In 2003 we switched up our SEO terminology from marketing ourselves a “web design” company to an “interactive agency.” We had several reasons for this move:

• Less competitive
• Higher quality traffic & leads
• More inclusive than just a “web design” or “web development” company

We’ve done well over the years optimizing for “interactive agency” and have benefited on secondary terms not specifically target till many years later. We weren’t the only agency calling ourself an “interactive agency”, but in 2009 we noticed a decrease in our “interactive agency” referral traffic & lead quality. We started seeing well-respected international competitors move to the term “digital agency.” Internally we started debating should we lead with “digital” or “interactive.” To settle this debate, we turned to Google Trends.

We ran a query on the two terms and yielded these results showing a drop in references made to “interactive agency” and a general increase in references for “digital agency.” Please check it out for yourself.

Using that data as our guidepost we’ve shifted our SEO strategy to focus on “digital agency.” If you are ever in a debate over which keywords are a good fit for your SEO strategy don’t be afraid to rely on Google Trends data.

The web analytic data is in, finally. In a continuation of the last post I’ve gathered the high-level results. I looked at Woopra, Reinvigorate, Quantcast and Google Analytics and here is the 5280 foot view looking at the results between October 1st, 2010 and November 30th, 2010.

I was surprised to see how similar the Page Views worked out, despite the variation in Visitors. I was disappointed that I couldn’t grab a range of date values out of Reinvigorate which explains the NA. Now that I’ve shared the high-level, please go ahead and dig deeper if you’d like. Here is the shared data for the 4 accounts for the month of December 2010.

• Google Analytics
• Woopra
• Reinvigorate (sorry can’t export the data)
• Quantcast

In the next post I’ll follow-up with pros & cons on the 4 systems I’ve looked at.

We get a boatload of questions from our clients when switching or comparing analytics packages and reports. Those questions are easily addressed, but sometimes we come across a real stumper that makes no logical sense and causes use to lose confidence in our analytic packages. For this post, I’m going to pick on Google Analytics.

In a limited test of a particular landing page we received the following results from Google Analytics during the timeframe of February 1st, 2010 and March 17th, 2010.

Aside from being unimpressive; it’s also not trustworthy. (Below) The view of the “conversion funnel” for the same set of data. Note the discrepancy between the number of conversions / forms submitted?

To check our sanity we compared the data to Google Adwords. AdWords reported 5 conversions; ok at least that is consistent with the first graphic. But here is the crux, Google AdWords *should* have been reporting a higher conversion rate because we tested the forms multiple times from several IP addresses. Google Analytics is filtering out our tests based on a few selected IPs, therefore Analytics’ numbers *should* be lower. The second problem is the change in results data from switching views from the “Goal Overview” page to the “Funnel Visualization” page. Why would Google Analytics show 5 in one view and 1 in the other view, using the same data set?

We’re not the only ones struggling with Google Analytics apparent data discrepancies. It’s discouraging that problems like this go unaddressed by Google. I understand the service is free, but Google’s lack of addressing these problems on their forums is exactly why more corporate clients have returned to tools like Webtrends, Woopra, Clickly and Mint.

First off, I’m surprised that there hasn’t been more said about the comparisons between Google Analytics and WebTrends. When Google acquired Urchin back in 2005 and suggested they would be giving the tool away for free, I thought WebTrends would last no more then another 2 years. But I’ve been totally wrong. They’ve still been able to ask for thousands of dollars for the privilege of using their software. I thought it was about time that we really compare these two popular tools and the data they report.

Ok, so Google loses on the matrix of features but let’s go into this a bit deeper.

Bot Traffic: Advantage WebTrends. If you absolutely need to know what bots are hitting your site then go with WebTrends because Google just can’t report that data.

Real-Time Analytics: Big Advantage to WebTrends. Real-time reporting requires investing an a substantial amount of server power. Sure Google has that power but they haven’t put it behind Analytics yet. My guess is you’ll see this in the future but right now the win goes to WebTrends. In my opinion, it’s the sales team that needs to know about real-time visitor activity and there are plenty of tools out there that can do a better job then WebTrends at reporting real-time activity.

Hits: For real? Who still uses this as a metrics and why? Slight Advantage to WebTrends.

Tracking Advertising: This can be accomplished in Google but it’s a bit of a hack to get it working. WebTrends is more eligant in it’s approach towards tracking advertising.

Animated Graphs: Advantage Google. I’m a data visualization junkie and I can easily lose hours working in the visualization tool; however for the majority of marketers this is overkill.

So, how does that data compare?

Total New & Returning Visitors

This data is comparing a 1 year time frame by monthly totals.

Referral Traffic Counts

Six months of data from Jan 1st, 2009 and June 30th, 2009

Page Views

Six months of data from Jan 1st, 2009 and June 30th, 2009

Verdict

To each their own. I personally can’t justify WebTrends to our clients. Google’s feature set is 95% of what is available in WebTrends and the few features that stand out don’t justify the hefty price tag. I’d love to chat with someone who feels WebTrends is superior to Google, I just haven’t found that person yet.

These are not valid metrics of the health of a website. These are numbers that executives like to hang their hats on, and they are shortcuts to thinking and in-depth analysis. I love metrics, no doubt, but it’s time to start telling stories of user-interaction. Hard numbers lack context; and therefore often send poorly informed decision makers down the wrong path. Let’s go over a few of my favorites.

Absolute Unique Visitors
This number is by far the most used metric of site success but it needs to be framed in the context of goals & objectives. Look at the weekly trend below. It’s a capture of our traffic pattern on supportdetails.com. Support Details is a one-page site that captures browser specs and sends them to a targeted contact via email.

Simply showing this graphic and looking at an absolute number doesn’t tell the story of what the users are doing on this site. When this graphic is supported by referral sites, repeat visitor trends and normalized for spikes then the numbers begin to talk.

The numbers are telling me the spikes in traffic have helped to create product awareness, overtime this increased awareness has led to increase usage of Support Details on a regular basis. By utilizing the visualization tools that Google Analytics has to offer the trend becomes pretty apparent.

Pageviews
More pages clicked is counter-intuitive to the rational of a good site
information architecture. So why is it valued as a positive metric? If someone is clicking on more pages it can either mean they aren’t able to find content, or it could mean they are deeply interested in the content. I usually suspect it’s the former.

Bounce Rate
Measured by a visitor coming to one-page of the site, then leaving. This isn’t necessarily an indicator of a problem. It could be a measure of excellent content. If a visitor is searching for information and they find it without clicking around, then wouldn’t this be considered success? When this metric is used in the context of goals, then it becomes important. As a standalone number, it’s a useless metric.

Time on Site
What does this really mean? Does increase time mean the site is difficult to navigate. Is it hard for me to find what I’m looking for, or am I engaged in reading the content. In-depth analysis would compare the objectives of the site, with the type of content, then the average stay on a particular page.

I could continue offering alternative views for just about any of the major metrics, but my point is it’s time to look at the bigger picture. We need to be asking questions rather then looking for shortcuts that make for pretty charts and reports. Dig deep, give real analysis into what’s perceived in reading the numbers; that is were the art & skill of analytics pays off.

I’d like to hear more stories of useless analytics that you’ve encountered. Please share the info.