The Words ‘Marketing Automation’ are Like Music To Our Ears

According to one definition:

Marketing automation is the use of software to automate marketing processes such as customer segmentation, customer data integration (CDI), and campaign management. The use of marketing automation makes processes that would otherwise have been performed manually much more efficient, and makes some new processes possible.

In plain English, marketing automation uses data (like your web analytics) to do some of your marketing tasks for you. Herein lies the problem I keep running into: Your decisions and those of your marketing automation platform are only as sound as your data.

I’ve seen marketing automation software that helps your email marketing, your ppc bid management, segmentation and personalization, and others. As Jeff Sexton recently pointed out, if you have the wrong analytics it could cost you 30% of your sales. Can you afford that today?

A few weeks ago we were helping a client optimize her website and we wanted access to her historical data. All she had was the analytics from her marketing automation vendor. Now the fact that you could only access these analytics using Internet Explorer (we are mostly on Macs) was one failure, but the main failure was that it looks like the analytics was an after-thought by the vendor. Anyone can throw up some reports on a screen — but the issue is, do they tell you anything meaningful? There was virtually nothing to make you smarter as a marketer. Today’s smart marketers understand the value of data-driven decisions. Unfortunately, this vendor’s reports provided in an abstract way what happened but did not provide the vital statistics to diagnosis and prescribe any sort of optimization to the company’s efforts.

Marketing Automation Must Make You Smarter Not Lazier

I was talking to friend who is a superstar B2B marketer. He was telling me about this new enterprise PPC bid management software he was evaluating. He deals with thousands and thousands of terms so automating the bidding would be a huge help. He told me about the slick interface and the bidding rules, etc. Then I asked him the question that made him stop like a deer in the headlights.

“Have you checked out the data reporting behind the algorithm? What actionable insights does your ppc automation vendor provide you?”

Of course, vendors will shout “proprietary formula” and we marketers fall for this marketing B.S. We don’t need the complex details behind it but we do need to get a sense of what and how they look at data, keyword attribution, etc. What metrics do they value most? If you fall for the “black box” how do you and the system continue to learn? How do remove it if you are unhappy with the vendor? How do you create your internal best practices unless you have a clear picture into what is happening?

Without good data at the core, you may just end up with a mechanical turk. You need data to share in your organization and data that tells you details of what you’re doing and how to improve it. Also, beware of bad software that takes what you need done and tries to completely automate it. Just because it is automated won’t guarantee it is optimal for the way a good marketer works.

Don’t Forget Your Job Is to Make More Money, Not to Make Your Job Easier

The point of marketing automation is to free you up to do more of what you are really good at by letting the glorified calculator do what it is really good at. Good marketing automation lets you use your insights about your customers in ways you couldn’t before; bad software takes those decisions away and prays that the computer will do it for you. Keep in mind we have created a computer that has barely beaten a great human chess player, despite its intricate and complex algorithm –  and we’re still far off from a computer to beat the best human poker players. Do you really believe that some algorithm is going to be better than you at creative marketing insights?

Without solid data, scientific method and reporting, how does your marketing automation software show you it is making money? Whether or not you are using marketing automation, you still need access to great metrics. In the case of marketing personalization, how do you know if the efforts are working if there aren’t control groups to measure against? How do you control for other external factors?

The Marketing Automation Future, Now

Don’t get me wrong — I am an advocate for marketing automation. But only if there is a core focus on the insight derived from data, not the automation, first. Analytics must be at the foundation and not an afterthought. You can identify first generation automation tools by their focus in on automation first and reports second. Today’s next-generation state-of-the-art tools have to have great metrics and analysis at their core and are focused on helping you optimize your business; that is, making you more money and proving their value to you.

Please feel free to tell me more about your marketing automation love fest or worries.

P.S. Full disclosure: like my good friend and analytics evangelist Avinash Kaushik, I work for and sit on several advisory boards of companies that use data as their foundation for marketing optimization and automation.

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?

Cost Per Visitor (CPV) – How many advertising, marketing, SEO, etc. dollars do you need to spend to bring in each Website visitor you’re getting.   Don’t look at conversion just yet – it’s your website’s job to convert the visitors; marketing’s job is to get them there in the first place.  So Cost Per Visitor is the best starting point for measuring your return on marketing spend.

Also, feel free to break this down by channel: SEO, e-mail marketing, PPC, conventional media, etc.  Some channels are easier to track than others, but give all of them your best shot.  Now plot your CPV performance from the beginning of the year till now and see how you’re doing.

Revenue Per Visitor (RPV) – Top line revenue is usually easier to calculate and track, so we go with RPV, but if you’ve got the metrics to figure out bottom line Profit Per Visitor, all the better.  So basically you’re looking for how much money you are bringing in per Website visitor, and you’re looking to see how this metric is changing from the beginning of the year until now.

CPV should be decreasing and RPV should be increasing

What to do if these metrics aren’t moving in the right direction:

1. Take a look at your marketing spend. What’s working?  What’s not working?  Look at differing channels, keywords, time of day, etc.  Get accountability from the tactics you are using to drive traffic.
2. Focus on improving your conversion rate.  Your Website’s conversion rate can act as a lever to both CPV and RPV.  By examine keywords and marketing campaigns in terms of scent and scent trails, you can improve the performance of your campaigns and drive down CPV.  By improving micro-conversions throughout the buying process, you can increase macro-conversions, average order value, repeat customers, etc – thereby improving RPV.  For tools on how to do this, take a look through our archives, read Always Be Testing (or any of our other books), or give us a call.

Feel free to let us know how you’re doing, or to post any questions you have on these metrics and improvement tactics.  We’d love to hear from you.

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

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]

• The rating system is too clunky. Most people get stuck between 3 and 4, usually with 4 sounding too good and 3 too wishy-washy, meaning that the results are often more indicative of a temporary mood than an honest difference.

• Written answers are almost always more informative than raw numbers and everyone knows it, but they’re rarely asked for.  The words people chose, the way they phrase things, what they actually comment on, what details are mentioned, all add up to a much richer insight into the psychology behind the responses.  They provide context.  But Likert scales are rarely asked in conjunction with written responses and the overwhelming preference is for Likert scales over full responses.

• Numbers are preferred over written answers because they’re easy – and easily averaged.  The reason organizations like Likert surveys is that the results are easily totaled and averaged.  You can express the results with mathematical certainty.  That’s harder to do with written responses.  So most organizations somehow decide that it’s better to be precisely wrong than approximately right.

• The mind provides misleading answers to questions of the heart. Ever noticed how most respectable psychological research “tricks” the participants.  Participants are always told the experimenter is studying or looking for one thing, when it’s really something entirely different.  This indirection is considered necessary so that the participants self-conscious desires and biases don’t taint the results.  Likert-scaled surveys almost never use this technique.  Instead they ask direct questions about participants feelings, actions, and future actions.  And as Coke’s misstep with New Coke proves, the results of these surveys simply can’t be trusted.

• No one bothers to write questions (and answers) in a psychologically astute manner. It usually helps to write questions and the attendant answers so that an honest response will not seem self-incriminating to the participant.  Ask a mom if she feeds her kids a lot of fast food, and you’ll probably get a false answer.  What kind of mom would answer yes?  Ask her if she frequently finds herself strapped for time and looking for food preparation and mealtime shortcuts and then follow that up with a question about the mom’s most used go-to solutions to food prep shortcuts, and you’ll get an entirely different outlook.*  Yet almost no one takes the time to do this with Likert-scaled surveys.  And so they get bullshit answers.  Go figure.

• The results are almost always abused.  Surveys are as easily used to bolster a prejudice or further an agenda as they are to actually shed light on a subject.  Of course, any study can fall prey to this manipulation – if you torture the data long enough, you can get it to confess to anything – but the doubly abstracted nature of Likert survey results are far more easily abused than a compilation of written survey answers.  Want an example of this and most of the previous concerns?

Check out this little work of horror from Marketing Sherpa.  Let’s start with their interpretation of the survey and work backwards from there.  So here’s what they think their survey indicated:

“Two-thirds of marketers who work for organizations that have not used any form of social media marketing or PR consider themselves “very knowledgeable” or “somewhat knowledgeable” about this emerging strategy.  Their overconfidence in unproven ability can doom social media initiatives to failure.”

And what do they base this interpretation on?  A worse-than-normal Likert-scaled survey with only 4 badly worded answers.  Marketing Sherpa didn’t provide the exact question in the post, but it was centered on the respondents’ knowledge of social media marketing for organizations.  At any rate, here are the possible answers:

1. Not knowledgeable at all
2. Not very knowledgeable
3. Somewhat knowledgeable
4. Very knowledgeable

So think about it: you’re a marketer, maybe even specializing in interactive/internet marketing.  You’ve played around enough with social media to be comfortable with its dynamics and to know that most so-called social media experts aren’t, mostly because it’s an emerging field and few can claim legitimately successful social media marketing campaigns for non-entertainment or cutting-edge/sexy companies.  Then again, you know you’re no expert either.  So what do you select?

