I dig this. And it looks like a couple of rings I already wear. Sign me up!
laughingsquid:

Arcus Motion Analyzer, A Ring-Sized Activity Tracker That Recognizes Gestures

I dig this. And it looks like a couple of rings I already wear. Sign me up!

laughingsquid:

Arcus Motion Analyzer, A Ring-Sized Activity Tracker That Recognizes Gestures

Cite Arrow reblogged from laughingsquid
fastcodesign:

Test participants who had used Facebook for 20 minutes reported being in a worse mood than those in two other test groups (one browsed the Internet, one served as a control and did nothing); the Facebook participants also felt their time had been used in a less meaningful way. 
Now go share this on Facebook.

fastcodesign:

Test participants who had used Facebook for 20 minutes reported being in a worse mood than those in two other test groups (one browsed the Internet, one served as a control and did nothing); the Facebook participants also felt their time had been used in a less meaningful way. 

Now go share this on Facebook.

Cite Arrow reblogged from fastcompany
hautepop:

New from @robertjparkin over on our FACE work blog:
How To Detect Communities Using Social Network Analysis
In it, Rob explains the network diagram pictured above:

Let’s start by revisiting the ego network from my Facebook graph that we investigated in the previous blog.
Here nodes are portioned by modularity, with each node belonging to a separate cluster or community, and coloured accordingly. For many of the separate and very distinct clusters on the edges of the network, it shouldn’t come as a surprise that these people belong to their own community.
What is interesting is within the main component, where without the colour coding it’s hard to see any clearly divided partitions. But now we now have four different communities (blue, brown, purple & maroon-ish). So the question is, are these 4 different groups just statistical figments of the network structure? Or do they relate to anything real about the relationships between the people involved?
The blue community is made up of people I met at school, all around my age (17% of the network).
The brown community is people I went to school with, but also lived close to where I grew up (9% of the network).
The maroon community also went to school with me, but all at least a year older that me (7% of the network).
The purple community is people I attended college with directly after finishing school (also 17% of the network).
This is a great example of how we can segment individuals by very subtle differences, simply by analyzing the structure of the connections they share.
But how could a network “know” these things about my friends? Well, it’s all based on the connections they have with each other. People who were in the same yeargroup at school are more likely to know each other, and therefore be friends on Facebook – so that’s what connects the real world to the network relationship.

This got me thinking more about brands and communities:
A community is most often defined as a group of individuals living in the same geographical location. It can also be used to describe a group of people with a shared characteristic or common interest: the research community, for example. Within the social sciences, communities are often understood as something socially and symbolically constructed - for example, the “imagined community” of the nation state (Benedict Anderson, 1983).
Using social networks analysis we define communities differently – by looking at how people are connected to each other through who follows whom, or who retweets whom - and clustering these into similar groups. So it is a statistical measure of connectedness, and it’s not based directly on whether these people would recognize themselves as being part of the same community.
However, what’s so fascinating about networked community detection is that the communities it identifies very often DO have significant real-world meaning - as demonstrated by Rob’s analysis of his Facebook friends - and can help us explore what it is that joins a community together.
At FACE we’ve done a number of network analysis projects, sometimes for PR (especially with Twitter), but also for internal use, helping brands understand the audience they’re talking to on Twitter.
What I’d like to see is more companies going public on their network analysis, illustrating their audiences back to their followers.
In part because it’s important to give back to the commons, the shared value that we all create through posting on Twitter. Twitter legally own this data, and there’s a fairly well-recognised value exchange in that users essentially sell the information value of their content in exchange for getting Twitter free. And speaking for myself, I certainly get a vast amount of value from using Twitter.
However, one thing we might say distinguishes a real community from just any old group of people is that relationships exist beyond the purely economic. There’s some degree of trust, and a greater degree to do favours. It’s called prosocial behaviour, and it stems from altruism rather than an expectation of immediate return. People give to their community.
Brands need to think more about how they can give to their communities. They get a lot of value from having communities - loyal purchasers and word-of-mouth advocates. And one way they might give back is by sharing insights and visualisations and research, the kind of thing that individual people just can’t do, or create, or find out - but might like to know and see. Like an understanding of the shape & dynamics of the community they’re part of.
Ideally I’d like to see a LOT more open research.
I just did a social media study on the different types of sustainability that the client is talking about sharing & publishing in this way, and that’s really exciting. Of course some research can’t be shared publicly because it’s strategically sensitive - but social media research, built on the commons of open data APIs, doesn’t tend to be so. So why not publish it, and give back insights and learning to the community who generated it?
The second reason to publicly share community visualisations is because, as we said, community isn’t just about shared interests but a shared imaginary, a shared recognition that “We are part of the same group.”
Sharing social network visualisations - illustrating that group as an entity, a multicoloured digital jellyfish - could be one tool for a brand to make real “customer community” beyond the jargon of a thousand Powerpoint decks. The visualisation illustrates the audience as a whole, makes it seeable, thinkable, comprehensible as a unit. It helps people see themselves as part of something bigger.
This happens already - the nod of recognition when you see someone with the same bike or dress as you. It’s a recognition that you have something in common, as expressed by your purchasing choices. (This may or may not be something you feel is a good thing, but that critique is another blog post.)
So what a social network visualisation may do, in a little way, is actually create community. It’s able to help a brand move beyond a 1-to-1 individualised relationship with buyers, towards something bigger and more powerful - positioning their brand as a source of cultural meaning and social value.

hautepop:

New from @robertjparkin over on our FACE work blog:

How To Detect Communities Using Social Network Analysis

In it, Rob explains the network diagram pictured above:

Let’s start by revisiting the ego network from my Facebook graph that we investigated in the previous blog.

