This was the question that someone asked on the Yahoo WA Forum today. “I work with B2B sites that have 2-5K visits a month,” the writer commented. A lot of things I learned at the eMetrics summit won’t work for me, he worried. In particular, he commented on multivariate testing, and how much easier that is for a site with a lot of traffic.

So is he right? Are those techniques mostly for large sites?

I think that split and MVT is harder for small sites, but not impossible. And let’s not assume that the game ends there, either.

So, let’s say that your site gets 5000 visits/month, and 20% of those people touch the page you want to test (e.g. the home page). So that’s 1000 visits/month, or 33 visits/day. If the conversion rate on the page is 2% and you are looking for/hoping for an increase to 2.5%, i.e. a 25% increase in your conversion rate, you can run four combinations and complete your test in a month. (If you want to check my math, go use my favorite tool, the Website Optimizer Calculator. ) Four combinations can be 2×2 or 1×4. Or, in real-people-speak, that would be two elements, like a headline and a photo, with a control and variation that you want to test for each of them. Or that could be one element, like a piece of copy, with a control and three variations you are testing. Either way, it is four combinations.

Granted, not 400, but helpful nonetheless. I find myself doing tests like this all the time, because I just want to know {fill in the blanks}. I just need to figure something out.

And how about A/B testing? One of my colleagues pointed out to me that an A/B test, early in the process, might be a lot more valuable than a whole bunch of multivariate combinations, especially when you can look at a site and say, “Oh my, how awful. We really think we know how to fix this.”

And not all optimization is about MVT or A/B..N. How about user testing? I really feel that user testing never gets enough press. It isn’t exciting like MVT, but I learn so much from it. When I present it to the customer, s/he often says, “Oh right, usability,” but the truth is, we learn things about the offer (”I would never spend that much money,”), we learn about trust, (”Well, ok, it’s your credit card,” they say to me, “But I would never give that site my card. I just don’t trust them.”) We learn that customers can’t even understand what the site does.

And now that you know that you can use the Google Website Optimizer for even the smallest of sites, head on over to sign up for one of the GWO upcoming webinars. There are going to be two webinars,  GWO for Newbies and GWO for Intermediate/Advanced folks. Tom Leung, the Chief Executive Officer of Website Optimizer says, send him questions ahead of time, and I really believe he will address them.

Introduction to Website Optimizer (New or inexperienced users)
Tuesday, October 30th, 2007 10:00 - 11:00am PDT
Register to attend

Website Optimizer: Creating & Launching Experiments (Intermediate and
advanced users)
Thursday, November 1st, 2007 10:00 - 11:00am PDT
Register to attend

I have been working on this series, Filters for Google Analytics, for almost six months now. This is the last part of the series I am going to write (at least in the foreseeable future.) You can get the full thread at the bottom of this post.

So once again, I will start with the question a lady asked me on Friday morning: how does one create exclude filters that function as if they were AND filters? How, she asked, can I create a profile and put on it two different exclude filters that work together: Exclude the visit if the visitor is a new visitor AND her language is German? We can’t do that with two separate exclude filters, because as soon as the first filter works, the visit gets thrown out. Exclude filters are, by nature, “or” filters.

(If you are a little lost, and don’t remember how multiple exclude filters work like OR filters and multiple include filters working like AND filters, and how you have to work to make them do the opposite — see this post that I wrote recently.)

Well, I had to think about this one, and then realized that it was just a great practice for this series on filters for GA. The reason why: It is both a rewrite (custom advanced filters) and an exclude (custom filter). Here is the overview: you rewrite the two fields into one field, and then you do an exclude on that one field, making sure that it matches both pieces of data.

If that was clear as mud, or you are more of a step-by-step “please show me” person (like I am) — then this is a good place to keep reading.

