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Well, my grumpy old men streak continues: not only do I not love the definition of web analytics, I am also finding myself fussing about what we consider our web analytics tools; the things we use as web analysts that help us do the job. Tools imply two things: mechanical advantage and outcomes (hammers increase your power; the outcome is two things stuck together by a nail), and the tools we choose to wield determine what level of mechanical advantage and what outcomes we should expect.

The trouble is that I think the majority of us look inside our toolboxes and we are blind to the best tools available for the job at hand. And, you guessed it, both our mechanical advantage AND our outcomes suffer, making us lose focus on the job at hand.

That job is cash flow.

Period.

So let’s take a look at the various schools of thought when it comes to web analytics tools, and peer into the toolbox through their eyes.

School 1 (Bachelor’s Degree): Tools are Data-Gathering Thingies

Yes, all web data-gathering thingies are web analytics tools. BUT not all web analytics tools are data-gathering thingies.

There is a lot of attention paid to tools that are relentlessly created and improved to get you more and more insight into what is happening out there. These tools render thousands of reports at this point, they can tell you what people cut and paste from your site, what users do in flash, what their income level is, and whether they have an innie or an outie. These tools are like flashlights. When you crawl into the attic, they allow you to find more and more things that were already there to begin with.

Mechanical advantage is how much the tool can show you (and how easily you can knit a data sweater), and the outcome is awareness/knowledge/data puke, etc.

If you relegate yourself to this school and think that these are the tools in your Batman utility belt, it’s no wonder nobody asks you for any thought. If you think the tools at your disposal are just dragnets that you sort through and clean up in Excel to satisfy requests for reports, that’s all your output will ever be, and that’s all your value will ever be.

School 2 (Master’s): Tools are Reports, Data, Analysis to bend ears and drive change!

On the second step to enlightenment, you start to see some other tools in your utility belt. These are tools that can stun your internal enemies and help turn naysayers into advocates. Recognizing reports, analysis and insight as tools (rather than work product) means that your actual work product will be INFLUENCE. At this level, the analyst starts to realize that they wield some power and can use these tools to turn heads. As the tools have more polish (more complete and focused analysis and conclusions), they provide more mechanical advantage.

So at this level, the outcome is influence, and with more polish and reputation, you gain mechanical advantage in the ratio of effort in per influence out.

If you’re at this level, you are making a contribution to the company by getting people in other departments thinking. Oftentimes, those people in other departments are thinking about how to make your death look like an accident, once the flaws in their thinking are exposed, but hey, at least they’re thinking! You are gaining value, but other people are still doing the work. When things don’t work, you get to tell the organization that a correction is needed. But you don’t make that correction, and you don’t get the credit when the correction works, because what the correction was wasn’t your idea. Identifying what does not work is not equal to identifying what does work.

School 3 (PhD): Tools are other disciplines (UX, SEM, SEO, IA), ACTION

At the super ninja badass level, the best tools in your arsenal finally come into focus. The best tool is always ACTION. This means you have shone your flashlight on an issue, you have brought the right people in and influenced them, and now you’re about to whip out your mighty hammer of DO THIS. At this level, you are the general practitioner. You have done the rotations in the other disciplines, and you can send the majority of your patients home healthy without redirecting them to a specialist. But you also know when to not cross the line and take on an open-heart surgery.

This is what makes successful web analytics (and business) people: the realization that your real tools are not the the tools used to identify the trend, and they are not the tools used to communicate that the trend is a bad one that needs to be fixed; they are the ones used to actually solve the problem and improve the situation.

At analytics nirvana, your tools produce cold, hard, beautiful Benjamins as an output, and your mechanical advantage is brought about by your ability to synthesize information and ideas: drawing on all of the competing priorities that go into a finished interface or architecture, and recommending (or testing) the ideas that balance all priorities for the betterment of the user and the bottom line. Very, very few people in your organization will be capable of balancing competing priorities (your company’s compensation plan virtually guarantees it), so solving one problem while also solving / minimizing downside to others is an incredibly valuable output that almost nobody in your company can do as well as you can. The only way that you can see the problem from everyone’s perspective, however, is to own their perspective by knowing how to do what they do.

