When talking about Google Analytics or Web Analytics in general, some metrics and reports get seemingly all the attention (and rightfully so). Metrics like Bounce Rate, while loved by Web Analysts on all corners of the globe, are just too popular. In fact, Bounce Rate is now trendy! Do you think it’s become a buzzword as well?
Anyway, while Bounce Rate, Revenue, Goal Conversions, and Transactions are as popular as your local high-school’s starting quarterback / class president / homecoming king, there are other metrics to look at in Google Analytics, you know! These next five metrics are probably some that you’ve seen before in reports, and probably available in SiteCatalyst, WebTrends, ClickTracks, and other Web Analytics programs, although they could be known by another name in those programs.
1. $Index – This metric basically tells you what the average value of each page is on your website. It takes the amount of either Ecommerce Revenue or Goal Value that each page was responsible for, and divides it by the number of Pageviews for each page to give you a financial value in your currency of choice. You can find it by going to the Top Content report in the Content section, all the way to the far right of the report table. Log-in to GA and bring this report up in your profile, and check out what the $Index is looking like for each page. The values may be as small as a couple of dollars, to as high as a few hundred dollars per page. The Goal here is to find that page or two that has a higher $Index than most of the other pages, that also has a good amount of Pageviews. It could benefit you greatly to further optimize that page, or, to create some special offers or promotions directly on that page.
2. % Search Exits – If you have an internal search function on your website (and if you don’t, why not?), this metric calculates the percentage of people who left your website altogether, immediately after they performed a search. These people did not go any deeper into your website, or did not refine their search at all – they simply left. Think of % Search Exits as the “Bounce Rate” of your search function. Now, there is the possibility that they found exactly what they were looking for and they are going to come back later. However, if a lot of people are doing this, chances are your search function isn’t working properly, or serving up relevant results. Our loyal readers of this very blog know that that is a pet peeve of mine.
3. Per Visit Goal Value – Another interesting economics-oriented metric, found toward the right-hand side of the main report table, underneath the Goal Conversion tab. Use this type of micro-analysis to evaluate how valuable each and every one of your website’s visits are (so basically this is $Index for your Visits, instead of for the pages on your site). And, much like $Index, this number can either be very small or very large, depending on your Goal Values and how valuable each visit is to your website.
4. Revenue Per Click – Are you noticing a trend here? If you’re advertising with Google AdWords and if both your AdWords and your Google Analytics accounts are properly synched up, this very small number can tell you exactly what the name of the metric reads – the revenue that each click on your ads generated for you. This will allow you to say “Hey, Ad “C” or “Keyword X” is delivery $0.87 a click!” This can definitely place your click management strategy under a whole new light
5. Abandonment Rate – This metric is available via the Goal Abandoned Funnels report within the Goals section of your Google Analytics profile. Having the ability to view this metric should not be an issue – because every profile SHOULD have Goals and Goal Funnels. This statistic is telling you the percentage of people that are leaving your Goal Funnel at some step along the way. Chances are that they are leaving your Goal Funnel, and not coming back to complete and match your Goal. If this number is very large, you need to evaluate the way people can get to your Goals (every page along the way). Even if this number isn’t very large, you should stay on top of the path that your visitors take to reach your Goals. It’s actually very surprising to me that this metric, and even this train of thought, is very under-utilized in Web Analytics, so I feel compelled to add it to this list.
Now log-in to your profiles and check these out for yourself!
It’s a bit surprising to me how many folks do not make use of their segmenting / cross-segmenting options in their Web Analytics Packages. Some folks don’t even know or aren’t even aware of what it means or what it does. So for today’s blog post, I would like to explain what it is, and how you can make use of it.
What is Segmenting?
In Analytics, segmenting is basically viewing one particular set of data by another set of data. It allows you to “drill-down” or “dig deeper” on a particular page, traffic source, or keyword.
