Occam's Razor by Avinash Kaushik » Customer Satisfaction

Excellent Analytics Tip #18: Make Love To Your Direct Traffic

Avinash Kaushik — Mon, 20 Sep 2010 09:14:51 +0000

Make love? Direct Traffic? Really?

I am not kidding. Direct traffic contains visitors that proactively seek you out, everyone else you have to "beg" to show up on your site!

Yet this question seems to bedevil a lot of people:

What the heck is Direct Traffic?

As if that was not sad enough, even people who do know what the definition of Direct traffic is rarely focus on it or work hard to tease out the opportunity that exists in Direct traffic.

I love analyzing Direct traffic because it contains a valuable set of visitors who deserve more love than we currently give them.

I want you to be just as excited.

So let's look at the definition, to make sure we understand, at least on paper, what this traffic is supposed to be. We'll also look at the challenges that exist in ensuring we are looking at the real unpolluted Direct traffic.

Definition.

Here is the simplest and cleanest definition:

Direct traffic contains all Visits to your website where in people arrived at your site directly (by typing the url) or via a bookmark.

Direct traffic is hence not traffic that results from people clicking on links on other sites to your site (that's referring urls traffic), it is not traffic that comes to your site by clicking on ads (that's Other in Google Analytics or Campaigns in other tools), it is not people who come from search engines (that is Search or Organic or PPC traffic).

The reason Direct traffic is a beloved of mine is that it represents (checkout the sweet contextual – red and green – numbers above):

1. People who are your existing customers / past purchasers, they'll type url and come to the site or via bookmarks.

2. People familiar with your brand. They need a solution and your name pops up into their head and they type.

3. People driven by word of mouth. Someone recommends your business / solution to someone else and boom they show up at the site. Uninvited, but we love them!

4. People driven by your offline campaigns. Saw an ad on TV, heard one on radio, saw a billboard and were motivated enough to typed the url and show up.

[If you were really smart you would use campaign tagged vanity url so you can segment them!]

5. [Remember the part below, but.] Free, non-campaign, traffic.

In a nutshell these are people show up without invitation (email, display, social campaigns) or they are people who already know you. There is an extra motivation connected to their visit which causes them to type your url of find the bookmark they made.

That little bit of extra intent, when compared to other visitor segments, is the reason that conversion numbers (on ecommerce or non-ecommerce sites) for clean direct traffic usually look like these. . . .

The only goal that is red is supposed to be red (fewer registrations from people who already know you is not unusual right?).

Now you'll agree when I say your job is to be extra sweet to them?

Segment them in your data, the delightful numbers you see in your KPI's will show you why.

So if Direct traffic is so important and often the metrics show very positive results then why don't we all obsess about it a lot more?

The Problem: Unfortunately. . . You!

Most website tag and campaign tracking implementations are poor (to put it charitably). This is always disappointing but it is particularly harmful to Direct traffic.

You see if you don't implement your links properly the person shows up to your site without any tracking parameters and thus fail to help your web analytics tool to put that visitor in the right source bucket.

Typically Direct traffic also contains all the Visits that originated from improperly tagged campaigns, untagged campaigns and problems with your JavaScript tag. I am sitting in a puddle of tears as I write this, that is how often Direct traffic is polluted and that is how painful (and profoundly sad) this is.

Here is a simple example:

You are the Acquisition manager for a company called Omniture.

You have purchased banner ads in various Android applications using AdMob to target high value analytics decision makers. You goal is to get people to buy your Discover data warehouse product.

You are using Google Analytics to track all you display campaigns.

The proper way to link your banner to your Discover2 website is:

omniture.com/discover2awesoemness/?utm_source=nytimes_mobile_homepage&utm_medium=masthead_banner
&utm_content=188_92&utm_campaign=affluent_readers

You actually use this url:

omniture.com/discover2awesoemness/

Guess where this category will be categorized?

Direct.

You see mobile applications don't send a referrer and it will look like all of a sudden you got very high converting Direct traffic.

With a simple stone you've killed two beautiful birds:

> The direct traffic is polluted and you'll never be able to focus on finding real insights for actual valuable lovely people who are seeking you out directly.

> Google Analytics will show that your mobile campaigns with AdMob stink. Of course that's not true, but you'll have no way of knowing that.

Not a great situation right?

Oh and what do you think is happening to the trackability of all your shortened urls in Social Media that you are not tagging with campaign parameters? 78% of people consume Facebook and Twitter content via applications and unless you use campaign parameters all that traffic is sitting in Direct. So sad.

Result?

Direct traffic is a fantastic segment to analyze because it contains desirable Visitors and yet because it is often polluted (due to our own inability to implement web analytics tools correctly).

Let's aim to fix this because it is too important not to.

. Why Does Direct Traffic Get Polluted / Mistakes You Should Avoid:

The good and the bad are all mixed in, and it is your job to ensure that that is not happening inside your web analytics data.

Here are the main reasons traffic that should not be Direct ends up there, try, please please pretty please, to ensure this is not happening to you:

1. Missing web analytics tag from landing pages

Perhaps the most common source of traffic being miscategorized.

Your urls are all tagged correctly with campaign parameters, or maybe people are just coming to from sites that link to you.

They land on a page that is missing the web analytics tag.

They click on a link on the landing page to go deeper into the site.

Guess what's the traffic source for this traffic?

Direct.

So sad.

You worked so hard to get that referring link / execute the campaign. Now not only do you not get rewarded for that work. you actually messed up your direct traffic.

Don't be that person.

Go purchase WASP from iPerceptions or an account with ObservePoint and address the cheapest problem to fix in Web Analytics. If you are a little bit tech savvy then go get REL Software's Web Link Validator, it's pretty good.

2. Untagged campaigns (search, email, display, social media etc)

This is perhaps the second biggest reason data in web analytics ends up in wrong places.

In case of untagged emails (to people who are using Outlook, Thunderbird etc) and mobile ads and mobile application links (think of all those Twitter / Facebook apps) and Adobe AIR applications (like my beloved NY Times Reader) and in rare cases where people are clicking on links in PDF documents etc, the data ends up in Direct (no referrer).

In case of untagged display campaigns usually there is a referrer so it will end up there rather than in Campaigns were you want it.

In case of untagged paid search campaigns it usually ends up in organic search data.

On behalf of your company you are spending precious budget on acquisition, not ensuring your campaigns are tagged properly is near criminal behavior. Don't be that person. Tag.

Oh one more thing.. if you are practicing bigamy and have two tools, say Google Analytics and Adobe's Site Catalyst you better remember to have campaign parameters for both GA and SC because they use different parameters for campaigns. Whichever one you forget to tag for will show your campaign traffic as Direct!

If you want to track the campaign in the first part of this post with both Google Analytics AND Omniture the url would look like this, as an example:

omniture.com/discover2awesoemness/?utm_source=nytimes_mobile_homepage&utm_medium=masthead_banner
&utm_content=188_92&utm_campaign=affluent_readers
&s_scid=TC-10013-3159426121-e-361634984

See both set's of campaign parameters? You don't do that one of them is wrong. Not so shiny to practice bigamy is it?

3. Improperly tagged campaign parameters / site tags

This one is probably not that hard to understand.

Instead of utm_source and s_scid you use utm-source or s-scid and you are. how to say this politely. screwed.

In both cases your two (or one) web analytics tool will most likely ignore the improper parameters and throw the traffic where it does not belong and mess up your ROI analysis.

Auditing your campaign tracking before they go live is a great idea. Do this at the very minimum for the 20% of the campaign that are responsible for 80% of your traffic / revenue.

If you use Google Analytics grab the Google Analytics Tracking Code Debugger. See this blog post for troubleshooting guide & detailed instructions: Debug Your Tracking Code.

Omniture, WebTrends, CoreMetrics, Unica all come with such debuggers. I can't link to them as location are not public (or you need to pay first!). Please reach out to your Account Managers to get access, just in case you don't already have them. Debug!

[Update:]

Ben Gaines from Adobe/Omniture was kind enough to share that a free debugger is available to Omniture clients. Log into the Knowledge Base and look for KB ID 534 and you are set! But here's something cooler. The debugger is actually a bookmarklet and here it is:

Omniture Analytics Tag Debugger

Create a bookmark in your browser. Copy the code in the above text file. Click edit on your bookmark. Paste the code where the Link is. Go to any page on your site with Site Catalyst. Click on the bookmarklet and bathe in bugs! :)

[/Update]

4. Improperly coded redirects / vanity urls etc

Another silly issue that causes problems with direct traffic.

When you get a email or a mobile campaign, and keep a close eye on the url window, you'll notice the click goes to your campaign solution provider and is then redirected to your site.

That's one example of a redirect. We use redirects / vanity urls in our multi-channel campaigns, in our display or search campaigns or even just for the heck of it.

That is not an issue.

Make sure they are permanent, 301, redirects. The delicious type of redirects that dutifully pass the referrer string to the landing page telling your web analytics provider where the person originally came from.

You use temporary, 302, redirects and the referrer never gets passed on. Depending on how the redirect server is configured either the click looks like it came from the redirect server or with a blank referrer (direct!).

5. Really heavy tag at the bottom of the page (switch to Async!)

A smaller problem for normal sites with just text and some images, but a huge problem for fat ugly flash heavy websites (especially the, still annoying, ones with flash intros).

It takes such a long time to load the flash file itself that person might have clicked skip intro or some other link on the page well before the fat flash file loads or before the web analytics JavaScript tag loads.

The data tracking behavior is exactly as if issue #1 above existed, no tracking code on the landing page.

I would recommend putting the tag in the header, except that is the selfish lover strategy and no one likes a selfish lover.

Make your pages as lean as you can, especially campaign landing pages. Keep the tag in the footer, you don't want the page to hang because of issues at your analytics provider.

If you use Google Analytics you are in a little bit of luck. Switch to the magical GA Async Code. It goes in the header, captures data without ever hampering your page loading and as if that were not enough is leaner and meaner.

One of these days all web analytics vendors will migrate to the Asynchronous making the Internet a faster place to live in.

