So the natural thing to do is trim non-performing words and phrases in order to increase the efficiency of your PPC spend.  And that’s exactly what one client did, except rather than increasing his efficiency, he dropped his sales by 30%.

Why?

Because, depending on what you sell, lots of people buy on their second, third, or umpteenth visit to your site, rather than the first visit.  Those visitors are building confidence in you as they move through their buying process.  But most systems don’t (or can’t) track user behavior over multiple visits.   So when those early and middle buying-stage keywords shown up as non-converters, they get cut.

The shame is that not everyone is able to track the following sales drop off, which may not occur for days, weeks, or months, back to the act of cutting those keywords.

Trading away Dennis Rodman as a Non-performing Player?

Would you trade Dennis Rodman for non-performance?  Of course not, right?  Rodman’s defensive stats alone tell the tale.  At his prime, Dennis was pulling down a truly astonishing 18.7 rebounds per game.  For reference, the previous year’s league leader in rebounds (David Robinson) averaged 13 per game.

But if the only stats you looked at involved scoring, you’d get a different picture. Comparing Rodman’s 8-9 points per game against other star players’ 20 or more points per game, you’d likely have been misled into trading Rodman, only to find yourself wondering why you started losing games and everyone else’s scoring stats went up against your team.

Think of your assisting keywords terms as the Dennis Rodman’s of your PPC campaign, except you’ll get all the assists and none of the off-court shenanigan’s.

There’s plenty of other ways myopic analysis can leading you astray

A recent eConsultancy post discusses how Google’s default window for tracking cookies can distort traffic data.  Left in its default cookie window setting, Google Analytics (GA) will classify visitors as “search”-driven traffic for six months following a single search based click through to your site – regardless of how they got to your site previous to that search or how they might arrive at your site following that search. Here’s an example of how this might skew your results:

Let’s say you’re driving traffic to your site via radio ads and that a listener, after hearing your ad, types your url directly into his browser.  Later, he comes back but this time, he types your business name into Google and clicks through on a displayed search result.  Following that, he visits your site three more times via bookmark or directly typing your URL into his site. That’s a total of 5 visits.

Question: How many of those visits would GA classify as search-driven?

Answer: 4 out of 5.

GA would count the first search-based visit and then all of the remaining 3 visits, despite the fact that the following three visits didn’t use search and may have taken place several months after the initial search.  Multiply that by all your visitors/visits, and you can see how your understanding of what drives traffic to your website might be distorted in favor of search. And under the impression that your traffic was mostly generated by search and not, say, your radio ads, you might be tempted to cut them from your ad spend.   Obviously, the same thing could apply with e-mail campaigns, magazine ads, etc.

Bringing Clarity and Orientation to Web Improvement Efforts

Any experienced Web Analyst or Website Optimizer could extend this list of “gotchas” and “classic mistakes” almost indefinitely.  It’s just not that uncommon for an uncareful analysis of data to lead online marketers either to analysis paralysis or sub-optimal optimization strategies.  Is it any wonder that 70% of businesses collecting wed data fail to act on their analytics data?

Obviously this issue has been central to Bryan and Jeffrey Eisenberg’s Web careers since the beginning.  It’s why they helped found the Web Analytics Association; why they published The Marketer’s Common Sense Guide to eMetrics, Call to Action and Always Be Testing; why they created Persuasion Architecture; and ultimately why they’ve built the OnTarget program.

The central theme amongst all of these issues is bringing clarity and actionable insight to Web improvement and online marketing efforts.  They are all answers to the business owner who feels confused or disoriented by the data he’s given and want’s a clear direction toward more sales/conversions and improved website performance.

So, if you find yourself struggling to make sense of your online marketing data, or frustrated by non- or counter-productive optimization efforts, ask yourself: are you giving credit where it’s deserved?  Or do you need help achieving greater clarity and actionable insight from your optimization efforts?

1) Where are they entering?

Most analytics packages (including Google Analytics) make it easy to view your top landing pages.  If you haven’t checked this before you might be surprised at the number of visitors who aren’t entering your site through the home page.  That can be crucial information.

Maybe your PPC landing pages don’t provide all the information visitors need and you’re not giving visitors clear links back to your main site.  Maybe your UVP is only clearly explained on the home page, so that someone landing on your services (or a product category) page wouldn’t get that info.

