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Q&A With Avinash Kaushik, Google Analytics Evangelist & Customer Insight Guru

Daniel Waisberg — Fri, 20 Nov 2009 22:56:55 +0000

You’re the analytics evangelist for Google. Doesn’t every marketer understand the importance of analytics? With hundreds of thousands or perhaps millions using Google Analytics, why would Google need an evangelist, and what do you see as the most important part of your job?

Numbers are hard to come by on this but in my humble experience a tiny fraction of people who should use data productively access it, and a tiny fraction of that actually end up using data effectively. We, as a universe, have a long way to go.

My role at Google is in two parts. In the inward facing part I am the “customer evangelist” as I help shape the vision, direction and features of 13 different Google tools that provide data to customers. In the outward facing role I help the top xx Google customers to leverage data more effectively.

The most important part of my role is that I am a small part of larger effort to create a data democracy in the online world.

All of the above is distinct from my role as a blogger (evangelizing the use of data in web decision making) and as the co-founder of MarketMotive (providing latest online marketing education and certification).

Avinash, following your first book, Web Analytics: An Hour a Day, what drove you to write your second book, Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity? Did the field change so much since the first book?

The world indeed has changed a lot in two years, especially in three areas: user centric design, competitive intelligence and social media. There are a raft of new and delicious options that simply did not exist when I wrote the first book.

But the primary impetus behind writing the book was to address challenges that we all now face, challenges that present new opportunities (to engage and influence current and future customers) and how to measure success is a complex ever evolving ecosystem.

An example of that last point is in Chapter 9, if you see Figure 9.04. It makes you stand back and marvel at how we are measuring anything at all!

Even in a “standard” area like paid search analytics there has been so much evolution in the last couple years, analytics of which are covered in the new book.

Do you see both books as an evolution? I mean, would you recommend readers start with the first and then go to the newest one?

It is definitely an evolution.

People who have read the first book should feel that the second book is an immediate step up to a more evolved way of thinking about analytics, from the classic Trinity to the new Web Analytics 2.0. With each chapter there is a new way of thinking about what we already know and assumed. The second half of the book is where all the delicious stuff is that will help you change the game—it covers analytical techniques, social media analysis, competitive intelligence, new ucd approaches and of course things like multi-touch campaign attribution analysis.

If you want to start with the basic and take a gradual course then I recommend Web Analytics: An Hour A Day, but if you are willing to be a bit brave then Web Analytics 2.0 will get you to the goal faster.

I did want to point out that both the book are written for marketers, executives and analysts. You don’t need particular deep technical knowledge to become a analysis ninja.

Can you describe in a few words what is the main philosophy behind the book, the concept of Web Analytics 2.0?

Here is my definition of Web Analytics 2.0.

It is: the analysis of qualitative and quantitative data from your website and the competition, to drive a continual improvement of the online experience of your customers and prospects, which translates into your desired outcomes (online and offline).

Put simply, it is the art and science behind making intelligent decisions about all you do online—as a company, blogger, non-profit.

One sentence in particular caught my attention: “We’ve evolved from hits to page views to visits. Now we have outcomes.” Can you elaborate on that?

I have become convinced that more of the online world is not data driven because we have been reporting “silly metrics.” By that I mean hits and visits and page views and even visitors. What is the point of all those metrics?

They are all “aggregate” metrics that simply tell you “consumption”.

What they don’t do is answer this question: “What the hell happened?”

That question is important to answer because that is what matters to every senior decision maker, people who cut checks, people who will promote you and me.

Hence my near paranoid focus on first measuring outcomes—what happened as a result of all those people showing up? Did we make money? Are more people coming to my protest against cutting redwood trees tomorrow? Am I wasting my time marketing on twitter? What was the point of using video to sell micro-chips to B2B customers of Texas Instruments? So on and so forth.

God will welcome into sweet heaven people who focus on measuring outcomes. Because outcomes help businesses and people get better each day.

Your book has a lot of great advice for big companies trying to understand how their customers interact with their websites. But if I work for a Small-Medium Business, with a very limited budget, how can I go about implement this strategy? Any advice on whether search marketers should hire skilled web analysts or outsource the job to experts?

The book should be useful to businesses of any size. Throughout the book there are recommendations where to start and what to do first or what tools to use. For example on Page 13 it tells you that if you are a small biz then you must do x first, then y and then z and don’t worry about a and b. Or in Chapter 10 The Ladder to Analytics Nirvana gives a very specific road map for someone who is small to someone who is big. Same thing with Paid Search, Chapter 4 has the basic to medium stuff in terms of what to analyze for higher ROI and Chapter 11 is where all the juicy complex “I am going to be awesome” advanced stuff is.

My hope was to always provide a shallow end of the pool so everyone can get in, then those who want to do more can slowly, with confidence, move to the deeper part.

In terms of hiring… it would depend on your budgets and in-house sophistication. I have come to believe that if you don’t know what you are doing it is best to hire a consultant and put them on a “profitability plan” (i.e. you do the work I don’t know and we’ll both share the profit—not just hourly rates). Over time as your budgets increase, you become a medium sized biz, it is prudent to bring it all in.

Another interesting subject you deal with in the book is the web analytics career. What do I need to succeed as a web analyst? And if my main focus is on SEM, how can your book help me succeed?

You need to loooooove the web and all the glory and all the possibilities. If you don’t have passion for this medium there is no way you can put up with the work that is required.

Other main skills I look for: Initiative. Curiosity. An aptitude for data. Statistics 101. Self taught.

If your focus is on search then first Chapter 13 will help you plan your career effectively and help you create your own path for success. But most of all I am sure at some level we all understand that Search is not everything, certainly not paid search. The book will help you understand how the broad portfolio of online marketing works and of course how to be king by being data driven.

In the end it should make you a more rounded individual, and thus, I hope, a more marketable person in the job market.

