Driving home that night from the hospital brought memories of my Mom and Dad and their great words of wisdom around parenting. “Your job as a parent is to screw up your child the least possible.” We are human and we are going to make mistakes; no child, no parent is perfect. It’s easy to look back and see where we made those poor decisions but the value comes when you start identifying those things “in the moment” and are able to make the changes so as not to repeat the past. It isn’t uncommon to find a first time parent who took the time to read the books, or take the classes on the grand theory of parenting only to be rudely awakened at the “real-time results.”

So why am I providing you with parenting advice on GrokDotCom? Because the lesson applies equally to your online marketing efforts. You’ll screw up and just like we shared during the “Survival of the Fittest” session to succeed you need to learn to be nimble and make changes on the fly. The key is to plan on optimizing, you don’t succeed with a set it and leave it mentality. What’s your plan for continuous improvement?

Join me in wishing Matthew much success in his life and in hoping I screw up as little as possible.

Here’s my take on some of the stages in developing an optimization culture:

• Acceptance – this is the stage where a business realizes that Optimization has value, and in order to reap the rewards, the status quo isn’t going to work.  Something additional has to be done, which calls for some combination of the following: a shift in focus, additional resources, new tools, and working with outside experts.
• Testing the Waters – this is the stage where the business starts testing and optimizing, and often gets some big wins just by making minor changes to their site, or removing basic conversion roadblocks.
• Infatuation – after getting some wins from “low hanging fruit,” our clients sometimes become fixated on testing and optimization.  They check their test dashboards multiple times a day, they cheer when they see Google Website Optimizer’s green bar, and they wring their hands when they see any yellow or red indicators.  The less-disciplined business will often lose focus at this point and miss out on all the fun/profit.
• Thinking About Resources – after things have settled down, there have been a few wins, and a few inconclusive tests (inconclusive changes still give you incredibly valuable data and piece of mind), the business starts to think about how to support an optimization process long-term.  They realize that this process isn’t free; it takes hard work and resources to create and administrate tests.  They evaluate their current teams and whether they can properly support a culture of continuous improvement.  This is a magnificent stage to witness, and once a business knows their resources, it’s much easier to stay OnTarget.
• Getting Analytical – once in the habit of optimization, we start to see clients question their assumptions, their vendors’ assumptions, and generally why the data is the way it is.  This is when things get fun.  Often, clients write me with test ideas or analysis of their very own, and I know that the training wheels have officially come off.
• The New Way of Doing Business – this stage shows our clients becoming calm and nonchalant when a site change gives them double or triple-digit improvements.  They are equally happy when a test has a negative or inconclusive impact, because it’s all part of the continuous improvement process.  They realize that even single-digit increases achieved on a regular basis will have incredible effects on their bottom line, like compounding interest in a bank account.

I hope this proves helpful, and I hope that more and more of our readers will develop an optization culture. Just please let us know if you need any help.

1. Improper Implementation

According to my friend, Stéphane Hamel the developer behind WASP, a FireFox plugin for detecting and reviewing web analytics implementations, nearly 100% of implementations are setup improperly. Common mistakes include: untagged pages, untagged or wrongly tagged transactions (i.e. transaction page is tagged like a regular page) and passing wrong values (especially for advanced tools like SiteCatalyst). In fact, several web analytics vendors websites also have these common errors.

To make sure your analytics don’t suffer you need to pick User Acceptance Tests (UAT) tests and re-run them specifically to look at tag quality (WASP can do a crawl that will work for content areas, but for transactions, there’s no better tests than actually running transactions to monitor the results.) Additionally, you should run continuous audits. Sites evolve and change, and the tagging quality suffers since different parts of the site may have been tagged at different times, etc.

2. No Goals Setup

The purpose of web analytics is to provide information about how well you are doing. Defining goals in the tool defines what game you are playing. How can you keep score without knowing where the goals are? Approximately 80%, of implementations have no goals setup. If you can’t define what is valuable to you, then how do expect to increase your results?