6. Corner cases causing traffic to end up in Direct.

Here are some reasons that don't happen a lot but you should be aware of:

~ Links encoded in JavaScript clicked in some browsers will send a null referrer (i.e put traffic into Direct). Often times you can't help his because you don't have control over people linking to you can do whatever they want. But do check that your campaigns in Facebook or Yahoo or other places are not using this method.

~ [Update, via Alec Cochrane:] https to http and vice a versa also won't have referrers passed due to (good) security reasons. So if possible make sure you put campaign tracking codes in links from https pages to ensure those visits don't end up in direct. For this you would have to know this is happening and then be able to find the person who will oblige you by changing the link. Tough to do but when you can do it!

~ Some smart folks will make changes to their browser configurations that cause referrers not to be passed. Happens in a tiny minority of cases.

~ This might impact only some tools but check with your vendor how this scenario is credited. . .

First visit: From a campaign (search, referring url, social, display, whatever).

Second visit: Direct to the site.

If you are using Google Analytics then that second visit will still be "credited" to the campaign (non-direct) because the _utmz cookie will be present in the browser.

In your web analytics tool that might not be the cause. Please check with your vendor.

~ Multi-domain / sub-domain "unique" web analytics implementations across many websites. With any tool these are really hard to do right, and really easy to do wrong. If you have one of these polka dotted puppies then get your expensive Consultant to triple check the code and cookie customizations with a special eye on Direct traffic.

~ [Update, via Pritesh Patel:] You could also have polluted Direct traffic if your entire company (hopefully of a good size!) has their home pages in browsers set as your company's website. This will clearly skew your direct traffic (and your bounce rates, after all they don't actually care about your site :)). You can easily use your tools admin settings to filter out all your internal IP's which would solve this issue.

~ [Update, via Deric Loh:] #1. iFrame: Whenever someone links to your site via an iFrame it is possible for them to code it in such a way that it does not pass referral data and the visit will look like Direct. We can do much about this but in case there are sources where you can avoid this issue or get it done properly then it is worth the effort.

#2. Company Gateways: Some companies might have a security gateway which has been set up to strip the referrers from request calls. This of course is not great for your clean Direct traffic. It won't happen a lot of times and then limited to just one source. But it is something you certainly should be aware of as a cause.

That's it. Six simple problems for you to take care of. : )

All kidding aside know that you'll accomplish a major clean-up if you address the first three issues and then YMMV.

Also know that it is totally worth it to get this data clean, the orange line below is Direct traffic conversion rate and the blue is overall conversion rate. . . .

Not bad eh?

You want to know who these people are.

You want to know what you can learn from analyzing their geographic locations.

You want to know their Visitor Loyalty and Visitor Recency profiles.

You want to know what content they are consuming.

You want to know what products they are purchasing.

You want to know what the differences between their behavior on your site is from your other campaign traffic.

You want to know if any of the spikes are correlated to you offline campaigns or catalogs you have sent out (and then establish causality between offline campaign calls to action and behavior by these people).

You want to establish the value of these visitors and then pay special attention to them if they are of value to you.

For the New York Times website I'll always be Direct traffic. I use a bookmark, I go to the site at least once a day, I click on Ads (I have nytimes.com on my adblock white-list!), I subscribe to the Times Reader, I am a big evangelist of their brand.

But only if they care to ensure their Direct traffic is clean, and then analyze that traffic will they ever know that.

If they are like every other company that obsesses with PPC and Yahoo! Banners and Facebook Display ads and Email campaigns etc etc then they'll never know that some of their best customers they should make happy are right under their nose.

I know that the NY Times web analysis team is super sharp. Are you?

In the small chance that you were not before I hope I have convinced you to truly bring the "make love" type of passion to this valuable, and usually large, segment of traffic to your site.

Good luck!

UPDATE: A clarification specific to Google Analytics:

Every tool uses delightful sets of attribution rules when it comes to assigning visits or conversion to campaigns. To share with you how Google Analytics will attribute these things here are a couple of scenarios….

Scenario 1:

Visit 1: Came from SEO click on keyword "ASOS Fashion"
A few days later…
Visit 2: Came direct to the website

In Google Analytics you will see this in your reports:

Keyword "ASOS Fashion": Visits: 2
Direct: Visits: 0

In effect Google Analytics will "understate" direct visits. It is difficult to have a perfect scenario here, some people will vehemently make the case that GA is doing it right and that the Visit did come via the organic click first so second visit should be attributed to it. I am personally in the camp that that is sub-optimal and that because we can't read too much into anything (we just don't know what is influencing what) we should report keyword visits = 1 and direct visits =1. But at least you know what GA is reporting.

Scenario 2:

Visit 1: Direct to the site.
Visit 2: Came from Affiliate Campaign click.
Visit 3: Came direct to the site.

In GA it will show:

Direct: Visits: 1
Affiliate Campaign: Visits: 2

See how that works? Regardless of how you think it should be you now know how it is. : ) Make sure you keep this in mind as you analyze the GA reports.

[My heartfelt thanks to David Williams for his help with a test for above cases.]

This stuff is complicated right? Remember none of this takes anything away from the importance of direct traffic or how hard you have to work to make sure your reporting of it is clean (tips above) or that it is worth focusing on. Whatever tool you have, do all of the above!

Ok your turn now.

Do you obsess about Direct traffic just as much as I do? What insights have you found from you analysis? What methods have you deployed to ensure that your Direct traffic segment is as clean as possible? Do you also look at any "Direct" traffic to really long complicated url's on your site and instantly doubt that could be direct?

Please share your experience / feedback / tips / critique via comments.

Thanks.

PS:
Couple other related posts you might find interesting:

Excellent Analytics Tip #18: Make Love To Your Direct Traffic is a post from: Occam's Razor by Avinash Kaushik

Win With Web Metrics: Ensure A Clear Line Of Sight To Net Income!

Avinash Kaushik — Mon, 28 Jun 2010 08:59:27 +0000

We have more web metrics and data than there are stars in the universe (slight exaggeration!).

Yet we stink at informing decisions. Our reports are ignored. Sites & online marketing continue to suck.

A large part of the reason is that a large part of our job seems to consist of glorified data puking, hoping someone will be impressed. After all there is so much data in those reports!! #fail

This blog post encourages you see the forest, the much hyped big picture, and shares a framework that will help you ensure that every single moment of your day is spent on activity that will be:

1. of value to your organization, hence appreciated and acted upon

2. has a clear line of sight to the one thing that matters: profit

If you don't want your professional life to be frittered away then please come along this short journey.

First some context…

If you have seen one of my keynotes recently then you have heard my near evangelical fervor when it comes to trying to convince you to compute Economic Value.

If you have Web Analytics 2.0 then you already know who much attention is paid to this concept in the book (jump to page 159 for how to compute it for your website).

The reason for this emphasis is to help fix our miserable failure at at creating data driven organizations.

To steal your energy away from being just in the report / data production business.

To encourage you to do better than spend a lifetime implementing analytics tools, building data warehouses, chasing the next shiny object.

My recommendation has been:

1. Identify your Macro Conversion (focus on this a lot!).

2. Report revenue. Report like crazy on the 2% conversion rate.

3. Identify your Micro Conversions.

4. Compute the Economic Value (see page 159). Show your bosses and HiPPO's the complete value of your website.

That last one will get any organization to sit up and pay attention.

Why?

Because for the first time in their young and passionate life they'll see the complete value your website is adding to the business. And because my dear it will be a huge number that no one can ignore! You are going to tie your work to the bottom line!

Revenue = Good. Economic Value = God! [Also slight exaggeration :)]

Professor Ken Wong's Magic Potion

Prof. Wong is the award winning Commerce '77 Teaching Fellow in Marketing at Queen's School of Business (and an awesome speaker, you should hire him for your next event!).

He took the stage after my talk and said, I am paraphrasing here, "Avinash did not go far enough in his keynote. Economic value is important but the only thing that matters is Profit!"

That was awesome!

One of Prof. Wong's key points was how the success of our work, as Marketers, is measured based on a lot of things but not often enough based on perhaps the most important metric of them all: Net Income.

Prof. Wong covered a lot of key points (as a MBA with a minor in Marketing I wanted to take off my clothes and jump for joy when he said the 4P's of Marketing are killing Marketing!).

I wanted to share two of his slides that left a lasting impression on me.

They are particularly applicable in the web analytics context. In sharing my interpretation of them my hope is it will change a little bit how you think about your work and success.

The very first slide, "Profit: The Ultimate Client Need", shares the key elements that need to function for the outcome (ROI) that causes companies to remain in business.

My interpretative points.

Net Income is driven by two important variables:

Unit Margins (how much you make on each X you sell or Y service you provide)

Unit Volumes (how many of X or Y you sell)

Margin times Volume gives you the golden metric Net Income!

[Keep this formula in mind, your life should be revolving around it else you are wasting everyone's time.]

Peel the onion back one more.

Unit Margins is in turn driven by two more variables:

Price (how much you charge for X product or Y service)

Cost (how much it costs you to make X or provide Y)

Price minus Cost equals Unit Margins.

Get it?

So if you want to have very high Margins you have two variables you can control. You can charge lots for your product or service (think of a Vertu phone).

You can also make it at the cheapest possible cost (no phone costs $100k, you make it for $300 and sell it for $100k).

You can of course also charge lots and lots and it costs you a lot to produce (think of a Tesla car). But give some thought to how you'll stay in business.

Continuing the onion peeling…

Unit Volumes, our other variable to have high Net Income, is driven by two variables:

Market Share (is your share 90% or 5%?)

Market Size (is that share of a market the size of Maldives or China?)

Both share and size are important.

You'll sell lots of X or Y if you have a high market share and the limit you'll hit is the size of the market (you can then play in the current size or grow the pie).

Line of Sight.

Having a clear line of sight means that you are able to map every metric you report on (or better still torture with segmented analysis to find insights) every single day directly to the strategic objective of the company.

