1. Look Nice – You want to put your best face forward. Your homepage is often the first thing that your visitor sees when they visit your site, so make sure that it is aesthetically pleasing and easy on the eye. Remember, for a vast majority of sites, the homepage has the highest bounce rate.  Give your a visitor a reason not to leave.

2. Make your prospect interested in what you have to offer – In the dating scene, this means opening up and making sure they know something about you that makes them want to learn more.  In website optimization, it means having a top notch Unique Value Proposition (UVP).

3. Remember them – Saving a visitor’s shopping cart for at least 30 days is a helpful tool for reminding visitors that they’re wanted (especially as Holiday shopping ramps up).

4. Don’t give them a reason to leave – The easier it is for your visitor to navigate your site, and the more quickly you can get them through their buying process, the more likely they are to convert.

5. Don’t talk up your best friend – The worst thing you can do is link to a site outside your own and push your visitor in that direction. Tools and references are always helpful, but don’t make them more attractive than the options that push them further though the conversion funnel. If you feel it’s necessary to link to outside domains, use a visual cue (like the common “tear off” icon) to indicate to the visitor that they’ll be leaving your site.

Now go ask for another date, or better yet, get down on one knee

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]

We define Home Runs as triple-digit increases in conversion rate.  When we help our clients hit home runs, we ring the bell and celebrate.

But one of the dangers of early testing efforts is the problem that some baseball players have: “swinging for the fences.”  (Apologies for the baseball references, but it’s getting to be that time of year.)  What if your test, or series of tests, doesn’t appear to raise conversion rate?  Do you dismiss the tests as failures because they’re not home runs?

Of course not!

Worst case scenario is that you’ve learned something about executing meaningful tests, and about what does or doesn’t resonate with your customers.  But more often than not, you are affecting your website in more subtle ways.  Remember that conversion rate is often a blended, averaged, blunt instrument.  Especially when it’s averaged across large volumes of organic search traffic, SEM traffic, email house list traffic, different product lines, etc.

Here are some things you can monitor when your tests aren’t having huge impacts on your overall conversion rate:

1. Micro-conversion rates – If you’re testing product detail page layouts and “Add to Cart” buttons, check if those test variables are having an effect on the micro-conversion rate of adding products to the cart.
2. Funnel conversion rates – If  you’re testing lots of minor copy changes to your shopping cart, check for changes in your funnel conversion rate.
3. Bounce rates – If you’re testing images, copy, or other changes designed to build up the credibility of your site, watch for changes in bounce rates.

These types of incremental improvements are tests results to get excited about!  If your micro-conversion rate increases, and your funnel conversion rate stays the same, that’s still more money in your bank account.  If you reduce the bounce rate, you’ve gained the chance to convert that customer later, instead of your competitor.

So don’t dismiss the base hits because you’re disappointed about not hitting a home run (this time.)  Take it from a patient analyst who’s favorite baseball player was famous for lots of base hits and not all that many home runs

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 Rimm-Kaufman Group’s Larry Becker writes about a recent study suggesting that:

. . .high growth companies are not evaluating and improving their home page designs in a systematic way. By comparing the home pages of the Fortune 30 against Inc Magazine’s fastest growing companies, researchers from Minnesota State University found the Fortune 30 had a usability score over 36% higher than the fast growing companies.

Sure, the brands in question were compared on “best practices” from 2001, but it seems the bigger brands are still beating the smaller guys at the fundamentals.

How has usability–good or bad–changed your opinion of a brand? Let’s hear some stories in the comments…

For instance, my example that although a “live chat” option may improve conversion rates incrementally in some cases, this minor conversion boost says nothing of how many customers you’ve turned off by demanding they interact on your terms–if only to “close window” and be done with it. Even worse, a conversion boost from something like a pushy live chat could mask the fact that you’re annoying potential customers. Rather than being concerned, you’d likely think you’re adding value. (I’ll explain more in a moment.)

Still, I do love you guys. You keep me honest.

So, how do you actually measure your “Piss-Off Factor” (POF)?

Like anything else, in order to know how to fix it, you must first define the problem.

The reason POF is so dangerous is the simple fact that measuring POF is very difficult. In the online world, the customer experience is measured largely by analytics. Most companies try to understand their customers by analyzing data about customer behavior. Data can tell you what your customers are doing, but it cannot tell you why.