Even if you don’t do commerce you should have goals setup. Common non-commerce goals include tracking your inquiries, subscribers, white paper downloads, webinar attendees, etc. The key to success in setting up goals is aligning your goals with your customers’ goals.

3. No Segmentation

Repeat after me…”Not all traffic is equal.” Any analyst worth their weight in salt will tell you that the greatest insights don’t come from average and aggregated data but from slicing and dicing the data to produce intelligent segments. One of the most obvious is first time visitors versus repeat visitors (there are probably a couple of different segments in your repeat visitors too).

One of the features that thrilled me about the latest Google Analytics release is the ability to setup advanced segments. Bloggers surely know, that rss readers behave very differently than social media traffic. The reason FutureNow develops personas for our clients is to insure that we look at the website from these different perspectives/segments and measure them that way too.

4. Paying Too Much Attention to Irrelevant Data

“Web data is dirty data.” Never in the history of Analytics have we been able to collect so much information about visitor activity. This however leads to a lot of noise, due to things like cookie deletion, individuals browsing from multiple machines, different collection methods and definitions, etc. This is just one of the reason why you should never focus too much on data accuracy but on relative trends.

The second issue here is that all the people who rely on so many data points that they have no way of keeping an eye on them all. My core philosophy is that if you can’t relate all your reports back to how they fit into your financial statements then it should probably not be reporting it. Only focus on the metrics that you can actually control.

5. Not Setting up Milestone Events Documentation

With any luck, your business changes. You send out emails, run new campaigns (online and offline), make changes to your pages and other things that could impact your web results. However, most companies do a terrible job of documenting when these changes occurred and correlating them to their web analytics results. It would be great to have this information in your web analytics solution, but you could also run a private wiki that lets everyone on your team leave documentation about these changes. If your team using Google Analytics and the FireFox browser you can use the just released Google Analytics Notes.

6. Not Combining Quantitative Data with Qualitative Data

What I have learned in my 10 years plus of optimizing websites using customer-centric persona tools is that you need to be data driven but customer focused. If you forget to include Voice of Customer analytics in to your mix, you will tend to skew more to the cold data driven side (left side of the brain thinking) and neglect many of the opportunities on the softer voice of customer side (right side of the brain thinking). The data side is often focused on the what and how many, but the voice of customer side gives you additional insight into the why. Use tools like TeaLeaf, Bazaarvoice*, iPerceptions, Omniture Survey, ForeSee, and OpinionLab. Here is a great example of how to use web analytics and voice of customer analytics together. You can always start for free using 4Q from iPerceptions* to get some early wins.

7. Not Taking Action On the Data

Unless you are in the business of research, collecting data without acting on it may qualify for the definition of insanity (ever seen the underpants gnomes on South Park?). The purpose for investing in web analytics is to make data-driven, informed decisions and not just rely on gut instincts. The reason to invest in turning your data into insights is to become a smarter marketer and to produce better results. This is the very core of a Six Sigma approach to a continuous improvement process. Use the data to make changes to your website, feed your email campaigns and tools like Google Website Optimizer, Omniture’s Test & Target, CoreMetrics Intelligent Offer, or personalization tools like SiteBrand and start increasing your results.

Do you need help with your sinful ways?

* Disclosure: I am on the Advisory Board of Bazaarvoice and iPerceptions.

Click here to listen to Bryan Eisenberg chat with Avinash Kaushik

(To download the interview for use on your ipod, etc., right-click here and “save as”.)

In case you missed it, our first podcast in the series is with Bernardo de Albergaria, VP & GM of eCommerce, Citrix Online. We’ve also recorded two  “Always Be Testing” monthly webinars so far, the archived versions are now available.

If you had your copy of Always Be Testing, you’d know all about the “stinky” image in this post.

How much are you investing in analytics? My friend Mel Carson is asking on the Microsoft AdCenter Analytics blog.

In the UK last week Brand Republic reported that UK spend on search engine marketing would reach £2.75bn this year.

However, just a tiny fraction of that cash – £330m – was spent on the art of SEO or search engine optimisation. The lion’s share of web site owner’s budget went on paid search solutions like Google AdWords or Microsoft adCenter.

