What’s the right price to charge for consulting? How much should I pay an experienced web analyst? How do I put those two things together?

I attended the Money, Jobs and Education WAA webinar last Thursday (9.20.07) for the sole purpose of learning the answer to that problem. Here’s the question I asked the panel who presented at the webinar:

Let’s assume that an experienced web analyst gets paid $100,000. Common wisdom says that you, the business owner, need to get 3-4 times an individual’s salary back in order to make a profit. Let’s just say, 3x. That means, s/he needs to bill $300,000.

But if the company bills at $150/hour, the analyst needs to bill out 2000 hours, i.e. ALL of his hours. If the company bills at $200/hour, the analyst needs to bill out 75% of his hours. Still difficult.

Is the problem a) Consultants should be expected to work more than 40 hours/week. b) Consultants who make $100k should be billing out at more than $200/hour or c) consultants who make $100K are not that profitable. They bring the business in and the less expensive employees are the profitable ones?

I didn’t get much of an answer, but I did get some offers for offline help. After the webinar, I had a queue of phone calls to answer (”Great question, can’t wait to see the answer”) and then a stack of emails to answer with the same comment.

If you want to read the answer that I put together, with Seth Romanow’s help, click through here, to the WAA website. You have to be logged in to the site as a member (but you’re a member, right?) I set up that article so that comments are enabled, and you can comment there. I’m sure there are a lot of other ways to make the numbers work, and hope that a few other people will chime in.

Dear Jared:

Before I say how much I disagree with your recent comments on five second tests and homepages, I should point out that I love your new series of podcasts. Not the stuff you do with Josh or the seven other usability experts who pontificate about what Brown University should do. That other stuff was so boring that I deleted you from my iPod. (Do I win the award for the Queen of Criticism or what?) But as luck would have it, I bought a new iPod and “made” my daughter set it up for me (I am just too busy) and she set it up to get ALL my podcasts. So I was surprised and delighted to hear that you and Christine Perfetti are doing a “usable” series on usability — stuff that I can really use. I listened to home pages and store pages and gallery pages. And then I heard you talk about five second tests.

(Now, for the other thousand people who may eavesdropping: a five second test is when you show a user a page for five seconds, take it away and ask them, “What does this page do?” Reason being: that’s about what users give a page, five seconds, before they decide that they are in the right place or not. It’s fast and cheap and helpful.)

But Jared - I think you are wrong when you say that five second tests aren’t helpful with home pages. I use five second tests with users to test home pages all the time.

In your podcasts, you said something like, “Users already know what the site is about. People don’t need to know what the homepage of UPS is all about, they know what UPS does, they go there to track a package, for example.” Well sure, that’s true if the site is UPS, or JC Penney, or Fidelity Investments, or your favorite site, the Bureau of Labor Statistics. But do you really believe that all municipal sewer engineers are familiar with RedZone Robotics? Do you think that every realtor knows HomeFeedBack? These non-Fortune-500 sites may be found in the organic listing (by their home page) and the user will give the site — what, maybe five seconds? — before deciding to bail. Bloggers and linkers like me almost always link to a homepage, and if someone follows a link, they may end up on a homepage of a site they don’t know, giving it what — five seconds? — before deciding to leave. Or not.

I have yet to start a user test with a five second homepage test and hear the user say, “Oh them. I know them.”

You also pointed out that when someone goes to a site with a specific purpose — like finding instructions on their HP printer — they only care if they can find the link to their printer. They don’t care if the page “looks” like a company that sells printers and computers.

But the example is somewhat lacking. It’s really not any different from the UPS example - the user has a task to complete and knows what site he should complete it on. What about when you are searching, when you are following a link, when you are typing a link in that you heard on the radio?

Recently, we did some user testing on a site that sells do it yourself pieces to construct parts of your home. As part of that test, we did a five second home page test. “I would use this site if I wanted to have the company do the construction for me,” users said, almost uniformly. They were all really surprised that the site was a place to buy the parts so that they could do the construction themselves. In retrospect, it’s clear as the nose on my face, but my nose was way too close to that site. Now, we are going to test the pieces of the home page that gave the users the wrong impression.