Prof. Wong is suggesting, rightly so, that that strategic objective is Net Income.

And you have only one of four things that you'll move through actions your company takes: Price. Cost. Market Share. Market Size.

Here's my crystallizing question for you. . . .

When you report the metric Page Views Per Visit which of the four are you solving for?

How about with Bounce Rate? Or Time on Site? Or % of New Visits? Or Visitor Loyalty? Or…..

Is there a direct line of sight between what you as a Marketer are being incented on, or you as an Analyst are spending time analyzing?

If not, are you surprised that no one loves you? Sorry… I mean… no one loves your work?

Here is a simple exercise you could go through: Pick out all the metrics you are reporting today (on your dashboards and top reports). Try to put them into one of the four important buckets from Prof. Wong's slide.

The clear line of sight exercise. . . .

Were you able to cleanly bucket all metrics you currently report? Time on Site and Conversion Rate and Task Completion Rate and % Internal Site Search Exits and Cart Abandonment Rate and % of the Page Scrolled and % of Visitors Refreshing Pages and all the other sweet things.

Some of the metrics in the above paragraph are complete crap, you are wasting your time and everyone else's time with them. And you'll now discover that very quickly because you won't have a place where you can bucket them.

Other metrics will make you think harder. Where do you bucket Conversion Rate? Are you impacting Price or Cost?

What about Customer Satisfaction? Or Page Rank!

Not every metric will map cleanly, and that is ok. I had to think really really hard to bucket each of my metric in the above picture. Some of the metrics were controversial. But bucket I did.

If it turns out your web metric has no line of site then it might be time to kill.

If the work you do can't be mapped into Price, Cost, Market Share or Market Size then why are you doing it?

Before you dip your hands into Omniture or WebTrends or Surfaid, :), answer that question.

I know it seems like a lot of work for a "lowly" Analyst to do. It is. But without it there is little hope for your personal success (promotions / bonuses) or your company's success (higher Net Income).

"What Matters Most" Fishbone Analysis

As you look at the picture above it is amply clear that the metrics I have chosen in each of the four buckets are perhaps unique to me/my business.

The reason is simple… they are a reflection of the strategy my company is currently executing, i.e. our "world domination via an effective data driven online marketing plan".

This simple truth, that metrics should reflect current business strategy, is the reason I loved another slide from Prof. Wong's presentation.

It leveraged the same framework, but added "what matters most". . .

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

The focus is still on Net Income driven by, hopefully, improved Margins and Volume which in turn are driven by much beloved 4 levers of Price, Cost, Share and Size.

What is awesome about the "fish bone" above is that it drills down to the 14 specific strategies that most businesses will use to become great (or simply survive).

You Ms. Web Analyst now have a framework you can take to your Marketing Directors and CMO's to discuss which of the 14 strategies they are currently executing to drive the 4 beloved levers.

Ask any Web Analytics "Guru" or "Professional Speaker" or "I am so important you are paying me $5,000 an hour to give you generic advice Consultant" and they will always tell you that all good journeys in web analytics start with asking your bosses this question: What are the goals of the organization?

The advice is sound (and well worth $5k/hr). The problem is that we never get an answer from the customers of our data / our management. You are $5k x 8 hrs short and still none the wiser.

Get off the slow train to nowhere…. You now have a new BFF: Prof. Wong's "What Matters Most" slide!

Don't ask the generic "What are the goals" question. Ask "Of these 14 specific strategies which are we currently executing".

Once they tell you which ones (be patient, it might shock them that you are giving them something tough and specific to think about), you'll be in business.

The 5 strategies they pick from the right-most column will help guide you in terms of picking the right Key Performance Indicators / Web Success Metrics for your business.

And you know why a win now is guaranteed?

Because each metric you identify starts with a specific business strategy which has a direct line of sight to the 4 beloved levers which will have a impact on Net Income!!!

Minorly orgasmic right? [Trust me, you do this and you'll agree. :)]

Summary:

Recommendation #1: The Web Analytics Maturity Mandate!

For far too long we have been like toddlers… bumping into things, having a limited vision, working just what we know (which is little).

What I love about this approach is that it forces us to grow up. It forces us to understand what we are solving for: Net Income. It forces us to have a line of sight between our work and the ultimate goal: Net Income. It forces us to not live in our dungeon but rather take a well defined framework to enable the discussion that will yield wins all around.

No lip service to how important process is. This blog post shares what you specifically must do to succeed!

Recommendation #2: Win With Web Metrics: Steps

Here are the specific steps I recommend you follow for optimal execution of the recommendations.

Step 1: Learn Finance 101 and the terms outlined in the slide titled "Profit The Ultimate Client Need".

Step 2: Don't pick any metrics, don't run reports, resist the charms of Google Analytics, Omniture Discover2 etc.

Step 3: Meet with your Management team (or the senior most Marketing person) and identify which strategies outlined in "What Matter's Most" the company is executing (/wants to execute).

Step 4: For each strategy identified in step 3 identify the Web Metrics / KPI's with a clear line of sight to the 4 beloved levers.

Step 5: Use the Web Analytics Measurement Framework as the foundation of all your reporting.

Step 6: Spend you work day on focused segmented analysis to identify actionable insights you can report using the Web Analytics Measurement Framework that will help drive data driven actions on "What Matters Most" so that your company will improve in the one thing that matters: Net Income.

Step 7: The happiness you'll get from leading a meaningful professional life will make you irresistible to the opposite sex which in turn will lead to happiness in your personal life! Enjoy it.

A simple but effective 7 step process.

Good luck.

Ok now it's your turn.

Do you agree that a focus on Net Income and a focus on "what matters most" is key to success in web analytics? Can Web Analytics tie the work they do, the metrics they report, into Price, Volume, Market Share & Market Size? Or is our work simply not that important? In your job today how do you ensure line of site? Will you change anything based on the recommendations from Prof. Wong?

Please share your feedback / critique / ideas.

Thanks.

[UPDATE]

Zach Olsen, who blogs at By Data Be Driven, has taken the Clear Line of Sight framework outlined in this post and applied it to a medium sized eCommerce website. It is so wonderful, take a look:

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

Zach's effort is awesome for these key reasons:

Really clear line of sight from Business Objective to Net Income.
Clean flow from What Matters Most to 4 beloved levers (Price, Cost, Share, Size).
(This one I love the most…) Identifying of Targets for each metric! You can't be serious about Web Analytics without doing this!

I hope you are as impressed by Zach's effort as I was.

He has also done something sweet for all of us… he has created a excel spreadsheet that you can download and customize for yourself, and hence get a jumpstart! You can download it at this blog, bottom of this post: Web Analytics Framework Example. Please download it!

My thanks to Zach for his effort and for his permission to share it here.

[/UPDATE]

PS:
Couple other related posts you might find interesting:

Win With Web Metrics: Ensure A Clear Line Of Sight To Net Income! is a post from: Occam's Razor by Avinash Kaushik

Online Marketing Still A Faith Based Initiative. Why? What's The Fix?

Avinash Kaushik — Tue, 01 Jun 2010 09:11:55 +0000

The world of the intertubes should be a lot more data driven and awe-sexy than it really is.

Yet for all our collective efforts at writing and tweeting and kvetching online marketing is still based mostly on faith. Not data.

Surprising at so many levels right?

Last week I had the privilege of being invited to deliver the keynote at the annual CMA President's Dinner. John Gustavson, President & CEO of the Canadian Marketing Association, invites a hand selected audience consisting of the crème de la crème of Canadian executives from a vast array of industries. This year they were joined by senior Canadian government officials.

It is difficult to choose something for an address to such a diverse, accomplished and senior audience. My choice was the above thought, faith & data.

My plan was to challenge the status quo, deliver tough love, and inspire transformation.

There were no slides, no notes, just me up on the stage talking. Ok there were around 10 or so bullet items, the talking points. On the flight to Toronto in order to prepare I also wrote down the speech (though I don't read my speeches, so it stayed on the computer).

I wanted to share the speech with you in the hope that it helps you accept the challenging reality we face. I hope it also provides you with a practical set of recommendations to kick your work up a notch or two so we can all win at this web thing.

TV. Internet Marketing. Faith. Data. Problems. Solutions. . . .

__________________________________________________

CMA President's Dinner Keynote.

Good evening.

It is a pleasure to be here tonight and address such a beautiful audience. I want to thank John for inviting me.

My plan tonight is to present some thoughts on how to transform people and companies in the age of the Web, for about 15 minutes, and then address your questions. You are welcome to ask me questions about my talk or anything else connected to the web, companies – marketing – opportunities.

I must admit up front that I am as hard core as any evangelical born again Christian in my passion when it comes to the web. The raw innovation and empowerment that a connected digital world has unleashed is the reason I lovingly refer to it as "God's gift to humanity".

To truly appreciate some of this let us consider the world where marketing is done on faith. Television. Or for that matter magazines or newspapers or radio. All wonderful channels, that are needed and will be around for a long time! But when it comes to measuring success of our marketing efforts all of these channels are largely faith based initiatives.

Consider how we measure success of our TV campaigns.

At a time when there is massive fragmentation of channels and content consumption, where the head is becoming ever smaller with each passing day and the tail becoming really really loooooong, it is amazing that we rely on a measurement system of sampling a handful of viewers who help determine success of tens of millions of dollars of content and millions of dollars of advertising spend. It is outright mind blowing that we use a system whose own legal disclaimers essentially boils down to: "Our data is massively suspect".

Now think of how thin the ice is when it comes to measuring the impact of our precious marketing dollars in magazines and newspapers and other offline channels.

Yet we accept it.

We continue to use faith rather than data to make decisions on $120 Billion (!!) of advertising spend because we don't have much of a choice. We chalk it up to: "It is just the way things have always been." Or: "TV is really hard to measure, those boxes just don't connect or share." [It is rare that we blame the fact that we have not carried out our duty to demand more from both the channel and offline measurement systems.]

All that should explain why I have minor mental orgasms when I think of the online marketing channels and measuring actual business value delivered by our ever more precious marketing dollars.