First, you use a custom advanced filter to rewrite the data so both pieces of info — the visitor language and visitor type, which is GA-Speak for “new” vs “returning” visitor — are in the same field. Like this:

Now we have both pieces of data in the same field. If we could look at them, they would look like this, concatenated together on the same line.

1. en-us/New Visitor
2. de/Returning Visitor
3. da/New Visitor

and so on. They would be the language code followed by a slash and the visitor type. (Right? That’s the way I set it up, $A1 captures everything in visitor language settings, then a slash, then $B1 captures everything in Visitor Type.) Above, I choose three languages for my examples: English-US (en-us), German (that’s de) and Danish (da).

Next, we create an exclude filter. The hypothetical example was to exclude a new visitor whose language is German - the two excludes that must work together. This is the heart of our problem, exclude two different kinds of variables. So here is our exclude:

So what does this say? It say, go to Custom Field 1, where we now have a list of concatenated languages and visitors types (en/Returning Visitor, and so forth). If one of those lines in the list matches de (which stands for German - Deutch, right?) and has a slash and then the word new, it’s a match, so please exclude it.

And that’s how you can exclude two different fields in Google Analytics at the same time.

If you would like to read all the other posts in this series:

• Part 1: Get ready with profiles and ReGex
• Part 2a: Filters for GA, What have we here?
• Part 2b: Why does anyone use filters?
• Part 3a: Easy Filter Implementation
• Part 3b: Custom Implementation
• Part 3c: How do you filter those utm links you create?
• Part 3d: When do you use them?
• Part 3e: Include vs Exclude filters, how do they work?
• Part 4a: Custom Advanced Filters
• Part 4b: More on Custom Advanced Filters
• Part 4c: Cascading Custom Advanced Filters

I should be writing some cool post after three days of Website Optimizer and Google Analytics Authorized Consultant training. Or writing more about yesterday’s GA and Urchin announcements (I will, I promise.) But first, while they are still fresh, I wanted to publish all my pictures from Google Analytics and Website Optimizer training.

Welcome to the new Google Analytics! I wasn’t at the announcement a few minutes ago in DC, but we announced Urchin 6.0 software, plus event tracking for GA and site search. I’ll write about event tracking over time, but first I want to write about site search — the new capabilities GA has to track how visitors search within the content of your own site.

At first, I wasn’t overly impressed. What’s the big deal here? I thought. I can already give my content > top content report the name of the parameter that pulls out my onsite searches, like search= or query= or even s=, and from there, get a report of what people searched once they were on my site. So who cares?

So, this proves that I wasn’t a very good beta tester. I had all this functionality and didn’t play with it (or even bother to understand it) until our team went to Google Analytics Authorized Consultant training last week. And there I saw Phil, the product manager, demo the functionality that I have been ignoring. (Wow, how cool! I thought. What analyst in her right mind wouldn’t want that in her reports?)

Sure, once you have site search analytics, you can see what was searched for, more easily. But it doesn’t stop there. You can see conversion rate and e-commerce metrics by on-site search term, just like you can with organic search terms coming in from search engines. You can also see what pages people were on when they did a search (so you could correlate that with entrance pages, and when the correlation isn’t very good, start to hypothesize that the navigation isn’t working for you on that particular page. Some people are just born searchers, and you have to assume that a search that is on an entrance page is very often a personality issue — they love to search — not a navigation issue.)

You can figure out how search helped you or not. For example, in the screenshot below, you’ll notice that those who used search on our site stayed for over 9 minutes, and those who didn’t, stayed for less than 2 minutes:

You can work with destination pages. For example you can choose a search term from the search terms menu, and then drill down and segment by destination page. In other words, when people typed in “red shoes,” did they choose the important red shoes page with the cool new red clogs, or did they choose that awful red shoes page with the old red ratty cheap sneakers? Or did they just exit in droves (no good destination page, one might assume?)

You can do other things with the usage (and I am sorry to skip around, but am working to keep the ideas with the screen shots.) For example, you can look at bounce rate by search (notice how our bounce rate goes way down if the visitor uses search). Or you can look at conversion rate, or time on site, or a whole bunch of other metrics.

