Another problem I'm going to introduce now, and
in the next lecture I'm going to show you some details about it.
So let's take a look at how Online Advertising works on the web.
Basically these are the websites that you all browse, too.
These are all of the online ads that you see, the pop-ups, the ads that chase
you and follow you after you put a product in the shopping cart.
And what companies can do when they show you these ads, they need to make a choice,
do they show the ads to you, or do they show the ads to a different consumer?
And also what they can do is, they can say,
I wanna show one consumer the same ad but on multiple websites.
If this consumer visits Yahoo.com and eBay.com and Amazon.com and
CNN.com, I'm gonna show the same ad to the same consumer,
and these ads are gonna chase this consumer.
Now because it is very,
very hard to tell if those ads actually impacted the consumer's decision to buy
a product, what companies do is they do something called attribution.
At the end of the process, they try to measure what was the impact of each ad
on the consumer's decision to purchase.
One simple way to do that is to say, did the consumer click the ad?
If consumers click the ads more, probably the ad have more impact.
And what companies are trying to measure is something called click-through rate,
which is, basically, if I showed this ad to 100 consumers,
how many of them are gonna actually click the ad?
And this ratio of the number of consumers that clicked to the number of consumers
that have seen the ads is actually the click-through rate of the ad.
So let's see an example.
What you see in this graph is basically how advertisers analyze data online.
What they say is, they say, I'm gonna show these ads
to the same consumer on different Channels or different websites.
On the x-axis you'll see
is the number of Channels that showed an ad to the same consumer.
So some consumers have seen 0 ads, just didn't see any ads.
Some consumers have seen 1 ad, some consumers have seen ads on 2 websites,
some consumers have seen ads on 3 websites.
And on the left hand side, we see the click-through rate.
What is the probability or
the percentage of consumers that actually clicked on the ad?
So if you see no ads, you don't click on ads.
That's great, that's perfect.
And it will appear from this analysis that if you show more and
more ads to the consumers on different website,s they click more and more ads.
The probability of clicking goes higher, which would imply
that actually those ads become more and more impactful the more ads you show.
In the next lecture, what I will show you is how you can analyze this data,
and try to understand does this model make sense?
Does showing more and
more ads to a consumer actually increase the probability of them clicking the ads?