A couple months ago Karine Joly launched the analytics revolution in higher ed by asking everyone to fill out a survey about the state of web analytics in higher education. She received 399 submissions.

The executive summary is out and available at the HigherEdAnalytics website. Taking a look at it, a few initial thoughts came to mind. I’m just going to run through them here in no particular order.

First, I was ecstatic that 95% of respondents track website traffic (I know it’s not 100% but in the words of Bill Murray – baby steps). What struck me, though, was that a full 35% did not track any conversions and of the 65% that do, a minority track clickstream and conversion from marketing campaigns (email, online advertising, print, etc.). Now, this may just mean that they aren’t in the marketing department. I’d love to see that data segmented by department. I’m hoping that the majority of folks in the marketing department do indeed track those stats. What’s more – even those folks *outside* the marketing department should be tracking if they do any kind of external communication via emails, social media, etc.

The report also states that 15% of respondents said they do nothing with the data. That makes me sad. : (

The most interesting part of the report for me was around tracking conversions. The  “would like to track” column being the most intriguing. To me, this shows that we *want* to measure conversions, we just can’t for one reason or another. In other words, we need help. The more I wondered about it the more I wondered about the reasons why we don’t (or can’t) track conversions … maybe:

1. The conversion doesn’t happen on our website and the third party site is either unable or unwilling to allow us to track.
2. If the conversion happens off our site, we don’t have the right technology in place to tie a campaign to a conversion (let’s say a submitted inquiry form or application).
3. We don’t think we have an actual conversion to track – for instance if the particular website in question is only informational, etc.
4. There are several owners of all websites and to try and track traffic much less conversion is so complicated and political that it’s just not worth it.
5. Folks are worried about the implications for privacy.

Whatever the case, it seems as though we really want to. Now we just need help to be able to do it.

Another area of the report that was interesting was the question, “who spends at least 20% of his/her time working on analytics?” 35% responded either 1, 2, or 3 people. This astounds me – in a good way. I was shocked to find that number so large as I realize that so many people in the higher ed web world are jacks of all trades. Obviously it would be awesome if at least some reported that, “it’s my entire job,” but … baby steps. As an industry we’re certainly nowhere near that yet. It’s definitely a good start, though. I know there were 50% that responded nobody : ( but this surprised me much less. I actually thought that number would have been higher.

Although the majority of people said they were tracking the basics – visits, page views, etc, when we get past the basics, the percentage really drops off. I wonder why. Is this because of a lack of resources? Is it because of the lack of *insights* we’re getting? If it is the lack of insights, the catch-22 here is that you’ll almost never get insights from the very basic metrics, especially if there is no segmentation (unless your site is down and your visits just flat-lined). That was something I also wondered about.

Anyway, I think the report shows both that we’re doing great stuff and there is also a long way to go. But we’re headed in the right direction. : )

Making web analytics a priority

So let’s get this party started! Starting August 12, on the 2nd Thursday of each month, we will be collecting data to start the analytics revolution in higher education. Karine’s group will then release the benchmarking data from the previous month at the end of month. For example, July’s benchmarking data will be released at the end of August and so forth.

To get a benchmarking report, all you need to do is participate in the benchmarking. Go to the HigherEdAnalytics website to join the revolution.

So, I’ve blabbed long enough. Go read the executive summary. I’d love to know your thoughts.

It’s about time we start a revolution … and we need your help! You know how important web analytics is for higher education websites, but we need to spread the word. So, where do we start? With a benchmark, of course.

Last week Karine Joly launched the “State of Higher Ed Online Analytics” survey to get a better idea of where we are as an industry with our use of web analytics.

Complete the survey today!

Enter your email address at the end of the survey to receive an executive summary in July highlighting the survey results.

Thanks to Karine for putting together the survey and starting the revolution!

Survey closes on May 24th.

Later today our annual inter-squad scrimmage (the “Blue/White game”) will be televised on EPSN2. We have a commercial airing twice during the game and I’m getting ready to track the impact on traffic to our site.

Obviously this won’t be a super popular game on TV – mostly very loyal fans and alumni, but that’s ok. It will still have some impact.