For example, let’s say I am looking at data from my Google.com Organic Traffic. I can see how many Visits, Pageviews, and so on that came from the Google.com Organic Search Results. The next thing that I think about is to discover what keywords from the Google Organic Search Result sent me the traffic. In whatever analytics program you use, you should have a “Segment” or “Drill-Down” option that will allow you to do this, either from a drop-down menu or a series of checkboxes and submit buttons. Then, you’d be able to see the keywords that brought you traffic from Google.com on one page.
This, like the title of this blog, “makes your life easier”, because you don’t have to open multiple report windows or spend a lot of time trying to find things in your analytics package of choice.
Can you give me some more examples of things that I can do with segmenting?
Yes. Here are some of our favorites here at MoreVisibility:
If you are someone who has never really made use of segmenting before, you need to start doing so right away. It’s a very powerful feature, and arguably the most important feature of all of web analytics, and you can really dig deep and slice & dice data in countless ways. It also saves you a bundle of time – and makes you look good, too!
As far as custom segmentation goes, this is great if your web analytics package has it. Play around with it and make use of creating custom segments to make you look even better! 🙂
In my latest, most desperate of attempts at trying to make our loyal blog readers think I’m hip by using titles that come straight out of popular phrases in rap songs (which is in conjunction with my last attempt with a blog post entitled “Tryin’ to make a dollar outta fifteen cent!“), I’d like to give you an idea of what the typical day-to-day life is like here for me at MoreVisibility. Every time I describe what I do to friends, colleagues, co-workers and even some clients, I talk about how being in Web Analytics is like being a private investigator or a federal agent of the internet. You gather data, compile statistics, find clues, compile some more data, interview a couple of people, and solve the mystery! Then you typically have to present your findings to your boss(es) and your clients, and then talk about where to go from there.
Here’s an outline of a typical day for me (which is sort-of a false statement, because no two days are the same, so there really is no such thing as a “typical” day…but you get the idea).
Date: Wednesday, July 9, 2008, Boca Raton, FL, USA (Temp: 91°)
7:04 AM – I have just woken up, and I’m already thinking about what I’m going to be doing for that day. Do I have an Analytics presentation to give? Do I need to check the coding on a site before it launches? What accounts will I be doing some investigating on? Do I have enough laundry to last until the weekend?
7:57 AM – I arrive at my office, turn on my computer, and see a yellow sticky note on my monitor that reads “Joe – Please see me about [Client]’s Top Landing Pages.”
8:01 AM – While my computer is loading and my email is downloading, I catch my co-worker who explains that our client is concerned that the exits from their homepage is too high. I suggest evaluating the page’s Bounce Rate and maybe a quick Navigation Summary to get a better idea of what is really going on with their homepage. I also mention something about A/B testing with Google Website Optimizer.
8:02 AM – I log-in to my Google Reader account and catch-up with the 60+ Web Analytics and Search Marketing blogs that I subscribe to, while simultaneously responding to emails with questions and discussions from co-workers.
8:41 AM – I am finalizing my speech for an in-person Analytics Presentation to one of our clients, when Amber (Client Strategist) buzzes me and tells me her client added an email address to their Google Analytics account, but they cannot log-in. She tells me she knows what the reason is: “The Email address is not a Google Account yet! It needs to be a Google Account in order to log-in with that Email address into their GA Account.” I start smiling, because that’s exactly right.
10:30 AM – I am out of water, and I’m starting to get hungry. I think about all of the different possible ordering options, and think how cool it would be if some of our favorite local take-outs would have an online ordering option, and imagine what I would give for a large turkey & swiss right now.
10:35 AM – I start to open up a brand new Google Analytics account for a new client. I provide our client with the necessary tracking code to be placed on every single page of the website. I also explain the many different options available, such as SiteSearch, Ecommerce, Benchmarking, and Filters that can be utilized.
10:59 AM – I receive a phone call from another client who asks me to explain the difference between A/B Testing and MVT (Multivariate Testing). We throw around some ideas of what to test and experiment back and forth, and we agree to launch an experiment using Google Website Optimizer for their AdWords Campaign’s landing page.
11:33 AM – Okay I am REALLY hungry right now and I can’t imagine being able to last another 27 minutes without eating something!