So welcome to the new Google Analytics. Soon I will write about the new ga.js and event tracking. (But before that, I have filter articles to finish and pictures to show.)

I spoke about implementation Google Analytics on Friday, and someone asked me, “How do I create Exclude AND filters?” This is a cool question, but it has to wait until I write the info below on how Google applies your filters (and how that differs on Include vs Exclude filters.) Note: you can read the GA documentation on this one, which is not terrible.

You might consider include multiple filters to be AND filters, when you think about the way that GA applies all of them to a profile. So if you create a profile where an include filter specifies Visitor City = Pittsburgh, and the another include filter specifies Campaign Source = organic, you will filter in only visits that came from people in Pittsburgh who used the organic search to find you. It’s not good enough that they came from Pittsburgh and used paid search, or followed a link. Both criteria must be met.

Exclude filters, on the other hand, could be looked at as OR filters. If the visit matches any of the exclude filters in a single profile, it is thrown away. So using the same example as above, Visitor City = Pittsburgh, and the Campaign Source = organic, you will exclude anyone who comes from Pittsburgh, no matter what their campaign source. And you will exclude everyone who comes on an organic search, no matter what their city.

There are ways around the AND and OR issues. For example, let’s say that I wanted to include everyone from Pittsburgh OR Raleigh. I cannot do it with two separate city filters — right? Include filters are AND filters, so two separate filters would say: include everyone who comes from both Pittsburgh AND Raleigh, which is a pretty hard act. But you certainly could do include visitor city = (pittsburgh)|(raleigh). By putting both cities in the same filter with an OR pipe, you achieve that goal.

Now that I showed you how to defeat the “ANDness” of Include filters, you will be wanting to know, how to do defeat the “ORnesss” of Exclude filters. Plus, you might want to know how to make include filters be OR filters for different kinds of fields — include if they came from Pittsburgh OR they came organically.

But that is a different topic and a new post. Maybe even tomorrow.

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.

Here at LunaMetrics, our “About Us” page is our third most popular page - right behind our  main blog page and our homepage.

In fact, “About Us” is a pretty popular page for lots of sites. But some site owners treat it like a necessary evil, instead of a place that they can sell their product and services in the most subtle and wonderful of manners. So I wanted to evaluate a variety of About Us pages, and since my company is as guilty as everyone else, I’ll start with LunaMetrics.

When you touch the “About Us” page of a consulting firm like ours, what do you want to know? Well, you want to know where they are located. You want to know if you trust the people, or if they are just going to steal your money. You want to feel like the people there are going to be your partners. And you want success stories. At the end of the day, you want to know that this is a company that you will feel really good about hiring. (See? I said that we are guilty of not having a great About Us page. Soon, soon.)

Similarly, we have a local customer who advertises themselves as a Pittsburgh company. They perceive that it’s one of their key differentiators. “So where are those Three Rivers pictures?” I wrote in the expert analysis. “I wouldn’t even be offended if your technical site’s About Us page ended, ‘Go Steelers!’ — it sure would make me believe that you’re a Pittsburgh company.”

Big, big companies can use their About Us page to humanize their company. Almost two years ago, I heard someone from Travelocity talk about their brand makeover. Users perceived that they were “just software” and not real people - and in fact, if you can find the Travelocity About Us page, you can read their Customer Bill of Rights, one of the campaigns they instituted as part of their “just us people” rebranding. Similarly, I didn’t believe that the people at Quicken were “real” until I saw this snapsnot.

Sure, we little companies can use our About Us page to make us ourselves look bigger, more important. The Internet is the great equalizer. But I think (and test, test, test, right?) that we work too hard at having fancy photos and not hard enough to sound human.

About Us is the place to say, “Believe in us.” So the question is always - what will it take the customer to believe in a company?