Not surprisingly 58% of the respondents selected “Somewhat knowledgeable.”  The survey basically forces you into that response unless you want to admit that you’re all but clueless about a rather important and emerging element of online marketing.  Even still, 28% of participants selected “Not very knowledgeable.” My guess is that if Marketing Sherpa had worded the choices more intelligently, avoiding the perception of self-incriminating answers, they would have had even more people falling between “not knowledgeable at all” and “somewhat knowledgeable.”

At any rate, the numbers show that 86% of respondents basically indicated that they are not totally clueless, but they aint all that, either.  Not exactly shocking answers given the question and possible answers.  And yet, this is the basis for Marketing Sherpa’s conclusion that the respondents were dangerously “overconfident.”  Give me a freakin’ break!

The real lessons of this?

Stay away from Likert-scales.  And especially avoid them when you’re trying to gauge people’s perceptions, feelings, ambivalencies, etc.  Do the real intellectual work of crafting intelligent and nuanced essay questions.  Invite open ended responses.  Comb through the answers with eye towards being approximately right rather than precisely wrong.

* Special thanks to the talented Holly Buchanon for sharing the McDonald’s survey example with me.

If you enjoyed this post please consider Tweeting it please.

In fact, whenever I work with B2B and complex sales clients it’s a sure bet their website won’t:

1) Adequately address the multiple decision-makers and influencers involved in securing the lead

If a sales manager needs to justify a training expense to his CEO and CFO, wouldn’t it help to provide your inside champion with messaging and tools to help him make his (read “your”) case?

It’s usually good to have sections of your website and messaging designed specifically for those secondary decision-makers and influencers that need to sign-off on the decision of your inside champion.  As an analogy to the consumer world, would you really want to construct a website that sells engagement rings without providing content and messaging for the prospective fiancee?

2) Have planned (and tracked) conversion points for visitors who are early in the buying process

To keep with the consumer analogy, let’s say you’re considering having a pool put into your back yard.  Assuming that one of your local pool suppliers/installers had a website with valuable early and middle stage content, how many times might you visit their website before actually contacting them and becoming a lead?

• You might come to them early on when doing preliminary research regarding what type of pool you wanted, what size, shape, depth, etc you should look at, what kind of associated expenses and purchases are involved, etc.  Reading this stuff might take 3-5 or even 15 different visits.  How would you know if any of these visits are successful?  How could you measure or get a handle on your Website’s influence on such a buyer?I’d normally suggest having a goal for these types of visitors.  Maybe it’s downloading a pool planning or pools for dummies report/PDF.  Maybe it’s playing with an interactive pool builder or pool cost calculator.  Whatever it is, having a trackable (and helpful) event for these early stage buyers helps to track your Website’s success in attracting and engaging

• Moving to the middle stage of the buying process, you might touch the site again when you are closer to buying and constructing a short list of potential contractors/installers.  This time you might drill down into why you should do business with them and not someone else, reading up on their installation timelines, the skill of their install crew, etc.You may or may not feel like filling out a lead form at this point.  But a valuable and well-merchandised free download titled something like, “10 Questions to Ask Any Pool Contractor,” might look far more attractive to you – especially if you only had to provide a name and e-mail (rather than the lead forms more detailed info requests) to get it.

• And then at the late stage of your buying process you might look at the site a third time to fill out the form or get the phone number to actually buy the pool. What a waste if the pool website only had the lead form as a conversion point, without ever providing (let alone tracking) any of the early and middle stage downloads and conversion events.  Questions would go unanswered, and prospective buyers would go unengaged / go somewhere else.

Needless to say, the exact same patterns of behavior occur for B2B sites as well.  And yet most B2B sites don’t have defined content and conversion points for their early and middle stage visitors.  Your prospective leads are going to go somewhere to get their questions answered, shouldn’t it be on your website not your competitors?

3)  Have metrics/analytics capable of tracking visitor behavior over multiple visits.

While early and middle stage conversion points help a Web analyst/website optimizer get a better handle on a sites overall success in engaging early and middle stage buyers, it still leaves them guessing at the big picture, simply because they can’t track a lead generation or sale all the way back to that prospect’s first visit to the Website.  This can be crucial for gauging the real success of a PPC campaign.  Key words that might look unprofitable (because they target earlier stage buyers) might be spectacularly profitable – but only after the 8th (or 20th) visit to the site.  Unfortunately, if you can’t track visitor behavior over multiple visits, it’s difficult to get a handle on real – vs. false- measures of keyword performance.

While I love, love, love Google Analytics / Google Ad Words, this is exactly one of these tools shortcomings.  And it’s one reason that we insist that our OnTarget clients install our software in addition to GA/GWO: OnTarget can bracket visitor behavior through keyword entry and track individual visit behavior over multiple visits.  It’s a wish-list come true for us Future Now Persuasion Architects and can be a positive boon for our On Target clients.

So there you have it: start matching your B2B and complex sale website to the real complexity of your sale.  I’ll be writing follow-up posts with exercises and steps on how to do this, but in the meantime, would it be too forward of me to suggest you sign up for On Target?

- 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.

• Established his own (very successful) ad agency
• Launched the Dodge and Chrysler brands
• Hired and mentored Leo Burnett, creator of the Marlboro Man, Tony the Tiger, Pillsbury Doughboy, and many other advertising icons that made his clients rich
• Turned positioning into a fine art form half a century before Ries and Trout even coined the term.
• Helped establish Cadillac’s pre-eminence among early automotive marks
• Wrote “The greatest ad of all time,” as voted in 1949 – an ad still listed in the top 50 of Ad Ages Top 100 Advertising Campaigns.

Interesting, but why should you care?  Because MacManus’s – and by extension Burnett’s – approach was the yin to Hopkins’ yang, and because MacManus’s approach still works today.

And what was that approach?

In a word, it was to position the client while dethroning competitors in the minds’ of the audience. He wanted to create, in the mind of the public, a deep-seated prejudice towards his client’s brand.

If, in the words of the legendary Gary Halbert, the biggest key to success is to sell to a starving crowd, then MacManus aimed to persuade the consumer that only his client’s product would fully cure their hunger, and then wait for the more-cheaply-persuaded and much larger mass audience to get hungry as their individual circumstances dictated.  This would be in contrast to targeting only hungry people and then selling to them via direct mail.

And so the two poles of advertising continue on to this day, as is clearly seen in the following comments by an extraordinarily successful brand builder, Chris Maddock.  Chris was responding to my request for his opinion on Google’s recent attempt to track the effect of offline advertising upon online sales/conversions.   Here’s what he had to say:

Jeff,

I think Google’s traditional ad analytics are interesting, sexy, and certainly useful on some level.  But I think the program could also be dangerous, in that it could give some folks faulty impressions of what is actually happening – or what is right – because it assumes advertisers know things they probably don’t.

Let’s say a local hardware store runs some print ads, and compares the online response to another time they’ve run radio ads.  If the print ads were for a short term offer, and the radio ad of a more institutional bent, the print ad could drive more traffic to the website and have the hardware store owner thinking that print’s the ticket.  The reality in such a situation is that the print advertising is impressing and motivating a tiny, albeit palpable, percentage of the market to respond and go the the website, while the time-sensitive nature of the offer makes the advertising all but invisible to the bulk of the market.  On the other hand the radio advertising is likely creating greater long-term top of mind awareness, yet probably not motivating as many to go the website.  Mr. Hardware likely thinks that the radio campaign was less effective, when in fact most category dominant businesses are those that eschew short-term sales, offers, promotions and the advertising tools that make them work, while leaning on intrusive media such as radio and television to push long-term awareness.  Over time, radio could likely drive many more visitors to the website – visitors who will likely buy.

So my worry is admittedly Hamiltonian.  Years of interaction with average business owners and traditional ad people has revealed a startling blindness to things like buying cycles, differences in long and short-term strategy, and proper media selection.

So these new Google analytics are cool.  I just hope the good people using them understand what they’re trying to make happen, and what the numbers returned really mean.

-    Chris

Do you see how Chris picks up the standard of Theodore McManus, Leo Burnett, and Roy Williams?  Although I think it is possible to intelligently and rigorously compare media, I can’t help but agree with Chris’s larger point.  Creating a prejudice in the mind of the customer before they’re hungry is often a more effective strategy than trying to only target hungry customers.*   But it requires a longer time horizon.  So if you are only measuring on the short term, you’ll likely come to the opposite conclusion and then deem your position to be “scientific.”  It’s a perfect example of one of the deadly sins of Web Analytics.

So what’s your time horizon?  And have you implemented a measuring/analytics system that will enable you to measure accordingly?

