As we spring to action full of passion I wanted to share with you all a short list of things that will expand your little world of online marketing & web analytics.

We all have a tendency of getting caught in a rut, using the same tool to do the same things and spew forth the same data. Change is hard, even if we know that we should be executing a multiplicity strategy to win in the web analytics 2.0 world.

Before all the excitement of the new year wears out, here are five simple things I would love for you to try so that your company will have a glorious truly data driven 2010!

#1: Don't suck.

Seems obvious. And yet in our quest for ever more hard problems to solve we forget that the number one goal of every website is not to suck. Especially at the really simple and basic things.

At a recent conference there were three keynotes.

One was extolling the wonderfulness of their multi channel campaign tracking. When I went to their website it was a 100% flash website with a constrained small size where it took too much looking to click on anything and then too much scrolling to read anything and unclear calls to actions (if any). That's sucking. No amount of great multi channel tracking will save this company, they suck at the basics.

The second was about predictive analytics and how using massive integrations between online and offline databases they had accomplished some really cool reporting of data (and make no doubt the IT work done over 18 months to accomplish this was cool). Their home page is a mess. 24% of the content covers what any visitor might want, rest is the company shouting at you (in many annoying ways). That's sucking.

The third was about how to create data driven cultures and how this person had created a impressively big cross functional team across multiple countries and standardized on Omniture after a lot of work over two and half years. I did a search on some of their products and they did not have page one search listings (on Google or Bing) for what should be their head terms. (That's sucking.) They did have PPC ads, which I click on the ad for specific product they land me on generic nonsense pages. That's sucking.

I share these stories to illustrate vividly how we in the web analytics world get lost in our data and Omniture and Google Analytics and reporting and lose sight of the the basics and the customer experience.

It is important to realize that if you suck nothing else matters. Not your api driven integrated massively multi channel attribution analyzed campaign lifetime databases. That is not going to save you or your company.

Before you attempt the hard make sure that you do all the standard stuff to ensure your company has a fighting chance to win.

Here are some tips to inspire you:

• I LOVE looking at the bounce rates for the top 20 landing / entry pages to the site. Find the losers, fix 'em. These guys are so bad they could not even get one click from the visitors.

• Sit down with the owner of the top ten pages to the site and look at them. I mean really look at them and ask this question: "What the heck are we trying to do with each page?" Make sure there is a clear answer (and a match between Customer Intent and Webpage Purpose).

• Check the load time of your important pages. Use something simple like: www.WebSiteOptimization.com Or whatever complicated tool you have.

• Sign up for your websites campaigns using your personal email address. See how the emails look. Relevant? Personal? Click on the links, what to you see on the landing pages? Fix!

• Create a funnel for your cart / checkout / lead submission process. Find the biggest abandonment page. Fix it.

• Ask your Finance department where most money is being spent on the web. PPC? Affiliate? Display? What? Take a week to segment that data and find out how to save 10% of the cost.

• Count the number of links on your main pages. I mean count them. There are 98 links on a travel site I am looking at right now, on the page for a hotel in Chicago. 98! This is a top site.

  What are the analytics people doing if they are not helping the product page owner figure out how to kill atleast 50% of those links on a product specific page. There should be one link: Search for Hotel or Make Reservation! Do this for your site.

• Fix the 25 things Dr. Pete lists in this delightful checklist: 25-point Website Usability Checklist.

There are so many ideas. I hope that before you go for massive web analytics glory that your use your wonderful powers first to make sure your site and customer acquisition strategy does not suck.

PS: Bonus tip: Make sure you visit your website once a week, atleast.

#2 Learn basic statistics.

The days of tools and reports simply puking data out are rapidly reducing. No longer can tools or "analysts" just puke 15 metrics on a report and hope to survive.

Web Analytics tools are starting to become smart (see: Analytics Becomes Intelligent). Data is starting to truly get numerous.

For all of the above reasons it is becoming ever more important that you are know atleast Statistics 101. You don't have to be armed with the knowledge of how to create various models or be able to jump into SAS and get naked with it. But you are going to have to know what a mean and a median and r squared and standard deviations and Z scores and confidence intervals and all that lovely stuff is.

If you have not been exposed to statistics perhaps you can take a class at a local community college or university. Many employers will pay for ongoing job relevant education.

Alternatively get one of the simpler books on the topic and immerse yourself in self education. Regardless of if you are a novice or an expert I think one of the best books to start with is The Cartoon Guide To Statistics ($13). A cartoon book? Yes. It is quite good.

Once you know statistics 101 you'll find that you'll think of data analysis differently and you'll get better at finding that proverbial needle of insight in the haystack of data. Knowledge of statistics is a key arrow to add to your analytical skills quiver.

Hello statistical significance!

#3 Try one (or two) new usability / VOC tool/'s.

My passion for the customer is, as they say, legendary!

Part of it is the humility I have developed at the powerlessness of clickstream data to answer all the needed questions. Part of it is that there are just so many darn good options out there to listen to our customers.

So this year why not try one of the newer more powerful and yet cheap usability analysis tools?

Here are some tools that are pretty cool and unique:

• Five Second Test. I absolutely love the idea of collecting "first impressions" from current customers, employees or just randomly selected people. Within thirty seconds you can take a screenshot of your lovely home page or landing page, upload it and for free get feedback from real people.

• 4Q / Kampyle / UserVoice. Each of these tools does something completely different, and yet each allows people to type things that you can read and be wow'ed or saddened by. Why not try one of these tools this year and truly get in touch with your customers and a real and meaningful way?

• UserTesting.com. You are not a small enough company, or a big enough one for that matter, to do usability testing. This is usability testing for ultra cheap, $29 per person. Set out the tasks, identify your audience, test happens, you watch the video and read comments, you cry, you fix things, you become rich.

  Also checkout Feedback Army.

• WebSort / OptimalSort. The information architecture on most website is terrible and the reason is that company employees create it for themselves. A great option to hear from the customers was to do card sorting studies. Problem? Expense! Not any more baby. Both these tools are quite affordable, all online and in a fraction of the time it would take to do a offline card sorting study you can get the key data you need. Sweet.

You don't have to do all of the above. But you do have to listen to your customers.

In 2010 Consider trying just two tools listed above that you have not used so far. I promise you that you'll want to give me a big hug the next time you see me.

#4 Try one new competitive intelligence tool.

I practically have a illicit love affair with competitive intelligence. And I am not embarrassed!

If I ever come to see your company, or you see me presenting publicly, then you have seen me present data about your company / industry and then proceed to say nice / not nice things. There is just so much gold out there to be discovered.