Here is what I plan on monitoring over the weekend to see how much of an impact the commercial (and even the game) had on traffic:

1. Visit trend
2. % branded keywords referrals
3. % direct traffic
4. % referral traffic from our main university website (psu.edu)
5. % goals completed from branded keywords referrals
6. % goals completed from direct traffic
7. % goals completed from main university referral traffic

When looking at these reports, I have to remember that “like” date ranges matter. For instance, I won’t want to measure the difference in those metrics from yesterday to today because I know that our traffic goes down naturally on weekends (Friday and Saturday aren’t like days). This weekend should be compared to last weekend. Further, I need to keep in mind that the game itself (regardless of the commercial) will likely have an impact on traffic. Unfortunately we don’t have a “like” weekend to run it against (a weekend where our blue/white game aired on ESPN2 without the commercial). So, we’ll have to make due with just realizing that the commercial itself may not have caused the traffic.

I do think the metrics that have to do with branded keyword referrals and direct traffic can show impact from the commercial itself. Why? Because they have to do specifically with users seeking us out by our unit name (not just happening on our site or coming to our site from our main university site).

What do you think? What other metrics should I be looking at?

This post is long overdue. I wanted to do a review of Brian Clifton’s book Advanced Web Metrics with Google Analytics (second edition) last month when it came out. For those of us in higher education, this book is essential reading. Period.

When it comes to web analytics and, specifically Google Analytics, Brian Clifton is at the top. The book is the second edition, but it is so much more than just an update of the first book – it’s almost a complete re-write. So much has happened since the first book came out. You can read all about it over on Brian’s blog.

Full disclosure: I was lucky enough to read the book before it was published and offer feedback and comments. I’ve never done that before, but what an excellent learning experience!

So, let’s get down to the book. The name of it says “advanced” but you don’t need to be an advanced user of Google Analytics to get a lot out of it. It takes you from the very basics of what web analytics is, how to get started with both web analytics and Google Analytics all the way to advanced topics and techniques.

Great content for higher education website owners.

Google Analytics vs. Urchin. There’s an entire section in the book about Urchin – the differences between Urchin and Google Analytics and how to choose which one fits best with  your organization. There have been a lot of questions lately about which one is better and what the differences are. This section spells out everything.

On Data accuracy. There is a large section that goes into data accuracy and implications. There is a great part about data misinterpretation that’s essential for newbies and really a good reminder for everyone. This section makes me think of when we deliver reports to leadership. We’re asked all the time why numbers don’t tie out, why unique visitors doesn’t mean “people,” why we don’t want to show hard numbers. This section has some great answers to those questions and much, much more. Photocopy the section and leave it on your boss’s chair.

Reports and implementation. The middle of the book goes into reporting and correct implementation. It’s here you’ll get the nitty-gritty of what each report means and tips about how to implement correctly – including advanced implementation techniques. There is an entire chapter dedicated to “best practices configuration.”

Key performance indicators and real-world tasks. My favorite part of the book talks about key performance indicators and goes into KPIs by job function – the marketer, the webmaster, the content provider, etc. This is where most people get stuck with web analytics – what do I measure? I have all this data to look at and I’m not sure where to start. Start here.

A couple of great KPIs that caught my attention:

• % Brand Engagement – # of visits with branded search terms + # of direct visits/total visits from search engines+total # of directs
• Conversion Quality Index – % goal conversions from referrer X/% visits from referrer X

From the book,

… the conversion quality index (CQI) is all about measuring how well targeted your campaigns are at driving conversion on your website.

Monetizing a non-e-commerce site. One of the things that is the key to getting leadership buy-in and getting things done is the ability to monetize as much as possible. Monetizing a non-e-commerce site is a section we should use to “kick it up a notch.” It talks about assigning goal values and enabling e-commerce reporting for our non-e-commerce sites.

I’ve been experimenting with the first technique (assigning goal values) and using average page value ($Index). This is a great metric that shows if a specific page is generating conversions. For example, if you go to the content report and sort by $Index, it will help you prioritize pages. What specific pages are contributing the most to your conversions?

But what if our *goal* is offsite? In higher education there are so many instances of our *goals* happening off our website. Sometimes they are on a sub-site within our domain. Sometimes they are on a completely different domain – a third party vendor or the like. How do we track to the conversion? There is a section explaining how to do it.

Those are just highlights. There’s so much more.

<update>

One thing I forgot to mention, which should have been front and center and I apologize , is the fact that this book goes deep into all the added functionality of GA in recent months and since the first edition of this book came out a couple years ago. The one new feature of GA that I’m most impressed with is their Intelligence section. I’ve worked with other tools that you can set up alerts with (if our visit rate goes below X, notify me), but I’ve never worked with a tool that will basically do that for you. Of course you can set up custom alerts, but this is different. It alerts you when things are *out of the norm* automatically. We’ve found this so useful. Brian goes into describing exactly how that happens how GA knows something is out of the norm – or how they describe – is a *significant change*.

