We did GA training in NYC earlier this month, and I got forms and emails and notes from people asking me when our next one was. They couldn’t make it that day (which was, bizarrely enough, good. We sold out. We printed 70 binders with all the slides to give away, and didn’t have a single one left for ourselves.)

So our next training, for all you folks who asked, and for a whole bunch of people who didn’t, is in Washington DC, August 12, at the American Institute of Architects.

We know that different audiences attend: Those who just want to use the analytics for analysis. And (and/or) those who need to configure them and/or implement. And not only are attendees driven by different tasks, they are at different levels, too. So we’ve tried hard to have the right mix of sessions, and you can see the agenda (and how the sessions are rated) here. And you can also read a more in-depth write-up of each session. You’ll see that the event includes tips and tricks, in-depth analysis, case studies, and even a session on GA 101 for beginners. For those who do configuration, we’ve got goals and filters and profiles, cross- and subdomains, e-commerce and user defined variables. Notice that there are also sessions on Google Website Optimizer and Google AdWords.

Don’t you hate it when people hide their prices? So we won’t: it costs $285. You can register now, and even if you have to cancel, we can refund your money in full until close of business on the Friday before the event. After that, you can transfer your registration to someone else, if you need to.

If you have questions about the event, or want to be sure that your GA problem gets solved there, send me email. Here’s the link where you can learn all about the event.

Robbin

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

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

Should WA consulting firms — or for that matter, conversion consulting firms, or management consulting firms — price by the hour or by the deliverable?

That was the question I started to discuss with Frank Demmler, who teaches in the Tepper Business School at CMU and is portfolio manager of Innovation Works. But we were cut off by time, and I never really got to tell him my problem (which is that my company mostly does fixed price work, and then works twice as hard as we should even if the customer doesn’t ask for it, just so that we delight the customer. Another one of my CMU-professor-friends, Economist Marty Gaynor, told me that this is a variation on “winner’s curse.” But I digress.)

I saw Frank yesterday again briefly, while on break from the Google Analytics Implementation seminar I taught across the hall, and then he sent me this advice on fixed price vs hourly:

Regarding pricing, as we discussed briefly, it’s a classic damned if you do, damned if you don’t conundrum. The granularity and visibility of hours is providing ammunition for an almost inevitable battle. A fixed price contract is one in which the client will rarely be satisfied and will claim that the contract included things that it didn’t.

One overriding comment is that you need to be disciplined and fairly aggressive to train your clients in either case. If it’s hourly, don’t allow yourself to get bogged down in the details. If there’s a substantive disagreement about project scope and resultants costs, that’s worth discussing. Otherwise, stand your ground and claim that you are a professional providing professional services and that’s what they cost. If they want to terminate the contract, so be it. Similarly, on flat fee project work, I’ve never seen a project that was correctly spec’ed out at the beginning. You’ll know when things are going off track. Rule of thumb is at the midpoint of the project, you should have a meeting to discuss progress and where changes have occurred that require an amendment to the existing contract and the fees for doing so.

I am hoping to talk to a lot of my friends this coming week about how to run a consulting company (but remember: not about prices themselves. That’s collusion.) So I wanted everyone to have the benefit of Frank’s thoughts.

Also, if you are a WAA member, you should read this article I wrote a week ago on the WAA site about the economics of running a WA consulting firm. I keep trying to pull the analytics for that page (does anybody read it beyond the eight people who starred it and the three who left comments?) but they make my computer crash. Every time.

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.

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

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