Here are some tools for you to try, ideas for analysis you could do:

• Compete.com / Trends for Websites. I love the depth of data now available in both tools for free (even if you use just the free part of Compete). Index your overall performance against your competitors.

  Where do people go after they leave your site? What are the top five referrers for your competitor? What are the top sites that get traffic for the word love? All free from Compete.

  People who visit my site, what other sites do they visit? What are the things they search for? What's the difference between US traffic and India? All free from Trends for Websites.

• Google's Search-based Keyword Tool. If you have never explored the long tail for your website (if you are a medium to large site) using SbKT you might be committing a crime. If you have never taken a list of keywords AND the landing pages recommended by SbKT where you have zero impression share and given it to your SEO team then you should feel bad. There is so much here.

  [Learn how to use SbKT here: Monetize The Long Tail of Search.]

• Google Ad Planner. Some display / banner ads stink because they are just terribly produced and blink and annoy you with sound and do insane things when you move your mouse over them inadvertently. Most display ads stink because they are not relevant / well targeted. Make sure that is not your ads. Use the Ad Planner to hone into the exact sites where you can find your audiences.

  What sites are visited by: Men who are in the market for engagement rings. Women who are interested in the NFL. Young adults who are looking to buy net books. Affluent 100k+ folks or comic book buffs or brides to be.

  Now go buy advertising on those sites (from any ad network) and earn a higher ROI on your campaigns.

  [Learn more about Ad Planner: Competitive Intelligence Analysis: Google Ad Planner]

These four tools should keep you busy for a long time. Don't go at it all at once. Ask your boss's boss what his next 90 day priorities are, find the tool above that might have the insights, go on a honeymoon with it.

#5 Identify two new micro-conversions and goal values for each.

The road to web analytics glory (and a promotion for you) runs through the Micro Conversions path.

I am absolutely convinced that we don't get the love that we deserve from our company leaders because (even if we get beyond data puking) we rarely quantify the impact of all of work that the website is doing.

During Q1 make it your personal quest to identify two new micro conversions for your website (many ideas in the preceding blog post).

Now make sure, and this is absolutely key, you take one more step and quantify the economic value of each micro conversion (instructions and ideas: pages 159 to 162 in my new book Web Analytics 2.0).

That economic value will help you arrive at the number on the right, $83,848. That number will finally help you understand the complete value your website is adding to your business (only $21,454 is from the Macro Conversion). That number will allow you to measure your campaigns with a level of accountability that will be supremely awesome.

If you do nothing else on this list (I hope it does not come to that), please make sure you do this item. It is that important (especially if you are a non-ecommerce b2b government peaceful protest photo sharing website).

For the true Analysis Ninjas let me share one bonus item, one thing that will put even them above the top. . . .

Bonus: #6 Measure one thing that is "intangible".

The hardest thing to do in online analytics is to measure the intangible. How did people feel about the website experience? What was the positive brand lift? Did the unaided brand recall improve 60 days after the campaign (online or offline)? And more such questions.

Each is really hard to answer, one must think differently.

Here is a post with seven different strategies: Brand Measurement: Analytics & Metrics for Branding Campaigns.

As an Analysis Ninja go all out on three of them this year and take your business to the next level of measurement and insights.

Good luck ya'll!

Ok now your turn.

Care to share examples of sucking that you have killed on your websites? Got a creative use of statistics in your web metrics practice? Which is your favorite online customer listening strategy? Have you had success with quantifying goal values for your micro conversions?

What is your company's online, or online analytics, new year resolution?

Please share your thoughts via comments, thanks much!

Five Sweet Web Analytics Resolutions To Kick It Up A Notch is a post from: Occam's Razor by Avinash Kaushik

Even with a broken right hand I can't help but write this post!

The waterfall of positive feeling stems from the fact that this book was very hard to write.

I only had one job, at Intuit, when I wrote my first web analytics book. I now have several full time jobs, plus this blog, plus speaking around the world, plus a family, plus… so much more.

It took weekends of writing and nights of editing and days of research combined with practicing the preaching by doing oodles of analysis and, more importantly, the support of the most understanding wife in the world.

At the end of it all it is rather gratifying to see one's book at a bookstore, helps grasp the magnitude of the process. And there's absolutely nothing quite like hearing your five year old yell in a busy Borders bookstore: "I FOUND DADDY'S BOOK!"

This blog post is in three parts: The pitch. Request for help. A lovely contest [Contest closed now, thanks for the entries!].

You don't have to read the whole thing & skip ahead, but that would hurt my feelings. :)

Here we go. . .

The Pitch:

I invite you to consider buying my second web analytics book. It is not only the most current book on everything important and bleeding edge in Web Analytics, it is a labor of love that will help you transform your personal thinking and assist in revolutionizing your organization (big or small).

It is not a technical book, though it will make you technically dangerous. It is not just a business book, though every dna strand in this book is more about online marketing than online analytics. It is not a hard book to read, though it is brain food.

Here's why I think you'll love it:

Chapter 1 The Bold New World of Web Analytics 2.0

No dragging of the feet, the book starts with a bang by laying out the framework that will be the center of every company that will leverage data (qualitative, quantitative, competitive) on the web. It ends with a challenge to embrace Multiplicity – without this it's goodbye greatness.

Chapter 2 The Optimal Strategy for Choosing Your Web Analytics Soul Mate

It will be hard for you to find a more compelling four step process to choose the right web analytics tool for your company. Soul searching, questions to torture vendors with, comparing vendors, running a pilot and negotiating a contract, it's all in there. You be off to the races right.

Chapter 3 The Awesome World of Clickstream Analysis: Metrics

The thing I enjoyed about this chapter (I know I wrote it, but still. . .) was that the first half works really hard to evolve your critical thinking skills. I love that because we take too much for granted, now you'll be skeptical. A good thing. The second half shows exactly how to pick the best metrics for your org and, my absolute favorite (Page 64), how to diagnose the root cause of a metrics performance.

Chapter 4 The Awesome World of Clickstream Analysis: Practical Solutions

When people think of web analytics everything they think about is chapter 4, and yet you'll find so many yummy treats here. The best WA report, segmentation, site search, SEO & PPC analysis, email, rich media, cookies, data sampling. . . . I am out of breath!

Chapter 5 The Key to Glory: Measuring Success

If I have one jihad it is to massively convert every person who touches the web to focus on measuring Outcomes! It is the one reason we can't achieve the greatness we so richly deserve. No more! Glory will be yours!! B2B. B2C. Small Biz. Large Biz. Non-Ecommerce. We make love to 'em all! One thing you'll read here that you'll read no where else? Computing Economic Value, a concept that will liberate you.