You’re well known for the 10/90 rule. Why do you think it’s more important to put the emphasis on people rather than technology? How much is enough? How do you set reasonable goals and know whether you’ve achieved them, or to put your head down and try, try again?

Here is the picture that illustrates my concept of Multiplicity:

What it shows is the breadth and depth of the tools that are required to answer the four important questions: What, How Much, Why and What Else.

Even a few years ago for you to get access to tools would have required you to spend a lot of money, that’s not the case any more. Clickstream? Surveys? Competitive intelligence? A/B or multivariate testing? You got it, every single one has a 95% world class tool available for free.

So having tools (access to data) is no longer the key differentiator between companies, large or small. Having the brains to actually make sense of it all, look to the right tool to get the right answer, be able to actually analyze the data and not just data puke is not cheap. That’s where humans come in, that’s where the strategic differentiator comes in.

I had created the 10/90 rule almost five years ago when I was at Intuit. Never in my wildest dreams did I think it would actually be practical, but it is now. Every company in the world should not shoot for 10/90 (10 tools and 90 in people), experiment and find your balance. I think many people start with 10/90 and in a few years might morph to 35/65. No worries as long as you can so ROI impact.

But I have to admit, if you are not egregiously overloaded in the big brains (internal hires or consultants) you don’t stand a chance.

There’s a lot of buzz around attribution modeling, knowing the “value” of certain clicks to the overall conversion process. Is it important to know whether the last click was the major influence on a conversion, or will analytics packages increasingly try to understand the various steps in the overall buying funnel? If so, how?

This is the only question on which I’ll bow out from answering, it is complex and I think the reason we are in the soup we are is we look for shortcut quick answers. There are none. Of course I absolutely apply critical thinking to this in the book and provide answers.

Analytics systems are notorious for delivering vastly different interpretations of seemingly simple data—how users interact with a site. Why aren’t there more standards, and why are the reports from different vendors so different?

This is like asking a four year old boy how come he is so lame that he does not already exhibit the mannerisms and sophistication of a fully grown man.

Our industry is a baby, it is in a growth spurt, we must be patient and let things evolve. And they will.

Complete side note: It is utterly futile to wait for perfect data to make decisions and / or spend time comparing numbers between Omniture and WebTrends. What is the point of it? So we are more comfortable that one piece of data is 5% better than the other? Pause and think for 60 seconds how tv ratings are measured. It will horrify you how the data is collected and subsequently used for multi million dollar decisions. On its worst day the worst third party cookie based tool gives better and more accountable data for Marketing spend online. I personally don’t recommend wasting time trying to get the last 5% accuracy, simply not worth it. Implement tools correctly and completely. Don’t worry about the wife you just divorced. Worry about the one you just married and make a happy life with her.

Thanks so much for the opportunity to do this interview.

Thank you for spending the time to map your most interesting views of this subject, Avinash.

Editor’s note: Want to know more about Avinash’s new book, Web Analytics 2.0? He’s written a short overview of the book in this blog post. You can also buy the book through this affiliate link with Amazon and Avinash will donate 100% of the proceeds to two charities, the The Smile Train and Ekal Vidyalaya.

Behavioral Targeting: Creating A Unique Experience For Each Visitor

Daniel Waisberg — Wed, 18 Nov 2009 05:07:57 +0000

Behavioral targeting (BT) has been the buzzword of the year for the last two years in the web analytics field. But is BT really all that important and valuable to the companies making use of it? The answer is usually yes. And does it take a team of PhDs to implement BT for a website? The answer is usually no. In this and a following post I will explain the value that behavioral targeting offers, and show how a marketer can make use of BT to make the website experience richer for users, and increase conversion rates.

According to Wikipedia, there are two principal types of behavioral targeting:

Onsite behavioral targeting is a technique that uses visitor behavior to target certain content that is proved to be more relevant to a segment of visitors. It should be preceded by an encompassing analysis of users and their characteristics (using web analytics tools). We can either define hard rules (for example, offer a special deal to anybody that adds any two or more products to a shopping cart) or use an engine to dynamically learn about and then target high-converting groups.

Offsite behavioral targeting is technique used by advertising networks to increase advertisement targeting. For example, Google is using this type of targeting to profile visitors to their website network according to subjects they like (their “interests) and then uses this info to provide users with targeted ads across the entire content network.

In this article I’ll focus on the first type of BT, onsite behavioral targeting, the type of technique used by website owners to improve user experience by delivering the right content to each person. Companies that current provide such a solution to website owners are:

From tracking to behavioral targeting

Web analytics has been constantly developing since the 1990s. In the beginning there was data, and initially the struggle was to collect it accurately and provide reports on the state of websites, usually from an IT perspective. Then, with the turn of the millennium, analysts felt the necessity to turn numbers into insights, and the field evolved from simple data reporting to analysis. Today, marketers increasingly understand that testing is the way to go when it comes to design and implementation of websites (in other words, intuition-based decisions don’t really work well). Said another way, the customer should decide what works and what doesn’t (this phase is still rapidly evolving).

In the last two years, marketers, analysts and executives have started to understand that customers should get what they want without having to ask for it. That’s what behavioral targeting is all about: delivering the right content to each visitor to a website. It moves the current focus on overall results to segment results. It enables the website owner to understand which visitors are struggling and which are succeeding with their objectives. It helps marketers build more relevant campaigns to target the right market, be it through search, content, media, or emails. These insights and actions should not come at the expense of website testing, but in addition to it. Testing is very important to recognize the low hanging fruit that is ready to be plucked. It is also a great way to persuade management of the importance of investing in both testing and targeting.

Analytics guru Jim Sterne defined the benefits of behavioral targeting as follows:

“We can attract prospects with customized campaigns according to their interests, engage site visitors with dynamic content in response to their conduct and desires, and put the right message in front of the right person at the right time. We can create a more pleasant and more individual buying experience. We can quickly identify the offers that will more likely convert those prospects to buyers.”

