Anticipative demand and consumer intent prediction

Social economic networks improve the value proposition for both individual and institutional consumers since products and services can be discovered and targeted with greater relevancy.

Rich attribute information posted publicly by social media users (individual and institutional) can be used by marketers and other interested parties (for example, potential employees) to infer the values, preferences, and interests of others. In response, hyper-personalized advertisements may be presented (Reference: Shih, The Facebook Era, 2009).

Hyper-targeted-marketing, recommendations, and authentic product endorsements from friends are some of the ways that social economic networks have improved commerce relevancy.

The next obvious step would be for vendors to predict demand before it occurs, responding to customer intention.

Intention prediction could be accomplished by merging aggregate Facebook or other social media ‘likes’ and comments from high-influence users into purchase intent well before sales transactions. An anticipative demand market could arise.

Traditional economics equations could be further transformed as vendors test large varieties of targeted offerings in cost-effective ways via the internet.

The long-tail of supply and demand could meet in millions of micro-markets, possibly even at the level of individual pricing and individual offerings. Smaller lot sizes means higher margin. There are numerous entrepreneurial opportunities in facilitating product and service generation, production, and distribution at the level of n=1.

Social currency unlocks value for individuals and organizations

Social currency, shared information which encourages further social encounters, is transacted through social economic networks.

From an economic perspective, the role of social economic networks is to unlock and monetize hidden value. This value is mainly in the form of information asymmetry as buyers and sellers hold information that is useful to each other. Both buyer and seller realize greater utility than if the social economic network did not exist.

Social economic networks are impacting both individuals and organizations at the global and local level. Transactions may be between anonymous parties or parties who know each other. For example, in the Groupon / Peixe Urbano group-purchasing model, individuals pre-commit to a purchase to obtain a discount if a minimum number of people participate.

With social economic networks, organizations can unlock intellectual capital (social business intelligence) in ways that were not possible before with tools such as prediction markets (a mechanism for collecting and aggregating opinion using market principles). The concepts are attractive on a global level and can be implemented on a local level with the democratizing power of the internet.

Social economic networks could likely grow in the next several years, particularly in the type of assets created, and in the venues and models for their exchange.

Social economic networks and the new intangibles

Social economic networks are helping to monetize the new intangibles that arise from alternative currencies such as intention, attention, time, ideas, creativity, and health data. Individuals are starting to realize that they have more assets that have economic value besides labor; multiple currencies that are starting to become monetizable.

The new currencies have new measurement metrics for monetization such as awareness, influence, authenticity, reach, action, engagement, impact, spread, connectedness, velocity, participation, shared values, and presence. As market principles become the norm for intangible resource allocation and exchange, all market agents are starting to have a more intuitive and pervasive concept of exchange and reciprocity.

Reputation has always been an important intangible asset, and was one of the first alternative currencies cited; however it was not really monetizable other than as an attribute of labor capital. Now, there are more alternative currencies, such as social currency, that are directly monetizable through social economic networks.

Real value and real assets are being created in social economic networks. For example, products and services have higher value when they are recommended. An information asset that has been generated, largely through crowd-sourced labor, is product and service recommendations. Some examples of these information resources that facilitate shopping include Amazon reviews, Yelp local business recommendations, social shopping sites (e.g.; Kaboodle, Polyvore, StyleHive, ThisNext), and product attribute discovery and dialogue sites (e.g.; Stickybits, ClickZ).

Long-tail economics extended to physical objects

Chris Anderson, editor of WIRED magazine, gave an excellent talk on August 5, 2010 at the PARC Forum. He explained how the long-tail economic models which have driven digital content (allowing consumers to access books, music, and movies in the 80% of the market that is not blockbusters) are now starting to appear in the world of physical goods.

The process of realizing long-tail economics in any sector is that of going one-to-many; democratizing the tools of creation, then the tools of production, and finally the tools of distribution. This is what happened with internet content such as publishing, where it is now easy for anyone to create, produce, and distribute content with blogs, twitter feeds, YouTube, etc. This has also happened with other digital content and some physical goods that are ordered and distributed via internet models (e.g.; Amazon, Zappos, etc.).

The new industrial revolution, argues Anderson, is in opensource hardware factories. The supply chain has now opened up to the digital and the small. The ability to make and distribute anything massively decentralizes traditional manufacturing and could completely reorganize industrial economies…atoms are the new bits. Matthew Sobol’s holons (communities of local resilience and sustainability) are in the works. Goods can be self-designed or crafted from available digital designs (e.g.; communities like ShapeWays and Ponoko), and then printed locally on the MakerBot or ordered from Alibaba or other global manufacturies. Opensource manufacturing is starting to have an impact on industries like auto design and construction (e.g.; Local Motors), drones (e.g.; DIY Drones), and general hardware design (empowered by the Beagle Board and Arduino).

