I’ve been getting a lot of nice emails from recruiters lately, and I really appreciate everyone’s interest. It makes me feel special!

But I’m sorry to tell you that I really don’t want a “web analytics job.” Not now, not ever in my future. And neither do your best analytics people.

Web analytics jobs, as they are today, are about learning (necessary learning). They are about developing skills and a methodology for decision making that is based on data. They are about understanding the technology and starting to appreciate exactly how little the technology actually does for us! They are about helping other departments make decisions, and helping drive change and advancement on the web site and in the business.

And I love all of these things, but…

At some point, you leave college, you leave boot camp, you leave law school or SEAL training, and the real world begins. You use all of your learning to build processes and models of how to deal with the real world, which is much more dynamic and interesting than the academics led you to believe. It’s a world that’s driven by human interaction, in addition to data, and it comes with politics, friction between smart people, bad decisions made for good reasons, and a whole basket of issues (including bullets, either PowerPoint or lead, depending on whether you went to SEAL training or got your MBA; these bullets have approximately the same lethality in both cases) you never learned about in your training. That world, the real world, is the world of business. It’s a world where we can’t always make the right choices or hide behind data and call people morons for not doing the exact thing we would have done. The training was essential — it couldn’t have been skipped if you want to survive out here — but it was incomplete and you know it.

In your training, you learned about usability, you learned about testing, implementation, IT, architecture, conversions, what makes things “work.” And while you were in training, you helped a lot of people out. When you get out, though, you take on risk, and you learn that the only thing that matters is cash flow: the quintessential math of revenue minus cost, and how that drives greed, fear, decisions, people, and countries. You use the arsenal of tools you learned about in your training to reach that single goal.

Why is the training valuable? Because not everyone had it. Web analytics people get angry that people don’t listen to them when they have the data and know how to come to the table with the most relevant, least biased recommendations. There are people in decision-making positions that did not have this training, or even some of it, and they aren’t qualified, in your opinion. There are opponents on the battlefield who did not perfect the basics and did not round out their talents. And in the long run, you have a huge advantage because of your training. Use it, but realize that using it means leaving the nest and venturing out into the wilderness.

Web analytics people — the good ones — are crafted to be some of the best businesspeople out there. They are capable of taking emotion out of difficult decisions, but hopefully understand the humanity involved in working with people, too. They have been trained in a number of arts. They can handle a number of questions you previously relied on specialists to answer (who can now work on complex problems, rather than simple questions), because they’ve had to learn, monitor, and interpret the effects of every single tactical discipline that comprises the final texture of a web site and the business it represents. And who else in the organization comes to the table with less bias? Nobody.

The good ones want to begin shifting into this strange, amorphous role of digital strategists: those general practitioners of the internet who can patch up the small wounds, interpret complex issues that span multiple disciplines and recruit the relevant specialists to execute against a central strategy. The “hubs” who can be trusted to translate strategy into tactics without bias relevant to their particular goals (present in marketing, HR, IT, sales, etc. leadership — which isn’t their fault, it’s how their compensation is structured!).

We don’t want to be the digital strategists who point on the map to where we should go; we want to be shepherds, literally walking the business to the destination, taking our place in the action, being present, monitoring progress, and redirecting the tactics when they start to spread too far apart.

This is our greatest value and the eventual destination of every great analyst. They will walk you to your greener pastures.

Yes, my head is in the clouds, but don’t you wish you had one of these people where you worked? You probably already do.

I keep having to come back to the same conclusion when trying to win people over or convince them of an idea: it’s not their fault.

Businesses are a tough animal. They’re tough because they have to live somewhere on this spectrum of control and fantasy, where one end is an organized, over-specialized, decisions-by-committee setup and the other is a highly-entrepreneurial, strategically-driven and trusting business. Most companies start on the second end of the spectrum, but as they grow, they get pushed toward specialization, process, and bureaucracy. And I’m not sure if that’s preventable.

Where the rubber meets the road in our industry is how web analytics, usability, architecture, etc. are handled. I got a job posting sent by a recruiter the other day, and these were the requirements and outputs for the role:

• 3-5 years Omniture experience
• Will create dashboards for departments
• Host learning sessions and have 1:1 training with other potential tool users
• Will maintain implementation of tool and work with tech on implementation for new content
• Will find good candidates for A/B and multivariate testing
• Able to collaborate strategically with other departments
• Organized, detail-oriented, and focused

I actually hate job descriptions like this. I know that this sounds like a dead bullseye for a web analyst, but it’s not, because there is no ownership of outcomes. This is a handmade description for yet another propellerhead analyst who will sit around and run reports for people, get in arguments with other people (or those same people), “agree to disagree” with other departments, and will eventually call everyone else an idiot and will recede into their cave before ultimately quitting for a director-level position at a different, big, resume-enhancing company where the process will repeat itself. Why? Because in 9/10 meetings this person will have, they’ll be arguing logic against opinion: this role does not empower them to tell other people that in that particular case, they are just not right.