However, the market is still not completely ready for this revolution. Recent research from eMarketer suggests that American internet users are not very fond of behavioral targeting techniques. As seen in the chart below, one of the conclusions of the research is that “respondents showed somewhat more interest in receiving personalized discounts and news, but still, less than one-half of Americans wanted any tailored Web content at all.”

Concluding, we can see a strong trend towards using behavioral targeting to provide web users with richer web experiences. But this will require a market education effort so that users don’t perceive companies using these techniques as not respecting user privacy.

In my next article I will go over a few examples showing how to implement behavioral targeting and analyze its results to increase website conversion rates.

Google Analytics New Features: Intelligence Engine, Custom Alerts & More

Daniel Waisberg — Tue, 20 Oct 2009 18:01:22 +0000

Google has just announced a number of new features for Google Analytics, including more powerful reporting capabilities, greater customization options and a new “intelligence engine” that Google says can help search marketers drive smarter data insights. Here’s a rundown of the new features, and why they’re important.

Analytics intelligence

Google Analytics new “intelligence engine” comes with default alerts that will show you interesting trends in the data: it surfaces insights. Exactly how the algorithm that does this works is not clear, but it certainly takes into consideration many variables, in a very Googly manner. This can be a great way to start your day looking for insights—a kind of a conversation initiator for web analysts.

As we can see in the screenshot, Google did not let us down when it comes to design and UI. The interface is very intuitive and lets the analyst move through new alerts quickly.

Some really interesting things you can do:

Define your alert sensitivity. This controls the number of automatic alerts that will be triggered to appear in the Intelligence report page. As Google explains, “a higher significance rating is assigned as the difference between the actual performance increases with the expected performance.”

Create advanced segments based on alerts. On the right column of each alert you will see a link to create a segment. This is highly useful, since through alerts you might discover high converting segments that should be tracked separately, so Google makes this segment only one click away.

Change grouping method. This is very handy if you prefer to look at the data grouped by metrics or by dimensions. It’s a very useful way to change the data arrangement.

Creating custom alerts

Creating alerts is a very effective way to track visitor segments that are specially interesting to you. Let’s say you run a banner campaign to bring people into the website. How can you decide when to stop the campaign? Now you can use alerts to have an email delivered to you once your campaign bounce rate increases by 10% compared to the same day in the previous week. This is valuable because the website visitors (where the banner is shown) might get used to it, meaning that you reached those users that were high probability prospects. The option to compare to the same day in the previous week is a very good addition since it accounts for weekly variability.

For help on how to create custom report you can visit this help article

Other new features

In addition to the intelligence engine and the ability to create custom alerts, Google has also enhanced Google Analytics with the following new features, according to this Google Analytics blog post:

Expanded goals & site engagement goals. Two new goal types allow you to measure user engagement and branding success on your site. The new goal types allow you to set thresholds for Time on Site and Pages per Visit. Furthermore, you can now define up to 20 goals per profile.

Expanded mobile reporting. Google Analytics now tracks mobile applications built for iPhone and Android devices. Mobile app developers can understand how users engage with their mobile apps, such as what actions are taken within an app and what features are used. In addition, for customers with a mobile website, Google Analytics can now track traffic to mobile sites from all web-enabled devices whether or not the device runs JavaScript.

Advanced analysis features (incl. advanced table filtering). Google Analytics provides an arsenal of power tools you can use to perform in-depth, on the fly analysis without having to export your data to spreadsheet tools. Using Secondary Dimensions, you can view multiple levels and combinations of data side by side instead of having to drill down into each level. You can then use the Pivoting feature to cross-tabulate two different metrics with two different dimensions.

Multiple custom variables. Custom Variables gives power-users the flexibility to customize Google Analytics tracking to collect the unique site data most important to their business. With this feature, users can classify any number of interactions on the site into trackable segments.

Despite all of these great new features, we will still be dependent on human beings to analyze and take action on the data. Even Google Analytics evangelist Avinash Kaushik has written about his 10/90 rule, which says that just 10% of web analytics relates to tools, while 90% of both cost and success has to do with humans who analyze data and make recommendations for change based on their insights.

Landing Page Testing: Choosing Between A/B Or Multivariate Approaches

Daniel Waisberg — Wed, 14 Oct 2009 19:21:01 +0000

In a previous post, I wrote about how to get started with website testing, both choosing which pages to test and how to define which elements will contribute the most to profits. However, there are quite a few testing methods to choose from. In this post I will delve into the two most common testing methods: A/B tests and multivariate tests (MVT). What is the difference between them? How can you choose which one best fits your needs?

Below is a comparison between the testing techniques mentioned, taking into consideration the overall use of the testing technique, coding needs, design needs, granularity of results and other considerations.

Most testing tools provide these options, but since Google Website Optimizer is a free tool that provides both options, it is a good place to start and try the examples I provide below.

A/B Test

An A/B test is the most common and easiest type of landing page test to conduct. It consists of creating alternative pages for a specific page and showing each of them to a certain percentage of visitors. For example, if you create 4 different variations of a landing page, 20% of visitors to the website will see each version (4 variations + original). Cookies are used to maintain a consistent user experience—if a visitor sees one version, they will see it again and again when visiting the website as long as the cookies are not deleted. Below is a representation of how this technique works.

Image created by Yam Designs. For a high res version of the image go to A/B test scheme.

To implement the test with Google Website Optimizer, scripts need to be included on the pages to be tested. These include:

Two JavaScript codes on the original page: one that performs a redirect to the additional variations (head of the page) and one that measures the number of times the page was seen (this can be placed anywhere below the redirect code).
One JavaScript code on each variation page to measure the number of visitors viewing each page.
One JavaScript code on the conversion page to measure which visitors converted; this will measure the success of each page variation.

Advantages of A/B tests

Design freedom. A/B tests are often used to experiment page design options that vary dramatically, including position of text and pictures, background colors, number of pictures on the page, use of icons and navigation structure. Implementing such tests using the multivariate technique is possible, but it is technically challenging (but if you really want to do it, and you are technically savvy, see this post on the Google Website Optimizer Tricks blog.