But more than all of that, you’re trying to get an understanding of how visitors move through your site and why they take the actions they do, so you’ll need to know visitor entry points.

2) How are they entering?

Your analytics package should let you analyze traffic, breaking visitors down by source: organic search traffic, paid ads, direct traffic, etc.  And for organic and paid search, you should be able to see what keywords brought the majority of your visitors to your website.  From this information, you should be able to get a sense of the following:

• What are their expectations? Given your visitors’ traffic source and keywords, what are they looking for?  What would they most expect to find when they land on your website?  What scent are they following?

• What are their likely goals? The same key word search could easily be used by people with differing goals.  Chances are you might be ignoring all but one of them.  For instance, I could be searching on “Pensacola Day Spas” because I wanted to buy a gift certificate for my wife.   Whereas my wife might search the same term to see if they take last-minute or walk-in appointments.  Or maybe she’s searching  to see if they have a specific treatment?  The point is, it helps to mentally force yourself to brainstorm as many real-world behind the search terms as possible.

• What do they already know? Someone searching on your name or on the name of a specific service or product line obviously knows more than a visitor entering from a general search term.  Use your keyword knowledge to get a sense of visitors’ differing stages of the buying process?   Are they just starting out and searching for general info?  Do they already know exactly what they want?  Or are they somewhere in between?

• How well is your landing page matching up with visitor expectations and goals? Would visitors find their keywords on their entrance pages?  Would they know that they are in the right place, based on a 7-second scan of the page?  Do your entry pages have high bounce rates?  What is the average time spent on the page?

3) Next-page navigation – where are they going when they first hit your Website?

Now that you know where visitors are entering your site and you have a sense of their motivation upon arriving at your site, take a look at where they navigate to upon their arrival.  What are the most popular next pages? Look at this information while looking at the actual landing page.

• Are the most popular “next pages” the same ones you would have guessed?

• Are they pages linked to by prominent calls to action or embedded links placed within the active window? Or are they pages only accessible through your top or side navigation?

• What questions would those pages answer for the visitor?  Why do you think the visitor is moving to those pages? Is that action congruent with what you’ve seen of visitor motivation from their keywords/scent?

After you see what those most popular next pages are, click through to them within your analytics package and see where visitors are going from that next page.  If the majority of entering traffic (for a given page) is clicking through to a couple of different pages, you’ll often find that visitors navigate to the remaining popular pages following their first click.  You should start to see patterns forming – key, or most navigated to, pages will stand out.

Watch out for situations where your most persuasive content is NOT one of those most navigated pages; you can’t persuade visitors with content they never see.  Also, watch out for situations where one of your most navigated pages are also exit points, in those cases the visitor either lost confidence or didn’t find what they were looking for.

4) Where (and Why) are they leaving?

First, let’s talk about the difference between bounce rate and exit rate. A bounce is sort of like it sounds, someone came in on a given page and left on that same page without going anywhere else on the site.  Unless visitors are also converting on that same page, bouncing is bad.  It means visitors are rejecting you – either because you are attracting the wrong visitors, or because your landing pages are not re-assuring them that they are in the right place to find what they came looking for.

An exit rate simply tells you how many of the people who came to that page also left your site from that page, including both people entering the site on that page AND people navigating to that page from somewhere else on your website.

• Planned and unplanned exits. Some exits are good.  You expect people to leave your site after buying something/filling in a lead form.  Customers who log-into a registered user domain from your home page will likely show up in your analytics as a bounce.  Etc.  But you obviously don’t want customers to leave before reaching their goal or your goal.  Often you’ll find visitors exiting from pages containing your conversion beacons – product pages containing the “add to cart” button, service pages containing your lead form, etc.  Or you’ll see cart/form abandonment, where visitors start to convert and then back out.

• Take a look at “time on page” for the conversion beacons. Abandoning a page after a few seconds isn’t the same as dropping it after a few minutes.  A few seconds means it was the wrong product or service for them.  Someone leaving your page after a few minutes engaged with your content and never got the answers to their questions and/or simply didn’t have the confidence to buy.  Take a look at the page itself, what information are you not giving them?  Are you using great photos, persuasive copy, points of action assurances, risk reversals, etc. in order to instill buyer confidence?  What about shipping information?  Most of the exits on both this page and the cart page are caused by inadequate information and content on these conversion beacon pages.