* To be fair, there are certainly also times when it pays to directly target hungry customers, rather than engage in a lengthier branding campaign.  I’m not necessarily advocating one over the other; I’m arguing that you shouldn’t base your decision on skewed metrics.

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.

(*post updated 6/18/09)

1. Social Media Metrics Greasemonkey Plugin For Google Analytics – it pulls the social media metrics right into Google Analytics Content Detail reports automatically, with links to the social media sites for your pages. It pulls in data from Digg, Sphinn, Mixx, Reddit, StumbleUpon, and Del.icio.us, with more to come.

2. The Google Analytics Report Enhancer – Get enhanced segmentation, you will also be able to segment by transaction, adgroup, and referral path anytime a segmenting opportunity comes up. Now you can see exactly which transactions are attributed to each source, medium, source/medium, keyword, campaign, new or returning visitors, and more. You also get the ability to see the raw number of conversions for each goal you have as well as goal revenue.

3. Google Analytics hacks to obtaining full referring URLs – Provides two ways to get full referring urls into Google Analytics.

4. Multiple Profile Greasemonkey Script – If you have multiple profiles setup for your google analytics account, you will be able to select a new profile to view you will see the same report you were just on, but it will be for the new profile which you selected. Also, if you wish to compare reports from two profiles, there is an option to view the new profile in a separate tab.

5. Unusual Keyword Trends in Google Analytics With Greasemonkey – provides a “What’s Changed” report which tells a) which referrers have sent most traffic in last few days and b) which have sent most traffic where they never did before.

6. Google Website Optimizer multivariate experiment data to show up in Google Analytics – While Google Website Optimizer by itself can give you a quick look at which combination is best at improving conversion, it tells you nothing about transactions, revenue, micro-conversions, navigation, segmentation by source, and bounce rate. If you integrate Google Analytics into your Google Website Optimizer experiments, you will get much richer data, and be able to get a true idea of how your test is doing.

7. Google Analytics for Wordpress – This plugin easily adds your Google Analytics tracking code (the new ga.js one!) to all pages within your blog. This plugin adds the possibility to tag and segment all outgoing links, so you can see whether a click came from a comment or an article. This WordPress plugin also gives you the possibility to track downloads with Google Analytics based on a set of extensions you specify and adds the possibility to track all image searches as organic and collect their keywords.

8. SiteScan – A Google Analytics Diagnostic tool designed to provide you with a complete audit of your Google Analytics setup. SiteScan is a free way to ensure that your Google Analytics is configured properly on your website. The most comprehensive web analytics debugger is the WASP Firefox extension.

9. Goal Copy Extension – The Goal Copy extension records all of the values in a Google Analytics Goal Settings form. You can then navigate to another profile where you want to put that copied goal and paste all of those values into the new form. That way, you can get your goals from one profile to another without all the tedium.

10. The Unofficial Google Analytics API – Uses Google’s email as XML function to send your data to Google Groups so you can use the data. There is also the Google Analytics Python API.

11. Google Analytics to Google Docs Greasemonkey Script – do a one-click export to create a Google spreadsheet for analyzing Google Analytics data.

12. Get Detailed PPC Keyword Data from Google Analytics – This filter shows exactly the Search Term (i.e. keywords that are searched on) rather than just the Bid Term (i.e. the keywords that triggered a PPC advert). For example, if a visitor searches for “sony digital camera” and you have an ad configured for the keywords “digital camera” as a Broad Match in Google AdWords. With this filter the same search will show “digital camera, (sony+digital+camera)” in any Google Analytics report that shows keywords (e.g. Marketing Optimization -> Search Engine Marketing -> Overall Keyword Conversion) or any time you cross-segment against keywords.

13. Analytics KPI gadget for iGoogle – This widget allows you to see important KPI information from Google Analytics directly in iGoogle.

14. Google Analytics Reporting Suite – Using Adobe Air the Google Analytics Reporting Suite brings Google Analytics to the desktop.

15. Customize the list of recognized search engines – Adds 60+ additional search engines for detection (rather than listed as a referrer) and differentiates regional variations e.g. google.co.uk, google.com, msn.se etc.

16. Script to capture first and last referrer in Google Analytics – From my friend, Brian Clifton’s book Advanced Web Metrics with Google Analytics.

17. Excluding Internal Traffic the Easy Way – Make sure your data isn’t polluted with your own or your company’s clicks.

18. Tracking Your Twitter Tweets with Google Analytics – This method will track anyone visiting the site as a result of your tweet, regardless of where they clicked on the URL. It doesn’t matter if it’s in an email client, hosted email app. etc.

19. The Official Google Analytics blog – Get the latest from the Google Analytics team. They also publish the excellent Conversion University.

20. Google Analytics Help Center – The official forum to get your questions answered about Google Analytics.

21. Google Analytics for iPhone – Access your Google analytics on your iPhone.

22. Google Analytics Notes – Keep track of events by adding notes directly into Google Analytics.

23. Better Google Analytics Firefox extension – This wraps up several scripts into one. This super-script will allow you to:

• Auto press the “Access Analytics” button, if it is displayed
• Remembers settings you set when you switch between profiles, and allows you to open another profile in a new tab quickly.
• Allows you to export any report available as CSV to Google Spreadsheets.
• Converts percent values to absolute values in tables.
• Provides one-click access to year-over-year reports in Google Analytics.
• Sorts the visible table rows.
• and Adds Digg, Sphinn, Mixx, Reddit, StumbleUpon, Del.icio.us, and Yahoo InLink Metrics to your content detail reports.

24. The Enhanced Google Analytics Firefox Plugin – is designed to allow analysts to get more action out of what changed in the Referring Sites and Keyword Reports.

25. Kampyle/Google Analytics Mashup – this plugin allows you to incorporate the feedback you get from using Kampyle on your website (you need account for both) and integrate it with your Google Analytics.

26. Excellent Analytics is a simple Excel plug in that lets you import web analytics data from Google Analytics in to an Excel spreadsheet.

Please help me maintain this list as the one place to find all the Google Analytics plugins, hacks and tricks. Do you know of any others that should be on the list?

I was responsible for the performance of those sites, and I was the de facto “web analytics guy” within my company.  But I wasn’t a full-time Web Analyst, and I had lots of other strategic and operational things to do.

Sound familiar?

When I did look at my web analytics, I often skimmed the information contained in my default “dashboard,” and rarely dove into the real data unless someone came to me with a specific question, or I had to produce a report.

There’s an obvious downside to that approach: The data in the dashboard is very “averaged out” and may lead us to miss more specific data points that we can leverage to do a better job.  But how do we get at the juicy money making data, while not spending too much time getting buried in minutia?

The solution? Scheduling in regular, recurring “data dives” to make sure you are not getting addicted to the dashboard view of your website.  Maybe start with once a week, and put it in your calendar. (If you don’t you’ll likely never find the time ☺)

Note: I am using Google Analytics in these examples because of its ubiquity, but they should all be applicable to any modern web analytics system:

Here are 5 tips to get you started:

1. Instead of the default “last 30 days” view of your analytics, try exploring different extended date ranges.  For example, I used to keep a rolling, 90-day dashboard.  Using the “timeline” function in the date selector tool is good for this.  So is selecting “date range” in the comparison dropdown menu; that way you can compare the same date range in the prior year, for example.
2. Make sure you assign goals and dollar amounts to every conversion on your site.  Most sites have a primary conversion like becoming a lead, subscribing, or purchasing, but micro-conversions are important, too.  Tag your primary conversion goal with your average order value, your lead conversions with a value per lead, etc.  For micro-conversions, figure out what percentage of your visitors that take that action eventually leads to sales.  If 1% of blog subscribers turn into deals, and the average deal is worth $500, then that micro-conversion goal value should be $5.
3. Explore the Traffic Sources reports to get a better understanding of your traffic “mix.”  Segmenting by traffic source can often yield quick, actionable insights.  Try looking at your organic traffic over the last 6 months, or your referral traffic over the last 3 months.  What does the traffic graph look like?  How well or poorly are they converting?  Has that KPI remained consistent?
4. Dive into your Top Content reports, and try sorting by “$Index.”  Note: This value is only calculated if you’ve assigned goal values and e-commerce revenue values across your site.  And believe it or not, there are ways to assign e-commerce values to your site pages even if you’re not running an e-commerce site.  $Index calculates the values of pages according to how often they’re accessed en route to a conversion.  It works kind of like the plus/minus point system used in the NHL.  If a player is on the ice when a goal is scored, they’re “+1,” and if they’re on the ice when a goal is scored against, they’re “-1.”  So if a page is very regularly visited by customers who convert, it will have a high $Index value.  It’s a great way to figure out which high-impact pages you should start testing and optimizing.
5. If you have site search, spend some time hooking your web analytics up to your in-site search, then dive headfirst into the very valuable data the Site Search reports can provide.  Are you able to see which keywords are delivering “zero results”?  What keywords are being used most often in search?  Are visitors who search more likely to convert?  Do they spend more per transaction?  Are there products are services your visitors ask for that you don’t offer?  Should you?