All because we did five second home page tests.

Robbin

Don’t you ever wonder about the computations of that little calculator that Google gives you to figure out the length of a multivariate test?

I don’t have any insider knowledge. But I have studied it enough to understand certain issues (and many thanks to Dylan Lewis of the Web Analytics Wiki for confirming my suspicions wrt how it should work.) Specifically, you should need more data to “prove the same thing” if your control has a higher conversion rate, up to a conversion rate of 50%.

So let’s start: why does the GWO calculator ask you to input the conversion rate of your current page? Well, here’s why they care. If you hold everything else the same and tell the calculator that your current conversion rate is 4% instead of 3%, it will want a larger sample (translation: more pageviews, or more time to get those more pageviews) in order to get the statistical significance it needs.

So look at these two examples. All the variables are the same (sort of — I promise I will explain.) However, in the examples below, one conversion rate was 3% and the other is 4%. Notice, also (here is the explanation just promised) that I changed the expected increase in conversion rate. With the 4% test, I have it expected to increase by 25% (so that I will get a one point lift in my conversion — after all, .25*4=1) And with the 3% test, it’s expected to increase by 33.33% (because 3% times .33333 is also a one point lift):

So when the current conversion rate is higher, and you are looking for the same absolute expected improvement, the test takes longer, so that you can get more pageviews - i.e. get a greater sample size.

Why?

Why do we need more data to prove improvement with a highly-converting page than with a poorly converting page? Here, I will use a more extreme example: an absolute increase of one point is pretty low when you are looking at a page that converts at 25%. So we need lots of data to prove that a test will do better than the 25%. But a one point increase — that a whopping increase if your control page converts at 4% right now. So we can prove that our new test is better than our old control with just a little bit of data in that situation.

Here’s the really interesting part: when your control has a conversion rate of 50%, you need the most pageviews, i.e. time to get those pageviews. As you keep going beyond 50%, the time to run your tests starts to decrease. When you get to a conversion rate of 75% for your control, the time it takes for the test should mirror the time it takes at a control conversion rate of 25%. (It’s not perfectly exact for mathematical reasons that are too boring to go into here.) But check it out:

(notice that 25* 10% is a 2.5 point lift, and 75* 3.33333 is a 2.5 lift in conversion rate, also.)

Why?

Why does it all turn around at 50%? And I want to try to explain this without using ps and qs and little hats, since I’m not a statistician. So I won’t use fancy equations. Just simple ones.

All these equations that are behind all these kinds of calculators, they include two events: heads or tails. Conversions or non-conversions. They never say (to the extent that they talk), “Conversion is good.” Only people think that conversion is good and non-conversion is bad. (Those equations also include other stuff, but we don’t have to go there.) In fact, you have to have five conversions and five non-conversions for a combination to show up in the graphical area of the website optimizer (the area where the bars are green and grey and red.)

So when you start playing with conversion times non-conversion, you find out that they multiply out to the largest amount when they are both 50%. Right? .5*.5= .25 but if you now use a little 2% conversion rate instead, you have .02*.98 = .0196. That’s way lower than .25 (and remember — this is not sample size, but is one of the important parts of the sample size equation.)

My fourth grade teacher, Mrs. Petrowski, insisted that I learn all those math laws, and one of them was about “commutativity” — it doesn’t matter what the order is in multiplication, you still get the same answer, she lectured. So we can swap those numbers and say that the conversion rate is 98%, leaving the non-conversion rate to be 2%, and the product is still .0196.

So whether you have a 98% conversion rate or a 2% conversion rate — your sample size is going to be the same. (Remember that there is a lot of other junk that goes into the equations, but this basic principle should hold, even though I don’t have access to the innards of the calculator.) And from all this gobbledygook we learn:

• To prove that a test is 1% better than the control, you need more pageviews if the control has a high conversion rate than you would if the control had a low conversion rate.
• However, once the control has a conversion rate over 50%, you start needing fewer pageviews.
• This is a hard topic. If you didn’t understand, please comment and I will do my best.

