For the second time in a month, an investment banker called me to talk about web analytics. What with mergers, acquisitions and IPOs (and of course, the development of the industry), it’s on their radar now.

His questions were so interesting, I wish I had been taking notes like I was when the big WA firms spoke at the Summit in Santa Barbara. In any case, here is what I can remember.

Investment Banker starts with an easy question: Who is the best customer for packages like CoreMetrics and WebSideStory and Omniture?
Robbin: E-commerce. Companies who sell on line can prove the ROI of the package quickly, although they have plenty of issues with multi-channel purchasing - the customer sees it on the web and buys it in the store. Companies who are doing lead generation have a harder time proving the ROI (Robbin neglects to say, especially when the company has to touch the lead many times before the sale is closed.) Companies who are doing on-line content, like CNN and the NYTimes.com, should be able to prove the same kind of ROI as an e-commerce company because they are selling online, it’s just that they are selling advertising.

Investment Banker: What will it take for WA to become more pervasive?
Robbin: People really won’t buy *and use* their web analytics until it is in their financial interest. So if you’re a content site, and a big advertiser comes to you wanting a deeper understanding of your reader behavior before signing a new contract, suddenly, it’s in your interest to have better analytics.

Investment Banker: Research firms are predicting that the WA space will grow to about $1B in five years in marketing capitalization. Do you think that’s enough marketing cap to support the number of current WA firms or will we see lots of consolidation?
Robbin: After business school, I went into direct marketing, not investment banking. You can run the numbers as well as I can or better.(Why do investment bankers waste time asking questions that they are in a better position to answer?) From where I sit, I just know that I would *love* to see consolidation in the industry so that we can do a better job with standards and so that my company doesn’t have to keep learning new software packages. Probably not the answer he wanted to hear.

Investment Banker: Which of the big firms have done a really good job investing in cutting edge technology, enabling themselves to leapfrog the competition?
Robbin: Well, WSS has made some interesting purchases with Atomz and Visual Sciences. But let me tell you what I really think, and I sincerely doubt you will hear this answer from other people because the individuals who are successfully implementing big packages have IT staffs that can customize them. So here’s what I think: I don’t think that cooler technology is going to rule here. The real problem is that you currently can’t get your money’s worth out of big packages without creating those custom evars and s.props and VISTA rules. Currently, buying a big package and then not having an IT staff that can and will customize it, and of course, an analyst, is like buying a Porche and driving it in first. (I get to use this analogy over and over again. Many thanks to the individual who gave it to me.) I think that those companies will have a hard time expanding really far until they can create the ability to customize without the analyst needing to be a javascript expert.

Investment Banker: Will BI firms get into the WA game?
Robbin. Sure. But the really important thing that will happen is, data will be more seamless, so that it can flow between your BI and WA and CRM. Easily, not with a 4 month integration project.

It’s probably just as well that I can’t remember everything we talked about. Leave the guy something to write about in his research report, now that my four readers have all learned what I said.

Robbin Steif
LunaMetrics

Twice in the last 24 hours, I had trouble with analytics — once with Omniture’s SiteCatalyst and once with Google Analytics. Both times, I “solved” the problem (more accurately, finally understood it) by making my time period shorter and shorter. But I’ll only show the Omniture example.

The Omniture/SiteCatalyst problem was that the customer was seeing more orders than items put into the shopping cart. So even if everyone only bought one item (somewhat unlikely), and everyone checked out (incredibly unlikely), there still weren’t enough items to justify all those purchases. We had already verified that the purchase numbers were pretty good, and it wasn’t that hard to see that items put into the checking cart, as a percent of visits, was incredibly low compared to recent history.

“So when did this start?” asked Omniture LiveSupport (a question I should have asked myself.)

I pulled a report for the last 60 days and found this:

You can see the crash on August 1, and when I “zoomed in” on August 1 and did a report by hour, I was able to find exactly when it happened. IT tied it to the change that they made. (By the way, the report is Commerce > Shopping Cart > Cart Additions.)

Now, this seems very straightforward. I had a similar program with Google Analytics (and that one is actually being reported as a change request, or a bug), but only by narrowing and narrowing my parameters was I able to delete enough variables to understand that the problem was truly a GA bug.

Time isn’t the only parameter to use when troubleshooting but it sure is a great place to start.

Robbin Steif
LunaMetrics

Web analytics can be a lonely field. It’s awesome to go to the eMetrics summit or other conferences and meet the people you correspond with all the time, but that only happens a couple of times a year. And how often do you get to sit down with another analyst and say, “Look at my stuff. What mistakes am I making?”

