My Digital Footprint

BUSINESS MODELS

My digital footprint, as defined in this book, is about the system of collection, storage, analysis and value. The inputs to the system have focused on data types that can be collected as the user is willing to provide the data (explicit/active) and data that can be gathered by sensor.net (passive/automatic). It has already been stated that there is little value in the long run in collection (harvesting) and storing (regulated). There are possibly a few expectations to this, which are data types that are slow to replicate and can create a differential advantage by having/owning. There is a lot of value in the algorithm and good analysis tool. The understanding of value creation opportunities from analysis will create differential advantage. The outputs or value components are well understood in terms that they can be seen to create value. Additional value is created from the feedback loop as this provides a method to hone, focus and provide depth on responses to an individual based on their data inputs, and also the ability to add flavour, breadth and width based on the individual’s social graph. It has been explored who will engage and participate, and how to create this virtuous cycle and keep it going by understanding the bonds and bridges between risk, privacy and trust. This section focuses on the fundamental question of who owns the data and what the business models are that my digital footprint creates.

The models to exploit my digital footprint are determined by who owns the data, the options being: ‘I own my own data’ or ‘I give up my data’. Indeed, it is likely that, in many cases, both owning and sharing will be a healthy and amicable compromise, but it is worth focusing on the two separate models of ownership, as from this it is possible to draw clear intentions, value and models. Those that combine joint and shared ownership will, like the rainbow of trust, create and fill in the prime groups.

Figure 44 provides the outline of the models that will be explored.

Figure 44 Business models based on data ownership

What data can I own? 

I am in no doubt that owning data is difficult, ignoring the fact that even if I can get it, the analysis may be too difficult to create value. Some data (name, address, date of birth, certificates and other identity data as discussed at the outset) are in fact easy to own but hard to prove. Utility bills, bank and credit card statements are easy to collect and are easy to add to your database. Electronically collecting this data is easy and there are programmes that will allow you to build your own spend profile. Data from Amazon, eBay, PayPal, Yahoo, MSN, iTunes, SMS, email, AudioBoo, Palringo, Google, Facebook, Flickr, blog, Twitter, etc, is rather a more difficult case.

Yes, I replicate everything via a small widget on all my devices/screens so that I own a copy of my data (passive and active) and so does the service provider. It may be difficult to replicate some purchase information, especially cash and near field cashless. Currently the terms and conditions of many of these services determine that they have the rights over your data, they are currently prevented from sharing this to help you. How this small widget combines all the data streams is somewhat more difficult, as is how does my algorithm compare data from my social group to add colour and flavour to my services. Finally, how will my analysis output become available so that it can be fed into a service and, hence, I can enjoy the value?

Difficult and practical questions, and I am aware that some companies are working on them and why there is a lot of wealth to be created in this area and why the business model is wide open.

I purposely have not mentioned too many examples as the website http://ww.mydigitalfootprint.com allows readers to add their own examples and promote their own services. I have also avoided the cross-subsidies, two side and freemium categorisation. In many cases, most of the economic models are available; it really depends on the motivation of the service provider, end customer and other parties on how they trade value for data.

I am aiming to gather views on collective action. Could/Should we as creators organise a tribe via Twitter and Google to recover ownership? Google own the link, but didn’t create it.

I own my data

Model 1: Pay for enhancement to service

In this simple and traditional business and economics model, data that is collected may provide access to some simple or basic features and functions. However, to gain access to enhanced, professional or premium services, a user needs to pay. The payment can be a one-off fee or a subscription-based model. The pricing of such services is becoming increasingly complex and there is a move from the traditional supply­–demand economics to funding pricing that is based on ‘bits are free’. In this case, I own my own data and there is a requirement for me to pay for the service of collection, store and analysis. I also need to pay for the presentation of my data to be able to receive the benefits that are offered.

In this case, the user/customer still worries about collection, store, analysis and presentation of the data; however, a service provider takes the analysis and trades this for access to enhanced services as this customer has value. This is a simple barter.

Like the direct trade model, the user/customer has the same responsibilities; however, in this case, an aggregator of data collects many users together to create a proposition that enables the user to gain access to many service providers’ enhanced services. The aggregator may well be performing a translation service if there are a number of presentation formats for my digital footprint generated from a fragmented market.

The simplest form don’t bother with the data and just buy the service.

Model 5: Trade data for service directly with service provider

Unlike model 2, trading for enhancements, in this case the user/customer has to barter information to gain access for the simplest or basic level. This model assumes that there is a lot of demand for the basic service and there is value in the user/subscriber. BLYK is a good example.

This is like model 3; however, in the same vein as model 5 (trade directly) this model depends on an aggregator of data to sit between the user and the provider, much like comparison shopping sites.

The model here is where a user/customer wants to pay to be protected. Ignoring any value in the data for an exchange and preferring to pay.