Less JavaScript coding. as described above, the codes necessary to implement an A/B test are very simple and can be added to the website in a matter of minutes.

Faster results. A/B tests usually involve fewer combinations with more extreme changes; multivariate tests involve many more combinations and variations. In addition, since A/Bs show significantly different designs, the expected improvement of the page is usually higher, diminishing the time the test will run.

Multivariate test

Rather than testing different versions of web pages, as we do with A/B tests, Multivariate tests experiment with elements inside one specific page (for purists, we are referring to full factorial experiments, which is the method used by most testing tools). Basically, we define elements inside a page (e.g. a picture, a text or a button) and provide different alternatives of each element. The testing tool will show each element combined with all other elements to visitors. The resulting combinations are derived from the number of elements multiplied by the number of element variations. Just as with A/B testing, however, each visitor sees only one particular combination of elements regardless of how many times they view a page. Below is a representation of how this technique works.

Image created by Yam Designs. For a high res version of the image go to Multivariate test scheme.

In terms of coding, the programming a multivariate test is slightly more complex than a simpler A/B test. A few pieces of JavaScript code need to be implemented: one opening the test, one for each tested element and one closing the test. In addition, a JavaScript will be added to the conversion page to measure combination success.

Advantages of multivariate tests

Granularity of results. Since it is a full factorial experiment, multivariate tests show which elements are the best performing separately, as well as the correlation between the elements. This can be very useful when projecting the results to other parts of the website.

No redirects required. Since all elements tested are inside the page, there is no need to redirect from the original page to the tested pages. Although redirects can be performed smoothly, I believe it is better not to use them whenever possible, as they can slow the flow and affect user experience.

Fewer design resources required. Since we will be testing different designs with existing elements on a page, this will not require too much design effort.

Concluding, both types of testing have their own advantages and disadvantages. Each can be a perfect technique, depending on the needs of the website. They should always go hand-in-hand, using one to test completely different designs and the other to optimize the current design. The important thing is to understand that testing is not a one-time effort It is an ongoing exercise that should be part of the mindset of an organization. As Avinash Kaushik once wrote in his blog, Experiment or go home!

A Primer On Website Testing

Daniel Waisberg — Sat, 19 Sep 2009 21:08:30 +0000

Search marketers can learn a lot from scientists. Scientists spend their life testing things, one after the other, incessantly trying to discover new interactions between atoms, molecules, viruses, bacteria, etc. One of the greatest scientists of all time, Albert Einstein, said, “A theory is something nobody believes, except the person who made it. An experiment is something everybody believes, except the person who made it.” Want everyone to believe in your website? “Experiment” with it—in other words, test it and tune it for optimal performance.

Websites are laboratories, not sculptures

This is the first principle when it comes to website optimization. People tend to think of their websites as a finished product, which was built taking into consideration customer needs and stakeholders requests. But isn’t the world changing? Isn’t it important to tap into new markets, new customers, new opportunities? Isn’t it always good to improve conversion rates?

The website should not exist solely to serve the needs and desires of the designer or the CEO of a company. It should serve the purpose of the customer; otherwise the CEO will be the only one visiting the website in the long run. In a recent two-part paper I wrote with Avinash Kaushik we propose a framework for Web Analytics 2.0: Empowering Customer Centricity (full pdf of Part II, to be published on Vol. 2 Issue 2 of SEMJ). We write about the benefits and best practices when it comes to testing. We believe that “the web analyst must try endlessly and learn to be wrong quickly; learn to test everything and understand that the customer should choose, not the designer or the website manager.”

How to choose a page to test?

With hundreds, thousands, or even millions of pages, how should you decide where to start? Which page, if tested, will bring the biggest increase in revenues? A good way to start is to perform a motion charts analysis on the Top Content report on Google Analytics. The following three metrics (which can be found in all web analytics tools) are highly useful when choosing pages to test:

Contribution to revenue. This metric can take different forms in different web analytics tools, but it basically tells you the contribution of each page to the overall revenue of the website. If the website has an ecommerce platform, this value should be some kind of purchase value divided by the pages seen before a purchase. If the website does not have an ecommerce platform, each goal should have a value linked to it so that we can calculate the contribution of each page to conversions.

Exit rate. This is the percentage of visitors that abandon the website from a specific page. A high exit rate shows that a page is not engaging enough and can be driving your customers away—unless the page is the “thank you for ordering” page, where it’s a good sign. If the objective is to test landing pages, the appropriate metric is the bounce rate, the percentage of visitors that leave the website without interacting with it. A high bounce rate shows that a landing page is performing poorly and should be optimized.

Average time on page. This metric can be an indication that visitors are having difficulty completing a task. For example, if you notice a very high time on page for one of the steps of a registration process, it might be a hint that users are having difficulties understanding what they are supposed to do—though this might not be true for content websites, where you do want your visitors to spend more time reading content.

These are the most common measures of success and failure of a page for most websites. It is important to consider all three metrics (and others that might be specific to your website) and prioritize pages to test. Once you know which pages are the most important, check which ones can be tested quickly. Go for the easiest! Once the first test is running and you tune the pages to improve results, management will implore for you to keep testing.

How long does testing take?

When choosing a page to test, it is also important to take into consideration what elements affect the time it will take in order to receive significant results. Basically, the variables that will affect the duration of your test are:

Number of combinations tested: As the number of combinations increases, the duration of the test increases.
Volume of traffic on the page: As the traffic of the tested page increases, the duration of the test decreases.
Conversion rate of page: As the conversion rates of the page increases (as defined by the tester when planning the test), the duration of the test decreases.
Expected improvement (the percentage by which you expect to improve the website): As the difference between the pages tested increases, the duration of the test decreases.