This job description is for a gear in a machine, and that’s why I hate it. It’s actually a pretty good list of responsibilities or list of things to learn for an entry-level or mid-level web analytics job, but for a passionate and experienced analyst, there is no pot of gold at the end of this rainbow. Where is the ownership? Where is the leadership? Where is the promise or opportunity to really leave some fingerprints on this brand?

You may say that if you do the above tasks, you will make a difference. But that’s hoping. They should be hiring a sheriff. They are hiring a deputy.

But it’s not their fault.

It’s not their fault because a good position for a web analytics person does not exist in the companies that can use these people most. The bigger the company, the more important a small difference becomes. For a site with 10,000 visits a month, an analytics person would have to improve conversion by double-digit percentages to scarcely pay for themselves. For Wal Mart, moving the conversion needle a tenth of a percent probably pays their lifetime salary in a week. But the problem at Wal Mart (and no, I have no prior experience with Wal Mart, so I’m just guessing) is that this person’s decisions have to go through 100 other people and their opinions before anyone ever even thinks about acting. And the job description is built around these limitations. So it’s not their fault.

The effective web analytics person knows usability, they know some design, they know information architecture, they know HTML, they are good communicators and can thusly write good web copy, and ultimately they are businesspeople who realize the purpose behind all of these crafts is cash flow: they probably know literally everything needed to make the ship move. But they aren’t able to move aircraft carriers. Rather than being careful, politically aware employees, effective analytics people are data-driven, quickdraw decision makers because they have two key assets:

1. Cold, hard facts in the form of data (and I don’t mean just Omniture data)
2. The ability to not have to decide: they can TEST

But there is nothing about big companies and aircraft carriers that gives a flying monkey poo about either of these. Big companies are ruled by coalitions of opinions, meetings, conference calls, and semi-educated executives. Data is actually a threat. Data is what gets people fired in big companies, not what gets them bonuses. Data is scary. But again, it’s exactly how it’s been built to ensure accountability and measurement. So it’s not their fault.  Honestly! It’s not the executive’s fault that he doesn’t understand the fundamentals: it’s how the system was built, and it’s built in such a way that disallows his education on what you consider fundamentals.

This might be throwing my arms up in the air, but I am just wondering about our future. My personal vision for web analytics is an entrusted resource that makes both subtle and quantum shifts in business. I hope that was evident in my definition of web analytics. But I don’t know if I see it coming. In reading Seth Godin’s Linchpin, I’m having trouble figuring out whether I’m the zealot or the Linchpin. Am I fighting the real world, or am I able to eventually break through and change it? Didn’t management consulting companies face the same skepticism? You’re going to come in here and tell me how to run my business better than I can?

Yes, we hope to!

P.S. People should make their own dashboards because the learning process involved is a hell of a lot more valuable than the dashboard ever will be. And that’s all I’ve got to say about that.

In my presentation yesterday (thanks to everyone who came!), I mentioned a new definition of web analytics after seeing how lame the definition on wikipedia is:

Wikipedia: “web analytics”

Web analytics is the measurement, collection, analysis and reporting of internet data for purposes of understanding and optimizing web usage.

It’s not that this definition is wrong. It’s more or less technically correct, but it doesn’t focus on output, value, the weight of the actions associated (measurement, collection, analysis, reporting), and it’s just that it’s not marketable. For the purposes of wikipedia and the fact that the definition has to fit tools, people, an industry, and a practice, well…I can live with it there. But I was disturbed that “analysis” was only one of four verbs that fit the description, so I was hoping for an inspiring definition of “analysis”:

Wikipedia: “analysis”

Analysis is the process of breaking a complex topic or substance into smaller parts to gain a better understanding of it.

Fail. I’m equally disappointed in this one. While this may again be true from the analyst’s perspective, I don’t think it captures the output or the value of analysis at all, nor does it accurately describe the true conclusion of analysis. Yes, analysis may consist of breaking things down into smaller pieces, but that is not what helps us understand things. The understanding comes once you begin to realize the ecosystem that is in place: how these various smaller pieces interact and influence each other.