Chapter 6 Solving the “Why” Puzzle: Leveraging Qualitative Data

Oh, oh, oh qualitative analysis!! I am a Mechanical Engineer with a MBA, a late covert to the power of understanding the super sexy "why" by leveraging lab usability studies, surveys, card sorts, online remote testing and more. You get a jump start. The thing you'll adore: Pages 190 – 192.

Chapter 7 Failing Faster: Unleashing the Power of Testing and Experimentation

Sure you've heard of A/B and multivariate testing. But do you know how to truly win the game? There is no technical mumbo-jumbo here, just the real deal and how to get testing right. The thing you might not know / realize the power of: Controlled Experiments. I am convinced this is God's gift to online humanity, you'll agree with me by the time you reach Page 208.

Chapter 8 Competitive Intelligence Analysis

The most magnificent advantage the web possesses: everyone's data is available for everyone else to use. If Hilton Hotels has the data for Choice Hotels why not use it to "crush" them (sorry Sarah!). This chapter shows you how. I think the thing you'll be surprised by is at the start of the chapter (Data Sources, Types and Secrets).

Chapter 9 Emerging Analytics: Social, Mobile, and Video

The chapter I had the second most fun writing. Mobile, twitter, blogs, videos etc are just so darned hard to measure and so much changes every few hours that I had to really really work hard to find the essence of each and then make specific practical measurement recommendations that will stand the test of time. It was hard.

Chapter 10 Optimal Solutions for Hidden Web Analytics Traps

This is a collection of major reasons I think people fail at web analytics, and of course I boldly try to share how to avoid that fate. Behavior targeting, dashboards, accuracy, data mining, predictive analytics, and, the thing you'll appreciate the most IMHO, five steps for intelligent analytics evolution!

Chapter 11 Guiding Principles for Becoming an Analysis Ninja

All my life learnings laid bare. . . this is where you, yes you, start to evolve from a Reporting Squirrel to an Analysis Ninja! No metrics, data pukes, guidance on creating every more reports. No, none of that. Rather… analytical techniques, tips and tricks to apply to your job, how to evolve your thinking to a higher level.

Chapter 12 Advanced Principles for Becoming an Analysis Ninja

The chapter I had most fun writing (and rewrote the most number of times). It deals with two of the hardest practical challenges we face in the field of measurement: multi-touch campaign attribution analysis and multi channel analytics. Both are very hard to get right, both have a ton of fud out there, it was fun to share my recommendations.

Chapter 13 The Web Analytics Career

The chapter I should have had in the first book. How to plan a career in web analytics (paths, salary, longevity), and how to then cultivate the right set of skills. If you are a leader then how to spot great talent, how to interview them and make the right choice.

Chapter 14 HiPPOs, Ninjas, and the Masses: Creating a Data-Driven Culture

Some might argue, rightly so, that the most elusive thing to accomplish is to truly bring data democracy to your organization. This chapter bravely hopes to help you do exactly that: excite people about data, remove organizational barriers, use data to change behavior, dealing with data quality, and creating data driven HiPPO's.

Convinced?

Nothing, absolutely nothing, in life is easy. But if you have the will and access to knowledge then that just might help you choose an optimal path, a path where your hard work will yield above normal results. That's my hope, and promise, with Web Analytics 2.0.

Jennie and I have decided to donate 100% of our proceeds from this book, just like for the first one, to two charities. This book benefits The Smile Train and Ekal Vidyalaya. We are very excited about that.

Request For Help:

As you all know my philosophy for this blog is eat like a bird, poop like an elephant. But if you are up for it I would love to ask you for a bit of help.

Recommend the book.
If you know someone who needs to turbocharge their online existence, please recommend Web Analytics 2.0 to them. Even in our hyper connected world, nothing works like a personal recommendation.

If you use a link please consider using: http://bit.ly/akwa20 That link has an affiliate code, all proceeds of which go to the above mentioned charities.

Review the book.
If you have a blog, website, twitter account, any kind of platform, it would be great if you could write a review of the book and help spread the word.

If you purchased the book online then please, pretty please, review the book on the store's website. Amazon. Borders. Target. Powells. Whatever you used.

Connect me.
I am very very bad at pimping. So if you know someone who is someone (or knows someone who knows someone) then please consider connecting us. Especially people outside our analytics / search circle. Authors. CEO's. Journalists. Influencers. TV anchors (or weather man/woman). Oprah (I can dream, can't I?).

Our world is separated by six degrees of separation, I am sure you know someone who just might consider helping me with my cause.

Share a picture.
I love getting to know my audience, and while your emails and tweets are pretty fun there is nothing like a picture.

I had a "Web Analytics: An Hour A Day Fan Mail" flickr group that has some incredible pictures from around the world, bringing my audience closer to me.

I would love to do the same again for my "Web Analytics 2.0: Fan Mail". Be as creative as you want to be. Babies. Cats. Posters. Cars. Places. Or the best, you. All would be welcome.

I will only post the pictures with your permission. Please send them to blog at kaushik dot net. Thanks!

A Lovely Contest:

[The contest is closed now. Winning entry details.]

Steve Cunningham invited me to be a part of a little "contest" he is running. The prize is a delight, you get to win a pack of seven books on online marketing & social media: Six Pixels of Separation, The New Community Rules, The Whuffie Factor, Trust Agents, Crush It!, Duct Tape Marketing, and Web Analytics 2.0.

How to win you ask? Two ways.

1. Answer this question in comments below: If you were to measure the success of a company's social media efforts how would you do it?

Pick any social media channel, or all. Only a short answer is required. The most innovative / interesting answer wins. No answer is too small or too simple.

[If you have my book already then my answers in the book to this question will win you major brownie points, but perhaps not the contest! :)]

2. You can get four more chances to win, if you want. Simply visit these blogs and answer a different question on each: Steve Cunningham, Beth Kanter, Tara Hunt, and John Jantsch.

Good luck!

A Word of Thanks:

This is from my book's acknowledgment page…

I would like to express my deep appreciation to the readers of my blog, Occam’s Razor. In approximately three and a half years I have written 411,725 words in my 204 blog posts, and the readers of my blog have written 615,192 words in comments! Their engagement means the world to me and motivates me to make each blog post better than the last. It is impossible to thank each person, so on their behalf let me thank three: Ned Kumar, Rick Curtis, and Joe Teixeira.

A very solid case can be made for the fact that neither one of my books would exist without you and your engagement and encouragement.

