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

We might actively think about the metrics we are computing (and avoid rookie analysis mistakes).

But it is rare that we, "Web Analysts", actually think, I mean think, about the story we are telling.

I think that's because that is not our job (I mean that in all seriousness).

Our job is to report data. On good days it is to understand and segment and morph and present analysis.

But we don't think about the implications of the data in a grander context and we don't think about the role we can play in connecting with the Business, the Marketers and be so bold as to try and change behavior of decision makers. Change company cultures.

This blog post is a short story about my small attempt at changing the culture and setting a higher bar for everyone. Using data.

The Use Case:

The data in question was survey data. This one was specifically about a day long conference / training / marketing event for current and prospective customers.

On a five point scale for each Presenter the Attendees were asked to rate "how satisfied were you with the presentation and content".

Quite straightforward.

Here are the results:

But you can also imagine getting this kind of data from your free website survey, like 4Q from iPerceptions ["Based on today's visit, how would you rate your site experience overall?"].

Or if you use free page level surveys from Get Satisfaction or Kampyle ["Please share your ratings for this page."]

In those cases you would analyze performance of content or the website.

The Data Analysis:

On surface this is not that difficult a problem to analyze.

Here is a common path I have seen people take in reporting this data, JAI! Just Average It! :)

The actual formula is to take the average of the last three columns (satisfied through extremely satisfied).

This is ok I suppose.

I find people have a hard time with smaller numbers and then you throw in the decimals and you might as well call it quits.

Your boss, Bruce, eyeballs this and says: "Looks like everyone performed well today, let's uncork the champagne."

Meh!

Those a bit more experienced amongst you know this and what we might see from you is not averaging but rather a more traditional Satisfaction computation.

The formula is to add the three ratings (satisfied through extremely satisfied) and divide that by the total number of responses. For Jonny: (6+12+0)/18

A bit better from a communication stand point.

6.0 is a number hanging in the air naked, without context, and hence is hard to truly "get".

100% on the other hand has some context (100 is max!) and so a simple minded highly paid executive can "get" it. Jonny, Chris and Apple did spectacularly well. Will and Brian get a hug, Guy was great (come on, 89% is not bad!!).

The Problem.

Well two really. One minor and one major.

The minor problem is (as you saw in Guy's case immediately above) percentages have a certain nasty habit of making some things look better than they are. From a perception perspective.

My hypothesis is that in general human beings think anything over 75% is great.

So maybe we should not use percentages.

My major problem is that this kind of analysis:

1. rewards meeting expectations
2. does not penalize mediocrity

Both are a disservice in terms of trying to make the business great. I have to admit they are signs of business as usual, let's get our paycheck attitude.

Think of mediocrity. Why in the name of all that is holy and pure should we let anyone off the hook for earning a dissatisfied rating? So sub optimal!!

Consider "meeting expectations". I was upset that our company was not shooting higher. Accepting a rating of Satisfied essentially translates to: "as long as we don't suck, let's accept that as success".

What a low bar.

I believe that every business should try to be great. Every interaction should aim to create delight. It won't always be the case, but its what we should shoot for.

And its what we should measure and reward.

Why?

Because our way of life should be to create "brand evangelists" through customer interactions that create delight.

You like us so much, because we worked so hard, because we set ourselves such a high bar, that you will go out and tell others. Be our Brand Evangelist.

Why?

So we don't have to do that.

The Solution.

Now it is very important to point out that worrying about all of the above was not in my job description. As the Manager of a small team of Analysts (or as an Analyst) I am supposed to supply what's asked for (sure with some analysis).

But I made two major changes to the calculation, and one minor.

1. Partly inspired by the Net Promoter concept I decided to discard the Satisfied rating.

   
   When we spend money Marketing (/Sales / Teaching / Advocating) I am aiming for delight.

2. Decided to penalize us for any negative ratings (even if slightly negative).
3. Index the results for optimal communication impact.

I call the new metric: Brand Evangelists Index. (Ok so its a bit wordy.) BEI.

The actual formula applied was:

{ [ (Very Sat + Ext Sat) - (Not Sat + Not At All Sat) ] / # Responses } *100

The Results.

Here's what the success measurement looked like:

The result was a radically different understanding of quality and impact of each Presenter.

Not obvious?

Check out all three measures next to each other:

Superyummylicious!

You can see how the Brand Evangelists Index separates the wheat from the chaff so well.

Compare Jonny's scores for example. Pretty solid before, now a bit less stellar.

In fact Will who initially scored worse then Jonny is now 11 points (!!) higher than Jonny.

That's because the BEI rewards Will's ability to give a "delight" experience to a lot more people (as should be the case).

Compare the unique case of Guy Berryman.

In other computations Guy was dead last but there was not much difference between him and say Will and Brian. Just a few points.

But the Brand Evangelists Index shows that Guy was not just a little bad, he was badly bad.

Sure he got a couple bad ratings but Guy failed miserably at creating delight.

He failed at creating Brand Evangelists.

