Tag Archives: Graph Theory

Adoption and growth

Early Network Growth

Leave a comment

HM Government’s target is for all British Citizens aged 15 years and above to have a Britizen account; and for as many of these accounts as possible to be used regularly. Participation will be voluntary initially; the government’s intention is that the platform has become ubiquitous before participation is made compulsory.

This post outlines how the number of Britizen users, speed of adoption and continued use of the platform will be facilitated.

Value Proposition

A value proposition is an innovation, service or feature intended to make a product or company attractive to customers. A value proposition shows how the product solves customer problems; improves their situation; or offers specific benefits.

Like Sesame Credit, Britizen offers tangible benefits to members which increase with their Britizen score. These benefits are designed to nudge or encourage members to support British values, promote trust and create a better society. Trust is encouraged by both rewarding trustworthy behaviour and allowing third parties to use an individuals’ credit score to assess them. Initial benefits are designed to appeal to a broad section of the population, and include tax reduction, priority in government housing, and discount vouchers for British services.

At a time of increasing concern about globalisation, using Britizen is a practical way people can demonstrate support for British values, culture, innovation and business.

Rogers Adoption Criteria

Rogers Diffusion of Innovations (Rogers, 1983) defined five criteria material to the adoption of new ideas and products: relative advantage, compatibility, complexity, trialability and observability.

These factors have been considered when determining the requirements and design of Britizen, to help ensure consumers are willing to try the platform.

Relative advantage: is outlined in the value proposition. Britizen will return most surplus profit to members in the form of tiered benefits with broad appeal. Tax benefits are targeted to better off users; priority on government housing waiting lists appeals to ‘strivers’ struggling to afford a home in modern Britain. As Britizen matures business sponsors and advertisers will be encouraged to extend the user benefits with special offers, discounts and tokens with appeal to a broad spectrum of users. This contrasts with the approach of private corporations; which are operated for profit.

Compatibility: Britizen will contain the features familiar to online social network users.

Complexity: Britizen will be intuitive and simple to use on a wide variety of devices.

Trialability: there is no charge to use Britizen; the only requirement is to have a valid National Insurance number.

Observability: Initially advertising and other marketing techniques will be used to make people aware of Britizen. The gamification component of Britizen scores will encourage people to discuss and compare their scores; users will be motivated to encourage others to sign up to enhance their own score. Early sponsors will be carefully chosen visionary and imaginative businesses who will produce exciting, attractive materials which make the site more attractive and appealing. Influential users will be identified a encouraged to encourage others to join.

 

Rogers Adoption Model

Rogers defines five categories of user over the product lifetime: innovators, early adopters, early majority, late majority and laggards. At this stage, the focus is from start up to a majority of the UK population using Britizen.

Sponsors will be selected to appeal to the type of user likely to join at each stage. Celebrity endorsement will be used to appeal to different user categories; network analysis will be used to identify less public members who are likely to be influential; those with high degree centrality, nodal betweenness and/or occupy structural holes. These members will be targeted to encourage others to join.

Mavens, Connectors and Salespeople

Gladwell’s Tipping Point (Gladwell, 2000) describes the importance of three different groups of people in influencing the spread of behaviour, which he calls Mavens, Connectors and Salespeople.

Mavens are known and respected for having expertise in specialised areas which they are willing to share. Martin Lewis’ Money Saving Expert[1] is an example of an influential British website highly respected for its specialised knowledge in how to save money. Information and advice about the benefits of Britizen from this site will help generate visibility and trust as well as providing encouragement to join Britizen.

Connectors are particularly valuable because they have connections to many people and often act as bridges between groups or clusters in social networks. Their ability to bridge groups is also important in spreading Britizen widely throughout the population.

Salespeople (also known as evangelists) have the skills to persuade people and convince people to action.

Not all mavens, connectors and salespeople act in professional or paid capacities.  Network analysis of the Britizen graph will be used to identify members who are likely to be influential; those with high degree centrality, nodal betweenness and/or occupy structural holes. These members will be specifically encouraged to persuade others to join Britizen.

Network effects (Direct, Cross & Indirect)

Direct Network Effect: The value of an online social network increases with the number of members; the higher percentage of an individual’s contacts using the network the more useful it is to that person. There tends to be a critical mass or ‘tipping point’ (Gladwell, 2000) of membership beyond which membership increases rapidly in a similar way to an epidemic. Once a network achieves ubiquity there is pressure for laggards to join to avoid being left out.

Cross Network Effect: occurs when a rise in one group of users makes the network more valuable for another group of users. For Britizen there is a symbiotic relationship between users and sponsors/advertisers. The sponsors and advertisers benefit directly from a larger user base. The benefits available to users will increase as the revenue generated from sponsors and advertisers increases. This is covered in more detail in my post about the Britizen Revenue Model.

Indirect Network Effect: is generated when third parties create complementary goods. This process is helped by having a reliable Application Programming Interface (API) and publishing easily useable ‘five star’ open data [2]. Third parties are more likely to be interested in developing related products once Britizen has an established user base.