Gracias. Arigato. Ngiyabonga. Xie xie. Obrigado. Shukriya.

Web Analytics 2.0 Book: In Stores Now!! is a post from: Occam's Razor by Avinash Kaushik

It is with immense excitement that I am sharing the news that I have just finished writing my second book!

Web Analytics 2.0:
The Art of Online Accountability & The Science of Customer Centricity

It is a long title ain't it? The good news is we are going to refer to it simply as Web Analytics 2.0.

In this post I wanted to share thoughts about the book, the process of writing it (and doing three rounds of edits!) and outcomes.

The Background

Since mid-2008 Willem Knibbe, my wonderful Acquisition Editor at Wiley, was very kindly encouraging me to update my (best selling!) first book, Web Analytics: An Hour a Day.

The "problem" was the book continued to sell at a nice rate and I was not sure what to update because 90% of the content was still current and relevant.

Still there was a lot of new stuff I had written, new models I had developed, new and more advanced techniques, new problems we were dealing with in the world and so on and so forth.

That lead to my proposal to Willem to write a new book that would use Web Analytics: An Hour a Day as a starting point. The second book would be an advanced book that would allow the first book's readers to truly become Super Analysis Ninjas, and for those that had not read the first book to have the finest possible immersion in web analytics.

And that's just what Web Analytics 2.0 is.

The 2.0 Book

The book's core philosophy is based on the framework you have seen me talk about on this blog. . . the quest to answer four key questions: the What, How Much, Why, and What Else. . .

The awesome thing about writing a advanced book is that I can start with a bang! No history and what not. It starts with: Here is how your world should look like and this is why its important, now let's get down to business.

That's by page 9. : )

And then it just keeps kicking it up a notch. Bam! Bam! Bam!

Like the first book this is not a book about Omniture or Xiti or Google Analytics. It is not a "press this button in the tool and then press that one" book.

It hopes to be brain food.

Here is how you should think. Here are the traps to avoid when picking key performance indicators. Here are the core analytical techniques you should apply. Here are a bunch of reality checks. Here is how to embrace outcomes, regardless of the size of business you have. Here is how to achieve higher highs with testing and by listening to customers (literally). Here is how you leverage your competitor's data. Here is how you becoming a true Analysis Ninja (step, by step, by step).

And none of that is even close to the coolest part of the book (see why I am so darn excited?).

There are so many topics I deal with each day that I have not had time to write about on the blog, all the things I practice all day long in the five jobs I hold.

The book gave me the impetus to write all that down.

So there are complete sections in the book that teach:

Why tracking the social web is such a massive problem.

How to measure success of blogs.

Meaningful non-crappy twitter analytics.

Mobile analytics! This was so much fun to write about.

Measuring rich applications whose primary usage happens with no internet connection.

And more such things.

But you might end up buying the book simply for Chapter 12, it covers two things that I think will rock your world:

1. Multi-touch campaign attribution analysis (dissected and presented in a way like you have not seen it any where, I think)

2. Multi-channel non-line analytics (practical tips, best practices, unique stories to inspire you)

Even after all that I was not completely satisfied. : ) There are two more new things to end the book. A complete chapter on how to start, nurture and advance a career in web analytics. The last chapter of the book is on how to overcome the hardest challenge of it all: creating a data driven organization!

The Writing Experience

This was a very hard book to write, in many ways harder than Web Analytics: An Hour a Day.

That's partly because this time around I had my full time job, my work with my start-up Market Motive, my advisory roles in three companies, my world travel to support my professional speaking career, my blogging (the only thing that suffered), and of course my family.

It is difficult to find time and energy to write a book with all that (and impossible without a magnificent wife who takes on three times a normal human's load to support you!). Especially to pull the writing and three rounds of edits in four months!

It was also hard because this is a much more advanced book with so many topics on the bleeding edge. It is hard to make sense of it all and understand it enough to apply a reality filter and then write something that people can apply today, and use for a very long time.

And yet it was a lot of fun to write this book.

I think that's primarily because with the first book I had no real sense for what the book would become, who it would impact, how far it would go.

This time around I have a much better sense for all that.

So many of you have written to me about all the ways the book has touched your lives. As I wrote this book that was constantly at the back of my mind. It pushed me to work harder and do better because I realized all the places it would go, all the people who will crack it open, all the expectations it had to meet.

I had this visual of all the people who might buy this book and how in some way something I wrote could have an impact on them. That was pressure, but it was also fun.

The Second Little Book That Could

Some of you know that my wife Jennie and I had decided that we would donate all the proceeds from the first book to charity. We had chosen The Smile Train and Doctor's Without Borders and split 50% of the proceeds between each.

My hope was that Web Analytics: An Hour a Day would sell enough for us to donate the $10,000 advanced we had received.

We have thus far received, and donated, 18 months worth of royalties from the book, approximately $70,000 (!!).

Not in my wildest dreams had I imagined that! And there is no way that we could have afforded to donate that much money.

In a very small way this blog and the book have helped other people in our lovely world. It has been an extremely gratifying experience for us.

With Web Analytics 2.0 we have decided to do the same again.

100% of my author proceeds from the book (and all the amazon affiliate sales) will be donated to The Smile Train and Ekal Vidyalaya.

Ekal Vidyalaya runs schools in remote locations that reach the poorest of the poor children in India. Without Ekal these children would have a very limited set of opportunities in life, if any.

When the going got really tough with this book the thing that kept me going was to produce a book that would have a big impact on people who buy it and a small impact on the charities Jennie and I choose.

The 411

The book can be pre ordered on amazon now, if you are so inclined.

It will be released mid-October 2009.

Wish me luck.

Web Analytics Books! is a post from: Occam's Razor by Avinash Kaushik

Sometimes they can be unqualified.

Usually they are "qualified". The depression comes from this singular flaw: The candidate's education is limited by the companies they work/worked at.

All I know is ecommerce because that is all my company does.

All I know is lead gen because that's my world.

All I know is PPC because my job involved just Search.

All I know is B2B because that's my company's vertical.

These are summaries of the excuses I hear. They don't actually use their words, but it takes 10 mins of questions for that essential summary to emerge.

These excuses are extremely corrosive and and sadly indicate how the candidates have allowed their environment to limit their full potential, stunt their professional growth.

Here's some bad news: Companies will never give you the time to truly learn and grow.

Sometimes they explicitly won't give you the opportunity, at other times they will give you the opportunity (and even some funding) but you still have your daily work load and you don't take advantage.

Here's a news flash: The world around you is always changing and growing. If you don't keep pace, you become stale. Quickly.

So?