11:34 AM – Marni (another Client Strategist) sends me an IM that reads “It’s working!!!” She is referring to the neat advanced filter that we wrote which added the name of the source and the visitor type in front of the transaction ID in this particular client’s Ecommerce Report section. This is great news, as I’m sure the client will be very happy to hear about this.
12:00 PM – I’m about to grab my sunglasses and walk across the street when I see an Email come in that reads “GA Tracking Issue – Please Help!”, flagged as High Importance. Guess lunch is going to have to wait a while…
12:19 PM – Problem solved! Turns out there were two sets of Google Analytics tracking code on the same page, one urchin.js version and one ga.js version, which is bad news. I then proceed to solve another problem – my hunger.
1:10 PM – I return and find some great discussions starting up on the Yahoo! Web Analytics Forum. It’s really a great forum to check out whenever you can.
1:15 PM – My in person analytics presentation is in 45 minutes. I am very obsessive when it comes to presentations, as I like everything to be perfect, neat, and organized, so I visit our client’s website one more time, and find that they have repaired a bug in their shopping cart that was the focus of one of my main points in the presentation!! I think of a good way to still use this slide in the presentation.
1:38 PM – One of Khrysti’s (Director of Optimized Services) clients is in a bind. They cannot figure out why they are not seeing “yahoo / cpc” or “msn / cpc” in their Google Analytics profile, like they can for “google / cpc”. I reference my latest blog post about Google Analytics URL Coding, and I strut away confidently as I’ve capitalized on another opportunity to tell someone about my Analytics Blog. 🙂
2:00 PM – It’s showtime! Our clients have arrived, and I hand out my business cards and begin with introductions. It’s always great to be able to meet people in person and talk analytics, Site Search, and Shopping Carts to them. This particular client is using both Google Analytics and WebTrends, and they were really concerned about the differences in data between the two, even though they swear that they have everything installed properly. I explained that different analytics packages will always report different values for the same metric, no matter how perfect your installation and coding is.
3:32 PM – I come back and check my own Google Analytics profile for this blog, and I’m surprised to find so much referring traffic from European blogs! I love that someone in Austria and someone in the Netherlands is reading a blog written by someone half-way around the world. I know this because I frequently check my referring traffic reports, to see who is bringing me additional traffic.
4:00 PM – Another one of Khrysti’s clients cannot for the life of them understand why people type in such simple, generic words such as “shoes”, “belts”, and “hats” into their website’s search feature on their online clothing store. They believe something is wrong, broken, or not working correctly. I am pretty sure that their search function is working properly, but I go to their site and double-check with some test searches anyways. After I verify that it is working properly, I pick up the phone and begin to explain to the client that people have much different behavior (and level of tolerance!) when they perform keyword searches on Google or Yahoo vs. performing keyword searches on someone’s website. Again, I direct their attention to my blog by referencing my post about a website’s internal search function.
4:45 PM – My day is starting to come to a close. I like to take a few minutes each day and “spot check” different analytics accounts, just to ensure that everything is still running smoothly and data is being collected and displayed properly. I’m glad I did this, because an important Goal in one of April’s (Director of Strategic Accounts) clients’ accounts has stopped collecting data. After a test on the client’s website, it turns out that the Goal URL has been changed from “thankyou.html” to “thanks.html”. Websites are updated all the time, which is a good reason to routinely double-check your Goals to make sure they are working properly.
5:03 PM – I’m just about wrapping it up here and saying good night to everyone in the office. Out of nowhere, Danielle (my boss) catches me right before I walk out the door. She explains that a new client needs to speak with someone urgently (first-thing tomorrow morning) about what analytics platform they should choose between Omniture SiteCatalyst Hitbox (HBX) or ClickTracks. They also need help in defining new Key Performance Indicators for their executive team, and possibly setting up some custom reporting. I love to think about things like this, especially on off-hours, so I’m glad I have this opportunity.
7:00 PM – Analytics is going to have to wait a while – an episode of Law and Order is on right now that I’ve never seen before. 🙂
All in a day’s work. 🙂