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.