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Google analytics-individual-qualification


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  • As time allows I'll be posting other links and content here that you can use to prepare for taking the GAIQ. My score? I received 92% on Google Analytics Qualified Individual exam and you can too. A passing score is now 80% and for people who aren't technical study Regular Expressions in detail, b/c there's questions on the exam.

    As mentioned in my Slideshare study guide these are the places to start:

    Google Analytics Channel on YouTube:
    Conversion University:

    Marc Joffe
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Google analytics-individual-qualification

  1. 1. Google Analytics Qualified Individual Study Guide Mass Media Marketing @joffemarc @massmediamarket Marc Joffe 1
  2. 2. Introduction It is my hope that the following material will help others pass and understand the content in the Google Analytics Qualified Individual Exam. Credit goes to Google for providing and excellent source and wealth of material to understand how to use their web analytics effectively and ultimately help our clients measure their traffic. Conversion University has provided the majority of content found in this study guide. For more information please review the material on Google at or Google “Conversion University” And Good Luck! Marc Joffe, November 11, 2010 2
  3. 3. Index Installing the Google Analytics Tracking code Goals in Google Analytics ECommerce Tracking Profiles in Google Analytics Filters in Google Analytics Regex in Google Analytics Domains & Subdomians Event Tracking & Vitual Pagviews Segmentation (Custom Visitor Segment Variable) Additional Customizations Campaign Tracking &AdWords Integration Time Metrics Cookies and Google Analytics 3
  4. 4. Accounts in Google Analytics: • In this lesson, you will learn: 1. how to create, manage, and delete accounts 2. best practices for managing accounts 3. when to create profiles 4. how to create, manage, and delete profiles ● First login takes you to the SETTINGS screen When you first login to your Analytics account, you’ll see the Analytics Settings screen. This is where you will manage the set-up and configuration of your account and profiles ● Manage configuration and setup up of accounts/profiles (My Analytics Accounts dropdown) ○ Wont see dropdown from AdWords Account ● Access to other Analytics accounts If you have access to multiple Analytics accounts, you can access each account from the My Analytics Account drop-down list. For example, if other administrators have added you to their accounts, you’ll see a list of those accounts in the drop down. Example: ○ etc... ○ news.massmediamarketing.cs When to create a new account? If you manage the analytics services for several websites which belong to different organizations, you’ll generally want to create a new account for each organization. ○ Manage multiple websites for different organizations you’ll create a new account for EACH organization ○ create a separate account for each organization you manage in analytics ● 25 Analytics Accounts per Google Username ex. ● Each Account can have a maximum of 50 Profiles ● Added as an Administrator to an unlimited amount of accounts ● Managing User Permissions - USER MANAGER ○ Must have Google Account to be added ○ SETTINGS - USER MANAGER ■ Admin - access to all reports AND can MODIFY SETTINGS 4
  5. 5. ■ Remember that an administrator has full administrative access to all profiles within the account. ■ If you manage the analytics services for several websites which belong to different organizations, the best practice is to create a separate Analytics account for each organization. ■ Otherwise, if you were to group all the websites of all the different organizations into a single account, any Administrators you created on the account would have access to all the reports for all the websites. ■ Not only would the administrators be able to see the reports of other organizations, they’d also be able to change analytics settings on profiles that don’t belong to them. ■ This raises the potential for an Administrator to accidentally edit -- or even delete -- another organization’s settings and data. ● Full access to all profiles within the ACCOUNT ● Access to ALL reports and PROFILES in ACCOUNT ● Can modify ACCOUNT SETTINGS ● PROFILES - FILTERS - GOALS - ADD USERS ■ User - Read Access to reports AND can’t modify Analytics SETTINGS - can limit viewing to RESTRICTED PROFILES ● If you want to change your e-mail login, create a new Google account. Add your new login as an administrator to your Google Analytics account. Remove old email from account. Profiles in Google Analytics: ● On your Analytics Settings page, you can see a list of the profiles that belong to the account you’ve selected. You’ll generally have a separate profile for every domain that you track. ● You might also have profiles that correspond to subdomains. Or you might set up a profile that only