That said, we still clash with the occasional lonely naysayer, who cites the lack of customized reporting or the limit of only four goals per profile as a reason not to go with Google.

But after today’s announcement from the Google Analytics team, the critics have a lot less to carp about. Clearly, Google has listened to its audience and, in turn, has unveiled some impressive new features that should elicit cheers from even the “power users” (Google’s term for Analytics users who want “fine-grained control over their site tracking and who have a burning desire to understand and manipulate the behavior of Analytics”).

Here’s a quick rundown of what the latest version of Google Analytics brings to the table.

Engagement goals

Once restricted to tracking the loading of specific pages, the Goals report now lets you set customized thresholds for key metrics like Time on Site and Pages Per Visit.

More goals per profile

Ever had to decide which four goals were most important to your site’s success and jettison the rest? Google Analytics now lets you set up to 20 goals per profile—which is a wise move, considering that engagement metrics can now be designated as goal completions.

Improved mobile reporting

Have a mobile-friendly site? A new code snippet (yet to be released) will let you gather data from all web-enabled devices—not just those that support JavaScript.

Advanced table filtering

No one drools over reams of data, but with the addition of Advanced Table Filtering, you can filter thousands of variables in a table according to the specific metrics and percentages that you deem radar-worthy.

Multiple custom variables

You could already track your visitors according to customized segments beyond Google’s preset categories. But with Multiple Custom Variables, you have even more power. Set multiple segments to track according to visitor attributes (are they a member?), session attributes (did they log in?) and page-level attributes (did they view a specific page?) for in-depth reporting with increased flexibility.

Increased sharing

Share a special URL link with anyone who has an Analytics account, and you can automatically import custom templates and segments to their profile.

Automatic intelligence and custom alerts

The above updates are powerful stuff, and most were expected. They’re the necessary culmination of where the market is headed—and what GA users (and detractors) are demanding. But what’s really rousing our interest is the unleashing of Analytics Intelligence. Because more than any other improvement, this one is a potential game changer.

Still in beta, Analytics Intelligence uses an algorithmic-driven engine to automatically record significant shifts in your data and organize them in a new Intelligence report.

Even better, you can customize the major changes that matter to you, and you can use new Custom Alerts to receive automatic notifications with every drastic change. Wondering whether a salacious tweet sent droves of targeted traffic to a goal-centric page? Analytics Intelligence will let you know.

Add to this the option to tweak the level of intensity of your alerts (you can assign a percentage to changes you deem worthwhile—there’s even a nifty slider!) and you’re guaranteed to spend significantly less time sifting through data to see what’s working and what isn’t.

1. If you’re not measuring it, you’re probably losing money. First and foremost, we often find that companies don’t have web analytics at all or, if they do, haven’t installed systems to track essential performance indicators through their entire sales funnel. So technically, they’re using analytics tools, but practically, they’re flying blind—or at least legally blind. And regularly, once we start gathering data, we find that expensive, non-data-driven assumptions are incorrect. For example, we often find that companies spend money on search engine optimization without knowing whether their search results drive qualified traffic. Their “measurement” was simply a visual observation of high ranking. Which brings us to point of failure number two.
2. If you’re measuring the wrong things, you’re probably making the wrong decisions. Another common problem is thinking that you’re measuring effectively just because you’re measuring. In daily life, we usually know what to measure. All else being equal, for example, you’ll buy the shoes that fit. But online, things aren’t so clear, in part because there are so many marketing options, and every business and marketing campaign has different objectives. In part due to this confusion, people tend to measure the most superficial things: whether something looks pretty, has cool functionality, has high search ranking. What’s important is measuring what’s meaningful to your business. After all, pretty, cool shoes are great. But if they’re three sizes too small, you won’t walk very far.
3. If you can’t make your data meaningful, your recommendations are probably meaningless. Too often, and in large part due to the availability of free tools such as Google Analytics, we see companies address issues one and two by gathering lots of data to cover their bases. So, for example, they might create a Google Analytics account and drop the JavaScript code in their footer, thereby capturing a broad spectrum of activity. But without proper analytics installation, configuration and interpretation, this typically results in data overload rather than wisdom. It’s like installing a fire hose to get a drink of water.
4. If you’re spending more on technology than interpretation, you’re probably overwhelmed with data and underwhelmed with insight. The problem of data overload is particularly common in organizations that have over-purchased analytics technology. Carrying large analytics license fees typically means less money for analytics services and human resources. It’s a tough place to be: lots of data, but nobody to make sense of it. Analytics evangelist Avinash Kaushik recommends the 10/90 rule: for every $10 spent on analytics tools, spend $90 on “intelligent resources/analysts.”
5. If your data’s not actionable, it’s probably paralyzing. This is the other end of the spectrum from not measuring anything: measuring too much, including irrelevant details, and having no way to separate signal from noise.  Typically, this happens when organizations recognize point of failure number one, overcompensate with point of failure number four, then find themselves with a morass of data that bogs down rather than enlightens decision-making.

So there you have it. My thoroughly unscientific, entirely anecdotal and experiential analysis of common web analytics failures. Think I missed something? Let me know in the comments.

Yesterday, Google announced a Forrester study, “Appraising Your Investment in Enterprise Web Analytics” (PDF), that helps clarify the situation.

One important finding—particularly for a Google Analytics consulting company like us—is that Forrester recommends spending more money on analytics services than platforms:

Enterprise companies must ask themselves if they are paying too much for capabilities that they simply do not need. In some cases, gaining fewer seldom-used capabilities is a worthwhile tradeoff if funds can be reallocated to hire more resources necessary for analysis.

Also, according to the study, “sixty percent of decision-makers agree that investments in web analytics people are more valuable than investments in web analytics technology.”

Some other interesting findings:

• 53% of enterprises surveyed use a free technology solution as their primary web analytics tool, and 71% use free tools in some way
• 66% of enterprises using a paid tool would consider switching to a free one
• 52% of practitioners fail to effectively use more than half the features of their tools—whether they’re free or paid
• 71% of enterprises surveyed report that web analytics data plays a significant role in decision-making
• Nearly two-thirds of enterprises would abandon their current web analytics provider under the right circumstances

I’m looking forward to digging more deeply into the report, which you can download free by following the link above.

And if your enterprise is considering a switch to—or start with—Google Analytics, or wants to make better use of its current Google Analytics implementation? Let’s talk.