SEO is an essential and vital route to improving usability and search engine visibility of web sites. So with what appears to be a disproportionate amount of  time and money being allocated to this fine discipline, it made me wonder how much was being invested in web analytics.

When I say investment, I mean investment in people. Although many web analytics tools cost money to run, some are now free but you still need people to make sense of the data they provide.

Mel makes some great points and there are many reasons resources are not allocated to website optimization. In website optimization I am including search engine optimization, content optimization, making changes to the experience and testing.

Some of the issues are:

• Advertising is sexy and fixing websites in not.
• They haven’t yet bought in to how important good rankings are.
• They haven’t yet bought in to how important converting those visitors is.
• Web Analytics is viewed as a shared resource.
• There aren’t enough analysts around to interpret the data collected.
• Teams haven’t been set up to make changes based on the data received from whatever analysis exists .
• Budgets for making changes are considered capital expenses not operational expenses (Thanks @timlb).
• Companies have not realized the leveraged ROI that continuous optimization provides.
• Many corporate cultures prefer to throw money at a problem than do the hard work it takes to make improvements. Feel free to throw money my way
• The fact that many of the web analytics tools are free.  Managers can check off a little box on their list saying they do web analytics.

These are just some of the reasons. What are some of the other reasons? Please comment below.

It was the CEO of Omniture, Josh James, in January of 2005 who said “Web analytics can pay for itself with a single business improvement — so the real question is how quickly can companies make data-driven decisions? This willingness to change will ultimately dictate time to ROI.”

That is the point I will be addressing this week at New York University to the new students entering the Master of Science in Integrated Marketing. How quickly companies and make and act on data-driven decisions will be the main competitive edge over the next 10 years. Should it really take 11 months to respond to a YouTube video by one of your brand advocates?

Amazon has this culture of optimization.  If Borders or even Barnes and Nobles ever truly want to compete then they need to adopt it too. They need to get quick at making data-driven decisions and have a  process for continuous optimization.

What are you doing to change the speed of optimization and communication in your company? I’d love to chat with you about it.

Success on the web involves adopting a culture of continuous improvement. Which means plan (but remember good enough really is good enough), measure (get good at free then invest in more robust tools and analysis) and most importantly improve (transform your thinking from always being right to always be testing).

Let’s try selling optimization as the need for speed.  Moving fast is sexy and very profitable.

Click here to view the embedded video.

What obstacles do you face in getting your organization to adopt a continuous optimization process? Do they need to see more success stories like these?

Editors Note: If you want to learn more about marketing optimization and meet Ralph, Jim and Bryan, register for the eMetrics Marketing Optimization Summit in Washington DC, October 20-23rd. If you want, you can use discount code FN10 for a 10% discount.

You shouldn’t feel bad if this is your situation. It’s unfortunately quite common, as many of the people who attended Search Engine Strategies San Jose and the Web Analytics Association Base Camp confirmed for me in the last couple of weeks. As anyone who attended last year’s Emetrics Summit knows, there’s a real shortage of analysts out there — talented or otherwise. You can see it in job search queries for “web analytics jobs” like this one.

Finding this “free agent person” is like finding a wooden nickel. Not likely.

On the other hand, I’ve met many organizations where all they do is hire someone just to go through the reports, create pretty Excel or Flash presentations, then distribute the reports to a group of people. They should consider changing the name of this position to “reporter” because all they do is spread the news. Don’t worry. Many of the analytics companies are or should be developing web analytics widgets to replace the human reporter. I’m sure you can find something more valuable to do with these people, anyway.

So what can you do?

1. Learn to squeeze more of your current web analytics. Do something quick and actionable like use Google Website Optimizer to run some simple tests on your website and improve your conversion rate like our friends at Jigsaw Health did. This advice can earn you a raise or a promotion, so this week I’ll make time for two more free samples. If you contact me directly, I’d be happy to point out a simple test you could run on your site. Just ask Scott McClintock from Fujitsu how I helped him make thousands of dollars from one of these simple tests.

