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This article is about how to get a clean list of externally referred sites, where site traffic is not contributed from email related domains, marketing campaigns, direct traffic, etc.

The referring sites report under "Traffic Sources" describes how people referred from other sites, but if you really want to separate out various marketing channels (email, image search, partner sites, etc.), you may want to set up some filters. Basically segment your data to only look at this traffic source group.

The purpose of filtering out any referring domains relating to non-marketing channel is to really understand which web sites are contributing traffic to your site. And these referring sites are directing traffic to your site for either two reasons, which are either good or bad.

The good reason is your site is so good, that other sites couldn't resist putting up link(s) to your site. That results from this should be really great because it has the potential to boost your PageRank in Google, increase your sites or products awareness, contribute increase in revenue or orders, etc.

Although, additional links for other sites are good, there could be bad reasons, too. Extreme case is getting links from phishing/scam/spammed sites, which could bring down your quality score. Other reasons are, people are talking bad about your site/services/products/content, and sites are referencing to your site. Hopefully the anchor link doesn't say something irrelevant to your site...

Some of the key metrics to observe from these referring sites are similar to looking at your traffic source metrics. Visits, Pages per visit, avg time on site, bounce rate, desired outcomes (conversions), order, revenues, etc.

How to set up a filter or create a segmentation so that you can narrow your report to non-marketing channel - referring sites:

1) Go to "Advanced Segments" > "Create new custom segment"

2) Use "Source" dimension from the dimensions selection list, and use "Does not contain" expression. Enter values such as "mail", "google", or any domains associating to your partner sites, affilicate sites, etc.

3) Use "Medium" dimension and select "referral" to make sure you're working of data set coming from Referring Sites report.

Now that you have a custom segment that with cleaner data set representing non-marketing channel referring sites, you may find something interesting about those traffic sources.

Enjoy!!

I had to create a post talking about this wonderful article from Justtin Cutroni (@justincutroni)at epikOne.

Justin posted an article on March '09 -- Integrating Google Analytics with a CRM

Basically, there is a configuration you can do on javascript so that you can capture Google Analytics values and throw it into forms, CRM, or other areas of datasets.

According to his explanation, you have to use javascript to extract data from Google Analytics, store it in hidden form elements, and attach it to the form when users hit that submit button.

Why this is a great idea? Well, a lot of simple sites, including my my site have a contact form, but it only parses the data entered by the users and other necessary values to make the parsing work properly (behind the scene).

Taking my contact form as an example, it only captures "Name", "E-mail", "Interest", and "Comments". Now with Justin's suggested configuration, you can pass along various Google Analytics values:

- Source (Possible campaign sources are Banner ad, Search PPC, Link Exchange, Newsletter, etc.)
- Medium
- Term
- Content
- Campaign Name
- Custom segmentation
- Number of visits

Wow... ok, what this means to me or you is that you can optimize the contact form to acquire not only the values we asked from the users, but all of these values from Google Analytics.

That means on an individual level, for example, I can tell Mr. ABC came from Google PPC, with the term "web analytics specialists", and had 4 visits before contacting me.

Some may say, you can do that in the Google Analytics tool. Well, you got to slow down and be careful about that comment. Note that it is against the Google Analytics terms of service to capture individual identity information.

That is why it is nice to see that Google Analytics data integrating directly to forms, emails (in my inbox), into external CRM database, etc.

For those who are running enterprise level CRM suite, this is probably a joke considering that those CRM solutions can dynamically capture way more data and perform segmentation. But for small sites, bloggers, or micro-sites running Google Analyitcs, I feel like this has opened a door to a new level of thinking in site tracking using Google Analytics.

Google Analytics has variety of reports to analyze different kinds of metrics (visits, page views, time on site, traffic source, conversions, geographic location of visitors, visitor loyalty, etc.). The most significant function of the analytics tool is to measure, identify potential area of improvements, bring actionable recommendations, and report the key performance indicators (KPI).

Google Analytics support e-commerce site, and the reports from e-commerce is really helpful in a sense that it can tie the metrics in terms of dollar value. It provides an insight into the e-commerce activity on your website, and better understands the success of your e-commerce site. Conversion rate, average order value, revenue, transactions are some of the main reports of this section that determine your website activity.

There are reports for various sections which include traffic (visitors), traffic sources, content, goal conversion, and e-commerce. The reports under these sections could be added to you dashboard to get an overall look, in one screen, at the metrics that matter most to you.

Google analytics has recently introduced the customs reports. They are those reports, which you create, save and edit to give you a specific view of the data. With the help of these, you can determine which information and metrics you want to see. You can organize them in the way you want to highlight the relevant data by using drag and drop interface. You also have the option to create a tab if you want to see related data in other dimension of metrics. In addition, when you create the custom report, you'll have the option in creating a drill-down or multiple levels of sub-reports, by selecting the sub-dimension.