Just thinking of all the data you can get is enough to put give you a temporary high. With 90+% accuracy you can measure the number of impressions of your ads. You can measure interactions with the ads. You can measure how many people end up on your websites. You can understand how many of them puke and leave! You can measure every facet of success (micro and macro conversions!!). You can measure revenue and economic value! For every dollar you spend! Oh my!!

And to think I have not yet started to talk about how finely you can tune your marketing by leveraging geographic and demographic and psychographic targeting. Leverage powerful metrics like Loyalty, Recency, Brand Perception, Task Completion Rate, Size of Second Level Network, Competitive Share of Voice and more. These are not "loser" metrics like visits and pageviews!

Oh, oh, and you can run experiments! You can fail faster! You can involve your customer in helping you choose the look and feel of your site or the prices you should charge for maximizing profit. You can run controlled experiments to measure incremental online/offline impact and balance the portfolio of media channels you are exposed to, rather than getting distracted by sideshows like "attribution analysis".

So much promise. So exciting. And these are all things you can do today. Don't get me started on the future and what lays ahead, the excitement of it all might cause me to faint.

Yet.

Yet if you look around you on the web you'll see that we swim in a sea of mediocrity. We still see irrelevant blinking banner ads. You'll see astonishingly sucky websites, belonging to come of the best companies in the world. You'll bump into advertising that is remarkable in how irrelevant it is to customer intent. You'll see horrid landing pages. You'll experience missing calls to action, rambling text, and waterboarding through Adobe Flash.

All of it largely driven by faith.

It breaks my heart.

If for no other reason than because your employees are frustrated (they want to be, and can be, so much better) and your customers are being tortured each and every day.

So in a channel that is so full of promise, so full of data, so empowering when it comes to relevance and creativity… why is it that we suck so much?

Based on my humble experience I have boiled it down to three important things:

1. The web has been around forever and yet it is not in the blood of the executives who staff the top echelons of companies.

Make no mistake, they are smart, they are successful and they want to do better. But the web is such a paradigm shift that if it is not in your blood it is very difficult to imagine its power and how to use it for good.

How do you demand innovation & creativity & radical rethink if you can't imagine it?

2. We still believe in and live in the world of "shout marketing", the thing we have practiced on tv and radio and magazines all our lives.

It is not that we don't mean well. But our mental models are jaded.

We still believe in getting lots of impressions. We want to interrupt. We don't despise irrelevance enough. We care about "eyeballs". Because that is all we know. Unfortunately the web (/interactive /digital /social) mandates new mental models, and we are the old dog that won't learn new tricks.

3. Our lousy standards for accountability.

Pause and think of how we measure success today. We measure "reach", we measure "exposure" and other such lame metrics. Partly because that is all we have been trained to expect.

We never say: "Here is a 100,000 for my search campaigns, please come back and report on task completion rates across the top three primary purposes and the economic value added." We never say: "Don't try to fool me with page views generated, did we impact page depth on our content site?" We rarely push hard by saying: "I don't care how frequently our content was updated, what was the impact on visitor loyalty." Or say: "Fine we improved online conversion rate by two percent, but what was the impact on the sales in our retail stores?".

Our bar for accountability is less than low. It is almost non existent.

So…. It turns out the problem is not the web, the problem is not the opportunity, the problem is not measurement.

The problem is you.

The problem is every person in this room.

Our raw understanding, mental models and expectations.

I am sorry. It is kind of a bummer to hear that.

But if you are the problem then the nice thing is that you hold in your hands the power to change your companies and bring about the promised revolution of data driven customer centric online marketing.

Problem identified, how do we fix it?

At the risk of being booed out of this impressive ballroom let me say that the solution is to Embarrass Management!

People who report to you and ask people who report to you to embarrass you.

Why is it awesome?

Turns out no one likes to have their egos bruised. Leverage this powerful force to start to address the three problems I had just outlined.

There are two specific strategies I recommend.

1. Leverage Your Customers.

They want to help. You just have to politely ask.

Not being polite is popping up a 35 question survey on your site. Being polite is inviting them to answer just a couple of questions about their experience when they leave the site. Being polite is uploading your latest "oh my god they are so going to love this (!)" design into fivesecondtest or usertesting and letting your customers share feedback at the cost of a few Tim Hortons coffees. Being polite is running a/b tests on your site so your customers tell you which call to action, piece of content, navigation structure or even product price will yield highest customer satisfaction AND revenue!

Leveraging customers means that when the HiPPO / Boss (perhaps you) opens her mouth to say: "I don't think that will work" or "I like that other way better" or "No one will buy a toothbrush priced $299" or "Twitter is dumb"…. you can say: "Why don't we mock up a quick experiment / online survey / media mix model to validate your hypothesis?"

Allow your customers to help you evolve your mental model. Allow you customers to teach you new and effective marketing strategies. Allow your customers to complement your existing intelligence and savvy.

And if it is hard to get to the above point…. leverage embarrassment!

I recently spoke at a major conference about how one of the top camera companies was disappointing its customers by stinking at the long tail of search. I searched for a digital camera, wireless printer and digital camcorder as a normal undecided customer would. None of my 18 or so searches threw up a single link for this company (not organic, not paid). And yet I was ready to spend $500.

Then I copied exact text from their website for multiple products and searched for them another 20 times. Result? They still would not show up.

Trust me nothing hurts like that raw view of massive failure of your online marketing on the single best acquisition channel on the web today.

Caused embarrassment. Forced a rethink at what is a glaring football field size hole in their marketing strategy.

Who wins? Customers. And the company, they will reduce acquisition cost and make more money.

When there was an argument at a top financial services company about what the home page, the holiest of holy properties per this company, should look like what do you think the company was going to do? Go with the version the President & CEO of the company liked. One smart person interjected to say: "Why don't we take your instinct and convert it into a HiPPOthesis?".

The CEO smiled. They tried three versions. The CEO's performed worst, on goals he had chosen. He still smiled after the test because 1. They made more money. 2. Avoided a big mistake. 3. Created happy customers. 4. He learned something new.

By involving customers companies have figured out that garish zebra print bed sheets are a perfect fit for being sold in their offline stores, identified the perfect song for their tv commercial, designed the best selling dvd covers, discovered pricing / discounts / product bundles that they would never have thought would have worked.

All faster and at a lower cost, with a higher impact on the business. Mental models evolved. Accountability increased.

2. Leverage Competitors.

I have rarely found a strategy that works better at elevating the game of any company than contrasting their efforts with those of their competitors.

It is astonishing that in a medium where your competitor is just a click away, the experience is absolutely frictionless, that we still live as if the burden and hurdles of the offline world exist online.

It is in comparing to competitors, known and unknown, that you can truly get the management to pay attention. Something about the size of the hit to the ego.

Here's an example.

Recently I visited the Sr. Executives of premier technology company and showed two sets of numbers. The ACSI has been measuring customer satisfaction for more than a decade. During that decade Apple's customer satisfaction went from 77 to 84. During that exact time period this tech company's numbers went from 78 (one point higher than Apple!) to 74.

Ouch. That hurts. Especially because they have poured many millions into "improving" the site (and a few million on analytics!).

Sure they don't have the "fanboyism" of Apple, yet Apple had that 10 years ago too. It is painful to realize that Apple started behind them and moved so far ahead, during a time where they not only did not defend their lead…. they actually regressed.

What do you think the management is doing now? Yep, questioning key things like who makes decisions, what the org structure looks like, how can they replace current hyper matrixed accountable structure with something that forces the right behavior at all levels.

Here's another example.

Rather than showing a CPG company how one of their sites was doing I took the liberty of comparing their tea website with their detergent website with their shampoo (personal grooming) website. It was astonishing how each was doing. For example the much smaller tea business was doing better than their key personal grooming business.

But I did not stop there. I compared them to an external benchmark.

What do you think I used? Their direct competition? No. I compared them to my blog's traffic.

It turns out I get two times the traffic when compared to all three of them combined!

Now my blog has nothing to do with a large multichannel CPG company. Yet I write a blog on an esoteric topic (I know that no one really cares about web analytics) and I write twice a month.

Yet I can get more traffic! Part time. With no marketing.

And they spent a couple of million dollars building their websites. To deliver what outcome?

Can you guess the result of this effort?

If you guessed a massive evaluation of their online strategy, ordered from the very top, then you would have guessed right.

Competitors provide a great contrast to your lameness or awesomeness. Be it leveraging the full power of online marketing channels. Be it creating optimal customer experiences. Be it bringing a new layer of imagination and accountability to your existence.

Embarrassment works.

Of course you have to do it right and be absolutely transparent that comes from a place of deep love and from a desire to to be better.

Because you see the goal is not to embarrass. The goal is not to be rude.

The goal is simply to provide context, fast. The goal is to get you, and your companies, to move beyond faith. The goal is to see the obvious potential in front of us. The goal is to throw away the shackles that have for far too long weighed us down.

That is what I mean by, now in quotes, "embarrass".

I hope you take away the passion I feel for making sure that advertising on the internet has to be magnificent and accountable. I hope you'll go empower your organization to "embarrass" you and that you'll do the same to them. I hope tomorrow will be the first day of a revolutionary transformation for your business.

Good luck!

__________________________________________________

The speech was received better then I expected (never easy to tell your audience they are the problem, or lay out tough to swallow solutions). I was profoundly grateful for that. The Q&A session following the speech was a of fun as well (always nice to get a chance to give my "It's not a OR world we live in, that's for super lame folks, it's a AND world!" mini sermon).

It's your turn now.

I would love to get feedback. What are your thoughts on the promise, the three problems and the two possible solutions to jump start a magical revolution?

Online Marketing Still A Faith Based Initiative. Why? What's The Fix? is a post from: Occam's Razor by Avinash Kaushik

Analyze This: 5 Rules For Awesome Impromptu Web Analysis

Avinash Kaushik — Tue, 04 May 2010 08:44:22 +0000

The hardest kind of "analysis" to provide is in response to open ended questions. That is why I love asking open ended questions!