2. Stop your addiction for useless data. If the information is not actionable or tied to your bottom line ignore it for now. Focus on one key metric or report and focus on taking action based on the report. Practice getting really good at that alone, then move on. I could tell you story after story of companies that focused on a report company-wide and the success they have because of it.

3. Move away from the idea that you need tools, talent, then process, to process, people (talented or not) then tools. The process must be focused on business optimization or in other ways how you you make more revenue by helping customers get what they want so you can get what you want, more revenue. Let us know if you would be interested in attending a workshop that teaches web analytics without the analyst early next year.

How would you finish the line? Web analytics is like…

There are 2 ways to begin a Persona project:

1) Hire a firm to conduct research.

Level of difficulty: easy
Likelihood of success: minimal

Expect to cough up tens or even hundreds of thousands of dollars on this research–and the wise marketer would do everything in her power not to entertain discussions of ROI (at least positive) from this exercise. Expect the resulting research to create beautiful-sounding Personas and make excellent posters to put up on the wall. In some organizations, you may even expect a raise for a job well done, but you’ll profit more from selling all your company stock short. (Bryan chronicled this approach in his ClickZ column, but it’s worth diving into even further, because the underlying question marketer’s are asking when they hire a research firm is an understandable, but flawed one.)

The question being asked of the research is, “How do we know which types of people make up our audience?” Cough up the dough, create a survey, and you’ll find out something absurd, like your audience is made up of “Info-Driven types,” “Conquerors,” and “Browse-2-Buy” types. How did they determine that? They asked about past purchases, of course, and–naturally–those are good predictors of future behavior, right?

Let me know how that works out for you.

Our clients undoubtedly tire of hearing us over-communicate, “Believe what they do, not what they say they’ll do“. Why? It’s simple. People lie. Not intentionally per se, but between people telling you what they think you want to hear (in America, there’s a bias against being “wrong”), people telling you what they want to be perceived as (what they wish were the case), and finally, people telling you something they simply don’t know (the right brain makes the decisions, and the left brain articulates & rationalizes them, yet both sides of the brain “speak” in different languages. Ever played the telephone game?), it’s virtually impossible to separate the signal from the noise.

“Who makes up my audience?” isn’t the question to be concerned with; rather, “How will each different type of person approach and buy my product?” The smart marketer uses this last insight to align the sales process with their customers’ buying process.

Let’s look at a concrete example of why “who” makes up your audience is irrelevant, while understanding the “buying mode” they’re in is essential.

My mom is a Methodical personality type, meaning her preference dictates a logical process, and one that is rather deliberate in its pace. She works professionally as a bookkeeper and routinely catches oversights by the auditors of her books. She remarks with bewilderment that someone whose singular concern is maintaining hyper-accuracy of the data can so easily miss the details. Notice, she wouldn’t qualify the details as minute, though to many they would be. To a strong Methodical, no detail is too fine. When she buys, chances are she’ll ask 10 – 20 extra questions than most other buyers, and with each successful answer, she’ll gain a touch more confidence.

My preference shares her bias towards a logical process, but has a much faster pace; what we call a Competitive personality type. Whereas Methodicals need a sense of order (or structure) to their process to gain confidence over time, Competitives are perfectly comfortable living amongst the chaos, and letting intuition guide their decision making process. The Competitive type can quickly dismiss logical-sounding fluff (you know, the statistical correlations marketers present when they have no actual causation to report). Think like “The Donald,” and you’re probably closely resembling the Competitive’s approach. When he buys, he’s in a hurry, and just wants the bottom line.

The key word in the examples above, is preference. My mother doesn’t methodically choose where to get her nails done, or where to go for a special dinner. In both of those cases, she buys more experientially, favoring more of an emotional process, and eschewing her normal deliberate pace for a much quicker one. She’s quite comfortable giving it a whirl. After all, “How bad could it be”? (Spoken like a true Spontaneous type, she’s operating outside of her typical buying mode.)