Here's my recommendation:Step out, take charge of your own learning.

Why let your employer take you down? Why let them add just tactical experience to your resume? Why let their online tactics limit your growth?

So what to do?

My own learning about web analytics truly transformed after I started my blog. The total cost was $65 (five bucks to buy a domain and five bucks a month to host it with a ISP).

Web Analytics Education.

Just writing a few simple posts a month got a couple thousand page views a month. That was more than enough for my blog to become my learning platform, a place where I could implement web analytics tools, get to play with real world data and educate myself.

In the last couple of years I have implemented atleast 25 analytics tools on my blog. In fact at this very moment here are the tools implemented on my blog: ClickTracks, Percent Mobile, TigTags, Urchin, StatCounter, Yahoo! Web Analytics, Xiti, GoingUp, Statsit and CrazyEgg.

I have learned so much about implementation, customizing data capture, data analysis, and tracking challenges.

Having all these tools on my blog, or having them on your blog, means that your company, or your mom or your life partner or a bear, can't limit your ability to learn. You are in charge of your own destiny, you are in control of if you want to grow or become stale.

My employer, be it FedEx or General Mills or Florida Oranges or Intuit or WPP, is unable to limit my ability to be smart and current.

[Think starting a blog might be much? That's ok, grab your dad's business site. Ask a non-profit to allow you to analyze your site. Beg your "social media god" brother-in-law for access to this site / blog / media presence so you can do analysis.]

Beyond Simply A Web Analytics Education.

It is eternally frustrating to me that "Web Analysts" limit their learnings to Omniture or WebTrends or Google Analytics only. Why?

Why not become really smart about Search Engine Optimization analytics? No, that does not come from logging into Site Catalyst!

Your corporate team has a SEO team who won't let you in. No worries.

Claim your blog in Webmaster Tools from Google and Microsoft (Yahoo!'s offering is quite poor in this regard). Log into the tools and see all the wonderful reports you have and educate yourself about data that is completely missing from Site Catalyst, yet absolutely key to understanding SEO performance.

Want to be smart about Competitive Intelligence? Don't wait for your boss to give you access to anything or approve a PO. Log into Compete, Google Insights for Search, Google's Ad Planner (psychographic and demographic audience segmentation for free!) and … and … and …

Online Advertising Education.

A couple years back the company I worked at not do display advertising or use AdSense.

My learning strategy?

Implemented display ads in my RSS feeds and implement AdSense on my blog.

Result? An education by working in the real world worth its weight in gold.

I could have read blogs about online marketing or attended presentations at popular conferences on those topics. But it is the pain of actually doing it and the frustration of actually trying to merge the data sets and trying to reconcile the first party and third party cookies that were the source of my learnings.

Not theory. Practice. And I did it all on my own, no permissions required from anyone.

Social Media Analytics Education.

Last year I read about a new tool to measure Social Media (twitter specifically). I visited the tool, punched in a few people's names. I quickly came to the summarization that the tool was…. what's a polite way of putting it….. let's just say flawed.

My response? I started a Twitter account .

Each medium on the web is unique. None of my prior work would have given me the knowledge I needed to opine intelligently.

I started my twitter account because I wanted to learn what this new fledgling medium was all about and what impact it might have on Influence and Marketing .

After three months of committed participation and learnings think I finally got it . What makes this medium unique, what success actually means, how to measure it, and, most important of all, how not to be faked out by crap metrics that are floating around.

Almost a year later with 10,802 followers and 2,010 tweets later I might even charge you $1,000 an hour to tell you all that! :^)

But I learned for free!! Ok, not totally free, I invested my time and my passion.

On that same vein I only started a Flickr Photostream and a YouTube account because I wanted to learn what kind of data could be collected and what new metrics could be developed to measure success in those mediums.

All of the above has two powerful outcomes:

Yes, you are right. It is a lot of hard work above. But nothing worth anything was ever easy right?

Bottom-line On Your Online Marketing & Analytics Education.

Don't let your web analytics vendor or your employer limit your education or your potential. Don't let their business tactics and restrictions make you yet another analyst that can't survive a real world interview.

I hope to stay current, and relevant, by doing all of the above. And it is absolutely not unique. There is no secret sauce.

You can do it too. You can stay current, informed, intelligent. You'll add value to your current employer by being smarter than you are supposed to be, and if you and I ever sit in a interview we can have a fun conversation!

What are you going to do today?

What is one new thing you are going to get educated about in the next three months?

Are you going to be a true Analysis Ninja?

PS:
Couple other related posts you might find interesting:

• Ten More Blogging Tips From A Novice Blogger
• Analytics Career Advice:”I am an Analytics God, I want more $$. How?”
• Web Analytics Career Advice: Statistics, Business, IT & Mushrooms
• Interviewing Tip: Stress Test Critical Thinking. Please.

Web Analytics Career Advice: Play In The Real World! is a post from: Occam's Razor by Avinash Kaushik

They had some biting, but fair, observations about short comings of Google Analytics. I appreciated that very much.

But the most valuable part for me was section 6.7.2. It was a listing of 11 barriers to an effective online measurement strategy. 11 painful reasons why extracting value from web analytics is still worse than attempting to climb Mt. Everest for some of the top companies.

Curious?

Here they are:

1. Lack of budget/resources (45%)
2. Lack of strategy (31%)
3. Siloed organization (29%)
4. Lack of understanding (25%)
5. Too much data (18%)
6. Lack of senior management buy-in (18%)
7. Difficulty reconciling data (17%)
8. IT blockages (17%)
9. Lack of trust in analytics (16%)
10. Finding staff (12%)
11. Poor technology (9%)

Makes for a slightly depressing read does it not?

Many, if not all, of these challenges are really hard and often the solutions are unique to each company. In as much it would be impossible to write a here is how you fix it all blog post.

Rather I am going to try and share some thoughts / ideas on that will atleast help you take step one. I very much encourage you to share your wisdom with us through comments.

First: A Brilliant Insight / Borderline Rant. : )

Before we go on nothing something absolutely astonishing…. we live in a culture where every Analyst, Blogger and Consultant is writing / posting / talking / presenting comparisons on web analytics tools.

We can't seem to take one step without stepping into one more pile of opinions about why this tool is great and what one is bad.

Yet the top ten barriers have absolutely no connection to features, and barely have any connection to tools. Its #11. An afterthought.

I wonder why we are not writing / posting / talking / presenting on how to solve these non-tool problems, things that actually matter to companies and practitioners in the real world.

Just because we are programmed to publish reports comparing tools?

