Seemingly for centuries, mapmakers focused solely on getting from point a to point b, but largely ignored describing the stuff in between in any detail.  And even today it seems if you want to create a mobile app that covers all the places around you, best practices seem to indicate that it’s necessary to use data from many different providers doing a lot of cleaning and matching along the way in order to paint a clear picture. The definitive database of places is still elusive it seems.

That said there are some quite interesting start ups, who aren’t letting that get in the way of trying to gather together even more and greater detailed information related to places. A few that come to mind include companies like Gigwalk, Centzy and Locu.

Gigwalk, seems to take the approach that attempting to gather much of this information via anything other than direct 1st person interaction is fruitless, so what do they do? They pay folks… anyone that downloads the app… to pick up micro, $3 or $4 gigs by walking into retailers and taking pictures, noting the address and generally gathering information about the place. And in this economy with the emergence of services like TaskRabbit, I am sure the supply of GigWalkers is plentiful.

Centzy, seems to also be taking on the direct approach of paying folks to gather things like store hours and pricing, currently focusing on service business in NYC and SF including “facials, hair salons, manicures, massages, pedicures, yoga.” A great article in VentureBeat quotes Centzy as saying that ” less than 25 percent of local service businesses put their prices online” which must make the manual data gather for those categories a necessity.

But evidently restaurants are putting their menus online in mass, which is why a company called Locu is taking a different approach by crawling, scraping and otherwise electronically gathering menus from across the web, and throwing good old patent pending machine learning against it.  Another great article in the Huffington Post covers the all the details,  including the launch of MenuPlatform and Locu’s CEO Rene Reinsberg’s quote on the company’s goal, which is beyond just menus to “create the world’s largest repository of semantically annotated real-time small-business offerings.”

To me what Locu is doing seems the most exciting and interesting and maybe challenging because I’ve felt for a long time that the necessary rich place based data simply doesn’t exist yet on the free Internet. If it did, Google should have already indexed, parsed and done whatever the hell Google does with data to give us better local search results that bridges the divide between digital and physical. But they haven’t… if you really think about it local mobile search result still generally suck.  Locu seems focused on trying to fix that and is doing it seemingly in a very Google-ly way.

I noticed a similar dynamic and two different approaches related to gathering local product inventory between companies like Retailigence (manual data gathering) and Goodzer (web data gathering) and am not sure there is one right approach, and like with the current state of POI data perhaps for a while best practices will require using a little of everything.

On a related note Greg Sterling brought up an interesting point related to the Locu business , which is even if you are successful in gathering good valuable data, with so many others also focused on this area, will it simply become a commodity and how do you form a profitable businesses around being a data supplier?

Perhaps, if you do it well enough you can simply build your own local search application on top of the data?

The company Euclid Elements uses a bunch of wi-fi receiver devices plugged into the wall inside the retail store which in turn hangs out and listen for wi-fi pings from customer phones looking to make a connection. No connection ever takes place, but data about “signal strength, ping frequency, and proximity to other sensors” are all captured from customers’ wi-fi enabled devices.

All the pinging can cover a wide area reaching out and around the retail store itself and the company expects that a typical store may have between 40-70% of customers walking around with wi-fi enabled devices.

So what is there for a retailer to learn for this data? Well plenty according to the company. First and foremost is better insights into customer loyalty, ie what percent of my customers are repeats versus new customers… which may be particularly interesting to look at after running that big Groupon deal last week. Other information like how long customers hang out in the store or how many people are being pulled in off the street because of a killer window display are other potential applications. Or maybe on the last Thursday of each month there is a ton of foot traffic outside your store ½ hour after closing hour… so you may want to stay open late those nights.

While the company says that for the forseeable future there is no intention of tying anything back to the level of individual customers, or sharing data between retailers, the potential uses for capturing store presence data and tying that back to the larger marketing ecosystem seems like it may present an irresistible opportunity.

Simply being able to target mobile or web ads to folks who have been in certain stores or types of stores with follow up marketing would be a great place to start. Then why not try to improve on the whole loyalty card mechanism, by remembering customers who are regular loyal customers and giving them special offers while they’re still shopping, rather than waiting for that small percentage of them to scan a card at the check-out register.

With Research group BIA/Kelsey showing that a whopping 97% of shoppers research online before buying online, representing a $1 trillion market next year…  and 90% of those using search, connecting those two to advertise to customers in store based on their previous online search seems like a no brainer. If I was searching for Magnavox HDTVs online and walked into a Best Buy the next day you’d have to expect that Magnavox would pay a pretty penny to reach me at that critical moment… Magnetic needs to get all over that!