</update>

For those of us in higher education who use Google Analytics, this should be required reading. Everyone knows that “web analyst” just doesn’t exist in higher education. We’re all jacks of all trades. This is probably the biggest reason this book is so relevant to us. Heard of a technique but just aren’t sure how to go about actually doing it? Brian talks about a technique and then steps you through how to implement it. It does tend to get a bit technical in parts, but for us, that’s a good thing.

I’ve written about segmentation in the past, but I still don’t think we give it the importance it deserves. There are so many valuable insights you can gain from using segmentation. Even more important, if you are only looking at your data in aggregate, without segmenting it, you can be making decisions based on misleading information.

Take this example – let’s say you open up your analytics tool and see that, on average, users view 5 pages per visit. Ok, pretty good. You take note and move on.  But if you used segmentation, you might see that the pages per visit is completely different depending on the type of user. Let’ say on average:

• IE users view 7 pages per visit
• Firefox users view 4 pages per visit
• Chrome users view 2 pages per visit
• Mobile users only view 1 page per visit
• Campaign A users only view 1 page per visit

Of course these are made up numbers, but you get my point. Doesn’t this tell you much more? My site doesn’t seem to render well on mobile devices and campaign A needs a good look.

The fact that my site averages 5 pages per visit actually tells me absolutely nothing.

This is why segmentation is essential. Averages are misleading.

Filters and Advanced Segments in Google Analytics

In Google Analytics you can segment users in different ways – the 2 main ways are using filters and advanced segments. Which one should you use?

When choosing between a filter and a segment, I usually go with this rule of thumb – if it’s a permanent segment, let’s say you *always* want to filter out internal traffic, then I’d create a filter. This is because filters segment out before the data gets into the reports. This also means that if, down the road, you no longer want to segment out internal traffic, although you can delete the filter, you can never get the data back.

For this reason, always keep one profile that has no filters.

If, on the other hand, you need more flexible segments – segments you want to turn off and on, then use the advanced segments feature.

Advanced Segments will help you make better decisions

For this post, I’m going to talk about using advanced segments, not filters.

The segments you use will depend on your goals. In the example above, if mobile visitors aren’t a priority right now you may not even look at that segment.

Almost all analytics tools offer segmentation now. Google Analytics released advanced segmentation about a year and a half ago. It’s amazing to me, though, how many Google Analytics users still don’t use this essential piece of functionality.

There are built-in advanced segments and also the ability to create custom segments. Google has both instructions and a video on creating your own (custom) advanced segments.

New and Returning Visitors

One of the most fundamental segments you will probably use is new and returning visitors. See how these 2 segments use your site differently. What’s the different in bounce rate, top landing page, referring keywords? For referring keywords, you might find that new visitors use more general keywords and returning visitors use more branded keywords.

Visits from Social Media sites

Creating a segment for social media sites will help you answer the question on everyone’s mind nowadays – what is our social media ROI? Of course there is a lot more that goes into that, but this segment will help. Don’t forget to include all social media sites that your audience uses. This means going beyond Twitter and Facebook.  Segment your social media traffic and see how they are behaving on our site. Are they converting? Are they doing something else? Of course this goes back to your social media goals. Is this segment doing what you want them to according to your social media goals?

Visits from a specific campaign (or campaigns vs. organic traffic)

This is another one of my favorite segments. First, how does your campaign traffic act differently than your organic traffic? What about pages per visit, internal site search keywords, time on site?

Next, to answer questions about how a specific campaign is performing, create a segment for traffic coming in only from that specific campaign. This will give you such great insights into campaigns – beyond just conversions and bounce rates. If you have a poorly performing campaign, use this method to dig deeper and find out why. High bounce rate or low conversion rate? How about looking at the internal site search keywords this segment uses to find out if it’s good or poor quality traffic?

Another use for looking at this segment is find out what else visitors from a specific campaign are doing on your site. It might surprise you to find out that a campaign for one area or program is actually bringing in traffic that is interested in another area or program. You also might find that traffic from this specific campaign are doing things other than the end-conversion. Maybe they are watching a specific video or visiting specific pages.