Whew. This post took me at least two months to write. Many thanks toDylan, again; to Wendi Malley; to Tom Leung (whom I have driven crazy on this topic); and to EV, the GWO engineer who must be sorry he ever gave me his email address.

Everyone who thinks that change in conversion rate should be viewed as a PERCENT and not as an absolute lift in conversion is welcome to flame in the comments.

Robbin

Every day, I wake up and read the Google Groups for GA. Here are the ten questions I see just about every day, with answers.  (Note: the tiny url for this post is http://tinyurl.com/2m3zrm)

Question #1: Can’t I reprocess the data in some way? Sorry. Google Analytics doesn’t let you go back and reprocess. A very best practice is to think about your needs while you are setting up your analytics, and try to anticipate the future. This includes creation of a profile for every important campaign that you run, whether you define “campaign” as a Google AdWords campaign, a banner ad campaign, or an email campaign.

Question #2: I don’t know how to set up links in my newsletter. Or, I don’t know how to set up links in the paid search for non-Google search engines. Answer: Google Analytics has a nice linkbuilder tool to solve this problem, but I like ROI Revolution’s better. It is more intuitive, and it doesn’t have any typos . You can use the linkbuilder to code the links in any of your marketing campaigns — your email marketing, your Yahoo campaigns, your banner ads. (You don’t have to code Google AdWords, the default in AdWords is auto-tagging — it codes for you.) Once external links are coded, they’ll talk to your GA.

Question #3. Why can’t I get rid of the site overlay? You’ll need to clear your cookies. The Site Overlay activates if the GA tracking code sees the “GASO” cookie when you visit your website. Just use Firefox, choose Tools>Options>Show cookies and type in GASO. Delete that cookie.

Question #4. Why is my site overlay broken? If you make any changes to your Request URI — for example, if you ask to only see page titles and not /mypage.com — the site overlay will not work for the profile where you have the changes made. You should set up a clean profile without those changes. (To be honest, I feel like the site overlay is just about always broken, and I am awed when I see people ask questions about why they can’t get a specific piece of data from it. )

Question #5. My AdWords used to be linked to one GA account. I unlinked them, but now I can’t relink them, for some reason, to the correct account. Why? Answer: Relinking a previously linked AdWords account has to be done by Google. Submit a support ticket and they’ll get right one it. GA knows that you can’t do it without their help, and they are pretty responsive to this problem, I hear.

Question #6. My site has a new name. How should I handle my analytics? Answer: GA doesn’t really care what the name of your site is. So you can take your previous code and put it on your new site. But why would you want to do that? Unless the pages match perfectly (example: you kept the same site but moved from .asp to .php), you will really be comparing apples and oranges. Why don’t you just create a new profile in the same account and put that new code on your new site?

Question #7: Why is my own site my top referring source? Why is it even in my list of referring sources? Answer: Probably because you have more than one domain (for example, you are using a third party shopping cart) and you didn’t take the time to learn how to do the cross-domain tracking. Or because you have an old domain that you are redirecting to your new domain, and you are doing the redirect with javascript intead of with a server side redirect.

Question #8: Can’t I get conversion numbers instead of conversion percentages? Answer: Well, you can get them in the Total Conversions report, but you probably want them in the traffic report. And you can get them by a) pulling out your calculator and multiplying or b) dumping it all into excel and multiplying.

Question #9: Can I mix the secure code and the regular code? Google Analytics has a regular form of code (that includes, but is not limited to, the line http://www.google-analytics.com/urchin.js — and they also have the secure code, which uses the secure version of that, https://ssl.google-analytics.com/urchin.js

There are three ways that you can do this:

Option I) Since the name of your site is probably http://www.mysite.com, you are probably tempted to tell GA that when you sign up. This will give you the non-secure code. You can put it on all of your pages (even the secure pages), but it will generate a security error, possibly scaring off potential customers. So, Option I is a lousy idea.