includes data for a filtered subset of traffic of one of your domains. ● *Profiles are very flexible -- they are basically just a set of rules that define what data is to be included in the reports. Here are some typical examples of profiles you might set up: ● Tracking Subdomains Separately: You might have a profile that only contains traffic data for a specific subdomain. ○ Set up a custom filter on the profile to return data only from that subdomain ● Tracking Sections Of A Site: You might have a profile that tracks only a certain part of a site or that only tracks a certain kind of traffic. ● Control Report Access: And you might have profiles each of which has a separate set of reports. You could give some users access to one of these profiles and other users access to another profile. The result would be that each user would only see reports that apply to them. 5
  6. 6. A profile consists of settings that define the reports that you see. These include user access, goals, and filter settings. ● When you create a profile, you have the option of creating a profile for a new domain or an existing domain. Below is a schematic showing an Analytics account with three profiles. The first two profiles are tracking domain A, and the third profile is tracking domain B. ● Notice the tracking code number for each profile. The longer number, represented by Xs, is the Google Analytics account number--all three profiles have the same account number. ● Next you see that Profiles 1 and 2 each have a “dash 1”, while Profile 3 has a “dash 2.” This smaller number is the property number. ● Profiles 1 and 2 are tracking the same domain and have the same property number. They can be referred to as “duplicate profiles.” ● Profile 3 is tracking a different domain, and has a different property number. Why would I create duplicate profiles? ● You might want to apply filters to your duplicate profile so that it contains a subset of data. So, for example, you might filter the data in Profile 2 so that it only includes AdWords visitors to domain A. ● In addition, you might want to give certain users access only to Profile 2. This has the effect of only allowing these users to see AdWords traffic to domain A. Admin Access 6
  7. 7. Can Add Profile - Can Edit Profile Edit Main website Profile Information Edit these setting: Default Page - E-commerce reporting - site search - Goals (20 Goals per profile), Filters, exclude query string parameters (session IDs) from reports that appear in the report interface. Deleting a profile deletes all historical data associated with it. Can’t be recovered. Filters in Google Analytics • In this lesson, you will learn: o when to apply filters in Google Analytics o how filters act on data o how to create custom filters o the differences between the different kinds of filters (i.e. exclude, include, etc) o how to filter Google AdWords traffic o how to use filters and profiles together to track certain kinds of traffic o best practices for using filters Filter Manager You can use the Filter manager to create new filters, to edit their settings, and to delete them. To apply filters to a profile, you edit the profile Google Analytics filters provide you with an extremely flexible way of defining what data is included in your reports and how it appears. You can use them to customize your reports so that data that you deem useful is highlighted in interesting ways. Filters can also help you clean up your data so that it is easier to read. Filters process your raw traffic data based on the filter specifications. The filtered data is then sent to the respective profile. Once data has been passed through a filter, Google cannot re-process the raw data. That’s why we always recommend that you maintain one unfiltered profile so that you always have access to all of your data. There are two types of filters in Google Analytics – predefined filters and custom filters. Predefined Google Analytics provides three commonly used predefined filters -- you’ll see these filters under the “Filter Type” drop-down when you are creating your filters. 7
  8. 8. The first filter called “Exclude all traffic from a domain” excludes traffic from the domain that you specify in the Domain field directly below the Filter Type dropdown. If you apply this filter, Google Analytics will apply a reverse lookup with each visitor’s IP address to determine if the visitor is coming in from a domain that should be filtered out. Domains usually represent the ISP of your visitor although larger companies generally have their IP addresses mapped to their domain name. The second filter, “Exclude all traffic from an IP address”, removes traffic from addresses entered into the IP address field. This filter is generally used to exclude your internal company traffic. The third filter, “Include only traffic to a subdirectory”, causes your profile to only report traffic to a specified directory on your site. This is typically used on a profile that is created to track one part of a website. As a best practice, we recommend that you create a filter to exclude your internal company traffic from your reports. To do this you can use the predefined filter type called “Exclude all traffic from an IP address”. You will need to enter your IP address or range of addresses into the ‘IP address” field. Custom Filters – greater control In addition to the three pre-defined filters that Analytics offers, you can also create custom filters for your profiles. Custom filters offer you greater control over what data appears in your profiles. To create a custom filter, select “Custom filter” from the “Filter Type” drop-down. Additional fields will appear when you choose this option. Each custom filter has three main parts. 