They expose a person's critical thinking ability (something I highly recommend you test when you hire web analysts: Interviewing Tip: Stress Test Critical Thinking. Please).

They also help you understand if someone really grasps key concepts.

Recently on behalf of Market Motive, my start up that focuses on online marketing education, I had the opportunity to offer one scholarship for the latest round of Master Certification in Web Analytics.

So at the end of my 10 Fundamental Web Analytics Truths blog post I requested readers who were interested in the scholarship to complete this simple task:

Pick a site you love and tell me three things you would change about it, and why.

Seems straight forward right? It is not!

First I must say that I was overwhelmed by the responses (thanks!) and I was impressed with the time people took to do the analysis. I got wonderfully created pdfs / Word docs and well written emails. I was amazed at the creativity on display (which validated the fact that I have chosen to be in the right industry!).

Based on the responses, some wonderful and some not quite as wonderful (!), in this post I thought I'll share with you some tips should someone (like me!) ask you an open ended question ("what would you and why").

The first part covers 5 rules, sourced mostly from what people did not do. The second part contains 4 things people did that delighted me.

Let's go.

When someone asks you an open ended question, at least connected to web analysis, here's what's important. . .

1. Don't offer your opinion, at least not right away.

This is a very very hard temptation to resist. But try.

These were most common fixes people wanted to make on sites they loved:

Remove big header
I don't like the colors.
I would change the entire site design.
Reduce font size / increase font size.
The font type is not great.

I have to tell you that the last thing anyone wants to hear, in this context, is your opinion.

Not your boss. Not your friend. Certainly not the HiPPO (Highest Paid Person's Opinion).

Even if you believe that you are "absolutely right"! [Note: I often think I am "absolutely right". :)]

You and I are poor proxies for the customer. And just because you don't like something… how should I put it so you'll understand…. oh let's try this…. you not liking something is not a statistically significant sample of data!

On a serious note… offering your opinion on something, unsupported by any data except "I think", is probably a really poor way to start a conversation with anyone in the Analytics field.

If you express your opinion then present it in the from of a hypothesis that can be tested. Win-win.

So for example consider saying something like:

"I have viewed the site through Google Browser Size. The huge header on the website is causing the main content to be visible to only 40% of the website visitors. Based on this my hypothesis is that reducing the size of the header will reduce bounce rate and increase click-through rate to key pages/products."

See the difference?

It is ok that you started with a hunch. You went and got some kind of data. Finally you offer a hypothesis that I can test, and you were clever enough to point to two things of value to the business (both of which can be measured!).

Your HiPPO / Boss is much much more likely to listen to you and accept your wisdom.

In the rarest of rare cases if you must express your opinion, present your credentials. Something like:

"I would change the layout of the site and eliminate the images because I am Jakob Nielsen and I know what the heck I am talking about!"

See that would be acceptable. :)

Overall: if you can, try not to offer your opinions (at least not in the opening statement).

2. Always offer alternatives / Think things through.

One of the persistent flaws in Web Analysts (and Marketers as well I am afraid) is that far too often we take a siloed view of things. We only see our slice of data. We only see our little world. We only care about what bothers us / what makes us happy.

You should always take a much more expansive view of things and when you make recommendations think of the big picture, think things through.

Here is a good example.

I was astonished at how many Ninja's included this in their fixes: Remove Ads.

Now I love adblock as much as the next guy and wish advertising (especially Display) were more relevant.

But when you as an Analyst recommend removing ads because you find them annoying (and they can be super annoying) you are essentially recommending the removal of a revenue stream.

Ok so if I accept your recommendation of removing ads what do you recommend I do about the revenue stream?

The "remove ads" recommendations did not consider that implication of their recommendation.

Now I don't expect you to be an expert on the intricacies of the business you are analyzing when I give you an assignment to do "impromptu analysis". But I would have loved to know that you thought about the big picture, what you thought about the implications of your recommendations.

You could have said:

"I would remove the ads because they are super annoying. I would recommend replacing them with an investment in targeting email campaigns which I believe will more than make up for the missed revenue.

Or:

"I would remove the ads and instead add a prominent "If you love the content donate money" button on the top navigation. The money we lose in advertising we will more than make up in donations."

Or:

"I would remove the ads. While that will mean we lose revenue in the short term, my hypothesis is that customer satisfaction will improve by 18 points which will lead to increased Visitor Loyalty and is that not what ESPN really wants?"

Give me a clue that you have: 1. Thought through the implications of your recommendations. 2. Have some alternatives handy, no matter how pie in the sky.

Here is another recommendation that is more nuanced, and something I think we as Analysts rarely think through.

The recommendation was that Flickr should allow posting of anonymous comments because it will likely result in more comments being published on pictures which will potentially increase User Engagement.

A very nice suggestion.

But by now it has been well established that anonymous comments very quickly lead to unintended consequences. [New York Times article.] All kinds of people jump in and, quite literally, say all kinds of things.

I would have loved to hear what your suggestion was to deal with this absolutely sure to happen outcome from your recommendation.

Think things through. As an Analyst, as someone who thinks more broadly.

[Note: I am not saying comments are bad. I am not saying all anonymous comments are bad. I am not saying comments should be 100% moderated and neutered before being posted. There is a happy medium and there are many wonderful options to deal with this problem.]

3. Offer data, even when you don't have access to the site's data.

Alec shared a guidance with me after the contest was announced. He said, and I am paraphrasing, "award the scholarship to the person who says that they can't make any recommendations to fix the site they love because they don't have access to the data".

Really good point.

I had very much kept my question open ended because I really wanted to see if people got creative with how they arrived at the recommendations (beyond the "I think").

I am afraid no one provided data.

On the surface it is understandable. You are doing analysis, impromptu analysis, on a site that you don't own. Of course you don't have access to data to base your opinions on.

Unfortunately that is not quite true.

You ALWAYS have access to data. For ANY website.

If you want to understand the clickstream data for any website you could go to Compete (here's ESPN's data, or this blog's). If you want data for a international site use Google Trends for Websites (here's H M V's data, and here's data for people from Switzerland who read the French newspaper LeMonde).

Sure the data is not 100% accurate, but it is directionally accurate and it will take a few minutes on either Compete or Trends to dig a bit and find something interesting you could base your recommendations on. It should take you a few more minutes to compare data for one site to its direct competitor and identify something even more interesting.

If you want to understand the search engine ecosystem then use Insights for Search. Check out how much delightful data is available to you: Acne vs. Poison. [Look out, poison making a massive come back!!]

Spend time understanding the keyword market and consumer interest for the business you are analyzing. Find strengths and weaknesses. Find opportunities (by geographic region or in the cluster of top related searches or, my fav, fastest rising searches). There are so many sources, so many possibilities (many free!).

If you want to get demographic or psychographic segmentation data use the DoubleClick Ad Planner. In a few minutes you can understand the demographic make up of any site.

Male – female, age, education, household income, audience interest and more. In a few more minutes you can get down identifying the psychographic segments. Affluent 100k+? Brides-to-be? Gossip Gurus? Home Buyers? Moms? Technology Geeks? Who are we talking to? Who do we want to talk to?

And these are just the basics. Check out: The Definitive Guide To (8) Competitive Intelligence Data Sources.

You always have access to data. Regardless of if you own the site or not.

If you are put in a position where you have to offer impromptu analysis please use these (and other) data sources to add the kind of power to your recommendations that can only come from being backed up with data. Some data.

4. Always, always, always state what you think the Objectives are.

This is such a common mistake when we present our analysis. We make recommendations without saying what we are actually solving for.

Before you present your recommendations first tell me what you think the website's objectives are. What you think the purpose of the website is. What you think the site is solving for.

Often analysis is not valued very highly not because it is stinky, it is because the producer and the receiver disagree on what the objectives of the site are.

I might think the purpose is: Orders, Leads, Job Applications.

You might think the purpose is: Facebook followers, Brand Perception Lift, Product Reviews.

If you don't tell me what you assumed the objectives were you'll see very quickly why I might think you produced nothing of value.

So make it clear.

I might still think your analysis was poor (or awesome!), but at least I know what you were solving for.

I have context within which I can place your analysis.

You might think that it is obvious what the purpose of GoNomad or NBA.com or SFAF is. But I assure you that it is not obvious. So make it obvious, we'll both come to your analysis / recommendations from the same perspective.

In your daily jobs you should never present your analysis without having shared vision around the objectives. Otherwise the best result is no action will be taken on your recommendations. The worst result is… we'll I don't have to say it do I? :)

[Use this if it helps: Web Analytics Measurement Framework. Though for impromptu analysis you don't have to get that detailed. Just keep the framework at the back of your mind.]

5. Focus on the obvious, and the non-obvious.

Even if you spend only 30 mins on doing some analysis try to say something that I won't anticipate by spending 5 mins on the site's home page.

Surprise me [/ your boss / your audience / children / god].

Here is an example.

I can guess the Macro Conversion on site in two seconds. So tell me about the three Micro Conversions that are not obvious but of great value to the site.

Say you looked at Williams-Sonoma. Points for telling me about ecommerce. Bonus points for grasping and telling me how to improve qualified sign-ups for the Williams-Sonoma Catalog (which brings a lot more revenue in the long term than a quickie online order). Or how to improve number of brides creating Wedding Registries (huge money there). Or memberships to the Wine Club. Or Gift Cards (which are essentially customers making interest free loans to Williams-Sonoma!).

Surprise me.

Visit the website of the site's biggest competitor and tell me two things they do well that you think your site should.

Dig out industry standard scores for Customer Satisfaction & Task Completion Rates and use that to tell me areas of opportunities.

Give me three specific ideas for A/B or Multivariate tests and state your hypothesis for what will change.

Present your analysis / recommendations in a different format.

Shock me by including a framework you use for your recommendations (which one person did, it looked like a house! so amazing!).

Postulate a good enough reason to use Social Media (not just because everyone is doing it).

Tell me about how the inevitable demographic shifts in the US population will destroy the current business that this company has.

Surprise me.