I know there are more handy tips around, but I limited this to 5 because I’m sure our readership has some brilliant ways they can share on how to do healthy and productive “data dives.”

And if this was useful, let us know, and maybe we’ll do a part two.

One final note:  Data diving is healthy and fun, but just remember to come up for air once in a while . Even more important, don’t let the stuff you learn from your analytics just sit there, turn your learnings into action and let’s move our conversion needles together.

A week ago, my friend called me to ask, “What’s the industry average time spent on a site?” Her boss asked her to find out because she was doing a presentation to the marketing team and would be attempting to describe what was happening on their website.

My friend was looking at her analytics reports, assuming they should be reporting metrics like “time spent”, but she couldn’t give me any explanation as to why they were measuring certain things or how it all fit together. This marketing team had no idea what their analytics were trying to tell them.

Sound familiar? Whether or not we care to admit it, this problem is all too common. By themselves, the facts can be deceiving. If the facts don’t fit into a larger story line, they’re meaningless. Just because something happened, that doesn’t make it newsworthy. That’s why…

Marketers should think like news editors.

Your web analytics program works for you, not the other way around. It’s the news wire that serves your staff of reporters and, as editor-in-chief, it’s your job to decide which stories are most important.

There are two types of approaches to web analytics reporting:

• The beat reporter reliably follows the same story from day-to-day. If you tell the beat reporter to follow “time spent”, she will diligently explain where visitors spent the most time, how much time they spent overall, and how much time they spent today versus yesterday, last month, last year, and so on.

• The investigative reporter tries to find the meat of the story; to get the bottom of what truly matters. If you tell the investigative reporter to follow the “time spent” story, she’ll start to ask big picture questions. She’ll want to know why time spent matters, how it relates to your other metrics, whether “time spent” means one thing on one page and something very different on another, and whether it even matters if visitors are spending more — or less — time on your site verses the competition’s. She even wonders if this whole “time spent” thing is really a distraction. She doesn’t want to spend her time chasing false leads.

Like other default metrics, average time spent tells us nothing on its own. The company that my friend works for has over a thousand employees. Most of the staff in their home office and brick-and-mortar stores use computers every day, and many of them likely have their browser set up to go directly to the company’s homepage automatically. Each day, a large amount of their traffic probably comes from employees, not potential customers. If this is the case, the average time spent on their site tells them very little about the customer experience on their website, because employees’ time spent would skew this number. Likewise, the traffic sources would be skewed and the average page views and bounce rates from the landing page would also be skewed.

Don’t use your analytics tool just to report the facts. Become an investigative reporter. For each piece of information you find, ask yourself why it matters. Ask how the metrics tie together. Most importantly, ask yourself how the web metrics you report on tie into your overall business goals.

That’s how reporters break news.

. .

About the Author: Melissa Burdon is an investigative reporter (or Persuasion Analyst) at FutureNow. She’s also a recovering Canadian. Oh, and it’s her birthday.

It’s true. Obama was underestimated, as was his Republican counterpart, Mike Huckabee, who beat his closest rival, Mitt Romney, by huge margin despite being outspent on the order of 15-to-1. Although Huckabee, the Christian evangelical former Governor of Arkansas, had risen sharply in the polls headed into the caucus — thanks to good performances in recent debates and a knack for off-the-cuff, wisecracking candor on live TV — not even his closest staffers could have dreamed of such a win (especially after a week of cringe-inducing PR gaffes by their candidate).

The race has only just begun for these two — very different — candidates, but their Iowa wins destroyed myths about what was possible for their campaigns.

Marketers should take notice.

Branding (a story that resonates)

Obama’s Story: “Change You Can Believe In” is the slogan, and it’s working. Experience in Washington isn’t everything; in fact, it’s a setback for anyone who wants to reform the system. He believes in “the audacity of hope” and is often mocked for his optimistic (some say “naive”) rhetoric. A freshman Senator with a mere 20 years in politics, he’s positioned himself as the only Democratic candidate who can truly offer a fresh start. He’s built an enthusiastic and diverse base, although he’s especially popular among young voters, who rarely turn out to vote before the general election and often show up in weak numbers when that happens. But they’re showing up now — and in big numbers. Our racial and economic divisions are possible to overcome, he believes, because that’s exactly what he’s done. He’s seen the U.S. from more angles than most of us, and that type of experience can’t be shown on a resume. Americans are tired of divisive politics, and Obama claims to be the one who can end the partisan gridlock that has characterized the Bush administration. More importantly, though, a vote for Obama is said to be more than a vote against his rivals; it’s a vote against cynicism and the status quo; a chance for YOU to have a voice in politics (”I’m asking you to believe. Not just in my ability to bring about real change in Washington … I’m asking you to believe in yours”). Besides, he’s even good at basketball. Oprah supports him and, apparently, so does Iowa. Shouldn’t you?

Huckabee’s Story: “Faith. Family. Freedom.” Just an ordinary guy; one who happens to have been a pastor, a governor, and a patient diagnosed with Type II diabetes, who then lost 110 pounds and ran three marathons. Tax reform (abolishing the income tax and replacing it with a heavier sales tax) and a return to traditional family values are two of our biggest priorities. A creationist evangelical who lived in a triple-wide trailer next to the Arkansas governor’s mansion just to save taxpayers’ money while it was being renovated. He’s become a media darling over the past few months after unpretentious, quick-witted appearances on The Colbert Report, The Daily Show with Jon Stewart, the CNN/YouTube Debates and, the night before his Iowa win, on The Tonight Show with Jay Leno. To say his is an untraditional campaign is an understatement, and, although comparatively broke (and that’s changing quickly), Huckabee has something worth more than money: Evangelical supporters (literally, in his case) who would rather vote for a guy like them than someone who’s just trying to buy their vote or pander to them. Chuck Norris supports him and, apparently, so does Iowa. Shouldn’t you?

Lesson #1: Nothing is inevitable. Nothing is impossible. When your competition seems unbeatable, don’t be afraid to compete on your own terms. People loves an underdog, especially one whose message reflects their own aspirations. A little candor goes a long way. Winning votes is one thing, but transcending old rules by tapping into the right message is what spreads word of mouth and grows your base.

Lesson #2: If either of these candidates had blindly followed the advice of so-called “experts,” they would seem more scripted and, consequently, less authentic. You don’t need to be negative to win, but you’d better know how to leverage other people’s mistakes.

Lesson #3: You can’t be all things to all people. Not everyone’s going to like what you’re saying (or selling). If you want to create brand awareness AND brand advocates, fearlessly define what you’re not.

Lesson #4: Leave the I-me-my stuff alone. A good campaign isn’t all about you (your brand), it’s all about “YOU” the customer). Too bad Hillary didn’t have the We-We Monitor years ago.

Money Isn’t Everything

Check out the difference in small money donations between Clinton…

and Obama…

Lesson #5: It’s important to look beyond the bottom line. Although Clinton leads in terms of total donations, the bulk of it is from (presumably) rich donors who have given the maximum contribution allowed by law. Obama, meanwhile, has more than doubled his rival in contributions under $200! Average Order Value, as it were, for Clinton is higher than it is for Obama, but in a world where a vote is a vote is a vote, there are simply more people willing to reach for their credit cards and checkbooks for Obama than for any other candidate.

Will Obama grab the nomination and upset Clinton? Can Huckabee translate his momentum into wins in other states? What else can we learn from these candidates?

Bryan Eisenberg

…marketing in an era when the customer is in greater control than ever. That businesses can ‘Always Be Testing’ (for free!). And, of course, for Hannah, Sammy & Stacey.

Cinde Johnson

…the fact that more e-tailers are coming to the realization that relevance, scent, and my buying process, are more important than their selling processes, and for making their sites more persuasive. (When you live in the “official” middle-of-nowhere, shopping online isn’t just a convenience, it’s a necessity!)

Holly Buchanan

…companies and marketers making more efforts to truly understand and communicate with their female customers. I fully believe this will lead to better results for marketers, and better results for women in general. When women are surrounded by advertising that doesn’t speak to them, isn’t relevant to them, where they don’t see themselves reflected, it’s a real problem.

Documentary filmmaker John Pilger once asked, “Does culture influence advertising, or does advertising influence culture?” I believe the answer is both. (Dove’s “Onslaught” video gives just a small taste of what it’s like to be surrounded by advertising to women.)

My hope is that in the near future, I can create video that is the opposite of “Onslaught” — that promotes all the thousands of ads that are relevant, inspiring, uplifting, and break through stereotypes. I’ll call it “Breakthrough.” I can’t wait to work on it.