Option II) You can follow the same instructions as above, but go in to the secure pages and be sure to change http://www.google-analytics.com/urchin.js to be https://ssl.google-analytics.com/urchin.js

Option III) Create a new profile, and pretend that your whole site is secure. To do that, choose the https beginning. GA will then automatically generate secure code for you, which you can put on your whole site. Using the secure site on all your pages - http and https alike — does not matter and will not affect your data. GA will not care that your site is mostly an http site.

Question #10) Why can’t I see the past the question mark in my referrers report? Answer: I really don’t have an answer. I would love if someone else would weigh in on this topic.

Bonus: How do I get the IP addresses of the visitors? Answer: you cannot, personally identifiable information is against GA’s terms of service.

Robbin

After I wrote about Justin Cutroni’s upcoming GA Shortcuts books, people wrote and said, “So? When is it going to come out?”

I just (we’re talking, 60 seconds ago) found out that it is now available. You don’t have to salivate anymore, go to the O’Reilly Site and buy his book for $9.99. And it even looks like you can buy it in hard copy for $29.99. And you can write a review before I get to, because it is 2:36 pm and I have four deadlines by 5 pm.

Plus, if I wrote a review, I would point out that the slashes go in the wrong direction in the figure that shows you how to create a filter to combine your hostname and request URI. And who needs me always criticizing their RegEx?

Justin — congratulations. I know how hard you worked, how many nights you stayed up, how many weekends were workdays for you, how you had to make your family go on vacation without you so that you could finish it. The web analytics world will be a better place because of you. Certainly, those of us who care about GA documentation are in heaven.

Speaking of which: to the two winners of the Google Analytics Documentation Contest - I will get your copies to you before this long weekend is over.

Robbin

When I was in Hawaii (I bet you didn’t expect me to start that way), I cut my foot on the coral reef, my first day there. This was because Justin Cutroni insisted that I go visit the North Shore of Oahu. So instead of running around, I spent a week sitting under the palm trees and read Web Analytics: An Hour a Day. But I had all these questions, and the author, Avinash Kaushik, answered them for me! Here is the fourth part of this incredibly detailed set of answers to my questions.  There are only three more questions here, but instead of just providing clarification, there are some big new thoughts and resources. You can read my thoughts in boldface and the author’s in quiet type.

Read Part 1
Read Part 2
Read Part 3

Why do you care so much about the customer experience and discount conversion rate so much? (We can say, p. 340, but you address this elsewhere too) The way that I look at it, there are either other conversions (like applying for a job, or getting help on the website), and the analyst is just forgetting to include those conversions. Or, it’s important that the customer have a good experience so that when he is ready to buy, he will (and it is a long term problem, but it is still about conversion rate.) Or, he will tell other people or write about what a good experience he had, and *they* will come and convert, eventually. So it is still a conversion rate problem. Ultimately, it is always about conversion rate. (Go ahead. Tell me that I’m wrong.)

I had written the above answer before I read this question!

Let me first say that I think you and I are defining conversion differently.

No matter what kind of site you have it is extremely likely that people come to your website for a very diverse set of reasons. Even on an ecommerce website people are there to buy, research, read the company’s bio, check order status / inventory, submit a review, bitch about something, look for support, find your address, whatever else is possible on earth.

If you accept that fundamental premise (and if you don’t just do a one question survey on your website and ask the visitors: “why are you visiting our website today”), then you’ll agree that if you want to make everyone on your website happy then focusing just on improving conversion (“sell”) is solving for just a minority of the site traffic. It also means that perhaps you are telling all other visitors to take a hike.

You do want to make money on your ecommerce website, you do want to figure out how to improve the conversion rate (orders/unique visitors). But that can’t possibly be your life’s mission, not even on a ecommerce website.

You need to figure out how to carry all other types of visitors with you and help them complete their tasks.

Ok here is the controversial part: You are a consultant and LunaMetrics is a very good consulting company. You have conversion rate as your middle name. If you get hired then you are probably supposed to simply improve the conversion rate. If you want to get paid, and rehired, then you have to solve that problem, and not care about any other type of visitor. I suspect even if you were of a very generous heart you can’t afford to care about any other type of visitor, you are being paid to sell more. That’s ok for you.