Tools can provide a marginal advantage to a company of any size. But given where we are in our evolutionary stage we have much bigger fish to fry.

I hope its out with lets drop our clothes and compare sizes and in with adding real value to practitioners by focusing on issues like the above ten.

Do I hear a amen?

Now on with the show. . . . .

#1: Lack of budget/resources:

In some sense this problem never goes away. It bedevils you when you are small and just want to buy a web analytics tool or just start testing. It will still be a issue even after you have been successful with Site Catalyst and now want to plunk down a million and half dollars to buy the behavior targeting platform.

How do you overcome this challenge?

Start for free and earn your right to ask for budget.

No matter what tool you want it is now available for free. Web Analytics. Multivariate Testing. Behavior Targeting. Whatever.

Why are you asking for a tool budget? I know some worry that they don't want to have a tool for a year or two and then switch. Look, no one knows what the world looks like in 18 months, why are your planning for five years?

Implement Yahoo! Web Analytics, Google Website Optimizer, BT Buckets and have at it.

When you run into limits you'll have a proven track record of success which will make it easier to ask for budget for WebTrends, SiteSpect and Kefta.

The only reason you'll get turned down is if you showed no value to the company. Then you might not ask for budget. :)

Other tips for getting more budget:

• Don't focus on the value of the tool. Quantify the value of the outcome you will deliver. "I want an Analyst for our tech support site because I can reduce calls to our phone center and reduce costs by $1.6 mil and increase satisfaction by 5 points."
• Enroll your Customers and Competitors to help you. More here: Lack Management Support or Buy-in? Embarrass Them!

#2 Lack of strategy:

I am a bit flummoxed. I am not sure what to make of this.

If the barrier to an effective web measurement strategy is that your business has no web strategy then I think you should look for another job. [You can start looking now, ride out the recession, and then bail at the first opportunity.]

Someone up there, the HiPPO's, truly needs to get it and create a web strategy. Once they create even a rough cut of it you can help them. Without a rough cut this is a lost cause.

If you are a Director or a VP perhaps you can try and help plant the seeds for a strategy. Especially if you notice Measurement/Analytics is owned by IT (usually a kiss of death – with sincerest apologies to all my IT friends). Get it moved to a business function.

Other tips to try and create some strategy:

• If you are at a large company with many divisions etc and no consensus, then try to pick one division/country and make them a hero. Don't try to get everyone to agree on a set of metrics.

• If you think your boss wants to create a strategy, but needs a final push the check out this post for tips: Six Rules For Creating A Data Driven Boss.

#3. Siloed organization.

It is important to realize that silo's can break if you are able to show value. Everyone wants a bonus and they want to get promoted. Oh and they also want to help the company.

Exploit that fact.

Start small. Show some value. Go bigger (cover another business unit or now cover Marketing or Paid Search in addition to Email Marketing). Show value. Go bigger still.

That was my strategy.

When I started it was me and one Analyst in the "center" and no one would listen to us. Not the business units. Not the business functions (IT, eCommerce owners etc). But we executed the above strategy and over time I proved how data can be valuable to one silo in the company. They wanted move.

My reply: "We have got to break down the IT and Analytics silo, we can't be filling out tickets all day to make minor changes."

Ok, some painful business gyrations, I got a couple technical folks transferred.

Next spent more time doing things faster better with help of the team, proved more value, earned credibility.

Question: "How can we move to the next level?" Answer: "We need to move into doing more qualitative analysis, but that function is in that other silo." Feedback: "Well then lets go fix that."

It got fixed. One more silo broken, a more cohesive team, significantly improved execution.

Maybe you don't want to break silos around data execution. I doubt your execution model would be different. Make the best of what you have today. Work hard all day. Strike oil. Go back to work harder next day.

Most people don't want to work this hard. Most people don't have the kind of patience required. Then it is easy to complain and wait for someone to fix the silos. Won't happen. Sorry.

#4: Lack of understanding.

It is unclear from the report exactly what falls into this bucket, it seems to be this general complaint: "No one understands me, no one appreciates me (except my mom!), no one will help me."

If there is a lack of understanding of the value of data then have someone from your management team to attend one of the Vendor webinars (Omniture does a bunch of these). These webinars present one client's experience (usually extremely rosy) and perhaps that can get your boss to appreciate value of data.

If there is a lack of understanding of what analytics can do, get Google Analytics and slap it on a micro site if you have to and improve organic search to show how you can improve the number of visitors from search. Notice everything in this sentence is free except your time.

If there is a lack of understanding of what technologies exist in the market, do a quick Google search, identify the main vendors, get them to come do a dog and pony show for you (online or in person). Sure there will be some showmanship, but you and your boss will also learn a bunch.

Other tips for creating an understanding:

• If you are low or mid level employee then realize that you can't do this. Find a Sugar Mommy (or Sugar Daddy) who will help you.
• I'll repeat this again: Any understanding can be created by doing rather than by simply talking.

#5: Too much data.

Finally a web analytics problem!

I am astounded only 18% complained about this. Just goes to show how many people are still executing Web Analytics 1.0, clickstream only, strategies. If they were truly doing Web Analytics 2.0 strategies more people would say this, and it would be a good thing.

Can I be blunt?

This is a problem we, Practitioners, create. We are simply so eager to impress others about how much data we have and how we are so fantastic that we have 28,205 metrics we can reports on day one.

Who cares!

Two words: Critical Few.

You must not send a single report out, no not even a number via email, until you have identified what your critical few metrics are. That process starts with the question: What the heck are we solving for with our website?

Ok so maybe a bit more polite than that.

But honestly identify the one Macro Conversion (big goal) for your website and, up to, three Micro Conversions.

Now focus on just the few metrics help you measure success of these four things, with the highest priority being the Macro Conversion. [Blog post with ideas: Measure Macro AND Micro Conversions.]

Do nothing else. Ok do nothing else until you have mastered these. Don't irritate your companies with lots of reports with lots of metrics.

Other tips for reducing amount of data:

• If you can't get your management to identify goals for you, update your resume and apply for other jobs. While you are waiting focus really hard on only reporting metrics that will help 1. increase revenue 2. reduce cost and 3. increase satisfaction. Can't go wrong with those three.
• If that does not work report these six metrics, just six, and you'll be adding value: Six Web Metrics / KPI’s To Die For.

#6: Lack of senior management buy-in.

For me this is the same as #1. They don't want to give you budget or resources because there is no buy in. Perhaps because you have reported too much data which leads to a lack of understanding resulting in a lack of strategy.