Internal vs. external traffic

Depending on your site and its goal and intended audience, you may even want to filter out your internal traffic. If you don’t use a filter, though, consider at least building segments for both. This way you can easily see how these 2 segments act differently. Chances are these segments act *very* differently.

Search Engines (from specific search engines or all organic traffic)

Segmenting on organic search traffic can bring valuable insights as well. Then you can drill into each search engine, see how much each is bringing. Further, drill into important keywords (within each search engine) and see the trend of traffic from those. Is it going up or down? Were you ranking for an important keyword, but now you’re not getting a lot of traffic from it?

Conclusion

Obviously there are many other segments you can use to help. These are just 5 that I’ve found very helpful. The important thing is to go back to your website goals and to use segments relevant to those. If your goals focus on geography (let’s say your continuing education or a community college) you may want to segment by state or region or city. Likewise if you have a goal of being more mobile-friendly next fiscal year, you can create the relevant segments to help you see how your mobile traffic is performing.

What other segments do you find helpful?

I love talking to colleagues about web analytics and yesterday I got to do just that – but on a much larger scale.

A little background … Penn State is very large. We have about 43,000 students at main campus and about 78,000 students throughout all of our campuses. Needless to say we have a lot of websites – I can’t even guess how many we have – 200? 400? 500? Not sure. It’s a lot, though. That much I know.

With so many websites owned by so many different units, community is so important. We have a great web community with a fantastic annual web conference and yesterday we started a different kind of web community – one devoted to web analytics.

Since most units at Penn State use Google Analytics, it was called the Google Analytics User Group kickoff event. Going forward we’re probably going to call it something less tool-specific, but we’ll see.

Some great folks at the Penn State Libraries – including doteduguru Nikki Massaro Kauffman – put the event together. It was an awesome event  and the attendee list was completely full only a few days after invitations went out.

We gathered in the morning at the libraries to kick off the event with an open panel – discussing how Google Analytics was being used at the university within different departments. It was so great to hear the different ways web analytics is having an impact at the university and how website owners are using it. Experience with the tool (and analytics in general) ran the gamut from just getting started to years of experience.

There were many sessions throughout the day including methodologies (which led into a discussion about privacy issues), Google Analytics implementation, new users, and reporting.

At the wrap up discussion we talked about how we will continue with the community. I’m very excited to continue the conversation within Penn State and we already have ideas of specific projects going forward. What a great way to end the week! I’m excited to continue the conversation.

I recently read Joseph Carrabis’ fantastic posts – The Unfulfilled Promise of Online Analytics part I and part II. If you haven’t read them already – do so. They are so thought-provoking and written like no other analytics posts you’ll ever read. Really great stuff.

For an analytics evangelist like myself, reading them was both a breath of fresh air and a punch in the gut.

It got me thinking about web analytics in general, but also in our little corner of the internet – the higher education websites. There are so many limitations as far as online analytics is concerned and, as Mr. Carrabis points out, most of it is because of people. Yes, people. People in the analytics industry. You. Me. All of us.

Why am I bringing all this up you may ask? Why not? I’m still an analytics evangelist, but I acknowledge the fact that there are holes … big holes that we need to work together to fill up. I also acknowledge the fact that higher education is *years* behind other industries when it comes to analytics – all analytics.  Sometimes I think this may work to our advantage.

If you really think about it, we aren’t unlike other industries in what we want to get out of our websites. We also aren’t unlike companies that have issues with web analytics – numbers don’t add up, leadership doesn’t take the recommendations of the analysts (that are based on *facts*), leadership doesn’t *trust* the numbers, etc.

They do have a point. The web analytics industry has yet to have any real standards. Definitions, tagging, metrics, are different from tool to tool. Because there are so many variables involved, numbers will never tie – heck numbers often don’t tie between tools from the same darn company because they gather the data differently between those tools. From the same darn company! It’s enough to drive you batty.

There isn’t a ton we can do about that right now, though. Question for all of us – have we done all we can to get the most out of these tools, even with all their limitations? We complain all the time (why can’t I do this or this or this) – I know I complain. I’m very guilty of this.

At most our institutions, the current times have given us the opportunity (yes, opportunity!) to scrutinize what we do more. To look at the numbers more. Website analytics is a small part of the larger analytics picture, but it is a part. It’s a very important part and it will only get more important.

Where can we do better? Let’s talk about training. How many of you in higher education have been trained in your analytics tool? I’m talking real training, whether it’s self-taught or classes, or consultants, or anything. I’m also not talking about, “training in your spare time” because we all know how that goes.

