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About a week ago, I read a post by Avinash that answered GA questions; but when I got to the part about the navigation report (see screen shot, left), I just didn’t agree. The question was, “Navigation summary question - why is previous and next page often the same as the page you are viewing? ” Like this report on the left: Notice that 6.23% of pages that lead to the index page come from the index page, and 6.23% of pages that come from the index page go to itself. A little strange, no?

Why I was suspicious of the original answer.

In his post, Avinash wrote that someone at GA explained what caused this peculiar beharior. Here is how he described it — basically, it is about viewers that look at a regular tagged page and then look at a picture on the page in larger format (which isn’t tagged). Here is the example he gives:

Visitor Action One (view): /avinash/2007/09/rethink-web-analytics-introducing-web-analytics-20.html
Result: javascript hit generated (data collected)

Visitor Action Two (click): http://www.kaushik.net/avinash/wp-content/uploads/2007/09/web_analytics_1.0.png
Result: NO javascript hit generated (no data collected)

Visitor Action Three (back): /avinash/2007/09/rethink-web-analytics-introducing-web-analytics-20.html
Result: javascript hit generated

Visitor Action Four (click): http://www.kaushik.net/avinash/wp-content/uploads/2007/09/web_analytics_2.0.png
Result: NO javascript hit generated

Visitor Action Five (back): /avinash/2007/09/rethink-web-analytics-introducing-web-analytics-20.html
Result: javascript hit generated

To Google Analytics (or any other Analytics tool), it will look like this:

1) /avinash/2007/09/rethink-web-analytics-introducing-web-analytics-20.html - javascript hit generated

2) /avinash/2007/09/rethink- web-analytics-introducing-web-analytics-20.html- javascript hit generated

3) /avinash/2007/09/rethink-web-analytics-introducing-web-analytics-20.html - javascript hit generated

</Avinash>

This sounded plausible, but too neat. Much too neat for me. What if someone got to one of those pictures - one of those untagged .png pages - and decided to leave the site altogether? If just a single person bailed out, that would make the percentages different. In order for this explanation to work, every single person would have to exhibit the identical behavior - they would all have to look at two pictures and come back to the same page. It has to be perfectly symmetrical, and it is in the hands of thousands of humans to do it the same way.

Do you believe that? I didn’t. But I didn’t know the answer.

The Truth According to John (aka Google Analytics Gang Signing)

So yesterday, I was working with John and Jonathan here at LunaMetrics. “Did you see Avinash’s post a week ago?” I asked them, “Those numbers are WAY too clean. How could a page refer to itself and then refer to itself again every single time?”

John thought to himself for a couple of minutes and then said, “Oh, I get it. Here is what happens. Whenever the page is viewed twice in a row - like a page reload — the whole thing automatically works.” He put his hands together in the configuration on the left. Jonathan nodded wisely. I looked at them like they were nuts.

But ultimately, I understood what he meant:

If a page precedes itself, it also follows itself. That’s what John meant with his fingers — on one side of the report, we see a page preceding itself, on the other side of the report, we see the page following itself. It is just the same story, told twice.

The key is, you can’t think of that report like a clickstream when it involves the same page more than once. Once you stop thinking about it that way, it becomes intelligible. The page is the same no matter which of the columns of the report it appears in, and the numbers have to match exactly because of that.

Still lost? I know that some of you are sitting there nodding your heads, while others are saying, “What is she talking about?” So for the latter crowd, let me describe it in a different way. I hope you won’t mind if I use numbers instead of percentages, just to make this clearer.

Let’s say that Page A refers to itself via a page reload 100 times. And let’s say that the website has only one page — Page A. The report would look like this — in a conceptual way:

Notice how we get 200 pageviews in the middle of the page (and we know that that’s how many there are.) Notice how the number of pageviews on the left and on the right are symmetrical. And notice how these are two identical pictures, which meet in the middle — just like the picture of John’s hands above.

So I think I have run out of ways to explain this problem. It is sometimes caused by a reload, and sometimes caused by part of the explanation that Avinash gave. But it never requires thousands of people to exhibit the identical behavior.

And in closing, John wanted me to show off that he is really known for his good looks and not for his gang signs, so here is he is.

Robbin

My daughter really wants to go see the opening of Mama Mia! this weekend. But, while a good play, it is not exactly what I am looking for in a movie. On the other hand, I am dying (heh) to see Heath Ledger’s posthumous appearance as the Joker in The Dark Knight.

“It got a ‘Must Go” rating on Fandango last night,” I pointed out to her. Ever the analysts daughter, she retorted, “And that was out of three people?”

