“I have done web analytics for five years, I have mastered Omniture, WebTrends and Google Analytics, I provide analysis and not just reporting. I feel like am an Analytics God.

What would be your advice for me in terms of next steps for my career? My goal is to climb the ranks and increase my salary.”

Let me hasten to add two things.

Michael is not his real name.

Modesty aside, :), Michael is good at what he does.

I get many emails in the spirit of this one and thought it was about time I wrote a proper post about it.

Another reason for writing the post now is that it is always a good time to think about your career path, but never more so than the current economic circumstances. Some of you face tough times, some might get laid off [see end of this post], some might make opportunistic leaps. Either way good time to ponder, do some self reflection and make a conscious choice.

Before we get going some assumptions I am making:

Every Web Analyst (or really Business Analyst) of any sort finds themselves at that critical point. Have been doing analysis for a while, now where does my career lead me?

The first and perhaps most important thing to realize that you have to make two very important very critical very life impacting choices:

Choice 1: Business or Technical.

Choice 2: Individual Contributor or Team Leader.

Each choice will help propel your career in a different direction (slope and length). Typically we don’t think that you have those choices (we all want to jump to Director / VP and get the chq, not so fast buster!).

Do some introspection.

Here’s the Avinash Kaushik Web Analytics Career Introspection Guide! Answer these questions:

#3. Are your true “Analyst” skills your massive mastery of how to solve every technical problem with every tool and how to implement anything and you could decode and reconstruct the debugging tool WASP in two days? You can hack the Google Analytics tag to capture people’s underwear size and color.

#4. Are your true “Analyst” skills your understand of your company’s business strategy, your mastery at translating “measure something” from a VP to three Critical Few metrics that bedazzle her, your ability to understand the long tail and get a ah ha moment that revolutionizes how you understand and measure of your search campaigns?

I am getting to how you can increase your salary part. Please stick with me.

Answering the above four questions honestly and critically is much harder than you think. Trust me on that.

At Intuit I truly learned the value of self awareness. Steve Bennett prioritized Management development (I’ll be eternally grateful to him for that) and my friend Scott Wilder really got me going on this path by doing my Enneagram assessment (MBTI is too shallow).

To me self awareness is the process of figuring out what you are truly good at, and really truly knowing (and accepting) what you are not good at. It takes time to get going, and is more of a lifetime journey and less a destination. It comes with great benefits. For example, I have learnt to maximize my being in roles / situations where my strengths will boost success.

Your answers to the four questions will ensure that you don’t end up in a job that 1) you’ll hate or 2) where very quickly you’ll rise to your level of incompetence.

There are jobs, based on your choices above, either in companies or, many people forget this, at web analytics vendors.

If you want to have a move your career forward in web analytics (from a Metrics Analyst) here are the four options for you (and yes they all will help you make more money, some more than others):

|1| Technical Individual Contributor.

A lot of people wrongly believe that to make lots of money you have to get into Management (technical or business). This is totally wrong. For the longest time, for example, I was well compensated for being a Senior Individual Contributor.

Roles in this category would include: Sr. Project Manager. Sr. Architect. Implementation God. Sr. Tech Lead. Tech Demo God (usually at a Vendor). And more.

For this role at a client (company) world the common theme in this role is that you report up to a Director or a VP and you get to set policy, rules and regulation, only have, if at all, the barest of dotted line responsibility for project implementations, you might be the master liaison with the business team and your vendor to make sure technically all that is supposed to be happening with the technical tag hacking and tool hacking is happening.

This role in the vendor world you get to go to various clients and show off cool detailed stuff that your VP of Marketing consistently screwed up so far and answer technical questions from wise guys. You might also be the one man army tapped to do rapid prototyping to prove you are better than Google Analytics (!), or it is likely that you are the point of contact for the first sixty days for a new client when your company is trying to impress the client by providing fast help (as the payment chq has not yet cleared). Make no mistake this can be fun, you get to travel, meet new companies and people.

It is quite likely that you’ll sit in the IT (CTO / CIO) function.

Career Prospects:

$$$ Prospects:

Long Term Job Title Growth:

|2| Business Individual Contributor.

If you are a Analyst today you are in a individual contributor role on the business side (if you are a Web Analyst in IT the best career move you could make for yourself is to get moved to Marketing - or a business function, it is really hard to have a strong Analyst - not reporting squirrel - role in IT).

Roles for you on the business side in this category would include: Sr. Analyst. Internal Evangelist. SPOC for CMO / CEO dashboards (supreme analysis). Central Business Liaison (for a large business, focus on getting people to implement web analytics and get going). Strategic Solutions Consultant (clearly with hype like that this a role at a vendor!). Product Genius (at a vendor, perhaps Apple :).

For this role at a company (client) the role can report to anyone from a Director to the CMO. Your job is heavily business focused - understand various businesses and their strategy and provide über analysis (pan business function) or create dashboards or be in charge of rolling Omniture across 90 business sites (beat them up until accomplished).

There are a rare few roles where you can become the internal Analytics Champion, I did this for a while. You are good at your analytics “game” but you are also a strong business person (I hate to say this but MBA / “strategic” type). You get to go around and work with VP’s, CMO’s and Sr. Leaders and identify measurements strategies for their impossible to answer questions (often they don’t know how ease these are so you totally look like a hero). As an Evangelist you pull your organization up by the bootstraps (quite gratifying).

This role in a vendor world can mean you are a product manager of the analytics product, you are a project manager for certain features, you are a professional services rep (sorry, “Strategic Solutions Consultant”) and roles like that. No one does Marketing (with a pinch of hype :) like Omniture, this excellent page on their site will help you understand what a business individual contributor role might look like at any vendor: Omniture Consulting.

For many of you there is also a option of a role I play now, an Evangelist. A business individual contributor role with significant influence over the vision and the product, as well as an opportunity to impact the external Analytics ecosystem.

Career Prospects:

$$$ Prospects:

Long Term Job Title Growth:

|3| Technical Team Leader.

Roles in this category would include: Manager, Analytics Implementation. Sr. Manager, Website Analytics. Group Manager, Web Operations Reporting. And still rare but sometimes: Manager, Web Analytics Data Warehouse (Steven I did not forget you!).