That was one of the reasons that I took ROI’s webinar - it includes a free GA audit. (The other reason was that I wanted to learn advanced GA, now that I have so many customers using them.) Today I had my audit with Michael Harrison, and it was so wonderful to actually go through the goals and filters and get advice. Once he even said, “It looks great. You’ve got it all set up right.”

The best part was when we talked about my regular expressions, which look like this:

/secondpage/register/

He asked, “You realize that this includes everything before the first slash and everything after the last slash?” I only answered, “Yes,” because his wife has been in labor for days now, and he was doing me a favor and calling me from his home. If he had had more time, I would have told him how I learned this from my Regular Expressions Tutorial.

Robbin
LunaMetrics

This is part II of my journey into Regular Expressions for Google Analytics, whereby I am learning them (they are abbreviated as RegEx, or maybe in the plural, RegExen) and teaching them at the same time. I have rewritten this old post to include only the dot, like the one at the end of this sentence. This is to make the post easier and create building blocks for future posts.

Google Analytics says this about dots:

. matches any one character

This is exactly what they mean, but it is so out of context, I couldn’t wrap my head around it. (Match any one character that comes from where? I asked myself…)

They mean that you can create a RegEx like this

.ate

and it will match hate, fate, sate, or any four character expression. For that matter, it will match 8ate (there were no rules saying that the character has to be a letter.) It won’t match just ate, because it wants one character to substitute for the dot.

This is why we don’t (usually) ask Google Analytics to match a regular expression that looks like this:

homepage.com

because the dot is a wild card that stands for any one character (right?), so this will also match homepagescom and homepage4com and homepagedcom. Instead, we need to use a backslash to turn the Regular Expression dot into a Plain Old dot. (This is a good time to read Regular Expressions Part I, backslashes, if you haven’t already.) Anyway, we would express it like this: homepage\.com.

And that’s why you see backslashes and dots together so often.
Backslashes \
Dots .
Carats ^
Dollars signs $
Question marks ?
Pipes |
Parentheses ()
Square brackets []and dashes -
Plus signs +
Stars *
Regular Expressions for Google Analytics: Now let’s Practice
Bad Greed
RegEx and Good Greed
{Braces}
Minimal Matching
Lookahead

Robbin
LunaMetrics

You can read Part I of this topic here.

Soon after writing about great thank you pages, I had a chance to look at one. We signed another new customer and I started poking around their site to learn more. I filled out a “contact us” form and was awed at the incredible reply. “Thank you for your request for information,” it read. “Your form is being routed to the person who can help you, which will be Jane Smith. She will get back to you in about 24 hours, but if you want to call her yourself, she is at 800-123-4567.” Then they included an opportunity to opt into their email newsletter (so that I would have a second chance to convert that day.) And finally, Jane Smith got back to me by email within an hour or so.

So they gave me a name, a timeline, a phone number and a chance to convert again, all in a sentence or two. And they lived up to their promise.

Robbin Steif
LunaMetrics

It’s true. I cheated on Google AdWords so that I could measure A/B Google tests in my Google Analytics.

First, the background. Lots of small websites and advertisers aren’t ready to take the multivariate testing plunge, so start by using Google AdWords to A/B test. This is pretty tried and true: You create two ads for the same AdGroup which are absolutely identical, down to the URL that shows on the Google page (SERP). However, when the customer clicks, each ad has a different landing page. Then the advertiser compares conversion rate (or revenue, or average order size) for all the customers who start with Ad1 vs Ad2.

Admittedly, it has its limitations. Search engines are demographically skewed, and just because it works for Google customers doesn’t mean that it will work on Yahoo. But it’s way better than saying, “I know what will work. I just know.”

Google has recently made measuring different ad versions easier in the AdWords interface, but with Google Analytics, you still have to know how pull down the right menus and segment to see what you need. And even then, if the ads have the same name, you can’t tell them apart.

Step 1: Pulling down the right menus. (I can’t remember whether I learned how to do this from Justin’s GA blog or from ROI’s GA blog, and I can’t find the reference.)

Choose Marketing Optimization > Marketing Campaign Results > Campaign Conversion. Left click on the Analysis Options next to one of your Google AdWord campaigns (which you get with the little red circle to the left of the campaigns - follow the top red arrow in my picture); choose Cross Segment performance (that’s the middle red arrow I’ve drawn); finally, choose Content. When you choose Content, you’ll get a list of the different ads that are running for that campaign, by goal.