Certain features and functions of Google Analytics reporting that are very useful that I recommend you to take full advantage of:

• Export: Google Analytics has an export feature that allows you to download the reports in PDF, XML, CSV, and TSV. Certain reports may only allow PDF or XML. These downloads will give you the flexibility to cater the reports to your users in different ways. You can pass along the PDF file without altering it, or pass XML into other reporting tools in a form of data-feed, or manipulate CSV file and enhance the reports/charts as you wish.
• Time frame: Setting the time frame is one of the most important feature when reporting out of Google Analytics, because you able to select your reporting period grouping the data by day, weeks, or months. It is easy to select the day, date or month you desire by the calendar interface. You can also compare a date, date range to another date, or date range by choosing the "compare to past" option. This helps you to know the performance trends on your site before and after a change made on your site or landing pages. The interface also provides you with a timeline feature, which shows you a bar graph of visits over time. A particular range can be selected which gives you a graphic representation of the fluctuations in your report.
• Email: This is a great feature when you want to share your data, reports, or dashboards to certain people by email. You can send a report instantly or schedule the report run and email it on a daily/weekly/monthly/quarterly basis. If you are sending out to a group of users, you may want to consider creating a group account email address so your IT admin can control the email list when a member leaves the company or what not (Google Analytics will only have that one group email address set).
• View/Chart options: There a several options to represent the data in various ways. Some options are ordinary table view, pie chart, bar graph, etc. Most reports contains a pie chart, a basic table vie and bar graphs. An extra highlight is the trend graph that is in default mode in most of the reports. It gives you a snapshot view of your site's performance for various data points like conversion rate, bounce rate , visits etc.
• Dashboards: a dashboard is a collection of various reports. You can add a favorite report on your dashboard for a quick look into the site performance. It shows you a snapshot view of the reports that is customizable. Handy and quick access to your entire data of your favorite reports is the greatest advantage of dashboards.
• Advanced segmentation: It is the recent development of Google Analytics, which help you to segment the data to get a better insight into it. I recommend setting up advanced segmentations and utilize the segmentations against the custom reporting to take advantage or your useful reports with meaningful metrics to you.

Some advanced segmentation I've set up when the feature was first enabled were, Engaged Audience and Not-Engaged Audience segmentations. This is simply to show the difference in performance from those two segments against the reporting metrics you choose to run. Engaged Audience will defer for all of you, but you can say, visitors who did not bounce and spent on your site more than the one minute, and had 4 page views per visit. Not-Engaged Audience could be visitors who bounced and spend on your site less than 30 seconds (this is just an example). When you use these segmentations against your traffic sources or site sections, you'll definitely gain some great insights.

"RSS is a family of Web feed formats used to publish frequently updated works such as blog entries, news headlines, audio, and videos in a standardized format. An RSS document (which is called a "feed", "web feed", or "channel") includes full or summarized text, plus metadata such as publishing dates and authorship. Web feeds benefit publishers by letting them syndicate content automatically." (1)

So for you bloggers and website owners out there, who are using Google Analytics and wish to track your site traffic from RSS or Atom feeds, try the following steps:

1. Identify your template within your blog CMS tool where the RSS or Atom feeds are generated.
2. Use Google's link builder tool to create the query parameters to attach at the end of your URL defined in the XML file. For example: http://www.zoommetrix.com/rss.xml?utm_source=RSS_Feed&utm_medium=RSS&utm_campaign=RSS_Syndication
3. After you set the query parameters into your URL within your xml file, publish or refresh your xml file.
4. If you get an error, you may want to change "&" to "&" so that the browser can render the entity properly.
5. Access your Google Analytics report, and go to Traffic Sources > Campaigns. You should be able to get the traffic data attributing to people who visited your site via RSS or XML feeds.

(1) Reference: http://en.wikipedia.org/wiki/RSS_(file_format)

KPIs mean key performance indicators. They are defined as business metrics (units of measure) that enables your organization to define, evaluate and analyze its progress towards organizational goals. KPIs do possess a signifying place in web analytics. Each website is created with certain objectives to be attained within the given time span.

KPIs provide a detailed data of the nature of our progress towards achieving the objectives of the organization. It will help us to re-establish our goals according to the analytics report of the KPIs.

It depends upon the nature of your site to select the significant KPIs. The basic KPIs in Google Analytics are covered in detail here. It is important to note that the KPIs that work for a particular site may not work for another site.

If you are looking for a general definition of KPIs supported by the Web Analytics Association, refer to Website's KPI Examples and Definitions - Basics

Number of visits
It studies the number of visits on a site over a specific time period. Most people analyses this KPI on a regular basis. The best practice is to set a target for this KPI, say, for over a period of one month. Try to improve your marketing strategy to achieve your aimed web traffic for the fixed period. This KPI is related to the web traffic and the majority of the web business is much concerned about its value. You should give your maximum talent to increase the value of this KPI to meet your targets. Give more attention to the trends in the visitor numbers in relation to your targets.