In the early genesis of web analytics, in the good old days, it was owned by IT this role was a lot more prominent in companies. Having WebTrends almost mandated that. The shift to ASP (javascript based) solutions (crediting HBX here) caused a shift of web analytics to the business side (an excellent outcome). It also eliminated the need to have a large IT staff to support web analytics.

An example is six years ago when I took over web analytics there was a four person team (one leader, three direct reports) in IT supporting just running WebTrends internally and churning 200 reports out. The shift to a asp based solution meant only one job remained and it became that of a Sr. Technical Individual Contributor (and I was lucky to have a very good one!). The other jobs were evolved or replaced with people who did analysis not reporting (an efficient use if there ever was one).

Roles in a company setting would be reporting up to Sr. Manager or Director (or rarely VP/CIO levels). Often you’ll find yourself in the Business Analytics team in the CIO / CTO function, you take care of that “web data”. :) In some companies there is also sometimes a role in the Web Analytics team that is in Marketing (/business) where you can carve out a nice technical team lead career (reporting to the Director of Web Research & Analytics :).

Roles at a vendor probably have a lot more technical team lead opportunities. Managing technical aspect of the analytics product or managing the technical army of consultants or things like that.

It goes without saying that this role requires something really really hard: Your ability to leave your leave your lone ranger mentality and the deep rooted habit of just doing all the technical stuff yourself (yes you are sooo good at this stuff and you don’t trust other people’s code).

It is harder for technically oriented people to blossom into people managers, but really that’s what you are signing up to do. You are going to have to be comfortable with some of your awesome hacker skills getting rusty as your leadership skills (and delegation!) mature.

The natural next growth in a company environment would be to

Career Prospects:

$$$ Prospects:

Long Term Job Title Growth:

|4| Business Team Leader.

When people think of making more money in web analytics jobs, 99% of the time this is the role they are thinking of. [Might I just quickly again encourage you to use the Avinash Kaushik Web Analytics Career Introspection Guide first.]

Roles in this category include: Sr. Manager, Web Analytics. Director, Web Research & Analytics. Manager, Web Metrics. Team Lead, CoreMetrics Reporting. Group Manager, Analytics & Optimization. Etc.

This role in a company setting is increasingly reporting to Sr. Directors, VP’s or, in companies that get it, the CMO. Ideal candidates were Analysis Ninja’s of supreme kind and have shown streaks of good people leadership skills. They are motivators, can inspire confidence, are inherently unselfish (key for leading people) and have the ability to charm the pants of Sr. Management (though come to think of it that might be a HR violation!).

I cannot overstate this enough: Ideally you have grown from a Reporting Squirrel to an Analysis Ninja, but your hard core technical skills are vastly overrated in this role. As is your ability to be, say, a Excel Master Blackbelt. Remember, you inspire and you lead.

This role, in a pure web analytics leader fashion, is a lot less needed or visible or available in a Vendor setting (unlike the other three above). Vendors need to mostly sell. Perhaps to analyze nedstat.com or unica.com for internal use. Or perhaps as a business lead for the $300 per hour consulting arm.

Career Prospects:

$$$ Prospects:

Long Term Job Title Growth:

That’s it. Four different job families. Each unique in its job, salary and future prospects.

My fondest hope is that as you evaluate your career that you’ll now be empowered beyond the normal job stuff that you often read. What you have above is the output of my humble experience in multiple multiple roles working as a Practitioner, Author, Evangelist, People Leader.

There is one job / role / career choice I have not covered here. Becoming a Consultant. Perhaps another day. For now let me share just this advice, the most common reason for Web Analytics Consultants failing (or not succeeding as much as they should) is that they believe technical skills are enough or just being good at business (analysis / understanding / savvy) is enough. It is not. It is hard to find both is one place as well. If you want to do that find a partner. You be the strongest Analyst on earth and let her be the Technical Goddess. Now you are set for greatness.

Before I end, I had promised something about being laid off in a down turn.

My Story.

I have had three professional jobs in the US. I have resigned from only one, the last one. The first two jobs (4.5 yrs and 2 yrs respectively) I was laid off.

The first in worst of personal financial times (market going down, first baby on the way etc). It was deeply stressful.

In hindsight though each layoff was the best thing that could have happened. Allowed me to start fresh. Each bumped my career trajectory in ways that would never have happened if I had stayed at the job.

I hope your job is secure. But if it is not I hope you take some inspiration in my humble experience of being laid off twice from good jobs (that I was good at) and the longer term results.

Ok your turn now.

What has worked in managing your own web analytics career? Anything above in my Web Analytics Career Introspection Guide resonates with you? What about the four job families? What did I not consider or get wrong?

Please share your stories, feedback and encouragement.

I appreciate your attention, thank you.

PS:
Couple other related posts you might find interesting:

• Nine Rules To Work / Live By
• Three “spire’s” of Great Leadership
• Multiplicity: Succeed Awesomely At Web Analytics 2.0!
• How To Excite People About Web Analytics: Five Tips.
• Web Analysis: In-house or Out-sourced or Something Else?
• Make a Great Vendor / Agency / Consulting Pitch - Win Big Contracts

Copyright © : 2006-2008 Occam's Razor by Avinash Kaushik | All Rights Reserved

Analytics Career Advice:”I am an Analytics God, I want more $$. How?”

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.

Copyright © : 2006-2008 Occam's Razor by Avinash Kaushik | All Rights Reserved

Excellent Analytics Tip #14: Measuring Value of Ecommerce Sales Tools

That was my call to action, Yoda inspired, last week to a group of international C-level executives. And I meant every word of it.

There is a tendency to think experimentation and testing is optional. Ouch!

I fundamentally believe that is wrong. For a few simple reasons:

# 1 It’s Not Expensive!

You can start for free with a superb tool: Google’s Website Optimizer. It is packed with enough features that I have no qualms flogging it (even though I work closely with the team!).

If you want to help our economy and pay for your tools then that is absolutely fabulous. Both Offermatica and Optimost are pretty nice options.

# 2 Six And A Half Minutes. That’s it!

Tom has tried this with many many Marketers, and its so true: If you have two different pages you want to test, it takes six and a half minutes for you to configure, test (QA) and launch a A/B test.
[Please read that literally, as it is written. You have two pages already. 6.5 mis to: Configure. QA. Launch.]

You have six and half minutes right?

I cannot recommend enough the wisdom of starting with a A/B test.