1) The first part of a custom filter is “Filter Types”. There are six filter types available and each one serves a specific purpose. We’ll look at these in a minute. 2) The second part is the “Filter Field”. There are numerous fields you can use to create your filter. Examples of some commonly used fields are the “Request URI” and “Visitor Country” fields. All the categorie are in this one... 3) The third part of a custom filter is the “Filter Pattern”. This is the text string that is used to attempt to match pageview data. The pattern that you provide is applied to the field and, if it matches any part of the field, it returns a positive result and causes an action to occur. You’ll need to use POSIX Regular Expressions to create the filter pattern. Learn more in the module on Regular Expressions. 8
  9. 9. Here’s a chart that describes the filter types. Exclude and Include filters are the most common types. They allow you to segment your data in many different ways. They’re frequently used to filter out or filter in traffic from a particular state or country. Lowercase and Uppercase filters do not require a filter pattern, only a filter field. Lowercase and Uppercase filters are very useful for consolidating line items in a report. Let’s say, for example, that you see multiple entries in your reports for a keyword or a URL, and the only difference between the multiple entries is that sometimes the URL or keyword appears with a different combination of uppercase and lowercase letters. You can use the Lowercase and Uppercase filters to consolidate these multiple entries into a single entry. Search and Replace filters replace one piece of data with another. They are often used to replace long URL strings with a shorter string that is easier to read and identify in your reports. example: Here’s an example of how you might use a Search and Replace filter. Let’s say that your website uses category IDs as an organizational structure. So, in your Top Content reports, you’d see a list of Request URIs that indicate the different pages on your site. The page “/category.asp?catid=5” is actually the Google Store Wearables page. You could make the Top Content report more meaningful by replacing “catid=5” with a descriptive word, like “Wearables”. 9
  10. 10. Here’s what the Search and Replace filter might look like. This particular filter would overwrite the entire Request URI with “Wearables.” This is a simplified example to give you an idea of how you can use filters. You can use Advanced filters to remove unnecessary data, replace one field with another, or combine elements from multiple filter fields. For example, a best practice when tracking multiple subdomains in a single profile is to append the subdomain name to the page names. You can do this by creating an advanced filter that appends Hostname to Request URI. Filters and Profiles You can track and segment multiple sites from the same Analytics account, using the same JavaScript code. And, once you’ve defined a filter, you can apply it to a single profile or across several profiles. So, for example, in the slide below, the graphic shows a single Analytics account with two profiles. Filter 1 has been applied to both profiles. Filter 2 has been applied only to Profile 2. 10
  11. 11. By setting up multiple profiles and applying filters creatively to each of them, you have a great deal of reporting and analysis flexibility. Again, you use the Filter Manager to create and manage filters. To apply filters to a profile, you edit the profile. By setting up multiple profiles and applying filters creatively to each of them, you have a great deal of reporting and analysis flexibility. Again, you use the Filter manager to create and manage filters. To apply filters to a profile, you edit the profile. You can also use profiles and filters together to create customized data views. Let’s say that you want to have two different views of your data -- one view includes only traffic to a subdomain and the other view only includes customers from a specific geographic region. To do this, you’d set up Profile 2 and Profile 3 as shown here in the chart below. 11
