Microsoft launched a new Silverlight-powered Bing Maps experience into beta, which offered a myriad of new features including powerful visualisation that stitches together images contributed by users (yes, clients’ favourite “UGC”) into 3D photo collages, via their Photosynth technology.

Both Microsoft and Google are experimenting with a variety of tools that make hunting for locations far more immersive, and they’ve a new Application Gallery that enables developers to include their own information on a map. If they are able to open the platform up to more developers (and hopefully for the platform to come to our shores soon), we are then able to truly realise the vision of making maps more like a video game than an Atlas utility. Imaging a virtual walkthrough of places you have never been before (possibly an idea for tourism boards), leveraging on local insights for specific data ranging from tweets, blog posts, local lens, videos, and even real time vodcasts.

While we’re sure Bing will continue to open up the technology to developers and to further enhance its visualisation properties, one can only hope they also improve the loading speed (if only its available here and we have the New Generation Broadband to overcome this challenge), the usability with the influx of functionalities, and of course for a growing pool of hungry photography prosumers to contribute colour vibrant pictures for massive stitching.

Explore Bing Map now:

The social phenomenon is not a homogeneous one. Alot of us tend to focus on “social quick fixes” by extending social footprint into our communications strategies. However, there are  giants out there revolutionising their workspaces with social software that vow to innovate with viral adoption techniques,  providing communication, portal, content and general collaboration platform offerings. Bundled support for real time messaging and conferencing, document management, workflow and business process modeling/support continue to blur boundaries between social softwares and other workflow technologies.

The most common struggle in improving “connectedness” within organizations is in balancing risk and business value, as well as the empowerment of end-users promised by social environments. However, there are critical benefits including virtual collaborations, cross-border talent identification and expertise lending, informal network support to empower communities of experts and common interests, and accessing relevant knowledge needed to formulate plans.

As a start, here is a list of minimal functionality required when evaluating social softwares:

1.) Multiple-User Management - ability to create,  modify,  retire user accounts, as well as support for multiple roles including editor, facilitator, community manager etc.

2.) Project/Community Brainstorm Areas- ability to create themed common spaces for like-minded users to get together, and brainstorm virtually

3.) Document storage and sharing - an easy-to-use and automated organization function to upload, store and share files.

4.) Discussion forums - support for a conducive environment to have virtual discussion and the ability for moderation

5.) Blogs - instant publishing functions with comments function

6.) Wikis - Internal linking, word clouds, etc

7.) Ability to support & integrate multimedia from existing platforms such as YouTube etc.

8.) Enabling of social functionality & sharing for content such as social network analysis, social tagging, social bookmarking, social search, etc

9.) Keep a record of all tangible data via generic analytics; the software should ideally be compatible with the Big Boys like Omniture, Google, etc.

10.) Last but not least, the degree to which the vendor is investing in R&D to continue innovation the tool. Creative energy in committing to new browser-based technologies like Ajax and browser-based rich authoring/content recommendations will bring more traction to your investment.

As Jive says, business is now social. Enjoy~

http://www.youtube.com/watch?v=0Y6aceiLzCI

At the recent Young Guns International – MunHoe Tung one of XM’s creative leaders got his feelings back when he scooped up a bronze for his work on the HP Wake up your Feelings campaign.

Wouldn’t it be great if we can one day predict the brand of car our customers will buy when they are at their peak, what brand of cornflakes they would eat every Sunday morning, when they will watch another 2012/Independence Day-type movie, right down to what gender of baby they are likely to have when they marry? “Predicting the unpredictable, quantifying the unquantifiable”, says Dogbert the guru*.  But before we are able to fully achieve that in the twilight years, lets see how we can predict the future with the pre-historical method of predictive analytics, summarized in eight easy steps (inspired by Dogbert).

1.) Use a previous campaign or a test as your base.

Say for example you need a conversion of 1000 respondents, and the industry/benchmark average is 2%, then we probably need a base of 50,000 to achieve your target or do an adequate test.

2.) Add geographic, demographic, psychographic & behavioural data to your base

Both the responders and the non-responders. Who wants to be known as Segment A when we can be described more adequately and be given a nice personality.

3.) Know what are all the possible ways (and the most effective way) of reaching your base

We do have mobile phones and a life in the social space.

4.) Test and Control

Divide your data into at least 2 groups everytime, equally. Test group carries the hypothesis, control group validates.

5.) Trash the anomalies

Don’t you hate it when you thought one of your content pillar is doing extremely well in terms of average time spent and when you deep dive into the data you realise that it’s some idiot who left the computer on with your website in the browser running throughout the lonely night? Discard the outliers, be it purchase patterns or web patterns.

6.) Design your modeling framework

We will usually start out with a typical multiple regression model before we move on the the more sophisticated models like CHAID etc. “A regression is an equation that describes the relationship between a dependent variable and more than one independant variable”.  Statistical definition of dependant variable connotes the action/consequence that will be influenced by how you set up the test environment, and indenpendant variable as the components that will not be influenced (e.g. demographic, geographic, behavioural data).

7.) Grade and weigh each variable and develop an algorithm

This step will help you in shortlisting the most important variables that will influence your results (e.g. income, age, family size, etc). One will probably need a PHD in statistics and a SAS or SPSS software to run a regression model and weigh the different variables, and to finally develop an algorithm ranking the deciles.

8.) Score the validation group

If the predicted results derived from the algorithm is a close match to your previous campaign/test, then  the algorithm developed will be useful to predict future campaigns. It should also help you identify the target segment more likely to respond to your campaign through the scoring exercise.

If all else fails, hire a consultant to do the work while you make yourself another cuppa! (*highly recommended)

Last but not least, meet Dogbert, the data guru.

Wired.com heads to San Francisco’s Exploratorium to see four exhibits that explore the effects of visual illusions and perceptual phenomena.

An article on PC World: “3D TV, HTML5, video over Wi-Fi, superfast USB, and mobile “augmented reality” will emerge as breakthrough technologies in the next few years. Here’s a preview of what they do and how they work.” Read on.