Pageviews
Pageviews is the total number of pages viewed on your site and is a general measure of how much your site is used. It is more useful as a basic indicator of the traffic load on your site and server rather than as a marketing measure.

Absolute Unique Visitors
"Absolute Unique Visitors" is how many visitors (people) came to your site, counting each person only once for the entire time period. Google Analytics seem to use IP adresse + User Agent + First Party Cookies to identify a visitor. Unique visitor is an ultimate measure to reflect the number of people that visited your site.

Bounce rate
Bounce Rate is the percentage of single-page visits (i.e. visits in which the person left your site from the entrance page). Bounce Rate is a measure of visit quality and a high Bounce Rate generally indicates that site entrance (landing) pages aren't relevant to your visitors. You can minimize Bounce Rates by tailoring landing pages to each keyword and ad that you run. Landing pages should provide the information and services that were promised in the ad copy.

High bounce rate means that the visitor was not attracted by the attributes of your site and visitors retracted their steps. The satisfaction of visitors is what matters here most. The main reason for this phenomenon is inappropriate content according to their taste on the landing page, unalluring design and technical problems.

It is clear from the above description that lower bounce rate is the indication of the success of your online marketing strategies. Your website is functioning in the best possible way according to your best efforts. Try to analyze the data of the bounce rate based on the trends in a given period of time rather than on daily basis, and by content or pages. A point to be noted here is that higher bounce rate does not always show a poor website performance. For example, in the case of blogs, a visitor may be directed to your website to read only a particular article in a particular page.

Time on site
Time on Site is one way of measuring visit quality. If visitors spend a long time visiting your site, they may be interacting extensively with it. However, Time on Site can be misleading because visitors often leave browser windows open when they are not actually viewing or using your site.

Conversion rate
For a non-ecommerce site, Conversion Rate is the primary metric for assessing how well marketing, site, and content work together to achieve business objectives. Conversion Rate is the percentage of visits that result in the visitor taking an action that you have defined as important to your business.

Every website is created with a pre-defined goal. It may be of various natures such as to contact the organization, to fill in a registration form or to purchase a product. In the case of blogs the goal may be to subscribe to the RSS feed. Thus, goals differ.

Conversion rate is an effective KPI that help to monitor the goals of the website. It is the rate at which the visitors take your goals or positive measures. If you have a high conversion rate, then it indicates that you have made a considerable amount of customers act according to your wishes in your website. To manage a high conversion rate your site should have the perfect mix of quality web traffic, an excellently managed customer experience or the right product offerings as a business.

The conversion rate KPI extracts the best value of such good measures. Google Analytics provide you with enormous stats of all the factors that affect the conversion rate. If you make improvements to your customer experience, your conversion rate will really improve. Blaming your low conversion rate on low traffic volume or the particular period of the year is bad practice.

Traffic sources
Google Analytics traffic sources report provides an overview of the different kinds of sources that send traffic to your site. The graph shows traffic trends; the pie-chart and tables show the traffic sources driving the trends. "Direct Traffic" is visits from people who clicked a bookmark to come to your site or who typed your site URL directly into their browser. "Referring Sites" shows visits from people who clicked to your site from another site. "Search Engines" shows visits from people who clicked to your site from a search engine result page.

Now, search engines marketing is on the top list of online marketing. Most of the organizations try hard to move up the search engine rankings for a better web traffic. This KPI will analyze the nature of the sources from which your web traffic has arrived on your sites. Depending entirely on search engines is a risky thing. If we depend on search engines for 90% of web traffic, then think about the day, suppose, when Google modify their algorithm or may remove your company from their database. This will put a sudden stop to your major revenue share. Therefore, it is better to increase your traffic from all sources including the small traffic sources over time. It will help you to stand in the long run. Make sure that your Google Analytics report of traffic sources should not show any source of traffic dominating for a long period, unless it is part of your strategies.

Keywords data shows the actual keywords used in search that referred traffic to the site. Additionally, Google Analytics is capable of segmenting the keywords by paid, non-paid (organic), and overall. Carefully monitor how your added or changed content affects the keywords searched over a period of time.

E-commerce
Google Analytics is great for tracking e-commerce transactions. There are various KPIs under e-commerce report, and it will help you measure your site's success to your revenue and sales over time.

