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Speaker 1: Get in touch with technology with tech Stuff from how

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Speaker 1: stuff works dot com. Hey there, and welcome to tech Stuff.

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Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer and

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Speaker 1: how Stuff Works and I love all things tech and

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Speaker 1: tech stuff. Listener Wrath wanted me to do a show

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Speaker 1: about web analytics, and specifically about web analytics and your

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Speaker 1: personal data. Your data being the general you out there,

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Speaker 1: like how much of your personal data gets wrapped up

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Speaker 1: in web analytics. This is actually a really big topic,

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Speaker 1: so I'm going to take a couple of episodes to

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Speaker 1: cover it, and this first one we're gonna talk just

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Speaker 1: about web analytics, what they are, why they are necessary

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Speaker 1: in the web that we know and love today, And

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Speaker 1: in the next episode, I'll go more into detail about

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Speaker 1: the sort of data that they can gather are about you.

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Speaker 1: So there's a lot to consider. Some of it gets

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Speaker 1: a little technical, but we're gonna go light on that.

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Speaker 1: Will will explain what the technical aspects are, but we

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Speaker 1: won't get too bogged down because it would involve talking

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Speaker 1: about lines of code and that would get pretty awkward

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Speaker 1: without visual aids. Uh. A lot of this can get

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Speaker 1: a little scary because web analytics are valuable, and they

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Speaker 1: really do chip away at your privacy. But let's start

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Speaker 1: from the top. What are web analytics. Well, at their

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Speaker 1: most basic level, web analytics would be a collection of

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Speaker 1: tools and strategies that allow people to collect and measure

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Speaker 1: Internet data, specifically user generated Internet data, typically as a

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Speaker 1: way to understand user behavior, and that is done so

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Speaker 1: that the website owner can optimize experiences and leverage that

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Speaker 1: user behavior in some way that ultimately corresponds to making money.

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Speaker 1: If I'm gonna be and entirely honest about this, it's

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Speaker 1: all about figuring out how to make the most compelling

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Speaker 1: experience to maximize the most return on an investment, that

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Speaker 1: investment being the time, money, and effort you put in

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Speaker 1: to creating a website. So this is not necessarily the

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Speaker 1: owner of the website and might be the advertising company

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Speaker 1: that brokers deals with various companies to place ads on websites.

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Speaker 1: But somewhere there's a person who's analyzing, or more likely

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Speaker 1: a system that's analyzing this information in an effort to

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Speaker 1: maximize that return. Now, in many ways, this is kind

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Speaker 1: of following a long tradition that's been effective in meat space,

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Speaker 1: you know, in the real world. If you go to

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Speaker 1: a brick and mortar shop regularly, you've probably noticed that

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Speaker 1: sometimes stuff gets moved around the shop might reorganize. Most

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Speaker 1: of the time, this is because the shop owners are

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Speaker 1: trying to change things up in order to encourage more purchases.

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Speaker 1: So grocery stores are a great example of this. The

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Speaker 1: layout of your basic supermarket in the United States tends

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Speaker 1: to be fairly standard. No matter what type of store

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Speaker 1: you go to. It could be a Kroger or a Wegman's,

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Speaker 1: or a Whole Foods or a Piggy Wiggly or a

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Speaker 1: safe Way or whatever, they all tend to have a

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Speaker 1: similar layout. So you walk in, you probably will see

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Speaker 1: flowers very frequently grocery stores and supermarkets. While flowers near

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Speaker 1: the entrance, this sets a pleasant scene. It reminds people

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Speaker 1: of freshness, bright colors. Behind that you typically find the

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Speaker 1: produce that contains fruits and vegetables and vibrant colors, and

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Speaker 1: that again engages your senses. It makes you think of

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Speaker 1: the food is being fresh. Over in the bakery section,

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Speaker 1: you've got an area which typically creates a lot of

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Speaker 1: very pleasing smells that will often make you feel hungry.

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Speaker 1: That means that when you're hung greet you you tend

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Speaker 1: to buy more than what you need. Right. So, if

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Speaker 1: you've ever had this experience, you know what I'm talking about.

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Speaker 1: You go into the grocery store, you've got a list,

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Speaker 1: You've got three things on your list, You walk by

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Speaker 1: that bakery. Next thing you know, you're in the checkoutline

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Speaker 1: with eight things in your cart. Instad of the three

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Speaker 1: things that you had planned. Happens to the best of us,

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Speaker 1: and it happens by design, by the design of the

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Speaker 1: grocery stores. They people figure this out. They said, well,

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Speaker 1: let's put this here because we'll make more sales. This

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Speaker 1: has all been studied, by the way. I'm not just

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Speaker 1: spit balling here. This is why grocery stores are laid

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Speaker 1: out the way they are. Uh. You also see this

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Speaker 1: in various types of box stores where the big ticket,

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Speaker 1: very popular items, maybe very far from the entrance that

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Speaker 1: requires you to walk through the rest of the store

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Speaker 1: in order to take a look at those things. These

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Speaker 1: areas that have a high interest level, and the hope

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Speaker 1: is that along the way you'll see something else that

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Speaker 1: catches your eye and you'll pick that up. To Now,

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Speaker 1: stores will experiment with where certain products should sit on shelves.

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Speaker 1: Sometimes you might display one product a shelf higher than

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Speaker 1: what it was on before, and that's all it will

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Speaker 1: take to move more units. Large chains might use certain

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Speaker 1: stores as test sites and they'll work on a new

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Speaker 1: layout configuration on this test site to see how well

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Speaker 1: it plays out in that market before they make a

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Speaker 1: decision about whether or not they'll roll it out to

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Speaker 1: everybody else. This is essentially what we call a B testing.

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Speaker 1: So a B testing is something that you see in

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Speaker 1: website design where you've got someone creating a website layout

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Speaker 1: typically and they deploy that layout so that some users

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Speaker 1: when they come to visit the site, see version A

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Speaker 1: of a website. Some users see version B, and then

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Speaker 1: they analyze the behaviors of users on A versus B

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Speaker 1: and see if there is a measurable difference in behaviors

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Speaker 1: so that you can determine well, it turns out that

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Speaker 1: version A people are not sticking around very long, the

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Speaker 1: version B people are engaged much more with the content

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Speaker 1: of the website. So this is a way of testing

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Speaker 1: out different approaches, different design layouts in order to determine

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Speaker 1: what is the most effective one. And it's the same

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Speaker 1: thing that we see in the real world. Uh, they

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Speaker 1: scrutinize web ALEXA is scrutinized Internet user behavior to get

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Speaker 1: a deeper understanding of what people want and what they

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Speaker 1: like so that website designers and advertisers can tweak their

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Speaker 1: approaches to tap into that and get the best result.

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Speaker 1: That result might be to get people to subscribe to

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Speaker 1: a service, to purchase products, to support a nonprofit, or

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Speaker 1: just spend more time on the web page. So let's

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Speaker 1: talk about how this might play out using actual web

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Speaker 1: pages as an example. And I'm going to use how

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Speaker 1: Stuff Works dot Com as an example because I used

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Speaker 1: to write articles for that site and I was in

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Speaker 1: meetings where we were talking about site design and what

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Speaker 1: was in iportant and the elements that we're going to

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Speaker 1: go into play and how that was going to change things.

