name
Burger King uses ‘musical shower’ as latest trick to entice Japanese clientele
Source: http://www.engadget.com/2010/07/08/burger-king-uses-musical-shower-as-latest-trick-to-entice-japa/
A new Burger King eatery opening up in Japan isn’t usually something we concern ourselves too much with, but this one comes with an interesting new twist. Those umbrella-aping translucent cones hanging over the tables are known as “musical showers,” and their function is to deliver music in an isolated fashion to you and your significant — but not too significant, it’s still BK, after all — other. All you’ll need to do is plug your portable media player into the provided receptacle and the tunes you know and love will literally shower down upon you. To be honest, if the audio channeling is sufficiently precise not to disturb nearby punters, we’re loving this idea. Now just give it a name that won’t make teenagers giggle and bring it westwards.
Burger King uses ‘musical shower’ as latest trick to entice Japanese clientele originally appeared on Engadget on Thu, 08 Jul 2010 07:39:00 EDT. Please see our terms for use of feeds.
Source: http://gizmodo.com/5574937/starbucks-is-slowly-reviving-the-coffee-nerding-of-america
The Clover was a nerd’s way to make coffee. Every parameter precisely, digitally controlled, for the most of tweaky of experimentation—or you can make the exact same cup over and over. Then Starbucks bought the company.
What happened next: Waves of independent coffee shops ditched their $10,000 Clover machines, for practical and philosophical reasons. Starbucks rolled them out to 50ish stores across the Northeast, Seattle and San Francisco. Then expansion stopped. That was almost two years ago.
Starbucks’ first Clover showed up in New York around two months ago, in a nearly 20-year-old location that’s been converted into a concept store. The thaw is beginning. Starbucks plans to finally expand the Clover’s footprint gradually over the next 6-8 months, as they figure out how to integrate the machine into the natural rhythm of stores—which is basically dominated by Frappuccinos these days, not coffee.
In a way, it’s a hard sell. The kind of people who would be most interested in coffee made via Clover, designed to pull the most out of a coffee—so shitty coffee would taste shittier—don’t go to Starbucks. Starbucks is so reviled by people who actually like coffee that they’ve experimented with burying the Starbucks name two pilot stores in Seattle which are designed to look more like the kind of place that serves Intelligentsia or Stumptown coffee. So it’s heartening to see them try to live up a bit more to the ideals of caring about coffee and how it’s served.
For instance, while 30 days is what Starbucks considers the expiration date on beans in a store—16 days longer than any self-conscious shop would serve them—if you order a cup made with Clover, you’re far more likely to get beans roasted within the 2-week mark. (In part because there are limited quantities of some coffees served using Clover, like the Jamaica Blue Mountain they’re offering starting tomorrow.)
They’re also making use of their spin on Clovernet, which was one of the big hype points of the machine: Shops and their baristas could share, upload and download recipes for coffees made via Clover. Starbucks pushes recipes for each coffee it serves on the Clover—around 4-6—to stores via a similar network, so there are custom parameters for each coffee. African coffees get a different treatment versus South American ones, as they should.
For all the technology in the Clover, though, it ultimately comes down to the guy (or girl) handling it. Hopefully, it’s someone nerdy enough to know what the Clover was before it landed in front of them at Starbucks.
Nielsen IAG Top Ten Most-Recalled In-Program Placements: Dramas/Comedies
Sex sells … well, sex .. but not much else. Victoria’s Secret was the most recalled product placement on TV — fortunately they sell products related to what was recalled. Not so sure about the mayo and cell phone.
