Google Website Optimizer is a very capable testing platform allowing you to setup complex multivariate experiments using a simple, intuitive interface. So what's the problem?

AVERAGES LIE

Simplicity, while being Website Optimizer's greatest strength, is also a tremendous weakness when it comes to data segmentation. Google Website Optimizer doesn't offer the data granularity that Google Analytics does.

In Website Optimizer all of your traffic, no matter how different the traffic source, is lumped together into a single bin. You might be sending traffic from paid search, organic, and content to the same page. When you view data for an experiment on the page, you'll see aggregate data across all traffic sources...

TEST RESULTS WILL DIFFER ACROSS TRAFFIC SOURCES

When we run a Website Optimizer test results at ROI, we manage our experiments just as you would expect - running a test until we have a winner within the Website Optimizer interface. However, when the test is completed, that's when things get interesting.

WHAT DOES A WIN REALLY LOOK LIKE?

We use Google Analytics to dive deep into our Website Optimizer test results, breaking up the test data by traffic source, campaign, ad group, and any other significant way we can segment traffic. When you view the results on campaign by campaign basis, things start to look a little different.

Here's an A/B test we recently ran for one of our clients testing a revamped headline on their paid search landing page:

Sweet - a 60% win overall! But our job isn't over yet...

When we break the test down campaign by campaign in Google Analytics, we can see that the new headline actually led to as much as a 40% decrease in conversion rate in some of our campaigns (Seeing A/B Experiments in Google Analytics). So what should you do about it?

ELIMINATE THE LOSSES

Well, the short answer is to segment your traffic. Typically, when people have a win in an A/B test they send all traffic to the winning page. When you do this, you understate your win.

Take the following example. We run a Website Optimizer test and find after a week of testing that Page B gets 100 more conversions then Page A. Accordingly, we send all traffic to Page B for a 6.45% improvement.

However, if you look closer at the data from our test, you'll see that Page A actually performed better than Page B in Campaign 2. If we optimize where we send our traffic, we can get an extra 50 conversions bumping our actual improvement up to 9.68%!

I GET IT, HOW SHOULD I SEGMENT MY TRAFFIC?

There are a number of different ways to send visitors from different traffic sources to different pages. By far the easiest method is simply update your destination URLs to point to an optimized page for each traffic source.

Really, it doesn't what method you choose to split your traffic to the appropriate page. Just make sure whatever system you go with is robust/manageable enough to handle ongoing testing.

If you're trying to get landing pages that really grab your visitors, there's one Google Analytics report you absolutely cannot live without. And guess what?

It's not Top Landing Pages.

Before I unveil the report that ROIers use to do quick landing page analysis, let's find out why we're not big fans of the built-in Top Landing Pages report:

It only shows entrances, bounces, and bounce rate
It doesn't tell us conversion data for our landing pages
It can't show the revenue generated by our landing pages

Thankfully, there is a way to get what we need for robust landing page analysis out of GA. Hit the jump to find out how.

The first method is the easiest. We just use an existing Google Analytics report, and segment by landing page. Just browse to Visitors > Map Overlay. Then use the dimension dropdown to select Landing Page:

Check it out:

Sure, Entrances and Visits aren't the same metric, but that's not really why I'm at this report. I'm here because I want to see how these landing pages stacked up when it came to getting visitors to sign up for my newsletter or buy my widgets. It wouldn't be the first time that I've seen a page with a higher bounce rate net me more cash than one with a slighter lower bounce rate.

So the Map Overlay report is fine and dandy, but you're probably wondering, "Why isn't he talking about Custom Reporting yet? Does he know there are Custom Reports now?"

Yes. He does. And you get a gold star, because this is a perfect case for why Custom Reports are awesome. If a built-in report isn't doing it for you, just build your own from scratch and start using the new one instead.

Here's a Custom Landing Pages Report:

Now you can compare everything you need. I've separated the Goal and Ecommerce data on separate tabs, but you can try and cram it all on one tab if you'd like. Add that bad boy to the Dashboard and you're good to go.

How do you like to check your landing page performance in Google Analytics? Leave a comment and let us know!

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 mov[…]

Everyone's new at some point right? Well if you're just starting out with Google Analytics, here are a few things you can watch out for to stay ahead of the game.

1. Missing Page Tags
Probably one of the most common mistakes that can cause problems in your Google Analytics data is missing page tags. Yes, the Google Analytics code needs to be on all pages of the site. It doesn't matter that someone in sales told you that "all we need are metrics from one or two pages." You're setting up Google Analytics already, so you might as well do it right and get accurate data. If any of your sites pages are missing the Google Analytics Tracking Code, you'll start seeing self referrals (where the real source information is overwritten with your site information) and a variety of other issues will occur as well. Comb through the site a few times and make sure you aren't skipping any pages and that every page will register with Google Analytics.