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Speaker 1: And so I've seen a lot about the ways that

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Speaker 1: people will analyze traffic data and try to use that

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Speaker 1: to help guide decisions for form and content. So How

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Speaker 1: Stuff Works, like many websites, generates revenue from ads placed

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Speaker 1: on the page. This is at the very heart of

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Speaker 1: why web analytics are so important. It's because of the

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Speaker 1: revenue model for making money on the web. The very

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Speaker 1: hard and soul of that is web advertising. So ads

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Speaker 1: can be based on a per click basis. That means

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Speaker 1: the advertiser only pays the web page for the actual

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Speaker 1: number of clicks the ads generate. So if the ads

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Speaker 1: do not get many clicks, the web page does not

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Speaker 1: make very much money. There are other variations of this,

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Speaker 1: but it's a general approach. There are things that you

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Speaker 1: can do to help engage more clicks. The positioning of

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Speaker 1: the ad on the web page but comes really important.

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Speaker 1: But the other important element is making sure the ads

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Speaker 1: actually appealed to the site's users. If you have a

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Speaker 1: fan page set up for a cartoon show, for example,

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Speaker 1: and you show ads that are for a professional video

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Speaker 1: conferencing service for medium to big businesses, that might not

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Speaker 1: get very many clicks because the ads that you're displaying

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Speaker 1: don't necessarily appeal to the audience coming to your website. Now,

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Speaker 1: the other approach besides this per click basis is to

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Speaker 1: have a fixed rate ad. Now, these ads have a

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Speaker 1: set rate, as I just mentioned, and typically that is

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Speaker 1: defined as per impressions or page views. So if you

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Speaker 1: hear people talk about impressions, they're really talking about how

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Speaker 1: many times has a device loaded that page. That is

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Speaker 1: an impression. The more page views a site gets, the

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Speaker 1: more money it will make off the ads that are

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Speaker 1: on those pages. And typically we measure this in the

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Speaker 1: thousands using the unit CPS. That's cost per meal meal

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Speaker 1: being one thousand m I L l E. So it's

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Speaker 1: not one million, it's one thousand. So if a website

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Speaker 1: charges advertisers or rate of two dollars CPM, that means

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Speaker 1: the advertiser will pay the publisher two dollars for every

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Speaker 1: one thousand impressions or page views that page generates that

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Speaker 1: has the ad on it. Right, So the ideas that well,

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Speaker 1: we've we've shown that this page has been loaded one

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Speaker 1: thousand times. Uh, that means your ad has been viewed

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Speaker 1: one thousand times on on various devices, not necessarily by

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Speaker 1: one thousand people, because if you have a website that

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Speaker 1: reloads frequently for some reason or another, then those uh,

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Speaker 1: those impressions could represent fewer than a thousand people, but

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Speaker 1: it would still be one thousand impressions you would get

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Speaker 1: the two dollars. Page Views and people are two very

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Speaker 1: different things. If you can rack up a large number

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Speaker 1: of page views with a limited number of people, that

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Speaker 1: still counts towards CPM. And this is why so many

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Speaker 1: web pages have things like quizzes or image galleries or

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Speaker 1: slide shows. Each time the page refreshes to give you

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Speaker 1: a new question or a new hilarious cat meme, that's

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Speaker 1: an impression. That's a page view. So if you've ever

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Speaker 1: gone to an article where it's not really an article,

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Speaker 1: it's a slide show and you have to click next

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Speaker 1: after each thing. This is largely why because it's a

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Speaker 1: way to engage the user to keep on clicking through

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Speaker 1: and refreshing the page, and it's a way to generate

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Speaker 1: those impressions. And the math is simple. Why would you

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Speaker 1: create a web page with the top twenty comedy movies

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Speaker 1: of all time and you put it all on one

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Speaker 1: page so you get one impression per visitor when they

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Speaker 1: come in to read your article. Or you could do

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Speaker 1: the smart thing, you create a slide show, and you

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Speaker 1: could potentially get twenty page views per visitor. Now, not

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Speaker 1: every visitor is going to stick around for all twenty items,

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Speaker 1: but even if they only show up and bounce, like

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Speaker 1: they see the first page and they see, oh, this

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Speaker 1: is a slide show, I don't want to use this,

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Speaker 1: and they go away, You're not gonna get fewer impressions

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Speaker 1: than if they were all on the same page. Right.

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Speaker 1: If you attract ten thou people, let's say, to your

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Speaker 1: one page version of the top twenty movies comedy movies

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Speaker 1: of all time, and they read the whole thing, that's great.

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Speaker 1: If you attract ten thousand to your slide show and

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Speaker 1: eight thousand of them just look at that first page

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Speaker 1: and they leave, but the other two thousand start clicking

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Speaker 1: at least a little bit, You've generated more than ten

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Speaker 1: thousand impressions. So it is a strategy that works, which

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Speaker 1: is why you see it out there now. I am

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Speaker 1: not a huge fan of that particular type of web

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Speaker 1: design from a user perspective, but from a business perspective,

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Speaker 1: I totally get it. It's a page view manufacturing machine,

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Speaker 1: and if the industry depends upon page views as a

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Speaker 1: way of measuring engagement and therefore tied to revenue, then

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Speaker 1: finding ways to maximize page views is always going to

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Speaker 1: be a priority. It's not necessarily the quality of the interaction,

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Speaker 1: but the quantity the number of impressions. However, quality can

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Speaker 1: matter too, and that's because websites have to first figure

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Speaker 1: out how much do they charge for those CPMs. You know,

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Speaker 1: I gave that two dollar figure, but that was just

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Speaker 1: a random example. A site that can demonstrate that its

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Speaker 1: users feel they're getting a really good quality experience can

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Speaker 1: typically demand much higher rates than other sites. If you

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Speaker 1: have a lot of traffic coming to your website, and

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Speaker 1: you can also demonstrate that the people who come to

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Speaker 1: your website are really engaged, they really stick around. They

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Speaker 1: often will explore the website or stay on pages for

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Speaker 1: a very long time. That shows that you have a

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Speaker 1: higher value you then a website that might get a

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Speaker 1: lot of people coming in, but then immediately they leave.

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Speaker 1: So this ties into a concept called bounce rate I

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Speaker 1: mentioned bounce earlier. Bounce rate refers to the percentage of

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Speaker 1: website visitors who leave or bounce after viewing just one page,

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Speaker 1: like a landing page or a home page. You want

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Speaker 1: your bounce rate to be really low because you want

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Speaker 1: visitors to be engaged in your site. You want them

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Speaker 1: to not just come to the landing page, but maybe

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Speaker 1: click on some of the links that go to other

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Speaker 1: pages in your website, and it shows that your site

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Speaker 1: has value. Plus, chances are you want people engage because

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Speaker 1: you put a lot of work into a website, and

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Speaker 1: it would be depressing if no one ever went beyond

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Speaker 1: a single page view. You know, why would you go

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Speaker 1: through the trouble of designing a fully engrossing website when

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Speaker 1: everyone just comes to one page on that site and

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Speaker 1: then they say, no, I'm out of here. That would

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Speaker 1: be really upsetting. And so a low bounce rate tends

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Speaker 1: to look really good to advertise. There's this is a

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Speaker 1: signal that says users value their time here, and so

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Speaker 1: you're advertising will be featured on a really good website.