And if we invest money, in these times or in good times, we demand more. Guy can't do, or has to do a lot better.

Note that Apple could also use some mentoring and evolution.

The Outcome.

Initial a few people said what the freak! Some stones were thrown.

But I took the concept of the Brand Evangelists Index two levels higher and presented it to the VP and the CMO.

They adored it.

The reasons were that the Brand Evangelists Index

1. demanded higher return on investment
2. it set a higher bar for performance and
3. it was truly customer centric

The BEI became the standard way of scoring performance in the company.

[In case it inspires you: That year I received the annual Marketer of the Year award (for the above work and other things like that). Imagine that. An Analyst getting the highest Marketer award!]

The Punch Line.

When you present data think of not just the data you are presenting but what are you measuring really and how you can lift up your company.

You have the data. You have immense power.

Now your turn.

What do you think of the Brand Evangelists Index? How would you have done it better? Got your own heroic stories to share? I would love to know how you used data to alter a company's culture.

Thanks.

PS:
Couple other related posts you might find interesting:

• Make Your Analysis/Reports “Connectable”
• Seven Steps to Creating a Data Driven Decision Making Culture
• Lack Management Support or Buy-in? Embarrass Them

Excellent Analytics Tip #16: Brand Evangelists Index is a post from: Occam's Razor by Avinash Kaushik

An Analysis Ninja, let's call him Philip Walford, asked a delightful question. Philip wanted to know if the impact of a faith based initiative in his company, product demo videos, could actually be measured using data.

Hurray!

Faith is good. Data is better. : )

[And before you flame me: know that I love my religion more than you love yours. Wait. That did not come out right. Let me rephrase that.]

In this thanksgiving week 2008 post I'll share Philip's question about how to identify value of video product demos on an ecommerce site, and my answer about involving customers.

Here's Philip. . . .

We are a large retailer with a lot of product on our site. In the past we have invested lots of dollars and time producing things like demo videos for our products, or adding other features and tools to our website to provide more information about a product. Our goal is to inspire customer confidence in their purchase (by giving them as much information is possible).

The question is, what are the KPIs of things like a demo video.

My recommendation was to measure conversion rate for the segment that views the video. If conversion is higher then the videos are bringing value. Others in my company have presented the hypothesis only customers that are a lot more invested in buying the product are likely to click on the video link and hence "pre qualified", hence that segment would have had a higher conversion rate regardless.

I understand their perspective but I feel they are reading too much into the situation but I don't know how to argue this point. There are several directions we could go with this but I wanted to see if you could share some guidance on this issue.

My answer to Philip. . . .

This is a complex problem, more than might be apparent on the surface.

It is also an example where it can be easy to jump into bed with your web analytics tool to get satisfaction but you wake up in the morning feeling. . . . well. . . . less than satisfied.

But before we go there I have to give a ton of credit to Philip and his crew for being skeptical of reading too much into their own opinions or biases.

I firmly believe that people who work for a company rarely (never!) represent customers. They are too close to the company and too different.

Just because I work for Microsoft and use a Zune (yes I do!) does not mean I can be a effective customer representative of Microsoft Zune customers. Company employee opinions rarely reflect those of customers. Do please be aware of that.

So when looking to make decisions, look for data (quant or qual).

I'll present Philip with three solutions / options as he battles the challenge of figuring out if the investment of muchos dineros in creating product videos is worth it (besides the fact that these videos ooze sexiness!).

1) Use ClickTracks (Compute Contextual Influence)

There are two challenges with using clickstream data and the "typical" measure of conversion rate to determine success.

A] You might be looking at a "biased" segment (as challengers to Philip's recommendation mentioned). I.E. Only the highly motivated people.

B] By comparing all people who converted and viewed the video with those that converted and did not see the video you are not comparing fair segments. You are also lumping all other "convince our visitors to buy" tools into one large bucket. Tools like Comparison Charts and Product Screenshots and Product information and Customer Reviews and more.

It is quite possible that those other tools might be getting people to convert at a much higher rate and by dumping them all together you are not being fair.

And of course you'll get a wrong read on conversion impact of the videos.

So even if you use your web analytics tools (your Google Analytics or Omniture or WebTrends or CoreMetrics or whatever) try to compute "contextual influence" (value of each feature in context of the others).

It is actually very hard (damn near impossible) to do this in all those tools (even for the Paid solutions, even after you plunk down half a million dollars for the mandatory Data Warehouse "add on").

ClickTracks is the only tool I know of that can do this out of the box, using its terribly named "funnel report". No data warehouse. No extra tags or variables or sprops or wt_&*#$. In fact not even much IT, I just need admin access to my tool (not site, web analytics tool).

Its easy to use. Create a hierarchy of your website. Add individual or groups of pages into each stage (notice I did not say step because you can jump steps here). Add an outcome (in my case say "Thanks for placing your order" page). Click Calculate.

Boom!

[You are not supposed to be able to read the analysis, sorry, privacy dictates that.]