Another possibility is to throw a few more beacons around and try to help the retailer figure out some navigation path data within the store… do people loiter in house wares when you really want them in your shoes department, or are they stuck in the check out line for way too long?? All data that retailers would find interesting but aren’t yet knowable via the current Euclid Elements system.

It will be interesting to see where Euclid Elements goes with their offering, while its certainly super innovative… at $200 per month or $1,600 per year I am not sure if there is enough value there yet for the typical retailer who probably expects a more clear path between the analytics and how he can make money from the analytics.

And considering that half of small businesses don’t even have a website, being touted as the the Google Analytics of Retail won’t be an automatic foot in the door.

I happen to be particularly interested in the area of local and location based search and data, but since I had already talked a lot about companies dealing with data like PlaceIQ, Retailigence, Locu and HyperPublic, I instead ended up talking about an offering called Sonic Notify which was created by a NYC digital “ideas agency” called DenseBrain.

To grossly simplify it, Sonic Notify is a system that transmits a sound that can be received by a mobile phone, which can then trigger some sort of event on the mobile device that is within range and contains the Sonic Notify software.  There is no consumer Sonic Notify product out there, instead it’s a capability that the company hopes will be embraced by marketers to power their own initiatives.

The idea stemmed out of conversations that the company was having with a client Proctor and Gamble, and talking about services like ShopKick and how it would be interesting to look at technology to be able to communicate and connect with customers down at the aisle level or product level, as opposed to the store level.

There are two main components to the system, the side that can broadcast out the sonic signal (which is  inaudible to people) and the software on the phone which can pick out the signal and trigger the action.

Sending the signal seems pretty straight forward, it seems that standard speakers for PA systems, TVs, computers etc can all do the job.  The company has also investigated very small and disposable mobile audio beacons that can broadcast out the audio signal for vey short range situations such as from within name tags and badges for conference attendees.

Receiving and processing the signal seems to be where much of the Sonic Notify IP comes in. Phones which contain the application, need to decipher the signal amongst all the noise, and then once the signal is verified, instruct the phone as to what to do next… trigger a push notification, open a browser, send an email or text, etc.

The application can act in both an active and a passive mode, meaning you can set it up where a user would need to open up an app before the phone would begin listening for the SonicNotify signal (active, like how ShopKick currently works), or where the phone would just listen for the signal behind the scenes (passive).  I asked the company how operating in passive mode effected the battery life of a mobile phone and they said that they had come up with some work arounds to only switch a phone into active mode when it sensed it was within range of a certain wider (wi-fi) network known to be nearby to the beacons, with one approach using a SSID broadcaster as an easy alternative to setting up a fully connected new network.

In much the same way that scanning a QR code can trigger a variety of actons, Sonic Notify, does the same thing, except without  a user having to do anything (in passive mode) except enter within range of a speaker broadcasting the Sonic Notify signal… which can have a range of only a few feet or can cover a large area like a sports stadium.

Once the phone successfully “hears” the signal is when the interesting stuff begins.   The potential seems immense. Some obvious application for someone like P&G include presenting coupons for Tide to customers standing in front of the cleaning products aisle.  The company is also looking closely at the area of social interaction, or providing a super simple way to share contact information with people you meet at a industry trade show,

Now we’ve seen passive place based triggers before, folks like Xtify and Placecast among others leverage Alcatel Lucent geo fencing tech to do similar things, but they’re more designed for covering wide areas to pull folks into a nearby retailer.  SonicNotify on the other hand seems like a nice complement to those technologies for situations where you’re working with a smaller environment.

ShopKick offers a similar solution but relies on the user remembering to open the app when they go to stores, using the usual badges and point schemes to try to get folks to remember to use it. SonicNotify seems to offer a more flexible platform.

I particularly like the potential at the retail store level.  I for one wouldn’t mind getting a push notification as I enter a retailer asking if I’d like help, and giving me the option to explore sales and specials happening in the store, or researching items I am there to purchase.  I am after all entering into the store, and expect to receive service…  and if I am not interested I can simply ignore it and it will go away.  It seems to me that you could use SonicNotify to simply push the option of in store customer service out to customers as they walk into the store via their phones… you can see how a retailer may want to layer on interesting services like bookmarking ala Matchbook (“hey did you enjoy our restaurant, save us to your phone and share us with your friends”) or a white labeled check in loyalty service (“let us know each time you come and we’ll give you rewards”) or even allowing folks to look into product availability inventory (Retailigence) and get reviews and details on items available within the store.

