Digital Analytics - University of Utah: webtrends

Showing posts with label webtrends. Show all posts

Wednesday, February 13, 2013

Metrification Autometrically!

Metrics! Metrics! Metrics! If I have to hear that word one more time I think I might just scream like Doc Brown at the end of Back to the Future II.

GREAT SCOTT!! I thought I sent Metric McFly back to the future!

But, that's the life of a web analyst. They look at metrics everyday. They read metrics everyday. They dream about page view percentages and average time on a site. They search through blogs and books about how to improve their SEO. They attend conferences and workshops with names like the eMetrics Summit or any of the following: SearchFest, Social Media & Web Analytics Innovation (try repeating that five times really fast!), or Webstock (which is like Woodstock, just without all of the drugs, half-naked people dancing everywhere and the legendary Santana and Jimi Hendrix).

Let me rephrase that, they devour metrics like 30 year old's devour Alphabits cereal.

Is that a bowl of Alphabits?! NO, fool it's an ice cold bowl of metrics! Eat up!

Metrics are like the blood that pumps through the veins of web analysts. They devote hours to scouring metrics with a combination of tools like Omniture, WebTrends and Google Analytics, just to name a few. They bust out metrics at a party like ghostbusters bust ghosts. They have Photoshopped pictures of themselves hanging out with Avinash Kaushik....what you don't know who that is?! Click here for some edumication.

LET'S GET METRICAL!

To further educate yourself in the ways of the web analyst there are is little metrics lingo that you will need to brush up on so you don't look like a complete maroon when attending those really neat conferences I previously mentioned above.

For example, you should know a little about the following:

Page Views - the amount of times a page on a website has been viewed. These can be viewed by new, repeat or a return visitor.
Entry page - which is generally the very first page on a website that is viewed. For example when you visit Walmart.com, that first page is the entry page.
Exit page - is the opposite of the entry page! Exactly! It is the last page you left from a website.
Bounce Rate - is basically the rate of how many times a visitor exited a page on a website versus those that have stayed on the page. For example, say you go to the Walmart.com link and search for motor oil. Then you decide that Autozone has motor oil to and for a better price, so you type in your address bar www.autozone.com. You bounced from the Walmart page to the Autozone page.
Conversion - this is a measurement of how many visitors have performed or completed some action on the web page. For example, purchasing an item from Amazon.com or initiating a download from a website.
Count - which is a measurement of how many visitors have entered a page on a website
Average time on Site - How long did visitors stay on your site.

Now with some lingo under your belt, your almost ready to get started into the world of web analytics. The next step is to understand exactly how some of these measurements are categorized. Generally there are 3 categories that metrics fall under:

Individual - Activity of a single web visitor for a defined period of time.
Aggregate - Total site traffic for a defined period of time.
Segmented - A subset of the site traffic for a defined period of time, filtered in some way to gain greater analytical insight.[1]

The next step to understand, is that all of these metrics are the results of visitors...visiting a website. This brings us back to another set of important metric lingo...visitors...

Not these visitors!

These visitors....

There are three types of visitors in the web analyst lingo.

New Visitors - Are visitors that have visited a website for the first time.
Return Visitors - Are visitors that have returned to the website.
Repeating Visitors - Visitors that have repeatedly visited a website during a specified time.
Unique Visitors - Wait didn't I say that there are 3 types of visitors?! I did, and I am glad you caught that, because that means you are actually reading this post!

The three types of visitors: New, Return, and Repeating, are considered part of Unique visitors. Unique visitor is defined as "the number of individuals within a designated reporting timeframe, with activity consisting of one or more visits to a site. Each visitor is only counted once in the unique visitor measure for the reporting period."[2]

So...uh..What Does All This Mean?

Now that you understand some of the basics it's now time to jump into the why of web analytics? One metric to notice when you are testing out some analytics tools on your website, is the Average Time on Site. For example, why were the visitors on your site so long?

Were they engrossed in a web article like this one

V-Day Special, How Web Analytics is a lot like Dating or were they staring off into space? It's a good idea to figure that one out.

If you have a shopping cart on your site, it's a good idea to ask yourself how long did it take for a visitor to get there and make a purchase. How many of those visitors were new visitors? There's a metric for that too!

So what do you do with all of these metrics? Like any good web analyst you search for patterns.

Do you see a pattern? Hmmm...keep looking.

Web analysts are excellent at finding patterns within their metrics. They can see why visitors spent too much time on their website or why they bounced out after 30 seconds off a specific page. All of these metrics set patterns and trends that are used to figure out how to improve conversion rates on a website...which is that completed event thing I mentioned before.

What do these trends tell you?

This is the Bounce rate of this blog.

This is the Number of Visits to this blog.