Focus on the things we have discussed before and you'll have the thing you crave from your management:

For more here are three posts that fall in this space:

Six Rules For Creating A Data Driven Boss

Management Support or Buy-in? Embarrass Them!

How To Excite People About Web Analytics: Five Tips

Other tips for getting senior management buy-in:

• Realize that there is a difference between reporting and analysis. Be a Analysis Ninja, not a Reporting Squirrel.

#7: Difficulty reconciling data.

Let's tackle this at two levels.

At a macro level you should know that it will be impossible to reconcile data and that it is ok. I believe that one the web we must execute a Multiplicity strategy.

That means different tools, with different data sources, different metrics. Again, this is ok. There is exponentially more value in using these data sources than the alternative.

In this case invest in educating your manage met team why the numbers differ. They won't accept it entirely. Start with making small decisions based on this data, show value, earn trust, move to bigger things.

At a micro level this refers to reconciling numbers between Google Analytics and NedStat. Or between HitWise and Compete. Other such cases.

If this is your case then please use the Ultimate Web Analytics Data Reconciliation Checklist to identify where the issues might be and fix them. You'll never them them to match 100% but if you get say close to 10% delta, you are pretty much there. Move on to other problems.

#8: IT blockages.

If you think you have a chance to take direct ownership of large (or all) parts of the IT work required (tagging primarily) then follow the strategy I have outlined in point #3 above (breaking silos).

It is likely that your company will simply not allow you to touch the site. In this case both to do web analytics work (tags etc) and online marketing work (update pages, fix urls for SEO etc) you are stuck with IT (an organization that tends to be ultra conservative).

Use the sparkling power of data to unclog the blockages.

My friends Shane Atchison and Jason Burby from Zaaz have long advocated creation of models that identify the cost of delays. Here's one of their earlier models. . .

Current conversion rate and the value is identified at the top. In the first column are subsequent improvements in conversion rates, based on the goodness that Zaaz is going to bring to the table. The columns indicate incremental orders and value and, sweetness, the impact of a launching the changes in a month of in four months.

The last column shows the cost of the delay.

The worst improvement in conversion will cost the company $342,930 in real revenue. The expected improvement is to 9.25%, which would mean a three month delay will result in $1.5 million in lost revenue!

Do you think you can get IT to get unclogged? You betcha.

Here's another one where they have monetized lost opportunity from delays in improvement for conversions that happen offline from online leads. . . .

Intelligent decisions can be made if the project should be delayed three months or six months. :)

Don't pick political battles with IT. Use data.

#9: Lack of trust in analytics.

I think there is overlap here with #7. [Linus perhaps we need some consolidation? Also between #6 and #1?]

If the problem is that they don't trust the data, then use the techniques described above in #7.

If the problem is they don't trust web data then use these techniques:

More details here: Slay The Analytics Data Quality Dragon & Win Your HiPPO’s Love!

#10: Finding staff.

I have advocated the 10/90 rule for magnificent web analytics success for almost five years now. People are the key (and in some sense I am disappointed they come our #10 here).

Finding staff is certainly not easy, but I don't believe that it is all that hard. I think we tend to look too narrowly.

We look for people with ten years of Omniture experience. Or with experience in WebTrends, Optimost, iPerceptions and making coffee.

These are very hard to find, and narrow the pool of potential candidates waay too much. We are a young industry and that means it is hard to find people with deep experience in one specific tool.

The ironic thing is that so much has changed about Omniture (or GA or whatever) and the web so much in the last five years that any tricks you knew from five years ago are irrelevant now.

When you look for Analysts look for people in the Finance function. Look for people who are doing traditional Business Intelligenc work. Look for fresh college graduates who have the web in their blood (unlike us old folks) and teach them what buttons to press in Xiti.

Don't close your eyes to other possibilities. A peer of mine just hired someone who was in the HR team doing People Analytics (what a great analyst!).

Other tips for hiring people:

• Should you higher a bright freshly minted college grad or someone who has been around for a while? Answer here: Fresh blood or old hands? Experience or Novicity?
• How to ensure the Analysis Ninja you want to hire does not turn out to be a reporting squirrel? Answer here: Interviewing Tip: Stress Test Critical Thinking. Please.

#11: Poor technology.

I almost don't want to dignify this with a comment. After all we live in a world where the freest of the free tool can still help you make a ton of progress for months.

Let me say this. . . . if you are looking for technology to do traditional web analytics or web analytics 2.0 then you are in luck. Lots of magnificently powerful technology exists all the way from free to you'll have take off all your clothes and even your underwear and send them with your chq expensive.

The only places I find "poor" (hate that word, I prefer early evolution) technology is on the bleeding edge. If you are unable to collect real rock solid data for mobile analytics or social media analytics or truly distributed content analytics then you have my sympathy.

As a human race we have not really figured out what these things are, and they are changing with every passing day. It will take us some time to figure our optimal data collection and associated technologies.

But other than that don't give, or accept, the excuse "poor technology".

End of story.

My highest expectation from this post is that it will give you possible starting points as you start to tackle some of these tough challenges. If you got three ideas you can take back and action, you have just made my day.

Ok your turn now.

What do you think of the 11 findings in the Econsultancy study? Do they reflect your reality? Would you prioritize them the same way they did?

Have you dealt with and conquered some of these challenges in your life? Even if it was one of them, would you please share your experience and lessons with us? It would be greatly helpful.

Thank you.

Barriers To An Effective Web Measurement Strategy [+ Solutions!] is a post from: Occam's Razor by Avinash Kaushik

Generations of Analysts, Data "People", Decision Makers have grown up with the principle of GIGO. Garbage in, garbage out.

It made a lot of sense for a very long time. Especially because we used to collect so little data, its lack of even a little quality crapified the decision a lot.

GIGO also fueled our every expanding quest for data perfection and data quality. There are entire companies built around helping your "clean up" your data. Especially if you look at the offline traditional business intelligence, erp, crm, data warehouse worlds.

The web unfortunately threw a big spanner into the works.

Couple important reasons.

First, it is important to realize that we collect a lot of data on the web (type of data, elements of data, what not).

Second, our beloved world wide web, remember still a little baby, is imperfect at every turn. We use data collection methodologies that reflect our efforts to do the best we can, but they are inherently flawed. Just take javascript as an example. It is good at what it does. But not everyone has javascript turned on (typically around 2-3%). Zing: imperfection.

A lot of data. Imperfect data collection system.

Here is the most common result of this challenge: The "Director of Analytics" spends her meager resources in the futile quest for clean data.