Step 2: This is where you cheat: Retitle your ads, ever so slightly. When you are using your Google AdWords to do A/B testing, as described above, the ads are identically worded. Google Analytics lists them out by title, which means, it can’t tell you that Ad1, titled, “Increase your Conversion Rate,” and which lands on www.lunametrics.com , is doing terribly, and that Ad2, titled, “Increase your Conversion Rate,” which lands on www.lunamerics.com/conversionrate, is doing great. It only sees one ad, called “Increase your Conversion Rate.” You can cheat on Google AdWords by changing the titles very very slightly. In this case, I would change one of the ads to have a capital Y in Your, so that it reads, “Increase Your Conversion Rate.” The difference is slight enough that it shouldn’t matter, and will enable you to read the results in GA.

Robbin Steif
LunaMetrics

Thank you pages serve a number of goals:

• They let the customer know that he successfully completed the transaction
• They may give the customer critical information (”Thank you for subscribing. Check your email to get your subscription link.”)
• They may be printed by the customer as a receipt
• They are an easy way to tell your web analytics that a conversion took place.

Besides serving all these goals, thank you pages provide a special opportunity that many sites, especially e-commerce sites, do not take advantage of. Most of us know by now that it is very important not to stop the customer when she is trying to spend money, and that’s why we don’t have mandatory registrations or surveys before the shopping cart. The thank you page is the perfect place for those things:

1) Surveys. Some e-commerce sites already have professional surveys, like BizRate. (Read what I wrote about invasive surveys.) Most do not have any surveys (because if they did, I’d be taking surveys every other day.) I pleaded with an e-commerce customer to put a survey on his website, and while we agonized about the wording and she dragged her feet for months, she ultimately did put the survey up. She has been awed at the kind of actionable information customer have been giving her on her survey (especially because she included a large freeform box for customers to make any comments that they like.)

2) Registration. Like a good etailer, you let them purchase as a guest. Why not ask for the registration now, on the thank you page? You’ve already got all the information you need except a password and username (and you might even make the email address into a username if that’s how your site works.)

3) Other opportunities. The thank you page is the perfect place to ask customers if they would like to be a member of a virtual focus group. Virtual focus groups give you a small mailing list that you can ask questions of — about the site, about your service, about new products. Most people don’t compensate the group but may do an annul coupon or other thank you gift. An even better way to recruit members for this group is to ask everyone who emails a complaint or a compliment to join — those people are already engaged with your company at a high emotional level.

4) And my favorite: The thank you page that gives you a chance to go back to the site and buy some more.

Robbin Steif
LunaMetrics

What are Google Analytics’ “Regular” Expressions?

This was the question that I asked in August 2006. Although this post is ostensibly from August, I am actually rewriting it in October. Now that I understand Regular Expressions for Google Analytics, I want to explain them in the easiest language possible (so I had to go back and rewrite.)

The most basic expression is \ the backslash. Google Analytics ascribes this meaning to it:

\ escape any of the above

What they mean is, you can use a backslash to turn any special character into a not-so-special character. Google (and everyone else who talks about Regular Expressions) makes this hard by using the word “escape,” when they merely mean, use a backslash to take the magic out of a special character and make it an everyday character.

Although the backslash can be used with any special character, I see it used most often with a dot. This is because a dot is both a special character (see Part II), and one that is used with the Internet all the time (Example: www.myspace.com — we see it there twice.) On the Internet (and so, with Google Analytics) we almost always are using dots as regular dots and so need a backslash to keep it as a mere dot. Here’s an example: mysite\.com and here’s another one (this time, an IP address): 64\.68\.82\.164

Many thanks to my tutor in Australia, Steve. With his help, help from Justin Cutroni, and many hours of reading and rereading the Wikipedia page on Regular Expressions (I won’t even link there, it is so difficult), I learned Regular Expressions. Very late comment: This started as a mere question for me. This ended with a seventeen part series.

Backslashes \
Dots .
Carats ^
Dollars signs $
Question marks ?
Pipes |
Parentheses ()
Square brackets []and dashes -
Plus signs +
Stars *
Regular Expressions for Google Analytics: Now let’s Practice
Bad Greed
RegEx and Good Greed
{Braces}
Minimal Matching
Lookahead

Robbin Steif
LunaMetrics

This is not really about e-commerce: it is based on experience with a lead gen website. The e-commerce angle makes it easier to understand, though.

What should you do if have a category page with five products on it, and one of them is head and shoulders above the rest in terms of popularity but is a much lower margin product?

