Surprise! Surprise! I recently had a chance to do some analysis of reporting tasks when done with Google Analytics vs. WebTrends. The idea here was to see if I could save some money using Google Analytics for web analytics reporting. Make sure to read at the bottom for caveats galore.
Compare reporting effort between Google Analytics and WebTrends for 15 web site profiles that utilize custom segmentation, event tracking, and goal analysis reporting. Being very experienced with WebTrends, I have a pretty good idea of the amount of time it will take to get the data I need from WebTrends. I then did similar tasks in Google Analytics to create a comparison. Keep in mind that this comparison only relates to the time to get the needed data out of each tool. Implementation and Analysis times are not considered. They are roughly the same anyway in this scenario.
Google Analytics can do most of the required reporting (The only data point I am unable to collect from my requirements is unique visitors by country). However, due to limitations in the way that data is accessed and exported using Google Analytics it would take more than three times the hours to collect the reports needed to perform analysis.
So using my ultra-complex mathematical algorithm: 5 hours per week with WebTrends now equals 15 hours per week with Google Analytics. Hmmm, over the course of a year that is 500 hours of my time. If I use Eric Peterson’s average web analyst salary data [pdf] that is $22,000 that Google Analytics is going to cost in salary. Ouch.
What causes the Gap
- ODBC. ODBC. ODBC. WebTrends having an ODBC connector that I can use to directly query the report database is a monster of a time saver.
- The persistent export of interval data before the main report in Google Analytics. This is sometimes useful, but not always what I want.
- Inability to create a custom report in Google Analytics. Especially around custom segmentation. I need to see multiple values in the reports 1st dimension and GA will only show me one at a time. It is enough to make a grown man cry. And before some kind soul recommends creating separate profiles for all of these just know that before doing that I am at 15 profiles already in this particular situation.
- Google Analytics is a robust web analytics solution. But we already knew that.
- While my reporting requirements were not all that intense, there were some aspects of it that really made life hard for me when using Google Analytics. I know there are probably ways around these issues that ingenious GAAC’s have thought up, but you begin to see diminishing returns at some point. I want to stay away from bailing wire and magic solutions that keep me from being replaceable.
- When you evaluate web analytics tools, it is important to carefully consider your needs. Just because Google Analytics is free doesn’t mean it is the lowest cost.
- I use Excel for web analytics analysis. I think that I am in pretty good company until I can afford some sweet software.
- None of this is meant to imply that people should use WebTrends over Google Analytics. Needs differ.
- This analysis was done by someone who is very experienced with both tools, so results may vary with familiarity, however it is probably fair to say that I am more skilled with WebTrends.
- This is not meant as a comparison of the features and functionality of each tool. The requirements did not utilize all features available in either tool.
- Why are you wasting away in caveatville? You should be making an awesome comment or subscribing to my feed.
Update: I made a mistake initially and wrote 2nd dimension only shows one value where I should have said 1st dimenstion only shows one value. Sorry for the confusion.
I love web analytics. It is one of my life’s highlights to have gotten involved with it when it was still fairly young, all the way back in 2004. For all of you that are longer in the tooth than I am, before scoffing just think about what was available online back then. Basically a couple of vendor sponsored white papers [PDF], ClickZ articles, A few blogs, and the Yahoo Group. Today, I have 45 web analytics blogs [OPML] in my Google Reader (and I am fairly selective). I recently wrote about some bloggers that need to post more. As evidence of my “pull” in the industry none of them have actually taken me up on it, but a couple have indicated a return soon. Yesterday I stumbled on another jewel of a web analytics blogger: Paul Strupp.
My endorsement is not exactly the Colbert Bump, but here’s why I like his blog:
Very intelligent and very experienced.
I can relate to his style. He doesn’t take a know it all attitude in his writing.
He is a real practitioner solving for real problems a web analyst faces.
Here are some links to good content to get you started. After that you should subscribe to his feed.
Starcom, Tacoda, and Comscore jointly published a study yesterday revealing that 6% of the online population accounts for 50% of all display advertising clicks. This audience fits the demographic of 25-44 and household income less than $40,000 annually. Additional details regarding this segment are that their online buying is not proportionate to time spent online, and they frequent auction, gambling, and career services sites. This is interesting data. I like to think. And here are some of my thoughts.
Click-Through rate shouldn’t be used by anybody as a success metric, even for brand-building campaigns
Is this the signal that the “unwashed masses” have come online? The heritage of the internet is smart, but as the internet becomes more available to everyone that means the internet will reflect society more and more. Go get your driver’s license renewed to see what I mean. A lot of times we are too NY/LA/ivorytower to really get a grip on this.
I love Tacoda. I mean really love them. Behavioral targeting is hella fun.
We have to keep pressing to understand people online. Web measurement is only part of the puzzle. So often, I see people attacking an online objective with only quantitative data. This is perturbing especially in the area of brand measurement where visitor behavior tells you very little about how your customer actually feels about you.
