Mymotech

Accenture announced today that they are acquiring Maxamine and Memetrics.

Maxamine is a company that audits a web site with a very specialized crawler, identifying where tags are missing and much more.

Memetrics is a Multi-Variate Testing vendor that has some pretty big name clients.

Overall a really good move for Accenture, if they can leverage the potential of these two companies.

To me, it is a good sign that these acquisitions continue to happen. The space has so many “little” players, and with these consolidations the web analytics industry is “growing up” so to speak. Doesn’t it make you wish you had launched a web analytics solution six or seven years ago?

If your feed reader is anything like mine, you have no problem getting up to the second SEO info, but my fellow web analytics bloggers are usually a little more taciturn. There are good reasons for this. A good web analytics post takes time to write. It is not some quick rant on why Google’s latest announcement is lame or awesome; it must be carefully considered and thought through. With that in mind here is my list of five Web Analytics Bloggers that I think need to put their spreadsheets down and let the world know what they are up to.

1. Eric Butler of Inside Analytics - Eric always has some interesting news about some cool widget or technical item, and usally WebTrends related. There just isn’t enough of that these days.
2. Dylan Lewis of Passionate Analyst - Seriously good posts always. His thoughtful posts are always enjoyable to read.
3. Ian Houston of Visioactive - Just because you were shortsighted and joined Visual Sciences right before they got acquired, doesn’t mean you should retire from the blogosphere in shame. A real authority on cookie issues and measurement of web 2.0.
4. Wendi of Coremark Analytics - Since I don’t have a statistics background, I rely on the internet to get me educated in this area. Wendi has some posts that are really great, but I need more.
5. Aaron Gray of Greater Returns - While I might disagree with Aaron on the college degree requirement to be a good web analyst, I find his posts insightful and relevant.

So that’s my list, if you know one of these people send an IM or an email and let them know that while writing a blog about web analytics may not make you famous, there are still people who read and enjoy it.

Now, who else has been silent for too long?

Like a small child quivering alone in his dark bedroom while mommy and daddy yell at each other in the den, I have marked with concern the recent blog posts coming from Eric Peterson and Avinash Kaushik.

To be fair, it would appear that the first blow was struck by Avinash in his post entitled “Web Analytics Demystified“, which is of course the name of not only Eric’s book but also his consulting business.

And then today I notice a post over one Eric’s blog entitled “Web Analytics: An Hour a Day” which of course is the title of Avinash’s book.

Well, what goes on here? is what I want to know. Here are some possibilities:

1. We have seen the first rift in two distinctly different schools of thought as they relate in approach to web analytics. Making way for the inevitable fulfillment of Chris Grant’s prophecy.
2. Eric and Avinash are experimenting with being a Fred?
3. Eric and Avinash are pulling some sort of friendly joke on each other, and forgot to tell me, not knowing that my world collapses when people I look up to start fighting.

But seriously, I hope that this is all a cool web2.0 thing that we will all look back and laugh about in a month or two, but if it is really a fight, I put my money on…. Oh I don’t know. In the words of Rodney King, “Can’t we all just get along?”

Final Thoughts:

Dang you, Mike Keyes for beating me to the punch on this post!

It has been a very eventful past few months. And Like Mike Keyes I am trying to get up the gumption to post more. Here’s a run-down on my recent whatevers.

• Got a new job, and have begun the transition to Chicago. And while the switch was not fomented by money it is nice to see that I am now being compensated in a fashion that is in line with my 4 years of experience.
• I am expecting child number 2 with my wife, which is awesome. Could I hope for a girl? Either one would be awesome.
• Saw the fizzling of a very promising side project, on account of items one and two, but that’s tuff.
• After a brief review of the data for this blog, I have established with relative certainty that the more you post the more traffic you will get. In web analytics circles we could call that the Marshall Sponder rule.
• I have recently decided to become an Excel expert, and began by downloading every sample Excel spreadsheet I could find by Juice Analytics and Clint Ivy. (You guys make me look smart)
• I watched an amazing video on the TED web site of Hans Rosling explaining some world health and wealth statistics. I dream that web analytics data can be that engaging.
• I still read many many blogs each week, including you if you blog about web analytics, and now since it is officially 2008 I give myself permission to start being engaged with the upcoming presidential election.

Well, that’s the news from this Panera in Elmhurst. May you hit your conversion targets in ‘08.

There have been many discussions about what is the value of web analytics. In fact there is a very interesting Forrester report that shows a significant ROI on a full time web analyst.

But in reality implementing a web analytics tool, producing reports, and even looking at those reports with an analytical eye does not actually create bottom line value.

All of the value of web analytics comes from what you actually do with the data you have analyzed. If you increase spend on MSN because you see that it converts better, then you have started to achieve an ROI on your analytics investment. If you A/B test your landing pages and find a better landing page design that converts better then you have begun achieving an ROI. If you start suggesting product Y when people are buying product X because you have noticed that people frequently buy them together, and you increase your average order value then you have gone down the path towards ROI.

The point is that unless you have thought all the way through your analytics strategy to the point that you have a plan in place to actually apply the data to specific areas you will get nothing from your web analytics investment.

So, what actions are you planning to take with your data?

Avinash Kaushik has recently published his top 10 Web Analytics Blogs. And while I am not on that list, it is interesting to see the emerging debate that it has sparked. The ranking factors for Avinash’s list are comprised of some wrangling of Feedburner subscribers and Technorati rank. But let’s face it ranking anything in the world of analytics is like throwing red meat to an audience of hungry rottweilers. So kudos to Avinash for a brilliant idea. While I do not expect to be on Avinash’s list any time soon, it is nice to see that the number and quality of web analytics blogs is gowing and changing. This is such a great industry to be a part of.

