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

Yet it is rarely followed.

We almost always present data.

Actually we don't present data, we send out reports. With data. Lots of it. With 6 size font and some pies and stacked bar graphs thrown in.

Then we are frustrated that no one seems to pat us on the back, sing songs in our glory, give us more money.

We don't truly tell stories because it seems like a lot of work. And it can be. But you'll be surprised at how often it is simply a matter of framing things differently, letting your imagination roam free.

Last month I had to present to a group of executives in New York. One of the key things I wanted to communicate was the power of not doing random advertising but rather using freely available data to target the advertising on sites where relevant audiences exist.

Goals Summary:

Below is how I did it. . . . hopefully it will inspire you to look for stories in your data, stories that will hold interest and might even get you some smiles (and you know that a raise is not far behind!).

My first step was to try and tap into current events / pop culture. That calls for some research. I use Google Insights for Search as the best way to get a pulse on what people find interesting.

Specifically what I often do is run this query: Who are the most popular celebrities in New York in the last 30 days?

Turns out it is someone called Kim Kardashian. It also turns out I have no idea who this person is, an unfortunate side effect of not have time to watch television.

Quick Google search and I am caught up on why Ms. Kardashian is "famous". She has some overlap with Paris Hilton in terms of the path to fame.

The key ingredient for any story is to have interesting protagonists. For this story due to their popularity it will be Ms. Hilton and Ms. Kardashian.

The plot: Your business has a need to market something related to Ms. Hilton and Ms. Kardashian, a perfume or a clothing line or a cd/dvd. Amongst other things you'll want to make use of display advertising (banners / widgets etc).

How do you figure out who the right audience is, and where you'll find them? As opposed to of course buying the main banner spot on www.yahoo.com were your ad might be a hit or a miss.

Tools for doing audience segmentation were quite expensive until recently. Google's Ad Planner is free and makes this valuable data democratic. You can segment by demographic (age, education, income, gender etc) and psychographic (Extreme Sports Fan, Film Buffs, Fantasy/Comic Book Readers etc) data.

Perhaps its most cool feature is the marriage between all the above data with Google's search data.

That's where the analysis starts.

Question: What are the websites that are visited by people who have searched for the keywords "paris hilton" and "kim kardashian"?

Here's the answer:

[Click on the image for a higher resolution version.]

Notice the I have typed the keywords on the bottom left. In the right frame are the sites that are visited by those who searched for those two terms. Some obvious sites, many surprises (good thing, now we know!).

I have a habit of sorting by Comp Index, just to check out concentration of the audience. For example a comp index of 990 means that you are approximately nine time as likely to find the same audience (paris, kim searchers) on wallpaperbase.com.

If you look at the higher resolution version (click on the image) you'll easily find out how many page views are on the target site, what kind of advertising they accept, ad impressions/day and other data you need to create a media plan.

So far so good.

I have always believed that Men are more interested in the kinds of stories and "entertainment" value that Ms. Hilton and Ms. Kardashian generate.

The nice thing is I can validate that hypothesis. I simply open the Gender option in the left panel and choose Male.

You are looking at the top part of the segmentation panel. Notice the delta between UV (users) between the overall segment and just the Males.

Turns out I was not totally right. Males make up a bit less than half of the audience.

No worries. They are still a lot bigger than what many people think (and it is wrong to think it is overwhelmingly female).

My next believe, perhaps controversial, is that older males are more interested in Ms. Hilton and Ms. Kardashian than younger males. Now this seems odd because Ms. Hilton and Ms. Kardashian seem to be more cool and hip and more of a young generation cup of tea.

Well we can test my hypothesis, in addition to Gender I can also choose Age. . .

This data is still just for people, in this case Males, who searched for the key words paris hilton and kim kardashian.

It might have been a odd thing to say but it seems that 45 and older males are a lot more interested in Ms. Hilton and Ms. Kardashian. By almost two to one.

Surprised?

: )

Let's prep for the punch line of this story.