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Speaker 1: And again, another important quantity to measure is the amount

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Speaker 1: of time people will spend on a web page. Do

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Speaker 1: you want that number to be high so you want

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Speaker 1: the bounce right to be low. The amount of time

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Speaker 1: spent on a web page to be high. That shows

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Speaker 1: people are spending more time on your service. That's attractive

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Speaker 1: to advertisers. It's a great way to demand higher CPM

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Speaker 1: rates if you can demonstrate that users come to your

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Speaker 1: site and spend a lot of time there. For one

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Speaker 1: thing that tells advertisers your site is a good spot

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Speaker 1: to reach people. If the time spent on your pages

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Speaker 1: is low. That might tell advertisers, hey, you know, maybe

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Speaker 1: don't put ads here because no one is spending enough

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Speaker 1: time on an individual page to even register that there

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Speaker 1: is an ad. If the average time spent on a

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Speaker 1: page on your site is half a minute or less

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Speaker 1: and you have lots of long articles, that indicates that

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Speaker 1: most users aren't actually reading the content you've created, and

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Speaker 1: that is not a good thing. So you want your

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Speaker 1: once right low. You want the amount of time you

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Speaker 1: spent spent on an individual page on your site to

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Speaker 1: be high, and that will keep advertisers interested in your

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Speaker 1: site as a place where ads may be most effective.

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Speaker 1: Beyond that, knowing that your users like one thing over

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Speaker 1: another in general is really helpful because it can help

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Speaker 1: you match up advertisers that are most appropriate for your demographic. Again,

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Speaker 1: let's going back to that fictional fan page I talked

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Speaker 1: about creating a fan site for a cartoon show. Let's

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Speaker 1: say you've done that and you've got great engagement, You've

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Speaker 1: got a really low bounce rate. People are spending a

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Speaker 1: good amount of time on your page and they're exploring

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Speaker 1: the various links on there. Then maybe you reach out

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Speaker 1: and you find an online store that sells merchandise related

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Speaker 1: to the show that your site is a fan site of.

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Speaker 1: That's a no brainer. That's a perfect relationship, and you

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Speaker 1: could probably demand decent CPMs for that, and ideally everyone benefits.

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Speaker 1: The advertiser gets a good spot to show ads, visitors

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Speaker 1: to the website have the opportunity to purchase merchandise related

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Speaker 1: to the show they love, you earn money from the impressions.

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Speaker 1: That's the idea. So generally speaking, it's not the worst

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Speaker 1: thing in the world, right this web analytics. It's the

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Speaker 1: idea of not just the advertising part, although that plays

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Speaker 1: a big part of this, but also what do my

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Speaker 1: users like? And how can I make my website more

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Speaker 1: of what my users like? How can I get rid

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Speaker 1: of stuff they don't like? How can I emphasize stuff

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Speaker 1: they do like and make a better experience so that

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Speaker 1: the work I put in is rewarded and I feel

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Speaker 1: good about what I've done, right, Like, I feel a

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Speaker 1: sense of accomplishment because I've created something that people value. Uh,

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Speaker 1: It's a very powerful feeling. Now, I got a lot

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Speaker 1: more to say about web analytics, but before I get

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Speaker 1: into any more of that, let's take a quick break

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Speaker 1: to thank our sponsor. Right to actually measure stuff like

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Speaker 1: bounce rate, time spent on pages, user preferences. We rely

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Speaker 1: on web analytics, and there are companies that specialize in

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Speaker 1: providing web analytics tools. Google is one of the big ones. Uh.

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Speaker 1: These services provide a ton of information to website owners

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Speaker 1: to help them keep an eye on how things are

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Speaker 1: going and how to react nimbly when an opportunity or

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Speaker 1: a crisis arises. The web analysis depends not only on tools,

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Speaker 1: but also some assumptions, and one of those assumptions is intent.

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Speaker 1: When you look at an analysis, you are assuming that

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Speaker 1: the behavior you're studying was intentional. So let's say again,

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Speaker 1: let's let's start with how stuffworks dot com. That site

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Speaker 1: has a lot of individual pages, hundreds hundreds of pages.

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Speaker 1: There are thousands of articles about all sorts of different subjects,

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Speaker 1: from technology to culture, to finance, everything else. There's a

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Speaker 1: home page which features links to new articles. There's probably

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Speaker 1: older articles up there that are maybe timely because of

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Speaker 1: something that's going on in the news, or maybe there's

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Speaker 1: some classic articles that are mixed in because they've consistently

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Speaker 1: performed well over time, so they're they're dependable whatever the case.

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Speaker 1: There are several links on the homepage that go directly

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Speaker 1: to articles, so you click on that and you're in

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Speaker 1: an article. There are also links that go to channel pages.

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Speaker 1: These are broader categories of topics like computers or electronics,

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Speaker 1: so you can click on that and go to the

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Speaker 1: homepage for that channel. And then there's also a search

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Speaker 1: engine tool so that you can actually search for articles

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Speaker 1: about a specific topic. If there's something you have in mind. Now,

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Speaker 1: when you're analyzing web traffic across the site, you want

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Speaker 1: to take close look at all the behavior. You want

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Speaker 1: to see how many people clicked into an article from

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Speaker 1: the homepage versus going through a channel link, like something

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Speaker 1: that was linked through going through one of those channel

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Speaker 1: landing pages or using a search engine. You want to

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Speaker 1: see how many people clicked into an article from an

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Speaker 1: external search engine, or maybe a piece of content somewhere

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Speaker 1: else on the web, something that's not on one of

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Speaker 1: your web pages but is linked from someone else's to

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Speaker 1: your site, or from a social media platform. There might

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Speaker 1: be social media marketing campaigns that you're running, and you

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Speaker 1: want to include a little string of data that will

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Speaker 1: let you know if someone's clicking into that article from

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Speaker 1: say Twitter or Facebook. All of that is valuable information

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Speaker 1: and it helps you figure out how were your well

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Speaker 1: your design works. So if most of your traffic is

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Speaker 1: coming in through search, it means you perform well when

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Speaker 1: people search stuff in in engines like Google. Like they're

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Speaker 1: looking for a topic in Google and your site is

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Speaker 1: popping up. That's great, Hey, you've got great seo. Your

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Speaker 1: website is is up in the first few uh selections

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Speaker 1: in a search engine. And we know from research that

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Speaker 1: if you are on the first page, you have a

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Speaker 1: lot better chance of having someone click on your length

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Speaker 1: than if you're buried down on page three or lower. Now,

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Speaker 1: a lot of people don't go past the second page

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Speaker 1: if they don't see what they're looking for. But if

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Speaker 1: that's the case, if most of your traffic is coming

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Speaker 1: in through search, that might indicate that your homepage is

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Speaker 1: not really a popular spot for people to visit just

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Speaker 1: on their own. So that might mean you should look

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Speaker 1: into a redesign for your homepage to attract more visitors

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Speaker 1: to say, this is a website you want to check regularly,

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Speaker 1: not just come here when you are searching for something,

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Speaker 1: and we happen to have what it is you're searching for.

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Speaker 1: But no matter what conclusions you draw from this data,

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Speaker 1: you're doing it based on the assumption that the users

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Speaker 1: intended to navigate to those links, Whether they did so

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Speaker 1: through a search engine, a link on another site, or

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Speaker 1: through the home page. Your analysis depends upon that assumption.