Peter Lee

…all the people who now believe in the power of conversion optimization. You’re making my job much easier.

Marijayne Bushy

…an environment that fosters growth and learning, and provides me with an opportunity to help businesses and organizations of all variety and sizes. I’m grateful for colleagues who are supportive, intelligent, insightful, and prolific. And lastly, I’m grateful for our wonderful clients, who are open to new ideas, putting a new spin on old ones, and taking criticism in a positive light — and for those who’ve never hired us, yet use our free resources to dig deep and explore innovative ways to grow their organizations.

Howard Kaplan

…among other things, the Boston Red Sox for winning their second championship in 89 years.

Melissa Burdon

…the fact that people are finally seeing that they shouldn’t settle for a 2% conversion rate and are investing in conversion optimization before spending more budget on search. I’m thankful to Robert for editing my articles. I’m thankful for all the male employees at FutureNow. (But I’ll be even more thankful when we hire more females. ) Oh, and I’m thankful that the ski season starts this week!

Brian Bond

…analysis and metrics becoming a much bigger focus for marketers this year. I’m also thankful that Google finally launched a pay-for-performance ad model.

Robert Gorell

…our readers. In nine short months, you’ve helped transform a cool bi-monthly newsletter with several thousand subscribers into a top marketing blog with 100,000-ish repeat monthly seekers of knowledge. Thank you for stopping by. I’m thankful for everyone who shares their comments — you challenge our thinking and help us to (hopefully) give you a better GrokDotCom. You keep the conversation going. I’m thankful for our writers, whose insights never cease to impress me. And for all of the bloggers who inspire us. Because of you, good ideas keep spreading — quickly.

Anthony Garcia

…a lot of things, but especially my beautiful wife & children, my clients, our team, and anyone who’s kind enough to read this. Most of all this year, I’m thankful for one of my favorite emerging brands — my brand-new, burping-yet-gracious baby daughter.

John Q(uarto-vonTivadar)

…finding this cool Thanksgiving t-shirt to add to my collection!

But this confusion among smart people makes sense when you think about it. When was the last time you had a face-to-face conversation with someone, only to realize they weren’t listening? How can we expect to measure engagement with metrics, when we often can’t tell if the person right in front of us is truly engaged? In fact, the only people who can reliably tell when you’re tuning out are your friends, family, and significant others. There’s a reason for that. They’ve seen your behavior before, analyzed it, and suddenly, in their minds, you’re easier to predict than Paris Hilton.

Likewise, engagement means different things to different websites. Since each site has its own unique characteristics and purpose, engagement must be defined by your site’s goals — not by Amazon’s, eBay’s, or Ms. Hilton’s.

The first step is to define how an engaged visitor behaves in terms of your site’s goals.

• What is the ultimate purpose of your site?
  • Content site example: Get people to read my cooking blog.
  • Commerce site example: Get people to buy hats from me.
• What actions do visitors exhibit when they’re interacting with the site and moving toward its ultimate purpose?
  • Content site examples: Reading articles, signing up for newsletter, subscribing to RSS.
  • Commerce site examples: Viewing products, reading reviews, viewing about us page, adding items to cart.

So, what exactly does an “engaged” visitor do on your site? What are some of the clues that engaged visitors leave behind in your analytics?

• Do they stay long?
• Do they click a lot?
• Do they visit the site many times?
• Are their repeat visits days apart? Weeks apart?
• Do they penetrate deep into the site or bounce off of it?
• Do they view lots of pages?
• Do they take a given action like sign-up for a newsletter, refer a friend, or download a file?
• Do they leave comments on your blog?
• Do they link, Digg, Stumble, or otherwise find you del.icio.us?
• Do they purchase?
• Do they purchase repeatedly?

Some sites will have an even harder time than others at capturing the elusive engagement in their analytics and may instead need to combine the quantitative data with qualitative analysis, like surveys. (Here are three great survey questions.) But proceed with caution. While many sites could benefit from using surveys on their quest to find missing pieces of the engagement puzzle, it’s easy to be mislead by what customers tell you in a survey. Ever take an online survey where the questions were fundamentally flawed? Do you prefer the taste of New Coke to CocaCola Classic? (The folks who were surveyed did.)

What’s even more dangerous is that only certain personality types bother to participate in surveys in the first place. (And good luck getting a Spontaneous customer to fill out a survey unless they’re either angry or bribed.)

A common approach to getting an initial handle on engagement is to take certain metrics that relate directly to your visitor’s main goals: those that measure if visitors are taking the actions you want them to. Monitor them closely, and see how these metrics play off each other when certain changes happen — e.g., changes in season, updates to a checkout process, special promotions, inactivity on a blog, industry trends — affect the site.

When Metrics Lie

When selecting which metrics to use, keep in mind that it’s easy to be deceived by your own numbers. Proceed with caution by giving an in-depth look into the stories these metrics can tell you before placing your trust in them. In order to be sure that your metrics are an accurate reflection of engagement, you shouldn’t take one-off metrics at face value.

“Page Views” are a great example of a metric not worth trusting on its own. In this case, it may very well be that a visitor isn’t finding what they’re looking for. Perhaps they’re “pogo-sticking” from page-to-page in search of what they need. Now you’re keeping them on the site longer, thus increasing “Time Spent,” which, again, can be deceiving by itself. Although wasting the customer’s time — so long as they don’t leave the site — will increase the page views and time spent, it may not mean you’re actually engaging visitors. (Not in the way we’d hope, anyway.)

Engagement Metrics + Toolkit

With your site’s goals in mind, and a rough understanding of how an engaged visitor behaves, here’s a sample of some metrics that may be useful relative to your site’s purpose:

• Visitor Engagement Index = (Visits) / (Visitors)
• Take Rate = (# of Visits Taking Part in Desired Activity) / (Visits)
• Repeat Visitor Share = (Repeat Visitors) / (Visitors)
• Heavy User Share = (# of Visits with X or More Pages Viewed) / (Visits)
• Committed Visitor Share = (# of Visits Lasting Longer Than X Minutes) / (Visits)
• Committed Visitor Index = (# of Page Views in Visits Lasting Longer Than X Minutes) / (# of Visits Lasting Longer Than X Minutes)
• Committed Visitor Volume = (# of Page Views in Visits Lasting Longer Than X Minutes) / (Page Views)
• Bounce Rate = (# of One Page Visits) / (Visits)
• Scanning Visitor Share = (# of One Minute Visits) / (Visits)
• Scanning Visitor Index = (# of Page Views in One Minute Visits) / (# of One Minute Visits)
• Scanning Visitor Volume = (# of Page Views in One Minute Visits) / (Page Views)
• Average Order Amount = (Total Sales) / (Total Orders)
• Sales Per Visit = (Total Sales) /(Visits)
• Repeat Order Rate = (# of Orders From Existing Customers) / (Total Orders)
• Order Acquisition Ratio = (Marketing Expense/Number of Orders) / (Marketing Expense/Visits)
• Conversion Rate = (Number of Sales) / (Visitors)
• Page Views per Visitor = (# of Page Views) / (Visitors)
• Average Time on Site

(Eric Peterson even offers his own complex engagement calculation, and discusses the web analytics community’s challenges to it.)

Once a set of metrics is selected that directly relates to potential engagement on your site, constructing a weighted average of the set might help. This needn’t be some painfully complicated multivariate regression model, needing someone with rocket science experience like our buddy John to make sense of it; just some metrics that can serve as a collective vital sign to measure how well your site is engaging people while carrying out its core mission.

Jim Novo makes a potent case for using visitor recency to measure engagement and how to leverage it. If you can collect information relative to the history of each specific user, and the recency of their visits, his approach can send your ROI skyrocketing.

Novo’s approach shows how recency can explain a visitor’s potential value, given their propensity to return to your site frequently, as represented by the horizontal axis below. The vertical axis, meanwhile, shows how often the visitor has taken the action being measured.

Although fuzzy and directionally correct at best, engagement is vitally important to measure because it’s a predictive metric. If your current visitors are exhibiting behaviors indicating that they’re engaged, they’re likely to return soon — and often. If you see signs that visitors are becoming less engaged with the site, it’s safe to suspect that recent changes to your site or the flow of its traffic may be working against you. Either that or your competition’s finally outdone you. Regardless, it’s always good to know when to hang it up and try something new.

Engagement can also be a useful measure of the effectiveness of your branding. If visitors are showing signs that they’re engaged with your site, they’re generally showing affinity for your brand.

While engagement has become a heated buzzword, and arguably an excuse, it’s important not to be mislead. Since it’s a state of mind for your visitors, and therefore not easily quantifiable, there’s no simple way to measure engagement. But attempting to measure will help you to keep your site from proposing on the first date.

Do you have any unique approaches for measuring engagement? Let us know. We’d love to get a conversation going in the comments.