Marketing Campaign

A carefully focussed marketing and advertising campaign will be used to:

  • foster the rapid initial adoption of Britizen until the tipping point is reached
  • maximise the opportunities afforded by the influencers outlined above
  • target groups of the population where uptake is relatively low
  • market the benefits of sponsoring Britizen to British businesses

 

References

Gladwell, M., 2000. The Tipping Point. Little, Brown and Company.

Rogers, E.M., 1983. Diffusion of Innovations, 3rd ed. Collier Macmillan, New York.

 

[1] www.moneysavingexpert.com

[2] http://5stardata.info/en/

Analysis of Similar Systems

Mining financial and social scores from social network data

Leave a comment

 

Image courtesy of cafecredit

Introduction

Britizen explores the concept of a social network where the social ‘credit score’ of members and the groups they belong to are co-dependent. This posts considers the academic literature related to developing financial and social credit scores from social network and online shopping platform data. As a result of this research we decided that in the UK it is more feasible to introduce a ‘social’ rather than ‘financial’ credit score social media application.

Analysis of similar Systems looks more closely at existing online social network systems.

Determining credit scores

In the UK, banks and other financial institutions use historical data to evaluate how ‘credit worthy’ an individual customer appears to be. This is used to determine the risk involved in making each loan, and the appropriate interest rate and or security required.

Credit reference agencies such as Experian[1] and Equifax[2] are used to share knowledge of consumer credit behaviour. The financial history of businesses is also recorded and shared via credit reference agencies such as Moody[3], Standard & Poor[4], and Fitch Ratings.[5]

In some countries (including China) micro businesses and consumers find it difficult to obtain credit from mainstream banks and financial instructions because these bodies do not hold such data about them (Kshetri, 2016; Shu, 2015; Wei et al., 2014) Data about online consumer behaviour can be gleaned from:

  • transaction data held by online shopping portals such as Alibaba[6] and Amazon.
  • online payments records from online payments systems such as Alipay[7]and PayPal
  • non-financial data gleaned from users posts and relationships on social media platforms such as Facebook[8]

China Rapid Finance claim to use both financial and ‘unstructured online social’ data[9] to predict whether a borrower is likely to repay a loan. Kapron (2016) suggests that it is unlikely that systems of this kind could operate in the US due to privacy concerns. in general the EU has stricter privacy legislation than the US; it is thought unlikely that use of unstructured social network data for financial credit scoring would be considered acceptable in the UK at present.

Sesame Credit uses a combination of five factors to assess credit. These include “users’ credit history, behavioral habits, ability to pay off debts, personal information and social networks” (China Daily, 2015).  Members can choose to publish their score. Gamification encourages competition between users as to who has the highest score; and incentivizes ‘desirable’ behaviour (making payments promptly). Users also have a direct incentive to recruit others to the platform: their own score increases with the number of their friends. Game theory can be used to model such effects.

In our focus group a Sesame Credit user commented that most Chinese people ‘just know that the more they consume, the higher mark they will get‘. Gamification in Sesame Credit appears to successfully modify user behaviour;  spending more to increase a personal score and obtain more benefits was a common thread.

Facebook have acquired a US patent[10] which includes using the credit rating of a user’s social network to determine whether to reject or proceed with a loan application (Lunt and Facebook, 2012). Kapron states that they have run and withdrawn a pilot experiment on these lines.

Academic literature includes Selde’s study which determined that Facebook data can be used to derive a useful financial credit score (Selde, 2013). Wei at al  also researched the potential effects of using social connections and data to determine credit scores; and suggest that low scoring individuals might be motivated to improve their behaviour in order to improve their scores.

Wei et al also concluded that there is a risk groups will become stratified (homophily) to protect their scores. In a different context; Kossinet and Watts carried out an empirical study into evolving social networks at a large university; and concluded that  the presence of strong ties between two strangers and a mutual aquaintance was stronger than the effects of homophily expressed as class, age, and gender in that situation. If this effect also applies to Britizen it could reduce the tendency of strong triadic closure to result in a very stratified network.

References

China Daily, 2015. Sesame Credit helps you open sesame – Business – Chinadaily.com.cn [WWW Document]. URL http://www.chinadaily.com.cn/business/2015-01/28/content_19431324.htm (accessed 3.4.17).

Kapron, Z., 2016. Measuring Credit: How Baidu, Alibaba And Tencent May Succeed Where Facebook Failed [WWW Document]. URL https://www.forbes.com/sites/zennonkapron/2016/03/17/measuring-credit-how-baidu-alibaba-and-tencent-may-succeed-where-facebook-failed/#332b551327c2 (accessed 3.2.17).

Kshetri, N., 2016. Big data’s role in expanding access to financial services in China [WWW Document]. URL http://dl.acm.org/citation.cfm?id=2906812 (accessed 3.2.17).

Lunt, C., Facebook, I., 2012. Authorization and authentication based on an individual’s social network. US9100400.