2. Mixing urchin.js and ga.js code
For those of you inheriting Google Analytics projects, you may be faced with the task of maintaining or updating a site that was previously tracked using the urchin.js version of the tracking code. Although Google states it is possible to use both the urchin and ga versions of the code as long as they aren't on the same page, my suggestion is to update the entire site to the new ga.js version of the tracking code. Mixing the two can cause some complications that are better left avoided. Save yourself some future headaches and update everything at once. Plus you'll get some cool new features with ga.js anyway, so why wouldn't you want to upgrade?

3. Not setting up ecommerce correctly
I've had numerous people come to me asking why they aren't seeing any ecommerce or revenue information within the Google Analytics reports. Aside from enabling ecommerce reporting in the Profile Settings, there is actually a separate script you'll need to setup on your site in order to get ecommerce working. Just grab the code and have your developers work their magic to get the dynamic transaction level variables passed into the ecommerce code for Google Analytics. Can't get all those fields? Read more about which variables are required and how to set up ecommerce.

4. Goal Conversion Setup
An important aspect of effectively using Google Analytics is to track the conversions that take place on your site. Aside from ecommerce you can set up goals within each profile to receive data on desired actions your visitors make on your site. I've seen some strange things when it comes to goal setups, but one of the most common is repeating the goal step in the funnel. After specifying the goal page, you don't need to repeat that step again in the funnel. Hopefully since Google added the "+ Yes, create a funnel for this goal" expandable selection this will help make this task a little clearer.

Also, be mindful of the match type you're selecting. Even with the helpful example next to the Goal URL field, I still see people that enter in the hostname in addition to the URI. If you're unsure about which match type you should use, the interface provides a link to an explanation of when you would each of the match types.

5. Campaign Tags Missing
If you're doing online (and even offline) marketing, you'll need to make sure you're tagging your URLs correctly in order to see metrics from those marketing efforts within Google Analytics. Typically by default in Google Analytics your paid traffic sources (with the exception of Adwords) will come in as a referral, so you must tag your URLs with the Google Analytics tagging parameters in order to see the correct referral information. To tag your URLs you can use our builder tool to generate the destination URL. By adding the necessary query parameters Google Analytics will attribute the visit information to the correct source. For Adwords users, just make sure Auto-tagging is enabled and Google will do the rest for you.

Tagging your URLs is also useful for other marketing efforts, like auto responder emails, offline campaigns, and banner ads. Without tagging your marketing efforts you'll be missing the opportunity to track the progress of your investments, so it's important that these steps are taken to get your Google Analytics data reporting accurately.

6. The Misuse of Filters
Filters can be applied to the information coming into your profiles to manipulate the final data in your reports. However, having an incorrect filter can severely impact the accuracy of your reports. When filtering out your office IP addresses make sure that you are using the correct regular expression. When creating include and exclude filters think carefully about what you're including and excluding. Include filters act as include only filters and will only include the information you specify into your reports. If your reports suddenly drop off and no changes were made to the site, check the filters that are set up on the profile to see if you are accidentally excluding your traffic. Carefully monitor any new filters because once the data has been manipulated (correctly or incorrectly) there's no going back.

7. Improper setup for subdomains and multiple domains.
Take a closer look at your site structure when you're setting up Google Analytics. Do you have any subdomains? Does the visitor ever cross over to another domain while browsing the site? Although this topic can be fairly advanced, tracking subdomains and multiple domains is arguably the most common mistake made by anyone setting up Google Analytics on their site. Check out the Google help files for instructions on setting up your Google Analytics Tracking Code to work with subdomains and for multiple domains to make sure you're getting it right.

 


Google Analytics is undoubtedly the most widely used web analytics application. Emerged from and based upon the analytics-package developed by Urchin Software Corporation (which was bought by Google in April 2005), the tool has become publicly available for free under the new flagship of Google Analytics. In May 2007 the application was heavily edited, developed and released; the design was simplified and more advanced featured were added. Over years Google Analytics managed to gain on popularity because of its simplicity and many advanced features for curious site owners and professional marketers.

You probably use Google Analytics on a regular basis, for basic stats tracking the performance of your site. And, just like most GA users, you probably very rarely venture far from the comfort of the reports shown on the dashboard. That’s all the analytical information you need, you may be thinking … or is it?