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Speaker 1: So if people ended up on your site by chance,

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Speaker 1: by mistake, that doesn't tell you anything other than there

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Speaker 1: may be links to your site that are misleading or

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Speaker 1: easy to click on by accident. Um. I'm reminded of

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Speaker 1: a lot of older web advertisements that were pop over

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Speaker 1: ads that would suddenly show up in front of your

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Speaker 1: view on a website, and it was very easy to

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Speaker 1: accidentally click on one while you were looking at a website,

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Speaker 1: because it would pop up just as you were about

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Speaker 1: to click on something else, and you would navigate to

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Speaker 1: whatever the ad linked you to. Well, that's not an

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Speaker 1: intentional click. That's that's like a shell game. It's smoke

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Speaker 1: and mirrors. It's it's tricking you, scamming you into clicking,

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Speaker 1: not to fool you or not to convince you to

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Speaker 1: buy anything, but because that makes it look really good

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Speaker 1: to your clients. Right, if you are a company that

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Speaker 1: that places ads on stuff and you can turn to

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Speaker 1: a potential client and say, here's the number of clicks

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Speaker 1: that are last campaign generated. Look how how popular it was,

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Speaker 1: and you just leave out the little detail that most

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Speaker 1: of those clicks were gathered by subterviews. Then you might

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Speaker 1: be able to land the juicy contract. It's not very ethical,

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Speaker 1: but it did happen quite a bit. Doesn't happen so

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Speaker 1: much in that format anymore. I'm sure it happens like

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Speaker 1: crazy and other formats still, So accidental traffic might count

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Speaker 1: the same as intentional when you're looking at number of impressions,

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Speaker 1: but it's not exactly a healthy business strategy because your

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Speaker 1: bounce rate is going to be super high, your time

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Speaker 1: spent on a website it's gonna be super low. That

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Speaker 1: people are going to associate the destination they went to

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Speaker 1: as an untrustworthy source, So it is a losing game

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Speaker 1: in the long run. So intention is a very important

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Speaker 1: concept in web analysis, particularly when you pair that concept

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Speaker 1: with other behaviors. So if you see a lot of

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Speaker 1: people are clicking into an article from the home page

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Speaker 1: of how Stuff Works, but then you see the bounce

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Speaker 1: rate on the article is very high, and the time

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Speaker 1: spent on the article is very low. It indicates that

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Speaker 1: what you've got it that link is not meeting the

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Speaker 1: expectation of visitors. Right they see a headline, they click

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Speaker 1: on it, they immediately back out or navigate away. That

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Speaker 1: tells you something is going wrong there. Either the article

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Speaker 1: is not a very good one, or the link was misleading.

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Speaker 1: Maybe the headline wasn't really appropriate for whatever the article was,

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Speaker 1: or maybe it gave mistaken impression that the content was

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Speaker 1: going to be in some other factor form factor like

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Speaker 1: video or audio. Uh So, if you if you work

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Speaker 1: from the assumption that the user intended to click on

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Speaker 1: the link and then went to the new page, but

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Speaker 1: they didn't like what they saw, it tells you, well,

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Speaker 1: I need to fix this. Maybe I need to change

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Speaker 1: that headline, or maybe I need to uh make more

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Speaker 1: clear what it is this is so that people don't

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Speaker 1: click on it and then just bounce away because that

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Speaker 1: doesn't look good either. So, using a different example, let's

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Speaker 1: say I'm looking at data from how stuff Works dot

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Speaker 1: com and I have an article there titled will Artificial

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Speaker 1: Intelligence Eliminate Your job? Right there on the home page,

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Speaker 1: And I'm looking at the traffic and I see a

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Speaker 1: lot of people are clicking on that link, but once

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Speaker 1: they get there, they either search for something in the

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Speaker 1: search engine or they back out the article. Now, that

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Speaker 1: could mean the users are not seeing what they expected

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Speaker 1: and the article title maybe isn't appropriate. On the other hand,

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Speaker 1: if I see the bounce rate is low and the

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Speaker 1: time spent on the page is a good amount, I

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Speaker 1: can assume this is an article that's really engaging and interesting,

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Speaker 1: and I might want to give it an even more

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Speaker 1: prominent placement on the home page to help drive more traffic.

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Speaker 1: If I see this is performing really well, let me

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Speaker 1: put it on the heroes spot on a carousel so

435
00:24:35,560 --> 00:24:38,359
Speaker 1: that it's the first thing people see when they load

436
00:24:38,480 --> 00:24:42,719
Speaker 1: up the home page and drive even more traffic to it.

437
00:24:42,880 --> 00:24:45,119
Speaker 1: Or I might want to make sure that I include

438
00:24:45,119 --> 00:24:48,199
Speaker 1: the article in the layout the following day. Right, So

439
00:24:48,280 --> 00:24:50,800
Speaker 1: if I have a carousel or slide show type display

440
00:24:50,880 --> 00:24:53,000
Speaker 1: for articles, I might say, all right, well, I'm not

441
00:24:53,000 --> 00:24:55,160
Speaker 1: gonna put it in the first spot because now it's

442
00:24:55,160 --> 00:24:57,520
Speaker 1: a day old, but I will put it in spot

443
00:24:57,720 --> 00:25:02,440
Speaker 1: two or three because there's still a good amount of

444
00:25:02,480 --> 00:25:05,639
Speaker 1: traffic coming into this article. There's a tail to it.

445
00:25:05,720 --> 00:25:07,840
Speaker 1: That's what we call the long tail, where you create

446
00:25:08,240 --> 00:25:12,040
Speaker 1: content that continues to have relevance after you've posted it.

447
00:25:12,600 --> 00:25:15,560
Speaker 1: Or maybe a visitor clicks on the homepage and then

448
00:25:15,560 --> 00:25:18,560
Speaker 1: types in the search engine Turing test because they've been

449
00:25:18,600 --> 00:25:22,040
Speaker 1: inspired by this AI article title, but they're more interested

450
00:25:22,040 --> 00:25:25,879
Speaker 1: in learning about Alan Turing's proposed intelligence test, not about

451
00:25:25,920 --> 00:25:27,640
Speaker 1: whether or not AI is going to take their job.

452
00:25:28,080 --> 00:25:30,840
Speaker 1: And because they use the search engine, I might conclude

453
00:25:30,840 --> 00:25:34,640
Speaker 1: that my homepage doesn't have great navigational tools that will

454
00:25:34,720 --> 00:25:38,080
Speaker 1: lead users to content they want to see. If I

455
00:25:38,119 --> 00:25:41,240
Speaker 1: did have really good navigational tools, then maybe the user

456
00:25:41,440 --> 00:25:44,000
Speaker 1: would see three or four articles that he or she

457
00:25:44,160 --> 00:25:46,439
Speaker 1: is interested in within that same subject. You know, they

458
00:25:46,480 --> 00:25:49,480
Speaker 1: click on a link that would take them to artificial

459
00:25:49,480 --> 00:25:53,120
Speaker 1: intelligence topics, and they might read several articles, and that's

460
00:25:53,119 --> 00:25:56,440
Speaker 1: going to benefit both the user and me. A search

461
00:25:56,480 --> 00:26:00,639
Speaker 1: result will pull up one article, presumably the the article

462
00:26:00,760 --> 00:26:04,600
Speaker 1: that's most relevant to the search terms. Navigation will offer

463
00:26:04,680 --> 00:26:07,719
Speaker 1: up a lot more. Now that being said, personally, I

464
00:26:07,760 --> 00:26:10,000
Speaker 1: often will use search because it gets me to what

465
00:26:10,080 --> 00:26:12,600
Speaker 1: I want a lot faster than just navigating through a

466
00:26:12,680 --> 00:26:16,280
Speaker 1: user interface. I do it for efficiency, but that's something

467
00:26:16,280 --> 00:26:19,720
Speaker 1: that web page designers try to work around to encourage engagement.