And the real output of analysis is communication in simple terms, not understanding. It’s the spreading of understanding, in our business. It’s wonderful for us (the practitioners) to analyze and understand things, but completely wasted if we’re not able to convey this understanding to others in a variety of simpler languages specific to the audience.

So, here’s my new and improved (at least according to me) definition of web analytics that we analysts should use to market ourselves to executives:

Web analytics is an unbiased discipline that actively finds and validates business opportunities by studying the habits and behavior of users, competitors, and trends in the “big picture”.

This describes what web analytics is in terms of output and value (and process), not just in terms of execution. The reason I don’t like the wikipedia definition is because it does not touch at all on context or purpose, and to me almost comes across sounding like on-demand operational overhead, rather than a proactive, value-generating process. The context/purpose of web analytics is its service to a business: the identification and validation of business opportunities (both for the web and in other areas). I completely disagree with the notion that the output of web analysis is always web-centric, so I see no reason whatsoever to say that the purpose of web analytics is optimizing web usage. The output can be thousands of things from offline advertising, to pricing, to shipping carriers, to CMS re-evaluations, to compensation plans, to organizational charts and workflow and process, and on and on. Most often, the output probably will be web-centric, but defining web analytics as web-centric makes us far less valuable than we are capable of being.

Sorry…sometimes I get a bit over-passionate

It also includes the analysis of competitors, which Avinash has covered in incredible depth (listen to him!), and of course a constant ear on the rail of the big picture. The “big picture” really describes the greater ecosystem of both the Internet and your large-scale business tides. Without paying attention to the fact that the housing market is tanking, that twitter has exploded as a news source (or untamed brand trashing arena) in your industry, or that the price of production at your company has increased 20%, all of this “webby” stuff we bury our faces in all day really doesn’t matter. We are accountable to context, and this “big picture” view is where stuff like @comcastcares comes from, or should come from, at least. Juicy stuff.

Finally, saying that web analytics is for the purpose of improving/optimizing web usage or specific offline changes is really only a small part of the story. As I wrote in a Search Engine Land post, “The Real Value of Web Analytics,” making your site a better, more conversion-prone web asset is a wonderful outcome of web analytics, but the problem is that most companies are completely paralyzed by operational inefficiencies and departments that don’t work as a team. The best possible output of web analytics for most companies is what happens when they watch themselves struggle to actually execute.

Just like how doctors can put a dye in your blood to see valve issues and leaks in your heart, you can watch your company execute and see the issues in your processes and teams, which can teach you how to improve your company. When you can improve operations, you can improve your web site at the speed of light, and annihilate the competition.

Give it some thought. And write some of those thoughts here in the comments!

I’m a metaphor guy. Here’s hoping you like them, too. I think they do a great job of explaining things without sounding whiny and desperate, and that’s great because the world of web analytics is getting very whiny and desperate for the recognition and authority we think we deserve.

So, do we?

Web Analytics-ology

What happens when something hurts, you have a cold, or you’re a generally weak person according to Tom Cruise? You go to your general practitioner or internist to see what’s up.

When you get there, you’ll start talking about what you’re feeling, the doctor will hit your knee and look in your ear, and he’ll figure out what’s going wrong. If you have something seriously wrong, he’ll send you to a specialist, but most of the time, he can recommend a solution to your problem that will put your body back on course. If the internist sees something wrong with your ear and fixes it, the ear doctor down the hall doesn’t throw a hissy fit and slash the MD’s tires. If the internist gives you a splint for a sprained wrist, no orthopedic surgeon goes to their boss whining about how the internist is trying to do their job. They trust that the internist knows enough to treat the patient well. And they do, most of the time.

So let’s think about what a day in the life of a large web operation looks like. What happens when the web analytics person tries to make recommendations on how to change the color and location of the call to action on a landing page? Usability and designer folks go ape shit. What happens when they find that the paid search campaign is blowing budget on a non-converting keyword, recommending that we eliminate it from the campaign? Nuclear war with marketing. How about when they realize that there’s a major browser incompatibility and they recommend a few changes to the CSS and HTML? You’re about to get shivved by a programmer.