You will start fast, you will find enough problems in your company, you can show easy wins.

Aim to get to the thing vendors are selling, MVT, but start with A/B regardless of the tool you use.

# 3 Show ‘em You Are Worth It.

There is a lot of pressure on all of us to prove our worth and make significant improvements to our web business.

ClickStream analysis with Omniture or Google Analytics or ClickTracks is well and good, testing will get you on the path of taking having a direct impact faster.

By the nature of it Testing is action oriented, and what better way to show the HiPPO’s that you are awesome then by moving the dial on that conversion rate in two weeks?

# 4 Big Bets, Low Risks, Happy Customers.

Very few people appreciate this unique feature of testing: You have an ability to take “controlled risks”.

Let’s say you want to replace your home page with pictures of naked people, yes in the quest of engagement . : ) Naked people are risky, even if they are holding strategically placed Buy Now buttons.

So run a test where only 10% of the site traffic sees version B (naked people).

You have just launched something risky, yet you have controlled the risk by reducing exposure of the risky idea.

Stress this idea to your bosses, the fact that testing does not mean destroying the business by trying different ideas. You can control the risk you want to take.

# 5 Tags, CMS, Reports & Regressions: All Included!

Pretty much all Testing tools are self contained, simple to launch (A/B is brain dead easy, MultiVariate needs your brain to be awake - that’s not hard is it?), they contain all reporting built in and the data is not that hard to understand.

So you don’t have to worry about integrations with analytics tools, you don’t have to worry about rushing to get a PhD in Statistics to interpret results and what not.

You will hear super lame arguments about mathematical purity or my factorial is better and the other guy’s whatever. Ignore. It will take you a while to hit those kinds of limits. And the nice thing is by then you’ll be smart enough to make up your own mind.

What’s important is you start. Do that today. This of this as dating and not a marriage. You are allowed to make mistakes. You are not going to marry the first guy you run into. Don’t take that approach here.

So agree with me? This is attractive? Right?

Think about it this way. If your analytics career is flagging then testing is the Viagra you need to take.

Seriously.

: )

So as my tiny gift for you here are five experimentation and testing ideas for you. I’ll try to go beyond the normal stuff you hear at other sources.

# 1 Fix The Biggest Loser, Landing Page. (& Be Bold.)

Now all that is well and good. But the sad thing in a common mistake people make is get excited and then go try to test Add To Cart buttons. Or three different hero images on the home page.

That’s all well and good. But honestly that’s not going to rock your boat. [Remember you are on Viagra!]

For your first test be bold, try something radical, bet big. I know that sounds crazy. But remember you can control risk.

If you start with a A/B test with some substantial difference then you can show value of testing faster because you’ll get a signal faster, you’ll start the emotional change required to embrace testing across the organization.

My favorite place to start, is the Top Landing Pages report (or Top Entry Pages if that’s what your vendor calls it) from your web analytics tool.

Find the biggest loser, the one with the highest bounce rate.

Click and look at the sites sending traffic to this page, look at the keywords driving traffic to this page. That will give you clues about customer intent (where people come from, and why).

Come up with two different (bold) ways to represent that page and deliver on that customer intent.

Your first A / B / C test.

# 2 Test a Single Page vs. Multi Page Checkout.

One of the highest ways to improve conversion is to reduce Cart & Checkout Abandonment rates. Take money from people who want to give you money!

Some websites have a one page checkout process: Shipping, billing, review and submit.

Some have it on four pages.

I have seen both work, you never know, it really depends on the types of visitors you attract.

So if you have a single page why not try the multi (if your abandonment rate is high, say more than 20% :). Or vise a versa?

I have seen very solid improvements in these tests.

Or here’s a bonus. Many shopping cart (or basket to my British friends) pages have a Apply Coupon Code box. This seems to case people to open Google and search for codes. So why not move this coupon code box to the Review Before Submit page?

It won’t send those who don’t have a coupon code looking for one, and by the Review Order page they are way too committed. For those that have a coupon code they can still apply it.

In both these scenarios you are helping your organization find value quickly by touching a high impact area.

And remember, this works for lead submission forms and other such delights.

# 3 Optimize the Number of Ads & Layout of Ads.

Ad supported sites are numerous. And the there is so little restraint, the core idea seems to be let’s slap as many ads on the site as we can.

More ads = more clicks = more revenue.

Usually this is never tested.

[I can't read Norwegian so this could be wrong, but I counted a total of 19 ads on this page! Ten above the fold. Important point: American sites are just the same.]

So test the number of ads you should have on a page. Its not that hard. It can be a simple A/B test or a MultiVariate test.

In a memorable test the client actually reduced the number of ads on the page by 25% and the outcomes improved by 40%. I kid you not, 40%. And guess in which version customers were happier.

There is a built in assumption there that you are simply not selling impression, in which case pile on the ads in the pages. You are not being held accountable for outcomes so enjoy the ad party.

Here’s a bonus idea.

There are sites were the ad is in the header, it takes up the whole header and is the first thing that loads. I have only seen one case where that worked.

The header takes up 30% of the space above the fold on a 1024 resolution.

So if that is you why not try a test with the header ad and without? See which one improves overall conversion / outcomes?

The other bonus idea is to try different ad layouts. Most people have banner blindness, top of the page and in the middle of the content (as in Yahoo news).

Why not try different layouts and formats? If not to see which one works the best then to just annoy your customers? :)

# 4 Test Different Prices / Selling Tactics.

You can of course test different pretty images, why not try to reinvent your business model using testing?

A company was selling just four products. But the environment got tough, the competitors got competitive. How to fight back? Some “genius” in the company had an idea “Why don’t we give our cheapest product, currently $15, away for free?”

CMO says: Radical idea. CEO says: Are you insane? CFO says: No way!

Now it did present a fundamental challenge, no one like to give revenue up. And people worried about how successful it would be, what would be the revenue impact, why would anyone buy a non-free version etc etc.

Rather than create prediction models (with faulty assumptions!) or giving up in face of the HiPPO pressure, the Analytics team just launched a A/B test. And they controlled for risk (after all the CFO did not want to go bankrupt) by doing a 95% control and 5% version A test.

Perhaps unsurprisingly the free version of the product sold lots of copies.

That was not surprising.