468
00:26:20,200 --> 00:26:23,080
Speaker 1: Or let's say that I've given prime position to my

469
00:26:23,160 --> 00:26:25,480
Speaker 1: AI article on the homepage. All right, it's got a

470
00:26:25,520 --> 00:26:28,399
Speaker 1: really good spot on there, but I see that way

471
00:26:28,440 --> 00:26:31,440
Speaker 1: more people are clicking on a totally different article. Uh.

472
00:26:31,640 --> 00:26:35,080
Speaker 1: We'll say it's taking the perfect Instagram photo of your food,

473
00:26:35,800 --> 00:26:38,600
Speaker 1: and that article is performing way better than the AI

474
00:26:38,720 --> 00:26:43,639
Speaker 1: r article. But that article is also featured lower down

475
00:26:43,640 --> 00:26:46,719
Speaker 1: on the homepage, below the fold, as we would say,

476
00:26:46,800 --> 00:26:48,919
Speaker 1: which means it's the point where you would have to

477
00:26:48,920 --> 00:26:52,520
Speaker 1: actually scroll down but beyond the initial homepage view to

478
00:26:52,680 --> 00:26:56,480
Speaker 1: actually see a link to that. Uh. We usually want

479
00:26:56,480 --> 00:27:00,399
Speaker 1: to put the stuff that is really relevant and interesting

480
00:27:00,480 --> 00:27:03,199
Speaker 1: and popular above the fold to make it easier for

481
00:27:03,240 --> 00:27:05,800
Speaker 1: people to see. So that would tell me people are

482
00:27:05,880 --> 00:27:08,920
Speaker 1: not as interested in the AI article as they are

483
00:27:09,000 --> 00:27:12,080
Speaker 1: in the Instagram article, and I should probably swap those

484
00:27:12,080 --> 00:27:14,600
Speaker 1: two out so that the more popular one that has

485
00:27:14,600 --> 00:27:17,960
Speaker 1: a more prominent place and generates more traffic. So how

486
00:27:18,000 --> 00:27:20,360
Speaker 1: do we get that data right? How do we actually

487
00:27:20,440 --> 00:27:24,520
Speaker 1: know what people are doing? Websites tend to have a

488
00:27:24,600 --> 00:27:29,240
Speaker 1: special file called an access log, and this log collects

489
00:27:29,359 --> 00:27:33,639
Speaker 1: raw data about user behavior across a website. An access

490
00:27:33,720 --> 00:27:36,879
Speaker 1: log is essentially a list of all the files that

491
00:27:37,000 --> 00:27:40,359
Speaker 1: users have requested from a website. So remember when you

492
00:27:40,520 --> 00:27:43,359
Speaker 1: visit a website, it means your computer is actually sending

493
00:27:43,400 --> 00:27:47,520
Speaker 1: out a request. This is activated through some interaction you

494
00:27:47,560 --> 00:27:50,439
Speaker 1: have with your web browsers, So you type in a

495
00:27:50,480 --> 00:27:54,000
Speaker 1: web address, you click on a link. Either of those

496
00:27:54,119 --> 00:27:57,239
Speaker 1: is technically a request. It gets sent out over the

497
00:27:57,240 --> 00:28:02,240
Speaker 1: Internet and it shoots over to the appropriate computer system

498
00:28:02,280 --> 00:28:07,119
Speaker 1: that houses those files. That computer processes the request and

499
00:28:07,200 --> 00:28:09,879
Speaker 1: response to it, shooting that file back to you in

500
00:28:09,920 --> 00:28:13,240
Speaker 1: the form of data packets which arrive at your computer,

501
00:28:13,400 --> 00:28:16,280
Speaker 1: get reassembled, and then in your web browser it gets

502
00:28:16,280 --> 00:28:19,880
Speaker 1: displayed as a web page. So for a web page,

503
00:28:19,920 --> 00:28:22,720
Speaker 1: that would be probably an HTML file and all the

504
00:28:22,760 --> 00:28:25,720
Speaker 1: associated files that go along with it, like embedded images

505
00:28:25,920 --> 00:28:29,120
Speaker 1: or other media. The access log keeps count of all

506
00:28:29,160 --> 00:28:32,480
Speaker 1: those requests across all the pages on a site. Now,

507
00:28:32,520 --> 00:28:35,480
Speaker 1: that can be a lot of data, particularly for a

508
00:28:35,600 --> 00:28:39,160
Speaker 1: really big website. So typically to make sense of all

509
00:28:39,160 --> 00:28:41,200
Speaker 1: of that, you would need another program to kind of

510
00:28:41,240 --> 00:28:43,520
Speaker 1: sort through all the information and put it into a

511
00:28:43,600 --> 00:28:47,960
Speaker 1: format that's more easily understood. But access logs are usually

512
00:28:48,000 --> 00:28:50,920
Speaker 1: a little limited in the information they can tell you.

513
00:28:50,960 --> 00:28:54,000
Speaker 1: They can tell you certain types of information, but not

514
00:28:55,320 --> 00:28:58,320
Speaker 1: all the granular stuff. Uh. Information it can tell you

515
00:28:58,360 --> 00:29:01,479
Speaker 1: might include things like the number of unique visitors you have,

516
00:29:01,880 --> 00:29:06,760
Speaker 1: which is uh uh. Which requests represent different devices versus

517
00:29:06,800 --> 00:29:09,440
Speaker 1: those that are linked to a single device. That's what

518
00:29:09,520 --> 00:29:12,240
Speaker 1: we mean by unique visitors. It doesn't again, doesn't necessarily

519
00:29:12,280 --> 00:29:16,440
Speaker 1: mean unique people. It could be the same person using

520
00:29:16,920 --> 00:29:19,920
Speaker 1: ten thousand different devices to access your website. That would

521
00:29:20,000 --> 00:29:24,520
Speaker 1: still be unique visitors because it would all be different devices. Uh.

522
00:29:24,600 --> 00:29:27,520
Speaker 1: The access log might also tell you where the visitors

523
00:29:27,560 --> 00:29:31,600
Speaker 1: associated servers domain name is, like whether the visitors navigating

524
00:29:31,680 --> 00:29:33,920
Speaker 1: from the dot E, d U or dot com or

525
00:29:33,960 --> 00:29:37,440
Speaker 1: dot gov site, or which online service provider the user

526
00:29:37,600 --> 00:29:40,600
Speaker 1: is using, which I s P they are using. The

527
00:29:40,640 --> 00:29:43,320
Speaker 1: access log can tell you which pages on a site

528
00:29:43,320 --> 00:29:46,400
Speaker 1: are getting the most requests. That essentially tells you which

529
00:29:46,400 --> 00:29:49,320
Speaker 1: pages are the most popular across your website. It might

530
00:29:49,360 --> 00:29:52,160
Speaker 1: tell you what times of day or week, or month

531
00:29:52,280 --> 00:29:55,120
Speaker 1: or even year are the most popular to visit your website.