But I hope that companies realize that sell, sell and figure out how to sell more is not a long term strategic choice. They need to identify all the reasons visitors come to their site (“Primary Purpose”) and help them all (improve “Task Completion Rate”).

p. 312. IMO, there is no way to get competitive conversion data outside of panel data. Am I wrong? (Go ahead, you don’t have to be nice.)

You can get it from ComScore (in case you did not mean that by panel data).

As I mention above you can also use the FireClick Index, they even break it out for new and returning visitors! And for the last 12 months!! And for six different industry verticals!!! Compare trends over time with the index and it will give you a great feel for how things are going for you.

You can also sign up for the delightful shop.org ecommerce / conversion report, many people think of that as the bible.

Finally, yesterday I got an email from Stephane Lagrange and I noticed on his blog, http://blog.webtarget.ca, he has referenced the Top 500 Guide published by InternetRetailer.com which also publishes conversion rates for top ecommerce websites. Here are some of the numbers, directly copied from Stephane’s blog:

#1 Amazon.com: 3.52%
#2 Staples.com: 9.62%
#3 Office Depot: 7.10%
#498 Broadspan Commerce LLC: 0.35%
#499 Musicnotes Inc: 3.25%
#500 KneeDraggers.com: 0.99%

Thank you for helping, and of course, for writing your great book. I loved every piece of it, except for the Six Sigma part. (That was way too dry for me, which is a shame, since that’s an area I know almost nothing about.) On page 286, you wrote, “It is amazing what people won’t tell you even in the most open and honest company environments, because they are just trying to be nice.” You clearly didn’t have me in mind when you wrote that line….

You are underestimating the value of what you bring to the table. Under any circumstance I know exactly where you stand and what your opinion is. Sometimes it might hurt to hear the truth, but it is always better to hear the truth. You are honest, direct and willing. It makes for a refreshing change in a world where one is always trying to parse nuances and syllables to understand where the other person stands. I am glad that you have the courage to share your real opinion and you don’t have a hidden agenda (and if you have one then you are doing very well hiding it! ).

Thanks for the opportunity to do this interview, you had great questions and it was fun to answer them.

After reading Web Analytics: An Hour a Day, I had a lot of questions, and the author was kind enough to answer them all. In this third installment, we talk about testing and just begin to talk about conversion rate. My questions are in bold and Avinash’s answers are indented.

Read Part 1
Read Part 2
Read Part 4

When you wrote about usability (p. 53), you commented, “Usability tests are best for optimizing UI designs and work flows, understanding the voice of the customer, and understanding what customers really do.” However, I do usability testing all the time. During testing, I learn about the offer and the price, I learn how much the customers trust the site, I learn if the customer understands the site. A whole lot more than usability. So what things is user testing *not* good for (besides statistical significance, and some would disagree with even that)??

My comment you quote stresses what Usability is really optimal for. It can, as you aptly point out, be used for a number of wonderful things and can be a rich source of learning.

With advent of various technologies (including live recruiting and remote testing, experimentation and testing) you have such a wonderful set of tools that you can deploy. For example I prefer to do offer experimentation using a multivariate or testing tool rather than usability. Offer is cleanly tied to a outcome (say conversion), so why should I ask eight people who might not be really representative of my customers what they think? I can just as easily throw an experiment on the site and ask a million people on my site what they think.

Lab usability testing is valuable. It is perhaps the only way to see a customer and observe them intimately. Look for non verbal cues and reactions. Applied for the right purposes it can be a rich source of learning.

It can also be extremely deceptive to ask 50 people what they think of your site / experience / offers and assume that you have it nailed. If that were true site redesigns based on extensive usability tests would not bomb with the frequency that they do.

Why does experience testing get you any close to a global maxima (p. 248)? At the end of the day, you still need to know what to test.

Let me say this first, in any scenario you need to have a very intimate understanding of your customer experience.

Customers overall are very good at telling your their problems, they are terrible at telling you the solutions (and that is quite ok, never ask a customer for a solution).

