Where do visitors go?

One of our goals for this redesign has been to simplify the website navigation for our  visitors. We’re taking a three pronged approach:

  1. Reduce the number of pages on the site
  2. Unify navigation
  3. Simplify entry page navigation

The first one is the most rewarding – we’re getting rid of pages. So far, we’ve cut 5920 pages by either deleting or moving them to a separate archive site. Hopefully we’re narrowing the focus of our site and reducing the number of links that would take you away from what you’re looking for.

The second two approaches are much harder, and will be the focus of this post. Both require a pretty serious knowledge of where people go our our website, as well as what people are looking for. The first place we’ll look for this data is our own internal search traffic, which we graphed a few posts ago. That gives us 50,000 searches for 3700 different terms over the last three months. We’ll scale it by a factor of 4 to get an estimate of what traffic looks like over the year.

Our second source is much bigger, 1,000,000 searches on Google for 500 different terms. We can immediately throw out the 83% that are people searching for the Lane homepage. Then we can combine similar searches: in addition to obvious misspellings, like “Modle” and “Moodle”, there’s terms like “fall classes” and “spring classes” that are really just searches for “schedule”. It’s important to combine the right things –  if we combine too many terms, we’re losing an opportunity to provide a more direct link to a resource. But if we combine too few, then our rankings might not be right.

When we’re all done, we can combine the Google searches with the internal searches, which leaves us with 278 different search terms. Here’s the top ten:

Search Term Google Internal Total
staff directory 8569 7832 16401
mylane 14196 1520 15716
moodle 12314 1756 14070
map 7934 5944 13878
testing 4036 6384 10420
library 6326 2928 9254
jobs 6594 2148 8742
nursing 3403 5252 8655
downtown center 5791 292 6083
express lane 2631 3312 5943

Our next step is to look at our actual page views. That’ll let us validate our search traffic, and tell us where our current navigation works. If a page is getting visited a ton, and no one is searching for it, then we did something right… right?

We’ll look at our 500 most popular URLs. Once again, our first step will be to combine them where appropriate, a job made somewhat more difficult since we’ve been switching URLs around as we move into Drupal. We’ll also look out for things that unfairly influence our page counts. For example, some of the computers on campus automatically open to the computer labs landing page – 65% of the page views on that page are “entrances”, meaning it was the first page viewed. To account for this, we’ll subtract the number of entrances, minus the number of times “computer labs” was searched (searches also generate entrances, and we don’t want to discount those). Our page views will now be:

Views = Views – (Entrances – Traffic from Search)

Sadly, that’s a real pain to calculate due to how our data is set up. But we have a pretty good idea of where this is applicable, so I’ll hand calculate it on the half dozen pages where it’s needed.

When we’re done, here’s our 10 most popular pages:

Page Pageviews
/schedule/ 1560548
/collegecatalog/ 196972
/library/ 148587
/explanestaff/ 144550
/calendars/academic.html 112589
/counseling/steps-new-students-enroll-credit-classes 94353
/collegecatalog/career-and-technical-programs 93282
/testing/placementtest.htm 91167
/esfs/admissions 89131
/es/students.html 83761

I’d rather use unique pageviews, to see what pages are important to people, rather than the pages visited most, but unique pageviews are impossible to accurately combine. But we’re really just doing a back of the envelope calculation here, just finding a starting point for our navigation. We’ll perfect it as we look at how people interact with the website after the launch of the new design.

At a quick glance, we see some differences between here and the search data set. But that’s somewhat explained by looking at the pages people go to while applying for admission – the steps to enroll and /esfs/admissions. It seems people don’t search for the application, they search for the institution, then apply. But overall, there’s a good deal of overlap in our two data sets. That’s good – it means our search data is a fairly valid representation of what people look for on our website.