The Conversion Rate (CR) tracks how well your website is achieving its main objective. This goal will vary depending on the type of site. An e-commerce site’s main objective, of course, is to get people to buy product. Here’s how a commerce site would calculate conversion:

CR = Number of Sales / Visitors (A metric often related to CR, especially with content-driven sites, is Take Rate.)

The higher the CR, the better the ROI (Return on Investment). Improving conversion increases the amount of money you can make with the same amount of traffic. To determine exactly how conversion affects ROI, calculate your Order Acquisition Ratio.

Understanding what affects conversion requires an in-depth look at the entire online marketing strategy. To begin, break down the steps involved in the site’s sales process. For instance, a retail site would look like: Homepage -> Category Page -> Subcategory Page -> Product Page -> Cart -> Checkout.

Along with these steps, the Exit Rate for each must be calculated. Exit Rate shows how many people are not converting by leaving the site at various stages in the sales process — often thought of as a funnel, although it’s slightly more complicated in reality. Still, the funnel gives us a visual representation of where to find the biggest leaks, so we can fix them and optimize the experience to recapture money that would otherwise be left on the table (if you don’t mind me further mixing metaphors).

Each stage in the process is a micro-action that will lead the visitor closer to the macro-action of converting (e.g., purchasing). The best way to diagnose why various steps, or micro-conversions, aren’t performing as well as they should is to ask three simple questions:

1. Who is the audience at this step?

2. What action would we like them to take?

3. What information do they need to feel confident enough to be compelled to take that action?

When asking these questions, it’s important to recognize that a website is not one size fits all; it should be many sizes fit all. Multiple scenarios, or pathways through a site, need to be planned ahead of time in order to suit different personality types and how they prefer to behave online. It’s also important to take into account how close a person is to making a decision. Are they early on in their buying process and just researching, or do they know exactly what product they want? (Bryan’s recent screencast shows how to appeal to different buying modes and temperments.)

To help understand why visitors may not be taking the necessary micro-actions to move closer to converting, the Hierarchy of Optimization provides a useful guide in addressing potential problems. This hierarchy forms a pyramid and starts with basic requirements, then moving higher up toward the top, where persuading visitors to take the action is the highest aspiration.

Let’s look at them in reverse order…

• Functional. Does the site offer something that the visitor needs?
• Accessible. Is the visitor able to access whatever it is that the site offers?
• Usable. Are there unnecessary difficulties or roadblocks that cause friction for the visitor?
• Intuitive. How well is the site’s sales process structured? Is it compatible with how the visitor likes to buy?
• Persuasive. Does the visitor truly want and understand the problem by clearly knowing that it will solve their needs? Do scent trails carry through to the more funnel-like, conversion point on the site (e.g., the checkout process)?

If your CR is less than 10%, you should focus on optimization — but there’s always room for improvement. Along with taking steps to remove obstacles that impair the visitor’s buying process, causing them to waste their time thinking instead of doing, the most potent tool is empathy. Anticipating your visitors’ motivations will help you to answer their questions at each step — and that requires a good deal of planning.

Remember, a website exists to help its visitors achieve their goals. Give people visiting your site all of that, and the ROI will be well worth the effort you put into it.

1.) Visits to your site

2.) Number of orders placed

3.) Total marketing expenditures (which can include fixed costs associated with maintaining the site, but let’s focus primarily on marketing expenses)*

With these variables in mind, we will get two contributing metrics with which to calculate order acquisition ratio.

Cost per Visit (CPV) = Marketing Expense / Visits

CPV measures how much you’re paying to attract each single visit to your site.

Cost per Order (CPO) = Marketing Expense / Number of Orders.

CPO tells you how much you’re paying in terms of marketing budget to get a visitor to your site who converts and becomes a customer. This is directly related to your Conversion Rate.

Order acquisition ratio is then calculated by taking the CPO and dividing it by the CPV.

Order Acquisition Ratio = (Marketing Expense/Number of Orders) / (Marketing Expense/Visits)

It should be a positive number (if not, you’re in trouble). The lower the ratio, the better your marketing budget is being used. Some of the best ways to lower OAR include:

• Boosting conversion! Increasing conversion lowers your CPO. Since conversion is the website’s primary goal, there are literally thousands of factors that affect conversion. (Conversion is so important to online health and wellness that improving is integral to everything we do for clients.)

• Improving organic search rankings with relevant content. When you spend the time and money to create relevant content, the CPV and CPO should both drop — and you’ll further lower CPO by converting more visitors.

• Targeting quality traffic sources. In your analytics, segment your site’s incoming traffic by source in order to identify where to put those marketing dollars. (Bounce Rate is a great starting point for this.)

• Optimizing PPC campaigns. With an effective PPC campaign, you’ll be able to convert more visitors. While this will increase your CPV, but when done correctly, it will yield a larger decrease in CPO by converting a higher percentage of traffic.**

Order Acquisition Ratio is based on more traditional bored boardroom metrics because it has a close relation to traditional financial statements. It has nothing to do with “Web 2.0,” “Web 1.0,” or Facebook. So, it’s great for sharing with your boss since it’s directly tied to the bottom line. There’s even a cousin to this metric; a non-ratio, cold-hard-cash version of the Order Acquisition Ratio known as the Order Acquisition Gap. To calculate it, simply subtract the CPO from the CPV to get a negative number. This number shows how much money you waste in marketing dollars on visitors that don’t convert.

Order Acquisition Gap = CPV – CPO

There are other close relatives in this family of metrics, all of which focus on costs associated with generating new customers. To calculate these similar metrics, you’ll need to be able to track the same figures discussed above — except they need to be further segmented. Track the following numbers, and you’ll also benefit from a few additional metrics (listed in the bullet points below):

1. New visitors to the site.
2. Number of orders placed by new customers.
3. Total new customer marketing expenditures.

With these figures you can see the effectiveness of your new customer acquisition efforts:

• Customer Acquisition Cost = (New Customer Marketing Expense) / (Total New Customer Orders)
• New Customer Cost per Visit = (New Customer Marketing Expense) / (New Customer Visits)
• Customer Acquisition Gap = (New Customer Marketing Expense/New Customer Visits) - (New Customer Marketing Expense/Total New Customer Orders)
• Customer Acquisition Ratio = (New Customer Marketing Expense/Total New Customer Orders) / (New Customer Marketing Expense/New Customer Visits)

[*Regardless of the expenses you include, it's crucial to set a standard and stick with it in order to accurately measure and account for the specific impact of such changes.]

[**When monitering your order acquisition ration, never tolerate any increase in the cost per visitor without an accompanying decrease in cost per order.]

To qualify as a bounce, analytics tools will typically take all visitors who only see one page and leave. Time may also be used to qualify a bounce (e.g., any visit under 10 seconds as a bounce).*

To calculate bounce rate, take the number of bounces and divide it by the number of visits. You can measure bounce rate for your entire site and measure the bounce rate for specific landing pages.

Example: 10,000 bounced visitors / 30,000 total visitors = 33% bounce rate.

There are many elements that will effect the bounce rate. The main idea is that people coming to your site are following a scent. If they arrive on your site and have no trace of the scent they were following, they will immediately leave. Some of the main elements to investigate when looking into your bounce include:

• Traffic source. Are certain traffic sources consistently delivering visitors that are more likely to bounce?
• Inbound links to your site. Look at the link and surrounding text that links to your site. Do the links give the visitor an accurate idea of what to expect on your site, and does your site contain what the link leads them to believe they will find on the page?
• Keywords. If you are measuring the traffic coming from search engines, are the keywords the visitor searches for visibly present on your landing page?
• Stating your unique value. Do you have a unique value proposition? Is it present across the site and particularly on your landing pages?
• Page title. Do you have a relevant page title that is telling of what your page contains.
• Headings and headlines. Are there relevant headings and headlines that tell a visitor where they are and what to expect.
• Global Navigation. Is your navigation intuitive? Does it use words and naming conventions that your visitor understands? If your sitewide bounce rate is high, this sitewide feature may be contributing.
• Load Time. Are your pages loading too slow for people to even give them a chance?
• Page descriptions. Are the page descriptions you created relevant to the page?
• Perceived length. If your pages are very long, they may be perceived as a waste of time, thus causing people to bounce. This also relates to forms. Are there any intimidating forms present?
• Look and feel. Does your site’s aesthetic match what a site in your industry typically looks like? Is your site cluttered and lacking in white space?
• Server. Are you testing to see if your server is up to par?
• Browser compatibility. Are different browsers viewing your pages correctly?