I have identified a audience that is of value to my goal, marketing Ms. Hilton and Ms. Kardashian (or things connected to them).

I want to target the top end of this audience, Males 55 and older, how many of them are there and where can I find them (to ensure my advertising will be relevant for this audience and my ad dollars are spent wisely)?

Here you go. . .

[Please click on the image for a higher resolution version.]

How about now… surprised?

I was.

The top sites listed for this audience (older Males interested in Ms. Hilton and Ms. Kardashian) turns out to be bedrock sites, typically, for Republicans and the Conservative movement! Starting with a Comp Index of 1700 for impactguns.com. Other sites: weeklystandard.com, rushlimbaugh.com, nationalreview.com, worldnetdaily.com, and townhall.com.

Not in my wildest dreams would have I have expected that this audience would be so highly correlated with actual searches done for Ms. Hilton and Ms. Kardashian. It seems odd with the conservative moral values espoused.

Very Important: I am not judging them. To each unto his / her own.

For my marketing campaign one more valuable nugget of insight is in th above data (click above for higher resolution). Turns out they are also very rich. Note the prominent appearance of morningstar.com, pgatour.com, seekingalpha.com and ft.com.

So a bumper crop: right audience, lots of money to spend. That's hot!

Now I have to go execute the campaign and I know where to target my ads, how many impressions/day I can expect and how many people I can hope to target.

Relevant audiences change with seasons, hot trends, shifting preferences. Repeat the analysis to ensure you have the most current data.

End of story.

Closing Thoughts:

Turns out this was a very effective story to tell, most people in the room were media buyers (especially offline).

They were impressed with the kind of data we have online, and how easily accessible it was.

They will never forget how wrong one can be about who the relevant audience might be (it would be impossible to guess the Weekly Standard, Rush Limbaugh audience might have any interest in Ms. Hilton or Ms. Kardashian).

Data Wins.

Ok its your turn now.

When you present data how do you tell your stories? How easy or hard is it? Got a favorite story to share with us?

What did you think of the above story? Methodology or conclusions? What did you link? What did I miss?

I would love to hear from you. Thanks much.

PS:
Couple other related posts you might find interesting:

• Make Your Web Analysis / Reports “Connectable”

• Competitive Intelligence Analysis: Google Ad Planner

• Competitive Intelligence Analysis: Google Insights for Search

Paris Hilton, Kim Kardashian & Telling Stories With Data is a post from: Occam's Razor by Avinash Kaushik

Guess what?

It's true!

All web analytics tools have a smattering of metrics and key performance indicators that were created just because someone decided it would be cute to add / subtract / multiply / divide some numbers.

Many of these don't pass the first sniff test and when if they do you are still left wondering: "What in God's name and all that is holy in this world am I supposed to action based on this metric?"

The answer?

Nothing.

With that gloriously upbeat set up let me tell you what we are going to cover today: Three metrics that are available in pretty much all "adult" web analytics tools. Daily, Weekly, Monthly Unique Visitors.

They are so common yet most people don't understand them well enough and fewer still realize how harmful these can be to your health even in day to day use.

So in this post we try to understand the most basic of the web analtyics basics, the Unique Visitor computation.

What's a Unique Visitor?

It is simple really. . . .

Technical Definition: Count of all the Unique cookie_id’s during a given time period.

English Definition: The first time someone visits your site a first party persistent cookie is set in their browser. This cookie lasts any where from several months to several years. Each time that person visits your site that cookie identifies them as the same browser.

Notice I said browser, not person. It is likely, but not always true, that each a unique visitor is a unique person.

You can learn a lot more about Visits and Unique Visitors in this post: Standard Metrics Revisited: #1: Visitors.

Very predictably every 18 months or so the blogosphere goes wild with how accurate, or not, the Unique Visitor metric is. Much mud is thrown around. Indignations are foisted on the world. Name calling ensues.

