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NewImageA recent study of buying behavior based on FaceBook-based marketing is a clear demonstration of the psychology of persuasion, specifically social proof. In Robert Cialdini’s seminal work, Influence: The Psychology of Persuasion, he notes the importance that social proof (one of the six pillars of influence) playing in a decision process. This first of a kind study now gives credence, albeit small, that social tools have a measurable impact on buying.

Last year, ComScore profiled the average spend at Target stores across the general population, compared to the average spend from Facebook fans and friends of fans. The research determined that fans of Target on Facebook were 97% more likely to spend at Target, and friends of fans were 51% more likely than the average population to spend at the retailer (the brand has over 18 million “likes”).

NewImageA corresponding study from March used a test and control methodology that aimed to quantify incremental purchase behavior that could be attributed to social media exposure. Research showed that fans who were exposed to Target’s messaging versus fans who weren’t exposed were 19% more likely to buy at Target. Friends of fans who were exposed to the retailer’s messaging were 27% more likely to buy at Target than those not exposed.

While both studies clearly demonstrate the social proof is playing an important, measurable roll, the second study is significant. It demonstrates that indirect influence, if properly triggered, can be a causation for buying. This is the kind of study that platform developers have been searching for, ones that enable measurable social commerce. But this should not come as a surprise to anybody who has studied Cialdini’s work, as it is only one more field study supporting the cause.


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NewImageA colleague asked me to comment on a recent article “Are you ‘network literate?,” by Ben Casnocha. The author notes that the information you know “will determine whether you win or lose.” Very true.

Information is changing too quickly (velocity), is to expansive (volume), and too diverse (variety) to make it possible for any one person to have a reasonable chance of remembering/recalling enough to be singularly useful in complex decision making.  As such, Casnocha notes that to address this issue:

– You need to know your network.
– You need to who in your network knows what.
– You need to know how to ask questions that elicit helpful information.
In essence,  the ability to solve problems and make effective decisions is proportional to the amount of knowledge in your network:
Accessible Knowledge (AK) is proportional to number of networks you have x people/network x question/person x knowledge/question. 
A very powerful equation.
NewImageBut, while I agree with these points, Casnocha does not give concrete examples on how to use modern technology/social tools to realize value from them. For example, LinkedIn is THE network tool used by professional to source a network. Right? FaceBook tends to be used for personal and some professional network sourcing, but does not provide any real relationship information (connections like in LinkedIn).
Casnocha also does not identify what tools can be used to identify who in your network knows what. In LinkedIn, people can use their deductive reasoning to learn a lot about what a person has done as a means of knowing what they know.  Are there tools that can do this? But even if there are, it is almost impossible to infer what people are truly capable of answering through inductive reasoning, which is a more important capability in effective decision making. This is a real gap in current social platforms.
In terms of how to ask questions, this is always an issue. English is a very ambiguous language and its interpretation is highly dependent on the educational level of the sender and receiver. Couple that with the highly unstructured nature of written content in social media and you open yourself to a lot of variance in results of knowledge calculus.
To more effectively manage and leverage Accessible Knowledge, social tools like LinkeIn need to start mining not only the connections, but the relative knowledge as well. It is only then that the artificial social networks, that are pervasively replacing our real ones, will become useful enough to support the fine grained decision making necessary for today’s complex problems.

My colleague noted that the AK lack consideration of critical thinking or maybe it was my analysis that lacked critical thinking. Hum. Oh well, let’s assume it was the former and that he is absolutely right. People today have lost this critical ability. I even find myself now and then forgetting to think before I act.

Extending and revising the original thought, here how I would interpret it:

AK = Kp(t) xTct [number of networks you have x people/network x question/person x knowledge/question]

Tct is the critical thinking transformation function
Kp is an efficiency factor dependent on the person and a point in time

That is, the sum total knowledge of your networks is transformed through the critical thinking process, which is spatially dependent on the individual and temporally dependent on when (mode, season, day/night, etc.) the thinking takes place.

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NewImageI thought I’d share this email observation I made earlier today about how Big Data seems to be quadricating into these orthogonal fields:

1. Data (the intrinsic 1/0 property of big data) which can be broken down subjective areas like interaction data, transaction data || structured, unstructured || realtime/streaming, batch/static || etc.

2. MapReduce platforms – AKA divide and conquer – virtual integration capabilities that enable aggregation and management of multiple name-spaced data sources (Hadoop, InfoSphere Streams, Pneuron, etc.)

3. Data Exploration, Data Mining, and Intelligence Platforms – technical capabilities that  enable one to derive insights from data (Pentaho, IBM InfoSphere, ListenLogic, MatLab, Mathematics, Statistica, etc.).

4. Knowledge Worker platform (AKA The human component) – The two most important capabilities come from data scientists (navigate through data) and  behavioral scientists (navigate through human behavior, which most important things seem to connect back to).

In essence, Big Data has data, an ability to find it and use it, and an ability to explore and learn from it.

