Online Platforms the Data and Insight Engines of the Digital Economy
Companies with online platforms in social media, healthcare, finance, travel and hospitality, education, have built business models, that enable the monetisation of data.
Through the leveraging of proprietary technologies, network effects, and the exploitation of economies, of scale and scope. From the massive amounts of online users generating behavioural data.
The next stage in data monetisation will focus on leveraging devices as machines to harvest user data to profile the user and create insights that can be used in -house or sold to third parties.
The market valuations of companies as diverse as Amazon, Booking.com, Facebook, Ant Financial, Grab, eBay, Topcoder, GitHub, Waze Microsoft and Google are a testament to the value of creating business models, that enable the monetisation of data.
Data Monetisation Frontiers
Today digital data comprises 99% of all data stored. Advances in AI and machine learning is enabling companies to make sense of the tsunami of data produced, and identify what data is of value to their organisation, and in some instances, create new services to offer the wider business community.
However, where are the data monetisation frontiers, likely to reside? And how can your organisation take advantage?
The migration of business models, mobile devices, consumers and business online. Along with the emergence of AI and machine learning technologies, and the creation of vast amounts of structured, semi structured and unstructured data.
Means that the economy has reached an inflection point, in transitioning from a knowledge based (KBE) to a data driven economy (DDE).
Data Monetisation Frontiers - Telcos
For example, telecommunication companies as a result of the operation of their cellular network. Are in the auspicious position of identifying who traversed an advertising asset, (Billboard, Electronic Kiosks,) this could be an individual or an occupied vehicle.
Also, as telco's own identifier data such as names, and addresses they can precisely match a consumer's movement to their mobile devices in real-time.
The technical term for this is called asset surveillance. Placing, telecommunication organisations in the advantageous position, of identifying the precise value of any advertising asset located within the area covered by their cellular network.
Geolocation technology enables telco companies to determine the location of a customer, this information may be sold onto marketing and advertising agencies. And demonstrates how asymmetric data may be monetised for profit.
In essence, the telco owns information, that is, rare and difficult to replicate, on marketing assets that other organisations, (marketing and advertising agencies), purchasing advertising space on the aforementioned assets do not.
These 3rd parties may be willing to spend money in exchange for access to the insights derived from the data.
The Consumer Perspective
The number of mobile phone users in 2020 is forecasted to grow to 3.5 billion, by 2021 that figure is expected to increase to 3.8 billion.
Whilst companies, such as telecommunication organisations, are well-positioned to capitalise on the vast volumes of mobile data produced each year.
According to hostingtribunal.com, global mobile data traffic will increase to 49 exabytes per month by 2021 from 7 exabytes in 2016.
Currently, there are no online platforms where consumers can sell their data to a variety of actors that may find their information useful in driving their business activities.
There is an on-going debate centred around the sovereignty of consumer data. This is related to the sharing of consumer data, between organisations with the permission of the data owner.
To facilitate the creation of innovative new products within the financial services.
However, the spill over effects of this conversation occurring within governments may also, impact, other industries where consumer data monopolies exist. Such as the telecommunications and energy sectors.
Currently, there are no platforms available for consumers, to monetise the mobile data generated when they engage in activities on their phones. These platforms where the exchange of consumer mobile data may occur. Could operate as a place for consumers sell their mobile data to businesses interested in harvesting their information.
Mobile sensors embedded within mobile phones enable the collection and analysis of sensed data, hence, when aggregated on a large scale is potentially monetisable within the platform.
Challenges
There are no platforms for monetising data that engages a wide range of primary data providers.
Consumers the de facto sovereign owners of the data are not compensated for sharing their personal data expect via non-monetary means.
There is a lack of clear classification of data quality levels across a wide range of to aid in determining the value of the information provided by consumers.
Things to Consider
Pervasive Information Asymmetry: In a data driven economy information asymmetry is a hinderance to the optimisation of supply chains. However, conversely, information asymmetry may be very profitable for owners of platforms, with access to proprietary data, on activities driven by the behaviour of actors operating within a platform.
This information can be sold to other organisations to enhance the value of their own value propositions. To the communities that my use their apps and or platforms.
Winner Takes Most: In a data driven economy organisations that deliver data driven services will capture the majority of value within a given industry
Industrialisation of Learning: Machines can learn at a significantly faster pace than humans. The data-driven economy industrialises learning itself through the deployment of AI (Ciuriak, 2018).
Reshaping the job market through the deployment of AI applications will accelerate the demand by employers and employees for lifelong learning to remain relevant.
Market Concentration, Superstar firms and Strategic Behaviour
The economies of scale in the digital economy is significantly steeper than in previous iterations of the economy. Due to the following factors.
Although the initial investment cost to capture assemble and process data is high, the marginal cost of expanding data assets is very low. As the infrastructure for the collection of additional amounts of data essentially has already been built.
Also, the distribution of digital products is marginal, insofar as, once a successful digital product is produced, the cost of creating the next version is close to zero.
The near frictionless commerce enabled by the Internet and globalisation facilitates the appropriation of greater market share by the most successful companies.
Also, network externalities, favour the emergence of natural monopolies, as the number of users and actors on the platforms grows, the value created in the platform increases. This in turn will enable the firm to appropriate greater market share within a given industry.
The Economics of Online Platforms Business Models
In online platforms sell side actors are used to recruit buy-side actors the expansion of users on the buy-side and sell side is what drives revenue within the business models.
Multi-sided platforms facilitate the interaction between different groups, who engage in value exchange reducing transaction costs.
Unlike traditional business models, multi-sided businesses are not linear, they appropriate value for multiple actors, incumbent within the platform, including the platform itself.
In the form of subscription fees, commission on each transaction conducted within the platforms. Leading to inter-dependencies between platform customer groups
Producers of complementary products (e.g. app developers) and end consumers (gamers),
Advertisers and readers,
Shoppers and sellers,
Job seekers and recruiters,
Accommodation providers and accommodation seekers,
Transportation providers and passengers.
Positive and Negative Network effects of Platforms
The internet a general-purpose technology has lowered the transaction costs associated with creating, distributing, acquiring and providing goods and services.
Platforms benefit from positive network effects. This essentially means that as the number of users on the platform increases this is beneficial to other users with the same characteristics.
Benefits of Online Market Places to Consumers
Hence on a multi -sided platform for home buyers and sellers, if the number of home buyers, increases this is beneficial to other home buyers as this will attract a greater number of sellers onto the platform.
Hence lowering the transaction costs associated with purchasing a home due to the aggregation of customers on the platform.
Indirect positive network effects exist where users of one group benefit from an increased presence of users from a different group. This is when sellers on an online marketplace benefit from a higher number of buyers.
For multi-sided platforms, strong indirect effects is an important feature distinguishing these platforms from one sided marketplaces. Hence, additional suppliers on a platform are beneficial to other suppliers as this increases the level of convenience, transparency and the reduction of costs.