Here are some KPIs under e-commerce are:

Total Revenue: Revenue is determined by the number of purchases and the average purchase value. Some important steps you can take to maximize revenue are:

Purchase targeted advertising and write effective ads (see the Traffic Sources reports)
Make sure your landing pages show the information, services, or products that you promise in your ads (review the Content reports to help minimize bounce rates)
Simplify your conversion funnels so that fewer would-be customers abandon the checkout process (review the Goals reports)
Conversion Rate: This report shows the rate at which visits to your site result in purchases. Tracking conversion rates over time is an effective way of determining whether your marketing and website are becoming more or less efficient at turning visitors into customers. Note that conversion rates are most useful as company-specific benchmarks against which to assess marketing and site effectiveness because conversion rates vary considerably across businesses (even within the same industry).

Average Order Value: Tracking changes to the average order value over time is important to catalog sites that may change and shift which products and services they are actively marketing. Many ecommerce sites monitor this metric to see if cross promotions are working. This is an important metric that works its way into many higher level executive and shareholder reports.

Product Overview (Product Performance): How much of each product do you sell? This report shows the number of items sold, the total revenue, the average price, and the average order quantity for each product you sell online. Click any SKU to drill down and view detail.

Product SKUs (Product Performance): This report shows the number of items for each SKU sold, the total revenue, the average price, and the average order quantity for each product you sell online.

Categories (Product Performance): How much of each product category, product, and SKU do you sell? For ecommerce sites, understanding which products are selling online is crucial for generating relevant content, promotions and advertisements. This report shows the number of items sold, the total revenue, the average price, and the average order quantity for each product you sell online.

Transactions: This report is a list of all transactions on your site, useful for auditing your transactions.

Visits to Purchase: How many visits does it take for visitors to purchase? Understanding your sales cycle is important to the overall success of your site. This report helps you understand how many visits it takes to convert your visitors into customers and, by extension, the kind of content you need to create in order to reach your prospects.

Time to Purchase: How long does it take before visitors make a purchase? Understanding your sales cycle is important to the overall success of your site. This report helps you understand how long it takes to convert your visitors into customers and, by extension, the kind of content you need to create in order to reach your prospects.

KPIs are a revelation in the sense that they inform us about our success or failures in our path to achieve the objectives. KPIs are the main criteria for determining the website activity and help us to take the necessary steps for boosting up the online marketing initiatives.

I hope you acquired a better understanding of these KPIs from Google Analyitcs to make your site better and successful.

Reference: Google - http://www.google.com/support/analytics/

If you are always on the lookout for the best practices in web analytics, then here is an article that will satisfy your heart's desire.

Before installing Google Analytics, you should have a discussion with your IT team and key business stakeholders, and sort out all the matters regarding the subject. You should have a better idea at the end of your discussion about the following points:

• Whether your site have multiple domains.
• Whether your site have multiple sub domains. You should be able to distinguish between multiple domains and multiple sub domains.
• Whether you should be provided with the reports of all of your sub domains packed up into a single report or separately.
• Whether you prefer to discard internal traffic from your web analytics report.
• You should also be aware of the default document of your site.
• Also select the four most important web pages in your site, visiting which can be concluded as a successful visit.

Through an in-depth discussion with your teams all the details regarding the above should be clearer. Now let us look at how to set up an account and the best practices involved in using Google Analytics.

1) The first step is to create a new Google Analytics account. If you already have a Google account, then it is a bit easier. In addition, it would nice to integrate your ad words account (if have one), since it can be linked up to analytics account on an account to account basis. If you do not have an analytics account, then never mind, you can sign up in the Google analytics site.

2) The next step is to configure the profiles created. Even after you sign up, nothing is configured yet and so it is your task to edit the account. In order to configure your default document, you should know the default document of your site. The earlier session with your IT team will come for your rescue here.

3) Create the required filters: In order to segment the data of web analytics create filters according to your requirements. For example if you have multiple sub domains, then create a filter, which makes it easier for Google to recognize your multiple sub domains. If you want to discard internal traffic, then create a filter for such a requirement. The recommended thing is to create an additional profile with the above-mentioned filter. This is better than applying your external traffic filter to all of your profiles because this won't let you know the quantity of internal traffic contributing to your key metrics.

4) Configure your goals: If you don't pre-plan your work in Google Analytics, then it will consume your time. A good insight about the concerned subject really helps us to work better with Google Analytics. In order to create goals, consider the criteria for a successful visit in terms of your monetary gains. For example, for a successful visit in a particular site, the criteria may be whether the visitor signs a newsletter or e-mail an article to a friend. Make the possible ways to connect your goals with actual pages on the site. After setting up the criteria, Google will help in configuring your goals.

5) Tag your pages: If your site is a single domain, then it is not needed. You just have to copy the codes provided by Google. If your site possesses multiple domains, then tag your pages, which will help you track the web traffic.

6) Tag all pages: The main problem with Google Analytics is that it may not be able to track all your pages. It is a much harder task to accomplish. Therefore, you should make it clear that you tag all your pages. All of your pop-up pages and all your external pages should be tagged. The main problem if you don't tag these pages is that if you set your goals against these pages then these pages will not be tracked for your web analytics task. Therefore, it is better to tag all your pages and avoid pitfalls.

