QR Code Analytics

QR codes have started to pop-up in lot of places such as store display, business cards, online ads, postcards etc. Whether QR codes are here to stay or not but from the measurement perspective they do present a huge opportunity in measuring advertising's (particularly offline) effectiveness.

If you are one of those marketers who have embraced QR code or are thinking about it or just curious to know how QR code measurement works then this post is for you.

Measuring URLs in QR Codes

You won’t be able to measure the number of impressions of the QR codes if they are distributed offline. What you can measure is how much traffic those QR codes are driving to your site or to your pages on 3rd party sites like facebook page, twitter account etc.

• Measuring QR code links to your site
  
  Measuring QR codes that sends user to your site is as simple as campaign tracking. Just add the campaign tracking variable to the URLs that you have in your QR Codes and treat it like any other campaign. Then you can use your campaign reports to see how much traffic QR codes are bringing and how valuable that traffic is.
  
  (Note: The tracking code, that you should append, depends on your Web Analytics tool.
  
  For Google Analytics, you need to append add at least 3 variables, Source, Medium and Campaign Name. to the URL for it to be tracked in the Google Analytics (Check out URL Shortner, http://clop.in as it’s URL builder let’s you append the variables for tracking in Google Analytics, Omniture, WebTrend and Unica NetInsights )
  
  Example
  Say I want to create a QR code to send people to
  http://webanalyis.blogspot.com
  
  Instead of simply creating a QR code to http://webanalyis.blogspot.com I appended Google Analytic campaign tracking code so my URL looks like the following http://webanalysis.blogspot.com?utm_source=qrcode&utm_medium=blog&utm_campaign=qrcodeblogpost
  
  
  
  
  
  Now I can use the campaign tracking in Google Analytics to see the stats on my QR code advertising.
  
  
• Measuring QR links to offfsite URLs such as Facebook page
  
  Since you won’t have your own web analytics tool running on a Facebook page you can use a URL shortener like http://clop.in or http://bit.ly (or better yet get a URL Shortener for your own domain with built in analytics from http://clop.in) to shorten the destination URL and then build a QR code using the shortened URL. This way you can use the built in analytics functionality of the URL shortener.
  
  Example:
  Say I want to send user to my facebook page http://www.facebook.com/TheAnilBatra
  
  Rather than sending user to the facebook page, via my QR code, I created a short URL using http://clop.in, http://clop.in/PByJfv and then used this shortened URL to build my QR Code.
  
  
  
  
  Now I can use the analytics reporting of http://clop.in/short-url-clopin.aspx?utm_source=qrcode&utm_medium=blog&utm_campaign=qrcodeblogpost to see the stats on my QR code advertising.

Tracking Phone Numbers in QR Code

To Track phone numbers, that get dialed when someone scans a QR code, use a unique phone number that you have tracking for. If you don't have unique phone number then you can use 3rd party services likes Marchex to get a unique phone number for each QR code that you publish.

Note: To create a QR code use a service like http://qrcode.kaywa.com/ 

Questions? Comments?

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Why is Google really rolling out Google Analytics opt-out plug-in?

Last week I wrote about a browser plug-in that will allow people to opt-out of the Google Analytics cookie. The release of this plug-in seems to be a proactive step towards another announcement.

Eric Peterson, on his blog, voiced his opinion on why Google is rolling out this plug-in. I think Eric has a point in his post about Google trying to make a push into Federal Government web sites and this roll out is a check-box to satisfy the needs of privacy advocates.

However, I am still not entirely clear on what Google will get if it can’t use all the data that it will collect on Federal Government website? It won’t be able to use in any way…well maybe at an aggregate level to compete with the likes of ComScore. So what do I think the reason is?

Behavioral Targeting

I think the real answer to Google Analytics’ rolling out Opt-out is “Behavioral Targeting”.
Google Analytics is deployed on thousands of websites and collects a wealth of data. However, so far this data is used by individual sites to optimize their ad spend and improve the site for customers while improving the websites impact on the bottom line. Google has not really used that data much other than providing benchmarking reports in Google Analytics. I think the time has come for Google to start using Google Analytics data to make more money.

Google Analytics Data Sharing

Remember, in 2006 Google Analytics started asking GA accounts to opt-in/opt-out of data sharing. As I wrote in my blog post on Google Analytics Data Sharing, “data sharing” was a step towards using Google Analytics data for behavioral targeting. This opt-out plug-in seems to be a next step in that direction.

Limited functionality of Adwords Remarketing

Last week Google Adwords announced the roll-out of “Remarketing” feature that will allow advertisers to remarket to the visitors (cookies) who came to their sites but left without taking the desired action i.e. without converting (this is also called Retargeting, a form of Behavioral Targeting). For this feature to work, Adwords advertisers will have to put a small script and identify the people (cookies) whom they want to target.
The functionality to identify the segment that you want to retarget seems to be very limited in Adwords.

Google Analytics role in enhancing Adwords Remarketing

Now imagine, you can create complex segment in Google Analytics and then use Adwords to target the visitors who fall in that segment. Won’t that be nice? Well that can’t happen unless you use Google Analytics. Here is an example to make this clear:
I want to target visitors who viewed more than 3 products and looked at the contact us page and then left without converting (or it could be more complex than this).
This is a segment that I won’t be able to create easily in Adwords without some coding on my pages. Using Google Analytics, advanced segment functionality this is a piece of cake. I create my segment then use Adwords to remarket to visitors who fall in that segment. Won’t that be more powerful? I think that’s where the money is.

Other Behavioral Targeting Scenarios with Google Analytics

Let’s take a hypothetical example to see how this will work.

Say I write a blog on luxury cars. I use Google Analytics as my web analytics tool (it is free, so why not). I don’t have real business model but I use Adsense ads to make some extra money. Since my blog is really popular I get lot of traffic. My blog reader are those who have interest in luxury cars because that’s all I write about.

Now imagine Google asks me to pool my visitors’ information, collected in Google Analytics, into a pool that they can use for advertising purposes. They tell me that by doing so I will be able to make some more money from my visitors even when the visitors have left my site. Hmm… free money. Sure :)

How will Google use that data?

Google will identify the visitors who come to my blog, read articles, write comments, come often etc. They will then put the visitors (cookies) who fulfill certain criteria (as defined by Google or the Advertiser) in a segment called “Luxury Car Enthusiast”. They will pool my data with other similar sites or similar pages on other sites to create a bigger pool than my site has to offer. Google now has a set of cookies who are interested in luxury cars.

BMW creates a campaign in Adwords to reach “Luxury Car Enthusiasts”. They are willing to play 2X-3X CPC or CPM to reach this target.