I went to buy my first car right out of college and, despite my bias toward a logical process, did zero research on the ‘net–and never checked out a consumer report. I also didn’t use my typical fast pace; I was much more deliberate. I talked to other people who’d owned the car previously and asked for their opinions and experiences. I considered the car to be an extension of my personal brand. My process was almost purely emotional and, with the deliberate pace, was the complete opposite of my typical buying preference.

Had the manufacturer done market research and decided Competitive types were their #1 audience segment, what would they have done? Built a micro-site catering only to fast-paced, logical thinkers. If they did, the conversion rate would’ve likely been the same anemic 2.4% we see today (because, after all, that’s what most sites today do: cater to one type of person, usually resembling the CEO/founder or IT professional who put the site together in the first place).

The point is, knowing your audience’s type doesn’t tell you which mode they’ll be in once they buy your product. That’s what you want to know and, unfortunately, research can’t tell you the answer to that question. If it can, it’s totally different research than anyone has ever done before. It involves using live test subjects, and not in some contrived listening lab. It involves designing the experiment so that the subjects don’t know they’re participating, they’re actually operating according to their own motivations. It involves making the experience become the experiment.

Planning the customer experience in advance, so you can hypothesize motivations, will drive their buying process (read: what mode they’ll be in). Once you’ve properly accounted for motivations, you can test their actual behavior–in a real environment–thus proving your assumptions about their motivations and optimizing the experience accordingly. The level of difficulty is far higher than simply hiring a firm to conduct research, but the likelihood of success is infinitely higher. And there’s a process to it, so you don’t have to bite off the entire approach in one sitting. This process leads me back to where I started, the second way to get going on Personas.

To be continued . . .

[Read Part 2 to learn how you can build Personas from the ground up without costly research, and build in the feedback loop necessary to know where you're right and where you need to focus additional energy.]

Most people will agree that you need three things to extract value from web analytics:

1. You must have clean, not accurate (that will always be a challenge), data.
2. You must have a talented person who can convert that data and into insight.
3. You must have a talented person who can absorb that insight and act on it..

And you’ll need to follow this process over and over again to get continuous improvement. This is what everybody agrees to be the formula. The truth is that this ONLY works when you have all 3 ingredients.

It’s not easy to find all three, right? There are only a few handfuls of companies that have managed to find all the talent. I wonder how long they can manage to retain it. As Anil points out, there are plenty of people looking to hire these people away from you.

Anyone who’s been in business long enough knows it’s virtually impossible to scale talent significantly. The secret in every industry category is process, people, then tools. Why do so many companies do this in reverse? They buy the tools or tactic du jour (a shiny object problem), then they try to hire someone (that person will “know”) and they never get far enough to actually develop process or get value (the tool didn’t work out).

Think of web analytics as accounting for the Web. Most companies would go out of business (or be unhappily popular with the IRS) if they looked for talent and disregarded standard accounting processes. When everyone is trained in the right process, you can always try and find people who are more talented in accounting. If you can’t find your own accounting genius, then at least you can substitute with someone familiar with the process to get the job done–even if it’s not very creative. Ideally, all your processes should be designed to be utilized by those with less talent, so they can scale.

The reason we at Future Now developed Persuasion Architecture™ (pdf)–a Six Sigma-like process that provides blueprints to plan, measure, and improve your online sales and marketing–is because after years of working with clients optimizing their sites with web analytics and A/B & multivariate testing tools, we realized clients would hit a plateau where they could not break through the optimization brick wall. It didn’t matter if they were retail, B2B, B2C, media or service organizations. They all suffered the same fate.

The main reason for this fate is not because they didn’t have the tools or the talent, but because they didn’t have processes in place to make sure that every bit of marketing they wanted to measure was planned and implemented with measurement in mind. They needed to sort out “fine” signal from noise. When the signal was loud and clear, the low hanging fruit of optimization, it was easier to detect. But without a process to define what signal actually means up-front, it becomes increasingly difficult to listen for it.

Eric Peterson was the first to write about Persuasion Architecture in a book called Web Analytics Demystified. And I’m continuously grateful to Jim Sterne for asking us to keep trying to explain it to his audiences at the Emetrics Summits. Although we haven’t always done the best job explaining it, Persuasion Architecture solves this critical “process, people, tools” dilemma.