To estimate the duration of your test, you can use the Website Optimizer Duration Calculator, a very handy calculator provided by Google.

What should be tested?

As a web analyst, I feel the urge to say the magic words it depends! It depends on the type of website, it depends on the targeted public, it depends on your budget and it depends on that totally unscientific factor, the mood of your boss. Here are three things to test that can bring high benefits with low costs.

Calls to action. Too often calls to action are hidden, by a loaded page with too many graphic elements, by appearing below the fold or by a bad design choice (too small, faint color, or a button that does not look like a button). By improving the call to action and making it prominent on the page, you can sometimes boost your conversion rates drastically

Look and feel. Pages must be visually comfy, i.e., people should feel at home in your website. This way they won’t feel threatened and maybe they will become your friends, register for your newsletter and even buy something in the website. One way to do this is to test different images. Sometimes using a baby picture works; sometimes using a couple at the beach; sometimes even using something creepy, like an insect—depends what people are looking for on your website.

Copywriting. For visitors to seriously consider buying your product, signing up for your newsletter, whatever—you must have a good unique selling proposition. And people should see it as soon as view a page or they will leave. So make your unique selling proposition simple and prominent. Depending on the page you are testing, you should adapt the length of your text: for landing pages, short text usually works better; for product pages, go longer, telling visitors all the reasons why your product is the best in the market.

For a comprehensive list of testing elements and methods, you might take a look at the excellent book written by Brian Eisenberg and John Quarto-vonTivadar: Always Be Testing.

Testing tools

The online testing market is growing at a very fast pace, and there are quite a few players offering comprehensive solutions. Here are the biggest players—each has its own advantages and disadvantages. Check their websites to find the most suitable one for your needs.

Testing can bring huge benefits to any website. So start testing today, and don’t stop!

How To Use Google Analytics Motion Charts To Maximize Results

Daniel Waisberg — Thu, 03 Sep 2009 21:24:45 +0000

Last year Google Analytics released a few new features, among them the Motion Charts. The feature is based on software developed by Gapminder, acquired by Google in 2007.

According to the Google Analytics blog, “Motion Charts provide a multi-dimensional, over-time analysis of the data in your report.”

This feature provides a powerful way to visualize data in five dimensions: x-axis, y-axis, size of bubble, color of bubble, and time. In fact, if you choose metrics that are combinations of more than one metric, such as conversion rates (number of conversions divided by number of visits) bounce rate (number of bounces divided by number of visits), and Pages/Visit (number of pages divided by number of visits), you can even increase the number of dimensions to eight.

Here’s an example of a Motion Chart:

When it comes to search marketing, Motion Charts can bring significant value in the following ways:

Improve SEO keyword targeting. As we will see in the examples below, one of the advantages of Motion Charts over other forms of visualization is that it enables the analysis of large numbers of keywords across several parameters. This helps finding emerging keywords both in terms of traffic and performance. In addition, by analyzing bounce rate trends for keywords, we get a feel for landing pages that are underperfoming.

Expand PPC keyword targeting. By analyzing SEO targeting and results (as above), we can understand which organic keywords can present an opportunity to tap into new markets. Sometimes visitors get to the website using keywords that were not previously thought of as a match for the website. Motion Charts can uncover these “hidden” gems, allowing us to incorporate them into paid search campaigns.

Analyze PPC keyword performance. Paid search optimizers often fall into the trap of analyzing the average performance of campaigns or keywords. However, as Avinash Kaushik says about disappointing measurement techniques, “averages have an astonishing capacity to give you “average” data, they have a great capacity to lie, and they hinder decision making”, therefore the need to analyze not only averages, but segmented traffic and trends over time.

How to choose data displayed on a Motion Chart

As we saw above, Motion Charts can be very useful when analyzing search traffic whether we are looking into organic or paid traffic. In the screenshot below we see the keywords report (which can be reached from the Traffic Sources section). We will use it to exemplify how to populate the Motion Chart in the best possible way, according to the website owner needs.

The screenshot uses Google Analytics data from this Global Warming website.

It is important to understand that the Motion Chart data is defined by the report from where it was triggered. Here are the 5 parameters that should be defined carefully:

Keyword medium. Just above the chart, in the upper-left side, you will find three links: all, paid and non-paid. This can be used to analyze all keywords, just paid keywords, or just non-paid (organic) keywords.

Time range. As with all Google Analytics reports, time range can be adjusted from one single day to a few years worth of data. In order to neutralize time series effects I recommended analyzing at least a few weeks worth of data. Searcher behavior varies between the days of the week, the weeks of the month and the months of the year. Therefore, when analyzing daily behavior I recommended analyzing at least eight days (1 week + 1 day). When analyzing weekly behavior, at least 5 weeks (1 month + 1 week) and when analyzing monthly behavior analyze at least 13 months (1 year + 1 month).

Data grouping. This refers to the grouping of data into daily, weekly or yearly buckets. If you choose a six month range and group data in months, you will see six data points on the Motion Chart time-axis. If you choose the same date range but group it into days, you will see around 180 data points in the time axis.

Show rows. With Motion Charts it is possible to analyze up to 500 keywords in one shot. By using the drop down in the bottom-right corner of the table, you can include 10, 25, 50, 100, 250 or 500 keywords in the Motion Chart (although more than 25 keywords is a bit cluttered).

Filter keyword. This can be used to include or exclude keywords on the report. Keyword filters a very useful in when analyzing branded vs. non-branded keywords separately, or to analyze groups of words that hint at specific segments of visitors. It is possible to use regular expressions to build complex patterns if simple filters aren’t adequate for your needs.

After choosing your parameters, click on the visualize button above the chart (see top-left gray buttons on the figure above). This builds the Motion Chart for you.

How to choose Metrics to be analyzed on the Motion Chart

As with all web analytics analyses, the most important step when using the Motion Chart is to understand the website objectives and what metrics should be used to measure and improve these objectives. Often, your objective will be determined by whether yours is an ecommerce site or not.