So, I logged into my Google Analytics account today, and saw a message about how they are going to be upgrading the Google Analytics interface over the next few weeks.
However, I wonder what is going to change, because they just said that they are introducing the new user interface.
But if they are improving things, here are some things I would love to see.

1. Put all organic search engine reporting together. I have already blogged about this, and it is annoying. POST: Is Google really as good as other tools
2. Make a more viable export option. The current options are craptastic, and require lots of finagling to get started doing some number crunching.
3. Allow me to save some of my more common report level filters. It is lame to have to type them in again week after week to get the same data.
4. Make it possible for me to customize my view. Just having the ability to arrange the reports how I like to go through them would save me a lot of time. Also, remembering how many rows I want to see for a particular report would be nice.
5. And this one is a biggie. Give me some sort of direct query capability so that I can go after report data with other tools and integrate them how I want to. This doesn’t need to be hard. A simple REST or SOAP API and we could be on our merry way.

Keep in mind that Google Analytics is not my main analytics tool. I don’t even use it for my clients. So, if I have said something glaringly wrong, I would be delighted to know that there is a way to do that thing.

Comscore recently published a press release about 1st and 3rd party cookie deletion rates that they measured in the month of December.

Here are the important details.

• Duration: December 2006
• Sample Size: 400,000
• Sample Site: Portal with content and an Ad serving 3rd party cookie
• Average number of 1st party cookies per computer measured: 2.5 (100 visitors becomes 250 visitors)

So, the gist of this press release is to say that 1st party cookies are an imperfect method for tracking unique visitors over time, and that using them will inflate visitor counts by as much as 150%.

OK, then what should a web analytics person do?

1. Don’t panic - Everybody already knows that 1st party cookies are an imperfect form of tracking unique visitors over time. Cookie deletion happens, people surf at work then at home, and a whole multitude of other scenarios that pretty much make 1st party cookies a crap shoot.
2. Look and see what metrics you are using that depend on unique visitors. Here are two samples:
• Visitor Conversion - This could be a biggie, but guess what; you are not overstating conversion you are understating it. Grab last months Visitor total and divide by 2.5 now use that number to calculate top level conversion. (Orders/Comscore Visitors) Boo Yaa right? For all you web analysts that get paid by conversion boosts, it is time to figure out where the pool goes. And practically speaking this doesn’t really change all that many things except to normalize and baseline at a different level. Obviously I am keeping it simple. This is a blog post after all.
• Campaign Response - Ok this one could tighten a little bit, especially when the sales cycle for your product is longer than a day or two. So what can you do? Start by understanding the difference between regular old visitor conversion and a campaign visitor conversion. Then get about learning how to understand your entire conversion process from offline to online and vice versa. Do some surveys to understand visitors who purchased better, and quit demanding a 4 to 1 ROI on Adwords. In actuality these numbers should drive you to your customers for answers and that is a good good thing.
3. Next start to redefine your metrics realistically. You have to fight against the current of web analytics vendor marketing speak, but you can choose and use metrics that do not leave you over-extended and washed up when Comscore points out the existing flaw in your underlying data. This is actually one of the harder steps, because it takes a special analyst not to jump on the next greatest metric band wagon, and to realize that every metric that gets used in the rest of the business world is not necessarily ready to be used in web analytics.
4. Don’t start writing the business case to move to a complete session based cookie tracking system yet. Comscore only surveyed one site and that with their panel of users who are provided spyware tools that may or may not recommend the removal of 1st party cookies. See Eric Peterson’s Blog for more on that.

So, these are interesting times. My advice: beware anyone who gets up in arms on either side of this issue about cookie deletion. Most likely they are trying to sell something. Get to know your visitors and customers. Cold stats are good for breakfast but you need more than that to sustain you.

The old put your name on it and you will take better care of it thing is not working. But in the interests of letting everyone know I am still alive, here is a quick list on what I have been up to lately.

1. I read a lot. You can have copies of my OPML file of web analytics and SEO blogs if you want.
2. I do a show with my brother. The Clickherder roundup. We will be posting episode 3 tomorrow, so surf now.
3. I shovel snow a lot. (Because Easter is when all the snow comes apparently)
4. I work. Things are going well, and I am involved in some exciting ecommerce projects (of course, I can’t talk about that).
5. I am building a website. I have teamed up with a friend to develop one of them niche type of sites, with an aim to test my mettle in the SEO ring. I am starting out in a relatively easy niche, and once I get a #1 on Google I will be sure to let you know of it.

Well, this is a blog about web analytics, so I guess a web analytics type post is in order.

Since Google Analytics came out last year, there has always been a question:

Isn’t Google Analytics just as good as other web analytics tools that cost more?

And while there are many different answers to that question, I ran across something today which inspired a closer analysis.

When looking at keyword reports in Google Analytics you can view the search phrases

Or You can view the Search Engines

But you can’t view both at the same time. In other words, You can’t see a report that displays all the search engines and their underlying search phrases simultaneously and vice versa. In addition the export function only grabs what is on the screen, so there is no correlation of those two data points in any exported report.

Briefly, I want to describe why it might be useful to see search engines by search phrases or vice versa. Let’s say that I am trying to optimize my site for the phrases, “wowza”, “yowza”, and “gyoza”. Wouldn’t it be useful to be able to track the number of referrals I got from Google and Yahoo over time without having to expand and collapse multiple boxes within the report? But it doesn’t appear that that is the case with Google Analytics.

The lack of this feature makes Google Analytics inferior to the likes of WebTrends, Omniture, Coremetrics, and WebSideStory. Although there is still no beating the price.
BTW, I would be happy to be wrong, so if you know some way to accomplish this in Google Analytics then please let me know, and I will obviously post an update.