I may be showing my age a bit, but I remember the days where
spam emails completely filled everyone's email box. Although my inbox was never quite as bad as the picture below, I do remember that a majority of emails were of the 'un-wanted' variety.
I will admit that probably one of the reasons for the horrible percentage of spam was the fact that I was a
hotmail user at the time. Hotmail had a
notoriously bad spam filter several years ago and it caused me to switch to Gmail. Prior to our class this week, I never really thought much about spam emails as I do not see them as much anymore in my inbox. But how as Gmail and the others been able to nearly eliminate the spam? I had to do some research.
It turns out that with three different strategies, much of the spam can be eliminated. The first is called
'Machine Learning'. The idea here is that the computer is trained to figure out which messages are spam and which messages are not. By recording various characteristics and the result of whether an email is spam, we can allow the computer to 'learn' which emails are spam.
Another way of identifying spam is by looking for
trigger words in the subject or the body that are used by spammers.
Finally, as users, we can help the spam filters by clicking on the 'Spam' button on our web email. As it turns out, all
three of these approaches are being used by Google's
Gmail email service. As can be seen below, the spam filters have been working well to reduce the missed spam as well as the false positives despite the fact that the amount of spam email traffic is over 50% for the past 7 years.
Why is this important for internet marketing? I would argue that the improvement in the spam filter means that the ethical and solicited emails that are requested by your customers are getting delivered and consumed at a higher rate. The odds that an email is read when it is surrounded by unsolicited emails would tend to result in many missed opportunities. Now, however, if your solicited email to a possible customer, it will more likely be read. Thanks spam filters!