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
I've said this before on here, but online advertising is incredibly dumb. If you consider all the info Google and Facebook have on me, it's a really sad state of affairs.
I bought a new bicycle and religiously researched this topic and consumed a ton of cycling videos. What ads do I see on YouTube? Cars. I don't have a driver's license.
I once bought a NI Maschine Midi Controller. YouTube then showed me video ads for the NI Maschine Midi Controller for over a year after the purchase. Great business for Google, not so much for Native Instruments.
During a vacation in South Korea, I had logged into Facebook to post a picture. Facebook then showed me Korean ads in Hangul for over a month after my return. They have all the info on me, where I was born, what language I speak, where I live, where I work. Hilariously bad.
1.If you have never visited a car company's website then it's just that Google categorized your profile wrongly and only the car companies are bidding for you when it comes to show an ad.
2. Just a company wrongly retargeting converters (people who have bought a product) with the same product that they have bought.
3. In Real Time Bidding [1] for Facebook, their information about the user is very much lacking [2] so depending on the advertiser that bids you might get very bad ads.
It's a game of averages - what you're doing is watching a blackjack game and saying "why on earth didn't you double down on that 18, the next card was a 3!"
Sure there's a lot of errors in advert targeting, but they don't need 100% accuracy to see results, and on a scale from "just chuck adverts at everyone, some will be relevant" to "let's have people manually look into every user to profile them and know exactly what to target them with" there has to be a point where it's not cost-effective to make things even more accurate.
No advertising "absolutely can be measured" because no one has access to time machines nor alternate universes to see what a consumer would have done without the advertising. This is a simple fact. Of course, when you can invent your own criteria ("brand consideration," "shopping behavior," "incremental purchase value,"), you can't be wrong.
One of the corner stones of their article is that in order to measure the lift on the ROI of an ad the sample sizes need to be incredible large - mainly due to noise and large variances.
The metrics/measure you mention are helpful but very limited. Since, IMHO the ROI is the most important metric for an advertiser.
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.
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.
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.
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"
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.
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