Where does this territorial nature come from? Well, for the first time, let’s stop blaming all of these specialists and look inward.  Do we really know usability? Do we really know design? HTML? The answer is probably sort-of, but we haven’t had the years of training that doctors go through, so the real answer is that we really have more opinions than knowledge, in all likelihood. And that drives these specialists nuts. The real truth is that the average analyst creates more work for these people, rather than reducing work that doesn’t require the full gamut of the specialists’ skill sets, like the internist does.

I’ve said before that web analytics people aren’t specialists, and it’s true. But I don’t think as a whole, we’re good enough yet to call ourselves generalists. We need training. We need to get out of the specialist mentality of training harder and harder at what we’re already good at, and we need to get into the mentality where we train our weaknesses, researching usability, design principles, HTML, PHP, javascript, etc. etc. We also need to study business fundamentals, marketing principles, branding, corporate communication, SEO, and more. Knowing a little about all of these things will make analysts much more valuable than knowing statistics, forecasting models, and all of that mess ever will. There are no shortage of specialists in the world that can handle that work, and we’ll bring them in when they’re needed. But there’s an enormous shortage of generalists who can direct traffic and questions to the right places, and clean the easy messes up themselves.

I was talking back and forth with someone I’ve begun working with about Google’s future: are they going to take over the world?  How can they give analytics away for free?  What does the future look like?

I was writing a reply when I realized this might be an interesting thing to explore here.  From a business standpoint, what’s going on here?  Are we seeing a shift in how businesses, even publicly-traded ones, treat cash flow? Google seems to make a lot of questionable profitability decisions.  But should we really care?

I think we’ve seen Google consistently give away products that support their key revenue sources.  They know that paid search works wonders, so providing a tool like analytics on a search stipend is a smart move – it’s a tool that proves the value of search with increased depth, and allows customers to compare search ROI to other channels that compete for budget. Also, Google is right to think that people have a right to understand what’s happening on their web sites for free.  It will get thousands of SMBs to consider and test marketing [that Google knows will be like crack for them] spends to increase their traffic and sales.  Without a free option to measure, it’s likely that significantly fewer business would take that investment risk. Plus, it builds on the friendship model: people love your brand, so your brand will thrive. And, of course, there is an upsell opportunity for Urchin.

Culturally, Google was founded on free tools without any real, concrete plans to monetize something the guys thought would make the world a better place.  Shortly thereafter, text ads were put in use and the rest is history, from a business standpoint. 90% of their revenue comes from paid search, but this hasn’t changed their roots that providing the internet the best tools for free will keep people around.  And one of Google’s key differentiators is that, from the moment they began, their pace of product creation and innovation has not slowed or been stymied by the business’s needs to find profit models to fit every line of work.  Asking Google to monetize their other products would be like asking the Friends writers to monetize every line in the script.  They know they don’t have to do it because their product has so much gravity, it will support other, more natural revenue sources that don’t risk ruining the fabric of that attraction in the first place.

If anything, pace has increased as Google [labs] has put out / bought / refined tools that permeate our day-to-day more and more.  This is why gmail became so dominant over Yahoo mail.  While Yahoo was busy figuring out how to sell display ads and make weather and news partnerships to layer on their very good mail service, Google stripped it down to the basics and made an online client that gets out of your way.  Once they did that, they made it better and better at a pace Yahoo found impossible to match.  And all of these gmail users are now using Google, and in many cases, about to subscribe to Google’s enterprise mail and calendaring systems.  Potentially a big attack on Microsoft and an eventual move into enterprise-level data management, sourced storage, SaaS hosting, etc. solutions?

I guess the point is that Google realizes that they don’t have to over-think the business side of things so long as they maintain / grow their audience with that gravity.  While it’s true that at their scale, basis points mean millions of dollars, I think they’ve realized that the process that goes into the management of basis points affects the quality and pace of their output, representing an enormous opportunity cost in terms of audience.

While I don’t know if this represents a phase shift in pushing Wall Street’s juice-squeezing mentality to the curb, I do think that an extreme, corporate value-creation mentality would be the beginning of the end for Google.  Trying to talk to a creative programmer about profitability is like trying to talk to a banker about creativity.  They both think that if they build it, people will come.  And while they’re both right, the age we’re in is siding with Mark Zuckerberg, Steve Chen, Jeff Bezos, Jack Dorsey and other people who are creating incredible magnetism on the internet, perhaps with some disregard to how they’re going to pay the rent. While you might argue that Bezos is a hell of a business person, you might also argue that his focus on business hasn’t interfered with his focus on what made Amazon important in the first place.