This is the Percentage of New Visits on this blog

The peaks tell us that there were quite a few that visited this blog on that specific date while the valleys are the opposite. The same can be said of the bounce rate and the % New Visitors. Since this blog first got started in January we have had 3,771 visitors, 2,067 of them unique with an average bounce rate of 60.81%.

From these trends we can also see from where our visitors are coming from:

The darker green = where most of the visitors are coming from.

Here you can see the the United States is the main visitor demographic with India in second place.

So far what does all of this tell us? The majority of our visitors are from the United States and let's see what page is the most viewed....looks like with a total of 10,039 page views that the post in the lead is customer analytics incorporating with 264 page views. Ah, but look at the unique visitors! The blog post about the problems with google analytics is leading the pack.

SO....with all of this new information swirling around your brain, it's a good idea to let it sit for awhile. And while you're at it, read some other more interesting posts like these for our blog site:

Adventures in Ghostery

Yesterday's Web Analytics is Today's Digital Analytics

The time has come to end this post before I get a higher bounce rate! Please read other posts while on this site to get those rates up!

Related Resources

[1] http://www.kaushik.net/avinash/web-analytics-standards-26-new-metrics-definitions/

[2] http://c.ymcdn.com/sites/www.digitalanalyticsassociation.org/resource/resmgr/PDF_standards/WebAnalyticsDefinitionsVol1.pdf

How did it all start ?

Figured it is only appropriate to write (and learn) about the history of web analytics for the last blog of the session. In addition, it would be interesting to find out whatever happened to the firms that had pioneered this industry; spoiler alert, most of them are no longer with us.

Origins

The first idea around creating web analytics, the accumulation and analysis of traffic and visitor behavior, came to fruition around 1992 (1). During this period this was a capability needed by administrators that wanted to get transparency into activity on their sites to ensure site was actually functional and it was up and available.

Probably, shortly after marketing firms started to look for ways that this information could be utilized to reach customers in a more efficient way. And it seems like this was the moment when the responsibility for web analytics moved from the technology division to the marketing teams.

Where are they now ?

In the beginning, 2 different schools of web analytics emerged, front runner to the birth of 2 types of analytics vendors (2); software retailers similar to WebTrends (still in business as an independent company!) and NetGenesis (which hasbeen acquired by SPSS in 2001) and ASPs (Application Service Providers) including Urchin (acquiredby Google in 2005) , Unica (now part ofIBM), CoreMetrics (anotherIBM target) and WebSideStory (boughtby Omniture which was later acquired by Adobe) which offered browser tag based approach. The “in-house” approach used installed application on a local hardware and meant to review data gathered in the web-logs. The other approach, Application Service Providers, tried to utilize the hosted solutions to view throughput and other relevant information. (3)

In the mid 90’s introduction of affiliate concept spurred an era of predictive web analytics shops and the first the company to came up with this idea was a small two year old company called Amazon (4) and popularized mainly by on hobby sites. At any time, a site could have a bar on top of their site with banners that connectedtheir affiliates. Usually, these sites (or affiliates) would have some common attribute with the other affiliates. As these relationships got more sophisticated, affiliate concept started to include sophisticated software which enabled the site to order links based on the visitor volume they got form their affiliate sites, basically incentivize affiliates to include links on their sites to swap visitors. Near these banner bars was usually a link to an external analytics service, where affiliates and site visitors could see how many unique visits the site received per day. (5)

Increasing amount of websites utilizing this sort of affiliate program drove the explosion in external web-analytics start-ups, and subscription driven services slowly started become more prominent. In the beginning, these subscription based offerings primarily targeted large enterprises, but over time started to target smaller entities and personal websites as they became more available and affordable with the emergence of e-commerce.

Following the dot com bubble burst, early 2000s, the web analytics industry entered an era of consolidation that even continues today and very evident a few paragraphs ago.

The Dilemma

I think the main question at this point is, whether such a rapid consolidation of a new field like web analysis raises the question of less innovation down the road. Obviously, in a very short period of time the huge technology companies Google, Adobe and IBM acquired almost all small, agile start-ups that had started the analytics paradigm. However, the obvious counter argument is these corporations have the means, both intellectual and capital, to fund costly software initiatives which could very well spurs growth and innovation. Only time will tell.

Meanwhile, Microsoft with 66 billion in equity (6) is nowhere to be seen in this market since 2009. I think it is not unfair to categorize this as an “historical” surrender and an interesting side note.

What is next ?

Finally, as the field matures, the new frontier and sure to be an historical milestone one day is the web ethics, that raises the question of the data should be collected and used. One thing is for certain, as the debate around ethics on the web, the utilization of cookies, tags and storing data increases, the analytics area will be impacted. It is going to be fascinating to see where the web analytics go next.