532
00:29:55,120 --> 00:29:58,320
Speaker 1: You can look at trends in data this way, so

533
00:29:58,360 --> 00:30:00,120
Speaker 1: you might see that a lot of people, say, are

534
00:30:00,200 --> 00:30:03,120
Speaker 1: visiting your site in the morning and fewer are visiting

535
00:30:03,120 --> 00:30:05,080
Speaker 1: it in the afternoon, so you might want to make

536
00:30:05,080 --> 00:30:08,520
Speaker 1: sure that you have the fresh content up in the

537
00:30:08,520 --> 00:30:12,560
Speaker 1: mornings so that people are energized to get there. And

538
00:30:12,640 --> 00:30:15,400
Speaker 1: maybe you even experiment, maybe you try and put up

539
00:30:15,520 --> 00:30:19,000
Speaker 1: a second round of new content in the afternoons to

540
00:30:19,040 --> 00:30:21,640
Speaker 1: see if you can encourage more visitors in the afternoons.

541
00:30:22,200 --> 00:30:24,120
Speaker 1: But again, if you have a really big website with

542
00:30:24,160 --> 00:30:27,120
Speaker 1: lots of pages, this approach can get a little unmanageable.

543
00:30:27,160 --> 00:30:29,080
Speaker 1: But there are other ways to get data from users,

544
00:30:29,120 --> 00:30:31,720
Speaker 1: and I'm going to go into that in just a moment,

545
00:30:31,760 --> 00:30:35,880
Speaker 1: but first let's take another quick break to thank our sponsors.

546
00:30:43,440 --> 00:30:46,800
Speaker 1: An alternative to using access logs is using some code

547
00:30:47,160 --> 00:30:51,320
Speaker 1: in JavaScript now. JavaScript is a coding language primarily used

548
00:30:51,400 --> 00:30:55,400
Speaker 1: for web development. Netscape created JavaScript in order to build

549
00:30:55,400 --> 00:30:58,720
Speaker 1: out interactive, dynamic elements in websites, so you didn't just

550
00:30:58,760 --> 00:31:02,920
Speaker 1: have static pages that you never changed and therefore there

551
00:31:02,960 --> 00:31:05,720
Speaker 1: was not really any reason to keep visiting them. It's

552
00:31:05,760 --> 00:31:09,800
Speaker 1: not actually related to the Java programming language directly. It

553
00:31:09,840 --> 00:31:14,640
Speaker 1: did take some inspiration from Java, but JavaScript really resembles

554
00:31:14,680 --> 00:31:18,560
Speaker 1: the c programming language more than Java, and it's a

555
00:31:18,640 --> 00:31:22,920
Speaker 1: client side scripting language. That means your browser processes the

556
00:31:22,960 --> 00:31:26,720
Speaker 1: code rather than the web server. So we have server

557
00:31:26,840 --> 00:31:30,680
Speaker 1: side and we have client side. JavaScript is client side

558
00:31:31,400 --> 00:31:37,480
Speaker 1: JavaScript tracking involves inserting some JavaScript code into a web page. Typically,

559
00:31:37,480 --> 00:31:40,680
Speaker 1: this code will send tracking information to an analytics service

560
00:31:40,760 --> 00:31:44,520
Speaker 1: like Google Analytics, and this gives the service the ability

561
00:31:44,560 --> 00:31:48,600
Speaker 1: to track specific behaviors on web pages that include that

562
00:31:48,680 --> 00:31:52,720
Speaker 1: JavaScript code, including targeted ones that you want to pay

563
00:31:52,880 --> 00:31:57,200
Speaker 1: very close attention to targeted behaviors. Um. For this to work,

564
00:31:57,520 --> 00:32:00,000
Speaker 1: the web designer has to include this code on every

565
00:32:00,080 --> 00:32:02,400
Speaker 1: web page on his or her site that they want

566
00:32:02,440 --> 00:32:05,040
Speaker 1: to track. So when a user visits a web page,

567
00:32:05,360 --> 00:32:09,320
Speaker 1: the user's browser executes the code in JavaScript. Assuming the

568
00:32:09,400 --> 00:32:13,320
Speaker 1: user doesn't have JavaScript turned off. You can turn off JavaScript,

569
00:32:13,920 --> 00:32:16,480
Speaker 1: so if you did that then this step would not happen.

570
00:32:16,920 --> 00:32:19,320
Speaker 1: But when it does happen, it sends what is called

571
00:32:19,320 --> 00:32:22,240
Speaker 1: an API called to the server to send data to

572
00:32:22,360 --> 00:32:25,880
Speaker 1: that server. This type of data is dependent upon the

573
00:32:25,920 --> 00:32:29,840
Speaker 1: code in that JavaScript code and the analysis engine that

574
00:32:29,920 --> 00:32:32,960
Speaker 1: you are using. So if a web developer is only

575
00:32:33,000 --> 00:32:35,760
Speaker 1: interested in where a user is coming from, where that

576
00:32:35,880 --> 00:32:38,960
Speaker 1: user is going, and how long they are, you know

577
00:32:39,040 --> 00:32:41,760
Speaker 1: where they went to after they were on your site

578
00:32:42,040 --> 00:32:44,880
Speaker 1: and how long they were spending on your website. You

579
00:32:44,920 --> 00:32:47,600
Speaker 1: could tweak your JavaScript to only collect that information if

580
00:32:47,640 --> 00:32:50,920
Speaker 1: you wanted to. But as for where you're coming from,

581
00:32:51,000 --> 00:32:53,280
Speaker 1: it can get a little more granular, in fact, a

582
00:32:53,280 --> 00:32:56,360
Speaker 1: lot more granular than just whether it's a dot com

583
00:32:56,480 --> 00:32:59,160
Speaker 1: or dot e du or dot gov. For example, you

584
00:32:59,200 --> 00:33:02,280
Speaker 1: may have seen links to sites from their official social

585
00:33:02,320 --> 00:33:06,680
Speaker 1: media feeds that contain some characters after the HTM tag

586
00:33:06,840 --> 00:33:08,920
Speaker 1: at the end of the u r L. Those characters

587
00:33:08,920 --> 00:33:12,200
Speaker 1: are codes. They give more information about how the user

588
00:33:12,320 --> 00:33:16,480
Speaker 1: navigated to that page. The web server can't make any

589
00:33:16,520 --> 00:33:19,040
Speaker 1: sense of this information and ignores it. So like when

590
00:33:19,080 --> 00:33:23,080
Speaker 1: your web browser asks for that page, the server looks

591
00:33:23,120 --> 00:33:25,760
Speaker 1: at everything that's after HTM and says, this doesn't make

592
00:33:25,760 --> 00:33:28,240
Speaker 1: any sense to me. Just send them the website and

593
00:33:28,280 --> 00:33:32,560
Speaker 1: they will. But the JavaScript code can see that tag

594
00:33:32,920 --> 00:33:36,000
Speaker 1: and link your visit with the associated social platform links.