From Mr. Carrabis:

… the use of any tool is going to require training across the usage spectrum. The use of new tools definitely so. This training can be self-training and the user should be prepared for scraped knuckles, smashed thumbs and lots of cursing. Self-training is great when the user has lots of time and patience. Otherwise, take a class or let the experts (”consultants”) in.

He goes on to say:

More training is the answer only if the training results in well-reasoned and understandable business actions*. Tools and trainings are worthless without knowing what one wants to build (”It reminds me of the development of web sites themselves ten years ago – everybody had to have one, still not being absolutely sure what to use them for. Of course the free tools have done their part in this evolution.”).

So, although the analytics industry has to get there … eh em … stuff … together, we do as well.

Bright Future?

So let’s get to the “bright future” part of this post before everyone ends up throwing in the towel and going back to the homepage hit counter. Yikes!

I really do think that web analytics has a bright future, especially in higher education. Some thoughts:

1. Web analytics is young. Avinash Kaushik has said it’s a toddler. When it comes to higher education, I’d say web analytics is an infant – still wearing 0 – 3 month clothes. We’re trying to figure all this out. We’re still at the joke-forward stage. Remember when you were first introduced to e-mail? You’d get jokes or stupid chain e-mails and forward them to your entire address book because it was something that was new and cool and you weren’t quite sure what to do with it? Today, if you get joke forwards or chain e-mails you either reply to sender cursing him/her out or just delete it without reading. Higher education is still there with web analytics. We spit out visit reports, see an increase after a certain marketing campaign and say, “cool, a  job well done” and nothing more. This is good news for us, though. There is nowhere to go but up! But, if we don’t change and evolve, this can be bad news. 2 years from now we shouldn’t still be forwarding jokes!
2. Higher education is slowly but surely coming to respect the power of analytics (not just web analytics!).  With a little centralization, some training, and some resources, we can do this. Should be easy, right? : )
3. Web analytics vendors are starting to feel the pressure from end-users to improve their products, both functionality and customer/technical service. Google Analytics alone has come out with a ton of new features just in the past few months. Remember, however, that we must practice (training!) using them or new features don’t mean a thing.
4. The web analytics industry is trying to standardize definitions. They’re not there yet, but they’re trying.

I hope that I’m not wrong on #2 above. With some of the conversations I had at HighEdWeb in October I may be. What we have now is better than what we had a year ago. It’s better than what we had 4 months ago.

Let’s face it – with the economy and layoffs, and everything else that’s going on in higher education these days, we are being asked to scrutinize more than ever before. For those of us that came from another industry, this is nothing new. Even with all the limitations, analytics has a lot to offer, but we must educate ourselves and leadership. We must continually ask for training and show leadership why it’s so important. Secondly, we must educate others on what web analytics can and can’t do. It cannot tell you how many *people* clicked a certain button while standing on one leg wearing a red t-shirt. It is not the be all, end all. It can tell you how many times that button was clicked, and using segmentation, what other things during those visits. to your site. If you’re using both quantitative and qualitative analytics, you can start to know not only the “what,” but the “why” as well. To me, that alone can tell you so much. So much so that it’s definitely worth the time and effort. As for the limitations – I’ll take them … and move on.

PostScript: My apologies for a stream of consciousness post. The 2 posts mentioned really got me thinking and this post is an attempt to articulate those thoughts – it may be a poor attempt, but it’s one nonetheless.

FYI … coming up within the next month - Look for a survey on the state of web analytics in higher education. After reading some analytics posts recently, I’d love to gather some data from higher education as to what we’re using, how we’re using it, etc. I really want to look in-depth, especially into how people are using the data (if at all).

*My emphasis

This will be a short post, as I’ve written about link styles before, specifically about how using underlined links in body text is still a best practice. If underlining is out of the question, then at least use a color that is in complete contrast to the text color. Why am I bringing this up again? I happened to be browsing some higher ed sites earlier this afternoon and I couldn’t help but notice that the trend seems to be getting worse, not better. Why?

Is it that we’re spending so much time focused on more complex user-friendliness issues (ie., can users navigate the site, is our online application usable, etc) that it’s almost like we’ve forgotten one of the fundamentals?

Dressing up link text with hover styles does nothing for the scanning eye. Finding what words are links on a website shouldn’t be an easter egg hunt. We should know *immediately* when we glance at a page that a word or phrase is a link, not after we move the mouse over it.

