We're going to be looking at how analytics fits into the user experience profession. It's been around for a long time. Analytics have been around for as long as the web, obviously. And so has usability and user experience. They've been around since before – *long before*, in fact, if we're talking about usability. But the two have really not come very much into contact with each other until fairly recently – I'd say in the last five or seven years,
we're starting to have much more interest in analytics from a user experience perspective. And bear in mind that analytics is really quite a big topic and that there are people who spend their entire lives looking at analytics. We're obviously going to be skimming the surface somewhat, but from a user experience perspective. So, the kinds of things that we're hoping to get out of analytics, whether we're talking about web or mobile app – I'm not going to differentiate
between the two very much. In fact, Google Analytics treats them pretty much as equivalent. But the kinds of things we can get out are largely around the area of behavioral data – which is obviously of great interest to us from a user experience perspective. But we'll also be looking at some of the other kinds of data – typically demographic – which also can be useful for user experience. So, *bounce rates* is a number that is often quoted in analytics circles.
It's how *often people appear* at a page on your website and then *immediately disappear*. So, they've bounced. Obviously, it's very disappointing for web designers to see that they've got high bounce rates on certain pages; and, of course, it can be a variety of issues that leads to that happening, and that's really one of the challenges facing us from a user experience perspective: Is it the content? Is it stuff that directed people to our site without our particularly being aware of it?
Is it faulty information? What kinds of things go on? *Conversion rates* – really the queen of statistics from an analytics perspective: Are people doing what you want them to do? That's what a conversion is. Are people coming to your website and buying stuff? Or subscribing to your newsletter? Or voting for your candidate in whatever kind of organization this might be? Those are all examples of conversions. And, from a UX perspective, we tend to think of those as achievement of goals, and
there is also the question, which we'll be talking a bit about later on, of our organizational goals versus users' individual goals; hopefully, those are aligned, but they may not be; and sometimes the analytics can help us with that. *Repeat usage* – how often people come back; obviously very important for most websites – we don't want people just dropping in and then disappearing forever. We really would like them to engage with our content in most cases.
*User profiles*, *demographics*, *platforms* – these are all the kinds of things that the analytics tools can tell us. And some of this information has been available since year dot in the web arena – information that's passed back to a web server by the browser, for example. But it has become much more elaborate and much more sophisticated of late, especially with platforms like Google Analytics doing a lot of that work for us. *Search behavior* – this has become a little bit complicated in recent years,
mostly because the search information used to be passed in with the request for a page. So, if you went to Google or Bing and you typed in a search string and then clicked on one of the resulting links, the search page would very kindly tell the server what the user was searching for at the time, but for various reasons that isn't happening so much now – some of it for information privacy reasons.
So, search behavior is dealt with slightly differently these days. We're not going to go into great detail on that particular topic, but if you're working with Google Analytics, which is what we're going to be using as an example of an analytics platform, then rest assured that you can get to the search behavior, but it involves integrating Google's search analytics with the web analytics for your interactive solutions. *User journey* is obviously very interesting from a user experience perspective –
Where are people going? What kind of people go where? How long are they spending at various locations? Does visiting one page or another improve or decrease the chances of them actually converting – buying something or signing up, what have you? Analytics is a really huge field, and we're going to be just kind of skimming in and looking at some of the highlights there and trying to understand how it all fits in. So, how this data is collected and reported
– what's good about it? What's bad about it? There are inherent weaknesses in some of the data that we're going to be looking at, and you obviously need to know and understand that. And that is one of the things that I'm planning to do for you – is to point out some of the really important weaknesses and obviously some of the important strengths, too, but a lot of this data can be very helpful when it comes to locating and possibly even fixing user experience problems.