595
00:33:36,000 --> 00:33:38,920
Speaker 1: So when you get all the information sent off to

596
00:33:38,960 --> 00:33:42,080
Speaker 1: the analytics company, they can return a report that says

597
00:33:42,680 --> 00:33:47,480
Speaker 1: X percent of your visitors to this particular article got

598
00:33:47,520 --> 00:33:52,600
Speaker 1: there through Facebook, why percent got there from Twitter, and

599
00:33:52,960 --> 00:33:57,160
Speaker 1: z percent came from your homepage, and you know, maybe

600
00:33:57,360 --> 00:34:00,320
Speaker 1: a percent came from search. You can get it broken

601
00:34:00,320 --> 00:34:02,040
Speaker 1: down in all these different ways, so you can really

602
00:34:02,080 --> 00:34:06,120
Speaker 1: see where people are coming in, how they are discovering

603
00:34:06,160 --> 00:34:09,839
Speaker 1: your your content, and that gives you ideas of where

604
00:34:09,880 --> 00:34:13,000
Speaker 1: you should spend your efforts promoting your site. And if

605
00:34:13,000 --> 00:34:15,399
Speaker 1: you see that hardly anyone is coming to your site

606
00:34:15,400 --> 00:34:19,120
Speaker 1: from Facebook, it probably means that your links aren't really

607
00:34:19,239 --> 00:34:21,560
Speaker 1: visible to a lot of people. They're not popping up

608
00:34:21,560 --> 00:34:23,560
Speaker 1: in a lot of news feeds. Facebook is famous for

609
00:34:23,600 --> 00:34:28,280
Speaker 1: tweaking its format several times uh and uh and changing

610
00:34:28,280 --> 00:34:31,960
Speaker 1: things out where you'll hear companies say, like especially content

611
00:34:32,000 --> 00:34:37,120
Speaker 1: companies say, Facebook change their algorithms and now we are

612
00:34:37,160 --> 00:34:41,920
Speaker 1: our traffic has dropped incredibly low because we can't get

613
00:34:41,920 --> 00:34:44,360
Speaker 1: our links out in front of people the way we

614
00:34:44,480 --> 00:34:48,200
Speaker 1: used to. Uh. This lesson, by the way, I think

615
00:34:48,360 --> 00:34:53,000
Speaker 1: is that you should never really commit fully to any

616
00:34:53,120 --> 00:34:59,640
Speaker 1: one social platform as your primary way of reaching potential visitors,

617
00:34:59,680 --> 00:35:02,880
Speaker 1: because as you have no control over whether or not

618
00:35:02,960 --> 00:35:06,439
Speaker 1: that platform will change things, and if they do change things,

619
00:35:06,520 --> 00:35:08,919
Speaker 1: it can it can really hurt you. It's a tough

620
00:35:09,000 --> 00:35:12,360
Speaker 1: lesson to learn. Now that might mean that you would

621
00:35:12,360 --> 00:35:15,160
Speaker 1: have to figure out some other strategy. You might have

622
00:35:15,200 --> 00:35:19,560
Speaker 1: to pay Facebook for a promotion so that your your

623
00:35:19,640 --> 00:35:23,120
Speaker 1: links get promoted in more news feeds and then you

624
00:35:23,200 --> 00:35:25,359
Speaker 1: might get a little more traffic. Or it might mean

625
00:35:25,440 --> 00:35:27,440
Speaker 1: you just have to use a totally different approach to

626
00:35:27,440 --> 00:35:31,200
Speaker 1: try and reach other users. Um, it's it's a tough

627
00:35:31,320 --> 00:35:34,680
Speaker 1: it's a tough situation to be in. JavaScript can also

628
00:35:34,719 --> 00:35:37,879
Speaker 1: track user interactions like downloads as well, so if there

629
00:35:37,920 --> 00:35:40,880
Speaker 1: is downloadable content on a web page, it's possible for

630
00:35:40,920 --> 00:35:43,439
Speaker 1: the web administrator to track all that. You can also

631
00:35:43,480 --> 00:35:48,719
Speaker 1: look at user settings like browser resolutions. You can look

632
00:35:48,719 --> 00:35:51,239
Speaker 1: for browser plug ins. If you've ever used an ad

633
00:35:51,280 --> 00:35:54,520
Speaker 1: blocking program and you've wondered how a website can detect that,

634
00:35:55,160 --> 00:35:57,080
Speaker 1: and it sends you a message saying, hey, we see

635
00:35:57,080 --> 00:36:00,640
Speaker 1: your blocking ads. Would you mind you know, not doing that?

636
00:36:00,640 --> 00:36:03,520
Speaker 1: That could come from a JavaScript code and the web page.

637
00:36:03,880 --> 00:36:05,759
Speaker 1: The JavaScript is able to tell that you've gotten ad

638
00:36:05,760 --> 00:36:08,000
Speaker 1: blocker installed, and it triggers this server to send you

639
00:36:08,040 --> 00:36:10,279
Speaker 1: the message to turn off that ad blocker if you

640
00:36:10,320 --> 00:36:14,880
Speaker 1: want to access the content. JavaScript can identify unique visitors

641
00:36:14,880 --> 00:36:19,439
Speaker 1: by analyzing cookies and the browsers quote unquote fingerprint. So

642
00:36:19,640 --> 00:36:23,600
Speaker 1: what exactly are cookies? I'm sure you heard about Internet cookies. Well,

643
00:36:23,640 --> 00:36:27,239
Speaker 1: those are special little data packets that your browser will

644
00:36:27,280 --> 00:36:31,000
Speaker 1: send to web servers when you visit a website. Uh,

645
00:36:31,160 --> 00:36:33,800
Speaker 1: they can get installed on your web browser. Because you

646
00:36:33,920 --> 00:36:37,080
Speaker 1: visit a web page, it installs a cookie on your

647
00:36:37,080 --> 00:36:40,719
Speaker 1: web browser, and then every time you come back, it

648
00:36:40,960 --> 00:36:45,080
Speaker 1: registers that it's you that you've done this. Uh. This

649
00:36:45,120 --> 00:36:47,600
Speaker 1: is actually a pretty valuable thing. It means that when

650
00:36:47,640 --> 00:36:50,759
Speaker 1: you go to a website, it can register that you

651
00:36:50,800 --> 00:36:53,960
Speaker 1: are a return visitor. And let's say you're using a

652
00:36:54,040 --> 00:36:57,080
Speaker 1: service frequently and you log into that service, like you

653
00:36:57,120 --> 00:36:59,120
Speaker 1: have to have a user name and password, Well, the

654
00:36:59,160 --> 00:37:03,439
Speaker 1: cookie might out so that the service recognizes when you're

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00:37:03,920 --> 00:37:06,640
Speaker 1: navigating back to that service, so you don't have to

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00:37:06,640 --> 00:37:09,240
Speaker 1: do the log in all over again. It has already

657
00:37:09,280 --> 00:37:12,960
Speaker 1: registered that you are you and you're fine, or maybe

658
00:37:13,280 --> 00:37:16,640
Speaker 1: you are watching a video or listening to some music

659
00:37:16,760 --> 00:37:20,200
Speaker 1: or something you navigate away. When you navigate back, it

660
00:37:20,239 --> 00:37:22,520
Speaker 1: could pick up right where you left off. Because there

661
00:37:22,560 --> 00:37:26,080
Speaker 1: was a cookie that was installed on your browser, it

662
00:37:26,160 --> 00:37:30,160
Speaker 1: was able to register when you stopped watching or listening

663
00:37:30,200 --> 00:37:33,319
Speaker 1: to something, and then when you return, it recognizes where

664
00:37:33,360 --> 00:37:35,360
Speaker 1: who you are and then goes right back to the

665
00:37:35,400 --> 00:37:39,080
Speaker 1: point where you left off. Cookies are what make that possible.

