recognise action is needed, which is why alliances such as Trusted IoT Alliance and MOBI have been created to deal with this topic, amongst others. In this blog post we are going to focus the discussion on the value that can be created from data and the opportunity that exists. But firstly, let’s provide some further context on why a dramatic change in thinking is needed within the automotive industry.

Many vehicle manufacturers are going through challenging times. There are multiple emerging trends in the mobility industry that pose a threat to the survival of traditional car brands. The shift from combustion to electric vehicles is one such challenge demanding huge investments by manufacturers — VW is investing €33bn into electromobility, GM $20bn and Ford $11bn. The Return on Investment is uncertain and the additional challenge presented by the recently emerged aspirational car brands of the 21st century like Tesla, who have built their brand on the foundation of electric vehicles and self driving, results in added pressure for these investments to be a success.

Other challenges include the general trend of servitisation, which moves customers from being vehicle owners to using sharing services instead, lowering the total number of cars being needed, and the holy grail of autonomous driving — whichever company achieves it first will get an advantage nearly impossible to beat by collecting enormous amount of driving data.

“Deutsche Telekom estimates that the vehicle data business is three times more lucrative than automotive production itself.”

Untapped resources

Despite the need for alternative business models among vehicle manufacturers, one of the biggest opportunities for income generation remains untapped — data generated by vehicles. Deutsche Telekom estimates that the vehicle data business is three times more lucrative than automotive production itself. So why are OEMs so hesitant in getting the maximum revenue from vehicle data?

Fear of negative customer reactions can be one of the factors holding vehicle manufacturers back from extracting the maximum possible value of car data. But is there a way to do this without upsetting customers? If we would try to analyse causes of customer´s unacceptance, we would see two most common reasons.

“There can be a major difference between what is legally seen as a user giving consent to monetise his data and a real informed decision of a user.”

Factors for negative customer reaction on data monetisation

1. Missing real customer consent. There can be a major difference between what is legally seen as a user giving consent to monetise his data (e.g. sharing it with a 3rd party for a fee) and a real informed decision of a user. Every time you install a new app or sign up for a new service you need to agree to their terms and conditions. These are typically 1000s of lines long and written by lawyers for lawyers. Most of the users don’t read them — they are just simply too long and hard to understand. Later, users may be surprised about what they have agreed to be done with their data.

2. No revenue sharing. Google and Facebook based their main business models on generating value from customer data, and generally companies monetising customer data earn billions of dollars without giving anything back to their customers. Sometimes they provide a “free service” in exchange, but how free is this service in reality, when you’re excluded from the revenue your data generates? In some cases even the service or product itself is not for free and customers have to pay for it in addition to the company monetising their data.

Is there a better way?

Is it possible to monetise your customer data without upsetting them? Let’s reflect on the previous 2 points:

1. Customer data monetisation should happen after a clear opt-in by the customer. The option “I agree to my data being sold to a 3rd party” has to be clearly presented to the user. Now you may be wondering, why would anyone agree to this? Lets have a look at the next point:

2. Revenue sharing with customers after their data is monetised. Again — it’s your customers’ data. If you made money out of it you should share a portion with your customers. This of course requires an infrastructure, also considering regional legal differences and the need for micropayments, but we will look into that.

Where to start

One of the biggest markets for user data is the advertising industry. Let’s take a look at a small case study example on how fair user data monetisation could work if you are a vehicle manufacturer.

Data extraction from vehicles

To make this offering viable, you want to offer data from as many cars as possible. Most likely your vehicles are not able to do an over-the-air update so you need to find another way. Luckily most modern cars have an entertainment system that can be extended with smartphone companion apps. These apps also have access to many data sets collected by the car (position, speed, state of vehicle) that we can leverage in our advertising use case. While driving this smartphone app can continuously read vehicle data, anonymise them and lower precision of selected values if needed. Afterwards, the app can forward this to a data marketplace for monetisation.

Each vehicle can have its own Ethereum based identity, which can be used to sign the data it produces and receive ERC-20 tokens in exchange when the data is sold.

Data Marketplace

In order to make this data discoverable and tradeable with potential buyers, you’ll need an open and transparent data marketplace with payment options. You can either join an existing data marketplace (e.g. Streamr Marketplace) or have your own whitelabelled instance as the whole technology stack has been open-sourced. This marketplace uses the Ethereum blockchain as an underlying layer for recording access rights, settlement and purchase when a data product is bought. Also, thanks to a P2P network developed for real-time data transfer, this data marketplace allows live data monetisation, a clear benefit as data has the highest value when it’s new.

Data Union for vehicle data (data flows from community members to data buyers, payments flow from data buyers to community members)

Data Union

To enable data buyers to buy data from a large number of vehicles with a single Ethereum transaction and in a unified format and quality, data from all participating vehicles can be offered via a single Data Union. Data Unions are a type of data product which support all data crowdsourcing aspects and significantly lowers the entry barrier for data buyers when crowdsourcing data directly from users.

Compared to regular Streamr data products, users producing the data don’t need any programming knowledge to participate and integrate their data — instead the data is collected via a product specific Data Union integration (in this case the smartphone app). Data Union integrations are developed by a Data Union admin — typically either an independent engineer, company helping its users to sell their data in a fair way, or a company in need of buying data that is currently not available on the market but can be crowdsourced. In this case, the Data Union product integration (in the form of a smartphone app) will be developed by, or on behalf of, the vehicle OEM.

The Data Union Admin (in this case, the OEM) develops and maintains the Data Union integration. To offset the costs of this work and make it sufficiently financially attractive, the Admin would typically take a percentage of the revenue from the data sold.

How to scale on Ethereum

Sharing the revenue between many participants with separate individual participant transactions can be very slow and expensive on the Ethereum blockchain (transaction costs can easily exceed the amount of revenue shared). Therefore, Data Unions use Streamr’s Monoplasma framework that allows one-to-many revenue sharing with 100,000s of users with a single on-chain transaction. For more details see Streamr’s Monoplasma blog post.

Data purchasing

Advertisers will be able to buy access to live data produced by participating vehicles via the data marketplace and analyse their demand for products and services. In return for this data, the advertisers will issue targeted offers — each targeted at a specific Ethereum identity representing a car that has produced part of the data being sold.

“A vehicle is sharing and selling its data live — including location and fuel tank level.”

Redeeming an offer

Some offers may be publicly available for everyone, and drivers can just be made aware of these by the advertisers. But the exciting part of this proposition are true individualized offers, valid only for a specific driver. To redeem an offer in a participating shop, the driver can present a QR code on his smartphone app.

Example of a targeted offer

A vehicle is sharing and selling its data live — including location and fuel tank level. When a car is low on fuel, the advertiser, that has purchased access to this live data, can react to this information and issue a targeted offer to this car which could include a discount to use a nearby gas station.

Kicking off a whole new model for the data economy — who will be the winner?

Whichever manufacturer will be the first one to offer this model of data monetisation, with revenue sharing to their customers, will be the one to receive all of the PR benefits for promoting this fair and open approach, in addition to the benefits of increased revenue from this new untapped source. Eventually this level of data handling can become a moral standard for a fair approach to data monetization, where other OEMs will have no choice but to offer the same level of service in order to stay competitive. As we are currently talking to several car OEMs and suppliers, this may become a reality sooner than you think.

This article was originally published on Medium.

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