What I want you to note is two things.

This is a site where each stage means a view of the site (and like a traditional funnel how many people get in, get out, move on etc).

Secondly note that each box (which represents a page/'s or a tool – videos, comparisons, reviews etc) has a different stage of blue.

What this lovely report does for you is compute "the influence"of each of those pages/tools in driving the ultimate outcome – purchase here. The darker the blue the more "influential" that piece of content. [Influence is defined by the existence of that piece of content in the visitor session, regardless of what path the visitor took, regardless of when the content was seen.]

Ain't that super sweet?

The analysis you see above is for a real ecommerce website. What it proved to us, delightfully, was that the product videos, we had created at a cost of over one hundred thousand dollars, yellow star above, was the least influential tool we had on our site.

The most influential, sexy pink star above, was a tool that had cost us $8 to produce – it was a page that compared different versions of the product (information that was handily available in the company).

We used actual customer behavior. We analyzed contextual segments. Ultimately it allowed us to put our precious few resources in the right area.

Of course it is quite likely that everyone who came to the site and did not buy (convert) might have loved the videos and rushed to stores to buy our products (one HiPPO actually said that!). There is no way to prove that using just the web analytics data.

What we did is proved impact on online buyers.

As to the HiPPO. . . . read on. . . .

2) Use Surveys (Actively Collect VOC)

When in doubt (or confronted by a HiPPO, remember don't run) what better way to go then gather some Voice of Customer. Dare I say the voice of god? :")

Two things I have tried (of many!) that work a lot of the times. Each covers one unique bucket of visitors to your website.

A] Consider sending a simple post purchase email survey to customers who have purchased on your site and ask them for the key influencers of their purchase.

You could share with them the various tools you have on your site (product information, comparison tools, images, videos, customer reviews etc etc) and simply ask them to rank order them in order of importance.

Don't ask them to tell you how much they like them, or choose ones they like, they tend to pick all. :) Just ask them to rank order. Or use a tactic similar to that.

This tells you want works for those who buy.

For the 98% that will never convert on your website. . . .

B] Consider a onsite survey like 4Q (though 4Q can only be customized so much so perhaps you want to use either your own or one of the big daddy paid survey tools).

This will go to a small random sample of people who are on your site (who may or may not buy). You'll ask them three or four questions about why they were there (primary purpose) and then what tools/features of your website they liked (rank ordered if at all your survey company can do that).

That will give you what you want.

Since this can also be thought of as a page level problem, you can also use something passive, a page level survey / poll, like Kampyle on your product pages and ask people to quickly rate the various features. There is a Site Content feedback topic in Kampyle which you can customize.

Now you have the most important piece of data you need, your customer's. Few website owners / marketers / hippo's can argue with this. Leverage this advantage.

Finally one last option for you. . . . hopefully one you'll use before you write a chq for a hundred grand to create your videos. . . .

3) Use… wait for it….. Testing! (Measure Actual Customer Behavior)

I am sure this does not surprise you. Run a A/B or Multivariate Test and let your customers help inform you of the value of these features.

For 30% or 40% or whatever %, don't show the product demo videos and for the rest show the product demo videos and see the impact on the data. Boom (!) you have your answer, without any biased opinions.

It is certainly going to take you a small amount of effort, get the Website Optimizer, talk to your IT folks, create version of the page with no product tour link etc.

But you are making a very expensive decision for your company are you not?

And here is the additional benefit of testing. You are free to use any kind of "conversion".

You can measure success as conversions (submit order).

You can measure success (of the test) as number of people abandoning from the product page.

You can measure success as the time people spend on the product page. [There is a very cool javascript code that does this with the Google Website Optimizer, it is especially helpful for rich media / flash sites. Without a doubt other vendors can do this as well, just ask.]

You can measure success through your survey tool if it is integrated (this is some extra work sadly, but for big bets I recommend it).

You can integrate your analytics tool with your testing tool (say Google Analytics with Website Optimizer) and use other metrics to measure success such as bounce rate or electric shocks etc :).

[For GA and GWO ROI has integration instructions .]

The bottomline is that you can define success and then let the customers tell you.

That's my answer to Philip.

Sounds exciting?

Am I the only one who thinks when you do this kind of analysis you are in a nearly orgasmic state?

Yes these methods are some small amount of work. But nothing in life worth having is easy. The tools might be free, but that does not eliminate your need to investing your time and effort! :)

And on the positive side with a recession looming people who involve customers in making decisions, rather than their opinions, will win big. The "guessers" will not win big. They might even win small. Or fail.

Plus if you do this you'll be a Analysis Ninja, not a Reporting Squirrel.

Ok now your turn.

Have you tried to analyze the features like Video Demo's on your website? Or perhaps other complex features you have launched? What works for you? What totally failed? In my recommendation to Philip, what did I overlook?

Please share your feedback, critique and hurray's.

Excellent Analytics Tip #14: Measuring Value of Ecommerce Sales Tools is a post from: Occam's Razor by Avinash Kaushik