When ecommerce is enabled in Google web analytics, interpreting results gets very intuitive. You know, for example, the value of a specific keyword (be it organic or paid) because you know how much revenue it brought. In the example below, the following metrics were chosen to be analyzed:

Visits (y-axis) shows the amount of visits for each keyword.

Bounce rate (x-axis) shows the % of bounces for each keyword. This is very helpful since it hints at whether a keyword matches the landing page or not—in other words, are you delivering the promise you give on your PPC ads or search result snippet? As Bryan Eisenberg writes: “keywords don’t fail to convert… we fail to convert visitors for that keyword.” Look for keywords far from the y-axis, especially red and/or big ones. Tip: optimize the landing page for these keywords.

Ecommerce conversion rate (color of bubble) shows the conversion rate for a keyword. This is important since you might have high converting keywords that are not receiving enough traffic. Look for red-small bubbles located close to the x-axis—thee keywords should get priority optimization treatment. Tip: increase exposure of these keywords on the website (and other SEO efforts) and focus on these and related keywords on your PPC campaigns.

Revenue (size of bubble) shows the amount of money this keyword is driving to your website. Look for big-blue bubbles—this is a signal that a keyword brings lots of money but could bring even more if it converted better. Tip: optimize the pages related to these keywords to improve conversion.

For websites that do not sell online (or for those that do not use Google Analytics ecommerce feature), we would analyze results using slightly different metrics.

Visits (y-axis) is the same as above.

Bounce Rate (x-axis) also the same as above.

Goal conversion (color of bubble). For websites that do not sell online, we can measure site success using several parameters: registrations, whitepaper downloads, comments from users, etc. It is highly important to have these goals configured on Google Analytics. We use goal conversion in a similar way we used ecommerce conversion rate above: to see keywords that convert well but do not get enough traffic.

Per visit goal value (size of bubble). Another important setting on Google Analytics is the $ index variable. It is used to understand the contribution of each source/page (in this specific case, keywords) of the website to conversions. In the Motion Charts this metric can be used to show how much revenue each keyword brought to the website.

The Motion Charts you create can be shared by sending a link to your colleagues directly from Google Analytics; this link will lead people to the exact same chart you created (note that the viewer must have access to the Google Analytics account). However, if you want to present the results to management and are not willing to trust internet for meetings, or if you want to share the results in a website widget, I recommend three alternative ways to share Motion Charts:

CamStudio is an open source screen recording tool that lets you record your screen very easily. This has the advantage that you can use Google Analytics as usual and just record the resulting chart. This might be handy for presentations, and you can also share it in a website using a YouTube widget. However, it has the disadvantage that you cannot interact with the chart and change its settings.

Google Docs Gadget is a great way to share, because it keeps all the functionality of the Motion Chart and you can change the settings as you analyze the numbers. Viewers do not need access to the Google Analytics account in order to view the chart. However, you will need to export the data and organize it in Google Docs, which might take a considerable amount of time, especially for large quantities of data (explanations on how to format the data). Unfortunately, as of today, the gadget works with Firefox but not with Internet Explorer or Chrome.

Successive screenshots: although this is far from optimal, since you lose the motion effect and you cannot interact with the chart, it might be needed to include in Powerpoint presentations or if you want to hide your company’s data (pictures are easier to edit than videos).

I believe that Motion Charts are more than just cool graphs—they really provide some deep visualization that is difficult to achieve through other tools. Motion Charts can be used together with other Web Analytics techniques to optimize search traffic results.

Bonus – if you ever thought that geeks are not talented when it comes to singing and playing the guitar, here is the proof that analysts know something about music: Motion Charts anthem.

Below is a Motion Chart created using Google Analytics taken from Google’s official Youtube channel; it was recorded and shared through YouTube:

If you have additional ideas on how to use this feature, please share them in the comments.

Googlebot Makes An Appearance In Web Analytics Reports

Daniel Waisberg — Mon, 03 Aug 2009 17:12:35 +0000

A few days days ago, I noticed some strange Google Analytics data: Googlebot appeared as a browser in the reports. Although this might sound like a not-so-important fact when it comes to SEO, it is a major change in the Web Analytics field. As Avinash Kaushik and I wrote in the SEMJ journal article Web Analytics 2.0: Empowering Customer Centricity, an important advantage of all JavaScript based solutions (Google Analytics, Omniture, Yahoo Web Analytics…) is:

The JavaScript is not read by crawlers, which generates high amounts of traffic and are not representative of customers’ behavior. Crawlers can be excluded from the analysis; however, it is a time consuming task, and many of them are not recognizable.

To check whether this bot is really from Google, and not some kind of user agent switcher, I drilled down on the data and here is what I found.

Googlebot appears in Google Analytics reports

First of all, as we can see below, the Googlebot is recognized as a browser (version 2.1):

Second, when we drill down to the network location report we find the following:

How does it affect the data?

If we look at the behavior of this bot, we see a very low time on site, very low pages/visit, and very high percentage of new visits. This might be due to the fact that the bot does not fetch cookies, which is essential to accurate analytics tracking. Below are some numbers:

Statistically speaking, this means that the Googlebot is an outlier, which is a data point that lies outside of the overall pattern of a distribution. It means that it can distort the numbers. In the example above, just a few visits with very low time on site and percentage of new visits can significantly decrease the overall average time on site andpercentage of new visitors, which is clearly bad for someone looking at the overall behavior of visitors.

How to exclude Googlebots from your Google Analytics data

Here is a filter that can be applied to Google Analytics profiles to exclude this Googlebot from messing with your data.

What lies ahead?

Google has been officialy scanning JavaScript since 2008. So maybe this has been a low priority or low usage technique untill now, used only in very specific cases. But recently we have seen an increase in this practice, so the big question is whether this is a trend that will increase as time passes or is it just a few specific tests run by Google? Editor’s note: Google declined to comment when asked for more information.