I’d never say that we should stop worrying about monetizing business lines, but I do think that Google might be on to something that many businesses can learn from.  It might just be okay for successful businesses to do great things for their customers and prospects to increase loyalty, reach, and brand love without any direct attempt to derive a return. And I’m not talking about giving away pens, golf towels, shirts, USB drives or notepads. Why shouldn’t BMW visit your city and teach owners and non-owners alike how to drive race-ready cars for a weekend, for free?  Because they’re giving up profits.  But I would gladly give up today’s profits for tomorrow’s, if today’s were sufficient.  BMW, are you listening?  This is a really good idea.

Ever have one of those startling moments of clarity when you suddenly realize that everything – literally EVERYTHING – we’re trying isn’t working?  Ever had one of those moments last three years? Oh, me neither.  I was just asking.

I think we need to realize that now is the time to take a step back and look at what we’re doing on the internet. What better time to worry a little less about the risk of putting a company on cruise control than when everything is out of our hands anyhow? Now, I’m not in any way advocating taking our eyes off the road; I’m just saying let’s just take our attention off of trying to work the pedals and control everything one piece at a time to reflect on what the hell is happening to us.

We’ve just gone through a long period of excess where every decision was right and newcomers to the stage were getting standing ovations.  And we know now that it was quickly followed by a stage where all of our mistakes came back to haunt us.  A quick drive through town shows us that: a lot of businesses with the lights out.

There are things I think we need to start thinking / worrying / crying about today.  And I mean TODAY.  Here are two of them, with more to come later.

1. Do the people I trust really know what they’re talking about? Are they holding that against me?

Your agencies.  Your employees.  Your neighbor who “fixed” your lawnmower.  Ever feel like every time you find expertise or help, everything goes to hell? There is a reason for it. There’s even a phrase for it.  You’re being bullshitted.

There are three types of internet professionals:

1. People who genuinely know what they’re talking about and are arrogant, lazy jackasses because of it (“It will take 3 months to develop that software [while I play Freecell].“)
2. People who are full of it (“We guarantee top position in Google.“)
3. People who genuinely care (“We are on it. We will do everything we can to succeed.“)

In essence, you have competence alone (Usain Bolt), work ethic alone (Bernie Madoff), or a combination of the two (Bill Gates, Steve Jobs, Jeff Bezos, Tiger Woods, Michael Jordan, Jesus).  How do you picture these different people in your mind? Can you see that some of your employees / agencies / neighbors strike a similar chord with you?  What category do they fall into?  We all hate both Usain and Bernie, and while we might grimace at a healthy ego in people like Steve Jobs and Tiger, they’ve earned it and we respect them for it.  And they’ll continue to earn it rather than resting on their accomplishments.

I used to work at an agency that doubled in size and earned its true stripes in the industry.  We celebrated the managing director of the office for facilitating this achievement, but everyone couldn’t stand this person because this person was faking their way through it and taking credit for some of my very talented colleagues’ hard work.  Sure, we doubled in size under this person’s watch.  But what would we have done if the role were filled by Warren Buffet? But this person was content with their success and felt that knowing what you’re doing isn’t necessary if you’re succeeding.

But success does not equal success.  A high school running back can set a school record, but never go to the NFL.  We have to all remember that we have a long way to go and a lot to learn.  We can rest after our 10th interview in Fortune Magazine.

Fire all of your Usains and Bernies. Today. And get feedback so you know who these people are.  Bernie Madoff scammed some of the smartest and most successful people in America.  Don’t be so egotistical as to think you aren’t being fooled, too. When you hire the next one (sometimes they’re hard to identify in interviews and you find out later), fire them once it becomes apparent. Period. You’re actually doing them a favor – this is the only way they will learn that change is necessary. Their egos flare every time they get away with their parlor tricks, so firing is the only way to teach.

2. Do I have an actual vision for my web site? Do I know the difference between goals, objectives, strategies, and tactics?

Generally, I reject this sort of corporate speak and feel like it puts us in a death spiral of executive blabber, but this part is important.  It’s how you plan and achieve.  If you don’t have a plan for your business, everything is an accident, both success and failure.

Goals, e.g., “Attract the most qualified users to the site and convert them with maximal efficiency.”

• Measurable: NO.  Seriously. Get over it.
• Scope: Large

Objectives, e.g., “Increase our web marketing ROI by 25% / Increase conversion rate by 10%.”

• Measurable: YES. Woohoo!
• Scope: Large

Strategies, e.g., “Understand the value of various traffic sources and optimize both spend and landing pages to increase conversion.”