Regardless of that Unique Visitors remains a valuable metric that used correctly, in place of Visits, measures success of your online marketing efforts.

Oh and your best weapon against ignorance? Education. See above post on Visitors. And this one: A Primer On Web Analytics Visitor Tracking Cookies. It covers cookies and deletion rates and other such yummy stuff. Read that and you have my word you'll be the smartest cookie in the room.

See what I did there? :)

Daily, Weekly, Monthly Unique Visitors:

In many web analytics tools (say Yahoo! Web Analytics, Omniture, WebTrends etc, but not in Google Analytics ) you'll also see Daily Unique Visitors, Weekly Unique Visitors, Monthly Unique Visitors and, sometimes, Absolute Unique Visitors.

Each is trying to tell you something about Unique Visitors, yet if you pause and think about it, I mean really pause and think about it, you'll realize two of these are really bad for your health, and the third should be used with caution.

The core reason is that what looks attractive initially becomes progressively worse as you extend the time period. The Daily metric, so to speak, does not even last in value beyond two days!

So let's spend a second understanding this slightly yucky phenomenon.

Here's the data, from omniture.com, where WebTrends is used for tracking Visitors. . .

Now let's go measure the complex set of metrics that'll stare at you, let's say when you crack open Omniture or WebTrends (or pretty much any other competitive web analtyics tool).

The Web Analytics Unique Visitors Story:

Before that realize that what you see will depend on the time period you are looking at. [Arrrh!]

And before I really really jump in… you'll see a metric called Absolute Unique Visitor. I am going to use that as a proxy for how unique visitors should be computed correctly, regardless of what time period you are computing it for. Keep an eye on that number.

Looking at Month 1 and Week 1 at the end of Day One:

If you ran your reports at the end of day one here is what your analytics tool will report to you, with some delight and joy I might add. . .

Makes sense right? Do a happy dance, high five someone next to you, heck give them a hug and a kiss.

Now let's make this more "complicated".

Looking at Month 1 and Week 1 at the end of Day Two:

If you ran your reports at the end of day two here is what you'll see. . .

Slow down the happy dance a bit.

Note the silly effect on Daily Unique Visitors, even though it was the exact same folks, Dennis and Matt, from the earlier day who visited on day two. They get counted twice.

Life lesson: Daily Unique Visitors is a useless number if you are looking at a time period of more than one day!

Let's keep going.

Looking at Month 1 at the end of Week One:

Crack open your analytics tool, it has been a long week, look at the metrics, here's what you'll see. . .

Note the continuing uselessness of the Daily Unique Visitor number (and even if you trend it over time, as in the blue graph above, analyze what it is actually showing you? what's the insight?).

In your Web Analytics Tool you might see a report that looks like this:

By know you know why there is a sad frowny face in that last Total row. Right?

Repeat: Life lesson: Daily Unique Visitors is a useless number if you are looking at a time period of more than one day!

Looking at Month 1 at the end of Week Two:

Gather everyone in your close proximity in the office, form a circle, hold hands, close your eyes, say a quite prayer, now open your analytics tool. . .

The Weekly number is wrong because it counts: Avinash, Dennis, Matt, Matt again, Ian and Jim. It counts Matt again because he visited during both weekly time periods.

Life lesson: Weekly Unique Visitors metric is useless if you are looking across multiple weeks. We've covered above why Daily Unique Visitors is, to put it mildly, sub optimal.

Ok only two more scenarios left, hang in there, it gets better.

Looking at the end of Month 1, for the whole month:

By now I am sure you are 100% up to speed on what you are going to see. . .

There is now triple or double counting happening in both the Daily Unique Visitors and Weekly Unique Visitors numbers.

Life lesson: Both Daily Unique Visitors and Weekly Unique Visitors numbers are useless when you look at a time period of a month.

One last scenario, not to make your brain hurt but rather to ensure you reach the state of maximum Analysis Ninja enlightenment!

Looking at the end of Month 2, for the two months:

Tingling with excitement. . . here's what you'll see. . .