7) Tags should be placed at the bottom of the pages. They should not be placed at the top or in the header or any other place. This is the best practice of using tags in web analytics. However, lately, there are analysts who recommends putting the tracking after the header, since some custom tracking requires the .js file to be called prior to custom tracking. Check out your requirements and technical implications with your IT team.

8) Tags should not be placed inside borders, tables, or frames. The correct position of tags will help you to get a precise data for your reports.

9) Should have knowledge about your unique page identity. Now websites have become more dynamic in the way they react to specific customers and how they personalize content. Know about the combination of file name and criteria that give your page its unique identity and make your web analytics tool more effective by providing it with this valuable information.

10) Make the intelligent use of cookies: Three types of information are collected by your Google Analytics tool. They are mainly source attributes, page attributes and user attributes.

Source attributes is mainly concerned with the path of your visitors to your website, i.e. whether they have entered your site from other websites, campaigns or search engines.

Page attributes looks at the quantity and nature of pages consumed by your visitors. User attributes is concerned with the identity of your visitor, i.e. if they have logged in or not.

User attributes are stored up in the cookies. Your tags will help you to read the information collected in your cookies much easier. Therefore, you should use your cookies intelligently.

11) Overcome the problem of JavaScript wrapper: Normally the links on your site are covered up in JavaScript. Due to this, if you want to know the click density, you might not be able to get the number of clicks in the report due to JavaScript. So the best practice is to use JavaScript wrapper only when you can't absolutely avoid it.

Advanced segmentation is a new tool introduced in Google Analytics to help us to have a detailed analytics data with a greater precision within seconds. Earlier filters were generating the data regarding web traffic. Through filters, it was possible to accumulate large amount of information. However, it took considerable amount of time to filter out the right kind of information from the large data basis. It was a time consuming and dreadful task. Now it has become very easy and convenient.

How to create advanced segments

Google Analytics always had great segmentation capabilities. However, the task needed sophisticated thinking to segment the data. When filters were used, it was a hectic job to create different filters for each profile. With the help of advanced segmentation, the segment created can be used in multiple profiles. Moreover, advanced segmentation is completely at your service. It is up to you to consider which types of visit you prefer to segment while you generate the data for a specific report.

By an analysis of the report provided by advanced segmentation, you can have quite a precise insight into the exact nature of web traffic in your site. It will help you to concentrate more on the weak segments and thus help you to increase the traffic as well as your income.

Advanced segmentation helps us to identify the prominent trends and common behaviour in web page traffic. Thus advanced segmentation is all set to challenge your dreams about the possibilities of Google Analytics.

Google has created a superb interface that helps you to drag and drop dimensions or metrics that you prefer to use in your segment. Advanced segments are of two types namely default segments created by Google and custom segments, which you could create. If you wish to segment a specific metric or dimension, choose the one, specify a value for the chosen metric or dimension and form a relationship between the two.

For Example:
If you want to analyze why certain visits last only for a few second, then create an advanced segment to view all the visits that has lasted only for ten seconds.
The next step is to choose the Time on site metric and drag it to the right position. You should also specify a condition for the above metric to meet and a value. Here, the condition is Time on site metric "to be greater than ten seconds". If you want to create a custom segment other than the default segments, you just have to type in your requirement and then click "create segment". The new custom segment is created which will help you with your specific requirement.

Another important feature of advanced segmentation is value field, which is a dynamic field that updates you with all your potential values while you type. It will provide you with all values collected for the metric or dimension used in the segment. We can add more metrics and dimensions to our advanced segment. When we apply it to a profile, the profile will be segmented. Thus, we can use the advanced segments in any profile. It helps us to improve our knowledge of how multiple campaigns, medium or geographic segments perform over time. A detailed study of the analytics and acting according to it can increase additional insights to the traffic behavior.

You can also test the segment you have created. It is a distinguishing feature of Google Analytics. You just have to click on the test segment and Google Analytics will search within the time limit you have chosen.

Before going into a detailed report of the working of advanced segmentation, let us consider two important concepts in analytics namely, dimensions and metrics.

Dimensions refer to the properties of site visitors or the visits created by them. Keyword, campaign are some examples of dimensions.
Metrics refer to the basic counts that take place on the website. Page views, visits, revenues and transactions are some examples of metrics.

How to create advanced segments

Potential usage of the new advanced segmentation

- It helps you to have an in-depth knowledge of the nature of visits in your website.

- It helps you to know how many visitors enter your site accidentally or by their preference and knowledge. We can call the second category visitors as loyal visitors. This helps us to analyze the types of pages the loyal visitors consume. You can know specific customer trends by creating an advanced segment.