Source: http://adage.com/madisonandvine/article?article_id=143808
![]() |
||||
| Rank | Brand | In-Program Placement Description | Program Airing Info | Recall Index |
|---|---|---|---|---|
| 1 | Victoria’s Secret | Michael interrupts meeting to offer Donna a retail store’s catalog | The Office (NBC, Apr 29) | 214 |
| 2 | Ford | Cole Austin points to his Mustang and says he still owns it | Cold Case (CBS, May 2) | 190 |
| 3 | Skype | Joyce tells Benson and Stabler that she talks to Andrew online | Law and Order: SVU (NBC, Apr 7) | 183 |
| 4 | Yamaha | Susan explains to Mike that she has inherited a piano | Desperate Housewives (ABC, May 2) | 181 |
| 5 | Rolex | Provo tells Fin that Jack stole his watch; member of the cooking staff is wearing it | Law and Order: SVU (NBC, Apr 7) | 178 |
| 6 | MedTec | Name is visible on the ambulance doors | Trauma (NBC, Apr 5) | 176 |
| 7 | Toyota | Mitchell and Cameron park their car at Charlie’s house | Modern Family (ABC, Apr 14) | 161 |
| 8 | Chevrolet | Winston drives with Guerrero, who identifies the car as a Camaro | Human Target (FOX, Apr 7) | 155 |
| 9 | Porsche | Zack asks Nick where he got his car from | Accidentally On Purpose (CBS, Apr 21) | 152 |
| 10 | Chevrolet | Pres. Hasaan rides in a black SUV after turning himself over to terrorists | 24 (FOX, Apr 5) | 147 |
Offermatic Gives You Sizeable Discounts Based on Your Spending Habits
Source: http://lifehacker.com/5532835/offermatic-gives-you-sizeable-discounts-based-on-your-spending-habits
The best discounts are for things you actually buy. Free web service Offermatic uses your credit card, through the same back-end as Mint.com, to offer 40-90 percent discounts on products similar to what you’ve already purchased.
If you’re not squeamish about providing financial information to financial scanning sites like Mint.com, Offermatic is a pretty sweet deal. You register your credit cards with Offermatic through their secure system, which then scans your purchases and spits back out high-discount offers from their advertisers, made to match your interests. You won’t necessarily get coupons for the exact stores you shop at, but the examples seem to be highly related.
Depending on how much you spend, you can also make up to $15 a year back per card (though, to be honest, we’re not about to spend $1,000 a month just to get $15 back at the end of the year, and we wouldn’t recommend you do either). But getting 40-90 percent off some pretty popular stores isn’t bad for a free service. For the folks on the fence about how Offermatic makes their cut, here’s what their FAQ has to say:
- If your service is free, how do you make money?
We make money by saving you money. We get a commission from the advertiser when our users purchase their offer through us.
- Do you sell my personal or individual data?
Never. When we send you an offer from one of our advertisers, it’s based on your anonymous purchase history. Advertisers do not know your name, email address, or location. Only if you choose to purchase an offer will that information be provided to the offer merchant so you can redeem the offer with them. We do not – and will not – provide or sell any personally identifiable information in order to present you an offer.
So, if you’re less than frightened about card-watching sites like Mint or Blippy, Offermatic is a deal you’ll want to take a closer look at.
Comparing Paid Celebrity Endorsements and Natural Search
Maria Sharapova vs Megan Fox
Canon has spent millions of dollars on promoting Maria Sharapova, but no one has spent much money on promoting Megan Fox on television ads. But from the search volume, Megan Fox has far larger search volume (implying people remember her name and search for it) versus Maria Sharapova.
How Google Crunches All That Data
Source: http://gizmodo.com/5495097/how-google-crunches-all-that-data
If data centers are the brains of an information company, then Google is one of the brainiest there is. Though always evolving, it is, fundamentally, in the business of knowing everything. Here are some of the ways it stays sharp.
For tackling massive amounts of data, the main weapon in Google’s arsenal is MapReduce, a system developed by the company itself. Whereas other frameworks require a thoroughly tagged and rigorously organized database, MapReduce breaks the process down into simple steps, allowing it to deal with any type of data, which it distributes across a legion of machines.
Looking at MapReduce in 2008, Wired imagined the task of determining word frequency in Google Books. As its name would suggest, the MapReduce magic comes from two main steps: mapping and reducing.
The first of these, the mapping, is where MapReduce is unique. A master computer evaluates the request and then divvies it up into smaller, more manageable “sub-problems,” which are assigned to other computers. These sub-problems, in turn, may be divided up even further, depending on the complexity of the data set. In our example, the entirety of Google Books would be split, say, by author (but more likely by the order in which they were scanned, or something like that) and distributed to the worker computers.