To solve complex problems on a higher magnitude where your solutions will “slash and burn” what exists today you have a great friend in experience testing. Rather than just optimizing a page, you can optimize huge chunks of the customer experience, if not the whole site, by trying radical solutions and seeing which works. The nice thing is you set participation rates which means that you can easily control for risk.

Experience testing helps you jump the curve (to a get on the global maxima curve potentially) because your canvas is so much bigger, you can take bigger more radical risks and win big.

With most testing your optimize a page, when was the last time that you or I ever had a website experience were one page was so golden that it had a disproportionate impact on the outcome. Probably not a lot.

How do people set conversion rate (or other) goals? It’s great if the CEO says, “We have to increase our sales from our web channel by 50%” — then you can just run the numbers. But absent direction from someone else, do people just say, “Hmm, wouldn’t it be great if we could increase our conversions by 12.45%?” Do they pull out their HP 12C calculators and do an internal rate of return based on the cost of testing and the cost of money? (p. 256)

Here is my recommendation…..

1) A: Sign up for the shop.org annual study and look at what your competitors are doing. Use that as a initial discussion starter of what your conversion rate should be.

1) B: Type “fireclick index” into google and look at last year’s worth of data for conversion rate for the web or for one of the six vertical industries that they provide. It is free. Use that as a starting point for discussion of what your goal should be.

2) Plot out your conversion rates (segmented by your core acquisition strategies - DM, Email, PPC, Display, whatever) for the last year and see where things are trending. Bring this to your fireclick/shop.org discussion.

3) Finally see where in your acquisition strategy or site optimization you are making increased investments. If you just hired a SEM Goddess pump up the goal by 50% for that stream of traffic (Goddess will deliver). If you are implementing MVT then see what that will do.

1 + 2 + 3 = An intelligent discussion.

You’ll come up with a goal for the next three months. It might be wrong but persist and repeat the process three months later, you’ll do better this time. In six months when you do it you’ll nail it.

Give yourself permission to be wrong, trust me you’ll get better so fast.

Coming next: Part 4, where Avinash continues to talk about my favorite topic, conversion rate.

Robbin

We interrupt our regularly scheduled programming (which was Part 3 of the Avinash Kaushik book addendum) to hear from Princess Angela Brown. The princess (who points out that she is of relatively minor lineage) is also co-chair of the Standards Committee for the Web Analytics Association. Today, her Committee announced their 26 Standards (finally), at Search Engine Strategies - San Jose. We bring you here the exclusive inside story, also known as, “What took so long to write 26 definitions?”

Today the WAA Standards Committee released its second definitions document; eight months after our “Big Three” definitions were released. Eight months seems a ridiculously long time to define 23 new terms (the “big 3″ were carried over from our previous doc). After all, I could have written this document myself in under eight hours. Jason, our co-chair, could easily have done the same. In fact, nearly any of our committee members — more than twenty very competent people working as web analytics consultants, practitioners, and vendors — could have written this document in a day, blindfolded, with one hand tied behind their back and balancing on one foot (yes, I have a lot of confidence in our committee members!). What took so long?

Web analytics is not rocket science. Rocket science uses far more Greek letters and squiggly things than even the most complicated web analytics problem. The questions web analytics sets out to answer are really quite simple: WHO came to our site? WHEN did they visit? WHERE did they come from? WHAT did they do? HOW did they do it? Coupled with good marketing research and/or usability tests, you can even get a good idea of WHY your visitors do what they do.

As I see it, there are two issues that make web analytics harder than it looks. First, even though the concepts are simple, proper execution can be complex. To get a lot of value from web analytics, you really need to segment the WHAT by the WHO, and the HOW by the WHY, and the WHERE by the WHEN by the WHAT by the WHO. Second, a lot of our existing terminology comes from the tools we use. That’s not awful in and of itself: there are a lot of very good web analytics tools out there, and all of them deal with essentially the same concepts. But going from one tool to another is like learning another language, and no matter how well you know your stuff you are bound to misinterpret something because similar terms are used to describe different concepts. To use a cliché, the devil is in the details, and it’s that devil that took up so much of our last eight months.