- In a tech support site, you can know whether visitors have found the right tech support answer. If you want to know, whether visitors coming by grand keywords on a social networking site are loyal or not, it is also possible by advanced segmentation.

- Advanced segmentation helps you to know the segment of visitors was converted into potential goals. The key visits, traffic sources, content reports, etc.; all are at your fingertips. All these reports help you to increase your monetary gains.

- The best usage of advanced segmentation is that you could segment your most valuable customers. It is great advantage for all those people who do onsite business, i.e. who are always on the look out for potential buyers on their sites. You can study the new trends in customer visits, which make you capable to increase your site earnings.

- You can also identify your precious customers. In e-commerce, advanced segmentation is really helpful.

- Engaged vs. Not Engages Traffic: Set criterias that will separate the two types of visitors, and compare against each other to find additional insights to what and where are the visitors engaged or not.

Advanced segmentation helps you better understand the site visitors and it brings granular insights to what is happening on the site, so you can make better decisioins to optimize your site and strategies.

This post "Optimize Form Length with Input Analysis" by Allaedin Ezzedin is fantastic. It covers a trick on how to use Google Analytics to assess form entries, and obtain insights to which form input has the highest obstacle in completing the form process.

To summarize what needs to be done to achieve this in Google Analaytics:

1. Use javascript to validate the form when users click submit.


2. In validation, call the "pageTracker._trackPageview" if the values do not exist. For example, "pageTracker._trackPageview('/contact_us.htm/empty/'+field_name)" will show "/contact_us.htm/empty/phone" when the phone number field is empty during submission.


3. Set a specific profile for the form using Custom Filer (Filter Type: Include, Filter Field: Request URI, Filter Patter:contact form page, Case Sensitive: No) so the field name are filtered out of thousands of page views in main profile.


4. Go to the new Contact Us Profile -> Content -> Top Content to assess the form input.

In addition to this brilliant implementation, I would suggest using Google Website Optimizer to test different forms for better user experience and form completion rate.

Another thing I would think about is, if you're throwing some kind of validation message or redirecting the users to an error page, then track the % of users completing the form after landing to "reminder of miss entry" page.

Since there will always be users miss entering the information, regardless of how well you arrange the forms, it is always nice to go beyond that to see if your users are interested enough in completing the form even after their form was rejected. In that case, you should also be testing and optimizing the page when users miss enter the form.

Related Articles:
Landing Page Optimization 101 - LPO
Site Optimization - Using Google Analytics and Website Optimizer Together
Optimizing User Experience Using Web Analytics - Part 2
Optimizing User Experience Using Web Analytics - Part2

Related Link:
The Official Google Website Optimizer Blog: Thought Leaders

Wider Funnel: Three Tips for Creating Action Pages

VKI Studios: Google Website Optimizer - 5 Big Mistakes most first time users make

The Google Analytics' user defined report allows analyst to compare visitors from segments that you have defined. I will go through several types of segmentations that you could possibly set. You can define these segments by calling a line of code/function in your web page. So every time a page with the code is requested, a custom value is captured and stored in the user defined variable.

The main approach to execute this is to simply apply a code like this:
pageTracker._setVar("test_value");

As an example, one of the sites I work on has English and Japanese sections. Each section will have a value to identify its section, defined as "/viewed/english" or "/viewed/japanese".
Once you have these segmentations in place, you'll be able to see how users are behaving differently in each section.

Visitor Type Segmentation
This is a powerful segmentation to get an actionable insight to who is behaving differently. Let's say you have a form entry that leads to a confirmation page. Assuming the form has a field with values "Engineer", "Project Manager" and "Director", and when the form is completed, one these values will be stored into user defined variable.

At certain point, you may learn that Directors are likely to complete the form and convert. This will tell you something about your visitor that you didn't know.

Landing Page Segmentation
You may have custom landing pages to serve different campaigns or promotions. Identifying the landing pages through user defined report would be a powerful method to analyze effective landing pages or even its campaign effectiveness.

(Example 1) Say you have two different direct mails with different slogan or description. You can have two different friendly URLs set in each of the direct mail. Direct mail A would have a landing page A, and landing page B for direct mail B. When traffic and performance for landing page B performed better than landing page A, that could mean that the direct mail B's strategy was more effective than version A.

(Example 2) You can have one campaign with a landing page, but a page can receive traffic from other various sources. Setting two different landing pages and segmenting it through user defined variables can show you which landing page is more effective while testing various traffic sources.

A/B Test
Above examples can speak as an example for A/B test. Another example to perform A/B test is testing different call to actions (CTA). Say you have two links; one with an image link and other as a simple text link.

You may distinguish these different CTAs (or possibly link type, position, etc.), and store it into user defined report to assess which criteria performed better.