Money is spent on consultants (especially the "scarady cats" who deftly stir this issue to favor their personal businesses). Everyone tries to reconcile everything across systems and logs. Omniture gets kicked out and WebTrends gets put in, supposedly for it "far superior" data quality (!!).

Makes me sad.

In the debate for perfect data is is important to realize that the reality is a lot more nuanced.

No Possible Complete Data on Le Web.

I humbly believe that the world of data perfection ("clean auditable data") does not exist any more. It did for a long time because life was cleaner, mistakes were human made, sources were fewer and there wasn't enough data to begin with (sure terabytes of it, but of what 300 fields? 600?).

On the web we now have too many sources of data. Quantatitive, qualitative, hearsay (sorry, surveys :), competitive intelligence, and so much. [Web Analytics 2.0 ] But these sources are "fragile".

Sometimes because of technology (tags / cookies / panels / ISP logs). Sometimes because of privacy reasons. Sometimes because we can't sample enough (surveys, usability tests). Sometimes because it is all so new, we don't even know what the heck we are doing and the world is changing too fast around us.

Killing the Holy Cows.

The old people who did BI (me for sure, maybe you?) and moved to the web have had to come to the realization that the old rules of making decisions are out of the door. Not just because that mental model of what now counts for "data" means but also because what counts for "decisions" has changed, the pace at which those decisions need to be made have changed. It took companies a long time to die in the past. That process happens at "web speed" now.

Given all that if I don't change, I'll become a hurdle to progress. If I don't change, I can't help my company make the kind of progress it should.

You need to fundamentally rewire your brain, like I have had do rewire mine (it was painful): The data is not complete and clean, yet it is more data of more type and it contains immense actionable insights.

If you would only get over yourself a little bit.

So how to do this if you really do want to be God's gift to web analysis?

The Six Step Soul Cleansing Process.

Based on my own personal evolution in this space I recommend you going through the following six step cleansing process to ensure that you are doing this right, and you move beyond the deeply counter productive data obsession.

1) Follow best practices to collect data, don't do stupid stuff.

2) Audit your data periodically to ensure you are collecting as complete a data set as possible (and as accurately as possible, #1).

3) Only collect as much data as you need: There is no upper limit to the amount of data you can collect and store on the web.

4) Ditch the old mental model of Accuracy, go for Precision (more here: Accuracy, Precision & Predictive Analytics). It might seem astonishing but your analysis will actually get more accurate if you go for precision.

5) Be comfortable, I mean really freaking comfortable, with incompleteness and learn to make decisions.

6) [In context of decision making] It used to be Think Smart, Move Fast. I think the next generation of true Analysis Ninjas will: Move Fast, Think Smart. Remember there is an opportunity cost associated with the quest for perfection.

An example of #1 is if you are using third party cookies in your web analytics tool like Omniture or CoreMetrics or WebTrends etc then you deserve the crappy data you are getting. For #2 use various website scanning tools for ensuring complete implementation, each vendor has their own, just ask. #3 is the reason more attempts to data warehouse web analytics data end up as massive expensive failures, or why you then get trapped constantly "mowing the grass".

You are not going to believe me but in #4 if you actually go for precision your analysis will actually get more accurate over time (whoa!).

#5 is the hardest thing for Analysts (and for many Marketers) to accept. Especially those that have doing data analysis in other fields. They are simply not comfortable with 90% complete data. Or even 95%. They work really really hard to get the other 5% because without that they are unable to accept that they could make business recommendations. Sometimes this is because of how their mental model is. Sometimes is is because the company is risk averse (not the Analyst's fault). Sometimes it is out of a genuine, if misplaced, desire to give the prefect answer.

Of course the net result is that lots of data collection, processing and perfection exercises happen. The business is starved for any insights to make even the most mundane decisions. I have had to layoff Analysts who simply could not accept incompleteness and had to have data that was clean and complete. Very hard for me to do.

#6 is a huge challenge because it requires an experience that most of us don't possess. Of having been there. Because of working in companies that plug us into the tribal knowledge and context. Because we work in massively multi layered bureaucracies in large companies. In my heart of heart I believe, sadly, that it will take a new generation of Analysts and a new generation of leaders in companies. Still we must try, even as I accept the criticism that the 10/90 rule is not followed and that we don't have enough Smart Analyst.

So: Best practices that collect as complete a data set as possible precisely allowing you to look beyond the incompleteness resulting you in moving fast while thinking smart.

Before You Jump All Over Me and Yell: Heretic!

Notice what I am not saying.

I am not saying make wrong decisions.

I am not saying accept bad data.

I am not saying don't do your damdest to make sure your data is as clean as it can be.

What I am saying is that your job does not depend on data with 100% integrity on the web. Your job depends on helping your company Move Fast and Think Smart.

I am also not saying it is easy.

Reality Check:

We live in the most data rich channel in the universe, we should be using data to find insights, no matter how a little bit off the perfect number they might be.

Just consider this.

How do you measure the effectiveness of your magazine ad? Now compare that to the data you have from doubleclick. How about measuring the ability of your TV ad to reach the right audience? Compare that with measuring reach through Paid Search (or Affiliate Marketing or …..). Do you think you get better data from Neilsen's TV panel of between 15k – 30k US residents to represent the diversity of TV content consumption of 200 million tv watching Americans?

There is simply no comparison. So why waste our life trying to get perfect data from our web sites and online marketing campaigns? Why does unsound, incomplete, and faith based data from TV, Magazines, Radio get a pass? Why be so harsh to your web channel? Just because you can collect data here means you won't do anything because it is imperfect?

Parting Words of Wisdom:

Stuart Gold is a VP at Omniture. Here's a quote from him:

"An educated mistake is better than no action at all."

Brilliant.

The web allows you to make educated mistakes. Fast. With each mistake you become smarter. With each mistake your next step becomes more intelligent.

Make educated mistakes.

EOM.

Ok now its your turn.

What do you think of the web data quality issue? What are the flawed assumptions I have made in making my recommendation above? How do you ensure your data is as complete and as precise as it can be? Got tools or horror stories to share? What is the next data collection mechanism on the horizon that will be our salvation on the web?

I look forward to your comments and feedback. Thanks.

PS:
Couple other related posts you might find interesting:

• Data Quality Sucks, Let’s Just Get Over It
• Web Analytics Technical Implementation Best Practices
• The Ultimate Web Analytics Data Reconciliation Checklist
• Convert Data Skeptics: Document, Educate & Pick Your Poison
• The Great Web Data Capture Debate: Web Logs or JavaScript Tags?

Web Data Quality: A 6 Step Process To Evolve Your Mental Model is a post from: Occam's Razor by Avinash Kaushik