Did you know that Google Analytics can generate up to 85 different reports that will help you analyze all possible data about your website traffic. It not only tracks visitors to your site or the number of page views, it can be used to see which content gets the most visits, time on site per visit, which ads are driving the most visitors to your site, it track the performances of your marketing campaigns, including AdWords, Adsense and emails and much, much more.

This post is not a be-all-and-end-all look at GA, but a rough guide to its many under-used features and reports. It is an easy to read guide that will help you understand and use the full power of Google Analytics. Honestly, it’s not that daunting.

General resources: Google Analytics Help Center, official forum and official blog.

You may be interested in the following related posts:

Perform Better With AdSense: The Ultimate Round-Up

The GA Tracking Code
Google Analytics will only track pages that contain the Google Analytics tracking code, this is a small Javascript snippet that needs to be added to each page of your site, either manually or through the use of plugins or tool. You will find some tools and plugins to help you do this near the bottom of this post.

For a static webpage or if you want to manually install the code into your pages, copy and paste the code segment into the bottom of your content, immediately before the body tag of each page that you wish to track.

To access your tracking code

Sign in to Google Analytics.
From the Analytics Settings page, find the profile for which you would like to retrieve the tracking code. Please note that tracking code is profile-specific.
From that profile’s Settings column, click Edit.
At the top right of the Main Website Profile Information box, click Check Status.
Your tracking code can be copied and pasted from the text box in the Instructions for adding tracking section.

The Dashboard and Analytical Reports
Log into Google Analytics and you’ll arrive at dashboard, the central hub that gives you an overview of all the popular reports (visitors, content, traffic sources and the cool map overlay) generated by Google Analytics. You can customize this page by changing what reports are shown, as well as dragging and dropping the reports into a format that suits your needs.

Google Analytics Interface TutorialA brief overview of how to use the Google Analytics interface. If you are new to Google Analytics or you’d like to pick up a few tips on how to use some of the different features, this video is a good place to start.

Interpreting Reports

Google offers comprehensive tutorials and guides to using Analytics, in the form of a series of Adobe Breeze Presentations. Below you will find the guides and presentations to understanding and using the reports generated by GA.

Guidelines to interpreting GA ReportsIn this presentation you will learn the best practices for analyzing data, how to analyze data trends and how to use the data visualizations in Google Analytics.

Pageviews, Visits, and VisitorsLearn where to find Pageviews, Visits, and Visitors metrics, how Pageviews, Visits, and Visitors are calculated, the difference between Pageviews and Unique Pageviews and the difference between Absolute Unique Visitors and New vs. Returning Visitors.

Time MetricsHow Time on Page and Time on Site are calculated, how Avg. Time on Page and Avg. Time on Site are calculated and learn about the Length of Visit report from this presentation.

Traffic SourcesLearn about the different kinds of traffic sources, how to identify quality traffic, how to identify revenue and conversion drivers, what kinds of information to look for in keyword reports, how campaign attribution works in Google Analytics

Content ReportsHow to use and interpret the Top Content, Content by Title, and Content Drilldown reports; how to use the Top Landing Pages report; how to use and interpret the Navigation Summary report; how to use and interpret the Entrance Paths report.

Analyze Traffic Sources, Content, and NavigationUse your Google Traffic Sources, Content, and Navigation reports effectively. In this video you will see the different sources of traffic, tracking content performance and analyzing visitor navigation.

Analytics and Flash and Flex Content
One of the most common Google Analytic implementation challenges has been tracking Flash content. In the past, Flash tracking was not provided out of the box, and every implementation had to be tailored to each individual site, developers who tracked Flash had to create their own processes to get it working.

Google now provides easy to implement tracking libraries for both Flash and Flex, the libraries include: Flash visual component, Flash AS3 library, Flex MXML component and Flex AS3 library.
Download: Flash and Flex Analytics Tracking Libraries.
Documentation: Developer Documentation.

Learn how easy it is to track Flash content using the new Google Analytics Tracking For Adobe Flash.

Analytics and Ecommerce
After you have enabled ecommerce transactions, Google Analytics will generate very detailed reports about every single transaction

Tracking Ecommerce with Google AnalyticsBy using Google Analytics with your Ecommerce website, you can gain valuable insights about your transactions, ROI, and customers.

Step-by-Step to enabling Ecommerce Reporting
The first step of tracking ecommerce transactions is to enable e-commerce reporting for your website’s profile.

Log in to your account.
Click Edit next to the profile you’d like to enable.
On the Profile Settings page, click edit next to Main Website Profile Information.
Change the E-Commerce Website radio button from No to Yes.