Here nodes are portioned by modularity, with each node belonging to a separate cluster or community, and coloured accordingly. For many of the separate and very distinct clusters on the edges of the network, it shouldn’t come as a surprise that these people belong to their own community.

What is interesting is within the main component, where without the colour coding it’s hard to see any clearly divided partitions. But now we now have four different communities (blue, brown, purple & maroon-ish). So the question is, are these 4 different groups just statistical figments of the network structure? Or do they relate to anything real about the relationships between the people involved?

  • The blue community is made up of people I met at school, all around my age (17% of the network).
  • The brown community is people I went to school with, but also lived close to where I grew up (9% of the network).
  • The maroon community also went to school with me, but all at least a year older that me (7% of the network).
  • The purple community is people I attended college with directly after finishing school (also 17% of the network).

This is a great example of how we can segment individuals by very subtle differences, simply by analyzing the structure of the connections they share.

But how could a network “know” these things about my friends? Well, it’s all based on the connections they have with each other. People who were in the same yeargroup at school are more likely to know each other, and therefore be friends on Facebook – so that’s what connects the real world to the network relationship.

This got me thinking more about brands and communities:

A community is most often defined as a group of individuals living in the same geographical location. It can also be used to describe a group of people with a shared characteristic or common interest: the research community, for example. Within the social sciences, communities are often understood as something socially and symbolically constructed - for example, the “imagined community” of the nation state (Benedict Anderson, 1983).

Using social networks analysis we define communities differently – by looking at how people are connected to each other through who follows whom, or who retweets whom - and clustering these into similar groups. So it is a statistical measure of connectedness, and it’s not based directly on whether these people would recognize themselves as being part of the same community.

However, what’s so fascinating about networked community detection is that the communities it identifies very often DO have significant real-world meaning - as demonstrated by Rob’s analysis of his Facebook friends - and can help us explore what it is that joins a community together.

At FACE we’ve done a number of network analysis projects, sometimes for PR (especially with Twitter), but also for internal use, helping brands understand the audience they’re talking to on Twitter.

What I’d like to see is more companies going public on their network analysis, illustrating their audiences back to their followers.

In part because it’s important to give back to the commons, the shared value that we all create through posting on Twitter. Twitter legally own this data, and there’s a fairly well-recognised value exchange in that users essentially sell the information value of their content in exchange for getting Twitter free. And speaking for myself, I certainly get a vast amount of value from using Twitter.

However, one thing we might say distinguishes a real community from just any old group of people is that relationships exist beyond the purely economic. There’s some degree of trust, and a greater degree to do favours. It’s called prosocial behaviour, and it stems from altruism rather than an expectation of immediate return. People give to their community.

Brands need to think more about how they can give to their communities. They get a lot of value from having communities - loyal purchasers and word-of-mouth advocates. And one way they might give back is by sharing insights and visualisations and research, the kind of thing that individual people just can’t do, or create, or find out - but might like to know and see. Like an understanding of the shape & dynamics of the community they’re part of.

Ideally I’d like to see a LOT more open research.

I just did a social media study on the different types of sustainability that the client is talking about sharing & publishing in this way, and that’s really exciting. Of course some research can’t be shared publicly because it’s strategically sensitive - but social media research, built on the commons of open data APIs, doesn’t tend to be so. So why not publish it, and give back insights and learning to the community who generated it?

The second reason to publicly share community visualisations is because, as we said, community isn’t just about shared interests but a shared imaginary, a shared recognition that “We are part of the same group.”

Sharing social network visualisations - illustrating that group as an entity, a multicoloured digital jellyfish - could be one tool for a brand to make real “customer community” beyond the jargon of a thousand Powerpoint decks. The visualisation illustrates the audience as a whole, makes it seeable, thinkable, comprehensible as a unit. It helps people see themselves as part of something bigger.

This happens already - the nod of recognition when you see someone with the same bike or dress as you. It’s a recognition that you have something in common, as expressed by your purchasing choices. (This may or may not be something you feel is a good thing, but that critique is another blog post.)

So what a social network visualisation may do, in a little way, is actually create community. It’s able to help a brand move beyond a 1-to-1 individualised relationship with buyers, towards something bigger and more powerful - positioning their brand as a source of cultural meaning and social value.

Cite Arrow reblogged from hautepop
If you look at Condé Nast, 10 years ago they were at the center of many conversations among the elite. Many people read The New Yorker, Vanity Fair, Vogue, Gourmet and more. Today they could disappear and nobody would miss them. It only took a decade.