What was surprising was that free helped shift the sku mix in a statistically significant way, i.e the presence of free caused more people to buy the more expensive options. Interesting. [In a delightfully revenue impacting way!]

The other positive side effect was to cause lots of new customers to be introduced to the franchise, as they “purchased” the free version. Lovely.

Here are some bonus ideas.

If you give discounts try 15% off vs $10 off (people tend go for the latter! :)).

Try $25 mail in rebate vs $7 instant rebate (or change amounts to suit).

You get the idea.

# 5 Test Box Layouts, DVD Covers, Offline Stuff.

Let’s say you are launching a new product or a dvd or something similar. You want to figure out what layout might be more appealing to people in stores.

You could ask your mom to pick a version she likes.

You could ask your agency to ask a few people.

Or you could launch a test online and see which version is rated highest by your website visitors!

I have done tests for DVD covers and the results were surprising.

Or here’s another idea…

You are a multi channel customer. You sell bikinis. Now you want to sell Accounting Software. Why not try it on your website before you reconfigure your stores?

Or you are Wal-Mart and it is expensive and takes a long time for you to put new products in your stores. That makes it risky to start stocking the “on paper hideous but perhaps weirdly appealing” Zebra Print Occasional Chairs in your store. What if it bombs?

Well why not add it to your site, see if it sells. If it gets 15 positive customer reviews (!!), then you know you have a winner on your hands.

The actual launch process is faster, you can reduce risk, and you don’t have to rely on just your company employees (the fashion mavens) from picking winners and losers.

All done.

I hope that you’ll find both compelling reasons for starting experimentation and I have managed to stretch your mind beyond “honey let’s start testing shopping cart buttons”.

There is so much you can do. This recession season buy your CEO the gift that keeps giving, a experimentation and testing tool.

Here’s a summary for you. . . .

Five reasons for online Experimentation & Testing:

#1 It’s Not Expensive!
#2 Six And A Half Minutes. That’s it!
#3 Show ‘em You Are Worth It.
#4 Big Bets, Low Risks, Happy Customers.
#5 Tags, CMS, Reports & Regressions: All Included!

Five off the beaten track Experimentation & Testing ideas:

#1 Fix The Biggest Loser, Landing Page. (& Be Bold.)
#2 Test a Single Page vs. Multi Page Checkout.
#3 Optimize the Number of Ads & Layout of Ads.
#4 Test Different Prices / Selling Tactics.
#5 Test Box Layouts, DVD Covers, Offline Stuff.

Ok now its your turn.

What are the reasons your company is not jumping on the awesome testing bandwagon? If it did, what finally convinced them? If you are doing testing, care to share some of your ideas? Anything off the beaten path you have tried? Any massive failures?

Please share your feedback, insights and stories.

Thank you.

PS:
Couple other related posts you might find interesting:

• Experimentation and Testing: A Primer
• Build A Great Web Experimentation & Testing Program

Copyright © : 2006-2008 Occam's Razor by Avinash Kaushik | All Rights Reserved

Experiment or Die. Five Reasons And Awesome Testing Ideas.

If you have nothing and you are starting out then sure have a few different ones, stress test them, pick the one you love (just like in real life!), but then practice monogamy.

At the heart of that recommendation is a painful lesson I have learned: It is a long hard slog to convert an organization to be truly data driven.

And that’s with one tool.

Having two tools just complicates life in many subtle and sub optimal ways. One “switch” commonly occurs is the shift from fighting the good fight of getting the organization to use data to bickering about data not matching, having to do multiple set of coding for campaigns (the page tagging work itself is trivial) and so on and so forth.

In a nutshell the efforts become all about data and not the quest for insights.

So if you can help it, have one tool. Bigamy atleast in this case is undesirable. [If that does not convince you remember the magnificent 10/90 rule from May 2006 when I was but a naïve web analytics Manager.]

But.

Pontification aside the reality is that many people run more than one tool on their website (though hopefully they are all on their way to picking the best of the lot). That means the bane of every Analyst’s existence: Data reconciliation!

It is a thankless task, takes way more time then needed and the “game” is so rigged that 1] it is nearly impossible to get to a conclusion and 2] it is rarely rewarding - i.e. worth it.

But reconcile we must. So in this post I want to share my personal checklist of things I look for when going through a data reconciliation exercise. Usually this helps get things to within 95% and then I give up. It is so totally not worth it to get the rest!

* This post is a bit technical, but a Marketer should be able to understand it. And my goal is you smile three times while you read it, either from the inside jokes or from the sheer pain on display! *

So if you are starting a data reconciliation project for your web analytics tools, make sure you check for these things:

Intrigued? Got your cup of coffee or beer? Ready to become sexycool?

Let’s deep dive. . . .

#1: Comparing Web Logs vs. JavaScript driven tools. Don’t.

I know, I know, you all get it. Yes you understand that this is not just comparing apples and oranges but more like comparing apples and monkeys.

For the five of us that are not in that camp: these two methods of collecting data are very different, the processing and storage is different, the things that impact each are very different.

So if you are using these two methods then know that your numbers might often not even come close (by that I mean within 85 - 90%).

The primary things that web logs have to deal with are effective and extensive filtering of robots (if you are not doing this you are screwed regardless), the definition of unique visitor (are you using cookies? just IP? IP + User Agent ids?) and, this is increasingly minor, but data caching (at a browser or server level) can also mean missing data from logs.

The primary things that afflict javascript tags, in this context (more later), are browsers that have javascript turned off (2-3% typical) and in that case will have their data missing from tag based files.

Be careful when you try to compare these two sources.

[Bonus Reading: The Great Web Data Capture Debate: Web Logs or JavaScript Tags?]

#2: First & Third Party Cookies. The gift that keeps giving!

Notice the sarcasm there? : )

It turns out that if you use first party cookies or third party cookies can have a huge impact on your metrics. Metrics like Unique Visitors, Returning Visits etc.

So check that.

Typically if you are 3rd party then your numbers will be higher (and of course wrong), compared to numbers from your 1st party cookie based tool.

Cookie flushing (clearing cookies upon closing browser or by your friendly “anti spyware” tool) affects both the same way.

Cookie rejection is more complex. Many new browsers don’t even accept 3rd party cookies (bad). Some users set their browsers to not accept any cookies, which hurts both types the same.

