The problem with hyperlocal is that most people interpret it wrong. Currently the most common practice is to use geolocation, you either enter your postal code or the application/website defines your location based on GPS or IP settings. So you get news, offers, information related to where you are. Very efficient but when thinking about hyperlocal the opportunities are beyond that. 

The reason why is the following:

1. I got many localities that are relevant for me.  I think about the place where I live, where I work, where I lived when I was young, … I have a bond with all these locations in a certain way so I’m interested in news from all these places and even other types of information. Today no-one is offering me a way to organize news gathering with this in mind. At best, like I mentioned before, you get that output for one of the chose locations, never for a mix of. Prove me otherwise.
2. The range of interest centered around me can differ in size depending on the topic and the moment. What I mean with that is that when I’m looking to buy new furniture I’m probably okay with driving a bit further than when I want to get a pack of cigarettes, just to name something. Or when I want to buy a car versus when I’m looking for an accountant. This means for me the range you take into account when talking about hyperlocal needs to be quite a bit more subtle than it is today.
3. Last but not least, hyperlocal doesn’t mean faits divers by default. The local version of my online newspaper tells me about a selection of the tiniest events I don’t care about in my city, but fails to mention when the Tour de France is passing by. Zooming in on hyperlocal seems to mean the same as zooming in on stuff that nobody cares about happening 2 blocks away. Why is that?

With more and more information, media being geotagged and with technologies that allow geofencing I hope that we’ll see an evolution in the way we deal with hyperlocal that takes the reasoning I wrote down into account.

Log in with LinkedIn and the tool will analyze your network and visualize it in a graph like the one below, which is actually the output of my LinkedIn network.

What’s extra interesting about it is that the output is dynamic (unlike this image) and that you can hover over each contact to see their specific connections within your network. That way you also get a view of how the clusters are made and InMaps allows you to put a label on each colored cluster to make it easier to see who’s who. Just give it a try, you’ll see for yourself.

Interesting results for myself is to see for instance that I have 2 Microsoft clusters (I’m ex-Microsoft remember), one for MSN/Windows Live related contacts and one for more general Microsoft contacts. Interesting to see that this split is made, although it’s actually pretty logical when you look at it. Also interesting is to see between which groups exist more links, not always what you would expect. I’m definitely not done analyzing this, but curious what your graph/learnings look like so please do share ;)

Last but not least, it’s also pretty interesting proof that people are organized in groups, clusters and that if you want to influence people it’s important you understand these clusters – or ‘spheres of influence’ like we used to call them, dixit David Armano.

“His thoughts around augmented cities and why maybe ‘augmented’ should be about taking things away instead of just adding them to the world as we are already drowning in data as it is.”

So when I got this video today from a colleague about a research project on ‘Dimished Reality’ by Jan Herling and Wolfgang Broll of the  Ilmenau University of Technology, it was like a proof of the concept Kevin talked about a year ago now. I don’t like the name ‘Dimished Reality’ because it still is doing more on top of what is really there. But in this case less really is more, check it out:

Let’s find out what happened in 1973 – the year I was born in case you were wondering ;)

[Via The Denver Egotist]

Something else bugs me even more. When making these ‘analysis’, infographics and what not, people are not comparing apples with apples. Nobody seems to find it a problem that we’re always comparing 500M Facebook users versus 145M Twitter users (and some even against the 300M Windows Live users). For Facebook that are registered users, and as such most likely unique users. For Twitter that are registered users, and most likely that means registered accounts – and not unique users. I’ve got one Facebook profile just like most people but do use 3 Twitter accounts (@crossthebreeze, @iblogmustang and @krishoet). For Windows Live however the 300M users mentioned are active users, active meaning that they’ve logged on to the service at least once during the last 30 days. You can discuss about whether that is a good measure for being active or not, the point I want to make is that although they’re all big numbers they all don’t really mean the same thing. And that makes it unfair to just compare them like they are in my point of view.

Especially the registered versus active users is something really important to think about. When promoting webservices such as the ones we’re talking about you can imagine that generating awareness is the first big task on the agenda just like any other company. But because they are webservices I presume once you get the attention needed, driving registrations is not the toughest part. Registering to an online service is easy, I’ve registered to hundreds of services by now but use only a percentage of those on a regular basis. Activating users/consumers is the toughest part. People show interest when the buzz is up, but what is it that you do to keep them interested? That’s a tough challenge, a challenge to which many services fail if you ask me.

And it’s not just webservices of course, same counts for apps etc. There’s a boatload of apps available for my phone apparently and still I find it hard to find a dozen decent ones to download on the device. So don’t just report on the big numers PR people give you, those don’t always mean much (at least not to me). And please compare numbers worth comparing, otherwise that makes no sense either.

There you go. Had to get that of my chest.

[Via TheNextWeb]

“The pic itself is a 1.3 gigapixel, 75,000 pixel-wide image compiled from 36 photos that took one minute to capture. They used two Hasselblad H4D-50 cameras with 50 megapixel digital backs and, camera geeks, a 150mm lens on top and 100mm lens tilt shift adapter. Both cameras were mounted vertically on a tripod and rotated at 10 degree increments to take the pictures.”

8.195 people are tagged as we speak, has it been confirmed yet that’s a record?

“Consumers’ ingrained lust for instant gratification is being satisfied by a host of novel, important (offline and online) real-time products, services and experiences. Consumers are also feverishly contributing to the real-time content avalanche that’s building as we speak. As a result, expect your brand and company to have no choice but to finally mirror and join the ‘now’, in all its splendid chaos, realness and excitement.”

Call it nowism, instant gratification, realtime, … if there’s one apparent trend that came out of 2009 it’s this one. Can you find a way to integrate the core idea behind this into your consumer communication, you’ll definitely be a step ahead of your competitors.

Here’s a good presentation that tells a bit more about what realtime really means, good stuff.

[Via @heldenmerk]

It did remind me of a Microsoft project I read & blogged about 3 years ago, a side project of Photosynth at that time. They talked about a very similar tool but don’t remember hearing from this after that.

Question to ask the Photosynth guys maybe? Or Steve, maybe you know (can find out)?