It is likely that long-tail economics can be applied to many other areas. Medicine is the next obvious example, where health care, health maintenance, drug development, and disease treatment are already starting to shift into n=1 or n=small group tiers of greater customization and ideally, lower cost as more precision is obtained in the measuring and understanding of disease and wellness.

The real-time economy

The encephalization of the earth (the coming together of human minds in a variety of higher resolution formats) is picking up speed. More and more people have a pass to join the information highway – Honest Signals points out that ten years ago, less than half the world’s population had made a phone call, but today, 70% of the world’s population has access to a phone for calls and texting.

Numerous collective intelligence tools have been emerging to uplevel and structure the context and quality of human interaction. The Wikipedia is the quintessential collective intelligence tool, as are wikis generally, social networks, buzzing and tweeting status updates, collaboration websites, question networks, social purchasing networks, and prediction markets.

The real-time economy
The pulse of activity from collective intelligence tools can be measured in many ways, and is importantly surfacing as a leading indicator for the real-time economy. Prediction markets and social purchasing networks could supplant traditional mechanisms for identifying economic activity and shifts.

For example, there were a number of ways to watch the real-time status of this week’s long-awaited launch of Starcraft II: Wings of Liberty (Blizzard Entertainment’s latest release in one of the highest grossing video game franchises of all time). The usual tweet stream and buzz feed provided an instant indication of activity. The next highest level was the Blippy feed of real-time purchases. Third, of greatest salience was the SimExchange video game prediction market which provided the highest resolution aggregation of opinion, and was early in calling the sales disappointment during the game's pre-launch and launch (Figures 1-2).

Figure 1: Starcraft II: Wings of Liberty, 7/28/10 (release day) (Source)

Figure 2: Starcraft II: Wings of Liberty, 7/31/10 (Source)

The next obvious step is predicting economic activity even earlier, merging aggregate Facebook likes with social network high-influencer opinions into purchase intent well before sales transactions, in fact, using the encephalization ether for market demand identification and product development.

Citizen scientists innovate research model

It is clear that quantified self-tracking, preventive medicine, and community-based research conducted by citizen scientists could be a huge new industry. The coming era of very large data sets and continuously collected information with algorithmic tools for signal-to-noise interpretation could significantly shift how the baseline measures of health are defined and managed. Citizen science is re-innovating the model for conducting science at every level.

In the traditional research model (Figure 1), there is a principal investigator at an institution, conducting research on subjects, under the purview of an Institutional Review Board, supported by grant funding and publishing results in journals.

Figure 1. Traditional Science Research Model

(source: DIYgenomics - an open platform for citizen science research)

The citizen science model (Figure 2) is different as there is no distinction between investigator and subject, everyone is an investigator and participant; therefore the analog to the IRB is different, perhaps there are citizen ethicists, or a list of FAQs. Funding could come from patient advocacy groups, innovative research foundations, social venture capital, and crowd-sourcing; and research results could be self-published on the web.

Figure 2. Citizen Science Research Model
(source: DIYgenomics - an open platform for citizen science research)

Blood tests 2.0: finger-stick and microneedle array

The farther future could include smartpatches - non-invasive, invisible, continuously-worn health self-monitoring skin patches. In the nearer future, a killer app for synthetic biology and other new chemistry and biology 2.0 methods could be the ability to create one's own vitamin supplements, and possibly innovate low-cost, non-prescription based finger-stick blood tests, and saliva and urine panels for self-testing.

Barrier to Citizen Science
A significant barrier to the wide-scale adoption of citizen science in the context of health self-management, intervention exploration, and preventive medicine implementation is the high cost, inconvenience and discomfort involved in obtaining traditional lab tests. While many tests may be ordered in a direct-to-consumer fashion through DirectLabs, the Life Extension Foundation, and other websites, it still costs ~$100 per test.

The challenge is to identify the requisite chemistry and processes involved and see if it may be possible to make simple consumer-friendly finger-stick blood test cartridges, similar to the glucose and HDL measurement kits sold at drug stores, which self-experimenters may perform at home or at community biolabs. Continuous monitoring via microneedle arrays would be useful for self-tracking glucose levels and other markers. For example, there could be consumer-targeted versions of the devices being developed by Orsense.

Figure 1. Non-invasive glucose monitoring device from Orsense

Community labs and high-end home labs may include the (CLIA-waived) Cholestech LDX machine (~$2,000 for the machine + ~$5-10 per measurement cassette) which can assess eight different lipid profiles.

Figure 2. Cholestech LDX finger-stick lipid measurement device

There is an urgent opportunity to expand the range of finger-stick measurement tests. Below is a Wish List of basic tests for one-off or comprehensive panel delivery.