Well, no, that were actually hundredds of people who succeeded in seeing it before it opened (Hmm, maybe it opened in other countries in other time zones, the way that you could get an iPhone in New Zealand almost a full day earlier than here.) But it got me to thinking. If there are only five rankings: Must Go, Go, So-So, No and Oh No! — then how does anyone ever achieve a ranking at the ends of the scales? It’s like asking someone to take a survey and they can choose a number between 1 (lousy) and 5 (awesome) — unless everyone chooses a 5, how does anyone end up with an average of 5?

“Aren’t you assuming a lot about Fandango’s algorithm?” asked John Henson, famous creator of the GA Goal Copy tool. “Maybe it’s like the Google ratings,” pointed out SEO Jim Gianoglio, “They count more if you not only rate but also write a review.”

Well, analytics to the rescue. If you click through, you can actually see the rankings in buckets (sort of like the Google Analytics loyalty charts, but without all the misleading titles):

Obviously, you don’t have to get all “fives” to get a five. So let’s expand the system and pretend that Fandango weights all answers on a scale of 1-10, and you have to get between a 9 and a 10 to score a “Must Go.” And maybe each vote gets the top of its category (so if you vote “must go,” it is worth ten points, and if you vote, “go” it is worth eight points. We would have (in my made-up algorithm):

45*2, 26*4, 63*6, 96*8 and 991*10

all of which gets divided by the number of votes, 1221. For a weighted average, i.e. raking of 9.21376 (OK, that is a little overly precise given that I don’t know the algorithm.)

Late note: After publishing, I realized that this (made up) algorithm only works at the high end. What if you had a lot of Oh No! and a scattering of other rankings — if you gave a “two” to an “oh no!” ranking, you could never get a movie to rank, overall, as an “oh no!” So probably it is more of a sliding scale — but the concept is the same.

Well anyway, that is your web analytics movie lesson. Enjoy the weekend. Comment when you see the movie and tell me if I should go.

On a post way back in April on Custom Advanced Filters, Idris left a comment asking about the required/not required selection (seconded by Paul):

Hey, great articles. I am trying to do some advanced filtering, but I’m confused by the “Field X Required” option. If I say “Yes” to the requirement, which of the following two things does that mean?

a. If the regex in this field does not match, do not include this hit in the profile at all.

b. If the regex in this field does not match, skip this filter, and move on to the next, but still include these hits in the profile.

These two are obviously very different. Which does Google Analytics do?

The confusion is about what exactly is “required”. We were pretty sure we knew, but we did an experiment to confirm. It’s basically b from what Idris suggested.

Here are the details:

1. If the field is required and the regex matches, the output is written to the field you select.
2. If the field is required and the regex does not match, the output is not written to the field you select.
3. If the field is not required, the output is written to the field you select regardless of whether the regex matches.

In no case are the pageviews excluded from the profile entirely (you need an exclude filter for that). The filter just doesn’t apply if the field is required and it doesn’t match.

Google is doing a triple event. I don’t really think that they need me to blog about it to our 1900 readers (which is why I never blog about new features, everyone has already heard about them by the time I get to my Wordpress dashboard.) But you do favors for your friends, and this is one of them.

In the PR, which you can also read on the GWO blog, they say that they will:

• Briefly introduce the products
• Highlight recent product releases and developments
• Discuss the benefits of using the products together
• Answer selected questions that attendees have submitted

So I believe it is a beginner seminar. Just ideal for the person who is beginning to work with one of those tools, or who works with one or two but doesn’t know the value of the others.

Here’s the What/Where/When:

TITLE: The Google Trifecta: Webmaster Tools, Analytics, Website
Optimizer
DATE: Tuesday, July 8, 2008
TIME: 9:00 - 10:00 am PT (Pacific Time)
JOIN US: Register to attend

Goals are one of the most useful things you can set up in your Google Analytics. Funnels go along with goals in helping you understand how visitors progress to your goal.

A Primer on Funnels

A funnel is just an ordered list of pages (up to ten) leading up to your goal page. For example, for a shopping cart, a funnel might be something like this:

1. Check out
2. Fill out shipping information
3. Fill out billing information
4. Confirm purchase

The funnel that make sense for your goal depends on your site and how you intend your visitors to progress to your goal. Not all goals have a natural funnel, and you aren’t required to define a funnel for a goal. However, for a goal like the shopping cart example above, defining a funnel can give you a lot of useful information about where people get hung up and decide to abandon the funnel, never reaching your goal.

You set up a funnel along with your goal, and the setup is the same — just put in the URLs for the funnel pages (using Head Match, Exact Match, and Regular Expression match just like the patterns for the goal URL). See How Do I Set Up Goals? in the Google Analytics Help for more information on setting up goals. One tip: Give the funnel steps descriptive names, since they’ll show up in the reports and you want them to be self-explanatory. “Step 1” and “Step 2” don’t help anyone much. Better to go with “Check out” and “Fill out shipping information.”

