New Search Engine

A slightly early holiday gift from the web team: new search!

Just before break, we finished our migration away from our Google Mini to Google’s hosted Site Search. We hope you’ll find it more reliable, more accurate, and easier to use on your phone. Try it out at lanecc.edu/search, or using the megamenu at the top of most Lane web pages.

Happy Holidays!

Search Engine Feedback

Have some feedback?

We're always interested in learning how to better improve our search engine. If you couldn't find something, fill out the form below and we'll do our best to find what you were looking for and fix it for others in the future.


Please include the exact text you typed into the search engine
Consider including what you expected to find, as well as a brief description of what you did find.

Thanks for your feedback! If you'd like us to get back to you, please include some contact information here:

Search Visualization

Not too long ago I wrote a post on how we use search data to influence our information architecture decisions. In our quest to be even better, we’ve made a few modifications.

Originally we were only looking at keywords (each of the words you search for) and queries (your exact search, often a phrase). As a refresher, here’s the graph of our common queries at the time:

Graph of Common Search QueriesRight away we can see some redundant queries. “staff directory” and “directory” are really people searching for the same thing. Similarly, “campus map” and “map” are both people looking for the campus map. Although this is useful information to know, as it lets us figure out what terminology to use, it’d be nice if we could condense things so we just saw what people were trying to find – these are the sites that should be more prominently linked.

So our first change was to condense the number of queries, by grouping related ones into their most common term. We didn’t do it for all of them – just the top 300 or so – but it was enough to represent the majority of our search traffic. Our second change was to increase the amount of data for better accuracy. We’re now looking at the top 500 keywords and queries every week, instead of just the top 100. After 12 weeks, that gives us 1523 different queries, and 921 different keywords.

That much data means we needed a new, fancier way to get a big picture of it. Conveniently, as part of a different project, I’ve been learning to visualize data using d3.js *, and the thousands of points in our search data make a perfect starter project for me.

To really see the power of d3, you’ve got to see the graph in person. But here’s an image, in case you’re on an older browser (IE7 & 8 support is sketchy):

top 50 Search Query, using a streamgraph
Top 50 Search Queries

This particular type of graph is called a streamgraph. To read it, click on it to go to the website where it’s actually hosted, then mouse over a particular band. The width of that stream represents the proportion of traffic that searched that a particular query. The thickness of the river represents the total amount of traffic. Because a streamgraph sits around a central line, rather than a bottom line (like the one in the first image of this post), it’s easier to see changes in volatile data.

If you look at the graph on the webpage (and not here!), you’ll see a few dots below the graph. Mouse over them to see annotated events that we think might have contributed to sudden search bursts. Some of them, like the ExpressLane burst, are obvious. Others are just my guesses. And others are totally unidentified. If you have any ideas what might have caused one of those bursts, let me know in a comment, so I can have an even better understanding of how our site is used!

* I also cheated and used a project called Rickshaw, which provides an even gentler interface to d3 for time series data.

Search Statistics

I promised earlier that there’d be a follow-up post with new and interesting search data from our Google Mini. I’ll do my best to geek-out with as many stats as I can.

Google’s search statistics are given for for two types of data: queries and keywords. A query is the actual search performed on the search engine, for example “Labrador Puppy”. The keywords are (mostly) the words in the query. For my example we’d have two keywords, “Labrador” and “Puppy”. Some keywords, such as “the” or “and” we choose to ignore – no one is seriously searching for “the” on our website and expecting to find something meaningful.

Every Monday we collect data on the 100 most common queries and keywords from the previous week. After two months of collecting data, we’re have 190 keywords and 330 queries in our database. Let’s look at just the top 15 of each:

Graph of Common Search QueriesThis graph is called a “Stacked Area Graph”, and it helps us to compare not only queries against each other, but also to see how queries change over time. So, in this chart, it appears that 6/2 was the busiest day on the search engine. In reality, because we’re only looking at the top 15 queries, we’re seeing some skewed data. If you look at all 300 of the queries we’re tracking, 6/2 was actually one of the slowest days.

So what can we learn? For one, we can learn what people are having trouble finding. The most popular search on our search engine has been for “soar”, and that it peaked last week – right before SOAR happened yesterday. This might be a hint that people were having trouble finding SOAR information without searching for it – a good indicator that maybe a more prominent link to SOAR should appear before the event.

We also see a few queries that should be combined. “map” and “campus map” is one example, “staff directory” and “directory” are another. We’re not combining them in our data right now because we want to see what people call things. For example, we can tell that more people are searching for “staff directory” than just “directory”, so it’s probably better to call our future staff directory (yes! this is coming!) a “Staff Directory” instead of just “Directory”.

We can also start to wonder why “library” was such a common query on 6/2, which is right around finals. If there’s often a lot of searches for the Library just before finals, we’d probably want to feature something on the Library on the homepage, to make it easier to find.

Graph of 15 most common KeywordsKeywords help us in different ways. Here we can see that our most popular keyword, “classes”, is actually used in searches more than any of our actual queries. So we know that many people are searching for classes, using a variety of queries. So we should probably investigate our analytics figure out where people are going after searching for classes. Then we can try to make those pages easier to find.

While there’s certainly improvements to make, most of this data is simply baseline information for after we finish revamping our information architecture. Then, as we implement our new Information Architecture, we should be able to see how that impacts our search traffic, to see if we’re providing a quantitatively better experience.

And to think, there’s thousands of data points inside the mini, and we’ve barely scratched the surface!

 

Search Tips & Our Mini

As previously mentioned, we’ve been tuning our Google Mini the last few weeks. Hopefully you’re getting a much better search experience. But to make sure you are, starting yesterday, when you do a search on our search server, you’ll find a blue bar at the top. If you do a search on our site and don’t find what you’re looking for, click the link in the blue bar and let us know! I’ll do my best to try to figure out what went wrong.Thanks Jace Smith for the suggestion to make a feedback form in the first place!

The Google mini is also going to provide us with lots of interesting search statistics. While it’s too early to look at them now, it’s not too early to talk about how we’re going to use these statistics to make a better website. Every week we pull a list of the 100 must commonly searched for keywords and phrases. Over time, we’re going to look for trends and try to learn what people can’t easily find on the website. So, if “Bike Lane” keeps showing up, we’ll know that we’re not doing a very good job of making “Bike Lane” easily findable on the homepage, and we’ll try to fix that.

We’ll also be using these statistics to improve the actual results of the search. For example, if we notice that people keep searching for “nuring”, we’ll tell the Google Mini to search for “nursing” instead. Or if a department changes it’s name, and people keep searching for the old name, we can tell the Mini to search the new name and save lots of confusion.

I should also note that although I’m trying to make the mini work as awesome as I can, I can’t control what Google does. So when you search on google.com, that has nothing to do with our search engine, and there’s only so much I can do to improve your results. That leads us to Search Engine Optimization, which is much too big of a topic for this post.