LBS, aka location-based service, just sold for a cool $33,001.

The new owner is hiding behind privacy, but I wonder if a local mobile site is on its way.

Pixel art movable map of Beijing.

Plus hover over any building and you get its name.

Where is the NYC-equivalent?

UPDATE:

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Nice little story on how Neal used the internet to save himself ~$250.

What kind of stood out to me though – Neal used Repair Pal to find out how much a new starter would cost – he really used to the site for research purposes, not for the actual transaction. So they helped him save money – but kept none of them.

The question to ask is – if something happens next time, will he use Repair Pal immediately? Have they converted him into a potential paying customer? Will he recommend the services of the website to others?

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I’ve changed my tune before – particularly that reviews are overrated and recommendations are the future.

But even more importantly – I’m realizing that the problem is that we are focusing too much on local ’search’ and too little on ‘local’ itself.

A while ago I was at the GeoDomain Expo 2009 in San Diego. It was pretty amazing how far geodomain owners (in this case – explicitly CITY.com – eg NewOrleans.com or SanDiego.com) had come from when I first met many of them (two years ago). Many of them had morphed from simple travel destinations into complex businesses that covered news, events, and a lot more.

What was most telling is that many of these websites were gaining immense growth while focusing on local – but completely skipping ’search’ One of my favorite examples was of a city of ~150,000. The #1 website in that city had an awful awful domain name. Local search was non-existent. The site had its own news staff, classifieds, forum, and so forth. It was doing roughly 30,000,000 pageviews a month – for a city of 150,000! And most telling – it was making millions and millions of dollars a year.

In itself that doesn’t seem like a seismic shift – but my thought process is starting to evolve to ‘everyone associates search to Google and a handful of other brands’ – and what may be the correct way on monetizing and profiting from local is to focus on the specifics of each location.

With that I’ve focused more on programmatically figuring out how to collect and make sense of different ‘local oriented’ streams of data and putting them together. I’ll post about that next.

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I’ve been lately working on trying to generate heatmaps from an assortment of data. To say it has been tough is an understatement – I have tried Python, PHP, and Ruby libs/classes, and all have been too slow, too weak, and/or plain ugly (high peak is red, not blue nor fire-colored).

In the case of local, it is a combination of:

• Generating data in the format you need (x,y) coordinates with a related ‘value’ (the higher the value, the more obvious in the heatmap)
• Utilizing the data and being able to quickly and efficiently plot it onto an image
• The ability to create multiple levels and multiple images. For example, if using Google Maps, there are at least 5 levels that are important enough. Each tile image is 256×256, and each zoom increases the # of tiles by a factor of 4 (when you zoom in, what was one tile becomes 4). This is arguably the hardest part – eg if you only create by 256×256 grids, you miss location information just out of the grid. There might be a heavy heat-spot you might miss. And generating one big image is out of the question as you would exhaust memory. Using rough math, and exactly full zoom out, we have 12 256×256 grids. Another level of zoom, you end up with 48 images. Another zoom you end up with 192 images. Another zoom nets you 768, and one more gets you at 3072 images. One image that is 3072 tiles of 256×256 is 201,000,000 pixels. Even 768 tiles ends up being 50 million pixels. One image = no go.
• Conversion of (latitude,longitude) point into X,Y coordinates. In itself not difficult, but when you are trying to keep track of grids, and minimize CPU time spent, it becomes much more difficult.

Anyway – more than anything, this post was just on a challenge I’ve been working on. I haven’t solved it, but what I love is how much it brings local to life, and makes for another way of looking at data. For example, fast food joints in California:

Ideally I can get this damn fast enough that I can generate this in real-time and release as a lib. If not – oh well, a very interesting learning experience.

I’ve come to an epiphany lately. It may seem obvious, but it truly changes the way you perceive things. The truth is that everything is local.

Think about it – what is synonymous with the internet? Sex. Travel. Weather. News. Sports. They are all very local oriented (sex – craigslist and AdultFriendFinder … whose affiliate managers email me twice a day ugh).

Really – the point of this post is for you to try to see the local aspect of your day to day life. The internet is a woven tapestry of local connections – but too often we see the finalized product, not the individual (local) links that bring it all together.

I will come back to this.

For every 20-30 emails we get at iBegin asking that we fix an issue, 1 of them always has the veiled threat of a lawsuit. “Fix my # or I will sue you!” “We have moved – fix it or I will have my lawyer deal with this!” etc etc. Of those threats, 1 out of 10 are just downright unstable. Capital letters. Abusive language. Even the occasional threat of bodily harm.

What boggles my mind is how these people stay in business. Yes bad information sucks. It can be annoying. But what is the harm in asking nicely? I can understand if you have emailed us before and we didn’t reply – but that doesn’t happen

Sadly enough – another reminder of the recession. The threatening tone in emails has increased – the more stress you put on the business owners, the more likely they are to pass it on.

I should note that while I can be crass here (and in other areas), all emails are always civil. Even with the random person who replies to me with mentions on how I must be working with the terrorists because of my Islamist name (true story).

I have a few favorite companies in the local space. UMI is one – especially after they did their new parking release. LDC is another one – fantastic work they have done in the UK. Add another one to the list – Yipit (furniture search).

I have long railed that there are too many ‘me-too’ companies in the local space. All doing the same with the same set (data, ideas, etc). Yipit is thankfully not one of them.

Having made the odd yet interesting decision to stick with furniture (and in NYC), the team has gone all out in indexing and collating their data. They give actual ‘depth’ to their data – new vs used, cheap vs expensive, antique vs modern, fabric vs leather, a lot of stock vs little choice – these are the magical attributes that change your search from ‘furniture in NYC’ to ‘cheap leather sofa’ – an experience that truly takes us from ‘yellow pages’ to ‘local search’

Their UI does need some work still (for example – why does each furniture store not have its own page that lists all their stuff?) but overall I am excited to see where they take this.

So as we continue to do quite a few verification phone calls every day, people tend to mess up. Human nature.

Recently I have gotten to thinking – Google has you enter a four digit PIN, and for whatever reason that popped in our head, we all agreed that a four digit PIN was good. But why four digits? Why not 3? 2? Or even 1? If the purpose is to verify that someone owns a phone, how does entering four digits make it any more verified? At the end of the day, if someone has access to a phone, the # of digits is irrelevant. I can understand the argument against one digit (they may accidentally hit a digit), but at two the likelyhood of someone entering in a PIN when they didn’t mean becomes rather unlikely (purely based on available #s, there is a 1% chance IF they intend on entering two digits).

Anyway – I think the four digit idea makes no sense. And yet almost everyone I have ever talked to it thought it was perfectly reasonable.