Using hybrid positioning systems that reach indoor should in theory make an in-store customer service type “portal” do-able, but just maybe delivering a local experience really requires a local systems, if for no other reason then to be sure the customer feels like they’re getting a message as a direct and readily apparent result of the door they just walked through or the items they’re standing in front of.

It’s hard to say which way things will go, there is certainly a huge advantage of not having to set up technology at individual stores, but it may just work better that way. I certainly give Sonic Notify credit for trying a new angle.

Last week someone told me about a new one called Matchbook, that launched a couple of months back that probably went under the radar of most people, heck there are now 425k apps in the Apple App store, so how you do get ON the radar of anyone these days is another issue altogether!

The reason Matchbook stood out for me is because it is solving what seems to be such an obvious problem, and is something I had thought many times needed to be built… but was always stumped by how you actually get people to use and re use it and how’d you’d make any money from having built it. But I am really glad these guys built it and I hope to become a regular user.

So here is what Matchbook is all about: Simply put, it allows you to store and tag places you find out about so you can remember them later, or more easily share “your” places with friends. That’s really it, sweet and simple.

For example, let’s say you walk by a shoe boutique that you think your wife will really love, or a restaurant that you think your parents will enjoy when they come to town next month… one click of the mobile app later you can scroll through a list of local retailers, select the store and then click bookmark. If you want you can tag it something like ‘parents’ to help you keep your new discoveries organized.

Or let’s say you’re online, reading through the NY Times.com Dining section and read about a new restaurant that looks interesting, install the matchbook bookmarklet on your browser and with a click of the button you can pretty easily search and find the restaurant from the article and save it to your Matchbook account, all without leaving the NYtimes.com webpage. Or let’s say that they guy next to you on the train to Westchester is going on and on about how great a bar in Brooklyn is, there is even the old school way of just firing up the app and searching places in your area using free form text search… simply click and save, and the next time you’re in Brooklyn looking for places to go you can fire up and consult your bookmarks.

As with so many start up apps in the location based world these days there is an enormous amount of focus on finding bars and eating out… and there’s no exception here, with the pre populated ‘tags’ focused on things like Drinks, Food and Vibe categories. So for example, for Campbell Apartment which is a classic and classy, old school lounge in Grand Central Station, I tagged <DressedUp>, <Chic> and <Cocktails>. Even though for my own purposes I really wanted to label it <out of towners> because it’s one of those places I’d like to zap over to the frequent visitors from out of town to go for a drink since its old school New York, with 20’s style cocktails and it’s in Grand Central station which most people are happy to check out even if they’re determined not to do “the tourist things”.

While I generally like Matchbook and where it’s going, I kinda wish it was more of a place oriented organization utility and less of yet another ‘going out’ tool for urbanites.  As much as I want to laude them for excluding things like check-ins or game mechanics, for the average consumer I do wonder how it moves from become a “once in a while” app, to well one that’s not limited to being used just every once in a while, or when you’re traveling.

While focusing on bars and restaurants is one way to go, I can see a ton of applications in all sorts of other use cases including selecting on demand meeting places, a broker sharing a list of houses with a client or an event planner keeping tabs of venues and their past client events there.  The ability to share all places that use a common user generated tag within your account seems like a great feature that they’re probably working on already. The possibilities seem nearly endless.

Commercially, one way I’d be interested to see it expand, would be to get custom alerts (push notifications?) when a tagged place is nearby… and why not include brands here. I grew up in central Florida, eating at the original Sonny’s Real Pit BBQ, which has since grown into successful chain of 150 restaurants across nine states in the South… and much to my wife’s dismay I will gladly drive many miles out of my way for a Big Deal if there is one around. But unless Sonny’s launches their own “BBQ Beacon” app, which isn’t too likely, it seems like an awesome opportunity to create a branded Sonny’s tag that I can save to my account and receive alerts when I pass within range of one of their restaurants! I know folks that have similar passions for places like Costco and Starbucks.

A tiered, freemium model also seems like a no brainer… a free app for the casual dinner and going out users, but for someone like the event planner who wants more sophisticated features, surely they’d be happy to pay.

I plan to keep plugging away with Matchbook, and hopefully they continue to gain some traction and keep developing features and the scope of the product, so the next time I am driving through Baton Rouge Louisiana I get a friendly reminder that I can indeed get my Big Deal with Pork, Beans and Sweet Tea while I am there.