Bounce rate is a great starting point when analyzing important aspects of your site. Here are some of the important elements you can measure with bounce rate:

• Where should your marketing spend go? By getting information about which traffic sources are delivering lower quality traffic, you can optimize these campaigns by analyzing the elements listed above and in the meantime divert your money into campaigns that are outperforming them.
• Which keywords should you be paying for? Use bounce rate a starting point for analyzing your keyword performance.
• Are your optimization efforts successful? If you are making changes to a page or sitewide feature, has the bounce rate gone up or down?
• How effective are your landing pages? If your landing pages are bouncing more than one out of three people visiting your site, you may want to investigate why this may be happening.

Avinash Kaushik has even called bounce rate the “Sexiest Metric Ever” — and I agree. As far as web metrics go, bounce rate is sexy. Don’t ignore the other metrics in light of bounce rate’s beauty.

So, get testing, and be sure to check out the next installment, where we cover “Order Acquisition Ratio.”

. . .

*It’s important to check what your analytics program considers a ‘bounce’ before analyzing any data.

[Editor's Note: Want to get less bounce to the ounce? Future Now can help.]

Key Performance Indicators or KPI’s (define) are the critical Web metrics you should be monitoring to evaluate the effectiveness of your site. Key performance indicators may differ depending on the business topology (ecommerce/retail, lead generation, content or self-service/support), but understanding them broadly is critical to any organization’s online success.

In this first installment of Unlocking KPI’s, we’ll discuss the “take rate”; the amount of people taking you up on a given offer on your site. It’s not necessarily your “conversion rate,” because that term is generally reserved for the site’s primary goal, or macro-conversion (e.g., acquiring a new lead, processing an e-commerce order). Take rate is used to measure micro-conversions. These can include:

• Newsletter subscriptions
• Downloadable materials such as ebooks
• Case studies
• White papers
• RSS subscriptions
• “Add to Friend” links for social networking sites
• Up-sell and cross-sell offers added to shopping cart

To calculate take rate, simply find the number of successes for the action being measured and divide it by the number of people exposed to the action.

Example: Lets say I write an ebook about where to find the best pizza in Brooklyn. 8,000 hungry people downloaded this ebook from my site last month. And during that month, my site received 80,000 visits. Of those visits, there were 40,000 unique visitors.

Take rate = 8,000/80,000 = 10%

This can also be done with unique visitors.

Take rate per unique visitor = 8,000/40,000 = 5% 20%

So now that we have the calculation behind take rate, lets look at what influences the take rate. Ultimately, the presentation of the material you want visitors to take has to be perceived as relevant and valuable. The specific elements that will influence how a visitor perceives your presentation need to be tested and optimized to find out what is working best. You will know you are moving in the right direction when your take rate increases.

Here’s a list of some main elements to test on your site that will influence its take rate:

• Call to Action. Does it consist of an imperative verb and an implied benefit? Is it clearly noticeable?
• Title. Is the title of the section containing your offer relevant and noticeable?
• Point of Action assurances. Are you easing the visitor’s concerns about taking the action? For instance, two commonly overlooked assurances regarding newsletters are privacy policy (i.e., that their email address will not be shared with third parties) and telling the visitor they can cancel anytime.
• Benefits associated with the offer. Are you speaking in terms of benefits that the people who accept your offer enjoy? Are you picking the most persuasive benefits relative to the segment of traffic you see the page attracting?
• Tell the visitor what to expect. If the material is downloadable, tell the visitor how large of a download is required. If it’s a newsletter, tell them how often its sent.
• Location of the call to action. Are you presenting the call to action (e.g., text link to white paper download, newsletter sign-up) above the fold? Is it in an area where the visitor can expect to find what your offering?
• Targeted keywords. What are the keywords you targeted to attract people to the page the offer is presented on? Are they relevant to your offer?
• Look and feel. Does the offer look like a banner ad? Is it contrasted against the rest of the page enough to stand out and be noticed?

Now that you have a framework of understanding what a take rate measures, and elements of its presentation to test to optimize, lets have a final look at why take rate is important to your site.

In planned scenarios, the take rate can be viewed as a leading indicator for the short-term performance of your site. Viewing a take rate as a micro-conversion point to indicate interest in your macro-conversion goals will tell you if people are moving forward in their buying decision process. If your take rate increases, you’ll qualify more people to move to your macro-conversion goal — like plugging holes in a leaky bucket.

For the next installment of Unlocking KPI’s, we’ll cover the ever-important “bounce rate.” Until then, if you have any questions, we’d love to hear from you in the comments.

As you can see, not only has almost every site on the list (save for Google and a few others) dropped considerably, there’s (obviously) no sign of many of today’s top players. No Facebook. No MySpace. No Wikipedia. No Craigslist. In fact, a lot of folks around here were surprised to see that Google came in at #12 — which seems pretty high, although this was when they started to get popular.

Say what you will about “attention” as a metric; it still shows that being the Web’s “next big thing” isn’t necessarily a goal worth having. (No offense to Neopets.com, but free cartoon screen saver downloads don’t quite have the “wow”-factor they used to.) Six trips around the Sun may not be a long time in human-years, but in Internet-years, it’s a lifetime.

When one company owns 40% of the market for online advertising, it’s just not sustainable (30% would be a much healthier number). Google may be one of the most important companies of this Internet era, but let’s face it: they don’t have the assets or a General Motors or the customer loyalty of, say, Wal-Mart. The other search engines are innovating faster. And, let’s not forget, Microsoft will go to great lengths to steal advertising market share.

Online, success means running a marathon, not sprinting to the top. As we’ve said since 2001, beware of selling yourself short on traffic.

What do you think? Will Google be the top dog in another six years?

Rank is something we bloggers take very seriously. The problem is, nobody seems to be that good at measuring it — not yet, anyway.

For the past couple years, bloggers have loosely relied on Technorati to do the job, with blogs ranked according to their number of incoming links from unique blogs. For some bloggers, though, that may change now that Techmeme has announced a new feature, Techmeme Leaderboard, that ranks blogs according to how often they appear on, well, Techmeme.

Over at TechCrunch (no relation), Michael Arrington has the scoop:

To be exact, top blogs will be ranked on presence – “the percentage of headline space a source occupies over the 30-day period.” Discussion links are not taken into consideration – only full headlines are counted.

I think this is a much better way of ranking the very top blogs than the Technorati approach. Technorati has deep flaws, for reasons stated above. Techmeme, by contrast, has zero spam and tends to mirror what the tech blogosphere is writing about perfectly.

That may be true, but keep in mind that a Techmeme rank will have limited value outside of the tech world. And how about a few other pros and cons for the two sites…

Technorati

Pros: All blogs treated equally, regardless of focus; rank determined by incoming links; current go-to source for comparing blog popularity (i.e., let’s you know where you stand vis-a-vis other blogs).

Cons: All blogs treated equally, regardless of focus; links from spam blogs and pay-to-link services can distort a blog’s true rank; buggy, and often slow to update.

Techmeme

Pros: Niche focus; real-time indicator of tech/business news stories; threads popular stories, linking to blogs that discuss the primary news source.

Cons: Bias toward tech news; encourages copycat/echo chamber-style blogging (e.g., right now I’m blogging about something a lot of other bloggers have covered); tends to reward popularity over analysis.

Back in August, when a glitch caused Technorati to bestow upon us the coveted #1 spot, I suggested to fellow bloggers that, if rank meant everything…

. . . every blogger who’s had even one link documented by Technorati could rejoice more than they already are after being accidentally ranked #1 today — thanks to a glitch.

If rank meant everything, you wouldn’t have to create fresh, original content.

If rank meant everything, blogs wouldn’t be worth reading.

Everyone would be baiting links (like I am).

Like money, when rank means everything, it means nothing.

Do blog readers really care about rank?

Would content by any other number smell as sweet?

Why does a blog’s rank actually matter? Well, there are a few answers. Rank matters to anyone selling ad space on their blog. It’s also directionally interesting since it helps bloggers get a sense of growth. Oh, and there’s that whole “human nature” thing: We’ve been grunting over who’s the biggest and baddest since our days as lesser, knuckle-dragging hominids — which, as geological time goes, wasn’t too long ago.

Any bloggers, tech or otherwise, like to share their thoughts?

Any Techmeme fans ever use Today.GrokDotCom to scoop stories? We do.

[UPDATE: Technorati names Richard Jalichandra as new CEO; Techmeme founder Gabe Rivera explains his new Leaderboard.]

That’s great. But how?

After reading comScore’s methodology overview, a 2-pager with scarce detail — if you don’t mind wading through jargon and registering for the download, click here — I’m stumped. From what’s been announced so far, it’s too early to say whether they’re onto something. The real story will unfold once comScore coughs up the data.

Meanwhile, on his Micro Persuasion blog, Edelman PR’s Steve Rubel shares his views on this research:

Based on a [sic] informal analysis, my belief is that many online communities, bloggers, social networks will never attract a critical mass of advertisers because they are not set up properly to attract visitors who have a commercial intent to buy products and services. Online media is not sold this way now, but I bet it will be in the very near future.