We should have been done away with this a long time ago but many vendors (including paid!) continue to use third party as default. I was just talking to a customer of OmniCore yesterday and they just finished implementation (eight months!!) and were using third party cookies.

I wanted to pull my hair out.

There are rare exceptions where you should use 3rd party cookies. But unless you know what you are doing, demand first party cookies. If free web analytics tools now offer only first party cookies standard there is no reason for you not to use them.

End of soap box.

Check type of cookies, it will explain lots of your data differences.

[Bonus Reading: A Primer On Web Analytics Visitor Tracking Cookies.]

#3: Imprecise website tagging.

Other than cookies I think this is your next BFF in data recon’ing.

Most of us use javascript tag based solutions. In case of web log files the server atleast collects the minimum data without much work because that is just built into web servers.

In case of javascript solutions, sadly, we are involved. We the people!

The problem manifests itself in two ways.

Incorrectly implemented tags:

The standard javascript tags are pretty easy to implement. Copy / paste and happy birthday.

But then you can add / adjust / caress them to do more things (now you know why it takes 8 months to implement). You can pass sprops and evars and user_defined_values and variables and bacteria.

You should make sure your WebTrends / Google Analytics / IndexTools / Unica are implemented correctly i.e. passing data back to the vendor as you expect. Else of course woe be on you!

To check that you have implemented the tags right, and the sprops are not passing evars and that user defined values are not sleeping with the vars, I like using tools like IEWatch Professional. [I am not affiliated with them in any way.]

[Update: From my friend Jennifer, if you are really really into this stuff, 3 more: Firebug, Web Developer Toolkit & Web Bug.]

Your tech person can use it and validate and assure you that the various tools implemented are passing correct data.

Incompletely implemented tags:

This one’s simple. Your IT department (or brother) implemented Omniture tags on some pages and Google Analytics on most pages. Well you have a problem.

Actually this is usually the culprit in a majority of the cases. Make sure you implement both tools on all the same pages (if not all the pages on the site).

Mercifully your tech person (or dare I say you!) can use some affordable tools to check for this.

You would have noticed in my book Web Analytics: An Hour A Day I recommended REL Software’s Web Link Validator. I continue to like it. Of course WASP, from our good friend Stephane, did not exist then and I am quite fond of it as well.

If you want to have a faster reconciliation between your tools, make sure you have implemented all your analytics tools correctly and completely.

[Bonus Reading: Web Analytics JavaScript Tags Implementation Best Practices..]

#4: Torture Your Vendor: Check Definitions of Key Metrics.

Perhaps you noticed in the very first image that StatCounter, ClickTracks and Google Analytics were showing three completely different numbers for Feb. But notice that they also all give that metric a different name.

Visits. Visitors. Unique Visitors. For the same metrics, “sessions”.

How exasperating!

As an industry we have grown organically and each vendor has hence created their own metrics or at other times taken standard metrics, and just to mess with us, decided to call them something else.

Here, honest to God, are three definitions of conversion rate I have gotten from web analytics vendors:

Conversion = Orders / Unique Visitors
Conversion = Orders / Visits
Conversion = Items Ordered / Clicks

What! Items Ordered / Clicks? Oh, the Humanity!

So before you tar and feather a particular web analytics tool (or worse listen to the vendors talking points) and decide which is better, torture them to understand exactly what the precise definition is of the metric you are comparing.

It can be hard.

Early in my career (just a few years ago, I am not that old!) I called the top vendor and tried to get the definition of Unique Visitor. What I saw on the screen was Daily Unique Visitor. I wanted to know if it was the same as, my tool, ClickTracks’s definition (which was count of distinct persistent cookie ids for whatever time period choosen).

The VP’s answer: “What do you want to measure? We can do it for you.”

Me: “I am looking at Unique Visitors in CT for this month. I am looking at Unique Visitors for that month in OmniCoreTrends, I see a number, it does not tie.”

VP: “We can measure Monthly Unique Visitors for you and add it to your account.”

Me: “What if I want to compare Unique Visitors for a week?”

VP: “We can add Weekly Unique Visitors to your account.”

Me: (Getting impressed at the savviness at stone walling) “What your definition of Unique Visitors?”

VP: “What is it that you need to measure? We can add it to you account.”

You have to give her / him this: they are very good at their job. But as a user my experience was bad.

Even if a metric has the same name between the tools check with the vendor. It is possible you are comparing apples and pineapples.

Torture your vendor.

[Bonus Reading: Web Metrics Demystified, Web Analytics Standards: 26 New Metrics Definitions.]

#5. Sessionization. One Tough Nut.

You can think of this as a unique case of a metric’s definition but it is just so important that I wanted to pull it out separately.

“Sessions” are important because they essentially measure the metric we know as Visit (or Visitors).

But taking your clicks and converting that into a session on the website can be very different with each vendor.

Some vendors will time out session after 29 minutes of inactivity. Some will do that after 15 mins. Which means right there you could be looking at the number 1 in visits or the number 2.

Here’s another place where how a vendor does sessionization could be a problem:

The fact that someone went to a search engine and came back to your site “breaks” the first session and starts another in one tool, but not the other.

One last thing, check the “max session timeout” settings between the tools. Some might have a hard limit of 30 mins, others have one (in using a top paid tool I found Visits that lasted 1140 mins or 2160 mins - visitors went to the site, left the page open, came back to work, clicked and kept browsing, or came back after the weekend).

Imagine what it does to Average Time on Site!

Probe this important process because it affects the most foundational of all metric (Visits or Visitors - Yes they are the same one, aarrrrhh!).

[Bonus Reading: Convert Data Skeptics: Document, Educate & Pick Your Poison.]

#6. URL Parameter Configuration. The Permanent Tripwire.

Life was so sweet when all the sites were static. URL’s were simple:

http://www.bestbuy.com/video/hot_hot_hottie_hot.html

It was easy for any web analytics tool to understand visits to that page and hence count page views.

The problem is that the web became dynamic and urls for web pages now look like this:

http://www.bestbuy.com/site/olspage.jsp?id=abcat0800000&type=category
(phone category page)

or

http://www.bestbuy.com/site//olspage.jsp?id=1205537515180&skuId=8793861&type=product
(particular phone page)

or

http://www.bestbuy.com/site/olspage.jsp?skuId=8793861&productCategoryId=abcat0802001&type=product&tab=7&id=1205537515180#productdetail
(same phone page, clicked on a tab on that page)

The problem is that while web analytics tools have gotten better and can probably understand that first page (phone category page), it is not quite as straight forward for the next two.