For now, we can only hope that this kind of data is not being collected by analytics packages from the back door. If it has been this might have been skewing the data quite a bit given Googlebot’s low time on site and percentage of new visits stats.

Disclosure: The data used on the screenshots above was extracted from the Web Analytics Association website. If you would like to take a look at this data, it is currently available to all members as part of the Web Analytics Championship.

Postscript: Google Analytics posted a response in the comments:

“The official Google bot does not execute Google Analytics JavaScript. We’re not sure what it is exactly, it could be anyone’s bot, some intern’s experiment, or other such traffic.”

I agree with this comment in that the official Googlebot reads JavaScript but does not execute it. Besides, it does not store and send cookies, which means that Paves/Visit would be exactly 1 and time on site exactly 0. Lastly, If the officiall Googlebot did execute JavaScript, we would have seen massive ammounts of visits.

It is also important to note that although we used Google Analytics as an example, we mean all JavaScript based solutions, including Omniture, Yahoo Web Analytics, WebTrends and others.

Please note that this issue requires additional investigation both in regards to Google Analytics and to how Google Search uses the Googlebot.

Using User Generated Content To Enhance Conversion-Driven SEO

Daniel Waisberg — Mon, 13 Jul 2009 19:44:39 +0000

As the web evolves, marketers must find creative solutions to engage customers with their websites and brands. Today, customers are no longer satisfied with consumption; they increasingly expect to be involved in the production of what they buy (or watch), turning them into “prosumers.” As Tapscott and Williams described in their enlightening book, Wikinomics: how mass collaboration changes everything, we have entered the era of prosumption. So how can marketers best take advantage of the voice of the customers, often referred to as user-generated content (UGC)?

UGC is not a passing fad, nor is it only for kids. Take a look at these stats from eMarketer:

What follows are some examples on how UGC can be used to improve both organic search results and conversion rates of a website (see other examples in this previous conversion-driven SEO post).

The benefits of user generated content

UGC can benefit a company in several ways. It enriches websites with precious (and free) content that feeds search crawlers. It is a source of information for newcomers, a place where they can understand products and read about how real people (not marketers!) are taking advantage of them. UGC is a forum for marketers to get feedback and ideas from customers and answer their questions. And finally, UGC is a mechanism that helps create a sense of community, a place where customers feel like stakeholders, a piece of website where they rule.

Amazon pioneered UGC, one of the earliest sites to introduce ratings, reviews, lists, customer images, tags, discussion forums, author blogs, and the list goes on and on. A very interesting UGC effort that Amazon recently launched lately is the Vine program. Since reviewers have been “donating” their time for years (and it looks like it helps selling products), which offers an additional incentive to write reviews for “trusted” users. Vine reviewers receive a monthly newsletter with merchandise to be launched in the next few weeks. Participants can choose a few items and get them for free! The Vine project shows how much Amazon values UGC.

UGC Challenges

Whenever a website launches with UGC areas, it runs the risk of being attacked by competitors or unscrupulous people. It also loses the power to control every single word published on the site. The best approach to handling this challenge is to provide robust usage guidelines to contributors, and to actively moderate UGC. An excellent example of UGC guidelines is offered by the BBC, which provides very comprehensive UGC guidelines for all their web properties.

Measuring the impact of UGC

You can apply similar metrics to UGC that you might use when evaluating your SEO efforts. There are four main areas in which to focus.

Content quantity. How many pieces of content have users contributed? Are there many people contributing to the website? Or does the UGC area of your site look like an abandoned castle?
Content linkability. Is UGC helping me to interlink my content? Good examples are tags, which help linking similar content and provide an excellent way for customers and crawlers to navigate the website.
Content strength. Are visitors using the keywords I am targeting? If so, where? How can I promote these areas?
Brand awareness or conversation with marketplace. What are visitors saying about your products or site? Are they happy? If not, why? This can become very clear when analyzing product ratings and reviews or website feedback.

You can analyze all the metrics proposed above by using a very interesting and powerful text analysis tool: Leximancer. It also provides some very neat graphs!

Leximancer makes it possible to analyze how often specific keywords are mentioned in any text. In addition, it is possible to find the linkability between keywords used in the text. Using this type of information it is possible to analyze, for example, if specific brands/products are linked to positive or negative terms. It is also possible to analyze the relationship between content and how visitors think.

In the screenshot below (see interactive version here) we can see the interface and the kind of info Leximancer provides. The example analyzes all US presidents’ inauguration speeches into meaningful “themes” (circles), “concepts” (colors) and their associated relationships.

As an example of how Leximancer can provide meaningful metrics on UGC, I analyzed analytics guru Avinash Kaushik’s blog, Occam’s Razor. We looked at all the comments on his blog (without scanning personally identifiable data apart from Avinash’s own posts). The first number I saw was astonishing: Avinash had written 187K out 398K words on the blog, less than 50%!

We analyzed the blog comments using Leximancer’s conceptual map and drew several interesting conclusions. In comments, visitors are using very positive terms like “great post” or “interesting read.” Meaning that Avinash is doing a good job engaging his community. We can also see industry terms such as “conversion rate,” “vendor experience” and “understand site.” This means that users are enriching the pages with targeted content.

In the short analysis above we saw how to measure all four metrics for UGC effectiveness proposed here: Content quantity, content linkability, content strength, and brand awareness.

However, one aspect not discussed above is how to use text mining to moderate your UGC. In conceptual maps, I have seen more than once (though not on Avinash’s blog), themes that relate to adult content. The tool helped me find, in a site with several million pages, where I was being attacked by abusers. This method is very helpful to keep an overall and drill-down view of the UGC being published on a website when you have minimal resources for moderation.

Concluding, leveraging user generated content is an advanced technique to improve a website conversion rate and, in parallel, its SEO efforts. And as we can see below, the UGC market is rapidly increasing both in number of users and in revenue to websites making use of it.