  12. 12. Or, for example, you might want to set up a profile that only inlcudes Google AdWords traffic. We’ll look at how to do this in the next slide. Remember, you always want to maintain a profile that contains all of your data. That’s Profile 1 in the chart. To set up a profile that includes only Google AdWords traffic, you need to apply the two Custom Include filters shown in the slide. In filter one, you’ll filter on campaign source for a pattern of google. In filter two, you’ll filter on campaign medium for a pattern of cpc. You can apply these two filters in any order. Let’s look at how you can use profiles and filters to track subdomains. Seperate Subdomians: If your subdomains are totally separate businesses, and you have no need for reports that include cumulative traffic to both, then you could simply create a unique profile for each subdomain. To do this, you’d install the “dash 1” version of your tracking code on your Subdomain A pages, and the “dash 2” version of your tracking code on your Subdomain B pages. 12
  13. 13. Across Both Subdomains: But what if you want to analyze the traffic aggregated across both subdomains? In this case, you could set up at 3 duplicate profiles. Then, you’d apply an Include filter to two of the profiles. Profile 1 includes all traffic to both subdomains. Profile 2 only includes traffic to subdomain A. Profile 3 only includes traffic to subdomain B. In this scenario, you’d install identical tracking code on every page of the site regardless of subdomain. Can’t go back: Remember, once your raw data has passed through filters, Google cannot go back and reprocess the data. So, maintaining an unfiltered profile provides you with a backup. You can apply multiple include and exclude filters to a single profile, but keep in mind that when more than one filter is applied, the filters will be executed in the same order that they are listed in your Profile Settings. In other words, the output from one filter is then used as the input for the next filter. If you want to include only users from California and Texas, you cannot create two separate include filters because they will cancel each other out. The solution is to create one filter that uses a regular expression to indicate that the Visitor must be from California or Texas. Adwords: If you drive traffic from AdWords to multiple sites, each of which is tracked in a separate Analytics profile, you’ll need to apply a filter to each site’s profile. Because, when you apply How is Cost Data applied? Campaign Target URL Cost data from an AdWords account, data from the entire account is applied to each profile - Google Analytics doesn’t automatically match campaigns to specific profiles. To illustrate what would happen if you don’t apply a filter, let’s imagine that you have two sites and you spend $50 to drive traffic to each of them. Without a filter, the Clicks tab on each profile would include $100 worth of cost data instead of just the $50 you spent for that site. So, for each profile that should include a subset of your AdWords data, you’ll need to create a custom include filter. In your profile settings, select “edit filter”. 13
  14. 14. Create a custom filter and select the Include filter type. For the filter field, select “Campaign Target URL”. *This field only applies to Google AdWords data. Use a regular expression to create the filter pattern based on the AdWords destination URL that is applicable to this profile. Once you’ve saved this filter, only AdWords data for this profile will be displayed in the reports. Regular Expressions • In this lesson, you will learn: o when to use regular expressions in Google Analytics o how to use the most common metacharacters: dot, backslash, etc. o some examples of common regular expressions in Google Analytics Definition: A regular expression is a set of characters and metacharacters that are used to match text in a specified pattern. You can use regular expressions to configure flexible goals and powerful filters. Filter Out IP Addresses: For example, if you want to create a filter that filters out a range of IP addresses, you’ll need to enter a string that describes the range of the IP addresses that you want excluded from your traffic. Let’s start off by looking at each metacharacter. Meta Character Defined: Metacharacters are characters that have special meanings in regular expressions. DOT: ( . ) Use the dot as a wildcard to match any single character. The operative word here is “single”, as the regex would NOT match Act 10, Scene 3. The dot only allows one character, and the number ten contains two characters -- a 1 and a 0. How would you write a regular expression that would match “Act 10, Scene 3”? You could use two dots. 14
  15. 15. To make your regex more flexible, and match EITHER “Act 1, Scene 3” or “Act 10, Scene 3”, you could use a quantifier like the + sign. (See diagram below) But we’ll talk about repetition a bit later in this module. Backslashes ( )allow you to use special characters, such as the dot, as though they were literal characters. Use: Enter the backslash immediately before each metacharacter you would like to escape. “U.S. Holiday” written this way with periods after the U and the S would match a number of unintended strings, including UPS. Holiday, U.Sb Holiday, and U3Sg Holiday. Remember that the dot is a special character that matches with any single character, so if you want to treat a dot like a regular dot, you have to escape it with the backslash. 15