A visitor, who left my site (A) and lands on a site (B) that, has nothing to do with luxury cars. Google can identify that visitor because that visitor is in the pool of cookies that belong to “Luxury Car Enthusiasts” segment. Google shows this visitor an ad from BMW on Site B. Visitor sees the ad that matches his/her interest and the advertiser reaches their target.

Note: This all is a speculation by me and I have no official information.

Win-Win Situation

• BMW finds its target
• Google gets more money for the same ad slot.
• Publisher of the ad makes more money.
• Sites, which pool their visitors in this segment, get a cut.

What does GA Plug-in has to do with all this?

Behavioral Targeting has been under scrutiny for a long time and there is a big uproar about tracking people. Privacy advocates want an easy way for people to opt-out of Behavioral targeting and this plug-in seems to be a proactive step in that direction.

What do you think?

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Google Analytics Opt-out Browser Plug-in

Late last week Google Analytics announced a browser plug-in that will allow users to opt-out of Google Analytics tracking.

Here is an offical statement from Amy Chang, group product manager at Google Analytics:

As an enterprise-class web analytics solution, Google Analytics not only provides site owners with information on their website traffic and marketing effectiveness, it also does so with high regard for protecting user data privacy. Over the past year, we have been exploring ways to offer users more choice on how their data is collected by Google Analytics. We concluded that the best approach would be to develop a global browser based plug-in to allow users to opt out of being tracked by Google Analytics. Our engineers are now hard at work finalizing and testing this opt-out functionality. We look forward to make it globally available to our users in the coming weeks.

How does it impact the website stats reported by Google Analytics

This is the biggest question everybody is asking. Since I don't have the full information on how this plug-in will exactly work, let's take a look two potential ways this plug-in can work.

• The plug-in will not collect any sort of data for the user
  Let's assume that this plug-in will ensure that absolutely no data about the users behavior on any of the site that user visits will be collected. Which means that Google Analytics will completly ignore the presence of that person (computer) as if that person never visited the site. In that case all of the data, i.e. visitors, visits and page views, conversion etc., will be under reported.
  
• The plug-in will collect the data but then destroy the cookie after every session (visit)
  In this case, a session level cookie will still work but this cookie will be removed from the users computer after every session. This will result in the accurate count of visits (sessions) and page views and all the data that is reported at visit or page view level. However, the visitors count will be inflated since same person (computer) will get a new cookie for every visits.

How big the impact will be?

Well, it is not clear how widespread the use of this plug-in will be. Currently, there are 3rd party tools available clear or block Google analytics cookies but the use of such tools do not seem to be an issue for Google Analytics tracking. So I wonder if this plug-in will have any huge impact on Google Analytics data. However keep in mind that there will be some impact.

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Is Your Conversion Rate Wrong?

According to Web Analytics Association (WAA) standard definition, a conversion is a visitor completing a target action.

Conversion rate is calculated by total number of visitors completing a target actions divided by a “relevant denominator” (Sometimes it is total number of target actions divided by a “relevant denominator).

The key here is “relevant denominator”. This is often ignored by many organization and they tend to use the default denominator provided by their Web Analytics tool provides. The most common denominator used by most of the tools is either total visits or total visitors.

If you are an eCommerce site then potentially every visitors or visit is a target for conversion and “Total Visits” or “Total Visitors” as a denominator might make sense. However if your site is a non-eCommerce site and conversion to you means getting people to register on the site then using a denominator like total visits or total visitors to calculate conversion rate, wrongly assumes that all of the visits to sites have not previously converted (registered) and hence are potential conversion worthy. We all know that’s not the case. These sites get a mix of visitors, visitors who have registered in past and are not going to register again and, visitors who have not registered yet and hence are a potential target. Examples of such sites are facebook, WSJ.com, espn, yahoo etc.

Calculating the Right Conversion rate

In my examples I will assume that number of visits is equal to the number of visitors.

Hypothetical site in our examples is a portal that requires visitors to login (register) for some actions but also has content that does not require a login.

This sites gets an average of 1000 visits a day and gets 50 new registrations (conversions) a day. By most common way of calculating the conversion rate, the conversion rate for this site is 5% (i.e. Conversion Rate = Conversions/Total Visits = 50/1000 = 5%)

Let’s assume that every day this site gets 50% of the visits from the people who have registered in past. So that means 500 (50% of 1000) are registered and won’t register again. Since they are not going to register, why do we even consider them when calculating the conversion rate? By removing them from the calculation of conversion rate, the new conversion rate becomes:
50/500 = 10% (Immediately you doubled your conversion rate)

Why is this important?

Let’s look at two scenarios to illustrate the importance of choosing a relevant denominator.

1. Scenario 1
   One day the customer retention department sends some emails to previously registered visitors that result in 500 more visits from people who had previously registered. As a result the site got 1500 instead of 1000 visits it used to get every day. Considering that nothing else changed on the “not-registered” visitor base, the site got 50 conversions, just like any other day.
   
   Using “Total Visits” as the denominator, it appears that the conversion rate drops to 50/1500 = 3.33%
   
   It looks bad, and might cause you to panic. Won’t it? However if you choose the right denominator you will find out that nothing really changed. The pool of people who had not previously registered is still 500, so the true conversion rate is still the same
   50/500 = 10%.
   
2. Scenario 2
   The “customer acquisition” department bought a new email list and sends emails to this list which resulted in 500 extra visits. Overall the site got 1500 customers, 1000 who had never registered and 500 who had registered previously. That day the site got 60 registrations, resulting in a conversion rate of
   60/1500 = 4%.
   
   Look like our email list did not work because it caused the conversion rate to go down.
   
   This might cause you to wrongly assume that the email list that the retention department bough was not as good as the other traffic that you have been getting. However when you calculate the true conversion rate, it turns out that the email list actually worked; it resulted in a conversion rate of 6% (60/1000).
   

Note: Some might argue that why won’t this company tag all the emails with proper campaign identifiers so that we can track the performance of the emails. In theory this sounds great and that’s how it should be. In reality though, many departments work in isolation and never interact with the ‘Web Analytics” or follow their best practices. Now you know why marketing departments should share the marketing calendar/activities with “Web Analytics” group and involve them before running any campaign.

Hope this gives you an a reason to investigate what denominator you are using in your conversion rate.

In the next post, I will show you how you can calculate the “True Conversion Rate” using Google Analytics.

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Google Analytics Motion Charts Overview with a PPC Example

Most people look at click through rates, clicks or visits when analyzing their keywords. Some people will go a step further and look at the conversion rates. If you have a content site with no end conversion you might look at bounce rate to figure out what keywords are working or you might look at the page views/visit or look at some other form of engagement metrics. To look at all the data points you need to do full analysis, which requires you to look at a few reports and maybe use excel to pull all that data together in one view. Google Analytics Motion Charts make it really easy to visualize several data points in one screen.