• Measurable: NO!
• Scope: Small/Medium!  Strategies are NOT at the company/site level.  They are discrete to certain goals and objectives and qualitatively describe the methods employed to achieve.

Tactics, e.g., “Identify top 5 SEO landing pages and align copy with popular keywords being used. Remove extraneous form fields. Test ’sale’ creative in PPC ads. Conduct A/B test of the ‘Buy Now’ button color.”

• Measurable: YES! Think of measurement as checkboxes with results: I did this and here’s what happened.
• Scope: Small

By understanding what each one of these things are, we can write down what we want to achieve, how we want to achieve it, how we know whether we’ve achieved it, and how we know what helped / hurt us in achieving it. I can’t think of any better way to understand what the hell is going on.

Please, share some of your experiences!

Here’s an exercise that will make you a better analyst and a better businessperson.  Even if you’re not the “web analytics guy,” do this anyhow and translate it to how you think about your web site.

Go to the mall and prop yourself down on a bench in front of of a store (how about the Apple store, because it has glass windows and you can usually tell what someone bought. And if you get the hankering to buy something, as a shareholder, I’d appreciate it).  What do you see?  People walk in, mill about inside, and then walk out, some of whom are carrying boxes and bags full of their shiny new toys.

If you were to measure the “engagement” of the Apple store, what would it look like? You’d have metrics for entries, metrics for exits, and metrics for conversion rates.  If you had particularly good eyesight, you might even be able to tell how many products people looked at, what those products were, how long they played with them, whether they talked to a salesperson, and infer whether that “touchy-feely” experience influenced (or was indicative of) purchase potential.  If someone was passing out bright orange flyers at the entrance of the mall, you could also see how successful that was at driving traffic to the store (they’d be carrying them).  And if you were to come up with a set of metrics to outline, “Apple Store Performance,” it would probably look like this:

Store Use:

• Entries
• Entries with flyers
• Time in store

Interactions:

• iPod views, duration
• Laptop views, duration
• Desktop views, duration
• % Talked to salesperson, duration

Conversion:

• iPod sales
• Laptop sales
• Desktop sales
• Exits

So you get it – we have a bunch of simple metrics that we can start to tie together.  Were people with orange flyers more likely to buy? Were people who talked to a salesperson longer than 4 minutes more likely to buy?  Were people that used the iPod for longer than 1 minute more likely to buy? You get it.  What we’re trying to figure out is what’s happening in the middle, because we know that the middle determines whether people walk out with armfulls of shareholder value.

We also know that handing out those flyers is getting more people in the top of the funnel, which, if we can preserve conversion rates, means more buyers coming out of the bottom of the funnel.  We may even choose to have salespeople treat orange flyer holders differently.

So let’s start translating:

• Entries = Visits
• Flyers = Paid Search, Natural Search, Display, Email campaigns
• Views, durations = Page Views, Product Views, “engagement” (whatever that means)
• Sales = Conversions

So my question is this: once we do this translation, are we still looking at what happens in the middle? Or more importantly, are we still doing something about what we’re seeing in the middle?  The answer is usually no.

In a retail store, the employees polish the iPods, train employees how to better talk to customers, and physically re-arrange the store in an effort to make the middle more effective.  Online, we watch, objectively, as if we are a third party being.  We measure.  We say that the orange pamphlets aren’t working because they’re not walking out with bags, but we didn’t notice that the salesperson assigned to talk to the orange pamphlet holders has huge pit stans and smells like Taco Bell.  We’re seeing that he’s talking to people for over 3.5 minutes, the magic number that increases conversion rate, but we’re not seeing that for the first minute, he’s talking about how hung over he is.  We’re boiling qualitative things into quantitative metrics in an effort to understand what works, and we’re missing the whole point: we’re getting this information to change it, not just to know it.

In the store, this guy’s hygiene is obvious.  Online, we might not realize the qualitative aspects of a landing page make a keyword with a high click-through-rate a repulsive experience when the same page does great for another keyword.  What I’m talking about is especially true for your marketing efforts – paid search, SEO, display, email, social, etc.  If you’re not thinking of the middle (judging a media by its endpoints, cost and return), you’re not learning anything.  Your lowest performing media could be your best performing media if you changed a few things.  But to know what to change, you have to be looking at the middle.