There’s a lot of confusion around how setting up a funnel affects your goal reporting, and what gets recorded in the funnel by Google Analytics. First of all, the funnel you define affects only the Funnel Visualization report. Your goal conversion counts and rates are still exactly the same as they would be without the funnel in the rest of the reports in GA. With that in mind, here are some answers and some troubleshooting for common problems with funnels.

Required Step

The “Required First Step” check box on the goal setup causes a lot of confusion. First of all, remember that this affects only the Funnel Visualization report. If you check off this box, here’s what happens: The Funnel Visualization report includes only conversions that passed through the required step. That’s it. Your other reports still include any visit that views the goal page, but the Funnel Visualization report only calls it a conversion if it visits the required funnel page.

The required step can be a way to separately measure multiple goals that have the same ultimate goal page, but start at different places. Simply set up more than one goal with a different required step for each one. (Again, remember that the differences will only be apparent in the Funnel Visualization report.)

Order of Steps and “Backfill”

Your funnel steps have an order, and they show up in that order in the Funnel Visualization Report. But the truth is, GA doesn’t care what order the steps occur in. It simply looks through the visit to see whether the funnel pages and the goal pages were viewed, and if they were, that’s represented in the Funnel Visualization report, regardless of the order they were viewed in. A visitor could view step 2, then step 1, then step 3, then the goal, but they’ll still show up in the funnel for each of the steps.

In fact, GA goes even further and “backfills” missed steps in the funnel. So if someone views step 1, skips to step 3, and then views the goal page, GA will actually show that they proceeded through step 2! It will fill in any pages between a visited step and the goal.

Converting More than Once

A conversion is when someone reaches your goal page. But what if someone
visits your goal page more than once? Whether they visit your goal page one
time or one hundred, GA will only report a single conversion for that visit.

Much like the scenario in “Order of Steps” above, GA simply looks through
the visit to see if the goal page was viewed, and if it was, the visit
counts as a conversion. So if a visitor repeats the funnel within the same
visit, you’ll only see one conversion.

Funnel Problems: 100% leave after a step, or 100% convert for several steps

Occasionally we see a funnel that looks like the one below. Something’s clearly wrong. 100% of the visitors leave after the first step, but the other reports clearly show goal conversions are happening.

This happens when you have a funnel step that matches the subsequent steps in the funnel. Remember you need to be careful if you are using Head Match or Regular Expression match in your URLs. If your funnel setup looks like the one below, you’ll end up with a Funnel Visualization report that looks like the one above, where everyone leaves after the first step, because all of the steps match the first one.

A related problem happens when only some of the later pages match a previous page in the funnel. Take a look here:

This problem is harder to detect, but 100% conversion across several steps looks fishy. You should expect to lose at least a few people, given enough data. So what’s happening here?

It’s similar to the first problem funnel setup. Here step 1 also matches
steps 2 and 3, but this time it does not match the goal page. Like the
first example, because steps 1 and 2 are the same, no visitors make it to
step 2, as far as GA is concerned. However, the goal page is different.
For every visitor that reaches the goal page, GA backfills into the previous
steps.

You can avoid problems with a step matching subsequent steps by using regular expression that have negative lookaheads to exclude the later steps.

Jonathan

Update to the Update:

Anders at IIH Copenhagen has modified the the Goal Copy extension to work with the alternate HTML that is being seen by some International Users (see comments).

You can get the alternate, international version from http://blog.iih.dk/goal-copy-extension-international/

Thanks Anders

——-

I have updated the Goal Copy extension for FF3 (I hope).

Let me know if there are any issues.

Update: Robbin pointed out the brief nature of this post and that many people would have no idea what I’m talking about. So for those who are going “what the heck is he talking about?”, the Goal Copy Firefox extension can be used to copy goals between profiles in Google Analytics. Take a look at my previous posts if you think this is something you might be interested in:

Goal Copy Extension Update

Copying Goals in Google Analytics (A Firefox Extension)

John

Update: I’ve added an additional URL to when this script runs.  It now runs on https://www.google.com/analytics/settings* as well.  If the script stopped working for you, this was probably why and should take care of it.

You can also make this change to the existing script by going to Tools->Greasemonkey->Manage User Scripts.  In the Included Pages area, click the Add button, paste in the above URL, and click OK.

————–

I was recently asked by Espen at zedge.net if there was anyway to automatically show all your profiles for the website profile list in GA.

The default is to display 10 profiles and you can either 1. page through them (painfully) in sets of 10 per page or 2. Select from a pulldown how many you want to show at once.

But when you have a lot of profiles it becomes annoying to select “Show 100″ every time you see this screen.