Does this seem right?  Missing anything? Please post or email me.

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NewImageEvery company should have a plan for dealing with the exponential growth in their data. That is, they need a Big Data Strategy. While the term, Big Data, has been thrown around a lot in both business and technical publications, very few stop to define it in such a way that make it a useful and actionable business concept.

Big data is characterized by the dramatic growth in the volume of data (internally generated and from external sources) available to businesses. It is a characteristic of a companies IP generating capability and presents new opportunities for companies to grow revenues through better customer (AKA data) insights. Data growth have been around since the beginning of time, but has become a challenge given the recent improvement in integration, adoption of the cloud, and leveraging of social networks.

There are some very powerful and somewhat overwhelming statistics driving the big data discussion that should make business stop, listen, and think:

– $600 to buy a disk drive that can store all of the world’s musicNewImage

– 5 billion mobile phones in use in 2010

– 30 billion pieces of content shared on Facebook every month

– 40%projected growth in global data generated

– 235 terabytes data collected by the US Library of Congress by April 2011

– 15 out of 17 sectors in the United States have more data stored per company than the US Library of Congress

– $300 billion potential annual value to US health care—more than double the total annual health care spending in Spain

– €250 billion potential annual value to Europe’s public sector administration—more than GDP of Greece- $600 billion potential annual consumer surplus from using personal location data globally

– 60% potential increase in retailers’ operating margins possible with big data

– By 2018, the United States alone could face a shortage of 140,000–190,000 more deep analytical talent positions and 1.5 million more data-savvy managers. This alone is hugh!

NewImageMcKinsey Global Institute understands this issue quite well. In there “Big data: The next frontier for innovation, competition, and productivity” report, released May 2011, they identified five ways that Big Data could create value:

1. Big data can unlock significant value by making information transparent and usable at much higher frequency.

2. As organizations create and store more transactional data in digital form, they can collect more accurate and detailed performance information on everything from product inventories to sick days, and therefore expose variability and boost performance. Leading companies are using data collection and analysis to conduct controlled experiments to make better management decisions; others are using data for basic low-frequency forecasting to high-frequency nowcasting to adjust their business levers just in time.

3. Big data allows ever-narrower segmentation of customers and therefore much more precisely tailored products or services.

4. Sophisticated analytics can substantially improve decision-making.

5. Big data can be used to improve the development of the next generation of products and services. For instance, manufacturers are using data obtained from sensors embedded in products to create innovative after-sales service offerings such as proactive maintenance (preventive measures that take place before a failure occurs or is even noticed).

So, if you are into Big Data, then spend some time mining the MSI report. It is time well $pent.

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I don’t usually promote webinars, but I am going to make an exception. On December 9, HubSpot is putting on a free webinar called, ” The Science of Blogging.” The agenda looks interesting, especially if you are looking for quantitative reasons to start or continue your work.  71.4% of consumers say that blogs effect their purchasing decisions “somewhat” or “very much.” Seems interesting.

Here is their agenda and I will be blogging about it afterwards:

— A round of live blogging reviews (register for the webinar to get your blog reviewed)

— Tips about the best times and days to post

— Trigger words you can use to make your posts go viral

— How to get your posts shared on Twitter and Facebook

You can find registration information at their Registration Link.

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I have been asked to list a few of my top cloud computing standards, based on the recent eBiz post. My top four services:

1. Service Laye Standards (SaaS, PaaS, IaaS) – For example, Infrastructure as a Service standards would include a common means of identifying, creating, starting, and terminating infrastructure components (e.g., a server, storage, etc.).

2. Security Standards – Mostly a means through which independent verification and validation can be achieved. Yes, there are standards like SAS (Type 1/2), but they have been shown to be inadequate for todays cloud computing environment.

3. Interoperability Standards – between and within cloud computing providers

4. Disaster Recovery Standards – Common means through with an outage in one provider can be mitigated through another.

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I posted a blog discussing risks that are not often associated with global product engineering. In that article I specifically raise the issue of pandemic planning, given the recent outbreak of H1N1. Disaster Recovery magazine pick up on the same concept in their article “Four Practical Ways to Improve Your Pandemic Plan.”

While the article covers many aspects that I have discussed, it did bring together four key ideas:

>> Lesson 1: Employee absenteeism can be unpredictable, as employees won’t be affected uniformly.

>> Lesson 2: Employees paid close attention to how their companies handled the situation and turned to their employers for guidance.

>> Lesson 3: Companies that took measures to ensure their employees remained healthy at work are currently reaping the benefits of enhanced loyalty and productivity among employees.

>> Lesson 4: Companies often need medical consultation on how to handle different situations as they arise, but local Departments of Public Health (DPH) are likely to be overwhelmed and unable to provide that information in a timely manner.

H1N1 will be a disruptive event to domestic and international operations. Revisiting your approach to dealing this virus specifically, and pandemics in general, can save your company significant losses both in terms of product delays and resource productivity.

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