We are fortunate to have a wide variety of Standards Committee members who have experience using different tools and analyzing different types of websites. This has led to some lively discussion about the meaning of the terms that so many of us use every day, and has underscored our industry’s need for precise terminology. For example, do you know the difference between a repeat visitor and a return visitor? How about a landing page versus an entry page? Single page visit versus bounce? Visit versus session? (The last one’s a trick question.)

For answers to these questions and more, download our document from the WAA site. We welcome your feedback.

In addition to her work as a guest blogger and her royal responsibilities, Angela Brown is the Web Analytics Manager for the MD Consult site at Elsevier. She has also been known to work for a large web analytics software vendor as a professional services consultant.

As I explained in Part I of this series, after I read Web Analytics: An Hour a Day, I had a lot of questions (and even some things I didn’t agree with.) So I wrote the author, and he sent me back nine pages of thoughts. That’s why I’m chunking my interview with Avinash into sections. Unlike the first part of this series, this one is very down in the weeds; I asked about some very specific best practices. You can see my questions below in boldface and his answers in quiet type, perfectly matching our personalities.

Moving from the very general to the very specific: On page 33, I scribbled, “First party cookies don’t talk to each other, and third party cookies get deleted.” Do you have any recommendations on choice of (vendor? technology) that deals with both of these issues? A first party cookie solution where the various sites in the enterprise talk to each other without lots of manual coding? A solution that you love?

In my prior role we had implemented first party cookies and “first party third party” cookies to overcome this challenge somewhat.

As an example let’s say my company was ZQ Insights and it had two sites www.zqinsights.com and www.webanalyticshour.com. I want to track each by itself and also the two pulled together.

I set a first party cookie on each (www.zqinsights.com and www.webanalyticshour.com). I am happy so far.

Now I also set a “first party third party” cookie on both, let’s call it tracking.zqinsight.com. The latter cookie I can use if I was looking at both sites as one monolith (to for example get true unique visitors).

It is less likely that this cookie will get blown away by spyware (because it is not being set from known domains of web analytics vendors), though high security settings will still be a issue.

One last point, you have to have a web analytics tool that allows you to create “local” (site specific) and “global” (all sites) datasets with ease and mix and merge sites. ClickTracks is one such tool.

I hope I have answered your question (and the answer is not clear as mud).

Question: On page 37, you stress the importance of having the analytics code at the bottom of the page (”Customer’s first.”) But what’s an analyst to do when the other fancy things on your page don’t work unless the tracking code loads before them?

Let me share some context.

The reason for the tracking code to last is simple: Nothing should interfere with the customer experience.

The page that the customer has requested has to go back as fast as possible so that they can get on with their life (and convert for example). Just in case you have something “funny” going on in the code, just in case your analytics providers servers are under heavy load, or just in case….. we want the customer to get the page first and us to get the data second.

There are always exceptions to any rule. I would set the bar really high to ensure that decisions to load the tag first pass rigorous scrutiny.

I think you do novice analysts a disservice by focusing so strongly on bounce rate. To you, bounce rate is about time on page. But most bounce rates are calculated as (visits entering and exiting on the same page without looking at another page) divided by (visits starting on that page.) Someone can bounce after spending 15 minutes reading the home page of this blog. So when you associate bounce with ways your website is failing (p. 145), the new analyst will be confused. I am not sure I have a question there, but you are welcome to respond.

For blogs my recommendation is that analysts should not measure either bounce rate or time on site. Both metrics will paint the wrong picture, precisely for the reasons you have so correctly identified.

Regardless of how it is computed for most types of websites Bounce Rate is a excellent metric that helps identify opportunities for improvement in acquisition strategies or website entry points.

On P. 274, you wrote that one of the questions you should be asking of your clickstream tool is, “What is the most influential content on the site? How do we know what convinced people to buy?” In general, how do most analysts figure that out, and specifically, how do you like to get that answer with Google Analytics?