Then the data is saved. To maximize efficiency, it remains on the worker computers’ local hard drives, as opposed to being sent, the whole petabyte-scale mess of it, back to some central location. Then comes the second central step: reduction. Other worker machines are assigned specifically to the task of grabbing the data from the computers that crunched it and paring it down to a format suitable for solving the problem at hand. In the Google Books example, this second set of machines would reduce and compile the processed data into lists of individual words and the frequency with which they appeared across Google’s digital library.
The finished product of the MapReduce system is, as Wired says, a “data set about your data,” one that has been crafted specifically to answer the initial question. In this case, the new data set would let you query any word and see how often it appeared in Google Books.
MapReduce is one way in which Google manipulates its massive amounts of data, sorting and resorting it into different sets that reveal new meanings and have unique uses. But another Herculean task Google faces is dealing with data that’s not already on its machines. It’s one of the most daunting data sets of all: the internet.
Last month, Wired got a rare look at the “algorithm that rules the web,” and the gist of it is that there is no single, set algorithm. Rather, Google rules the internet by constantly refining its search technologies, charting new territories like social media and refining the ones in which users tread most often with personalized searches.
But of course it’s not just about matching the terms people search for to the web sites that contain them. Amit Singhal, a Google Search guru, explains, “you are not matching words; you are actually trying to match meaning.”
Words are a finite data set. And you don’t need an entire data center to store them—a dictionary does just fine. But meaning is perhaps the most profound data set humanity has ever produced, and it’s one we’re charged with managing every day. Our own mental MapReduce probes for intent and scans for context, informing how we respond to the world around us.
In a sense, Google’s memory may be better than any one individual’s, and complex frameworks like MapReduce ensure that it will only continue to outpace us in that respect. But in terms of the capacity to process meaning, in all of its nuance, any one person could outperform all the machines in the Googleplex. For now, anyway. [Wired, Wikipedia, and Wired]
Image credit CNET
Memory [Forever] is our week-long consideration of what it really means when our memories, encoded in bits, flow in a million directions, and might truly live forever.
About Me
Tags
Popular Posts
- HP Mini 311 Nvidia ION Netbook Hackintosh'ed
- Facebook advertising metrics and benchmarks
- When NOT to use Groupon (as an advertiser)
- How-To View Gmail for iPad on Your Regular Computer - Chrome and Safari
- social media benchmarks
- What is Web 3.0? Characteristics of Web 3.0
- Facebook's Security Check Asks Users to Identify Photos of Friends' Dogs, Gummi Bears
- Vapor4 May Be the First Bumper Worthy of the iPhone 4
- Two Social Success Stories - Groupon and FourSquare
Recent Posts
- ‘we are prioritizing our Android platform’
- 1531
- 1529
- 1527
- HP Labs teams up with Hynix to manufacture memristors, plans assault on flash memory in 2013
- Amazon planning subscription video service to challenge Netflix and Hulu?
- It’s Time To Make Standardized Ratings For Gadgets
- Arcade Fire and Google Pushing HTML5 Together
- New ARM architecture (likely Eagle) better suited for OS virtualization
- view movie service by end of 2010, says Financial Times
Recent Articles by Dr. Augustine Fou
- Augustine Fou | ClickZ
- ClickZ Welcomes Augustine Fou | ClickZ
- The ROI for Social Media Is Zero | ClickZ
- A New Definition of 'Digital' | ClickZ
- Social Commerce: In Friends We Trust | ClickZ
- 10 Commandments of Modern Marketing | ClickZ
- Digital is the DNA of All Advertising | ClickZ
- Experiential Marketing | ClickZ
- Social Intensity: A New Measure for Campaign Success? | ClickZ
- Beyond Targeting in the Age of the Modern Consumer | ClickZ
Pages
Archives
- September 2010 (6)
- August 2010 (101)
- July 2010 (61)
- June 2010 (28)
- May 2010 (28)
- April 2010 (26)
- March 2010 (33)
- February 2010 (21)
- January 2010 (12)
- December 2009 (4)
- November 2009 (2)
- October 2009 (14)
- September 2009 (6)
- August 2009 (19)
- July 2009 (34)
- June 2009 (11)
- May 2009 (4)
- April 2009 (6)
- March 2009 (13)
- February 2009 (32)
- January 2009 (25)
- December 2008 (1)
- October 2008 (1)
- November 2007 (1)
