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00:37:39,160 --> 00:37:41,880
Speaker 1: But those data packets can send other types of information

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00:37:41,880 --> 00:37:45,520
Speaker 1: to servers, like which pages you have recently visited, or

668
00:37:45,560 --> 00:37:48,680
Speaker 1: which ones you go to frequently, or topics you might

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00:37:48,719 --> 00:37:51,320
Speaker 1: have searched for in the past. And that information is

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00:37:51,400 --> 00:37:54,200
Speaker 1: valuable because it not only tells web administrators more about

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00:37:54,280 --> 00:37:57,200
Speaker 1: user behavior, it can also be a really valuable tool

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00:37:57,320 --> 00:38:01,640
Speaker 1: for marketing and advertising companies. This is where targeting advertising

673
00:38:01,680 --> 00:38:05,880
Speaker 1: comes into play. So again, uh, in an ideal implementation,

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00:38:06,160 --> 00:38:10,439
Speaker 1: one where everybody benefits, targeted advertising would mean you would

675
00:38:10,440 --> 00:38:13,400
Speaker 1: see ads for stuff you were already interested in. You

676
00:38:13,440 --> 00:38:15,680
Speaker 1: would not see ads for stuff that did not pertain

677
00:38:15,719 --> 00:38:19,319
Speaker 1: to you. The advertisers would quote unquote know what you

678
00:38:19,360 --> 00:38:22,719
Speaker 1: are interested in because of web analytics and cookies and

679
00:38:22,760 --> 00:38:25,280
Speaker 1: that kind of thing. The data your computer is sending

680
00:38:25,320 --> 00:38:29,560
Speaker 1: servers gives little bits of information about your interests and desires,

681
00:38:29,960 --> 00:38:32,719
Speaker 1: and if it all works properly and everyone's on the

682
00:38:32,800 --> 00:38:36,040
Speaker 1: up and up, the advertiser sends adds that you're most

683
00:38:36,120 --> 00:38:39,560
Speaker 1: likely to find valuable, and that means that you might

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00:38:39,600 --> 00:38:42,120
Speaker 1: see an ad that you are legitimately interested in you

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00:38:42,160 --> 00:38:46,239
Speaker 1: actually want to buy that product or service, so you

686
00:38:46,360 --> 00:38:49,000
Speaker 1: end up doing that because you were informed by that

687
00:38:49,080 --> 00:38:52,600
Speaker 1: ad and everybody's a winner. The web content providers a winner,

688
00:38:52,680 --> 00:38:55,920
Speaker 1: the advertisers a winner, the company you bought the service

689
00:38:56,000 --> 00:38:57,640
Speaker 1: or product for as a winner, and you're a winner

690
00:38:57,680 --> 00:39:00,440
Speaker 1: because you all got what you wanted and it's all

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00:39:00,480 --> 00:39:03,759
Speaker 1: done without your actual identity being part of that equation.

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00:39:04,280 --> 00:39:07,719
Speaker 1: The web analytics company doesn't care who you are. They

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00:39:07,719 --> 00:39:11,480
Speaker 1: care about what you like, so you're a user, a

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00:39:11,560 --> 00:39:16,160
Speaker 1: website visitor. The advertiser just doesn't have any desire to

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00:39:16,200 --> 00:39:19,000
Speaker 1: go beyond that. They just want to know what they

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00:39:19,040 --> 00:39:23,520
Speaker 1: can serve to you that will most UH entice you

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00:39:24,000 --> 00:39:28,839
Speaker 1: to engage with content and with advertising. That's the ideal implementation,

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00:39:28,880 --> 00:39:31,239
Speaker 1: but as we know, we do not live in an

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00:39:31,280 --> 00:39:35,600
Speaker 1: ideal world. Now, you can elect to block JavaScript, and

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00:39:35,640 --> 00:39:38,319
Speaker 1: you can block cookies that will prevent your browser from

701
00:39:38,320 --> 00:39:41,120
Speaker 1: sending information to web servers in the ways i've described.

702
00:39:41,680 --> 00:39:44,799
Speaker 1: The web access logs will still register when you visit

703
00:39:44,840 --> 00:39:49,080
Speaker 1: a site, not you specifically, but rather that the site

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00:39:49,680 --> 00:39:53,600
Speaker 1: is UH is one among all the others you've hit

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00:39:54,239 --> 00:39:57,560
Speaker 1: that day. Now, before I conclude this episode, I want

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00:39:57,560 --> 00:40:01,800
Speaker 1: to stress that web analytics are gitimate and they are valuable.

707
00:40:02,440 --> 00:40:05,680
Speaker 1: They help website administrators create better sites that people want

708
00:40:05,680 --> 00:40:08,200
Speaker 1: to go to. They help content companies make sure they're

709
00:40:08,239 --> 00:40:11,600
Speaker 1: creating the stuff people want to see. Uh. They help

710
00:40:11,680 --> 00:40:14,960
Speaker 1: online retailers market their products more effectively so that people

711
00:40:15,000 --> 00:40:17,840
Speaker 1: find what they're looking for more easily. They can improve

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00:40:17,880 --> 00:40:21,799
Speaker 1: the experience for all sides of the equation if they

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00:40:21,800 --> 00:40:25,239
Speaker 1: are used responsibly. But in our next episode, I'll look

714
00:40:25,239 --> 00:40:28,160
Speaker 1: at how things can go wrong when we aren't careful.

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00:40:28,560 --> 00:40:31,719
Speaker 1: That wraps up this overview of web analytics and a

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00:40:31,719 --> 00:40:34,760
Speaker 1: little bit of online advertising, and to explain why it's important.

717
00:40:35,160 --> 00:40:38,360
Speaker 1: In our next episode, we'll talk more about privacy issues

718
00:40:38,360 --> 00:40:41,520
Speaker 1: and security issues. If you have any suggestions for future

719
00:40:41,560 --> 00:40:44,400
Speaker 1: episodes of tech Stuff, send me an email the addresses

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00:40:44,440 --> 00:40:46,799
Speaker 1: tech Stuff at how stuff rex dot com or drop

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00:40:46,840 --> 00:40:49,400
Speaker 1: me a line on Facebook or Twitter. The handle for

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00:40:49,440 --> 00:40:52,520
Speaker 1: both of those is tech Stuff H s W. Don't

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00:40:52,520 --> 00:40:55,720
Speaker 1: forget check out t public dot com slash tech stuff

724
00:40:55,719 --> 00:41:00,719
Speaker 1: for all your tech stuff merchandise needs. Speaking of targeted advertise, UH,

725
00:41:00,960 --> 00:41:03,719
Speaker 1: go get yourself a coffee mug or a T shirt

726
00:41:03,800 --> 00:41:06,960
Speaker 1: or some stickers, and don't forget to follow us on

727
00:41:07,080 --> 00:41:16,360
Speaker 1: Instagram and I'll talk to you again really soon For

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00:41:16,520 --> 00:41:18,800
Speaker 1: more on this and thousands of other topics. Is that

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00:41:18,880 --> 00:41:29,920
Speaker 1: how stuff works dot com