So, I wrote this very simple greasemonkey script that watches for certain location.hrefs (URLs) and adds the parameter ns=100 to the end of the URL. The ns=100 parameter directs GA to show 100 profiles at once (which is the highest option in the pulldown).

If you don’t already have Greasemonkey installed you can get it here.

Then download and install the Show 100 script. (If you have greasemonkey installed, you should be prompted to install the script when you click on it. Otherwise download it and use the greasemonkey interface to add the script).

It is not a perfect solution but it has worked well for me so far, and it may help you put off that carpal tunnel surgery for a while longer. If you have a better or smarter way to accomplish the same thing, let’s discuss it.

UPDATE: André made a code suggestion (see comments) which I have incorporated into the script.  Now it will not add the &ns=100 parameter if there are 10 or fewer profiles.  Thanks André

-John

Earlier this week (Monday, June 2), the Web Analytics Association started the WAA Championship. The idea behind the championship is for analysts to show their stuff (and have fun.) Everyone gets to evaluate the same site (www.webanalyticsassociation.org) for insight into how we are achieving our goals, how we are enabling visitors and members to achieve their goals, and at the end (later this month), the best analyses will win. The WAA Marketing Committee is giving away real prizes, too — I know that the first prize is a trip to an eMetrics Summit, including hotel, and second/third prizes are big big Amazon gift certificates.

Only WAA members can play. So go play and win and get another notch in your web analyst belt. Full disclosure: I worked on the Championship a lot when I was the board member in charge of Marketing. I’m working with different committees now, but Marketing always has the fondest place in my heart — especially Daniel Waisberg, the Championship’s architect.

I worked and worked and worked with Bernadette, at the New York City Harvard Club (where we are having our Google Analytics training on Wednesday, 6/4/08) so that we could accommodate extra people. She is such a gem. I drive her crazy, I know…

If you are coming, now is the time to register. We’ll have two concurrent tracks: implementation and analysis.

Implementation Track: If you are a techie (or even if you aren’t a techie, but need to do the technicals to make your Google Analytics work well), you’ll want to hear John Henson talk about filters and profiles, goals and cross-domain tracking.

Analysis Track: If you’re an analyst (or even if you aren’t, but your company expects you to do that kind of work), you’ll want to hear us talk about how to make sense of all that Google Analytics data. (That’s me — I am speaking for the first three sessions of the day.) Traci Scharf will talk about creating a leaner, meaner AdWords program. Megan Kiel is going to join us from the Google Website Optimizer team to talk about testing your website.

At the end of the day, Jonathan Weber will talk about getting the whole organization on board. And we’re going to work and work and work to be sure your questions are answered.

Don’t worry, you’ll be able to pick and choose among the sessions, and if you have to miss a critical session, we’ll see if we can’t sit with you at lunch and go through the key points. Everyone will get copies of all the handouts, too.

So here’s the link to read all about the training, and here’s the link to look at the agenda.

Robbin

I was really surprised to read Taylor Pratt’s article about the state of SEO. If we can all just get along and respect each other, he said — not in so many words– we’re on the road to victory, and that road leads toward more conversions.

Really?

I think Taylor cares about conversion, but I just don’t think that a lot of other SEOs are on board there. Maybe I am just out of touch… but it just seems like the vast majority of SEOs show ranking reports. “You used to be in position 25 in the SERPs, sir, and now you are in position 5!”

In fact, there are really three ways to measure how well your SEO is doing:

1) Showing the customer how their position has changed in the search engines (Position)
2) Showing the customer how many more visits they got from the keyword. (Clickthrough)
3) Showing the customer how many more conversions they got from the keyword (Conversion)

Position is the easiest to prove. And after all, many SEOs feel like that is their job. Clickthrough is harder to achieve, because the click is a function of position, title tag and description. The description might be the one you wrote, or not at all. So it is capricious.

But what about conversion? Some web analytics tools allow you to easily track conversion to the first referrer and last referrer (and everyone in between.) In Google Analytics, you will always get the last “real” referrer. (Use of a bookmark or directly typing in your URL, for example, won’t overwrite a real referrer like a banner ad click, but every other kind of ad/keyword/reference will. Sure, you can do some fancy footwork to capture the first referrer, but most people do not.) This is a topic that has been addressed a lot…

Unless you take the time and effort to set up your analytics, or unless you have a site where most conversions take place on the first visit, you will often feel like your organic efforts are for naught. Sure, they’ll find you on a non-branded keyword, but will often come back on a branded keyword. So I think most sites (who aren’t going to do that kind of analytics set up, which has its drawbacks, too) should be doing trend analysis — comparing increase in organic traffic to increase in conversion, even if those conversion ultimately came on branded searches or through advertisements.

Robbin