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As someone who leads an analytics team in the advertising industry I have to say this title and the studies they are referencing are not accurate to the entire industry at all.

Advertising absolutely works when done right. The effect on brand consideration, shopping behavior, and incremental purchase value can be quantified. The most sophisticated advertisers spend a lot of money to accurately track and ensure their campaigns are lifting their desires metrics.

Now to the eBay study they reference. That study is specific to eBay, a large brand that has spent hundreds of millions a year on advertising for many years and is a top web property visited by a significant percent of the online audience. For eBay it turns out brand search marketing largely does not have a contribution as most of their shoppers are likely going to buy anyway.

Trying to generalize that to a brand that did not have the amount of equity, natural SEO rankings, and established shopping behaviors would be foolhardy. Additionally if you dig deeper into the eBay study they did find a positive effect for the small percent of users that are new shoppers to eBay. They just happen to be a relatively small percent of the audience reached with the spend given the large size of eBay.

In the digital space there is a huge variability in performance based on the type of ad, the nature of the targeting, the product being advertised, the creative message, etc. Trying to generalize to all online advertising without controlling for the kind of brand, product being sold, current marketing positioning, and campaign objective seems a bit naive.

In our work we find huge variability in performance even within the same web property dependent on the placement of the ad within the site and the unit being served. We measure how long the ad was on the page, how many users actually hovered over it in view, and then the incremental lift of exposed users compared to control group. Turns out if you properly optimize to maximize true ad viewing and engagement you will see lifts in brand response, digital visitation, and shopping metrics compared to the control.

In fact I'd much rather have money for digital advertising any day over old fashioned ads with the limited tracking possible. I know how many people saw our spot on the YouTube home page, how long they spent interacting with it, and can tell you exactly what they were interested in. For that TV spot I don't know if you were watching, skipping, going to the bathroom, looking at your phone, or any number of other factors which could diminish effectiveness.

TLDR; online advertising works when done correctly and absolutely can be measured

Is it possible to bring in your own data sets? It seems the more interesting algorithms would be those that merge the pure financial volume data with outside sources like news, social data, weather patterns, or other predictors relevant to individual stock prices.

I do data mining work (not in finance) and often the best signal is the one missing. Often more prediction value is gained from additional feature construction and the layering of more interesting data sources onto the problem than simply a better algorithm on the data at hand.

Concur with this comment -- it might also help the community provide feedback on structure and ways to segment that data so that there are more directed efforts to consume small parts of the crawl for processing

Quantcast will only see web traffic and create estimates from their panel + live cookie data. A lot of Twitter's usage is via mobile or API which will not be reported in these numbers.

Wow this is amazing! In the real world data can be messy and this looks like a great tool to transform it without an extensive custom ETL process that requires code

For those curious Expedia actually captures a stupendous amount of information down to session level activity. They can play back failed sessions to discover areas of opportunity. This was discussed at an analytics conference I attended on how they implement testing across a range of systems to find possible areas of friction and improve the business.

They might find other ways to monetize it through ads outside of Facebook. So the experience inside Facebook could remain more pure but then advertisers would pay to know they are definitely reaching an audience with a certain message. Last I saw they were nearing $2B in ad revenue and they have not fully tapped the larger potential.

I'm sorry -- as an advertiser who manages large budgets the claim that a global network with rich audience data and precise targeting is worthless is quite silly and not in touch with the reality of most online business models.

Google is currently the king but Facebook is building the hooks to make it an even larger force for ad revenue.

People want to get ahead so what matters is the % relative to your surroundings. The amount doesn't matter as much as purchasing power. Money is illusory anyway -- just a social contract we agree to as a mechanism of exchange. People want expansion in various ways whether it is more money, more status, more goods, more sex, or even more religiousness. You can't stop that.

As to effectiveness -- that is dependent on your personal goals. Some people are very effective at chilling out and not doing much. Others are very effective at building business, or playing a sport, or programming, or whatever. Dependent on what you want emulate the ones succeeding in that and you will be "effective"

It would depend on how your system is setup.

In Google Analytics you can enable "e-commerce tracking" for the profile that contains your payments.

Then whenever a new payment is made you can make a call to GA and record the transaction.

Check here for more info: http://www.google.com/support/googleanalytics/bin/answer.py?...

Not that accurate -- a better method is to use the Google keyword tool and numbers you have internally on response rates. You will get a more accurate range that way.

Of course, relevancy of the ad to the keyword is the critical factor. If your ad or service is not appropriate to the keyword then you cannot expect a good response rate.

I agree the most important thing is great rank worthy content.

However, if you build that content all in flash, setup your robots.txt incorrectly, or any of a number of other technical snafus then you can screw up your rankings. Hence why it is important to be setup in the right way for the search engines to find you. Otherwise you will miss out on on most of the traffic.

I've done full SEO campaigns with larger budgets and currently manage millions of paid media on search engines and other places.

SEO is about two things -- site architecture and correct promotion.

Many people can help you with the fundamentals of getting your site together but most of the action is in marketing your site and frankly, having a good site and product that people want to talk about.

Beware of tricks and claims of performance. Many people can do things to manipulate your ranking in the short run but you will be punished long run. Think quality content and alignment with your target audience and you will be fine.

As someone who does this for a living it is not that it wasn't being taken advantage of but that the technology to do it at scale easily was not there -- and still isn't really.

Think about this -- you run an online campaign, serving hundreds of millions to billions of impressions, with different levels of users creating different interactions with your ads, website, etc and a certain percent "converting" to the action you want. How do you reliably process hundreds of millions to billions of rows of data and tie it together? What factors are reliable predictors of future actions? If you increase one aspect does it correlate with other efforts increasing? If there is a flaw in the data collection, how do you spot it?

What about offline behavior? Can you correlate interaction with a widget with store purchase behavior? A lot of activity happens that can never be tracked and it needs to be factored into the models.

So the point being when you dig deep it is not as simple as it seems and there is still a long way to go for all of the technology to work well together and provide the analysis needed to react in real time and change human behavior for the desired result.

If you want to explore a full range of meditation techniques, check out Osho's "The Book of Secrets". It explains the 112 methods from one of the ancient texts describing the various methods of meditation (or dhyana in sanskrit).

Read through it, try a few, see what works for you. Different techniques work for different people.

The best is to learn in a live environment from a trained teacher. I recommend Isha Yoga (www.ishafoundation.org) They have a program called "inner engineering" which imparts a yogic practice which is quite effective at lowering stress and bringing clarity to the mind. There have even been some scientific studies looking at changes in the brain through doing the practice.

If you want to do something about it, this is an organization that has global programs to feed and help save starving children around the world:

http://www.worldvision.org/

You can also check out http://www.care.org/

How about this for a startup idea -- software tools to help empower non-profits to help those around the world. Tools to help them communicate together, coordinate logistics, respond where aid is needed best.