  16. 16. You’ll use backslashes a lot, because dots are used so frequently in precisely the strings you are trying to match, like URLs and IP addresses. Creating a Filter: For example, if you are creating a filter to exclude an IP address, remember to escape the dots. Character Sets and Ranges Use square brackets to enclose all of the characters you want as match possibilities. So, in the slide below, you’re trying to match the string U.S. Holiday, regardless of whether the U and the S are capitalized. 16
  17. 17. However, the expression won’t match U.S. Holiday unless periods are used after both the U and the S. The expression also requires that the H is capitalized. Question Mark: There is a regex you can write to match all of these variations. The question mark used here is another “quantifier”, like the ‘+’ sign mentioned earlier. You can either individually list all the characters you want to match, as we did in the first example, or you can specify a range. Use a hyphen inside a character set to specify a range. So instead of typing square bracket 0 1 2 3 4 5 6 7 8 9, you can type square bracket 0 dash 9. example [0-9] (See Diagram above) And, you can negate a match using a caret ^ [^ 0-9] (see diagram above) after the opening square bracket. Typing square bracket caret zero dash nine will exclude all numbers from matching. 17
  18. 18. Note that later in this module, you will see the caret used a different way—as an anchor. ^ Carat Specific to Character Sets: The use of the caret shown here is specific to character sets, and the negating behaviour occurs only when the caret is used after the opening square bracket in a character set. Quantifiers and Repetition .* matches anything Dot star will match a string of any size. Dot star is an easy way to say “match anything,” and is commonly used in Google Analytics goals and filters. (See diagram below) Grouping 18
  19. 19. Pipe Symbol: It is handy to use the parentheses and the pipe symbol (also known as the OR symbol) together. Basically, you can just list the strings you want to match, separating each string with a pipe symbol -- and enclosing the whole list in parentheses. Below, we’ve listed four variations of “US” that we’ll accept as a match for US Holiday. If it’s not in the list, it won’t get matched. That’s why “US Holiday” won’t get matched if one of the periods is missing. In our list, we’ve accounted for both periods missing, but not for just one period missing. Using question marks, the second regex in the slide will match all of the above. 19
  20. 20. Anchors (Regex Slide 8) The caret signals the beginning of an expression. In order to match, the string must BEGIN with what the regex specifies.. The dollar sign says, if there are any more characters after the END of this string, then it’s not a match. Shorthand Character Classes 20
  21. 21. Review Below, we’ve created an expression that will match URLs for internet and theatrical movie trailers. 21
  22. 22. The first part of the expression indicates that the URL can begin with anything. Then the expression specifies that the URL must end with index.php?dl=video/trailers/ and then either internet or theatrical. The $ sign ensures that any URLs that are any longer than this won’t get included in the match. Common Uses For Regular Expressions 22
  23. 23. Examples in Analytics RegEx Filters 23
  24. 24. RegexGoals 24
  25. 25. 25
  26. 26. Can be used to group pages and Funnel Steps Within Reports Regular Expression Generator will do this for me: You’ll find a number of useful applications for regex as you use Google Analytics. But, it’s important that you think through all the implications of each expression that you use when you set up a filter or a goal. It’s easy to make a mistake and not get the data or the result you’re looking for. Set up a duplicate profile to test your regex statements. After enough data has been collected, check your results and make sure they’re what you expect. Remember to always maintain a backup profile that includes all your data. Domains & Subdomains • In this lesson, you will learn: o when to track across domains using the _link() method o when to track across domains using the _linkByPost() method o how to track across subdomains o best practices for tracking across subdomains o how to track across multiple domains with subdomains You may sometimes need to track activity across multiple domains. A common example of this is when you send visitors from your site to a separate shopping cart site to complete their purchases However, since Google Analytics uses exclusively first party cookies, it can’t automatically track whether those visitors actually complete a purchase or not, because the purchase is taking place on another site. When a Session Spans Multiple Domains: Phrased more generally, if a session spans multiple domains, it would not be possible to track the session as a single visit attributed to one visitor. So, you’ll need a way of sharing the cookie information between the two domains. _link() Method (added to link to other site) (First change GA code as in 1) 26