You’re currently not going to get much information from the website yet, other the fact that they “transform location into context”. So what does that mean exactly?

Well it may help to back up and think about how context comes into play in the world in general.  Context is the just the stuff around something that helps you relate to it or understand it better.  So, seeing the situation around a person or the other words around a word create context which can trigger something in your brain that help with your understanding… and advertisers hope that this context makes you more receptive to what they have to say.

The advertising world pretty much revolves around the concepts of audiences and context… in fact advertisers just love context. For many it’s not enough to just get your ad in front of a 1 million people, it needs to be the right 1 million people and ideally at a time when their brains are well tuned to whatever it is you want to tell them. Which is why an advertiser of salad dressing might choose to place ads in Better Homes & Gardens (the right audience) adjacent to their food editorial (right context) to communicate to women who may be planning the next meal for their families.

In the online world the same thing happens… if Delta wants to advertise new low prices on flights, where better to do so then in the context of a travel site? If Mattel wants to advertise their newest Spongebob licensed board game, where better to advertise it then on the pages of Nickelodeon.com (the right audience) in the Spongebob games section (right context). Contextual selling is part of the bread and butter of what media companies do.

On the web, companies like ContextWeb and Peer39 among others have built entire enterprises around the ability to understand the context of a web page, and how that may have an effect on a users receptiveness to advertising on that page.

So now about PlaceIQ. If you start to think about the world beyond magazine pages, television spots and banner ads on your PC… the world is quickly going mobile. And with this mobility comes an interesting new twist on the concept of context.  Sure you may be deeply engaged in the world of Angry Birds catapulting themselves at pigs, Zombies munching on your row of spitting mushrooms, or the latest article about LeBron’s 30 point night… but sooner or later you you’ll look up and disengage from that virtual world and realize that you’re sitting in a train station, or on a beach or in your doctors office… and where you are is context too. Not only is “where you are” a somewhat unique type of context to advertisers, but potentially a very important and powerful one… after all reading about Lebron James’s lighting it up in the Garden last night on my mobile ESPN app may correctly categorize me for advertisers, but so does the fact that I am sitting on a beach in a swanky area of South Beach while doing so… in fact the “signal” that the latter data point sends is probably much more useful. It’s also something very unique and novel for the industry to wrap their heads around.

So that in essence is what PlaceIQ is all about. Gaining a deeper understanding of places… everyplace, down to a 100×100 meter ‘tile’… so that mobile and out of home advertisers can better understand the context of what is happening in those areas when it comes time to place or deliver an ad.

The PlaceIQ data is gathered from a variety of sources near and far, with the company looking at anything from sensors (ie the behind the scenes ‘reporting’ of location from mobile devices) to good old fashioned web content, as well as a number of proprietary and government data sets. Since no one data set provides the complete picture, they all compliment and reinforce one another to make the most complete picture possible.

To take it all a step further the data is also organized temporally… which as anyone that has walked into a bar at 10 o’clock in the morning knows, a bar at 10 in the morning is often quite a different place than the same bar at 10 in the evening… same goes for baseball parks during the time of a game, and a train station during the morning and evening rush hours. Spaces have different profiles at different times of day… which is important when you’re about to serving an ad hoping to reach a certain type of person.

There are seemingly any number of people that could take advantage of this type of data, but the players in the mobile advertising ecosystem are some of the first to show interest. Use of the mobile web and mobile applications is exploding, and increasingly the ad “calls” within that content can be tied back to a geographic location, and the ability to use this location data to sell and target ads more effectively creates a compelling opportunity.

In the web world there is a lot of focus these days on audience buying… in other words I don’t care if you are reading a webpage about cars, I am going to serve you an ad for a blender instead because I know you were on a cooking site earlier, or you fit the demographic profile of people who typically buys blenders because of the registration data you provided ten sites ago. This practice has always been an area of scrutiny, because it generally relies on cookie swapping to recognize users as they pass between websites.

As you might imagine when it comes to mobile location data, this is an area that becomes a lot more sensitive. For PlaceIQ, how the whole mobile cookie capabilities nets out is important but not critical… as the data is organized around places, not people. In the same way that you can infer something about a person by the web page they’re on, you can similarly infer something about a person from the geographic place they’re currently at, and the time of day that they’re there. Of course the whole thing becomes a lot more sophisticated if there is some sort of location history that tells me that you like to visit museums, or Chinese restaurants, or that you just came from a Yankees game. Even in bulk aggregated form, information that people that go here, also tend to go there holds a lot of value in the world of digital advertising. But when and if that information ever becomes a viable basis for ad delivery is still up in the air.