When Avinash talks about the 90/10 rule, I believe this is where he’s going with it.  We’ve created huge, sophisticaed tools that can tell us wonderful things in the language of numbers, but we need people looking at why, telling the stories, understanding what can be done in the middle to get more bags out the door.

Probably the most frequently asked question I get is, “Evan, how can I tell a good analyst from a bad one?  What should I be looking for in a resume?”

Of course, the astute analyst will immediately recognize that those are two questions.  Well done!

Usually, my answer is a simple one: “You probably already have everything you need; you just need to start asking more / better questions of the people you have.”  The truth is that most businesses have already done a pretty decent job of hiring, believe it or not.  People who know me well will probably be surprised to hear me say that, but it’s true.

So what’s the problem?  Well, cue the first the three “things”:

Thing 1: Good web analytics people are carefully disguised as . . . your own employees!

What?  Yes, it’s true.  Good web analytics practitioners are all over the place.  They’re designers.  They’re usability people.  They’re your product managers, and even sometimes your IT people.  What these people don’t have, though, is your trust, the right tools and training, and an environment where they can collaborate and learn.

It’s very important that a large organization acknowledges the value of a healthy cat fight, but demands that each fighter does their homework.  Most everyone has an opinion on how things should be done, and a lot of those opinions are valid, but nobody is going to concede or collaborate if there isn’t some degree of data involved, and that’s where analytics comes in.  See, these people are yearning to be part-time analysts, and some of them full-time, if it wasn’t seen as a reporting job.

So what do you do? First, when people say, “I’d like to learn more about . . .,” make sure your gut reaction is not asking them why they want to learn something new, or even worse, why they don’t know this stuff already.  They’re asking you how to be a better employee, so don’t be a jerk – help them help you, Jerry Maguire style.

Thing 2: People with web analytics “experience” are most often not your most promising web analytics candidates.

This is the part where you start wondering if there is any good news.  It’s coming, I promise.  But first, let’s keep chipping away at reality.

The sad truth is this: very, very few businesses have figured out how to take advantage of web analytics in their organization.  They have competitive intelligence people, business intelligence people, product strategists, upper management, designers, and more, all telling the business, “Here’s what we need to do differently.”  Add to that the fact that most of these people are using different tools to measure and justify what they’re dreaming up, so they all get different numbers for the same thing, which makes the executives not trust any of it, or side with some numbers and not with others, based on which vendor paid for the more expensive steak dinner.

Yes, we know it’s silly, but it’s true.  No amount of us analysts saying, “That’s just silly logic,” is going to change this behavior, so it’s incumbent on us to figure out another, more successful way of convincing management that even though the numbers aren’t the “right”, they’re all “correct.”

The result of this organizational difficulty is that most people who have been hired as analysts are almost exclusively a source of reporting for a business.  While the analysts may add some text and reasoning to the report that they’re delivering, that only makes it a report with text, not an analytics deliverable.  These analysts, although they may indeed be talented, have been so stymied by their previous organization that they are too pacifist to argue their valid points and force your company to accommodate their valuable input.

You need fighters, and most current analysts have been too badly beaten: they’re scared dogs.

Thing 3: Your interview process prevents you from hiring good people.

Looking under the category of “hard to change,” we’ll see this one at the top of the list.  Here’s the deal: the people who are going to be interviewing  for the best web analytics person out there are going to be threatened as hell when they actually find one.  Let’s take Avinash Kaushik, for example.  He might be the nicest guy on the planet, but people know that if they hire him, things are going to change and that scares the hell out of them.

Things like peoples’ job performance, accuracy of insights, flaws in designs, poor calls to action, poor product planning and / or research will be revealed.  Gaps in knowledge will be exposed where people should be experts.  Flawed management techniques and approaches toward resolving conflict will be called to the mattresses.  Those who have decided to go with anecdotal choice A over anecdotal choice B will be asked why they didn’t consider data-driven choice C.

It’s important that the people doing the interviewing and hiring are able to get their own fears and egos out of the way.  I think that most people can easily identify the people who are intimidated or defensive, so just make sure that you involve some good people who are more interested in company success than personal protection, especially if they are junior to the true decision makers – they will quickly identify people they can learn from and want them nearby.

Thing 3.5: Your idea of an appropriate salary is way out of whack.

What fraction of a percent does your head web analytics guy have to move the conversion rate to pay for his whole salary in two weeks?  If you were to really Moses this one and part the seas for a talented person to point out flaws and implement recommendations, what would a 0.5% increase in conversion rate mean to your business – or even a 0.3% or o.1%?  If you’re a major (or even a middle-tier) online retailer, would this not equal hundreds of thousands of dollars of additional revenue per month?