As part of the new design, we’ll be adding landing pages for each of our visitor types. Students, Employees, Future Students, and Community Members will all have a page full of relevant links and information. Since each of those pages will be linked from the homepage, we can create a goal: within two clicks of the homepage you should be able to access all of the pages that account for at least 85% of our page views. Put another way, if you land on the Lane homepage, there should be an 85% chance of getting you where you want to be with only two clicks of the mouse.

In addition to the landing pages, we’ll also have a dedicated Mega Menu on all of our pages on all of our sites. Since there isn’t as much real estate to work with, we can’t have quite as many links. But we’ll also need to use all of the data we’ve collected to build these links with the same goal – the pages people need should be easily accessible.

Unfortunately, now we’ve reached the point where things get a little more subjective.

  • Some of these links aren’t relevant for some of our visitors. Most new students don’t really care about staff instructions for accessing email.
  • There’s still grouping to do. We can’t link to each department, but we can link to a department listing. There’s a couple options for this.
  • Some pages, like guest lecturer information, were only relevant this last year.
  • We need to consider marketing needs. There’s often a program or event that we’re trying to advertise to campus. We cannot ignore this need – it’s how new programs are discovered.
  • There’s some things that aren’t links that need to be added to those pages. One example would be announcements about things like financial aid deadlines. We need to get that information out, but it won’t show up in either of our data sources.

In order to avoid any bias from me, I’ll convene a group of people to dig through this data a bit more and build our links and menu using both the search data and the list of popular pages.. When we’re done, it’ll be time to start testing. Expect updates then!

Unplanned downtime, 10/29

Our apologies for the unplanned website downtime around 10:30 this morning.Everything should have been working again by 10:40.

As part of our process of modernizing our servers, last week we upgraded the operating system software running our website, making some improvements as we did it. Unfortunately, there was a mistyped IP address, causing the server to hiccup a couple times a day.The really bad news is that while fixing that this morning, the networking service froze up, causing the server to stop responding. A quick restart fixed things.

Things should be fixed now. And the silver lining to all of this is that we further tuned some database parameters this time around – the administrative interface to the website should be much faster than it was.

Analyzing Traffic on the Lane Website

I was on a bike ride through West Eugene the other day, and I got to thinking about people that visit the Lane Website. What is it they’re looking for? What pages do they go to? Where do they come from? What web browsers do they use? Where are they from? I couldn’t wait to get home and find out.

So as soon as I got home, I fired up Google Analytics and started digging around. It wasn’t long before I realized that I wasn’t going to just find a couple quick answers to my questions. Every answer I found raised two questions. There was a lot of exploring to do. So over the next few months, every Friday I’m going to try to make a post about analyzing some particular aspect of our website. Hopefully it’ll help us refine the designs we’ve been working with for the website redesign.

We’ve been tracking visits to the Lane homepage since 2008, giving us lots of data to work with. So much with that it’s almost impossible to draw any conclusions – think about how things have changed on the Internet in the last five years! So, for the purposes of this analysis, we’ll mostly be working with data from the last year – Oct 15, 2011 to Oct 15, 2012.

While we analyze that data, it’s helpful to keep some simple statistics in the back of your mind, just to help frame things. This way you’ll have an anchor in mind – so that if I tell you that some website sent us 150 visits last year, you’ll know that isn’t many when you’re talking about a website that sees 4.8 million visits a year. Here’s the stats:

Visits 4,872,025
Unique Visits 1,420,264
Pages/Visit 2.57
Avg Visit Duration 00:04:00
Bounce Rate 59.06%

Bounce rate is a helpful term to know – it simply means the number of people that saw one page and left. A high bounce rate is good on some websites, where people just go for quick bits of information (like a thesaurus). But on our website, where we want people to learn and explore a little, we generally want a low bounce rate.

Next week I’ll post about how people actually find the Lane Website, and I’ll try to update this post with links to subsequent posts as we go:

And now’s a good a time as any to plug what we can do with Analytics for your website. If you’ve got a website on campus and you’re interested in how people find and use your website, send Lori Brenden or me an email. We’ll hook you up.