In this post I will show:

1. Step-by-step overview of how motion charts work.


2. An example of how I used Google Analytics motion charts to figure out which keyword to spend money on.
   Note (I could have got similar information from a few reports in Google Analytics, but motions charts just made it easier and faster).

Let’s get started

To access motion charts,

1. Click on your report (keywords report in this case).


2. Select the date range that you want to analyze.


3. Click on Visualize button on the top. This will bring the motion chart (see below).

In the motion charts interface you can choose up to four dimensions that you can plot your data point against and see it in this graph. The four dimension areas are circled in the image below. Two dimensions can be plotted on the chart on X-axis and Y-axis, one using the color and the fourth using the size of the bubble that represents the data point.



For the dimensions on X-Axis and Y-Axis you have the option to plot the data either on “Linear” or “Log” scale. I chose linear in this case. (Note: You should choose log when your data points have too much variations in their values from one day to another. Using a linear scale will make it hard to draw them on one chart but log scale will make the chart much cleaner.)



You can select the dimensions by clicking on appropriate section (see below)



After you have selected your dimensions and chosen the scale (log or linear) you want, click on the data points (bubbles in the middle of the chart) to show the name of the data point. Also, those data points are will be tracked when the “Trails” option is enabled (discussed below).



Once all your selections are done you can check the “Trails” check box to track the progression of each data point on each of the dimensions you selected over the time period that you selected. Even though “Trails” is optional, I have found it to be an important feature to explore the full power of motion charts.
Note: if you select too many bubbles (keywords in this case) along with “Trails” then the motion charts become very crowded. You should limit selection to no more than 3 bubbles at a time.

In this case I chose two keywords, Keyword A and Keyword B since I wanted to see how they compare to each other on the dimensions that I chose. (Actual keywords are disguised for this example).

So why did I choose those two keywords? I actually chose a lot of keyword combinations. I was trying to find the keywords which I should buy on search engines to drive more traffic. Since the budget is limited (isn’t that the case everywhere?) I had to pick the keywords that will give us the biggest bang for our buck.

This site had two main site goals:

1. Convert visitors to registered members (Registration).


2. Drive more page views/visit to increase the ad inventory and hence ad revenue.

Based on these goals we needed to see following metrics:

1. Conversions driven by keywords


2. Visits Driven by Keywords


3. Page views/Visit


4. Bounce Rate

Since both the keywords had about same conversion rate, it was not important for us to plot it on X and Y-axis and it was chosen to be represented by the bubble size. I plotted metrics 1 and 2 (see above) on Y-axis and X-axis respectively since I wanted to see how the traffic is driven and how many pages people view when they visit the site. Bounce Rate was chosen to show different colors.

In my option, any critical metrics should go on X-axis and Y-axis. You should play with plotting all different metrics on different axis, color and size to see which one provide you more meaningful view. Plotting them in different ways provide different views and ideas of additional metrics that you might want to look at.

After all the dimension selections were made, I checked the “Trails” option and hit the “Play” button to see the motion chart in action (You can also manually move the slider next to play button).

Here is the final Motion Chart:



Looking at this it is clear that Keyword A is driving more traffic but lower Pages/Visit than Keyword B. The bounce rate is also higher for keyword A. The conversion rate is about the same for both keywords.

It is clear that we should put more dollars behind Keyword B as it helps us achieve goal number 2 better than Keyword A. Goal 1 is about the same for both these keywords.

Hope this post was helpful in demystifying Google Analytics Motion Charts.

For any questions on Motion Charts and Google Analytics please visit Ask an Expert section on my site.

Comments? Questions?

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Looking to fill your Web Analytics or Online Marketing position?Post your open jobs on http://www.web-analytics-jobs.com/
Sr/Lead Analytic Warehouse/Java Engineer at Saas Company In the SF Bay Area (Emeryville, CA)
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Site: AnilBatra.com
Twitter: http://www.twitter.com/anilbatra

Things I have been working on

There has been a lag in my blog posting lately, and it’s gone on longer than I like. Lately, things have been hectic at work leaving very little time for blogging. Any time left has been consumed the following activities:

1. Working on my Site, AnilBatra.com
   
   
   
   1. Ask an expert – I started a section for you to ask questions on Web Analytics, Behavioral Targeting and Web Analytics tools, particularly Omniture, WebTrends and Google Analytics. The questions will be answered by one of the people who have volunteered, one of my team members at Ascentium or me personally. So if you have a question please go ahead and fill out the form and someone will get back to you within 48 hours. If you would like to be one of the experts please email me a brief description about your skills and experience.
   
   
   2. Twitter – Google Analytics URL Builder – Nothing fancy here but a tool that allows you to create short URLs that you can post in Twitter and track them in your Google Analytics. It allows you to create short URLs for both your internal links (links to you own site) and external links (links that reside outside your site).
   
   
   3. Calculators – I am working on some basic and advanced calculators related to Web Analytics and Online Marketing. So far I have added a CPM, CPC, and CPA calculator (will be adding few more optional fields to it). More calculators will be added to this one. If you have suggestions on what calculators I should add then please send them to me.
   
   


2. Industry Average Bounce Rates – I conducted a survey to understand what Bounce Rates to expect for various types of sites. I added a pdf that shows the results of this survey.
   


3. Google Analytics Session for Seattle Tech Startup Group - I, along with Loren Bast, conducted a Google Analytics training session for the Tech Startup community of Seattle. Download the Seattle Tech Startup Google Analytics Presentation.
   


4. Future of Web Analytics Panel at SDMA – I have been busy putting together a panel for the Seattle Direct Marketing Association to be held on March 11.
   


5. Preparing for Breakfast Event in San Francisco – Gary Angel, Akin Arikan and I will be speaking at a breakfast event in San Francisco on March 9th. You can find more information and registration on my site.


6. Neel – Neel is the name of my 5.5 month old son. He is growing and getting more and more active every day and needs more of my time.

I expect to resume my blog writing schedule very soon.

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Looking to fill your Web Analytics or Online Marketing position?
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Sr/Lead Analytic Warehouse/Java Engineer at Saas Company In the SF Bay Area (Emeryville, CA)

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Site: AnilBatra.com
Twitter: http://www.twitter.com/anilbatra

Social Network in Action: How Twitter Helped Me

Twitter has become a tool that I have come to love. It has provided me a way to connect with people I have never met, and it has helped me find information that I might have missed otherwise. A recent experience on Twitter showed me how this tool can be used to gather customer feedback and also to collaborate with others to solve a problem.

Last week I wrote a small tool to help me create short url’s with Google Analytics Tracking embedded in them. This tool allows me to create short URLs for links that are both external (not residing on my site) as well as internal (residing on my site). The tool is open to the public so please give it and try and send me your feedback. It is nothing fancy but something that I needed for my own use. (More on this in another blog post). (Also see, Twitter Analytics and Google Analytics Twitter URL Builder)

At 11:04 p.m. on February 5th I tweeted about this tool.