• Page prior and broken scent? If you find a high exit rate page, look at the most popular entry paths to that page.  Look for mismatches between expectations in moving from the prior page to the exit page.  What were visitors hoping to find on that exit page and what did they actually find?  Was the hyperlink misleading or was the content simply anemic?  Try to figure out the Piss-Off Factor.

5) Form a hypothesis and test

Completing steps 1-4 should have shown you several mismatches between what you and/or your visitor expected and wanted to happen vs. what actually happened.  You should also be able to come up with some pretty good theories for why these mismatches are happening and what might fix them.  Even better, you should have a strong idea about what success would look like if your tested theory proves true.  In other words, you know what metrics are indicating a problem, so you know what metrics you should see change.  Congratulations, you’ve now made your analytics actionable.

Here are some further tips to help keep you going down the right path:

• Don’t test randomly - always test with a hypothesis regarding visitor motivation/behavior.  You’re after insight as much as lift – a “negative” test that gives you a better idea of what motivates your visitor is     actually better for your long-term success than a positive test that provides little or no new insight.

• The difference between micro-conversion vs. macro-conversion. Testing a page variable that reduces bounce rate and/or moves more people to a key persuasive page may or may not immediately impact your conversion rate, as you may be moving people down a funnel that’s leaking somewhere else.  Or maybe you’re engaging early stage buyers that won’t convert for another month or so.

• Know when to test for micro-conversions, such as moving from one page to the next; when to test for macro-conversions, as in how much bottom-line impact this change made; and when to set-up a secondary, earlier-stage conversion, such as signing for the newsletter or downloading a white paper vs. buying or filling out a lead form.

Bonus step – answer their questions, manage their anxiety, stoke their imagination.

When looking at a page in terms of visitor behavior and motivation, always ask yourself how well that page is answering visitor questions, how well it is re-assuring them emotionally that they are in the right place and on the right track to accomplish their goal, and finally how well it is appealing to their real desires.

P.S.  A quick note on how to integrate “best practices” into your optimization efforts.  Rather than blindly testing best practices, allow your knowledge of them to help you form theories about why visitors are or are not taking a certain action.  For instance, it’s a best practice to place your calls to action within the active window.  If your main call to action is in a side-bar and almost no visitors are taking that action, you might test moving your CTA into the active window.  For some fabulous books on best practices and testing, take a look at Call to Action and Always Be Testing.

P.P.S. If you enjoyed this post please consider Tweeting it please.

[Editor's note: the author of this post is now blogging at jeffsextonwrites.com]

Here are other apps besides OnTarget that are using Google Analytics’ Data Export API.

Here is OnTarget for Google Analytics:

OnTarget provides full optimization, testing, and improvement cycle recommendations on how to improve goals online and increase conversions from marketing campaigns. Clients determine how many resources can be devoted towards optimization each month. FutureNow’s analysts deliver a to-do list of suggested improvements matched to client goals via the OnTarget interface. These changes are tracked using Google Analytics and the impact is fed directly into the next round of ensuing recommendation.

We’ll be announcing lots of cool new features and soon you’ll see specialized OnTarget for Retail and OnTarget for Lead Geneartion products. Just stay tuned…same bat time..same bat channel.

2. Google Analytics also announces the availability of a read-only API to their application. Several customer examples of applications built on this API are announced, including FutureNow’s OnTarget for Google Analytics. We can now leverage customer’s Google Analytics tags and bring in the data into OnTarget where our analysts can provide you your to-do list of conversion improvements.

3. According to the Silicon Alley Insider the U.S. now has almost as many paid bloggers as lawyers. As my friend David Cross asks “what do you call 10 bloggers at the bottom of a lake?”

4. Interesting analysis of why these twelve major brands that will disappear by the end of 2010.

5. In March 2009, Business.com completed an analytics study of more than 27,000 B2B web sites. It’s a great study and well worth downloading.

6. Fivesecondtest is a simple online usability test that helps you identify the most prominent elements of your user interfaces that we stumbled upon last week. It’s enlightening to do a few tests yourself to see how little about a website you can gather in just five seconds. I am not sure it compares favorably to other forms of usability testing.