I refer to a specific example of using the ClickTracks “funnel” report to identify influential content on your website. I am not aware of any other web analytics tool that can do that (or as easily as ClickTracks does), even if they all have “funnel” reports. It is something unique, and built into, ClickTracks.

If you have access to Discover2 or MarketingLab or your own data warehouse environment I suppose you can construct a complex query to replicate the ClickTracks logic. If you want to understand content influence you should so that, it is amazing what you’ll learn.

You can also use page level surveys (described in detail in the book) to understand value and influence of individual pieces of content on your page (and do it at scale).

 

Coming next - Avinash answers my questions about testing.

Part 1  Part 3  Part 4

Robbin

Justin Cutroni will soon publish the Google Analytics Shortcuts book. And it will be the best ten bucks you will ever spend, if you care about advanced GA implementation. It’s hard to believe that the book is almost here - I remember standing in the lobby of a hotel somewhere in California just a few months ago, and Justin whispered, “I’m going to write a book about GA.”

I am not exactly impartial here. This is a book that I have read over and over and over again. I appointed myself Editor in Chief and rewrote parts of it. “Didn’t we fix this utmSetVar typo once already?” I wrote the author last week. When I read the penultimate (I hope) copy last week, I found out that this blog is in it. And did I mention that Justin is one of my best WA friends? Like I said, not impartial.

So I am a little like Bridget Jones. She loves Mark Darcy, even though his mother buys him awful gifts and she seriously believes he should rethink the length of his sideburns. I love the book, despite its imperfections.

Since this is a real review, let me discuss the imperfections. First, I think you need to be a pretty advanced GA user for Shortcuts. If you are already reading Justin’s blog, religiously, you have definitely taken a step in the right direction.

I think Justin goes to great pains to tell you why GA works the way it does, information that is badly needed. But I think he would be smarter to have put some of that in the appendix — it is just way too boring until you absolutely need it. (And then, of course, you are desperate for it.)

Periodically, Justin lapses into GA-speak. For example, he writes this about the Item line in the e-commerce hidden form: “There will be one item line for each distinct product purchased by the visitor. This usually means one item line per SKU or unique product ID.” When I read this I feel like I need to create the I: line 50,000 times if I have 50,000 SKUs. (And you don’t have to do that.) In a similar vein he says, if you have e-commerce tracking, you can just leave the goal value blank. But this drives users crazy, because there is no way to leave it blank - GA insists on zero.

In a couple of (very rare) instances, I think he is wrong. But remember, I got a chance to point out problems all along the way, and he didn’t correct them - so maybe I am wrong. I am mostly thinking about applying AdWords cost data — you really don’t have to apply it to all the Analytics profiles that are linked to that AdWords account, you can choose, even though he says you have to link to all, and GA says so too. (Or maybe I am the only person in the universe who is always able to make this choice when I set up AdWords and Analytics.) And I am thinking about his Count Me Out! hack, which works fabulously to take yourself out of the data - but he also has a workaround in the book that doesn’t work. He says, use Firefox, go to the website where you want to be counted out, type this into the address bar, javascript:__utmSetVar(‘foo’), and you will create a utmv (a user defined cookie) called foo for that site. But it never works. Maybe it’s just this blogger who doesn’t know how to do it? (OK, I figured this out. When Justin wrote the book, he did it in MS Word, and Word assigns “Smart Quotes.” That’s how it knows when to turn the quotes to the right and the left, even though you only have one key on your keyboard. Anyway those special characters were gunking up the works.)

And wouldn’t it be great if the .pdf used the power of html? So that when he says, “I’ll be covering that later in my section on…. ” you could just click to it? (Maybe that will be in the final version.)

So when I write that you should drop everything and then keep dropping, i.e. drop ten bucks on this e-book as soon as it is available, it is not because I am starry eyed. I do see little imperfections, but still…. It is an incredible resource, and no GA analyst should be without it. I sure wouldn’t want to work without it anymore. That’s one of the reasons that I wanted to give away two copies to winners of the GA contest - I knew it was the perfect gift. The one you don’t have but absolutely need.

So salivate. It will be here soon.

Robbin