Getting your PhD

I don’t think you can call yourself a web analytics ninja without a decent degree of competency in the following disciplines:

• Usability
• Information Architecture
• SEO
• Various web marketing/advertising tactics (PPC, display, email)
• Social Media (I do not classify this as web marketing or advertising, and I don’t believe you should, either)
• Design (it’s okay if you suck at it, but put some effort into it so you have credz when you start drawing out ideas)
• Copywriting
• Making sites (HTML, .NET, PHP, SQL, Javascript, etc.)

If you’re missing skills, don’t fret. While it can take considerable time for you to learn about all of this stuff, you’re going to love it because you’ll immediately see new action tools popping up all around you. Hopefully, your organization is one where people love to cross boundaries and teach different disciplines about their own specialties (picture a medical school). I don’t see this much, but if you’re around these types of people, consider yourself blessed.

If you don’t work at a company like this, either go to a company that does, or you’ll have to try your best to get the med school mentality: if the cardiologist faints in the middle of a procedure, the remaining people in the room have enough working knowledge to get the patient out of the situation alive. If you can’t say the same for your organization, that may be a BIG problem.

You might also like:

Are you a web analytics beagle or a performance wolf? (Lame title on purpose)

6 Comments

 ~ FIN ~

Google announced a secure version of their search, located at https://www.google.com. This is great if you’re worried about the black helicopters, but for analytics, this is very not great at the moment.

As good buddy and coworker Brian Ussery pointed out yesterday, when you come from https, for security reasons, your referral data is NOT retained. This means that if people search and find your site on Google SSL, you’ll never know that they came from search — they’ll appear to be direct traffic to your site.

The exception to this rule is if they click on a paid search ad that has your campaign parameters (or auto-tagged GCLID parameter) present. They will then be recorded as paid search.

I’d recommend that in the next month or so, you take a look at what percentage of your paid search is coming from Google SSL to get a feel for whether your users are taking advantage of this new offering. If you’re getting a significant percentage of traffic from the https site, you may infer that users are also generating natural search traffic from the same site, while you’re blind to it.

A good way to go about this would be to write a little script that looks at document.referrer. If it is blank (or your own site), but the URI has GCLID or utm_* parameters present, drop a note in your custom variable to identify that visit as coming from Google SSL. After a few weeks, you’ll have a good idea of what percentage of your paid search traffic is coming from the secure site vs the folks coming from regular Google, or ReGoogle.

I am making up words now so I can take credit for them in 5 years.

Go take a look at Brian’s blog post, and the rest of his blog, which is pretty excellent.

1 Comment

 ~ FIN ~

Thanks to everyone who read last week’s post “I don’t want a web analytics job.”

A dude in Ottawa replied to me that he wrote a follow-up post, and I think it’s very good, but I have a few follow-up notes.

Atlanta Analytics posts are all about fanning the flames and pushing for change in this industry by getting you thinking; not giving anyone a checklist of how to get there, which is first, impossible and second, assumes my audience is less capable or creative than I imagine you are. We are adolescents, as an industry, and need to realize that what we see today — how companies are structured and what roles exist — isn’t what the future looks like.

But that future won’t change much unless we usher it in the right direction. The future role of an analyst isn’t a CIO. Maybe a CEO at best in an SMB environment — they will be the ones starting and/or turning these online companies around. But probably (especially in a big company), it’s going to be a VP-level digital strategist of sorts, but one who is hands-on and must exit of his digital cave every now and then. The best outcome would be taking the job of running the entire site over from the CMO, maybe creating a new position of CWO, who is a person who “gets it” on all fronts. Those people do exist. They are the future of current-day analysts and other rare positions that are unspecialized by nature. I can’t think of a more concrete and actionable recommendation than that (maybe not concrete, but that’s about as much direction as is possible in changing our world). Let’s get there.

Getting traction with web analytics is hard. Winning a gold medal is hard. Getting a business built is hard. Everything is hard. And I really don’t care. And am I am saying web analytics is beneath us? Absolutely! It is! Who in the hell wants this job after they’ve done it for a while? We all want the job to evolve. We want to be involved. We want to get a piece of the action. And no, that doesn’t require us being executives, but it does require us to move beyond reports, tests, etc. and learn what’s really happening in the business so we can come up with recommendations and own them all the way to the end, rather than passing them off to someone else to manage. We want to get out of the weeds (and let the future of the industry get into them), and start to take this incredibly-rare, unbiased, multi-discipline understanding to its logical application.