There is now triple or double counting happening everywhere, the Daily Unique Visitors, Weekly Unique Visitors and Monthly Unique Visitors numbers.

The correct measure of unique is the Absolute Unique Visitors metric because it de-dupes the unique visitors across the entire time period you are reporting on.

Life lesson: Both Daily Unique Visitors and Weekly Unique Visitors numbers are totally really useless when you look across months. Use Monthly Unique Visitors with caution, knowing it is only de-duping for each month and then summing the number for each month.

If your tool provides Absolute Unique Visitors you are in luck because then you are getting true unique visitors across whatever arbitrary time period you choose.

Google Analytics provides you with the Absolute Unique Visitors metric.

It will do that across set time periods, like the month of March (or any number of months). . .

or across arbitrary time periods, as Monday March 9th through Thursday March 19th. . .

It will dedupe the numbers when it reports to you, rather than adding the totals of each day, week or month.

Complex but bonus for Ninjas: Depending on which graph you look at, daily, weekly or monthly, it will intelligently compute the number for each time period and also show you the aggregate deduped number for that time period.

Fly in the otherwise rather healing ointment?

Google Analtyics does not compute Absolute Unique Visitors when you segment the data, when you use the Advanced Segmentation feature. Those of you who read the blog know my utter infatuation with segmentation, so you can easily understand how sad this makes me.

You can get Absolute Unique Visitors for segments by using the "create a filtered profile that just data for the segment" method and that works if you have forethought. But it is sub optimal, just like some "enterprise" web analytics vendors telling you that you can only segment if you tell them before the fact what you might want to segment later.

Why do Web Analytics Vendors torture you with Daily, Weekly, Monthly Unique Visitors?

I knew you were asking yourself this question!

Good on you Mate.

If these metrics are that sub optimal, why do web analytics vendors put us through this torture?

Simple: Compute power (translation: cost, for them).

It is very computationally intensive to calculate for you the true real (Absolute) Unique Visitor number across any arbitrary time period or across multiple weeks or months.

Increased computational intensity for the vendor means more processing time and higher costs.

So doing Daily, Weekly and Monthly counts (and then summing them up) is cheaper for them.

After the first vendor decided to do this, and there were no major outcry from Web Analytics Users (or even Ninjas!), others quickly followed.

For the more prevalent vendors in the space Google Analytics is one the rarest that provides the truly de-duped Absolute Unique Visitor metric (in aggregate, not segmented, boo!). Only time will tell when Google will buckle under the computation/cost weight and stop providing it true Absolute Unique Visitors.

[Update: Both NedStat and Xiti, two wonderful European companies do allow for computation of Absolute Unique Visitors out of their standard packages, no additional payment or gyrations required. Add Unica's NetInsight to that list as well! Hurray!!]

There are some vendors that will tell you that you can buy their more expensive data warehouse solutions (at an additional cost on top of what you pay today) and then compute Absolute Unique Visitors yourself. True. Ask for the cost. Ask if its really Absolute. If prudent, pay more. Regardless, be informed.

Long lesson.

But now you are truly at a Analysis Ninja black belt level of proficiency!

Now your turn.

Please share your comments / feedback / critique / hugs / non-hugs about this post. What does your tool do? How do you think we should improve things? What would you eliminate? What would you add? What did I miss?

PS:
Couple other related posts you might find interesting:

• Standard Metrics Revisited: #1: Visitors
• A Primer On Web Analytics Visitor Tracking Cookies
• Five Rules for High Impact Web Analytics Dashboards
• The Ultimate Web Analytics Data Reconciliation Checklist
• Excellent Analytics Tip#5: Conversion Rate Basics & Best Practices
• Excellent Analytics Tip#4: Make Your Analysis/Reports “Connectable”

Standard Metrics Revisited: #6: Daily, Weekly, Monthly Unique Visitors. is a post from: Occam's Razor by Avinash Kaushik