Today, most advertisers size up community sites, blogs and social networks using traditional media buying models – namely, reach and frequency. Unfortunately, the reality is that many Web 2.0 sites, can’t deliver marketers the numbers they want because of the effect of Long Tail [define]. It’s simple supply and demand economics at work. This is why efforts like the one announced by comScore and Federated Media are fundamentally flawed.

Enter (Edelman client) Microsoft. In order for advertisers to assess a blog’s value, Rubel suggests they use a tool developed by Microsoft AdCenter Labs that claims to measure Online Commercial Intent by using “…terabytes of search data to calculate the likelihood of a web site to attract buyers.”

According to the Microsoft tool, Amazon visitors have a 52% intent to buy, or at least find information about buying something. Very cool. Too bad it’s not so reliable (yet, anyway).

I tried to repeat Rubel’s results for several of the sites he mentioned and, in most cases, my results differed from moment to moment. That’s not to say he’s lying. It just seems that, depending on when you search, results vary as much as 20%. Try it out for yourself if you’d like to compare your results to Rubel’s:

Consumerist – 49% of visitors have a commercial intent
Gizmodo – 47%
Autoblog.com – 45%
Treehugger – 41%
Techmeme – 41%
Engadget – 40%
Gridskipper – 38%
YouTube – 38%
TechCrunch.com – 37%
digg.com – 34%
del.icio.us – 29%
PerezHilton.com – 27%
Wikipedia – 14%
Flickr – 14%
Facebook – 10%
Twitter – 5%

Although it’s nice to see GrokDotCom come in at 49%* — give or take 5% — I wonder what all those terabytes can really tell us about niche visitor intent and/or buying modality.

Since we blog about buying online, it’s not a huge surprise that Grok did so well. But at a certain point, volume matters. Just ask celebrity blogger Perez Hilton (a great example from Rubel). Do you think his advertisers care about e-commerce buying modalities? Perhaps, but they must have some sense of whose eyeballs they’re getting, how many, and where they shop without waiting for comScore’s or Microsoft’s data to salt their spreadsheets.

But that’s the point. An entertainment blog has more in common with TV than Wikipedia. Is PerezHilton.com niche media simply because it’s a blog? Not really.

Sometimes volume combines with relevance to create something real. For instance, a search engine’s job isn’t to help you search, it’s supposed to help you find things. In 2003, from data collected by WebSideStory (now Visual Sciences), we found that Google was the lowest-converting search engine for e-commerce. Ask Jeeves all ya want. More people still prefer Google.

*The half of you who intend, at least partially, to hire us should do it.

[...] what is the likelihood these households reflect the overall “label” of the PRIZM cluster? Combine this with the fact that for customer analysis, demographics are generally descriptive or suggestive but not nearly as predictive as behavior and you have a bit of a mess.

Here’s a test for you. It only requires rough knowledge of your neighbors, so should not be very difficult (for most people!)

1. What is your “demographic”?
2. If you were to walk around the block and knock on doors, how many households would you find that are “in your demographic”?

Right. Maybe a handful, unless you live in a brand new housing development or other special situation. Now think about walking your zip code, or walking out 10 blocks or so from your house in any direction, and knocking on doors. Do you find most of these people are in the same demographic as you are? Did you ever find the “cluster average” neighbor? [Keep reading "PRIZM Clusters Not as Predictive as Behavior"... ]

For a bit of background context, check out “The Marketing/Technology Interface,” where Jim discusses how the scientists among us are making it difficult for the
marketing folks to learn about using data by obscuring the actionable with the scientific. He pleas for “the technical side to be a little ‘less scientific‘ and the marketing side to be a little ‘more specific,’ so they can meet in the middle.

With all the talk of “engagement” as the elusive metric, chased by marketers and statisticians alike, it’s worth noting that Jim Novo & Bryan Eisenberg formulated it some 7 years ago in the Marketer’s Common Sense Guide to E-Metrics. It’s just that back in them days, it didn’t have such an elegant name: “Scanning Visitor Share/Index/Volume” and “Committed Visitor Share/Index/Volume“.

I reckon “engagement” has a better ring to it.

It’s OK, you can hold the applause. We did.

Sure, it’s flattering to be on any list that suggests you’re a top blog, but what does this say about influence? Things get more dubious once channels like Twitter, Facebook, and LinkedIn are used to assess influence.

Here’s what David Brain had to say:

When people talked about on-line influence in the past they were often referring to bloggers and Technorati scores, though obviously influence was always more complicated than that. But now with the increasing mass adoption of Twitter and Facebook and favourites listings like Digg and Del.icio.us things have moved on. Bloggers Twitter and Facebookers Dig. Many of us are multi-platform users and so our online ‘footprint’ is much more dispersed.

Hmm… Is “dispersed” naturally better, even for PR folk like Steve Rubel, an Edelman SVP whose Micro Persuasion blog ranked #5 on Edelman’s “Top Blogs” list and #1 on its “Social Media Index”? And why should bloggers who don’t use Twitter, Facebook, or LinkedIn to engage readers care about Edelman’s index? Such measures are worthless in the case of influential multi-author blogs like SearchEngineLand or TechCrunch, where individual self-promotion tactics — e.g., hosting a Twitter widget, or linking to one’s Facebook account — would be irrelevant to readers. Of course, Rubel & company thinks these tactics are influential.

So, do we really need a blog-ranking index to account for Twitter activity between Rubel and Robert Scoble? Isn’t it enough they’re bombarding some 5,900 “followers” — as Rubel phrases it — with micro-minutia? You mean that’s “social media,” not plain-old broadcasting?

I asked Jeffrey what he thought about Twitter being used to measure influence, knowing full-well I’d get something like this:

…Twitter’s about as important as a pimple on a mole on an elephant’s a$$ in the real world. Marketers, without exception, overestimate their importance to their audience. It’s an occupational hazard. Early adopters are even worse. Blogging is important, but not truly mainstream yet. The Wall Street Journal, which has no social networking, is still more influential than Boing Boing. We all need to get over it.

Some might disagree, but there isn’t much life in Edelman’s index. That being said, it is interesting, if not problematic. They’ve simply taken a list with questionable value and filtered it through the lens which most interests them — and that’s fine. But what of other influential media channels like newsletters, forums, or books? How could Twitter activity be a greater measure of influence than something as concrete as book sales?

Everyone loves lists. We love lists. Sometimes we agree with Steve. Sometimes we don’t. He’s an opinionated guy, and we respect that, but is Rubel’s Web 2.0 platform more influential than Seth Godin’s blog and book platform? In the “twitterverse,” perhaps. In the world where people take money out of their wallets to pay for ideas, no.

Edelman thinks he is.

Is an “undead” metric any better than a dead one?

What’s funny is that Bryan Eisenberg and I were just chatting about this over IM last night, wondering what ever happened to Nielsen’s “June announcement” about this dumb sea change in metrics. For those who don’t know, Bryan eulogized the Web Page last October in his ClickZ column, and did so in person at Emetrics Summit. Still, I thought he said it best over IM (edited for grammar):

None of these metrics measure anything telling about the user experience in a Web world. They’re proxies for the old “reach” and “frequency” metrics Nielsen’s been pawning for years. When old media wonks wanted some “scientific” measurement system to “accurately” buy and sell media. Yup, those panel surveys were accurate and scientific, alright. Because of the inconsistencies from one experience to the next, this medium cannot–and by it’s nature will not–allow for comparative metrics. In this medium, the visitor’s in control and, as we can see from comScore’s cookie-based research we’ve seen, they’ll continually make it harder to measure them.

Google’s succeeded in selling lots of ads because they didn’t buy into the old school paradigm. Everyone else just doesn’t want to admit they’re waiting for their cat to bark, and for the world to go their way again. Let me know how that works out…

Speaking of IM, it turns out that “time spent” now gives AOL ranking credit not just for people at AOL.com, but for people using AIM–to which we can only say, “LOL!” Google’s rank drops from #3 to #5 because they give people quick, relevant results, while AOL jumps to #1 from #6 because people are using a one-off application. Hmm…

Of course, the blogs are already going nuts. Micro Persuasion’s Steve Rubel who, months after Bryan, predicted the death of the page view in Not-stradamus-like fashion is reveling in the news. Back in February, Rubel asked “What Willl Replace the Almighty Page View?” (whether he read my response about the futility of “time spent” is anyone’s guess). Meanwhile, some are more hesitant to rejoice:

The news immediately made Slashdot, where worries were expressed that this emphasis on viewing time will cause designers (and their bosses) to try anything they can think of to slow down the user.

OK, now that I’ve flooded you with links, here are the real questions:

• What are the rankers at Nielsen smoking?
• Are they aware of this thing called “tabbed browsing”?

[UPDATE: Bryan Eisenberg discusses "What Advertisers Should Be Measuring" and why "time spent" could prove disastrous.]