Two of my favorite commercials recently are for minivans clearly targeted at new parents who don’t want to feel old just yet:

• Toyota’s Swagger Wagon
• Judas Priest sells Honda Odyssey

• Formal looking design is not always superior choice when trying to get people to reveal about themselves.
• Creating cues that make people feel a certain way and suggest the behavior you want from them can very much influence their actions (see Cialdini’s Influence for great examples)

Recent research suggests that we can be motivated by the notion of receiving feedback quickly after performing a task. Two Canadian researchers ran an experiment where students giving a presentation were told in advance when their work would be evaluated – a randomly assigned delay ranging from 0 – 17 days. The results?

“Students who were told they would receive feedback quickly on their performance earned higher grades than students who expected feedback at a later time. Furthermore, when students expected to receive their grades quickly, they predicted that their performance would be worse than students who were to receive feedback later. This pattern suggests that anticipating rapid feedback may improve performance because the threat of disappointment is more prominent.”

Potential implications?

• Consider setting the norm of giving your team members feedback immediately after important tasks, rather than waiting for weekly 1:1s or quarterly performance reviews.
• If stakes are suitably large (ie user needs to care about the outcome), tight feedback loops in consumer web experiences are desirable.

What do AC/DC and Canadian researchers have in common? Their investigation of testosterone. While the Aussies drew connection between large balls and throwing parties, three academics at University of British Columbia analyzed the role of testosterone in corporate mergers and acquisition behavior. 

The other day i had a brilliant flash of inspiration. It’s no longer about serial entrepreneurism, it’s about being a parallel entrepreneur. What a brilliant turn of phrase to explain the activities of friends like Shervin Pishevar who build companies, advise world leaders, inspire students and raise a family.

Googled the term and found i was late to the party. The #1 result for “parallel entrepreneur” is a 2006 blog post by Fred Wilson. I guess this means i’m as insightful in 2010 as Fred Wilson was in 2006. Hmm, four years late although compared to Fred’s proclivity for early insights, i might still be ahead of the curve.

In re-reading his post, there are some great quotes re: Evan Williams/Odeo and Kevin Rose which in retrospect suggest true largescale parallel entrepreneurism is a challenge.

Ev talk about Obvious Labs being a place where they will spin off projects. Fred notes how they’re able to work on projects like Odeo and Twitter at the same time.

Similarly, the post recounts speculation how Kevin Rose is going to build Revision3 while still running Digg.

So looking at those two examples, we might draw two conclusions about parallel entrepreneurism:
1. In the Obvious Labs case, when you’ve got a project of meaning, it often requires you to forget the dreams of multitasking and do one thing really well.
2. In the Kevin Rose case (and i don’t know him at all), he was able to build Revision3 but was it at the expense of Digg? If he’d remained CEO of Digg would it be something even greater today instead of the challenges they currently face?

Fun article on guys entering runs aimed at women: 


“Ahead of its Oct. 2 inaugural half marathon, Run Like a Diva announced that finishers’ medals will be awarded by bare-chested male firefighters. “We had four men signed up, but two dropped out when they heard about the firemen,” says Mr. Pozo, the race organizer. “We’re making this race so girly that men won’t want any part of it.””

YouTube’s hyperactive six year old Fred just drew 7.6 millions viewers for a TV movie on Nickelodeon, making him the #1 tv movie for kids 2-11 this year. Some people were surprised. Like duh. He’s been drawing millions and millions of viewers on YouTube for the past several years.

The world of the VideoOS, where i can get all my content on any device at any time, is going to need terminology changes in order to stay relevant. New content creators, new formats, new devices will make words like “tv show” less relevant. When Fred’s next episode is seen by 10 million viewers – 5 million on GoogleTV, 4 million on a laptop and 1 million on mobile phones – what do you call it? A webisode? A tv show? Doesn’t matter. What you call it is “AUDIENCE” and this increasingly is going to be what advertisers target independent of delivery hardware. The business model will follow the content to the viewer.

The future of video is user-centric, IP-delivered content. That’s a fancy way of saying you’re going to be able to get the content you want on any device. For YouTube this means the transformation from being a “video website” to what i think about as the Video Operating System. The VideoOS will be about the ability for anyone to broadcast themselves to millions of worldwide users across laptops, tablets, phones and living rooms. The world has never had a single TV station available where anyone can access any piece of content. 

On the heels of my TechCrunch post on why Foursquare users check in off the grid, HuffPo intern Jake Bialer turned me on to some work being done at Carnegie Mellon about mobile social services. From CMU Associate Professor Jason Hong:


1) Rethinking Location Sharing: Exploring the Implications of Social-Driven vs. Purpose-Driven Location Sharing
// Compares Purpose-Driven Location Sharing (eg to coordinate plans) vs Social-Driven (sharing because it’s fun, not because others need to know).
// “social-driven location sharing favored semantic location names, blurring of location information, and using location information to attract attention and boost self-presentation.”
// “In one-to-one location sharing, the user’s decision is simple: is the user comfortable telling this specific person her location. For one-to-many sharing, the decision is more complex: what may have been okay sharing with one person may not be okay sharing with many people. There are three reasons why large-group sharing might differ: (1) there is a larger variance in who receives the information, (2) there is a different motivation for sharing, and (3) there is a different expectation of plausible deniability.”
// “The success of Facebook is indicative that users are relatively comfortable sharing the same status information with everyone in their online social network (i.e., people of varying tie strength), but it is unclear if the same holds true for location sharing.”


2) Modeling People’s Place Naming Preferences in Location Sharing
// “Most location sharing applications display people’s locations on a map. However, people use a rich variety of terms to refer to their locations, such as “home,” “Starbucks,” or “the bus stop near my house.” Our longterm goal is to create a system that can automatically generate appropriate place names based on real-time context and user preferences.”
// “We also present a machine learning model for predicting how people name places. Using our data, this model is able to predict the place naming method people choose with an average accuracy higher than 85%.”
// When location was shared with more intimate social groups like family members or close friends, the portion of using geographic naming method was small (<15%) and the average granularity was finer (between street level and building level). However, when the location information was shared with less intimate social groups, such as
strangers, the usage of geographic naming was much higher but the average granularity drops dramatically (i.e. as coarse as city level granularity). This observation also confirmed people’s location blurring intentions get stronger when sharing with less intimate social groups.”


3) Bridging the Gap Between Physical Location and Online Social Networks
// Can co-location result in the next social graph? “We introduce a novel set of locationbased features for analyzing the social context of a geographic region, including location entropy, which measures the diversity of unique visitors of a location. Using these features, we provide a model for predicting friendship between two users by analyzing their location trails.”
// “The co-location network has roughly 3 times the number of edges as the social network, yet the social network is better connected. The co-location network has many small disconnected components, but it has a single large and highly connected subcomponent. Despite these differences, we have shown that the co-location graph contains important information that can be used to reconstruct a portion of the social network.”
// “Social network designers may find our methodology useful for designing social applications, such as location-aware information sharing platforms, privacy control mechanisms, and friend suggestion systems.”


4) Empirical Models of Privacy in Location Sharing
// “Our results show that users appear more comfortable sharing their presence at locations visited by a large and diverse set of people. Our study also indicates that people who visit a wider number of places tend to also be the subject of a greater number of requests for their locations. Over time these same people tend to also evolve more sophisticated privacy preferences, reflected by an increase in time- and location-based restrictions.”

Just published on TechCrunch re: Off the Grid private check ins on Foursquare.