Within minutes I got my first feedback in a direct message (also called “DM” in twitter language).



Yes, I had not tested the tool in other browsers and O/S but my Twitter friends came to my rescue and provided me valuable information. Several other people jumped in and provided feedback. I immediately jumped into action to fix this issue. Had it not been for Twitter I don’t think I would have been able to get such feedback so quickly.
Next I was able to isolate the issue, which was a JavaScript problem. The JavaScript I had on the page worked fine on IE but not on Firefox. Since I am rusty with my JavaScript I had 4 options

1. Search on a search engine and try to sort out all the content and find what I was looking for.


2. Call one of friends/colleagues/Freelancers who are JavaScript gurus


3. Buy a JavaScript book and try it on my own


4. Try to find if my Twitter friends (people I might not have met in person but are following me on twitter) will help again

Given that it was late, I went to bed and thought about fixing the JavaScript issue the next morning. The next morning I decided to give option number 4 a try, and posted the following message in Twitter:




I posted the message on Twitter at 7:25 a.m. and within minutes I got reply from my Twitter friends, who helped to debug or find a solution for me.



Isn’t Twitter a powerful tool for feedback and collaboration? Despite all the noise that happens on Twitter, it can be a very valuable tool, as I have found it on several occasions.

Following are my Twitter Friends, who provided me the valuable feedback, helped with the javascript issue and/or help spread the word via their ReTweets (Thank you all).

• Bryan T Robertson


• Deepak Kumar


• Stephane Hamel


• Birger Friedrichs


• Marcelo Calbucci


• David Iwanow


• Jeremy Sisson


• Krishna


• DorisEichmeier


• cbgreenwood


• moniforce


• Thomas Bosilevac


• Shannon Yelland


• Aaron Lovelace


• Neil Minetto


• Stuart Schwartz (He has helped me a lot with the JavaScript used on that tool)

Comments? Questions?

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Looking to fill your Web Analytics or Online Marketing position?

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Site: AnilBatra.com
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Google Analytics: Creating Advanced Segments and an Issue

Last month Google Analytics released Advanced Segmentation functionality. I am very impressed with it so far, however this functionality is still in beta, which means it could potentially have some issues. In this post I will show you how to create an advanced segment and one issue that I found with it.

Business Problem: I want to see all the data for visits that originate from Google.

Solution: Create an Advanced Segment that will have all the visits that has the source as google.

Let’s see how to create such a segment. (Not this is a very simple segment but the same steps can be used to create more complex segments).

Creating an "Advanced Segment"

1. Click on the "Advanced Segments" link on the left navigation bar under the “Settings” section.
   
   




2. In the next screen you will see all the "Advanced Segments". In this screen you manage all the advanced segments. Google Analytics has predefined some of the segments and they are grouped under "Default Segments". The segments that you create will be listed under "Custom Segments". To create a new segment, click on the “Create new custom segment” link on the top right hand corner.
   
   
   



3. The next screen is where you create the segment. The segments can be created by using one or more dimensions and metrics. On the left hand side you have 2 sections "Dimensions" and "Metrics". I chose a dimension of "Source" listed under "Traffic Source" as I wanted to see all the visits which originated from Google (i.e. the source was Google). I chose "contains" as the condition as I wanted to get all the visits that originated from anything that contained Google in the source. Finally I entered the word "google" in the value.
   
   
   



4. Click on “Test Segment” button to do a sanity check and see if the segment size is as expected. Once you are satisfied with the segment, give it a name in "New Segment" filed and click "Save Segment" to Save the segment.
   
   



5. Once you the save the segment you will be taken back to "Mange Segments" where your new segment will appear. See below, a new segment called "Google Visits" show up. The new segment is now ready to be applied to various reports.
   
   
   

So far so good. However, I found one potential issue with the data.

The Issue

I applied this segment to one of the pages in my Content Report (see below) and chose the date as Nov 3rd.




As you can see my "Google Visit" segment is reporting 328 pageviews while my "All Segments" is reporting only 175 pageviews. That does not seem right. Similarly Unique Views is 112 for "All Visits" while 201 for "Google Visits". As you can also see from the graph, "Google Visits" are higher than "All Visits" on several dates not just November 3rd. Has anyone else seen something similar? Am I not reading these reports correctly?

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Twitter: http://www.twitter.com/anilbatra
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Goal Attribution to Organic Keywords - Google Analytics Tips and Tricks

In April I wrote a blog post to show you why some of your keywords show 0 Visits and 0 page views in your Google Analytics Report. In this post I am going to show the attribution of goal to the search engine keywords, when a user searches multiple keywords on the search engines to visit your site (all within the same session) and converts from one of the keywords.

Note: The past post and this one are both based on the Organics keywords searches and clicks.

I conducted two following two experiments

1. Converted on the Last Keyword
   
   
   1. Searched “1 page no register seattleindian” on Google, arrived on http://www.seattleindian.com/ , viewed one page and existed the site by typing Google.com in the browser address bar
   
   
   2. Searched “2 pages no register seattleindian” on Google, arrived on http://www.seattleindian.com, viewed 2 pages and then exited the site by typing Google.com in the browser address bar
   
   
   3. Searched “4 pages register seattleindian” on Google, arrived on http://www.seattleindian.com , registered on the site (converted, Goal 1), viewed total of 4 pages and then exited the site by closing the browser
   
   
   4. All of the above was done within 30 minutes and using the same browser session
   
   
   
   Visit and Page View Attribution
   
   As you can see my visit resulted in 3 keywords, total of 7 page views and 1 visit (visit time out is 30 mins and all of it was done in 30 minutes). As I showed you in the last post, 1 page view is shown and attributed to 1st keyword. The other keywords do not get visits or page views attribution (Figure 1). The total pages are accounted and counted in the keyword report even though 6 pages were not attributed to any particular keyword (Figure 2)
   
   
   Figure 1 (click on the image to enlarge it)
   
   
   Figure 2 (click on the image to enlarge it)
   
   Goal Attribution
   
   In this scenario, the Goal is attributed to overall search engine keywords but not to any particular keyword.
   
   
   Figure 3 (click on the image to enlarge it)
   


2. Converted on the First Keyword
   
   
   1. Searched “SeattleIndian 4 pages register test 3” on Google, arrived on http://www.seattleindian.com , viewed 4 pages, registered on the site (converted, Goal 1) and then exited the site by typing in Google.com in the browser address bar
   
   
   2. Searched “SeattleIndian 3 pages no register test 3” on Google, arrived on http://www.seattleindian.com, viewed 3 pages and then exited the site by typing Google.com in the browser address bar
   
   
   3. Searched “SeattleIndian 1 pages no register test 3” on Google, arrived on http://www.seattleindian.com , viewed 1 page and then existed the site by closing the browser
   
   
   4. All of the above was done within 30 minutes and using the same browser session
   
   
   
   Visit and Page View Attribution
   
   In this case I converted (Goal 1) when I arrived via the first keyword. When I look at the Site Usage of keywords, the first keywords is credited with 1 visit and 4 pages, the other two keywords did not get any credit of the visit or the pages that were viewed as a result of click on those keywords. So the 3 pages are not attributed to any keyword. This is what I showed in my last post.
   