I guess the thing that interests me the most with the company is that for years and years the ‘web’ has been this virtual parallel world, generally disconnected from reality, where the rules were different… you were either on the web or off. Many created virtual identities, funny little virtual currencies and virtual images of themselves living their virtual Second Life. The mobile web, tied together with location can bring us collectively back from the virtual la-la land to real reality, simply Powered By the Internet. And in that world, having a deep digital collection of knowledge that describes what’s going on in that world, down to an area of a hundred meter tiles… well just seems like a pretty valuable thing to have.

A quick search on Google and I noticed that they had a partnerships with Qualcomm, as an early user of an open source project called AllJoyn, which seems to power some of the wifi and Bluetooth side of the technology behind Lokast.  What the hell does Alljoyn do, well I can’t tell you in any great detail for sure, since I opted not to spend 2 hours reading through all the documentation and SDKs, but per their FAQs it’s “peer-to-peer technology that enables ad hoc, proximity-based, device-to-device communication without the use of an intermediary server…  that will enhance the user experience by simplifying how devices interact with one another.” And “AllJoyn was developed to solve many of the problems that exist in enabling peer-to-peer communication such as simple discovery, pairing, message routing, security, transport independence etc.”

So the takeaway from my non techie little brain is: 1. it’s location specific, 2. it’s an easy way to connect between devices, and 3. you can share stuff.

So while the use case that they seem to be pushing for AllJoyn is around gaming, and Lokast is taking it in the social direction. I think the big retailers like a Best Buy or Home Depot should have a look, not necessarily to allow me to connect to the other customers in the store at the time, but to use it as a way to provide better service to me and connect me with the store just for the time I am in there.  I am thinking of it less as true random, out in the wild peer to peer network, but more as a one super peer “authority” device (the store)  that will always be present in a store creating the foundation for a quick and easy ad hoc communication system  between a store and its patrons.

How would I like to be “connected” to the store while I am there?  Well some stuff is simple, like notifying the store that I want someone to come help me, or leaving feedback like the fact that salesman Bob really knows his cameras.  If there is some promotion happening in the store like 20% off DVDs, it would be good to know that as I make a bee line for the computer section on the opposite side of the store.

Then you could really start to get fancy, by say loading up a ton of product information and demos, so when customers want to do a little in store research of a product they’re considering buying they can get at it quickly and easily, without having to resort to a search of the entire web of data on the subject via Google.  Customers could sample clips of songs or movies in the DVDs section before buying, or peruse curated content of peer reviews of dishwashers or toys before buying. Not to mention that all the in store mobile search query data would be a massive goldmine for ad retargeting ala someone like Magnetic, Akamai/Acerno or Channel Intelligence.

I think if any of these in store retail plays like the area that Shopkick is going after will ever be successful, they’ll need to forget about the silly point schemes and game mechanics and trying to develop a one size fits all mobile app solution from their HQ in California.  I think the more successful route would be to build a simple platform that allows each retailers to take control, and build from the ground up, specifically around the needs of their store and communicating directly there locally with their customers.  Not to say that a lot of the content, like product reviews, couldn’t be one size fits all, but the implementation and people running the system need to be there locally in the store.

It seems to me something like AllJoyn could be pretty easily modified to do all this.

One of the pieces of news that was making the rounds over the past week, at least in my little corner of the twitter-sphere was news that Watson a computer system baked up by the fun folks at IBM beat the pants off two of the all time best players on the popular trivia show Jeopardy. Like its predecessor Deeper Blue in 1997 who beat the pants off of the then world’s best human chess champion… Watson was designed from the ground up to perform a specific task, and to do it quite well thanks to modern capabilities around processing power, data storage and hundreds of simultaneous algorithms tasked with interpreting the natural human language.

But reading a bit more of the press about the event, something caught my eye, a reference to the fact that Watson doesn’t even use the Internet.  To which my immediate reaction (yes I think I’ve become a jaded and skeptical New Yorker) was something like this, well if it coulda, it woulda, so since it didn’t…  well something is up.   And my suspicions were confirmed when the author of the IBM post was kind enough to elaborate that yes he believed that accessing the free and open Internet for information would have been detrimental to Watson’s performance. Which upon reflection makes all the sense in the world…  why would you sift through the entire Internet of information, when you can carefully curate all the information you need for the job in less that 1 terabyte of data held in 90 servers stacked up back stage.