Traditional Blood markers:

• Homocysteine
• Vitamin B-12
• Folate
• Vitamin D
• Creatinine
• eGFR
• Cortisol
• Calcium
• Iron
• Aldosterone

Hormones

• Estrogen
• Progesterone
• Testosterone
• Estradiol

Ethics of historical revivification

Thought experiment: Assuming a world or worlds without basic resource constraints, if technologically possible, would it be more humane or less human humane to revive dead persons from history? Even those recently dead could be out of sync with the current milieu. Obviously, there would need to be rehab programs as contemplated in science fiction, for example,

"Life 101: Introducing Genghis Khan to the iPhone"

If is arguable that some large percent of dead persons would find enjoyment and utility in revivification.

The interpretation of the core rights of the individual could be different in the future. “Life, liberty, and the pursuit of happiness” seems immutable, even when considered in the possible farther future context of many worlds, uploaded mindfiles, and human/AI hybrid intelligences. However, how these principles are applied in practice could seem strange from different historical viewpoints.

Attributes that might be important to an individual now, for example embodiment or corporeality (being physically instantiated in a body), could well be moot in the future. On-demand instantiation could be a norm to complement digital mindfiles.

It could be queried whether revived historical persons should have the option to re-die? Dying and suicide could be much different conceptually in a digital upload culture. Choosing not to run your mindfile could be legal, but deleting it (and all backups) could be the equivalent of suicide, which is generally illegal in contemporary society.

Automated nourishment

An interesting question arose from discussions at the recent IFTF annual forecast presentation - Would people be more or less healthy in a possible future era of 3-D food-printing on-demand?

Both sides of the case can be seen. The immediate conclusion might be that if anyone could print any food item on-demand any time, people would over-consume and be less healthy.

However, one of the biggest mistakes that can occur when considering a potential future advance is thinking of it in isolation and not bringing forward all other aspects of technology and society to this point too. In an era with on-demand 3-D food printing, other changes are also likely to have occurred. The first and most obvious is that perhaps food content or accompanying supplements, drugs, and nutraceuticals have changed to mean that food that tastes good is not necessarily unhealthy, even when consumed in large quantities. Non-fat non-sugar substitutes may have become seamless matches in the quality of taste but not in caloric consumption. Today’s unhealthy foods could go the way of cigarettes. Automated calorie consumption data collection might finally be possible.

A second argument for why people would be more rather than less healthy in an era of on-demand 3-D food printing is the massively granular physical tracking and biofeedback tools that could exist for each person. Smarthouse and smartclothing data collection through scanning and air, toilet, and unnoticeable blood stick diagnostics could be inputs to a continuously updating personal digital health model (e.g.; the future analog to Entelos's virtual patient or Archimedes's virtual twin). A personal digital health model could be used to assess exactly which real-time nutritional adjustments are needed by an individual. An automated menu plan from the kitchen printer may be preferable for creating meals based on an individual’s known preferences and reactions together with real-time needs. The portable personal digital health model could be permissioned into restaurant settings to similarly allow for customized meal synthesis.

A third argument comes from considering the potential trajectories of social networking and behavior change research. Already peer social networks have a strong influence on individual behavior. One’s whole peer network or interest group could be encouraging healthy behavior via team-based support and/or competition. The advent and widespread adoption of self-tracking and social interaction tools could bring about a new sensibility and personal responsibility for health self-management. Optional financial incentives from insurance companies could further facilitate behavior change.

Conclusion
In any possible future, there could be different technologies and social behavioral norms influencing the process of human nourishment. Food could become healthier over time and unobtrusive self-tracking tools and financial incentives could shift people to automated menu plans. Healthier behavior could be triggered just by making it easy.

Questions uplevel the web

A new internet trend has popped up – asking questions to friends and strangers. Questions are a light-weight means of bringing structure and context to social interaction.

Many people start off with a low level of engagement (e.g.; what is the best pizza place in your neighborhood?). Things can start scaling up (e.g.; how much does it cost for a family to live in London on average?) and become quite detailed (e.g.; can a publisher see the average CPC or eCPM of a particular ad or advertiser on AdSense?). More importantly, more complex thoughts, opinion, philosophy, and value systems are being elicited (e.g.; what is a good real-world example of the "prisoner's dilemma" in recent history?).

The question-asking trend began with Hunch asking users questions to draw a taste profile map for users. The current generation of the concept features sites like Quora and formspring where users ask each other questions. Users have profiles and friending/following capability, with their questions and answer activity appearing in a status feed. It is like a friend network with topic precision.

Metrics would be interesting, such as the level of semantic complexity of questions, the number of repeated questions (an indicator of what is on the collective mind), and the ratio of asked to answered questions.

Question networks could be the real start of the semantic web, the natural automated approach (akin to Google’s automated machine learning) for creating the next higher level of information density.