   
   Figure 4 (click on the image to enlarge it)
   
   
   Figure 5 (click on the image to enlarge it)
   
   Goal Attribution
   
   In this scenario when the conversion happens from the first keyword, the goal is properly attributed to that keyword.
   

Conclusion

When a user searches multiple keywords to arrive to the site,

1. The visit is attributed to the first keyword only


2. The page views directly related to the first keyword are attributed to that keyword and other keywords show 0 visit and 0 page views


3. Total page views from all the keywords are counted in the overall keyword report


4. If the conversion happens as a result of the first keyword then it is attributed to that keyword


5. If the conversion happens as a result of any of the keyword other than the first one, then the conversion is not attributed to any of the keywords


6. The conversion from any keyword is counted in the overall keyword report

What’s next? I will be testing how attribution works when a user clicks both Organic (SEO) and Paid PPC (search result) within the same visit.

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Web Analytics Buyer’s Guide, Assessing Vendors’ Competencies and Value

John Lovett from Jupiter Research released his new report titled Web Analytics Buyer’s Guide, Assessing Vendors’ Competencies and Value. In this report he analyzed the web analytics market and various vendors, and concluded:

The Web analytics feature race is largely over and we are left with Web Analytics providers competing on Price and Flexibility.

John provides great analysis and insights in this report but I do not fully agree with his conclusion that feature race is largely over. I believe that as new trends in web continue to emerge so is the need for new features. As Phil Kemelor, another great analyst, writes that audio and video are becoming an important part of the web, so there are clearly features needed to support their tracking. Other features currently missing are for Mobile Analytics. Mobile web is clearly gaining momentum and so is a need for Mobile Analytics. I am sure Product Managers of these tool providers are not ready to quit yet.

I do agree that most of the vendors are mostly competing on Price and Flexibility (post-data-capture segmentation, reporting on custom data elements etc.) at this time. (In my view, flexibility is also a feature though). However competing on price when there is still a lot of room for innovation and differentiation is a very myopic view by current web analytics vendor and will provide a way for someone to disrupt their business very quickly.

Satisfaction with the current tool

One of the surprising results in this report was that more than 69% of the web analytics clients have decided to stay with their current web analytics tool. This is a big change from the trend that we have seen in past. A lot of this has to do with education about web analytics tools, what they can do, how they operate and the fact that several most used features and reports are comparable in various tools.
72% of those 69% where completely satisfied with their current provider.
47% of the customer said that the biggest challenge they were trying to solve with Web Analytics tools was Vistor Segmentation. 47% also said that customer engagement was their biggest challenge.

And the Winner Is?

This report has a great 3 dimensional chart showing how different tool vendors rate in terms of business value, market suitability and breadth of company.
Omniture, Unica, and Coremetrics emerged as industry leaders for large enterprises while WebTrends, Google Analytics, IndexTools and Lyris HQ ClickTracks emerged as industry leader for small-to-midsize businesses along with the three listed for large enterprise customers.

It was surprising to see that WebTrends was not considered an enterprise tool anymore, though WebTrends was the only company to score 100% on availability of basic features. (Sidenote: A customer of ours is replacing Coremetrics and going with WebTrends).
Another surprising result was that Omniture was the overall winner even for small-to-midsize businesses.

You can get the complete report at http://www.jupiterresearch.com/bin/item.pl/research:vision/79/id=100411


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Google Ad Planner

A lot of you might already know that Google announced the release of Google Ad Planner. This free media research and planner tool allows advertisers/agencies to find the Web sites that match their desired target audiences so that they can decide where to spend their advertising dollars.

This tool along with other tools such as Google Analytics Benchmarking, Google Trends for Websites positions Google well in competition with Nielsen , Quantcast, Hitwise and Compete.

I got my account to Google Ad Planner last week and I can tell you that I was impressed. Yes, there are a lot of features that are not there yet but nonetheless this tool is pretty powerful. Using this tool you can find smaller sites to advertise that you would normally not look at.

How does Google Ad Planner Work

1. When you first enter the tool it show you how many total Unique Visitors and Pageviews that you can reach (that is total internet usage) if you advertised on the whole internet.


2. Then you can choose specific country and/or language to narrow down your target audience.


3. Next you can enter any demographic information to further narrow down your target audience. The demographics that are available are gender, age range, education and household income.


4. Finally you can narrow or expand your target audience by particular sites. You have two options in this filter to choose from
   
   1. any site below
   2. all sites below
   
   Below is the description of this filter from Google Ad Planner Help.
   Choosing any site below means any internet user in the sample set who meets at least one of the criteria will be included in your audience.
   Choosing all sites below means internet users in the sample set must meet all of the criteria in order to be included in your audience.
   For example, if you specify 'Site A,' 'Site B,' and 'Site C' as sites your audience is likely to visit, then select the all sites below filter, only internet users in the sample set who visit all three sites will be included in your audience.
   If, however, you select the any site below filter, an internet user in the sample set who only visits Site A and Site C will still be included in your search results.
   


5. Another filter option is to limit your audience to only those sites that are in Google Content Network and the ad sizes these publishers support. This option is very useful if you are limited to using Google Adwords for your media buys.

Apart from Media planning, this tool can be used to do competitive analysis. For example, it can show you what percentage of your users also go to your competitor’s site. It can show you what other sites your competitor’s visitors visit – Good for analysis and then planning your media buy. It can show you the demographic mix of your competitors visitors.

Like Google trends, Google Ad Planner needs to be integrated into Google Analytics. Microsoft Gatineau overlaid some of the demographic data into the web analytics reporting, Google just showed you that they have that data too, plus some more. So it is matter of time when this data will be available in Google Analytics.

Google started using its Monopolistic Powers? Do No Evil?

On Monday, I wrote about Google Trends for Websites, a tool that lets you trend and compare unique visitor counts for websites.

It combines data from variety of sources, such as aggregated Google search data, aggregated opt-in anonymous Google Analytics data, opt-in consumer panel data, and other third-party market research. Remember, a while back Google asked you to opt-into data sharing in Google Analytics, this is one place where your data is being used.

If you don’t want your site to be listed in this tool because you don’t want you competitors to know how you are doing, then how do you opt-out?