Get the most out of your Google Analytics with this collection of links to implement, configure and get insights from Google Analytics. * Last updated 6/10/09.

Initial Setup of Google Analytics

Google Analytics Setup Checklist

* Google Analytics IQ Lessons from Google’s Conversion University with videos

A Video Tutorial to Google Analytics Setup

Google’s Support Installation Guide

How to speed up your website when using Google Analytics

8 Stupid Things Webmasters Do To Mess Up Their Analytics

How to Link Google Analytics to your AdWords Account

Click here to view the embedded video.

Video: How to Setup Google Analytics with Flash

Google Analytics within Flex/Flash Applications

Tools to Be Sure Your Website Is Tagged Properly

SiteScan for Google Analytics

Web Analytics Solution Profiler

Firebug Plugin for Firefox

Create and Configure Multiple Profiles

Exclude Internal Traffic the Easy Way

How to Use Google Analytics Filters to Create Profiles

To Meet and Exceed Your Goals, You Must Have Them Set Up

How to setup Goal Tracking

Why It Is Important to Monetize Your Goals

How to Setup Ecommerce & Lead Tracking

Video: Tracking Ecommerce with Google Analytics

Click here to view the embedded video.

How Google Analytics Ecommerce Tracking Works

Installation & Setup of Ecommerce Tracking

Tracking Lead Gen Forms

Google Analytics Variable List

Tracking Conversion across Multiple Domains

Call Tracking in Google Analytics White Paper

* How To Track Wordpress Signups and Comments With Google Analytics

Working With Filters

Matching Specific Transactions to Specific Keywords

Intro to GA Regular Expressions

Video: How to Setup Google Analytics Filters for Better Traffic Reports

Click here to view the embedded video.

Make Internal Search Work For You

Click here to view the embedded video.

5 Easy Steps to Enable Google Analytics Site Search Tracking

Google’s How do I set up Site Search for my profile?

Track How Often a Link on Your Website is Clicked

How To Track Internal Links in Google Analytics

Tracking UI Level Links: An Open Source Script

How to Setup Google Analytics Campaign Tracking

A 4 Step Approach to Google Analytics Campaign Tracking

Twitter and Google Analytics: What to Track

Adding Twitter Search to Google Analytics

Tracking Universal Search results

How to Make Reports More Accurate

How to Maximize Google Analytics Site Overlay Tool

Decrease Bounce Rate by Using target=”_blank” on External Links

Google Analytics Reports

Video: Google Analytics Dashboard: Measure Your Web Site’s Success

Click here to view the embedded video.

How to view Google Analytics Funnels for Segmented Data

Find Poor Performing Campaigns and Keywords

Click here to view the embedded video.

Google Analytics Benchmarking: How do you Compare?

Have Your Reports Emailed to You

Google Analytics Motion Charts Overview with a PPC Example

Setup Advanced Segments

Video: Creating Custom Reports

*Find Out When Your Campaigns Suck with GA Custom Reports

*Video Tutorial: Hacking Google Analytics for Keyword Research

Get More Out of Google Analytics With Plugins & Hacks

The Ultimate Google Analytics Plugins, Hacks & Tricks Collection

The Complete Google Analytics Power User Guide

[Editor's note: the author of this post is now blogging at bryaneisenberg.com]

- Elaine in the movie Airplane

Does looking at an instrumentation panel like this (picture on the left) create feelings of information overload? It does for most non-pilots I know.

Pilots on the other hand, quickly identify the primary flight gauges and navigation equipment.  They know what’s immediately important for flying the plane, and can scan across multiple gauges (rather than fixating on one or two of them) to develop a “big picture” of what the plane is actually doing.

Even more importantly, when they make a control input (like adding power), they know where to look to verify its intended effect (e.g., altimeter and airspeed).

Web Optimization is a lot like that.

Emotionally, many business owners experience that exact sense of information overload when looking at traditional Web Analytics.  No one has taught them how to assemble a composite picture of visitor behavior – what measurements to look for first, what to look at in combination, and how to verify that website changes worked as expected.

Flying blind becomes the inevitable result.