If Scott or Brett or Dai or Trevor or someone else can spend a few minutes on the website and come to the exact same conclusions as you then it is unlikely that your analysis will be as impressive as you think it should be.

So… focus on the things that will be obvious to many and then include at least one non-obvious thing that almost no one will focus on because only you, the unique awesome genius person that you are, will see it.

Summary: Don't just offer opinions, think things through, offer data, clarify what you are solving for and finally do at least one thing that falls in the non-obvious category.

Amongst the submissions that was presented there were some common themes in the I was quite delighted by.

Here are a few of them, you should do these too when you do analysis…

1. "Why before the how"

Almost everyone focused on redesigning the home page, with one holy goal in mind: Make the value proposition of the company really clear really fast.

I love that!

One person framed it so well: "Address the why before the how."

Brilliantly put.

Use that mantra every day.

Some things were common in many submissions, and these I really really liked:

2. Obsess about SEO.

Some folks diligently focused on SEO, and I LOVE SEO!

From garbled urls to missing title tags to poorly linked internal pages to missing site maps. I am so happy people found these things (and EVERYONE of you can too with basic knowledge of SEO!).

It is "free" traffic, but more than that it is investing in the long term success. It is pretty attractive to jump to Paid Search recommendations or doing more Email Campaigns. You should do that, but if you come to me with that and not mention SEO you are going to break my heart.

[Even if you are an Analyst I expect you to have the knowledge described here: Official Google Search Engine Optimization (SEO) Starter Guide.]

3. Be different.

I covered this a bit in #5 above. But wanted to share more context with you.

In their analysis some people tried to be different. That is always a good thing.

Instead of sharing a site and three things one person shared three things they would change about the state of Texas!

Made me smile (and I sent him a free copy of Web Analytics 2.0 :)).

On a serious note… you know the obvious things people will say in these situations, and so do the HiPPO's (they have heard it all before). Try to be different (though not Texas different!).

4. Be sweet.

Without exception everyone was very sweet. Most people tried really hard to send me the best submission they could. I got special graphs, images, wonderfully formatted word documents… so much.

It was so nice. I feel profoundly grateful.

Life is short. Be sweet to those around you. They'll reflect it back. One person at a time we can make the world a better and less bitter place.

Closing Thoughts.

I recognize that you won't do all of the above for an "impromptu analysis", else there would be nothing impromptu about it.

I hope that you'll take the principles outlined in this blog post and make them a part of your DNA. When you are asked to do some quick analysis that you'll activate these principles, even without thinking about them too much.

When I have to analyze a site I quickly make a note of the two or three objectives of the site (and one of those falls in the non-obvious category). I log into Compete and Trends and get some data about clickstream. I see if there are clues in Insights for Search and Ad Planner about the site's business. Then I write down two of three things recommendations / fixes that I can back up with data, or in case of no data formulate and preset a couple hypotheses for testing.

It takes me between 30 mins to an hour. I won't change the website's trajectory in a massive way, but I'll definitely give them some concrete things that will have a short term noticeable positive impact.

And you can too!

Ok now it's your turn.

What is your approach when put on the spot and asked for some analysis of a site you don't own? What are one or two techniques that work for you? Thoughts on the above nine principles?

Please share your critique / approaches / feedback in comments below.

Thank you.

Analyze This: 5 Rules For Awesome Impromptu Web Analysis is a post from: Occam's Razor by Avinash Kaushik

10 Fundamental Web Analytics Truths: Embrace 'Em & Win Big

Avinash Kaushik — Tue, 23 Mar 2010 09:48:23 +0000

There are more mistruths and F U D about Web analytics out there than I think is reasonable.

Part of it fueled by Vendors. What a competitive bunch!

Part of it fueled by some Consultants. I suppose the rational is: self preservation before all else.

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. They generally feel it is beneath them to use a standard tool, they push a utopian world that is hard for anyone to accomplish, including themselves, even after spending a minor fortune.

This is sad. Even a little frustrating.

My problem with these mistruths and FUD is that they result in a ton of practitioners and companies making profoundly sub optimal choices, which in turn results in not just much longer slogs but also spectacular career implosions and the entire web analytics industry suffering.

Let's try to change that. If you agree to help I am confident we can accomplish a lot.

Web Analytics, this beautiful child, was born just the other day in the midst of tumultuous times, quite literally, when everything changes every day. This constant evolution means that every time it learns how to do something the world changes around her and then it is on to learning the new things to stay relevant.

It has simply not had a break to catch a breath and mature.

And I doubt it is going to happen soon. The web is changing too fast. Too many new things are happening too fast and those of us charged with measuring it have to change the wheels while the bicycle is moving at 30 miles per hour (and this bicycle will become a car before we know it – all while it keeps moving, ever faster).

Yet. Yet. Yet, yet, yet, yet…. there is so much we can do.

Now.

This instant.

We can make use of what we have. Javascript tag driven click data processed in the cloud provided through a web based front end that allows you to segment and create meaningful views of the data unique to you.

Even with the tools we have, in the state we have them, we can be smart. In fact smarter than you would be through any other channel on the planet!

Don't fall for the FUD. See through the mistruths. Don't go down rabbit holes.

The opportunity is too big for you to be distracted.

In this blog post let me share with you some ground truths from my own humble experience. It's a bit of black and white in a world that admitted has lots of gray.

My hope is that it inspires you. That it helps you focus your precious time and resources. That it results in you making fewer mistakes.

Finally, that it helps you go kick some bottay!

Here are ten web analytics ground truths….

1. If you have more than one clickstream tool, you are going to fail.

Strong words!

It is perfectly ok to date as many people as you want. It is ok to put them in tough situations (just introduce her/him to your parents!). It is ok to go all the way and see if things click.

Once you make up your mind and get married, practice monogamy. Bigamy is vastly overrated.

Here are some reasons:

~ It is really really hard to make sure you have implemented one tool correctly. Not just javascript tags but the ecommerce customizations, the custom variables / sprops / evars, the unique campaign tags required by each tool (for search and affiliate and email marketing etc), the internal site search configuration, the insane javascript tag updates just to make the darn segmentation work (except in some like Google and Yahoo Analytics), the… I could keep going.

You'll be hard pressed to do one right, doing two is like asking for King Kong to slap you. Repeatedly.

~ It is really hard to get a organization to use one set of numbers (and remember they are not going to be clean or complete, no matter what you do). Why do you think introducing a completely different set of numbers is going to make your life easier?

Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization. Why? Because every tool uses its own sweet metrics definitions, cookie rules, session start and end rules and so much more.

You'll have no time for data analysis, certainly not for data actioning.

~ It is a bit silly to believe you can use one tool for purpose x (say search analysis) and another for purpose y (say everything else).

When it comes to proving which campaigns are better and which numbers to report to the management what will you do? How will you make sure you are in every meeting where people bitch and fight about getting credit?

There is nothing magical about they way clickstream data gets collected by any tool. They are all 95% the same.

Date around, find the one you love, marry it, stick with it.

If nothing else convinces you, remember that clickstream data is a small part of the data you'll use to make smart Web Analytics 2.0 decisions. For big success you'll need to have a Multiplicity strategy:

So when you step back and realize at the minimum you'll also have to use one Voice of Customer tool (for qualitative analysis), one Experimentation tool and (if you want to be great) one Competitive Intelligence tool…. do you still want to have two clickstream tools?

Likely not.

2. Omniture cannot save you. Only you can save yourself.

There is a absurd belief that if you buy a paid web analytics tool that you'll bathe in milk and honey and magically insights will be delivered.

Paid web analytics tool come with clickstream analysis tools that are hobbled on two counts:

1. They come with legacy problems in their code and architecture that make it nearly impossible for you to do anything fast, or even do simple things like one the fly advanced segmentation – you constantly need to change the code and know everything you want to analyze up front.

2. They will never be as powerful as Yahoo! Web Analytics or Google Analytics because otherwise Paid Vendors could not upsell you to, in case of Omniture toDiscover2 and Insight. In case of WebTrends replace those terms with Marketing Intelligence / Visitor Data Mart etc. In case of Coremetrics….. well you know.

This means when you buy a paid web analytics tool you'll be hobbled until you buy the versions of the product that actually do the job you want (and more).

Now if you decide that you don't want hobbled clickstream tools but would rather buy the complete suite on day one this is what you buy:

A 18 month implementation schedule and a 12 month process of redoing things (life changed in 18 months) and no money for Analysts (you sent have $3 mil to your analytics vendor by now) and you the lone ranger have in two and half years barely managed to deliver improvements to reduce bounce rates for top email campaigns.

Was that what you set out to buy?

Know what you are buying. Not insights, as alluring as they sound. You are buying implementation with a possible future promise of some actionable data three years down the road.

Ready to use Google or Yahoo! Analytics today to make 85% of the decisions you need to make after 3 weeks of implementation?

If you are just starting your analytics journey does it not sound reasonable?

Let's flip the coin.

You already have the paid analytics software combos mentioned above.

It is just as absurd to believe that Google Analytics is better than your Omniture Site Catalyst + Genesis + Discover with a dash of Insight. I have to bang my head on the wall when I hear that someone just replaced Omniture Site Catalyst + Discover with Google Analytics.

Why?

You just spent two years implementing them! And you paid three million dollars!!

There is nothing you get with Google Analytics that you did not already have. In fact with Discover you probably have 12 things Google Analytics can't do (that's whey you are paying an additional million dollars plus on top of what you are paying for Site Catalyst!).

Google Analytics can't save you if you already have the set up above or CoreMetrics Analytics + Explore or Unica's NetInsight OnDemand + Customer Insight + PredictivInsight!

If you are still failing then the problem is not the tools.

The problem is you. Your organization. Your skills. Your budget allocation priorities. Your silos. Your HiPPO.

Switching to Google Analytics, in the set up above, is not going to help you.

Fix what's actually broken, it's your WebTrends combo of Analytics9 + Visitor Data Mart or your CoreMetrics combo of Analytics + Explore + Benchmark + whateverelseweboughtbecuaseitsoundedgoodinthesalespitch.