Analytical Goals
As a simplified explanation, Goals are only a page view, nothing complicated about that. If you define a goal in Google Analytics, you are telling it what page view constitutes the completion of a Goal, and Analytics then tracks it. It is an easier way to generate the reports that you need as well as a great way to measure your business objectives.

How to create Google Analytics Conversion GoalsIn this video you will be shown how to create conversion goals in Google Analytics.

Step-by-Step to setting up Goals in Analytics

Log in to your Google Analytics account at https://www.google.com/analytics/.
Select the account that contains the profile you’ll be creating goals in from the Overview page.
Find the profile for which you will be creating goals, and click ‘Edit’ under the ‘Actions’ column.

Under the ‘Conversion Goals and Funnel’ section, select one of the four goal slots available for that profile and click ‘Edit.’
Turn the goal ‘On’ or ‘Off.’ If you choose ‘On,’ that means you want Google Analytics should track this conversion goal at this time. Since there are no ways of deleting goals, turning it ‘Off’ can make the goal inactive.
Select from one of the three match types that Google Analytics uses to identify the goal.
Enter the Request URI in the Goal URL box. Reaching this page marks a successful conversion. For example, a registration confirmation page, a checkout complete page, or a thank you page.
Enter the ‘Goal name’ as it should appear in your Google Analytics account.
If your goal URL is case sensitive, this means your goal URLs are capitalized exactly like the visited goal URLs.
Enter the ‘Goal value.’

10 Must Track Google Analytics GoalsThe author of this article gives you 10 ideas for using Analytics Goals. He advises to setup goals for visitor comments on your blogs, social bookmarking actions, newsletter subscriptions, track feed subscriptions… and much more.

Import your Google Analytics Goals into AdWords and use them with Conversion OptimizerIn order to track your ROI from AdWords, you need to be able to see which keywords, ads and campaigns lead to conversions on your site. If you use Google Analytics, you can now import your Google Analytics Goals and Transactions into your AdWords account to use as conversion actions. This lets you track the ROI from your AdWords campaigns directly inside the AdWords interface.

Custom Reporting
Custom reports in Analytics give faster access to the information you need and less data reports to sift through. Simply, they remove the data that is relevant to you, leaving you with the bare bones reports that you need. You choose the information and metrics you want to see, organized in the way you want to see it.

Quick Start Guide to Custom Reporting
If you are stepping into custom reporting you should really read this official guide, from Google Support. You’ll learn to get from conceptualizing your custom report to actually building it, and will give you a basic insight into concepts and terminology involved in analytics and custom reporting. Check out also Quick Start Guide for Custom Reporting and Google Analytics Glossary

Custom Reporting in Analytics VideoLearn how to create custom reports in Google Analytics that show the inf[…]

It is such a cliché: Don’t just present data, tell a story.
Yet it is rarely followed.
We almost always present data.
Actually we don’t present data, we send out reports. With data. Lots of it. With 6 size font and some pies and stacked bar graphs thrown in.
Then we are frustrated that no one seems to pat us on the back, sing songs in our glory, give us more money.
We don’t truly tell stories because it seems like a lot of work. And it can be. But you’ll be surprised at how often it is simply a matter of framing things differently, letting your imagination roam free.
Last month I had to present to a group of executives in New York. One of the key things I wanted to communicate was the power of not doing random advertising but rather using freely available data to target the advertising on sites where relevant audiences exist.
Goals Summary:
1. Show the power of free tools available. [Google's Ad Planner specifically.] 2. Highlight the importance spending money on advertising to relevant audiences. 3. Tell a memorable story.

Below is how I did it. . . . hopefully it will inspire you to look for stories in your data, stories that will hold interest and might even get you some smiles (and you know that a raise is not far behind!).
My first step was to try and tap into current events / pop culture. That calls for some research. I use Google Insights for Search as the best way to get a pulse on what people find interesting.
Specifically what I often do is run this query: Who are the most popular celebrities in New York in the last 30 days?

Turns out it is someone called Kim Kardashian. It also turns out I have no idea who this person is, an unfortunate side effect of not have time to watch television.
Quick Google search and I am caught up on why Ms. Kardashian is “famous”. She has some overlap with Paris Hilton in terms of the path to fame.
The key ingredient for any story is to have interesting protagonists. For this story due to their popularity it will be Ms. Hilton and Ms. Kardashian.
The plot: Your business has a need to market something related to Ms. Hilton and Ms. Kardashian, a perfume or a clothing line or a cd/dvd. Amongst other things you’ll want to make use of display advertising (banners / widgets etc).
How do you figure out who the right audience is, and where you’ll find them? As opposed to of course buying the main banner spot on www.yahoo.com were your ad might be a hit or a miss.
Tools for doing audience segmentation were quite expensive until recently. Google’s Ad Planner is free and makes this valuable data democratic. You can segment by demographic (age, education, income, gender etc) and psychographic (Extreme Sports Fan, Film Buffs, Fantasy/Comic Book Readers etc) data.
Perhaps its most cool feature is the marriage between all the above data with Google’s search data.
That’s where the analysis starts.
Question: What are the websites that are visited by people who have searched for the keywords “paris hilton” and “kim kardashian”?
Here’s the answer:

[Click on the image for a higher resolution version.]
Notice the I have typed the keywords on the bottom left. In the right frame are the sites that are visited by those who searched for those two terms. Some obvious sites, many surprises (good thing, now we know!).
I have a habit of sorting by Comp Index, just to check out concentration of the audience. For example a comp index of 990 means that you are approximately nine time as likely to find the same audience (paris, kim searchers) on wallpaperbase.com.
If you look at the higher resolution version (click on the image) you’ll easily find out how many page views are on the target site, what kind of advertising they accept, ad impressions/day and other data you need to create a media plan.
So far so good.
I have always believed that Men are more interested in the kinds of stories and “entertainment” value that Ms. Hilton and Ms. Kardashian generate.
The nice thing is I can validate that hypothesis. I simply open the Gender option in the left panel and choose Male.

You are looking at the top part of the segmentation panel. Notice the delta between UV (users) between the overall segment and just the Males.
Turns out I was not totally right. Males make up a bit less than half of the audience.
No worries. They are still a lot bigger than what many people think (and it is wrong to think it is overwhelmingly female).
My next believe, perhaps controversial, is that older males are more interested in Ms. Hilton and Ms. Kardashian than younger males. Now this seems odd because Ms. Hilton and Ms. Kardashian seem to be more cool and hip and more of a young generation cup of tea.
Well we can test my hypothesis, in addition to Gender I can also choose Age. . .

This data is still just for people, in this case Males, who searched for the key words paris hilton and kim kardashian.
It might have been a odd thing to say but it seems that 45 and older males are a lot more interested in Ms. Hilton and Ms. Kardashian. By almost two to one.
Surprised?
: )
Let’s prep for the punch line of this story.
I have identified a audience that is of value to my goal, marketing Ms. Hilton and Ms. Kardashian (or things connected to them).
I want to target the top end of this audience, Males 55 and older, how many of them are there and where can I find them (to ensure my advertising will be relevant for this audience and my ad dollars are spent wisely)?
Here you go. . .

[Please click on the image for a higher resolution version.]
How about now… surprised?
I was.
The top sites listed for this audience (older Males interested in Ms. Hilton and Ms. Kardashian) turns out to be bedrock sites, typically, for Republicans and the Conservative movement! Starting with a Comp Index of 1700 for impactguns.com. Other sites: weeklystandard.com, rushlimbaugh.com, nationalreview.com, worldnetdaily.com, and townhall.com.
Not in my wildest dreams would have I have expected that this audience would be so highly correlated with actual searches done for Ms. Hilton and Ms. Kardashian. It seems odd with the conservative moral values espoused.
Very Important: I am not judging them. To each unto his / her own.
For my marketing campaign one more valuable nugget of insight is in th above data (click above for higher resolution). Turns out they are also very rich. Note the prominent appearance of morningstar.com, pgatour.com, seekingalpha.com and ft.com.
So a bumper crop: right audience, lots of money to spend. That’s hot!
Now I have to go execute the campaign and I know where to target my ads, how many impressions/day I can expect and how many people I can hope to target.
Relevant audiences change with seasons, hot trends, shifting preferences. Repeat the analysis to ensure you have the most current data.
End of story.
Closing Thoughts:
Turns out this was a very effective story to tell, most people in the room were media buyers (especially offline).
They were impressed with the kind of data we have online, and how easily accessible it was.
They will never forget how wrong one can be about who the relevant audience might be (it would be impossible to guess the Weekly Standard, Rush Limbaugh audience might have any interest in Ms. Hilton or Ms. Kardashian).
Data Wins.
Ok its your turn now.
When you present data how do you tell your stories? How easy or hard is it? Got a favorite story to share with us?
What did you think of the above story? Methodology or conclusions? What did you link? What did I miss?
I would love to hear from you. Thanks much.
PS: Couple other related posts you might find interesting:
Make Your Web Analysis / Reports “Connectable”Competitive Intelligence Analysis: Google Ad PlannerCompetitive Intelligence Analysis: Google Insights for SearchParis Hilton, Kim Kardashian & Telling Stories With Data is a post from: Occam's Razor by Avinash Kaushik