They contain “tracking parameters” or “system parameters” (crap from the server) or other junk. Different pieces of information, some worth ignoring and others you ignore at your own peril.

Your web analytics tool has a hard time taking all these pieces and painting the right portrait (or count the page views correctly).

So what you have to do is sit down with your beloved IT folks and first you spend time documenting what all the junk in the url is. Things like skuId, productCategoryId, type, tab, id.

Some of these make a web page unique, like say skuId, productCategoryId and tab. I.E. their presence and values contained mean its a unique page. So skuId=8793861 means one phone and skuId=8824739 is another.

But there will be some that don’t mean anything. For example it does not matter if type=product is in the URL or not.

Here’s your To Do: Go teach your web analytics tool which parameters to use and which to ignore.

And here’s how that part looks like for Google Analytics. . . .

In ClickTracks it is called “masking and unmasking” parameters. In Omniture its called josephine. I kid, I kid. :)

If you don’t do this then each tool will try to make their own guesses. Which means they’ll do it imprecisely. Which means they won’t tie. Much worse they’ll be living in the land of “truthiness”!

And make sure you do the same configuration in both the tools! That will get you going in terms of ensuring that the all important Page Views metric will be correct (or atleast less inaccurate).

I won’t touch on it here but if you are using Event Logging for Web 2.0 / rich media experiences it adds more pain.

Or if you are generating fake page views to do various things like tracking form submissions or to track outbound links (boo Google Analytics!) or other such stuff then do that the same way between tools.

Just be aware of that. By doing the right config for your URL parameters in your web analytics tool you are ensuring accurate count of your page views, and across all the tools you are comparing. Well worth investing some effort for this cause.

[Bonus Reading: Data Mining And Predictive Analytics On Web Data Works? Nyet!]

#7. Campaign Parameter Configuration. The Problem of the Big.

Ok maybe all of us run campaigns. But the “big” do this a lot more.

If you run lots of campaigns (Email, Affiliates, Paid Search, Display, Mobile, etc) then it is very important that you tag your campaigns correctly and then go configure your web analytics tools correctly to ensure your campaigns are reported correct, your referrers are reported correctly, your revenue and conversions are attributed correctly.

Here is a simple example.

If you search for Omniture in Yahoo:

[To the person running Omniture's paid search campaigns: I realize Omniture is important but you might reconsider mentioning your company's name twice! I have seen this ad on Yahoo for months (yes I search for Omniture that much!) . :)]

You end up here:

http://www.omniture.com/static/278?s_scid=680217600000000309&clicksource=standard&OVRAW=omniture&OVKEY=omniture&OVMTC=standard&OVADID=4822371011&OVKWID=130976483511

If you search for Omniture on Google, you end up here:

http://www.omniture.com/static/278?s_kwcid=omniture|2109240905&s_scid=omniture|2109240905

You’ll note that Omniture’s done a great job of tagging their campaigns. Absolutely lovely. Now. . . .

Let’s say Omniture is using WebTrends and IndexTools on their website to do web analytics. Then they would have to go into each of those tools and “teach” them all campaign parameters they are using, the hierarchies and what not.

That will ensure that when they click on Paid Search tab / button / link in the tool that these campaigns will be reported correctly.

You’ll have to repeat this for your affiliate and email and display and all other things you are doing.

If you have two tools you’ll have to do it twice. And each tool might not accept this data in the same way. For WebTrends you might have to place it in the URL stem, in IndexTools you might have to put it in the cookies, in Google Analytics it might have to be a customized javascript.

Suffice it to say not a walk in the park. (Now you’ll understand why clean campaign tracking is the hardest thing to do, see link immediately below.)

[Bonus Video: Evolve Intelligently: Achieve Web Analytics Nirvana, Successfully.]

#8. Data Sampling. The Hidden “Angel”.

This is a problem (see “angel” :)) that many people are not aware of, and under estimate in terms of its impact.

But I want to emphasize that it will, usually, only impact large to larger companies.

There will be more about sampling at the link at the end of this section. But in a nutshell there are two kinds of sampling in web analytics.

Data Sampling at Source:

Web Analytics is getting to be very expensive if you are a site of a decent size.

If you are decent size (or plus some) then a typical strategy from the paid web analytics vendor is not to collect all your data - because your web analytics bill is based on page views you send over.

So you don’t tag all your pages or you tag all your pages but they only store a sample of data.

This can cause a data reconciliation issue.

Data Sampling at “Run Time”:

In this case all the data is collected (by your free or paid tool) but when you run your reports / queries it will be sampled to make it run fast.

Sometimes you have the control over the sampling (like in ClickTracks) and at other times not quite (like in Omniture Discover or WebTrends Marketing Lab etc) and at other times still no control at all (like in Google Analytics).

Sampling at “run time” is always better because you have all the data (should you be that paranoid).

But as you can imagine depending on the tool you are using data sampling can greatly impact the Key Performance Indicators you are using. This means all / none / some of your data will not reconcile.

So investigate this, most vendors are not as transparent about this as they should be, push ‘em.

[Bonus Reading: Web Analytics Data Sampling 411.]

#9. Order of the Tags. Love it, Hate it, Happens.

This, being the last one, is not the hugest of deals. But on heavily trafficked websites, or ones that are just heavy (can sites be obese?), this can also affect the differences in the data.

As your web page starts to load the tags are the last thing to load (a very good thing, always have your tags just above the [/body] tags, please). If you have more than one tag then they get executed in the order they are implemented.

Sometimes on fat pages some of the tags might just not get executed.

It happens because the user has already clicked. It happens because you have custom hacked the bejesus out of the tag and it is now a obese tag, and does not let the other, Heidi Klum type sexy and lean tags load in the time available.

If you want that last amount of extra checking, switch the order of the tags and see if it helps. It might help explain the last percent of difference you are dying to get. :)

That’s it! We are done!! Well I am. :)

I suspect you’ll understand a lot better why I recommend having just one tool (after rigorous evaluation of many tools) and then actually spending time creating a data driven organization.

Ok its your turn now.