I always like to call out “most popular” products and put them in eyesight order (i.e. the most popular product is in the upper left hand corner of the active portion of the product page.) Yesterday, I had a customer complain about doing that.

“But we don’t want them to buy the less expensive, lower margin product,” she said. “We want them to buy the more expensive product.” Well, true enough. But we can’t always have what we want, and sometimes we take the best of what is within our grasp.

There are three reasons that I like to point out the most popular product:

1) Jared Spool’s company addresses this issue with what they call “Inukshuk content.” An inukshuk (also spelled “inuksuk”) is a beacon of sorts, usually a little stone totem, that people would build or leave a rock on to say, “I was here.” Just as there is something wonderfully gratifying about finding out that others have gone before you in the wilderness, it is comforting when you see that others have bought the product. This can take many forms (product reviews are a better format than the etailer himself writing, “Most popular.”)

2) At a much less sophisticated level — I’d rather get a small sale than no sale

3) If you have a lifetime value to your customer, and not all sites really do — then a small, successful sale will often bring in larger, even more successful sales.

Robbin Steif
LunaMetrics

Podcasters can consider this unpaid user testing: I usually write from the client’s side of the aisle, but tonight I want to be a customer. Specifically, I am a very avid listener of podcasts, yet podcasts and podcasters can drive me a little crazy sometimes — enough to make me stop downloading them (bad) or stop listening to them (arguably worse, since they don’t have my share of mind but their analytics can’t tell that. )

Mistake #1: Your website makes it really hard for me to subscribe to your podcast. If you already know what the feed address is, why can’t you tell me instead of asking me to click on a link that brings up my Quicktime and insists that I sit at my computer to listen to you?

Mistake #2: Your website doesn’t have links to sites/software that you/your guest discussed during the podcast. I know that you think I am sitting at my computer and listening to you, but in fact, I am driving, and I just can’t write down the name of a suggested destination, no matter how carefully you spell it, while switching gears and accelerating. For example, I listened to a wonderful (albeit too long) podcast today on design, with someone on Good Karma/Webmaster Radio. The speaker gave out a number of sites that might have been interesting to look at, but I was exercising and then driving.

Mistake #3: You think I am paying attention to you all the time. and Mistake #4: You think that I listen to you from beginning to end in one sitting Here’s the problem: You may ask a guest a question or start in on a news item that I already know or am not interested in. By the time I notice that you’ve moved on to a new, more interesting topic or question, you’ve already announced the topic name. This means that I get to hear the item but I never hear the subject or the subject name. If, for example, you are talking about a new pay per click feature, I can probably figure out whether the subject was Google or MSN or Yahoo. But if you are talking about some cool feature that a new, little-known website introduced, I won’t know what the site name was unless you find a way to close the news item or question with a reference to the site again. This same issue rears its head when I listen to only part of a podcast, get to my destination and turn off my iPod, only to pick up the next day without a clue as to what the specific subject was.

Mistake #5: Your equipment is lousy and that of your guests is worse. I am somewhat more sympathetic to this topic than the others because when I did my podcast with Eric Mattson, we used Skype. The sound was crystal clear yet the technology burped in the middle and we didn’t know it until listening. I was amazed that people listened to the end (and I know they did, because they sent me comments about this issue). I just find it too painful to listen to anything that is not mission critical when the equipment makes the voices hard to hear.

Mistake #6: You think I already know who you are and how your show works. For months, I listened to Danny Sullivan talk about “the chat room” on the Daily Searchcast and assumed that it was something you participated in if you were one of his subscribers. Eventually I figured out that the chat room he was referring to is a function of Webmaster Radio. I think.

Mistake #7: You spend too much time joking and wasting time and not enough giving me really hard information or important thoughts. Enough said.

Mistake #8: You work too hard to be funny even though you aren’t a funny guy because you think that’s the way it works. Well, maybe others will disagree, but I think podcasting is like blogging: your audience has to love you for who you are and not who you think you should be. (Or maybe that’s Bridget Jones.) I can’t even give you any examples for this one anymore because all those podcasters have long since been deleted from my iTunes.

Mistake #9: You allocate an hour for your podcast when 20 or 25 minutes would be just great. See Mistake #4.

Mistake #10: The name of each cast is not descriptive enough for me to know if I’m interested in the download.

Having said all that — I still love podcasts (at least, the ones that I haven’t deleted from my iTunes.) They enable me to multi-process, i.e. learn while I am doing a second activity at the same time.

Robbin Steif
LunaMetrics