Referrer Segmentation
Google analytics has a sophisticated campaign tracking method. However, you can choose to use user defined report to parse certain attribute within URLs and apply it to the report. One possible example of such application would be an existing links with identifier in the URL (not compliant to Google's campaign tracking), where the links are located in two different sites.

Site abc.com with a link "yoursite.com?source=123"
Site xyz.com with a link "yoursite.com?source=456"

Your landing page could parse these source codes and allocate proper value to a segment. Therefore you should be able to assess the referrers' performance and its effectiveness.

Useful links:
How can I classify my visitors according to what pages they visit on my site or what their responses on a form are?

How you start is as important as you finish.

Google released a new version of its Google Analytics tracking code in December 2007. The new tracking code is referred to as "ga.js"

The new tracking code is a complete rewrite of JavaScript inherited from Urchin analytics. This is the first time the two products have been decoupled. The previous version of the Google Analytics tracking code is referred to as "urchin.js", and it is suppose to work until the end of 2008.

Going forward, Google will only release new features on the new "ga.js" tracker. Therefore, it is recommended to upgrade your tracking code to the new version.

What's new?

• The new Google Analytics tracker supports proper JavaScript name spacing and intuitive configuration methods.


• Some test shows that it has a faster execution while the size of ga.js is minimized.


• Makes advanced features a lot more accessible.


• Track a page on multiple Google Analytics accounts.


• The new event tracker lets you segment a set of related actions.


• E-commerce tracking is improved.

Articles associated to this topic:
Announcing new graphing tools, ga.js tracking, and six new languages
Google Analytics Tracking Code Migration Guide

In order to track subdomains within the same profile as the primary domain, you will need to add an extra line in every pages with the tracking code.

Assuming your primary domain is ".your-site.com"
Following is the line you will need to add:
pageTracker._setDomainName(".your-site.com");

For example, it will look like this...

<script type="text/javascript">

var pageTracker = _gat._getTracker("UA-xxxxxx-x");

pageTracker._setDomainName(".your-site.com");

pageTracker._initData();

pageTracker._trackPageview();

</script>


As a result, Google Analytics will throw the following results for each of these URLs.

• www.your-site.com/default.html --> /default.html


• shop.your-site.com/info.html --> /info.html

If you want to distinguish between your subdomains, you'll need to create an "Advanced Filter" for your profile.

Filter Type: Custom filter > Advanced Field A: Hostname
Extract A: (.*)
Field B: Request URI
Extract B: (.*)
Output To: Request URI
Constructor: /$A1$B1

Now, the results for the above examples will look like:

• www.your-site.com/default.html --> www.your-site.com/default.html


• shop.your-site.com/info.html --> shop.your-site.com/info.html

Related Articles:
Google Analytics - Linking Across Different Domains
Analytics Tracking and Reporting Online and Offline Campaigns
Overview of Implementing Google Analytics Tracking Codes

Tracking your source of visitors is very important, and Google Analytics's campaign tracking allows you to measure your success from various sources. Possible area of investments that could be done in traffic driving initiatives are; banners, e-mails, link exchange, offline to online via friendly URL, etc.

Before you implement the tracking information into the URI, think through of the following data elements. Source, Medium, Name of the Campaign, Content, and Terms (if PPC).

Campaign Source
Obviously, the source is required to identify where the traffic is coming from.
What to use: utm_source
Example: Craigslist, Newletter-May2008, AdWords_PPC, etc.

Medium
Medium is to identify the medium of the campaign that it resides on.
What to use: utm_medium
Example: E-mail, CPC (cost-per-click), Banner

Campaign Name
Assign campaign name to identify a specific promotion or strategic campaign
What to use: utm_campaign
Example: Summer sale, XYZ Product Sale, Free T-shirt Campaign

Content (optional)
Used to differentiate ads or links that point to the same URL. Likely used for A/B testing.
What to use: utm_content
Example: image link, text link

Term (optional)
Used for paid search. It will identify the keywords used for the ad.
What to use: utm_term

The result could look something like this:
http://www.XYZ.com/product.html?utm_source=NewsLetter_001&
utm_medium=Email&utm_campaign=Monthly_ProductPromo_NL

Google provides a URL builder tool that makes this process very easy.

The interesting thing about the Google Analytic's campaign logging is that it reads the client's first-party cookie, and it increments the session counter in the cookie. Therefore, Google Analytics knows the original referral. So this allows Google Analytics to do multi-session tracking. Good stuff!

Since you want to know your ROI on your effort of the campaigns and promotions, you probably don't want to forget to set up the goal or conversion data in Google Analytics. That will tie the source to conversion and close the loop of your ROI analysis.

There are two ways in approaching tracking the website across multiple domains using Google Analytics.

First, note the difference between "multiple subdomains" and "multiple root domains".