What did I miss? What are other things you have discovered that can cause data discrepancies between tools? Which one of the above nine is your absolute favorite? Cookies? URL’s? Page Parameters?

Please share your own delightful experiences, insights and help me and our community.

Thank you.

PS:
In case you are in the process of considering a web analytics tool, here is my, truly comprehensive (more than you ever wanted to know) guide through the process:

• How to Choose a Web Analytics Tool: A Radical Alternative
• Web Analytics Tools Comparison: A Recommendation
• Video: Web Analytics Vendor Tools Comparison (And One Challenge)
• Find You Web Analytics Soul Mate (How To Run An Effective Tool Pilot)
• Web Analytics Tool Selection: 10 Questions to ask Vendors
• Web Analytics Tool Selection: 3 Questions to ask Yourself
• Negotiating A Web Analytics Vendor Contract? Check SLA’s

and a bonus

• Redefining Conventional Wisdom On “Enterprise Class” Web Analytics

Copyright © : 2006-2008 Occam's Razor by Avinash Kaushik | All Rights Reserved

The Ultimate Web Analytics Data Reconciliation Checklist

In the process of becoming a citizen there was one document, with a wonderful snippet, that continues to be deeply inspiring for me. It reflects the promise of America.

The document was the United States Declaration of Independence [text here], and these words. . . .

We hold these truths to be self-evident, that all people are created equal, that they are endowed by their Creator with certain unalienable Rights, that among these are Life, Liberty and the pursuit of Happiness.

That last part forms for me the essence of what it means to be truly free.

It is a commitment, to you and to me and to us, of the opportunity that we are blessed with. An opportunity to make choices that you and I would like to as we live our humble lives.

One of those choices you and I can make is the choice of who we can marry.

It is in support of that choice that I request you to consider voting No on prop 8.

I have profound respect for the choice you make in whom to marry. I am asking that my right to marry the person of my choice be preserved.

And the right of my friends. And my neighbours. And my fellow citizens.

For Life, Liberty and the pursuit of Happiness.

Thank you.

Update: Nov 5th, 1400 hrs.

I am deeply disappointed that Prop 8 passed. That we have now institutionalized and legalized civil discrimination against our own citizens in California.

But.

At the turn of the last century dogs and a specific race were asked to stay out public establishments.

Less than a hundred years ago one human gender could not even vote.

Less than fifty years ago one race in this country was asked to ride at the back of the bus, we still believed in “separate but equal“.

Just eight years ago an American University ended a ban on interracial dating (something that would have prevented my beloved wife and I from ever being a couple).

I am confident that in my lifetime this nation will allow any person who wants to marry to marry, and marry the one they choose to marry.

I leave you with words that inspire me:

Let us not wallow in the valley of despair, I say to you today, my friends.

And so even though we face the difficulties of today and tomorrow, I still have a dream. It is a dream deeply rooted in the American dream.

I have a dream that one day this nation will rise up and live out the true meaning of its creed: “We hold these truths to be self-evident, that all men are created equal.”

I have a dream that one day on the red hills of Georgia, the sons of former slaves and the sons of former slave owners will be able to sit down together at the table of brotherhood.

I have a dream that one day even the state of Mississippi, a state sweltering with the heat of injustice, sweltering with the heat of oppression, will be transformed into an oasis of freedom and justice.

I have a dream that my four little children will one day live in a nation where they will not be judged by the color of their skin but by the content of their character.

I have a dream today!

I have a dream that one day, down in Alabama, with its vicious racists, with its governor having his lips dripping with the words of “interposition” and “nullification” — one day right there in Alabama little black boys and black girls will be able to join hands with little white boys and white girls as sisters and brothers.

I have a dream today!

I have a dream that one day every valley shall be exalted, and every hill and mountain shall be made low, the rough places will be made plain, and the crooked places will be made straight; “and the glory of the Lord shall be revealed and all flesh shall see it together.”

This is our hope.


-“I Have a Dream”, Martin Luther King.

Copyright © : 2006-2008 Occam's Razor by Avinash Kaushik | All Rights Reserved

Life, Liberty And The Pursuit Of Happiness

Without a doubt the feature that I am most excited about is Advanced Segmentation. This has been a long time coming (can you sense my pushiness!), and in this post I wanted to share with you all how to use this awesome feature.

Along the way I’ll share three different segments that you must have in your web analytics tool. Regardless of why your website exists or what tool you use, Google Analytics or an alternative. I’ll close with a approach you can use to get answers to your ad-hoc questions / queries faster, in mere minutes rather than days.

But before we go on here are all the features released today:

AdSense and API are in Private Beta (access by invitation). Motion Charts, Custom Reports, Advanced Segmentation are all in Public Beta (being released starting today, gradually to everyone in the next few weeks).

If you particularly can’t wait to use the Public Beta features then see the end of this post to get access sooner.

Now to evolving from being Reporting Squirrels to being Analysis Ninjas!

Why Segmentation?

Analyzing data in aggregate is a crime.

Bold statement, but the reality is that a “monolith” does not come to your website. Your site does not exist for a singular reason either. The core drivers of traffic are magnificently different for each core group of visitors.

So your website’s really a mix of Visitor Sources, Visitor Behavior and your Desired Outcomes.

When you look at all that in aggregate you get nothing. You think Average Time on Site means something. No! You think All Visits and Overall Conversion Rate gives you insights. Nyet! You think understanding Keywords without drilling down to each search engine will be awesome. Non!

If you want to find actionable insights you need to segment your web analytics data. You need to separate out the various Sources, Behavior and Outcomes.

Then you’ll understand behavior of micro-segments of your website visitors, which in turn will lead you to actionable insights because you are not focusing on a “glob” rather you are focused on a “specific”.

Need more convincing? Want a specific case study? See this post: Excellent Analytics Tip#2: Segment Absolutely Everything.

Segmentation in Google Analytics:

Google Analytics always had rich segmentation capabilities. The problem is that you needed to be Robbin Stief to use it. She is super bright (went to Harvard!). She is technically super competent (regex anyone?). She is extremely aggressive! (Of course I say that with love!!)

This release of Advanced Segmentation means that the simplest of folks (Me, hurray!) can now perform sophisticated analysis.

Even my seven year old Damini daughter created two segments in ten minutes. Its that simple!!