I’ve written volumes on Persuasion Architecture; but because it’s made up of so many disciplines, people have a hard time grasping it without actually seeing it. I’m going to summarize the process again:

• People do things for their own reasons. So, first clarify what makes different kinds of people click. This is segmentation based on psychographics and linguistic preferences, since that is how people actually navigate and make decisions on the web. (Uncover your Personas)
• Model a blueprint of those clicks to plan the experience that helps your Personas buy the way they want to. This is a click-based experience model, unlike the wireframes people use, but more similar to the way developers plan interaction states in software.
• Build your website from that model which defines the responsibilities of every word, pixel and click. This is where it’s valuable to have talented marketing and creative staff or resources. Could you go to your site’s homepage now, click on any link and then tell me why any phrase, link or image exists? Which market segment should it appeal to? What action do you hope people in that segment will take after reading those words, seeing that image or clicking that hyperlink?
• Once every business decision and click is documented in the model, development times can decrease by over 30%. You’ll recover more than the time spent by reducing the number of iterations copywriters, designers and developers go through in more traditional website design.
• Learn from every click you’ve modeled to see if your Personas click as you expected (the virtually neglected but real value of web analytics).
• If the clicks aren’t what you expected, continuously improve what to click and what the clicks say. You do this by first testing your execution (try variations of the same headlines, copy or images to accomplish the same objectives you specified in the model in different styles or formats); if you try several variations and you don’t move the needle, you should re-examine the assumptions that went into defining that particular piece of the overall objective.

Like accounting, it’s deliberate, and less exciting creatively, but anyone can do it. And anyone can then use web analytics to continuously improve their web marketing. Isn’t that what companies are looking for?

I don’t mean to discourage you but, rather, to help you understand that as long as you aren’t converting 100% of your visitors, there’s room for ongoing improvement and room to make more money or generate more leads.

No one has a perfect sales process online that is mapped out to every individual, idiosyncratic buying process of every potential customer. You can’t just fix your site in one shot and say it’s perfect; it’s literally impossible to do so.

To put this in perspective, most websites are converting less than 3% of their visitors and are therefore pushing away 97% or more of their visitors. If they can just convert a slightly larger percentage of their visitors, think about the dollars this opportunity translates into.

There will always be new questions you realize your customers are asking, that you may not be answering on your site in the appropriate places. You need to be able to translate those findings into your web site in the appropriate places, where the visitors needs to find that information.

Where to Get Started

You can start improving your website’s conversion rate by thinking about how you’re going to find out where the conversion and persuasion challenges lie within your site.

Before you do anything else, take a look at your analytics program to check the site’s performance and to try to understand what’s happening throughout the site. Although you’re likely tracking unplanned scent trails, your analytics can still give you an idea of where things are broken. Even basic analytics information at various key points in the site can help you better understand how to give the site’s visitors what they want. It’s the first baby steps toward analyzing your website.

Instead of looking at your overall conversion rate, look at it on a micro level and track each individual click to see how you can improve micro-conversions.

• Where is your traffic coming from?
• Where is this traffic landing on your site?
• Once the traffic lands on your main landing pages, what are the most common links they are clicking on next?
• Once the visitors click through from the landing pages, to the most commonly clicked pages, what is the drop off rate on these pages?
• Are you persuading them to take action with a clear call to action on these pages and giving them other text links to move forward or are they leaving your site because they don’t have any scent to follow?

Persuasion Tip: If you can’t figure out what the most common questions people are asking when they come to your site are, ask your customer service reps what questions people are calling in with. Go onto message boards to see what people are saying in your industry. And go to your competitors sites and see how they’re funneling visitors around.

Take a look at your shopping cart and/or forms, and ask yourself:

• What is the drop-off rate for those individuals who are entering your shopping cart but not purchasing?

This will give you an indication of whether you’re making it easy for visitor to complete purchases or become leads.

Be the investigator. If your visitors are not taking the actions you want them to, look at the micro landscape and find out why that might be.