If you do not aspire to be an executive (or close), holistically managing the site, you will be an analyst forever. If you aren’t spending more time learning about what generates cash flow than you’re spending learning what generates page views, you are getting passed. It’s perfectly fine if you love this job and want to stay right where you are, but be aware that you are only of marginal value to a business. This job is worth a million-dollar salary, easy. But only if we get to the real world and own this set of skills. Really own it and its implications.

We spend a lot of time talking about executive buy-in, convincing organizations to be data-driven, etc., and how hard it all is. And it’s true. It is hard. But until we can get a CFO to attend eMetrics and not want to hang himself in his shower after a day of sessions, we are not there. It’s great for us to refine our skills (and eMetrics is a phenomenal learning opportunity), but there are two sides to the job, and two languages we need to learn. We are incredibly skilled at our own language, but incredibly inept at the language of business, resource allocation, process management, operations, etc. where our findings really have application. This is the language that will create change. Is inept too strong a word? Maybe, but the analysts on the front page of the WSJ are not of the web variety, yet.

Let’s get there. There isn’t a “road map.” There isn’t a list of instructions. It’s going to require you to get creative with your executives, because every business is different. And believe me, if there was a list of instructions, you’re not going to get that million-dollar paycheck. Ever.

2 Comments

 ~ FIN ~

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.

9 Comments

 ~ FIN ~

I’ve seen this question a zillion times, so please link the hell out of this so it shows up in search results and helps people (Matt Cutts, please ignore the previous statement, I’m just trying to help people). I also posted this at the Google Analytics help forums and will do a post on Search Engine Land next week, so hopefully one of these will rank and the world will be a happier place.

ONCE AND FOR ALL! LET’S DO THIS!

Google Analytics will report the ORIGINAL referrer to the ORIGINAL requested page if a server-side 301 (or 302) redirect is in place.

Let’s shake out an example.

You own mySite.com and have a page called unicorns.html. You decide that you want to make a better page for this, so you make “DOUBLE-unicorns.html”.

Then you realize that you want to remove the original unicorns.html because it is lame compared to your double unicorns page, but you want to make sure that people who linked to that old page see the new, awesome double unicorns page. Because you’re a good, SEO-conscious person, you do a 301 redirect from “/unicorns.html” to “http://www.mySite.com/DOUBLE-unicorns.html”.

OK, breathe…here we go.

Let’s say that the site unicornUniverse.com loved your original page, and had a link on it. Now that your 301 redirect is present, what happens when someone clicks on that link at unicornUniverse.com? What shows up as a referrer?

Yes: unicornUniverse.com is the referrer! And what is your landing page? DOUBLE-unicorns.html is your landing page.

This happens because the browser never actually sees the first file: the server redirects your browser and the field of the DOM that monitors your referrer isn’t updated. This field is referred to by the document.referrer variable, and a quick cheat to check what’s in it is to type the following in your location bar:

javascript:alert(document.referrer);

If you’re a browser ninja, you might have firebug installed, and you can look at the DOM map there to see the same thing.

Let’s take another example:

What if someone searches for “super awesome unicorn page” on Google, just MINUTES after you put your redirect up? Well, Google hasn’t had time to find your redirect and update the URL in their index! OH MY! What will happen?

All is well in the world (almost, see the last paragraph below for what’s not well in the world), because when someone clicks the link to http://www.mySite.com/unicorns.html in the Google search results, they will be 301 redirected to http://www.mySite.com/DOUBLE-unicorns.html. Referrer? google.com (the document.referrer will actually read: http://www.google.com/search?q=super+awesome+unicorn+page — that is how it knows your search engine keywords). And again, DOUBLE-unicorns.html will be the landing page.

So, direct is direct, search is search, referred is referred.

Exceptions:

There are times when a 301 redirect will NOT preserve referrer information, but they are rare. The most common example is when an https page links through a redirect on a non-https page. Again, drop the javascript above into your browser to audit this on your own site if this is a concern. If that script tells you the right referrer information, Google Analytics will be cool as a cucumber.

Also, if you’re trying to do a 301 that isn’t of the server-side variety (I’ve seen some people try to state 301 in HTML or through a JavaScript redirect — don’t ask), you will definitely have problems.

Google’s documentation on this refers to javascript and tracking redirects, and is MISLEADING. It is technically correct, but it is NOT talking about server-side 301/302 redirects. In the isolated case it refers to (which isn’t well explained), it is right.

