When we pick up a newspaper, we are looking for the maximum information
content. So, naturally, more surprising events make
for better news. And in passing, as you read the news, you
and I glance at some advertisements, and the paper makes some money.
Of course, the questions the newspaper needs to ask is, when to place an ad, and
where to place an ad? Which newspapers against which stories?
Unfortunately print newspapers just don't have that freedom.
Sometimes the interesting news is on the sports page, whereas your most expensive
ad is right up front. To understand how better advertising
model, in particular online advertising, is related to information theory, let's
first see what Shannon did with his concept of information being related to
surprise. Shannon was concerned with communication
along a noisy channel, like a telephone line or the radio waves on the air.
Today he'd be concerned about communicating on the internet.
But of course the internet wasn't there in his times.
The model that he used was the transmitted signal at one end of the channel.
It could be a sequence of messages or, today, a sequence of bits received on the
other side as another sequence of messages.
There's an important concept that he defined called the mutual information
between the transmitted signal and the received signal.
And the purpose of the channel, these days the cell phone network or the internet is
to maximize the mutual information between what is transmitted and what is received.
So obviously, you really want to hear what your friend is saying at the other end of
the line. Now let's model the advertising problem in
the language of communication along a noisy channel.
The advertising context we approach, the newspaper or webpages with some intent.
And some degree of attention and interest. And the advertiser would like to measure
which pages we are interested in and when we have an intention to buy.
Unfortunately for normal print or media advertising, the only signal available to
an advertiser is the actual sales transactions at the end of a quarter or
the ad revenue that one spends and after the fact, correlation of the two is all
that one is really able to do. This is highly erroneous and so the mutual
information between our actual intent and attention and the lag measures, which come
much later of sales transactions or advertising revenue incurred is very low.
In other words, it's very difficult to predict which paper to advertise in.
And on which page do advertising simply based on this signals.
The online world of course changes everything.
Because the signals we have are the clicks made by users, the queries made when they
search, and the actual content that they are reading.
The mutual information therefore is much higher.
Let's see how. A brief overview of online advertising
first. In the case of search advertising
advertisers bid for keywords in Google's online keyword option, which is happening
continuously all the time. The highest bidders ads are place against
the matching searches, so if y bid for shoes and you searched for shoes and mine
was the highest bid, then my ad would come up against your query and so on.
The actual auction mechanism is a bit more complex than that, but we won't go into
that right now. The result of this advertising model is
that the mutual information between the advertising dollars, spent, and the sales
that they translate into is improved considerably from traditional media, and
is fundamentally responsible for the success of online advertising.