Now like most people, I don’t have a clue as to how much general knowledge trivia there is in the world, uh… a lot? But am I a little surprised that it  can all be crammed into 90 computers, well yeah I guess so, I’ve never really thought about it. I am certainly impressed with the fact that Watson can fish out any little corner of it in about the same time as it would take Alex to type in the question.

But I guess my whole point here is the bigger picture stuff… the folks at IBM wanted to solve a single problem… find answers to trivia questions.  And with the state of things in the world of processing, data storage and algorithms getting, storing and retrieving that information was best done in a closed environment…  the 1TB of factual data necessary, apparently not that big of a deal.

So getting back to local search. Now I had not dealt with buying or selling web search in quite some time now, but within the past couple of years I have started to go back to shows like SMX East, the east coast edition of one of the larger search marketing trade shows, where the subject of local search is a pretty hot topic these days.  What surprised me a bit is that finding places and things in the real world was generally just viewed as more or less the same as searching for and finding web pages about places and things.

Maybe it’s just me but this just seems downright weird.  The web is home to billion if not trillions of pages of content on topics ranging from what Julie in San Jose had for dinner last night to how to calculate the weight of an African tree frog… 99.9% of which has absolutely nothing to do with what’s in the ½, 5 or 10 mile radius around me where I live the vast majority of my life.

Now if someone can sort out the web stuff that’s relevant to my little physical personal world that would be an improvement, but still people put some pretty useless and irrelevant stuff on the web, thousands of people I don’t know or care about and a huge chunk of retail businesses with no significant web presence to speak of.

What I need is just access to the stuff that is relevant to me, good detailed information on stores and products, people I know or might like to know or communicate with, events, relevant news etc.  Much of this information already exists, but like with Watson, just because it exists doesn’t mean that one can get at it quickly and easily, and sorting through the entire web of content to find it, well just wouldn’t be the best way to do it.

Until last night I wasn’t very aware of what folks were doing in terms of creating hyper local networks, but at the LBS Apps developer meet up last night here in NYC,  a company called Nearverse demo’d  their app LoKast. The application allows an organizer to create an ad hoc local network between users of the application who all share a common space of between 300-1000 ft… using a combination of Bluetooth, wi fi or your cell carriers’ wireless data connection.  With file sharing at its foundation, the idea is to allow folks who share a common space to share, well…almost anything digital that they want, including videos, songs, photos, contacts or webpages.

Now Nearverse doesn’t seem to be looking at areas around local search necessarily, and I am not sure if it really directly fits, but it would seem to support the idea that just because there is the capability to push info out to the one mass Internet doesn’t mean that this is the best and only way to do something. Perhaps million of tiny micro locally relevant Internets that just contain locally relevant data, or a massive database of only locally relevant data that is built around location from the ground up would be two novel ways to help connect people with just the relevant info about the world directly around them.

And most people seem happy enough that the plumbing behind Google does a pretty good job of spinning all the relevant information from everywhere on the web around like a centrifuge, drawing the good stuff that we want to the top where we can easily get to it. 

But the Google centrifuge can only work its magic on the stuff that is present in the tube. And while there is a huge amount and diversity of information out there on the web to be spun, what tends to get put out there is created by folks in the general category of ‘authors’. Web “authors” can of course be anyone from professional authors who create long, elegant and thoughtful prose for a living,  to corporate copywriters describing a box of cereal, to you and me “authoring” content  about all the crazy sh*t we did last night.   There are no arbiters of good or bad… simply tons and tons of contextual text, tags and links to be spun.

But when it comes to mobile search, as the folks that run research in this area will tell you, the stuff that we are often looking for is, well different. We’re less likely to be researching the African tree frog or stalking information about our ex gym teacher… we save that for the full 1024×768 glory of our desktop PCs.  Much of the time when conducting a mobile search we’re in search of something more specific and something directly around us in the world that we want to find or know more about.

But the problem is that since the beginning of the web, it’s been viewed as this virtual and separate world, while very much connected to the real world by its authors and what is being written about, but with very little efforts to make specific connections in real world space and time… at it’s best it’s an incredible depository of content but at it’s worse a historical dumping ground of nearly anything and everything that can be written or recorded on video.  An impressive collection of trillions of pages of inter connected content, but still generally just authored pages of web content. 