Lastly, webkit-based browsers (Chrome and Safari among them) have a known problem with opening content in new tabs and windows. If a user right-clicks a link and selects Open in a New Window or Open in a New Tab, referrer data is LOST! MIND BLOWN! But if they simply hold CTRL or command (on a mac) while they click to launch in a new tab, referrer data is preserved. DOUBLE BLOWN!

KEEP IN MIND:

If you are using 301 redirects, make sure they preserve your tracking parameters (utm_source, etc., at the end of your destination URL). Commonly, parameters that may specify display, email, or paid search campaigns may be stripped. What happens here? The URL of the referring site becomes a referrer and your campaign information is lost.

For example:

1) Your email that someone reads on Gmail should be counted as source:”email” medium:”email” campaign:”super email campaign”

if you forget to keep your URL parameters, instead of this visit being attributed to the email campaign, it will count as a referral from google.com! WHAT?!? Yes!

2) You are running a paid search campaign and have the keyword “unicorn site.” You expect source:”google” medium:”cpc” campaign:”generic unicorn terms”

if you forget to keep your URL parameters, instead of the paid search campaign being recorded, this visit will be attributed to NON-PAID search!!! Holy shnikeys!

The last thing to keep in mind is that before 301 destination pages replace your original pages in search engines (or if you use 302 redirects, and the URLs are not replaced in that case), your actual link URL from the engines and your Entry Page will NOT be the same! In the example above, Google linked to http://www.mySite.com/unicorns.html, but the entry page was DOUBLE-unicorns.html. If you’re trying to compare traffic to entry pages with your ranking reports (tisk tisk for running ranking reports!), they will not mesh up if you marry them by URL!

Good luck!

7 Comments

 ~ FIN ~

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.

4 Comments

 ~ FIN ~

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!

9 Comments

 ~ FIN ~

If you’re bored, hungry, and want to talk about being a rock star web analytics dude, come to Maggiano’s Buckhead for heaping portions of pasta and reality.

The topic today is how to get web analytics taken seriously in your organization.  When analysts cover the front page of the Wall St. Journal, why can’t we get a word in edgewise?

Looking forward to meeting everyone!

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 ~ FIN ~

Avinash wrote a great summary of competitive intelligence tools (CIs) and other good “market” data sources on his blog the other day, and it’s a must-read.

We’ve been saying for years that all of these tools come with caveats, but people still look at tools like comscore and think that the numbers are real.  In truth, they’re often nowhere close.

Where the majority of competitive intelligence tools shine is in scalar measurement: what % up or down did we see in the data?  Comscore, unless you’re talking about a mega-popular site, is a pretty terrible tool for measuring traffic levels, unique visitor levels, page views, actions, etc.  It is, however, a good tool for seeing the percentage change of all of these things. While the small population it uses to measure audience behavior might not be a good sample size to get volume, it is a good sample of how these trends rise and fall.

Tools like Hitwise rely on ISP data, or data collected by the services you connect to the internet through. They typically have a sample size that is much higher (about 100X comscore), but they don’t get the same depth of data from a behavioral standpoint.

What’s the best tool for finding out how much traffic your competitor has? Twitter. Follow their marketing and web analytics people.  They brag about their traffic and complain about their problems all the time. Make friends with a web analytics person over there, and they might voice their frustrations and ask you about yours. Hey, data sources are data sources.

Don’t forget to pay Avinash’s site a visit, though.  He goes into a lot of detail.

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 ~ FIN ~

I’m going to be up at SMX Toronto / eMetrics Toronto in early April.  These are great conferences and you should go, too.

If you’re going to go, use this SMX discount code and save some Canadian dollars: SEDISCOVER15.

I’m going to be on a panel, so it’s not exactly a keynote, but it should be a fun discussion on important metrics for SEO and search in general.  What should you be looking at, how to interpret it, and how to avoid the pitfalls.

Here’s the description from the SMX Toronto site:

Search Analytics

[SA-2] Defining SEO and PPC Measures for Success
SEO and PPC campaigns offer unmatched opportunities for measurement, testing and refining. However, to fully take advantage of these opportunities we need to define the metrics, points of conversion, content consumption or actions completed that indicate success. In this session advanced SEM professionals will discuss how Success Metrics or Key Performance Indicators (KPI) are determined and show examples of how KPI are used both real time and historically to measure the efficiency of a campaign, the success of SEO, or the real time results of an integrated marketing program.

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 ~ FIN ~

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