Org. Skills. Structure. Process. Courage.

The only reason to switch to Google Analytics when you have the above is that you can't fix what's broken (org structure, skills, hippo). You might as well save the $3 million you are sending to your web analytics vendor.

3. It is faster to fail and learn then wait for an "industry case study" or find relevancy in a "industry leader white paper".

I met a small group of top companies in London recently. Post my keynote the feedback I got was: "Your presentation was powerful, you made a compelling case for how we can do the things you have outlined to take advantage of the opportunity. Do you have some relevant case studies you could share with us?"

I let out a quiet scream.

In this day and age I completely fail to grasp the need for "case studies" and "white papers".

In my offline life I looked for case studies because it was very expensive to try something new, you wanted someone to have failed already. I wanted a white paper so I could convince my HiPPO (Highest Paid Person's Opinion) that some magnificent Thought Leader pontificated something so we should do it.

Most case studies were at best from tangential businesses. 100% of the time the companies did not have the priorities that our business was currently executing, neither were they driving towards the same outcome.

Yet case studies in some sense reduced risk, even if they were simply over blown marketing fluff written by the vendor.

I don't need case studies now, not on the web.

Why?

If someone tell's me that vanity url's are a great way to start measuring multi channel impact then I can just try it for 500 times less effort than it would take me to find a case study.

If I go to a conference and hear that doing test and control experiments is a great way to measure cannibalization by paid search links on well ranked organic keywords, then I can just run a small test myself and see if it works for me.

If you blog that a short on-exit survey or a feedback button is a great way to collect voice of customer, I don't have to be lazy or hyper paranoid and wait for a convincing case study. Both of those are available for free, I'll just implement and be my own case study.

Email campaign ideas, content improvement, behavior targeting, testing product prices, hiring a supposedly awesome consultant, using offline calls to action, measuring impact of television on the web, opening a twitter account of a B2B business, doing….

Anything you can think of I can do it. Usually for free. Usually with a modest effort. Usually at least a test.

I can fail or succeed all by myself in my unique circumstances delivering for my unique business goals in my own organization.

Why do I need a case study?

Neither do you.

There is such little risk to actually trying. You don't need no stinking false comfort that something worked for someone else.

Fail faster.

[I realize for some HiPPO's old habits die hard, they won't even let you run a report without seeing a case study. Update your resume and start looking for another job - because the org you are with will never be as successful as it should be. Meanwhile see if you can convince your HiPPO to run a small test while you look for a case study (and a job).]

4. You are never smart enough not to have a Practitioner Consultant on your side (constantly help you kick it up a notch).

The field of web analytics (especially 2.0) changes far too much in far too short a time.

That's because the web changes too fast (and vendors that don't update their software to take advantage of these opportunities every quarter will die).

Yet companies, falsely, believe that they can keep pace and do it all with no external help.

That almost never works. Because…

1. You are far too busy actually reporting and analyzing to keep pace with all the wonderful evolution

2. It is cheaper to get someone to answer your question at $60 or $80 or $100 or $150 an hour than spend a week "trying to figure it out".

Hire a Practitioner Consultant (someone who just does not speak at conferences but actually rolls up her sleeves and does the dirty work) on some kind of a retainer, or buy a bank of hours you can cash out say during the next six months (or whatever) and get solutions delivered to you. You focus on taking action.

I recommend this blog post: Web Analysis: In-house or Out-sourced or Something Else?

In it I describe four stages into which each company fits (in terms of its current analytics evolution) and what you should expect from a consultant in each stage.

This will help you figure out exactly what you might need and hold your consultant accountable.

Here are three additional tips about hiring consultants, from my humble experience:

1. Compute how long the person has been consulting, call this X. Compute how long the person had actually worked as a practitioner in a real company (hopefully in your industry), call this Y.

If X > Y, it is possible the consultant might be disconnected from the reality of what it really takes to get businesses to use data (and not it is not just tool expertise). [This means I have 3.5 yrs left to be a hands on practitioner consultant!]

If X >> Y (substantially greater :), avoid.

2. If you can try to hire an independent external consultant.

It is not that the consultants at Omniture or CoreMetrics or WebTrends are sub-standard, they are Absolutely Not. But they do face dual pressures of selling you more consulting and up-sell products. If you have a independent consultant they only try to sell you more consulting! :)

That is the reason I am partial to hiring authorized consultants for Google Analytics (GAAC's) and Yahoo! Analytics (YWAAC's) or for Omniture / CoreMetrics / WebTrends going with someone such as Stratigent or Zaaz.

Oh and don't forget rule #1 above.

3. Do a Google search for the Consultant. Read what people say about them. Read what they say about themselves and others. Read how they contribute to the blogosphere, to forums. Form an opinion, then hire.

If possible hire a nice person. Life is too short to work with jerks, no matter how skilled or knowledgeable they are./p>

Good consultants will help you stay current, solve problems faster, deliver solutions and not just reports, allow you to focus on analyzing data and finding insights.

5. Your job is to create happy customers and a healthier bottom-line.

If you think your job is to analyze the "numbers" your career will be limited.

People (you? :) whose job it is to do "the data thing" spend day after day after day in analytics tools producing numbers (if they have time left over from tagging, begging IT, changing tags, turning down vendor up-sells, begging vendor for more svars and eprops and asi slots…).

Numbers with data and tables and graphs and pivots and font sizes and automated pdf's and…. a lifetime spent producing numbers.

Here's a major reason why all that effort, the numbers deluge, changes nothing for a company:

You / me / they never ever bother to actually go to the website.

Never bother to search for their company and look at the paid and organic results (to find broken things).

Never bother to sign up for their own email campaigns (to see how much they stink).

Never bother to buy something on their site see live the torture.

Never bother to try and return the product/service purchased via the site (and see how much that stinks).

Never bother to visit competitor sites and find nice or terrible things (to take advantage of).

Never bother to do a online usability study (it just costs $20 a pop!!).

Never bother to….

Look, if you are not going to go out there and feel the heat how do you expect to get the insights you need about where to focus and what to do?

Your web analytics tools only provide you with numbers. Then its up to you. And you can only begin to focus, prioritize, find stories and fixes and opportunities if you actually immerse yourself in understanding what you are supposed to analyze.

Walk in the customer's shoes so you'll understand how much your site stinks (then find the numbers that help prove that, or not). Email people who have placed orders, asked them for their frustrations. Answer tech support emails for a day.

Every single day ask yourself this question: What amongst the data I have provided today will create happier customers tomorrow?

If you don't have a direct line of site from your work to happy customers, you are doomed.

Ditto, perhaps even more so, if you are not incessantly focused, every single day, to providing data stories (or "info snacks") that help improve your company's bottom-line. Every day. Wait. I said that already. : )

If you, the "Web Analyst" don't believe that you hold in your hands the power to change your company's existence then you are either at the wrong company or, more likely, in the wrong job.

6. If you don't kill 25% of your metrics each year, you are doing something wrong.

In ancient times we would hire Accenture or some such august consulting group to come in, spend six months systematically going through the business and recommend Measurable Success Factors (shorthand: metrics) and those then would be carved into stones, handed to the Good Lord's messenger and the rest of us would for ever follow the commandments unquestionably no matter what happened.

While I am exaggerating a bit for effect, most web businesses, if they identify key metrics, and then never go back and revisit and revalidate.

It should not come as a surprise that after just a few months you find that no one looks at your dashboards, no one can seem to find insights from the data and the company has reverted to "faith based initiatives" rather than "data driven initiatives".

The web changes too fast for us to believe that we can be stationary with 1. our measurement strategies 2. what to focus on priorities 3. success measures.

We need to change our measurement strategies as changes occur in:

1. Marketing strategies (from forums to display to search to social to mobile to…)

2. Business priorities (no we are not doing ecommerce, we want leads!)

3. Structure, purpose, audience (oh my!)

4. Available measurement technologies (ohh…. sentiment analysis!)

5. Skill set available (wow we finally got someone who know what r squared is?)

6. HiPPO's bonus measurement metric (you will never succeed unless you are trying to get the person on top promoted or a higher bonus, keep very closely informed as to how they get paid, find insights that solve for that, you will have eternal love and a data driven org)

All of the above happens all the time to every website. So why should your reports, dashboard, measurement priorities and "Measurable Success Factors" stay stagnant?

By forcing yourself to have a target for killing metrics you are ensuring that you'll focus on an important activity once a quarter. You'll re-visit your assumptions and what's important to the business. You'll be forced to talk to HiPPO's, Marketers and pretty much anyone who currently consumes the output from you/your team.

And that, as Martha would say it, is a good thing.

[Allow me to point out that only 50% of the metrics I love exist in clickstream tools - like webtrends or xiti or unica. The other 50%, the ones that help drive key changes to the business exist in other places. Metrics like: Multi channel value index. Impression Share. Task Completion Rate. Keep that in mind when you choose metrics to ensure you are not over-leveraged in metrics that don't matter.]

[Bonus Reading: Five Rules for High Impact Web Analytics Dashboards.]

7. A majority of web analytics data warehousing efforts fail. Miserably.

There are few investments as overrated as building a catch all massive data warehouse to give you the "global cross functional multi channel single view of the customer experience and lifetime value on demand through a business intelligence report powered by an econometric model that takes into account page view probabilities using the Clopper-Pearson binomal confidence interval".

Yet that is exactly how internal data warehousing projects are championed or external cloud based data warehousing solutions are sold by vendors.

As of 2010 I still have a lot more years that I spend in the traditional data warehousing / business intelligence world than in web analytics. I have personally executed data warehousing projects for web data (in the broadest sense), and they have mostly been miserable failures. [Warning: There is a distinct possibility perhaps I am the problem here!]

Here are some problems you face with web data (when it comes to warehousing):

1. There is too much granular data! Yes yes I have purchased the Netezza appliance, yes other promise "massively parallel processing data warehousing appliances". The problem is not the hardware or the hardware company, the problem is the amount and type of data (most of it is actually worthless, even if you can get much of it into the warehouse). Things of course get worse when you think of warehousing in traditional software only solutions.