Let’s assume that you are using Google Analytics and have opted-in to Google Analytics Data Sharing. In that case Google should be using your Google Analytics data to show your site starts in Google Trends, that is more accurate than any other kind of data (well sort of). So if you do opt-out from Google Analytics data sharing, Google will revert to other sources of data e.g. toolbar, Google search data etc, which means you will still be listed in Google Trends for Websites.

The only way to completely remove your site from Google Trends from websites is by opting-out of Google Search engine by using a robot.txt to not let googlebot crawl your site. Remember, by doing so you will probably loose a good chuck of you traffic, traffic that comes via Google search engine. And why would you do that? In other words, you don’t have a choice. You are opted-in in Google Trends for websites by default and you have no way out. (Note, even if you could opt-out of Google Trends, competitors can still find out about your traffic etc using other services such as comScore but this one is Free so makes your data widely available).

On the other hand Google Properties such as Google.com, Orkut, do not have to follow the same process. According to Google, "We do not show Google.com properties on Trends for Websites. We have policy of not providing interim financial guidance, and have decided not to release Google numbers in accordance with that policy." Hmmm...what about other companies? Should Google not respect their policy?

Now won’t you call using (abusing) your monopolistic power?

Comments?

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Google Trends for Websites

Google has released a new tool called Google Trends for Websites to compete with the likes of Alexa, Compete, Hitwise, Comscore Nielsen Net Ratings. This is exactly what I predicted in my blog post on April, Friday the 13th, 2007. I wrote, "Another effect of the widespread code of Google could be the death of companies like Alexa, Compete, Comscore etc. Google can provide the internet usage data that won’t be based on a sample of those who participate (voluntarily or by installing some kind of application such as a toolbar) but on the Google cookies which will be on almost every single computer connected to the internet."

I also said, "However, this business might not be so lucrative for them. Why would they want to let others know how people use internet when they can use it to make it Googlenet (formerly known as internet) or GWW - Google Wide Web (formerly know as World Wide Web).” I think this business might not make them money but will help them dominate Word Wide Web and make it Google Wide Web."


So how does Google Trends for Websites work?

Google Trends for Websites allow you to trend and compare number of daily unique visitors for up to 5 sites.

Below is a screen shot of Google Trends for Websites. I compared Walmart.com with Amazon.com.



Source: http://trends.google.com/websites?q=walmart.com%2C+amazon.com&geo=all&date=all&sort=0

You can see daily visitors on the graph and a list of

1. regions where visitors originated from


2. Other websites that they have also visited. The list shows a correlation between different sites.


3. search terms they have also searched for. The list shows a correlation between different sites

You can breakdown the data by region and time frame.

It combines data from variety of sources, such as aggregated Google search data, aggregated opt-in anonymous Google Analytics data, opt-in consumer panel data, and other third-party market research. Remember, a while back Google asked you to opt-into data sharing in Google Analytics, this is one place where your data is being used.

Are all Sites Included in this tool?

No, at this time not all the sites are included in Google Trends for Websites. Here is why certain sites may not be included

• Websites with low traffic volume below certain threshold


• Websites that don't wish to be indexed by Google and have indicated their preference through a robots.txt exclusion file


• Websites that don't adhere to Google Quality Guidelines


• Other websites for miscellaneous reasons

Just like other similar service (Compete, Alexa, Comscore etc.), Google Trends numbers won’t match the number you will see with your web analytics tool. However, considering the number of sources that Google can potentially collect and aggregate data from, in future this might provide the best approximation, totally outdoing other competing tools.

What’s next?

1. Integration of Google Trends with Google Analytics, so that you can get competitive information in one place.


2. A service for website owners to collect “Voice of Customer” data - surveys, opinions etc. (Watch out OpinionLab, you are next) This service will enhance Google Services such as Search (page rank algorithm), Google Trends and Google Analytics.

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Tracking TV Campaigns on Google AdWords using Google Analytics

Today Google announced, that the advertisers who run TV Campaigns via Google AdWords can track the online impact of those TV ads using Google Analytics.
According to Google AdWords blog, you can track website metrics, such as visits, conversion rates and revenue, alongside metrics from your TV Ads campaigns such as:

• Impressions delivered


• Number of ad plays


• Cost


• CPM paid

• Impression Delivered is Total impressions delivered -- an impression is defined as an active television that is tuned to and displays your commercial for 2 seconds or more.


• Number of Ad plays – I am not sure what this means but this probably refers to total number of active televisions that viewed the entire ad. I will provide more information as I get more detials.


• Cost is the total cost that was paid for the campaign


• CPM is the cost per thousand impressions delivered

So now you can start to see online, radio and TV ads all in the same reporting. Pretty cool!!

Here is a screen shot of the report that you will get.

Google Analytics Data Sharing

Google Analytics has an option to allow you to share your analytics data with Google in return for services like Google Benchmarking and enhanced ad features that will be released in future. Google provides following two options for data sharing.

1. With Google products only
   
   What do you get with this option? Enable enhanced ad features and an improved experience with AdWords, AdSense and other Google products by sharing your website's Google Analytics data with other Google services. Only Google services (no third parties) will be able to access your data.
   


2. Anonymously with Google products and the benchmarking service
   
   What do you get with this option? Enable benchmarking within Google Analytics by sharing your website data in an anonymous form. Google will remove all identifiable information about your website, combine the data with hundreds of other anonymous sites in comparable industries and report aggregate trends in the benchmarking service. Google will also use this data in anonymous form to improve our products and services.

Since companies are concerned about their data, the first question that most of them are asking is “Should we share data with Google and how will the data be used?”
In this post I will provide my views on Google Analytics data sharing service. Please note that I am not associated with Google or any Google entity and have not worked with them in any capacity. These are my views only, based on my past experience with Analytics , Online Adverting and Behavioral Targeting companies and services.

So what do I think?

As I had written in past, Google will be entering the Behavioral Targeting space. For it to realize full power of Behavioral Targeting it will need to aggregate the data it collects from sites across the web via its various services such as Google Toolbar, Adsense, Adwords, Google Analytics, YouTube, Google Checkout, Google Optimizer etc. Since there is so much concern about privacy and data usage by Companies like Google, it will create a lot of problem for Google if they just start aggregating all this data. To make sure Google is easing these concerns about how Google can use the data it collects from its services, in particular data from its business oriented services such Google Analytics, Adword etc , it has to seek permission from the site owners (and visitors).
Google is starting this with Google Analytics. It is asking your permission to allow them to aggregate your Google Analytics data in return for some free services such as Benchmarking and others services yet to come.

Option 1

Let’s start with Option 1 “With Google products only”. The description of this option can be interpreted in the following two ways

1. If you chose this option your Analytics data will be shared by other Google services that you use. This data will only be used to enhance Google products, Adwords, Adsense etc. used by you using your Google Analytics data. So they are asking you to opt-in into tighter integration of these products (sort of like Omniture genesis). Your data will not be shared with any other company or used to enhance Adwords or Adsense for any other company.


