I wholeheartedly agree. Especially in higher education, the recipient of an analytics report rarely knows what the term *unique *really means in this context or the problems with measuring unique visitors.

“Unique visitors” is misleading. Why? According to Brian’s post:

Firstly, cookies get lost, blocked and deleted. Research has shown that after a period of four weeks, nearly one third of tracking cookies are missing, which means the visitor will be incorrectly considered a new unique visitor should they return to the same website.

The longer the time period, the greater the chance of this happening, which makes comparing year-on-year data invalid for example. In addition, browsers make it very easy these days for cookies to be removed – see the new ‘incognito’ features of the latest Firefox, Chrome and Internet Explorer browsers.

However, the biggest issue for counting uniques faced by both on and off-site web analytics tools is how many devices people use to access the web.

The problem I see with unique visitors is the name. Most (and by most I mean the recipients of your report!) *assume* unique visitor means a person. Unique implies … well … that it’s just that … unique – one – a person.

Even the Web Analytics Association definition of unique visitors says it’s an “inferred” person.

The number of inferred individual people (filtered for spiders and robots), within a designated reporting timeframe, with activity consisting of one or more visits to a site. Each individual is counted only once in the unique visitor measure for the reporting period.

Using the term “inferred” makes the statement, I guess, more true, but it’s misleading nonetheless. The document does go on to note the problems with measuring unique visitors, so that’s good.

The only way to true measure of “unique visitors” is by using authentication, but the majority of our sites and pages don’t do this.

In the past, when I’ve been asked for unique visitor rates because we want to measure how many *people* have come to the website, I’ve pushed back.

The argument for using unique visitors has been that we want to create conversion rates for enrollments, which are “people” so using “unique visitors” would be apples to apples.

That’s not true, though. That *assumes* it’s apples to apples, but it isn’t.

Use visits instead. It’s a more accurate number and more importantly doesn’t “infer” that it’s something it’s not.

Last week while taking a training session at Omniture Summit, I was shocked that our instructor said that unique visitors meant people. He preceded the statement with something like, “yeah, yeah, there are a ton of things that can skew unique visitors, but …” and then proceeded to say that they are essentially people.

I almost flipped my lid.

I know. I take this stuff too seriously.

This is big, though. Remember who the recipients of your reports are. Management? Leadership? Will they assume unique visitors is people? Probably. That’s not only misleading, it’s irresponsible on our part.

If you absolutely must use unique visitors, make a big, red, flashing label on your report that spells out why that term does not mean people.

Better yet, just use visits instead.

This was my first year at the summit and it was completely worth every penny. I learned so much, mostly in the Omniture University course I took last Monday.

Other than learning about classifications, VISTA rules, and advanced campaign strategies at the Omniture University course, I went to sessions on advanced use of SiteCatalyst, tracking Web 2.0 technologies, and video tracking.

I’ve always said that the one reason web analytics hasn’t made it into the higher ed community at the rate it should is that it has always been considered a *marketing* function – something that those marketers do and we as admissions, help desk, library, whatever, don’t have time or the need to pay attention to.
This couldn’t be more wrong.

If you own or have anything to do with a website, whether you like it or not, you are a marketer. Do you want your users  do something on your website? Then you’re a marketer. Plain and simple.

At the Omniture Summit, most of the sessions were geared toward e-commerce sites. At first, I was a bit frustrated at their focus on them, but then I got thinking – this is still very much relevant to us. Why? Because, again, we have goals on our site and we want users to do something (download a request information form, sign up for a course, apply for a degree). Why can’t this be like buying a widget? No, users don’t go through a check out process per se, but  they do go through a *process* of some sort.

That “every site is a customer service website” mentality came back to my mind. This is what we need to keep in mind. The conversion from visitor-to-widgit buyer may not make sense to us, but the conversion from click-to-visitor-to-prospect or visitor-to-applicant does.

It’s the same exact thing and we track it in almost the same way.

At the summit we talked about goals and key performance indicators – something every website should and *needs* to have to be successful, regardless of the type of website.

We talked about conversions – something we all should be tracking regardless of how our *conversion* is defined.

There were many tactical things I learned at the summit as I stated at the beginning of this post, but my biggest takeaway is this: when it comes to websites, everything is connected. Offisite mentions, onsite processes, search engine optimization, usability, relevant content – it all fits together. Anlaytics is how we know it’s working or not working and how we prioritize tasks and projects to fix issues. It’s how we know where to put our money and resources.

So, SiteCatalyst for Power Users it was … an advanced course, although I was pleasantly surprised that we are already incorporating half of what was presented in class.

The biggest takeaway I got from the Power Users course was the use of Classifications and of Vista Rules.

Classifications can be used to group or classify certain data. For instance, let’s say you have a bunch of degrees as your “products.” You can thenn classify those degrees into other groups (I’m not sure I’d use these classification names, but you get the point):

• Type of Degree (undergraduate, graduate)
• Level of Degree (masters, bachelors, associate)
• Topic Area of Degree (business, education, technology, health)

So you can classify your product (in this case each “degree” is a product so our product list might contain, MBA, Bachelor of Business, etc.)  and then you can which classifications or “groups” converted most, etc. Cool stuff, huh?

The best thing about classifications? They’re retro-active!! So, upload your classifications and it retro-actively applies them to the data already there. Very … very cool!

VISTA rules are ways to segment the data before it gets into any Omniture Suite. For those using Omniture, you know that suites are used to segment sections of the website into smaller “sub-sections” allowing you to report on those segmented portions.

In Google Analytics you can do this with profiles or filters. It’s basically the same thing.

VISTA rules are a way to segment data in real-time. Through VISTA rules, for example, you can segment out your internal IPs and send them to another report suite so you can see what your internal people are doing on the site. I never actually thought about that! Of course we filter *out* internal IPs, but our internal folks are our users too, right? So why not see what they’re doing?

There are a couple of other VISTA rules I’m looking at as well.

All-in-all it was a great day. I won’t mention, though, that our instructor (who was fantastic) referred to unique visitors as “people” – eek! I have to disagree with that one. That is  very misleading, especially when you’re presenting to people who don’t know about analytics and what a unique visitor actually is. Having those people assume it’s a person is wrong, in my opinion.  Actually, for this reason, I usually only report on visits. Again, in my opinion, it’s a “truer” number. But I digress. That’s another post for another time.

Gotta run. Sessions are starting a 1/2 hour.

Stay tuned for day two!

Just like setting goals for a website, I find goals helpful going into a conference.

So, I’m going to focus on:

1. Social media metrics
2. Video metrics
3. Moving to the next level with Discover (Omniture’s advanced segmentation tool)

What *aren’t* we taking advantage of and how can we start? For example, I have yet to truly dive into video metrics, so I’m very excited about getting my hands dirty with video metrics.

One thing I am alsoo excited about is live blogging throughout the conference. This will be my first time live blogging, so we’ll see how it goes.

Stay tuned … off to Salt Lake.