Take a look at these examples. Can you tell where the link text is immediately? Now imagine these little snippets were part of a much larger page with much more text. Do you still think you could pick out the links without really staring at the page – or worse, without “mouse hunting?”

There is 1 link in the above example.

There are 4 links in the above example.

There are 4 links in the above example.

There are 2 links in the above example.

There is 1 link in the above example.

Compare the examples above to these.

It’s interesting that almost all of the websites that don’t underline links use a different link style on hover, usually a vastly different style (different background color, normal-to-bold, underline, italicize, etc). Some of the hover styles add in the underline when the user hovers over the non-underlined link. What sense does this make? It’s not apparent that it’s a link until you hover? I don’t get it. There’s nothing wrong with hover styles. It can’t be the only (or easiest) way to find a link, though.

How could we measure the effectiveness of this? Good question. Can we really measure the effectiveness of changing our link styles? An easy way, obviously, is to do a quick usability test. Can we do it using our analytics tool, though? I think so. If your site uses Google Analytics and uses Site Overlay, you could measure before and after changing your link styles to see if making them more visible increase clicks. I bet it will. I think that would be an interesting test.

Let’s get back to basics and start underlining our links again. Who’s with me?

It seems that some (notice I said some, not all!) higher education web professionals still don’t think using web analytics on their site is useful.

Why do I think this? It became apparent after a couple conversations during the HighEdWeb conference I recently attended in Milwaukee. First, let me say that this has nothing to do with the conference. It was a fantastic conference and I learned a ton from the great presenters and attendees. I would go again in an instant.

More than once, however, I found myself in the midst of a conversation about how using web analytics is pretty much “useless.”

I doubt that the people in the conversation had any idea who I was (who would?) and that I was actually presenting at the conference about web analytics (both conversations took place before the presentation). So, I decided to keep my mouth shut and just listen. I wanted to see *why* they thought web analytics was useless on their sites before I jumped in to defend the practice.

Conversations like these happen all the time. They could have very easily happened at any of our campuses. In any of our offices. I’ve heard it all before and I’m sure I’ll hear it many times again. So, I’ll bring up some excuses I heard and offer some recommendations.

So … here goes …

We always meet our enrollment goals, so what’s the point?

The first excuse was that the university/college had a waiting list a mile long to get into the school, so why bother using web analytics to make the site more useful?

I’ve heard this excuse many times before, even by some people at my own institution. This, beyond anything else, is the most frustrating of excuses. Why? Because it screams, “I don’t care about my customers!”

For the sake of argument, let’s forget about using web analytics to optimize marketing efforts. Let’s just talk about usability in general.

To not use a tool that can help improve the usability of a website *and* help save money just because you’re meeting your [insert goal here] goals just doesn’t make sense. Without even mentioning the fact that you may not always meet your goals, let’s go straight to customer service. Do we not care about customer service anymore? Should the fact that “we aren’t Best Buy,” mean that we completely ignore the fact that our website might suck and that users might be frustrated?

But we run usability tests. We care about our users! Yes, usability tests are fantastic and we all should run them. But usability isn’t 1 and done. After your usability tests are done, you make your design changes, how do you know it worked? Making sure your website is useful is a never-ending task. Your content changes constantly, right? Then how do you know it’s continuing to be useful without continuing to look at the stats?

Secondly, web analytics can save you time and money. Do those in higher education care about whether they are losing money (hard and soft costs!) due to poor design? Your enrollment goals might be met, but how much money are you wasting on staff time when users call in because they couldn’t figure something out on the website?

We looked at the analytics, but all we saw was that *everyone* was clicking on [insert link here].

This is where segmentation comes in. When someone says, “everyone” did something, I always question that statement. Who is everyone? How many is everyone? Did you use segmentation? For example, did you segment out first time vs. returing visitors? Chances are, if that was a “current students” or “log in” link, the vast majority of the users clicking it were returning. So segment that group out. What were the *rest* of your users doing?

If you aren’t segmenting your data, then yes, in almost all circumstances the data will be pretty much useless.

Here is a very simple example:

So if I didn’t segment new vs. returning visitors here, I’d think that my bounce rate and average time on site might be ok (although 39% is pretty high for a bounce rate). I wouldn’t have a clue that we need to dig deeper with our new visitors and find out why their bounce rate is so high and they are not spending a lot of time on our site.