Yet rather than looking for a pilot or investing in flying lessons, many business owners buy into optimization efforts based on sophisticated data gathering capabilities and overly complex testing methodologies.

Why would they do that when they need more actionable insight and situational awareness, and not more gauges to look at?

Because flight instructors are in short supply.  And because this kind of sense making, as a so-called “soft skill,” has always been a more difficult sell than hard-core data collection and taguchi testing.

But those interesting in learning to fly their web optimization efforts have a viable option:  Follow Bryan Eisenberg’s free Webinars and get free flight lessons each month.

On January 15th, Bryan and Jim Sterne (considered the godfather of web analytics) will cover specific techniques to get a composite picture of visitor flow and the importance of looking at analytics through the lens of visitor intent.  Consider it a first, free flight lesson that can be followed up with Bryan’s recorded Webinars.

And for those that want more, I’d invite you to check out FutureNow’s OnTarget product as an affordable way to hire an “on demand” flight instructor for your web optimization efforts.

And Tom isn’t alone in considering Michael Lewis’s sports writing to be a hidden treasure; just look at this marketing-based analysis of his book,  Money Ball.  But Tom Peters has been alone in recognizing the business applications of Michael Lewis’s astonishing article on the surprising innovation and success of Texas Tech Football, written no less than three years ago.

Click here to view the embedded video.

Action & Tempo:

“…[Coach Leach] had been harping on tempo all week: he thinks the team that wins is the team that moves fastest, and the team that moves fastest is the team that wants to. He believes that both failure and success slow players down, unless they will themselves not to slow down. ‘When they fail, they become frustrated,’ he says. ‘When they have success, they want to become the thinking-man’s football team. They start having these quilting bees, these little bridge parties at the line of scrimmage.’”

You have to learn by implementing, and it’s incredibly advantageous if you work hard to keep your testing tempo as fast and continuous as possible.  Theory and intuition are great at helping you figure out what to test, what to look for in your analytics, and how to interpret your data, but untested assumptions can kill you.  If you think that customers would respond well to X, figure out an easy-to-implement test to confirm or disprove that.  The last thing you want to do is let your website sit static for months while you plan a major change based off of faulty assumptions about the market and/or customer motivations.

Plus, even if you have a brilliant plan to improve your website, it won’t help you until you’ve actually implemented the changes.  So a fast cycle of smaller tests and changes not only keeps you safer by verifying assumptions and improving learning, but successful tests implemented early can pay off during the time you would have wasted staging a larger “batch” of changes.

In a similar manner, Texas Tech is well aware of the “opportunity costs” involved in not keeping their offensive op-tempo as high as possible:

“An idea about the use of football time was being challenged. The typical football offense seeks to eat up as much of it as it can. The Texas Tech offense, which at that point in the season had passed for more touchdowns than any team in the country, uses just a shade over two minutes on each drive. But speeding everything up has a curious effect on game time. A typical college football team runs 65 to 75 offensive plays a game. Texas Tech tries to run 90 – and sometimes does. A college team with a robust passing game might throw the football 35 times a game; at this point, 8 games into an 11-game regular season, the Red Raiders were averaging 53 passes a game.”

Preferring batch implementation of changes and tests is kind of luck holding onto the football to control the clock – you’re wasting opportunities to move the ball down the field and score.  Yet most companies, like most traditional football offensive teams, don’t have Texas Tech’s sense of urgency; they don’t understand the often substantial opportunity costs involved.  Here’s a real life example:

I presented a client with a lead generation website for a considered purchase with a Persuasive Scenario Analysis towards the end of August.   As part of that report, I also presented a prioritized list of “most likely to generate dramatic improvement” changes/tests.  And among those suggested tests, I predicted that the easiest to implement change that was also most likely to produce immediate results was to prominently display the company’s phone number within their banner.

About 1.5 weeks ago they finally made that change (along with several others) and went from getting 0 calls from their website each week to 20 calls in the first full week they had stats for the revised website.  One of those 20 calls converted into a sale.  Most sales average in at $20,000 to $30,000.

Now, I’m hesitant to put too much weight on only one week’s worth of results, but even conservatively downgrading those figures still results in a significant opportunity cost for NOT implementing that change right away.