So just think about it – if you want to put someone behind the steering wheel of your company’s data-driven decision making, how much should you be paying that person?  If you can get past what “analyst” means in the web space and start thinking of what “analyst” means in the financial space, for example, consider the potential impact that someone can have when they are highly effective at pointing out barriers to conversion AND architecting specific, implementable solutions.  I can tell you, it’s enormous.

We are all guilty of wasting time, energy, and money. But when it comes to how organizations spend these three things on web analytics, or more appropriately mis-spend these resources, it can literally cost millions of wasted dollars when you consider how many people and days (or months) of work and senseless arguments it can drive.

There are a handful of things that we should stop doing immediately.  I’ve identified three here, most of which I’ll cover in greater detail in later posts.  I believe that if companies can reduce the amount of time they spend on these activities and increase the time they spend on practicing analytics, the world will be a significantly better place, your paychecks will increase, and you will want to hit inanimate objects less often.

1. You are implementing analytics on new pages and tools last. I don’t know if I can tell you one example of web analytics implementation being a pervasive theme in content development.  Often, the product development people come up with an idea of what their content is going to do, they will come up with a handful of success metrics, and then once everything is built, analytics will be installed, usually requiring much of the more complex javascript – or even worse: flash – to be dragged back into the developer’s hands to open the hood and make sure this wonky tool can measure everything.
   
   It’s completely unacceptable in 2009 that a developer wouldn’t know the language of web analytics tools, the functions available for tracking in different ways, and your analysts (who will be the ones looking at all of this) not being a part of relevant conversations and directly involved in (and capable of) the physical implementation work.
   
   
2. You care one iota about Unique Visitors and try to get the tool to count them correctly. Now this is certainly a topic I’ll want to cover in more detail in a future post, but let’s examine the facts:
   
   We know that the metric is ALWAYS wrong, across ALL tools.  Period.  There is no fixing this metric when people delete cookies, change computers or browsers, or have more than one person in a household.
   
   We know that we’re not going to act on the data, other than to tell our advertisers, partners, or someone else who asks for the metric.  And you don’t need a web analytics person for that – just tell a secretary to look up the number and be done with it. If you’re not sure of the accuracy, see above.
   
   None of your marketing or referral traffic efforts can be controlled to target or not target unique visitors.  With the exception of retargeting campaigns, which can also fail if cookies are deleted of different browsers are used, Uniques is not a metric that you can optimize to, nor is it a metric that you pay against.  You are paying and optimizing to impressions, clicks, visits, or some other de-personalized metric that can’t tell the difference.
   
   The biggest advertisers in the world have realized that it’s not about uniques, it’s about “touches.”  Finally, the beauty of it is that advertisers like Coke and Pepsi already realize that they’ll succeed by talking to the same people over and over again, because that’s exactly what it takes.  And nowhere else in the world are people less loyal to your brand than on the web: search has made sure of that.  If I’ve been to REI a thousand times before, it doesn’t mean I’m not going to search for my next parka or pair of hiking boots on Google to see what’s out there.  With zero competitive barriers present, don’t be foolish enough to think that you have any loyal customers who don’t need a constant reminder of your presence and offering.
3. You are trying to get the numbers from any 2 of your 10 tools to match, be close, resemble each other, anything!!!So, I feel your pain on this one but that’s where it ends.  Let’s face it: we’re all spoiled online and we think that just because our analytics tool can give us an inch, we should be looking for a mile.  It’s just not the case.The truth is probably a few-fold: your implementation sucks (it does, trust me), many of the metrics used in each report are different in some way, and you’re completely mis-using the tools to begin with.

   A good friend of mine used to work for WebTrends and came up with a simple, but brilliant statement.  ”We’re looking at web trends, not web accounting.”  Another way of looking at it is this way: if you were in the middle of the desert and had to choose between a pedometer and a compass, which one would you choose?

   Of course, the answer is obvious.  You’d much rather know if you’re going in the right direction than how many steps you’ve taken, and that’s exactly what web analytics tools offer us: insight into where we are going, if we’re going the right direction, how we should change course, etc.  But instead of listening to that information, we’re off firing people because we have two numbers that are unexplainably 8% off.

Let me know what the barriers to stopping with these modes of business are in your workplace.  What’s keeping us locked on the pedometer when the compass is what we asked for in the first place?