Or it could also mean


2. Your data will be used at an aggregated level to enhance Adwords, Adsense or other Google products to help Google. This is along the lines of Behavioral Targeting. Say you operate an online golf store. You have some buyer who frequently come and buy products from you. Google knows a lot about those users (e.g. they buy golf balls on regular basis and hence are avid golfers). When these users goes on another sites that serves Adsense ads, Google can serve ads about Golf balls or other Golf products even though that site might have nothing to do with Golf, but it knows that these visitors are avid golfers and are more likely to click on golf ads. Now these ads could be yours or of your competitors, you won’t know. Also Google will be able to charge more as they will allow advertisers to reach the right target customers, a great deal for the advertiser and Google. This raises 2 main questions (and maybe a lot more).
   
   
   
   1. Why should you allow Google to use your data to power your competitors’ ads and hence loose customers?
   
   
   2. Why should you allow Google to charge more for targeting based on the data that was collected on your site? Shouldn’t you get a piece of it?
   
   

Option 2

“Anonymously with Google products and the benchmarking service” has the following two components

1. Benchmarking: Most of the companies want to benchmark and see how they are doing compared to other companies in their vertical, size etc. This sort of data is usually available from companies like Nielsen Net Ratings, Comscore, Hitwise, Compete for a fee. Realizing the needs of consumers Google Analytics is providing this service as an option in Google Analytics. The data is anonymous and aggregated so I don’t have a problem with letting them use my data and provide me free benchmarking data. (Note: I had talked about them entering this space in my blog post, on April 13 , 2007 ( “Google and Behavioral Targeting” , way before they released the data sharing services).



2. Google Products: Even tough Google is saying that it will make the data “anonymous”, what it really is saying is that it will remove information about your site from the data (the site where data is collected). In nutshell, I think this still refers to the same type of data sharing as mentioned in point number 2 of Option 1 (above) so I have same concerns as I already mentioned.

So what should you do?

It depends on your situation.

Option Number 1: If it is really to help you better your ads and optimize your site and conversion then you should opt-in. At this time it is not clear. I would say opt-in for a less strategic site (if you have multiple) and see how it works then you can always opt-out if it is not what you expect. I will of course blog about it in future on how they actually use the data.

Option Number 2: For now, in my opinion, you are ok with sharing your data to use Benchmarking services. You can always opt-out later when Google starts to use this data to power Adwords and Adsense.

User Privacy

Even though Google is making the data anonymous it is only referring to privacy of the site not of the individual visitors. It is up for debate who owns the data, the visitor, the website where data is collected or third party tool like Google Analytics. They are asking your (site owners) permission by asking you to opt-in to data sharing. To ensure Google covers all it bases when (note I did not say IF) they decide to behavioral targeting based on all the data collected they will seek to get user permission too (or I think they should).

Privacy policies are different in different countries so you should comply with local privacy policies before allowing Google to aggregate data collected on your site. It is always a good idea to clearly mention in your sites’ privacy policy how you are allowing 3rd parties to anonymously collect and aggregate the data for Benchmarking and other marketing services.

Comments? Questions?

Web Analytics Industry - Consolidation Continues

Last month I wrote about ZeroDash1 and IndexTools getting into partnership. Few days later we (ZeroDash1) were acquired by Ascentium, a marketing an technology company based in Bellevue, WA.

Now IndexTool has been acquired by Yahoo.

"Yahoo! believes that the ability to generate the most valuable and relevant insights is essential to seizing market opportunities and creating successful campaigns," said Bassel Ojjeh "We expect that the IndexTools' technology platform will provide our customers the opportunity to more quickly uncover and act on these insights, enhancing Yahoo!'s status as a partner of choice in online marketing and the must buy for the world's advertisers."

I am not sure if IndexTools will continue to offer its tool for a fee (as it is today) or become a free webanalytics tool like Google Analytics. I think that Yahoo will take the route of Google Analytics and Microsoft Gatineau and make it a free tool. IndexTool is, however, a better tool in terms of functionality it offers compared to Google and Microsoft’s tool.

A free offering from Yahoo will change the Web Analytics landscape. If yahoo is smart they will make index tool available for free as soon as possible. I will replace GA with IndexTool in a heartbeat (as I don’t tie my Adwords to GA).

So what’s next?

Here are few scenarios

Scenario 1

1. Google Analytics, Microsoft Analytics (and some other tools) will not be able to compete with IndexTools free offering.


2. Microsoft will need to step up its offering quite a bit (considering the deal with Yahoo is not happening), they should buy WebTrends. Webtrends is built on MS technology and provides far more functionality than IndexTools (Let’s call it Yahoo Analytics). Which will make Microsoft the leader, Yahoo second and Google third in web analytics capability.


3. Now, Google won’t stand still. They will use their stock power to buy Omniture and replace Google Analytics with Omniture.


4. Which will make Google the leader once again, Microsoft second and Yahoo Third


5. Microsoft then buys Yahoo and it will be down to two Google and Microsoft. We won’t have one clear leader as both will be close.

Scenario 2

1. Google Analytics, Microsoft Analytics (and some other tools) will not be able to compete with IndexTools free offering.


2. Considering Microsoft’s intent to buy Yahoo, Google will spring into action and buy Webtrends and Omniture.


3. Which will make Google the leader once again, Microsoft second and Yahoo Third


4. Microsoft then buys Yahoo and it will be down to two Google and Microsoft. We won’t have one clear leader as both will be close.

Scenario 3:

1. Google Analytics, Microsoft Analytics (and some other tools) will not be able to compete with IndexTools free offering.


2. Microsoft will need to step up its offering quite a bit (considering the deal with Yahoo is not happening), they should buy WebTrends. Webtrends is built on MS technology and provides far more functionality than IndexTools (Let’s call it Yahoo Analytics). Which will make Microsoft the leader, Yahoo second and Google third in web analytics capability.


3. Oracle, which is on the sidelines but one Web analytics company recently, jumps into action and buys Omniture and makes it free.


4. Which will make Oracle the leader once again, Microsoft second and Yahoo Third and Google the fourth.
   
5. Microsoft then buys Yahoo and it will be down to three Oracle, Microsoft and Google.

Some other combinations of the above are also possible. Also, there is a possibility of AOL and some agencies getting into the action but you get the idea that the consolidation will continue.

If any one of the above scenarios happen then Ian Thomas will be proven right, when he said in 5 years web analytics will be everywhere and all web analytics software will be free. I disagreed with Ian in my response to his prediction, but I also did not deny the possibility of web analytics vendor aggregating the user data across sites and then using that to provide targeted advertising and in return providing the tool for free.

What do you think? Comments?