Orientation

“Leach made his way to the sideline and from his back pocket pulled a crumpled piece of paper with the notations for dozens of plays typed on it, along with a red pen. When a play doesn’t work, he puts an X next to it. When a play works well, he draws a circle beside it – “to remind myself to run it again.” But at the start of a game, he’s unsure what’s going to work…

The Red Raiders trotted off the field at halftime with a lead, but not a large one: 14-10. A disappointing half, yet with hidden value. For 40 plays Leach’s offense had groped – digressing, probing to learn something new – and it had been useful to see how the empty spaces on the field shifted. Coach and quarterback now knew what they wanted to know about the A.&M. defense.  They had paid for the knowledge with time, but time means less to them than it does to any other offense in the land. A half to the Texas Tech offense is as good as a full game to most. The game within the game was about to begin…

In the five full years Leach has coached Texas Tech, four or five times each season the team has flopped around ineffectually for the first third or so of a game before racing off to score touchdowns at a rate unheard of in organized tackle football. It’s as if his opponent’s defense has some deep dark secret that takes time for his offense to extract.”

Action isn’t good enough if you’re just throwing stuff against the wall and not learning from it by reinforcing your successes and killing your failures.  Coach Leach doesn’t just know that this play worked and this play didn’t, he also seeks to understand why, so that he and his quarterback can adjust their overall strategy accordingly.  Once the Raiders have correctly sized up their opponents, that’s when the real scoring opportunities begin to appear.  Here’s what that looks like in the game Michael Lewis was describing:

“Leach had just a few minutes with Hodges, but he told him what he had noticed. First, the A.&M. cornerbacks were disguising their intentions. They were lining up as if to cover the fade routes – that is, before the play began, they stood between the receiver and the sidelines – but then, just as the ball was snapped, they were scampering back into the middle of the field. To Hodges it looked as if fade routes would be covered, so he had been sending his receivers on slants into the middle of the field. ‘Throw the fade,’ Leach said. ‘It doesn’t look like it’s there, but it is.’

The other glaring opportunity, to Leach’s mind, was A.&M.’s response to Tech’s formations. On the few occasions when Texas Tech lined up in a formation that suggested a running play, with two running backs, the Aggies ’put their ears back and stop the run.’ But when Tech was, as it preferred, in its passing formation, A.&M.’s fear of the pass caused them to leave huge empty spaces to run in. In the second half, the Tech running backs would be charging into pass coverage, and the Tech receivers would be running toward the sidelines.

There was one other thing Leach had noticed – and Hodges had noticed it, too. The A.&M. front line appeared tired. ‘The minute you see the defensive line bent over and their hands on their hips,’ Hodges told me, ‘that’s when you know you have them.’ The A.&M. linemen were a lot bigger than the Texas Tech linemen. They may or may not have been fatter – Leach insists they were – but their bodies were clearly designed for a different sort of football game than this frenetic one. ‘That’s the risk of playing 330-pound guys,’ Leach said later. ‘You get good push, but if you got to run around a lot, you get tired.’”

The problem with most companies is that even when they do run A/B and multivariate tests, they’re often just testing random variables or best practices, which means they have no basis for interpreting the results in terms of a larger ‘game strategy.’ If you only know that headline “A” outperformed headline “B” without understanding WHY headline “A” worked best, it would be like Coach Leach only knowing that play X worked and play Y didn’t without seeing the larger patterns or flaws in his opponents defense and without being able to exploit that during the second half.

Here’s a practical web example of this principle taken from Microsoft’s Experimentation Platform blog.  The post in question features three separate A/B tests and the second test of two different site search bars is a perfect example of how the WHY is so crucial.  But first, here are the two search bar designs:

Which one worked better?  Neither: the results were statistically negligible.  Now, if that’s all that you took away from that test, you’d have lost out.  But if you started the tests with some hypothesis about why one design might work better, you could follow up with goal scoring, revised search bar.

For instance, most people would find the search area of Option A much more inviting because it’s more spacious.  Plus, the “Popular Searches” is labeled as such in Option A whereas it’s something of a disconcerting mystery in Option B.