Two big areas where we’ve tried to connect back all those virtual historical pages of data directly back to specific things in the real world have been through people and places. With Facebook the current leader as the center point for information tied back to real specific people… and Facebook, Yelp, Google, Localeze and others all aggressively trying to build a similar stature as the centerpoint for information tied to places, but with no clear leader there yet.

A few months back I came across another company focused on yet another area of connecting the virtual world to physical… not with people or places, but with things. In this case things to buy in stores.

Retailigence is a San Francisco based start up that is looking to dig deep into the bowels of retail businesses, well into their inventory systems specifically, to do a better job of letting the virtual world know more about what products are available and at what color and price and most importantly where.  The company is not looking to launch the next great location aware shopping application, but instead wants to power a new era of capabilities that connect customers to the products they’re looking for by providing the core underlying data to other Internet companies through an API.  As a recent TechCrunch article points out, they’re kind of a Localeze for local product rather than place level information.

The obvious customers for their data would be folks like Milo who are specifically in the online local product search business. The not so obvious customer would be folks like Nordstrom’s  who recently opened up access to their inventory systems which gave their own internal sales staff better visibility into where product may be anywhere throughout the virtual ecommerce warehouse or in stores across the country. According to Jamie Nordstrom, the President of Nordstrom Direct, same store sales saw a 8% lift, and “inventory publishing has a significant impact”.  There is a great NY Times article with all the details worth checking out.

Just yesterday, Retailigence won the judges pick for best in show at the 2010 Under The Radar conference and during the Q&A with the judges (video below), one judge makes reference to how mainstream “high funnel” marketers could use this data in their advertising… for example Best Buy could turn a somewhat generic national online banner ad or even a magazine ad into one that features (online) or is easily linkable (magazine) to the local price and availability of that big screen Samsung LCD you’ve had your eye on. The opportunities in the traditional and digital ad and marketing ecosystem seem quite interesting.

We certainly aren’t there yet, but it seems to be getting closer to the point where a reference or search on the web with high local intent doesn’t return the entire Internet full of HTML information related to a topic, but instead recognizes our location and context and attempts to discriminate for the better about what we really want.

So I started this post well over two months ago, after learning about a new app called Foodspotting  that presented here in New York at a meet-up group that’s quite popular, and regularly pulls in 700-800 people.  I didn’t RSVP in time and the event was sold out and I didn’t have a chance to attend and see the demo in person so I tried to load it up and give it a trial run after the fact.  Well that didn’t work out so well, something to do with the iPhone OS changeover or something, but alas a few months and a new release later its up and working for me.

When I first read the description of Foodspotting, my reaction was ‘really?! There is an app for that?’  I have occasionally seen folks sitting at a restaurant taking pictures of their food, but frankly I think it’s kinda weird… I like food and eat out regularly, and even consider myself a very minor league foodie… but I am sorry taking pictures of what I am eating just seems strange.

Well evidently the whole food picture thing is becoming quite popular, beyond just the Japanese tourists at high end restaurants…. According to a recent NY times artice,one of the most popular and active groups on Flickr is a group called “I ate this” with 30k pictures uploaded by 19k members.

So here we have it, an app for those that like to take pictures of their food, seems kinda silly to me but then again so did the idea of micro blogging to damn near everyone in the world just a few years ago, yet now there are some 100 million registered users on Twitter…so what do we know.

Foodspotting is all about the documenting and discovery of food.  The general idea seems to be to take picture of the food that you like on our mobile phone, and the place where you spotted it, and then share it with the rest of the Foodspotting community.  If it looks good other users can either vote to “Want It” thereby keeping a nice running list of foods to try someday, or “Nom It” as in voting for the fact that a particular dish (or picture) is a good one.  You can then follow those folks who  you find interesting or who seem to have taste in food that fits with your own.

I must admit that seeing pictues of the actual food is kinda nice… it’s a lot more telling than just a bunch of words about a restaurant that relies more on the ability of the author to write good creative copy than anything else. To a degree, seeing is believing, but then again a guy with a minor in food photography can probably make most any food look good, and the quality of the photo has a huge impact. 

The whole thing reminds me a bit of Flook the serendipitous discovery engine, that is also driven primarily by big beautiful imagery of places where you can flick through a stream of images, rather than more utilitarian text descriptions.  But like Flook, I wonder if this is really how people want to discover new things?  If that is really the goal here.  