This is a complex model; the user/customer has the same responsibilities as for all ‘I own my data’ models. However, in this case, the user opens the data presentation layer to a trusted third party who will use the analysis of the data to bring and offer services to the user. This offer could be in the form of free enhanced services or cash (or cash equivalents) given to the user/customer, as their data is seen as valuable to certain brands or marketing companies, remembering that MY DIGITAL FOOTPRINT covers all the screens of life across mobile, web and broadcast.

In each of these models there is a question about the user giving up control to a single service provider or many. If control is given to many, does each of the service providers have identical data or specific to their utility value? Does eBay only see your auction items, or can it see Amazon’s and Google’s data, or will single service providers, such as mobile phone operators, collect it all and distribute it? But will the user trust them in return, and how moveable will the data types need to be to prevent unfair competitive barriers being erected?

Model 1: Pay for enhancement to service 

As with owing my own data, this is a simple model, data that is collected may provide access to some simple or basic features and functions. However, to gain access to enhanced, professional or premium services, a user needs to pay. The payment can be a one-off fee or a subscription-based model. The pricing of such services is becoming increasingly complex and there is a move from the traditional supply–demand economics to funding pricing that is based on ‘bits are free’. In this case, I give up my data to a service provider in exchange for collection, store and analysis.

A service provider takes the collection, store and analysis and trades this for access to enhanced services, as this customer has value. This is a simple barter, but does demand enormous trust.

Like the direct trade model, the service provider has certain responsibilities; however, in this case, an aggregator of data collects many users together to create a proposition that enables the user to gain access to many service providers’ enhanced services. The aggregator may well be performing a translation service if there are a number of presentation formats for my digital footprint generated from a fragmented market.

The simplest form don’t bother with the data and just buy the service.

Model 5: Trade data for service directly with service provider

Unlike model 2, trading for enhancements, in this case the user/customer has to barter information to gain access for the simplest or basic level. This model assumes that there is a lot of demand for the basic service and there is value in the user/subscriber, and that the user has an economic value to the service provider.

Model 6: Trade data for services via a third party (indirect), such as an aggregation party

This is like model 3; however, in the same vein as model 5, trade directly, this model depends on an aggregator of data to sit between the user and the provider, much like comparison shopping sites. The issue being, as described at the beginning of this session, does the aggregator have the power or the service provider, and which one does the user trust?

Not possible if you give up your data, the model assumes that you keep it to yourself.

This is a complex model; the service provider has the same responsibilities as for all ‘give up my data’ models. However, in this case, the service provider opens the data presentation layer to other trusted third parties who will use the analysis of the data to bring and offer services to the user. This offer could be in the form of free enhanced services or cash (or cash equivalents that could be bartered with the service provider for free access or basic services) given to the user/customer, as their data is seen as valuable to certain brands or marketing companies, remembering that MY DIGITAL FOOTPRINT covers all the screens of life across mobile, web and broadcast.

The reason for soliciting and collecting consumer data has fundamentally changed due to the web.

Web 1.0 enabled successful companies to gain power by collecting, aggregating, and analysing the customer data they collected and offered something relevant back, this was a useful addition to the zero cost of distribution.

Web 2.0 brought about a new dimension to data, that of data created by the user. Users started to contribute explicit data about themselves, their social graph, how they consumed content or about purchases. This data extended click-and-search data that characterised Web 1.0, and Amazon reviews, using inherent knowledge to offer trusted recommendations, led the way. Online collaboration, such as Wikipedia, increased transparency leading to users being able to help themselves and their community. Web 2.0 is a model of creation, engagement and collaboration where success is built on rewarding users who contribute data, honest data now builds a reputation. Marketing strategies are evolving from how brands engage with consumers based on what data is collected and how they analyse it, to creating value. Consumers now expect and experience relationships and the ability to trade or barter (exchange).

The web has undergone three data revolutions, starting where companies implicitly captured consumer data, which they used to infer intent. This moved to consumers explicitly providing data about themselves and that embraced users/consumers expecting something in return for the data they provided. The third move involved the linkage of the person to social graphs and Web 2.0 was in full swing. The next phase of Web 2.0 will be sharing my digital footprint across platform (web, mobile and broadcast) and service provider. Thus, it will no longer be about what you consumed, but rather the social context of what you consumed. The semantic web (Web 3.0), where the web has intelligence, is a long way off.

Capitalism, it could be argued, has broken the trust between users and companies. For companies to thrive they need to rebuild (or build) trust through engagement, relationships, communication, participation, co-operation and collaboration with their customers, this could mean a shift from the economies of scale to a rainbow (economy) of trust.

When I die?

What happens to my digital data when I die? I have purposefully left this section open to collect views from the web site. Personally I am happy for it to remain, but if I believed it could be a hindrance for my family, maybe I should find a route to erase it? I can see that for the family of a celebrity is could be of great value and great pain, knowing what was done and when, but amazing information for a biography or life works. Divorce law and pre-nuptial agreements have just become more complex.

What should happen to www.tonyfish.com when I am gone?