On the other hand, Option B does one very important thing right, that Option A doesn’t: it labels with strong verbs!  Rather than guessing that the magnifying glass means “search,” I can look at the big green button and instantly know that clicking on it will start my search.  That one is kind of a no-brainer, actually, especially since Steve Krug has rather famously taught that search buttons should either say “Search” or “Go.”

If you started with those assumptions, you might have actually created an Option C that combined the best elements of both features.  Something like this:

And then I’d be willing to bet rather heavily that you’d come up with a very clear winner. But if you simply threw Options A and B up in a simple split test and accepted the results without thinking about them, you’d never get to an improved search bar.

So how can you more consistently move past a “best practices” or a “let’s test everything” approach to Website optimization?  What kind of methodology will let you advance beyond page-level optimization to Website-wide conversion improvement?

Well, while that subject definitely builds on what we’ve just discussed, it’s also worthy of a post in itself, so make sure to subscribe to get Part II as soon as it comes out.

25 Web Form Optimization Tips – Covers most of the basics, a good reminder.

Usability of Toilet Paper – who could resist this analysis, especially as my friend David Dalka reminded me – P&G said at a search conference, no one would ever blog about toilet paper. Should it be bottom up or top down?

If you are so inclined you can read the review on the new book “The Toilet Paper Entrepreneur.”

Does your blogging move people? My buddy Mitch Joel explores the BuzzLogic/JupiterResearch study finds blogs influence purchase behavior. I had the pleasure of meeting Sandra Ponce de León, Senior Director of Marketing of BuzzLogic, right before she presented this at the recent eMetrics Summit.

Google Notes – a new plugin to add business data to Google Analytics data. I did add it to The Ultimate Google Analytics Plugins, Hacks & Tricks Collection.

Happy Halloween! Feel free to share some very interesting posts below in the comments (but please be considerate of our readers).

*Custom reports* enable customers to create their own reports with the metrics they want to compare organized in the way they want to see it. You no longer have to look at the standard reports and using drag and drop you choose the data you want to analyze on your report. Avinash likes to calls these “micro-ecosystems.” The entire company can get one report with just the custom metrics the key groups in your organizations care about.

http://www.youtube.com/watch?v=NGgl137×3Yw

*Advanced segmentation* enables customers to isolate and analyze unlimited subsets of their traffic. They can select from predefined custom segments such as “Paid Traffic” and “Visits with Conversions,” or create their own segments with a flexible, easy-to-use drag and drop segment builder. As you can see in the screenshot below you can see the “values” of your segments on the fly. Never look at data in aggregate again. The key to success in online marketing and web analytics has always been segmentation. Avinash hopes this is the death to standard reports. This will allow you to also do deep dives into the history, without changing tags, no touching code and no popups and just work through this one page feature.

Click here to view the embedded video.

*The application programming interface (API)*, currently in private beta, enables developers to access all of their Google Analytics data and export it for any type of use. Possible uses include integrating information into other data sources, building custom visualizations or interfaces, and conducting offline analysis.

*The updated interface* that was released yesterday for everyone, includes several new features in the administrative interface and a cleaner reporting screen that highlights tools for changing the way reports display data. A new navigation, administrators’ ability to rename accounts and profiles, and account and profile locater functionality are designed to help increase customers’ efficiency and ease of account management.

*Motion Charts* provide advanced but easy-to-use multi-dimensional analysis. Customers can select their own metrics to compare and then view how those metrics interact over time. By animating data, Motion Charts make discovering insights much easier and more obvious than when viewing data in traditional graphs and columns.

Click here to view the embedded video.

*Integration with Google AdSense gives new and existing AdSense publishers access to granular reports that break down AdSense performance by both page and referring site. Armed with this new data about user activity, they can now make more informed decisions on how to improve user experience on their sites and optimize their AdSense units to increase revenue potential.

The aim of this new feature set is to offer customers the flexibility to choose how their data is presented to them and the extensibility to integrate Google Analytics data with their other data sources. These capabilities will help further unlock the potential of both large and smaller website owners to improve visitor interaction with their websites and improve the value of their marketing investments.

More details on the entire new feature set including screen shots and videos demonstrating the new features will be available on the Google Analytics blog: http://analytics.blogspot.com.

If you would like early access to the feature set, please contact us. As Google Analytics Authorized Consultants we can offer a handful of clients to start with these new features and place them on the early release list.