Selde, E., 2013. Study of credit scorecard using only Facebook data – Big Data Scoring.

Shu, C., 2015. Data From Alibaba’s E-Commerce Sites Is Now Powering A Credit-Scoring Service | TechCrunch [WWW Document]. URL https://techcrunch.com/2015/01/27/data-from-alibabas-e-commerce-sites-is-now-powering-a-credit-scoring-service/ (accessed 3.2.17).

Wei, Y., Yildirim, P., Bulte, V. den, Christophe, Dellarocas, C., 2014. Credit Scoring with Social Network Data. doi:10.2139/ssrn.2475265

[1] http://www.experian.co.uk/

[2] https://www.equifax.co.uk/

[3] https://www.moodys.com/

[4] https://www.standardandpoors.com/en_US/web/guest/home

[5] https://www.fitchratings.com/site/home

[6] https://www.alibaba.com

[7] https://global.alipay.com/

[8] https://www.facebook.com

[9] http://chinarapidfinance.com/

[10] US9100400

Business Plan, Revenue model

Britizen Revenue Model

Leave a comment
Image about monetizing Web 2.0
Dion Hinchcliffe

Britizen will be free to use for consumers; and funded by multiple income streams. The initial sources of revenue will be advertising and sponsorship.

Once Britizen is established there is potential to generate income from additional sources. The concept and software can be franchised or licensed to other governments. Anonymised user data can also be sold to carefully chosen partners.

Profits will largely be used to fund benefits for Britizen members; creating a virtuous circle in which more members are encouraged to join and existing members encouraged to stay as benefits increase. This is known as a cross network effect (Shuen, 2008 p.42). The value of an online social network to advertisers and sponsors increases with the number of activate members; generating increased income and profit which can be ploughed back into member benefits.

Part of the Britizen ethos is to support the British economy; all sponsors and advertisers will be British brands. Platform users will be encouraged to support British businesses.

A sample advertisement on a use timeline is shown in Figure 6 of the mockup design.

 

Early stages

Sponsors and advertisers will provide the initial external revenue sources. The value proposition (Kaplan and Norton, 2000) for these actors will be carefully formulated. Initial sponsors and advertisers need to be attracted to spend their advertising budget on Britizen instead of other social media platforms.

Britizen is a new concept; sponsorship opportunities will initially be focussed on the ‘Innovators’ of Rogers Adoption Model (Rogers, 1983); visionary and imaginative businesses who will produce exciting, attractive materials for the site. The next group of potential sponsors (Rogers ‘early Adopters’) should have strong brands and use innovative techniques to gain a social and economic edge. These businesses (such as Virgin and Innocent) are likely to be willing to form partnerships contributing to the success of the platform.  Early sponsors may be offered advantageous rates as inducements to partner with Britizen. The platform needs to generate sufficient income to minimise burn rate (Shuen, 2008, p.24), create a positive cash flow and sustain growth quickly, as HM Government cannot afford to continue providing a subsidy long term. Maximising profit is less important than establishing a strong consumer brand and customer value proposition at this stage; in the short term it is more important to attract large numbers of active users quickly.

The involvement of trend setting sponsors and advertisers will help Britizen appeal to the early user adopters of the platform, and benefit from exposure to these users.

Moving from early stages towards maturity

As the platform expands and matures established high profile businesses such as Vodaphone, Marks and Spencer, and major supermarkets will also be targeted as sponsors. Similar to Rogers ‘Early Majority’; these businesses need solid proof of benefits but are comfortable with innovative ideas. They offer strong customer service and support which appeal to the ‘Early Majority’ consumers the platform will aim to bring on board at this stage. They will be encouraged to extend the user benefits with special offers, discounts and tokens similar to those offered by Tesco Clubcard Rewards and Airline Miles Reward Programs. Such inducements are targeted to the increasingly wide user base.

Maturity

Britizen will continue to generate revenue from sponsors and advertisers as the platform matures and the number of users increases. As the platform develops a track record and large user base revenue will increase; allowing an increased amount to be spent on benefits attracting and retaining users as well as funding increased growth.

Evidence that the platform is successful is also a sound basis to franchise or license the Britizen concept to other governments. These governments may use the platform to encourage similar or different behaviours appropriate to their culture and situation.

Consumer data will be increasingly valuable as both the number of users and quantity of longitudinal data increases. As well as providing a rich source of data for government analysis; there is potential to sell anonymised date to universities and other research organisations. It is important that users build and retain trust in Britizen; such data sales need to be handled sensitively.

 

References

Kaplan, R.S., Norton, D.P., 2000. Having Trouble with Your Strategy? Then Map It [WWW Document]. Harv. Bus. Rev. URL https://hbr.org/2000/09/having-trouble-with-your-strategy-then-map-it (accessed 4.13.17).

Rogers, E.M., 1983. Diffusion of Innovations, 3rd ed. Collier Macmillan, New York.

Shuen, A., 2008. Web 2.0: A strategy guide. O’Reilly Media Inc., Sevastopol, CA.