The other problem with data is it measures only what “is,” and not what “could be.” If the problem is something that exists on your website, then you have an easier chance measuring the POF factor. But sometimes it’s what’s missing that causes a problem. Something should be there that isn’t. How can you measure something that doesn’t exist? I have some thoughts on both.

Find Out Where You’re Pissing People Off:

Look at pages with high abandonment rates. How did the visitor get to that page? What link did they click? What was the verbiage of that link? What were they expecting to see? Did the link deliver on the promise?

EXAMPLE: You’re on a product page. You want to find out more about that particular product. You click on “Learn more about our products,” expecting to be taken to a page that gives more detail about, that’s right, the company’s products. But instead, you’re taken to a product category page that only lists their products with little or no information. You wanted to “learn more,” but the link didn’t deliver on its promise. (A more accurate link would have been “See our products.”)

Check for copy that sounds “sales-y.” What verbiage are you using that’s turning them off? Look for any language that sounds like canned hype. At best, customers are ignoring it. At worst, it makes you seem pushy and fake.

EXAMPLE: “Better than money-back guarantee!” sounds like a gimmick. Instead, try “Money back guarantee. We mean it.” AND if you say you’re the “best,” you’d better have proof to back it up. Grandiose, unsubstantiated claims turn people off.

Mine your customer communications. Look at emails, monitor phone calls, and pay close attention to live chat sessions. Talk to customer service reps, sales people, and anyone else who has direct customer contact. What issues are your customers having? What questions are they asking? What are their objections? Make sure that you’re answering their questions and addressing their objections on the website.

EXAMPLE: You have a subscription model, and you charge a membership fee. Other competitors offer a similar service for free. A common customer objection is “Why should I have to pay?” Make sure you have verbiage on your site, at the Point of Action, that either explains or explicitly says “Here’s why you should pay.” Clearly explain why you’re different from the free site and list out the specific benefits members get with your paid memberships. Ignoring objections and not answering your customers’ questions will piss them off.

Gain customer insight through usability testing. I say this with some trepidation. The artificial environment of many usability tests can taint the results. But it can be useful when you’re too familiar with your products and website and need a fresh perspective on how customers approach and use your site.

EXAMPLE: You think a Call to Action is perfectly clear, yet the visitor has to look really hard to find it.

Only ask for the personal information you absolutely must have. The more personal information you ask for, the more you’ll piss off would-be customers. Ask for the minimum and be very clear about why you need that information and what you’ll do with it.

EXAMPLE: My personal pet peeve is when sites ask for a title “Mr., Mrs., or Ms.” I’m not a Mrs., but I despise Ms. Men can just click “Mr.” But for women, why do you need my marital status?

See what blogs are saying about you. Search the blogosphere to see if anyone is talking about their experience with your website or product.

As far as exit surveys go, proceed with caution. You can get some very valuable information, but they can also increase your POF.

What You’re NOT Doing That’s Pissing People Off:

This one is a lot more tricky. What is it that your customers want from you that they’re not getting? What are they looking for that they cannot find? What deeper motivations do they have that you are not addressing?

This is where the “data” problem intensifies. This is where “what” your customers are doing is little or no help; it doesn’t provide the deeper customer insight you need.

That’s why Future Now developed Persuasion Architectureâ„¢ (click to download the white paper). The methodology gives you deeper insight into your customers and allows you to see your website through their eyes. We do this by creating customer personas.

Personas allow you to view your site through the eyes not of your “average” customer, but from the viewpoint of different customer buying modalities taking into account different needs, motivations, knowledge levels, and goals. What one customer likes may actually turn off another customer. One customer may only need one question answered; another may need lots of questions answered.

In my experience, personas are by far the best way to truly look at your website from your customer’s idiosyncratic points of view. Plus, it takes into account different points of view and allows you map out what’s missing–and what “could be.”

EXAMPLE: If you’re a wireless company selling phones on the Internet, customer personas will have differing buying needs. Some are very knowledgeable about these phones. Some are not as knowledgeable. Some care about having lots of cool features like Internet access, taking pictures, etc. Another persona may care about personalized ringtones. Read about my experience with Verizon Wireless to get a sense of how what’s missing is actually causing a high POF.

To sum it all up: Use the suggestions above to gain insight into what you’re currently doing that’s causing a high POF. If you want to know what you’re NOT doing that is causing a high POF, consider creating personas to give you the deeper insight that data and analytics can’t provide.