In essence, this data in aggregate is pretty much useless. When you segment, you begin to get great insights.

We don’t have time to really use web analytics.

I’ve written about this one before as well. If you truly want to be user-centric, you find the time. Period. Do you have *time* to run usability tests and analyze that data? Do you have *time* to read blogs, articles, and tweets about web design, development, or whatever, for your own professional development? No. But, you find the time. Why? Because it will benefit your users. The usability tests will help you find website issues. The blogs, articles, etc. will help you improve your skills thus helping you to create a better experience for your users. Isn’t that the idea?

That’s why I don’t buy the “I don’t have time” excuse. Nobody has time.

Recommendations

So none of my ranting probably changes the fact that some people still don’t think web analytics is useful. So, how do we solve this issue? Here are some quick recommendations:

1. Segment Your Data – As I mentioned before, if you are not segmenting your data, you will either a) make a potential wrong decision based on the *average* data or b) think the data is useless. Neither conclusion is good. Segment your data!!
2. Focus – Know your business goals and website goals. Develop key performance indicators. This will save you time and give you focus. Know what reports to look at and forget the rest. If one of your goals is to achieve better search engine rankings, know what reports will help you with that and only look at them for that goal. If one of your goals is to increase online course registration, know what reports drive users to that goal and look at those. And so on … forget the rest.
3. Create a Dashboard – This will also save you time. Again, look at your goals, know what metrics to look at to see if your website is achieving those goals (KPIs!) and create a dashboard using those reports.
4. Look at Your Quantitative and Qualitative Data Together – When you’re running your usability tests, surveys, focus groups, remember to look at your on-site web analytics as well (your quantitative data – the *what*) to see if it jibes with your usability/survey/focus group results (your qualitative data – the *why*).

What I usually find is that most people who think web analytics is useless don’t know exactly how to use it effectively. That’s fine. There’s nothing wrong with that. Don’t make the mistake of thinking that it’s useless, however, without finding out more about it – without making sure you’re getting the best insights you can possibly get out of your tool.

Customer-focused. Remember that is our mantra. Web analytics can help you get there.

]]> http://www.trendingupward.net/2009/10/frustrating-conversations-we-dont-need-web-analytics/feed/ 11 http://www.trendingupward.net/2009/10/highedweb/?utm_source=subscriber&utm_medium=rss&utm_campaign=rss http://www.trendingupward.net/2009/10/highedweb/#comments Sat, 03 Oct 2009 23:16:43 +0000 Shelby Thayer http://www.trendingupward.net/?p=1703

Tomorrow, bright and early, I’ll be on my way to the HighEdWeb Conference in Milwaukee, Wisconsin.  I know I will be learning a ton. I’m also looking forward to meeting some great people I’ve been conversing with via blogs, Twitter, and the like for so long.

Joshua Ellis, a fellow Penn State Outreach-er, and I will be presenting “Actionable Web Analytics” on Tuesday morning. We have a terrific time slot.  This will be our 4th presentation in less than a year and I’m really looking forward to it.

I’ve been looking through the selection of sessions and I think I have mine almost picked out. So far, I’ve picked out:

• Building a Strategic Plan with Douglas Tschopp – This is my first time to highedweb conference and Douglas is the program chair of the conference. I’m looking forward to his session on creating a communications plan.
• Talking to your boss about Twitter with Lori Packer – This presentation seems really interesting and I’m curious to see how Lori will bring ROI into the conversation.
• Goal-Driven Web Strategy: Implementing Technology with an Eye on ROI with Karlyn Morissette – Hey, it’s a session on web strategy and ROI. Is there any doubt in your mind that I would be there? Plus, I’ve been following Karlyn for a while via Twitter, .eduGuru, and her own blog and am looking forward to meeting her.
• The Kids Are Alright with Mark Greenfield – I met Mark a couple  years ago at the Penn State Web Conference and have been following him on Twitter,  delicious, and the University Web Developer’s ning site he started. It will be great to see him again.
• This is Not a Brand with Doug Gapinski – When I read this session description I loved it and was instantly thinking of specific examples of this happening. You can’t go wrong with someone from mStoner, either.

I haven’t made my mind up about the other sessions yet, but must say that there are a lot of great sessions to choose from. I will definitely learn a lot.

I don’t plan on live-blogging, however, I will be tweeting throughout the conference.  There will be many others doing the same. Follow #heweb09 to catch updates.