Full slides for this presentation below:

Note: This article was based on a presentation given recently at the Emetrics Summit. Full slides for this presentation are available here: UGC – Measuring The Voice Of The Customer

How To Optimize For Conversion In Organic Search Results

Daniel Waisberg — Tue, 12 May 2009 20:24:02 +0000

In the past, SEO success was measured by rankings of target keywords; then the focus moved to traffic; today we have moved into the bottom-line era: organic traffic should be measured by its impact on revenue. This post is based on a presentation delivered at eMetrics San Jose 2009. It is about ways to integrate and improve SEO and website usability (using web analytics) and create a synergy that will improve the conversion rates of websites.

Measuring SEO success using rankings is out-of-date: rankings fluctuate significantly and do not show any improvement on the website success. Traffic does not fluctuate so much, but it still does not show you the money. The way to measure SEO is by measuring its ROI.

Many people still think of organic traffic as free traffic. Although it is possible to get free organic traffic, to go to the next level and attract the masses to any website, it is highly important to invest resources, either with an agency or in-house people. Besides, many changes to the website are needed. Therefore, it is very important to consider all the expenditure with SEO, be it with consultancy, in-house development, or other. This way, it is possible to get to the understanding of the SEO ROI: how much profit you are getting from your organic traffic?

Content is king, but usability is queen

As we all heard time and again: when it comes to SEO, content is king. We don’t disagree. Relevant content is really essential in any website, both for SEO and for conversions. However, there is a clear tradeoff between content and usability (the design). Sometimes people are so worried about one of these elements that they completely forget about the other one.

The image below represents all the content (above the fold) before/after a change made for SEO purposes. The only change was the addition of fresh content above the product info, which pushed all product info to below the fold. Including more content on the page should not hurt the conversions of the website. However, the product pages have a very high conversion rate, and we saw a significant decrease in the visits on product pages. Conclusion: we saw an increase in the organic traffic, but a decrease in the overall conversion rates of the website.

As Nathan Rodriguez puts it, “Content is King, but sometimes the Queen rules!”

SEO for landing pages

When we talk about paid search campaigns, it is very natural to talk about landing page optimization. However, this is not so obvious when talking about organic SEO campaigns. But the importance is the same; both should be highly efficient in converting incoming traffic. The first question we should ask is: “Should I create or use an existing page for a keyword I am targeting with SEO?” And the answer: It depends! Depends whether your site already has relevant content for this keyword or not.

If you have a juice website, and you want to rank first for “soft drinks” it is not very efficient to use your homepage or another juice page for the keyword “soft drinks.” Even if you do succeed to rank first for this keyword you will probably have 100% bounce rate. But if you create a special page in which you show a comparison of different types of juices and soft drinks, it might persuade people to read further. A useful tool to test the success of SEO landing pages before you target them is AdWords. You can create a campaign in which you send visitors coming from “soft drinks“ to different pages and decide on the best SEO landing page. If content is the king and usability is the queen, relevance is the prince!

aniBoom is an animations’ website where people can create and upload their animations to be seen by other people. The site owners target content creators and they have a web-application called ShapeShifter in which users can create animations for free. The ShapeShifter main page receives traffic for keywords such as “create your own animation” and “free animation software”. When analyzing the organic traffic to this page, we saw a very significant bounce rate and understood something was wrong. The problem was that the most prominent element of the page, and probably the first words people read, are “$59.99″ (this banner was from one of their partners). When people click on “free animation software” and see a big $ on the landing page, they are very likely to bounce! Here is how the main element of the page looks before and after the analysis:

Another important element to optimize is the snippet that appears on the search results page: this is the first interaction of the user with your website, and ultimately may determine the click through rate from visitors coming from search engines. The snippet is what you promise to your user; are you delivering it in the landing page? You should be.

Targeting customer intent using internal site search

It is very common nowadays to optimize SEO by measuring the success of keywords bringing traffic to the website. While this is great, by doing that we lose a precious source of keywords: the keywords your customers are typing in your website, i.e. your internal site search. This is what they are really looking for, and you should check if you are targeting those keywords. Here is an example of a way to analyze internal search and optimize your SEO efforts using it.

TED is a very interesting conference that makes some of their talks available on their website (we did not analyze TED website, but did the same analysis for several websites). In the table below you can see on the left-most column search terms used by the visitors in the website (which keywords were typed in the internal search box). Each additional column represents a KPI for this term: how long users stayed on the website after searching, how many users clicked on a result from this search, newsletter signup (conversion), and registration (conversion). For each KPI, you can see if the keyword ranked above or below the average.

So, for example, people that searched for “good talks” in the website stayed longer than the average searcher in the website, they clicked more often than the average on the results, but they converted less than the average for both conversion types. Sir Ken Robinson was above the average for all KPIs.

TED always has some kind of cloud tags in its homepage, either with text links or image links. The way they usually organize the homepage is by recency of the talks, meaning that the latest talks get the better spot. Although this might be a good way to organize the website, we think a different way could be to organize it by highest converting search terms. So for example, it might be that every single person that gets to Bill Gates talk (which was the latest talk when this article was written) leaves the website. So why should it be the first one, just because it is the most recent one? Based on internal site search we can find the most converting terms and include them in the homepage: this would improve the usability of the website, meaning that people would find what they are looking for on the homepage, and it would improve the ranking for this specific term on search engines. These high-converting keywords should certainly be part of your target SEO keywords.

In summary, it is essential to adopt a customer centricity approach to web analytics. Rankings and traffic are not good measures of success for SEO efforts; we should focus on conversions and be sure to calculate the ROI of our organic traffic as we do for all other medium. A few takeaways: keep in mind the tradeoff between including content in the website and keeping it focused on conversions; choose carefully and optimize SEO landing pages; use your internal search to expand your keyword targeting on search engines and to give customers what they are looking for.

Full slides for this presentation are here:

Conversion-Driven SEO

View more presentations from Daniel Waisberg.