Now having a service that is targeted at the plate level rather than the restaurant level, has some benefits, particularly for those who really care about the finding new and interesting food.. or if you’re sitting in a restaurant perusing the menu trying to decide what you’ll order I can see how it would be handy to be able to thumb through pictures and comments on dishes before you make a decision. I’ve never worked in a restaurant, but I can imagine that there must be a certain chain reaction of orders of people saying ‘I’ll have what they’re having’ as they spot good looking dishes at neighboring tables.  I can genuinely see a good number of people wanting to TAKE information from Foodspotting… but what I am not sure I see is a large amount of people CONTRIBUTING pictures to Foodspotting.  I know I’ve read that most communities of this kind have the number of takers far numbering contributors by wide margin anyway, but I suspect that building a community of contributors to Foodspotting will be particularly challenging. 

 I’ve heard rumors that the company isn’t interested in staying focused just on food, but on the more broad “spotting” phenomenon, so you can see some equally interesting vertical areas where the further platform-ization of the idea could apply to areas like celebrity-spotting,  fashion-spotting, sale-spotting, car-spotting, sights-spotting, etc.  The concept seems to combine at least three powerful drivers… 1. building a community of like minded folks, with a common interest or passion… 2. tying what’s being spotted to a place which in turn says something about the place (Madonna shopped here on Thursday, wow!),  and 3. a practical way to crowdsource valuable, locally relevant information in real time through the use of a social community features

I am not sure I’ll become a regular FoodSpotting user anytime soon, but I am pretty sure it’s only a matter of time before some 19 year old Stanford undergrad develops Hottie-Spotting and successfully raises a few hundred million dollars and gets a movie made about it!

 Up until now, access to such data required reaching out and working directly with Verizon to obtain and use the information, on a case by case basis, something that didn’t happen much. The newly released APIs will change all of that, allowing developers more streamlined access and allowing added value service providers like Loc Aid and Location Labs to finally offer a complete coverage offering, allowing unified location based services across all tier one carriers in the U.S.

Why are folks like Loc Aid and Location Labs so excited about this development?  Well, the logic is that anyone who has always wanted to develop a location based services and deploy it to everyone in the country, has up until now been hamstrung by how to include the 90 million Verizon Wireless users into the mix.  It wasn’t an easy task.  But now this barrier is gone, or at least greatly lowered, and in theory at least so should all the excuses to not build a service… so let the flood of new services commence.

Ubiquitous availability is one part of the equation but so is price and availability of the type of location data that developers want and it’s still unclear how much of a barrier those present.

Verizon is offering location in two forms via its newfangled APIs, coarse location via cell ID good for a mile or two accuracy depending on where you are, and more granular location via GPS or WiFi, all available as a single fix or as a tracking session.  I’ve heard that in the past, that the cost to dip into this data generally ran from fractions of a cent for a coarse location and more like four cents for the more accurate stuff, or a few dollar CPMs up to $40 respectively per thousand if you’re a media person and this is how you view such things… not cheap stuff for a lot of applications.  However the verbiage around the Verizon NavBuilder Inside sitetalks about how “it’s the fastest way to add location based services to your apps for free”.  At the same time I’ve also heard folks like Loc Aid positioned as re -SELLERS of this data, so it’s still a bit unclear to to me if this is going to be free or if it’s something for sale.  Any help from a more tuned in  source here?

At the end of the day, these APIs certainly do solve some key problems of building location oriented applications for Verizon customers. The vast majority of phones, ie feature phones, will still be limited to the more coarse location accuracy of Cell ID, which will certainly still be a limiting factor for introducing many location oriented services.  But on the other hand, higher end smartphones on Verizon will be able to take advantage of always on, higher accuracy (Wi fi or GPS) positioning for extended sessions which for example could pave the way for hands free social check-in services that, after an initial approval, could register presence or check you in automatically.  If the user doesn’t need to regularly push a button to ‘check-in’ anymore will the whole concept of check-ins just slowly fade away and a mobile record of presence at place of sale take its place?

It was also interesting to note that location fixes are defined as Fast, Normal and Accurate…  a “Fast” fix is achieved in under 2 seconds, a “Normal” one up to 10 seconds and an accurate one, well 60 seconds or more.  Since location can apparently happen more behind the scenes, depending on how its implemented,  the user may in many instances be blissfully unaware of how long its taking to get this information for their use, but such lag times times could also pose to be a hurdle for services accustomed to working in times in microseconds… like say ad targeting and serving.

So while it seems that we have indeed taken a major step toward ubiquitous availability of of location here in the U.S. there is still a lot TBD here particularly around speed, accuracy and costs of this data, so while it may be there, everywhere… is it the kind that’s needed and at a cost thats affordable to developers of new services?