  27. 27. By calling the _link() method, you can send this cookie information across domains. This allows Google Analytics to track a user across multiple domains by sending cookies via URL parameters. To track across domains, you’ll need to follow two steps. 1) First, add a few lines to the Google Analytics Tracking Code on all pages of each site. The lines you need to add are shown here, in blue. _setDomainName() Call _setDomainName() with an argument of “none”. _setAllowLinker() And call _setAllowLinker() with an argument of “true”. 27
  28. 28. 2) The second step involves the _link() method. Use this method in all links between domains. In the example above, we’re updating all links from to and vice versa. We update each link to call the _link() method as shown below. Now, when a user clicks on a link that takes them to the other domain, the session information is preserved and the user is identified as being the same visitor across both domains. Forms and_linkByPost() Method (third Party Shopping carts) _linkByPost() If you use a form to transfer your visitors from one domain to another, you will need to use the _linkByPost() method instead of the _link() method. 28
  29. 29. *This situation occurs most often with third party shopping carts. To use forms to transfer from one domain to another, you must modify all the appropriate forms with the code shown here. The _linkByPost() method will change the form action by adding query-string parameters to the value in the action attribute when the visitor submits the form. Tracking Session Across Multiple Subdomains (Not Automatic) For example, has several subdomains such as,, and Since Google Analytics uses first-party cookies, cookies set on a subdomain can not automatically be read on the main domain, and vice versa. As with multiple domains, you need to explicitly share the cookie information between subdomains or you’ll lose session information. 29
  30. 30. If you don’t share cookie information between your subdomains, it may appear as though your own site is a referrer since only one domain is recognized as the main domain. _setDomainName() To track across multiple subdomains, call _setDomainName() and specify your parent domain name as the argument. This will allow the Google Analytics Tracking Code to use the same cookies across the subdomains. For example, to track across Google’s various subdomains, you would call _setDomainName() with an argument of “dot google dot com” (see below) Best Practices Track Across Multiple Subdomains First, create separate profiles for each subdomain. This way, you’ll be able to see reports for each subdomain. Set up duplicate profiles - one master profile, plus one profile for each subdomain. In example below, we’re looking at two subdomains. 30
  31. 31. Your master profile has no filters, and each of the other two has an Include filter. Profile 1 includes all traffic to both subdomains. Profile 2 includes only traffic to subdomain A. Profile 3 includes only traffic to subdomain B. Work Around: Tracks only the request URI, so same page names on seperate subdomains may be wrongly interpreted as the same page. Solution is an advance filter below. 31
  32. 32. Tracking Across Multiple Domains With Multiple Subdomains If you want to track across both multiple domains and subdomains, you’ll need to ensure that the Analytics cookies are set across the subdomains and that the cookies are being passed between the parent domains. _setAllowHash() There are two steps. 1) For the first step, add the lines of code shown in blue to Google Analytics Tracking Code on every page of one of Domain 1 and each of its subdomains. Make sure that _setAllowLinker() has an argument of true and _setAllowHash() has an argument of false. 32
  33. 33. Then, to each page of Domain 2 and each of its subdomains, add the same code -- but with a different argument to _setDomainName(). 2)For step 2, call _link() or _linkByPost() in all links and forms that cross between the two parent domains. For example, the code shown in the slide shows how you’d do this to track across and *****Note that you don’t need to use _link() or _linkByPost() in links between subdomains within the same domain. Again, you should create separate profiles in your account for each primary domain and/or each subdomain. You can easily do this by using an Include filter based on the hostname field. 33