Side Note: The interesting thing is that IndexTool will become part of Yahoo!'s Strategic Data Solutions. Bassel was one of the co-founders of my ex-company digiMine (which is now called Revenue Science).

Google Analytics: Tips and Tricks – Why do some search keywords show 0 visits

Question 1: A visitor goes to Google searches for a keyword, come to my site views few pages then goes back to Google does another search and comes back to my site all within 30 minutes (same visit). Which keyword will get credit for the visitors activity?

Question 2: I see a lot of keywords with 0 visits and 0 page views in my Google Analytics keyword report. What does that mean?

Answer:
Google Analytics, assigns the visitors activity to the first keyword that drove visitor to the site and assigns only those pages to the keyword that were a direct result of the first keyword. Note: This test was done on Organic results only, I will look at the impact of paid search (PPC) in my future tests.
Let’s look at an example. I used SeattleIndian.com for this test.
Here are the steps that I took

1. Did a search on “SeattleIndian.com 0 pages” and landed on SeattleIndian.com via a click on search results.


2. Bounced back (viewed only 1 page) and went to Google (by typing in Google.com)
3. Did a search on “SeattleIndian.com 1 pages” and landed again on SeattleIndian.com via a click on search results.
   
4. Again bounced back (viewed only 1 page) to Google (by again typing in Google.com)
   
5. Did a search on “SeattleIndian.com 4 pages” and landed again on SeattleIndian.com via a click on search results


6. Viewed 4 pages and left.

Below is the Google Analytics report showing the activity.



As you can see one page that I viewed from 1st keyword “SeattleIndian.com 0 pages” get assigned to that keyword and it also gets the credit for visit. The other 2 keywords do not get the credit for the visit or the pages views. The other 2 keywords will show 0 visit and 0 page views.

So where do the page views associated with the other keyword go? Well, I don’t have an answer for that yet. I am still researching and will blog once I have an answer.

In next article I will discuss which keyword gets the credit for conversion if a visitor uses multiple keywords to come to the site and converts with one of the keywords. Is it the first keyword, 2nd keyword or the 3rd keyword that gets credit? (Assuming visitors used 3 keywords).

Video Analytics by YouTube

YouTube launches analytics for the video providers (user, partners and advertisers). According to Google Blog, this tool (service) called Insight will initially allow video providers statistics such as

• How often videos are viewed in different geographic regions


• How popular a video is relative to all videos in that market over a given period of time


• Data on lifecycle of the videos, like how long it takes for a video to become popular, and what happens to video views as popularity peaks

According to YouTube blog,
"We'll be making new features and additional information available fairly quickly -- like a specific breakdown of how viewers discovered the video"

YouTube videos are embedded in several sites and blogs, so it will also be nice to see what sites, blogs etc. are embedded the video on their site and on what pages.
Some bloggers, TV news and news sites are claiming that YouTube will track and show at individual level i.e. show the name, IP of an individual who watched the video. I believe that YouTube has such data (when you consider tying Google Accounts with YouTube) but I do not believe that YouTube will reveal that kind of information in the Video Analytics, as it could result in all sorts of privacy issues.

I expect Google (who owns YouTube) to integrate these services with Google Analytics. Not only will video providers able to see the stats mentioned above in one interface but all see the impact of videos and visitors driven by these videos on their site and hence make better decision for future video productions and promotions.

Thoughts? Comments?

Google Analytics Benchmarking Review

About a month ago, Google Analytics rolled out a new feature called “Benchmarking”.
This service shows how your website's statistics compare against other sites. The data used for this service is collected via Google Analytics from the sites that opt-in to use this service. In the beta release of this service, you are able to compare your site's Visits, Pageviews, Pages per Visit, Bounce Rate, Average Time on Site, and New Visits data against benchmark data from categories of other participating websites.

After a wait of few weeks, last week I was able to see the benchmarking data for the first time.

Benchmarking data is available under “Visitors” section of Google Analytics (See below).




As you can see above, this site rocked it had 386% more visits then the benchmark data. Actually most of the stats were better than the comparable sites. Does that mean we can open Champagne and celebrate??? Not so fast. Let’s look at what I was comparing to?

According to Google Analytics, I was comparing to “All sites of similar size”.

So what does “All sites of similar size” mean?

All sites are grouped together under three classifications: small, medium, and large based on number of visits each site receives. You can compare yourself to other similarly sized sites but not to sites in other size classifications.
I did not find it very useful since I don’t know what the range of the stats was. If the site I was looking was being compared to one or two page personal sites then sure this site will rock compared to the other site, not very helpful comparison though. I needed to compare to my industry vertical.

Comparing to a vertical

Google provide a list of site categories that are available for the site size (based on visits) your site falls into. However I was not sure which vertical to pick for this particular site. Some sites fall perfectly in one vertical but a lot of them do not fall into any one vertical, as was the case with the site that I was looking the data for. It would have been nice if Google had allowed me to see which vertical it was categorizing my site in so that I could have picked the same vertical.



I know this is only beta release and it will get better with new releases so now I am eagerly waiting for the next release so that I can get some meaningful stats.

What are your thoughts on this service?

Google Analytics: Tips and Tricks - Show Visitor Behavior from Specific Countries

Problem:
We need to see the online behaviors of visitors from USA and Canada using Google Analytics. In other words we need a profile which only has traffic from USA and Canada.

Solution:

1. Create a profile in Google Analytics in which you would like to capture visits from USA and Canada.
2. Create a filter that includes visits from USA and Canada only (described below).
3. 
   
4. Apply the filter to the profile that you would like to show the data in. (The filter is automatically applied to the profile that you use to create the filter).

Creating the filter to include US and Canada Traffic Only

1. Filter Name: Give a Name to your Filter.
   


2. Filter Type: Select “Custom Filter” and select “Include” in the radio button. We are creating a custom filter to include US and Canada Traffic Only.
   


3. Filter Field: Select “Visitor Country” as the filter field. Visitor country is populated based on the IP address of the visitors.
   
   
4. Filter Pattern: This is where you enter the country names. The small trick is with the format and finding out what to enter as the country names. In this case where I needed the visitor behavior from US and Canada, I used United States and Canada as the countries and my filter was
   (Canada|United States). () is required to group all the values together and | is used as on OR.
   So what this filter patter is telling is to match either one of the 2 values (Canada and United States) in the Filter Field (Visitor Country).
   
   
   Here is the final view
   
   
   

   Now the question is why did I enter United Sates and Not United States of America of USA or US?
   You need to enter what Google Analytics captures the country name as. To find out what you should enter in the country name, go to a profile that does not have any country filters. Go to Visitors --> Map Overlay and scroll down to see the names of the countries. Use the name exactly as it shows in this list.
   
   
   

More Google Analytics Tips.

Comments? Questions?