Example of Multiple Subdomains
www.example_site.com
and
blog.example_site.com

Example of Multiple Root Domains (two different domains)
www.example_site.com
and
www.example_store.com

How to track the subdomains of the website in one profile

1) You can track subdomains within the same profile as the domain by addin an extra line into your tracking code (in bold).

NEW CODE (ga.js)
var pageTracker = _gat._getTracker("UA-xxxxxx-x");
-> pageTracker._setDomainName("example_site.com");
pageTracker._initData();

OLD CODE (urchin.js)
_uacct = "UA-xxxx-x"
-> _udn="example_site.com";
urchinTracker();

Keep in mind that this will allow you to track subdomains within one profile, but you may not be able to distinguish between pages coming from the main domain versus the subdomain.

2) If you need to distinguish between the subdomains, advanced filter for your profile needs to be set.

For Example

Filter Type: Custom filter > Advanced
Field A: Hostname
Extract A: (.*)
Field B: Request URI
Extract B: (.*)
Output To: Request URI
Constructor: /$A1$B1

How to track the site across multiple domains

1) You need to add the following lines (in bold) to your Google Analytics tracking code.

NEW CODE (ga.js)
var pageTracker = _gat._getTracker("UA-12345-1");
-> pageTracker._setDomainName("none");
-> pageTracker._setAllowLinker(true);
pageTracker._initData();

OLD CODE (urchin.js)
_uacct="UA-xxxx-x"
-> _udn="none"
-> _ulink=1;
urchinTracker();

2) Next, you will need to add the _link function to any links between the domains.

Example for new ga.js :
.. href="http://www.example_store.com"> onclick="pageTracker._link(this.href); return false;"...

Example old urchin.js :
.. href="http://www.example_store.com"> onclick="javascript:__utmLinker(this.href); return false;"...

3) If you send information between domains using forms, you'll need to apply the following.

Example for new ga.js :
.. action="http://newdomain.com/form.cgi" onSubmit="javascript:pageTracker._linkByPost(this)"

Example old urchin.js :
.. action="http://newdomain.com/form.cgi" onSubmit="javascript:__utmLinkPost(this)"

4) The data in the report will only include the request URI and not the domain name. If you want to see the domain names, then you need to create an Advanced filter for your profile.

Filter Type : Custom filter > Advanced
Field A : Hostname Extract A : (.*)
Field B : Request URI
Extract B : (.*)
Output To : Request URI
Constructor : $A1$B1

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Recently, Google Analytics has introduced a benchmarking (beta) option that shows how the website's statistics compare against other industry verticals. Currently (at the time of this writing), the available metrics you are able to compare are Visits, Pageviews, Pages per Visit, Bounce Rate, Average Time on Site, and New Visits.

I've tested it against my wife's blog site regards to "Graphic Design & Publishing" verticle. What I've noticed is that the Google's benchmarking data starts to appear from February 09, 2008.

It could be a temporary thing, but based on what I observed, it is best to check when the benchmarking data appear and use that starting date as the first point of comparison.

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Once, I've updated the date range for better comparison, following result appeared. (She has been slacking on updating her blog recently...). One thing I've learned is that recent optimization for SEO done on her site actually seemed to work. Maybe I should start writing about SEO...

I was surprised to see her site perform +327.5% better than other similar sized site in her verticle.

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As Google Analytics is probably the most popular free web analytics tools out there. To support web the analysts, it would be important for me to cover and share the findings with you.

One of the thing I've noticed recently is that Google Analytics have introduced their new tracking code in 2007. According to their migration guide(www.google.com/analytics/GATCmigrationguide.pdf), the original urchin.js will continue to function for at least a year after the new version is released. Which means sometime in 2008.

The benefit of the new tracking code is:
- Easily customize the tracking code for the site's need.
- Conveniently set up e-commerce and cross-domain tracking.
- Quickly enjoy new features and reports as they roll out.

There are a lot of custom trackings that could be done by utilizing the tracking code which a lot of it is listed out in the document. Following are some of the examples:

- Tracking virtual page views
- Tracking downloaded files
- Tracking a page in multiple accounts
- Tracking subdomains
- Track a visitor across domains using a link
- Track a visitor across domains using a form
- E-commerce transactions
- Adding organic sources
- Segmenting visitor types
- Restrict cookie data to a subdirectory
- Control data collection settings
- Control session timeout
- Control campaign conversion timeout
- Custom campaign fields
- Using the anchor (#) with campaign data
- Setting keyword ignore preferences
- Control the data sampling rate
- Using Google Analytics and Urchin

It is important to follow what is Google is doing with their analytics solution since they are continuously rolling out changes to their system. One best way to follow is checking out their blog and discussion forum.

Google Analytics Blog: http://analytics.blogspot.com/

Google Groups: http://groups.google.com/group/analytics-help