Seth Godin

TechCrunch: It’s Never Been A Better Time To Create A Luxury Startup

(via davemorin)

Cite Arrow reblogged from davemorin
Why Juicy Went Sour

Fast Company writes about What Businesses Could Learn From The Fall Of Juicy Couture but while mentioning the sale to Fifth & Pacific to Authentic Brands Group, the piece appears to attribute the fall to a shift in consumer culture — a trending away from ostentatious and over to understated. 

While valid, I can’t help feeling that the fall of the brand was almost entirely due to way too aggressive growth by Fifth & Pacific (formerly Liz Claiborne) and then Authentic Brands for allowing the brand to become almost entirely disconnected from its founders, Gela Nash-Taylor and Pamela Skaist-Levy. 

And that’s where I think the real lesson for businesses lies. In an age of brand marketing that hinges on authenticity, trust, and storytelling (thanks in part to overwhelming choice), it’s no wonder consumers are often more likely to open their wallets to brands whose founders are still in the picture. 

Gela and Pam were part of the appeal of Juicy. Even if, like me, you couldn’t stand the sight of those matchy sweatsuits with JUICY emblazoned below what one could only imagine was a “tramp stamp” on the wearer, you couldn’t help but buy into the story of the increasingly glamorous life of its hard working founders. 

The pair of SoCal moms invested their own money in their company and barely a year went by that their beachside homes weren’t featured in C or InStyle. They were a PR machine onto themselves. Yet once the brand was sold, the soul and the story of the company was lost. There was nothing to PR anymore. Not much to care about. Store openings for the sake of store openings and endless line extensions don’t mean much without an underlying, well-told raison d’être.

Sure, shifts in taste and the times are valid. But for those in the big business of acquisition, I believe the fall of Juicy Couture came down to the disappearance of its story. 

So as the doors close, people are reassigned to new roles, and the mountains of fast-fashion fabrics are shipped out to deep discounters, we should shift our gaze back to the sparkling shores of Southern California, and wish good luck to the founders on the rise of their new venture, Pam & Gela.

IKEA “Wakes Up” to Behavioral Insights, Cements Itself as a Lifestyle Brand

I am (for shame) one of the 24% of New Yorkers that hits the snooze button more than once, according to a new report by IKEA. The furniture company’s ‘A World Wake Up’ report  tracks the habits of people in major cities from New York to Shanghai. 

Not only is the infinite scroll UI quite beautiful (like Pew’s Next America report, I love the GIFs in the city ledes), the site is full of domestic ritual data and quotes, which is entirely ownable for a brand like IKEA — a company that describes itself as “a values-driven company with a passion for life at home. Every product we create is our idea for making home a better place. At the IKEA Group, we have 298 stores in 26 countries.”

As you dig into the data, there are some solid insights, like this one from the New York “Play Into the Day” section: 

"Wanting to play more, especially with one’s children, is a pattern which repeats itself in all cities. We want to have more play time, and feel it is of utmost importance, but we rarely give ourselves the time to have this fun with our near and dear. Mornings are the time of day when we’re often urged to prepare for the day in an orderly fashion. But what if we’ve got our priorities wrong? 

Using time logs, writer Laura Vanderkam has made priorities in her research a priority, and dug into the mystery of mastering a so-called work-life balance. She found that writing down what you spend time on is a golden way of actually finding more time by rescheduling and daring to miss out on other activities or duties that you thought you needed to do. She has changed her language and encourages others to do the same. Instead of saying “I don’t have time”, she now simply pronounces “It’s not a priority”.

What I like about this site and the study is that you can’t hear the marketer’s drumbeat of ROI and sales conversion banging through the content.

This is a story of IKEA, the lifestyle brand — and a company that takes studying their customer’s lifestyles seriously. Perhaps this is a sign of Leontyne Green Skyes’ (newish hire as CMO, IKEA North America) promise to hire a strategic insight manager

As more retailers and brands have access to data, it’s interesting to see them doing something creative with it, outwardly and hopefully internally, too. Will these insights inform product development? In IKEA’s case, I have to think it does. Mainly because this site calibrates my belief that IKEA makes things with people in mind. 

womensweardaily:

Gilt Partners With ‘Orange is the New Black’
Courtesy Photo
Gilt partnered up with Dress for Success and the Netflix series “Orange is the New Black” on a special sale that will correlate to the second episode of the show’s second season. For More

womensweardaily:

Gilt Partners With ‘Orange is the New Black’

Courtesy Photo

Gilt partnered up with Dress for Success and the Netflix series “Orange is the New Black” on a special sale that will correlate to the second episode of the show’s second season. For More

Cite Arrow reblogged from womensweardaily
What happened to trust? An interesting dataset based from the question, “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people?”
via nevver:

Red = Cannot, Most people can be trusted 1972-2012

What happened to trust? An interesting dataset based from the question, “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people?”

via nevver:

Red = Cannot, Most people can be trusted 1972-2012

Cite Arrow reblogged from nevver