Every one’s favorite analyst, Dylan Lewis, started a Web Analytics Wiki back in June 2007. When it launched I thought it was a great idea. A community around web analytics that was a living breathing Wiki. Well then I got busy again and forgot about it. A couple of weeks ago I remembered the web analytics wiki, so I thought I would check it out and see how the community was coming. I jumped to the “recent changes” page and to my delight there were updates from that day.
I jumped to one of the pages to see what the community had developed, and lo and behold this is what met my eye.
Needless to say I was horrified. I made a couple of edits to try to get rid of some spam pages, but if this wiki is ever going to get going again it will take the community to get in there and fix it. So what do you say, let’s all get our iShovels out and get rid of a few pages of spam and help get this wiki back on track again.
Two of my favorite web analytics stars are at it again. It wasn’t difficult to see before that the divergence in their thinking centered around Eric Peterson stating that Web Analytics is hard, and Avinash Kaushik stating that web analytics is complex, and now it is out in the open.
But what is truly at issue here? Is this really the throw down between complexity and hardness?
When I got involved in web analytics back in 2004, I was surprised at how easy it was get good reports out of the tools. But I was also amazed at all the little details I needed to know to make sure my reports were as accurate as possible. Things like whether or not my PDF downloads were throwing off multiple 206 return codes and giving me way too many download counts, or trying to figure out why 80% of my visitors came from Reston, VA. and other stuff like that. Because of this I started saying, “Web analytics isn’t rocket science it is just a lot of information.” In other words, Web analytics is complex.
As I progressed in this field I started to realize that producing the world’s most accurate reports was one thing, getting someone to do something about it was quite another. The actionability crisis was on. And this is where things got difficult. To make an organization that was unaccustomed to paying attention to web metrics to make decisions on this new data set was a monumental task that required not only a strong understanding of their business but also enlisting the participation of executives who could effect change within their organization and bring about a metrics revolution. This is where web analytics is hard. Really really hard. That is why many organizations today still struggle with what most web analytics experts think is commonplace; picking a KPI and then doing something about it. It is hard to get organizations in the habit of doing that. Especially organizations that don’t reward risk taking. In this way, web analytics is hard.
When the Giants beat the Patriots in the SuperBowl, they used the same combination. It was hard to beat the patriots, and to do it they utilized complex schemes of attacking the QB with different guys coming free at Brady. And on the offensive side of the ball they used complex patterns and routes for their receivers and tight ends. Beating the Patriots was hard and to do it they had to implement a complex strategy.
So, at the end of the day web analytics is hard and complex. As excellent web analysts we must be comfortable with both the complexity and the hardship of web analytics.
Eric Peterson and Avinash Kaushik are both right.
You know you have arrived when you get a reciprocal linking request. This arrived in my inbox today:
We visited your site [name] and are interested to swap links
with your site.
We would add your link at the home page of
[URL removed] which will actually
help to increase the search engine rank of your site and give you some
targeted traffic too.
We’d appreciate a link back from the home/internal page of your site for
the mutual benefit.
If you are interested please reply to this email with your link details.
We look forward for your positive response.
Well, it must still work, I guess. There is only one problem, the URL they sent me where my link would go was to a domain that expired five days ago.
Woops. I mean seriously, get it together. You are going to ask for a reciprocal link, but then tack on a domain that is not there. Maybe the barrier to entry is too low online.
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.
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.
of Passionate Analyst
– Seriously good posts always. His thoughtful posts are always enjoyable to read.
– 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.
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.
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?
Matt Cutts has boldly gone and painted with a broad brush. In a blog post he insinuates a connection between using Google-unapproved SEO techniques and criminal behavior.
For a while now, I’ve had a slight hunch that clients that embrace blackhat SEO on their site are willing to cut corners in other areas of business as well… Can I definitively claim that there’s a connection between a willingness to embrace blackhat SEO and a willingness to cut corners in other areas of business? No, of course not…
The problem with Matt Cutts’ statement is that there is a difference between people who employ blackhat SEO techniques and people who misrepresent themselves to clients in an attempt to defraud them out of money for services performed poorly. In reality the latter is what got TrafficPower in trouble. The SEO methods that they used were ancillary to the wrongdoing they were engaged in.
Mr. Cutts is placing Blackhat SEO usage on the same level as business ethics. That is a fallacy. I am sure Matt would like us to believe that using blackhat techniques somehow compromises your integrity. The imposition of morality is always a tricky thing. Google controls 65% of all searches today, is that a mandate to impose laws on web sites? Does “might make right” on the internet today? The reality is that Google does not have the right to impose morality on anyone.
I can understand the temptation to view blackhat SEO as somehow immoral, but it just isn’t so. Is it a good long term strategy for a site that wants to be around in six months? Absolutely not. However, that doesn’t make blackhat SEO itself a crime. Selling SEO services with a guarantee you knowingly cannot fulfill, that is wrong.
In fairness to Matt he did not make the argument definitively, but it is troubling when the person at Google who is in charge of detecting and defeating spam begins to see his job as the battle between right and wrong in the moral sense.
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:
- 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.
- Eric and Avinash are experimenting with being a Fred?
- 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?”
Dang you, Mike Keyes for beating me to the punch on this post!