Click on the “Advanced Segmentation (Beta)” link and boom!

What you are seeing are a list of “default” segments. The GA team had a nice brainstorming session about what segments might apply to most people. The ones you see were a result of that, and are pre-created and available in every account.

You could just use the ones above that apply to you. You could also choose one of the above as a starting point, just click on Copy and then further customize them. For example I might click on New Visitors, Copy and then customize it to identify New Visitors from Iceland.

You could also simply click on the link that says “Create new custom segment”, if you do you’ll be on your way. . . .

What you are looking at is Step One in creating any segment. On you left are the Dimensions (customer & campaign attributes) and Metrics (numbers, key performance indicators) you can choose to create custom segments of your own.

Ok with that briefest of tutorials let’s dive in and have some fun with this puppy.

[The first example is a lot more detailed, just to show you all the steps. After that we'll do the bare bones.]

Idea #1: Segment out your Brand Search Keywords.

Branding baby!

Most search portfolios (Search Engine Marketing or Search Engine Optimization) have a unhealthy obsessions with our brand terms. Yes it is important to care but for many it takes over all our life and thinking. That is not good.

So the first segment is to segment out your brand terms (this thus far was not that easy in Analytics). We want to get a reality check on how big that segment is, how important it is, and is it worthy of our obsession.

In the search box on top of Dimensions type in Key and Analytics will guess and find the relevant options for you. . . .

Pick up Keywords and drag it on to the the Dimension or Metric box. Take a breath. :)

To keep things simple I am going to use “avinash” to identify my brand terms. For you it could be “maxim” or “obama” or “quickbooks” or “sexyback44″ or “dell” or. . . .

As I type in “av” in the Value box Google Analytics will do a real time look up and tell me my options to aid me in choosing the word I want. Pretty nice. My favorite “tealeaf avinash”. :)

Click on “avinash” and I am done!

Of course I could also add another statement and include “avanish” or maybe even “occam’s razor” (which I think of as my “brand” term). But for now I want to keep this simple.

One sweet feature that differentiates segment creation in Google Analytics from that of other vendors is the ability to do real time QA (quality control) and test the segment you have created.

In most web analytics tools (NedStat is a notable exception) you create the segment, process the data, take a nap, wake up and realize you made a boo boo. Then you repeat the process. With Analytics (and NedStat) you don’t have to do that.

Its like making sure that you go out on a first date before you propose marriage. Always prudent.

When I click on Test Segment GA will run a life query for the time period I had chosen and bring me the actual data for my segment.

So of the 44,528 Visits in these weeks I only good 576 Visits from my brand terms?

Heart attack!

Denial!

Ego bruised!!

Breath. Breath. Look. Ahh… I made a mistake.

Turns out that in the Condition I choose “Matches Exactly” (look in the middle above).

So the segment I have created is how many Visits from people typing in the exact term “avinash”, what I wanted was Visits generated by every variation of “avinash”. avinash kaushik. avinash blog. analytics blog avinash. amazing avinash awesome author. Ok that last one’s made up.

I’ll make one small change to my segment:

I click on the Condition and change from Matches Exactly to Contains.

Notice above that without knowing too much about regex and what not you can easily choose a number of conditions you can apply to your segment.

At the bottom I type in Brand Keywords and click Create Segment (after testing it one time!) and I am done.

Next step, trying to be a Analysis Ninja.

You now have tha ability to apply this segment you have created on pretty much every single report that you have in Analytics.

For example you could go in and see what content (pages) do people who come on Brand Keywords consume. What products do they buy? If I were GM then which product brochures do the download? On a tech support site did they find the right tech support answer? For a social networking site, do people under brand terms show a higher Visitor Loyalty or lower? And on and on.

For me I wanted to start with understanding the size. Recall I have a fragile heart.

So I go into the Keywords report and look at the Visits graph. . . .

I have to admit it did make a cry just a bit.

That orange line is the number of Visits from my Brand Keywords and the blue line is All Visits. So every variation of my brand makes up such a pathetic number of my overall Visits.

Ok let’s put the kidding aside. This proves a very important point I make in my presentations. Search has a very very long tail.

As is clear above I don’t got a few visits from my brand terms, even though they dominate the top ten keywords report I look at every day in Google Analytics (or Omniture or WebTrends or CoreMetrics or IndexTools or ClickTracks or whatever else).

I have hundreds and hundreds of keywords that individually drive five or ten visits each.

If I were running a business here then I would use the above simple graph to get my Management team to start paying attention, and creating a solid strategy, to the long tail of search .

Remember your brand terms are important, these are people who know you. But it is equally important that you have a solid long tail strategy because that’s where you’ll find people new to your franchise.

Next I care about money. Is this segment of Visitors converting (meeting goal targets)?

Sweet.

While they form a much smaller % of my overall Visits, Visitors on my brand terms form a nice % of my overall conversions. 18% of the all important Goal 3 (which has a very high $$$ value!).

Looking at the percentage view confirms the obvious. . . .

Nice.

When was the last time that you understood this much about a valuable part of your traffic, all in less than 10 mins? This stuff is not that difficult, and now its even more straightforward.

Next I would look at landing pages for my brand terms and see if I could tighten them up.

I would certainly figure how to create a solid search long tail strategy.

And I’ll do one more thing to help with that. Create a new custom segment for my non-branded keywords.

Here is one way of doing that. . . .

Notice all I did is:

~ Switch the Condition from “Contains” to “Does Not Contain”.

~ Added Source Contains the search engines (Yahoo, Google, Live - those are 99% of my traffic).

I save it and I am done. 99% accurate but good enough. I can get the last 1% accuracy if I can afford to spend a couple hours. In my case it is simply not worth the investment of time. You’ll make your own choice, just make sure you are balancing time invested with the reward you get.

I recommend looking at your key Visits, Traffic Sources, Content reports to identify how to start monetizing your long tail.

Trust me it is not that much work, and it is just so much sexy fun.

Idea #2: % Visits with a high “Degree of Engagement”.

Yes I did use the word engagement! But atleast I am following the simplicity and guidance from Theo Papadakis.

From the dimension selector choose Page Depth. . . .

What I am looking for is the number of people who see more than a certain number of pages. To convince you of my greatness you have to read atleast three posts I have written. Yes it is not instant impression! :)

In your case it could b