2. The data is rarely deep (say about a person), is mostly anonymous (about a person) and full of holes (cookies, scripts off, plugins). This goes counter to the strengths of what data warehousing is able to pull off so well with offline data (years and years of data too).

3. Warehouses expect logical structures and relationships, you'll be astonished at how little of this exists in your web analtyics data (see reason above).

4. It is worse than extracting all your teeth with a toothpick to try and get your offline data merged with your online data (even if, and it is a BIG IF, you can get the requisite primary keys).

5. BI tools stink at answering questions web analytics tools answer with ease (how many people clicked on a link on our home page, how many sessions from keyword "avinash" came from Google and abandoned products in their cart,….). This means trying to replace a WA tool with a Warehouse only results in an organization slowing down further.

6. Campaigns, tags, links, meta data (if any that might exist), data relationships, metrics, website url structures etc cause there to be a constant demand to make changes to the underlying structure of your data warehouse every single day. Yet no dw team is organized to execute on a daily schedule, you'll be lucky to get monthly. All of the aforementioned is not a problem for your web analtyics tools.

I could keep going on. Please please please make sure you don't make a decision to invest millions of dollars (that's what it will take by the way for a fortune 5000 company) based on the promise of data warehousing, look at the reality and apply that filter. It will be humbling.

Oh and before you tell me that you want to build a data warehouse to store history let me point you to this blog post: History Is Overrated. (Atleast For Us, Atleast For Now.) Please give it a quick read and make sure the traps outlined there don't exist in your case.

History, and historical comparisons, beyond the last 13 months are vastly overrated, and almost never worth the cost that data hangs around your neck.

There is always one exception to the rule. :) It can be of some value to take aggregated data about your visitors (especially those that converted) and put it into your corporate data warehouse where all other data of your company sits. This allows you to do strategic analysis of you web acquisitions in context of retail, call center, etc.

Not page level analysis type (that's tactical!) rather the cross channel purchases and returns etc (the real strategic kind).

Think really really hard before you buy the hype of web analytics data warehousing. They tend to be expensive multi year commitments that rarely deliver even nominal value not matter how much vendors and consultants hype them.

It is possible that you'll be the exception and build the first clickstream data warehouse where you'll deliver positive ROI (against the Total Cost of Ownership). But even if 110% of the signs point to that first make sure you have aggregated all the marginal gains.

It would be silly to not pick up the high ROI low cost stuff first right?

8. There is no magic bullet for multi-channel analytics.

The reason you have had a hard time finding a multi channel (online plus offline) analytics solution is….. it does not exist!

And here's the thing, it won't for quite some time. The problem is the missing primary keys, and we won't solve it in the near future.

Yet there are Vendors that blatantly say they provide a "comprehensive integrated multi channel solution" and imply that they can track every interaction across any channel and help you compute "true ROI".

It is a bunch of @#%^*

The best thing such solutions do is they sell you a campaign management solution for your offline marketing activities with some possibility of running those campaigns (think email) online as well. In the most optimistic scenario what you'll get is response rate from a mailer (postal) and a email campaign because the email campaigns were auto tagged.

That's it.

They won't help you understand impact of search on store sales, they won't help you understand impact of tv on your website (not without massive pain even after you buy the "comprehensive integrated multichannel solution"), they won't help you…. well a lot of things.

Be wary. Be very very way of these people/solutions.

Now make no mistake… measuring multi-channel impact (non-line marketing baby!) is critically important. You *should* do it.

But it is a long hard slog. It requires people, it demands begging many people in your company and agency to cooperate with you, it mandates building custom solutions, it needs lots of creative thinking. There is also a big payoff in the end, just no easy answers.

You'll need a portfolio strategy (from my book Web Analytics: An Hour A Day, Page 235):

Here are two blog posts that comprehensively outline why multi channel analytics is important, what the problems are and a portfolio of 11 solutions you can deploy:

Updated versions of the strategies outlined in above posts are in Web Analytics 2.0 (starting Page 368, in case you have the book).

9. Experiment, or die.

Let me beat this dead horse one more time. Sorry.

If you don't have a robust experimentation program in your company you are going to die.

It is just a matter of time.

[I know, I know, it seems like we have been through this so many times, and I also know that secretly you know how critical this is, sadly others stand in your way.]

In today's world there are so many questions that we can't answer with any degree of certainty (even with petabytes of data!). Here are some such questions…

1. How much cannibalization happens between paid and organic search for my brand keywords?

2. What is the online impact of my promotional flyers sent in postal mail?

3. What is the optimal price I should charge for my product to maximize profits?

4. Should I go for overwhelming, pungent, or just plain pukey for my home page design?

5. Should I show an Add To Cart link to our own ecommerce store or also to other places on the web people can buy the exact same product (often cheaper, so people buy a lot more of what they might not have bought at all)?

6. What is the impact of having a live twitter feed of all mentions on each product page of our website?

7. Will people from Ireland buy that?

Your imagination is the limitation in terms of hypotheses and "I wonder…" ideas that you come up with every day.

Yet Site Catalyst and Unica and Google Analytics and Indextoos stink at answering all of the above questions.

But if only you could answer any one or two of the above, it would dramatically alter how you do business online.

Oh and when I say Experimentation I don't mean testing button sizes (BOO!). I mean doing big important things that matter (every one in the list above, and more).

Start with something simple, try three different layouts of your home page, the product line page and the highest trafficked landing page. You are on your way to A/B testing. Progress points? 20.

Next move to changing two things at one time on your product description pages. That's multi-variate testing. Progress points 25.

Now you are ready for the kind of testing that is life changing: running controlled experiments! [Web Analytics 2.0: Pages 205 - 208.]

That's most of the tests above. They will help answer the almost unanswerable questions from cannibalization to multi channel impact to brand impact and more. Aim for this.

Hire at least one or two people dedicated to experimentation (not just a/b testing, or Google Website Optimizer / Test & Target) in your team if you are a Large company, and part of a person if you are medium sized.

If you want to truly being data driven, if you want to crush your competition, if you want to really win on the web, then all roads lead through robust experimentation.

10. The single most effective strategy to win over "stubborn single-minded" HiPPO's is to embarrass them.

Finally perhaps the bane of our existence, the magnificent HiPPO (the Highest Paid Person's Opinion).

Our beloved HiPPO's bring their entrenched mindsets and loud voices (in terms of power) and performance review writing authority to bless our projects, or more likely stand in the way of progress.

Often HiPPO's don't impede progress / change or crush valid opinions / suggestions because of malice. Sometimes they don't know this interweb thing as well as they should, sometimes they know things have worked a certain way forever and they are reluctant to try new things, and other times they are convinced that they are right (even when they are magnificently wrong).

Net net things are rarely as cute as this…

Here is what does not work when it comes to convincing HiPPO's:

1. Your opinion. Really, no one cares what you or I think (not that high in the organization).

2. Repeating yourself time and again.

3. Data puking (though we tend to thing as data persuasion).

Here is what does work with heavenly precision: embarrassment.

Their embarrassment.

You just have to be nuanced (to ensure you don't make the above three mistakes).

You two BFF's in the HiPPO's nuanced embarrassment:

1. Data about your competitors (and your performance against that data set)

2. The voice of your customers (and your awesomeness or suckiness that shines through that)

I only know a handful of HiPPO's that can resist having competitors crush them (especially results of their opinions that were actioned!). I know only a couple of HiPPO's who once made aware of will ignore the pain of customers.

Here are six specific strategies you can use to move even the heaviest of HiPPO's:

# 1: Implement a Experimentation & Testing Program.

# 2: Capture Voice of Customer. Surveys, Remote Usability, Etc.

# 3: Deploy the Benchmarks I Say, Deploy 'em Now!

# 4: Competitive Intelligence is Your New Best Friend.

# 5: Hijack a Friendly Website (/ Earn Your Right to be Heard).

# 6: If All Else Fails. . . . .

Please check out this blog post for additional details and examples for each recommendation: Lack Management Support or Buy-in? Embarrass Them!

Next time you see me don't complain about how your hands are tied and your boss is a pain or how you feel like the loneliest person in the world and no one understands you. Your destiny is in your hands, use the strategies above, go after your HiPPO (respectfully), and make change happen!

EOM. Phew!

If I could summarize the philosophy I have formed from a lifetime of bruised it would be this…

The only way to succeed in Web Analytics is to: Be agile. Be flexible. Move fast.

Decisions you make today based on data you have right now will have greater impact on your business, than decisions you can make in the future based on solutions you will implement over the next eighteen months with data that will be so perfect it is as if God is speaking to you.

Ok now it's your turn.

What do you think of the ten fundamental truths? Agree with 'em? Vehemently disagree? Got a #11 you would add? Perhaps not just #11 but #11 through 16? :) Please share your thoughts / feedback / criticism / love via comments.

It would be fabulous to hear from you.

[A Small Contest:]

My online learning startup Market Motive is holding a small contest to award scholarship for a Master Certification course ($3,500) in Web Analytics. The course starts on April 15th. Our goal is to give someone deserving an opportunity to become a Ninja.

If you think you could gain value from a three month structured course (with exams and quizzes!) then please contact me. Here are the rules… please e m a i l me the following…

1. A short (really short) paragraph on why you want the scholarship.
2. Pick a site you love and tell me three things you would change about it, and why.

That's it.

~~Please fit the whole thing in one page (6 sized font automatically disqualified! :)).~~

Contest close date: March 31st.

Thanks.
[/A Small Contest:]

10 Fundamental Web Analytics Truths: Embrace 'Em & Win Big is a post from: Occam's Razor by Avinash Kaushik

Five Sweet Web Analytics Resolutions To Kick It Up A Notch

Avinash Kaushik — Wed, 06 Jan 2010 09:13:37 +0000

The new year is such a wonderful time. Wonderful smells in the air. The world is full of hope. Unachievable things seem achievable and are being polished into shiny resolutions. World peace seems within grasp.

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