  34. 34. Event Tracking and Virtual Pageviews • when to use virtual pageviews versus event tracking • how to generate a virtual pageview • how to track an event using _trackEvent() • the relationship between Categories, Actions, Labels, and Values • the difference between Total Events and Unique Events • best practices for setting up Event Tracking Web Analytics and Interactive Activities Many websites use technologies such as Flash and Ajax to interact with visitors. For example, some websites embed video players, games, and other interactive experiences on site pages. However, the basic web analytics model of tracking pageviews doesn’t capture these kinds of interactions. When a visitor interacts with a video player, for example, no pageview is generated. Some other examples of interactions that don’t generate pageviews are Ajax-based activities, file downloads, and clicks on links that take the visitor to another site. There are two ways: virtual pageviews and Event Tracking. (aka. non-pageview interactions) Virtual Pageviews _trackPageview() shown in Top Content and Content Drilldown reports. You can create a virtual pageview to represent practically any kind of activity or interaction you want. You simply call _trackPageview() and provide any name you want as the argument. It’s “virtual” because you’re telling Google Analytics to register a pageview even though no new page has actually been loaded. You’ll see these virtual pageviews alongside ordinary pageviews in the Top Content and Content Drilldown reports. 34
  35. 35. Here are some more examples. In the first example below, we’re tracking a download. In the second example, we’re tracking a Flash event. In each of these cases, we’re simply calling _trackPageview() to register a virtual pageview. 35
  36. 36. It’s a good idea to adopt a clear naming convention for your virtual pageviews. You might, for example, group virtual pageviews into categories by giving them a virtual subdirectory. Also, since virtual pageviews appear along with standard pageviews in reports, you may wish to create a duplicate profile where you filter out the virtual pageviews. To make this easy, you might organize all of your virtual pageviews into a “virtual” subdirectory. Event Tracking (show up in the Event Tracking reports within the Content section) • Doesn’t generate and extra pageview • Easy to organize events into readable labels The other way to track non-pageview interactions is to use Event Tracking. One advantage of using Event Tracking is that you won’t generate an extra pageview each time an interaction occurs. Another advantage is that you can easily organize your events into categories, actions, and provide labels and even values for each event you track. All of your events show up in the Event Tracking reports within the Content section. 36
  37. 37. Best Practices for Event Tracking: The arguments you provide when you call _trackEvent will govern how events are organized in your reports. So, before you add the calls to _trackEvent to your site, consider these best practices. First, determine in advance all of the kinds of events you’ll want to track. Try to create a hierarchy of Categories, Actions, and Labels that will grow with your needs. Work with your report users to make sure that the hierarchy makes sense. And use a clear and consistent naming convention for your Categories, Actions, and Labels. Finally, note that a maximum of 500 events per visit will be tracked. So, avoid tracking highly repetitive events such as mouse movements 37
  38. 38. Event tracking VS Virtual PageViews *Event tracking is Better Analyze user interactions in much greater detail Avoid inflating the pageview count • Using trackEvent() allows you to analyze event based interactions in much greater detail than is possible using virtual pageviews. • For example, instead of just seeing how many times a movie was played on your site, you can analyze how people use your video player, and see how different events correlate with site usage and ecommerce metrics. • Also, by tracking events separately from pageviews, you won’t inflate your pageview count. Will show Labels on the report like “Button” or “Image” Advanced Segmentation the Customer Visitor Segment Variable 38
  39. 39. • In this lesson, you will learn: o how Advanced Segments differ from filtered profiles o to apply an Advanced Segment to your reports o how to create and modify an Advanced Segment With Advanced Segments, you can quickly isolate and analyze subsets of your traffic. You can create an advanced segment that only includes visits that meet a specific set of criteria. So, for example you can create an advanced segment that only includes visits from a certain geographic region or visits during which more than $100 was spent Differences between Filtered Profiles and Advanced Segments (up to 4 at a time) While it's possible to create filtered profiles that segment traffic data, there are some differences between filtered profiles and advanced segments. Historical Data: Advanced segments can be applied to historical data, but a filtered profile will only filter traffic going forward. When you create an advanced segment, that segment is available across all of your accounts and profiles. But, a filtered profile is only useful for a specific web property. You can compare up to four advanced segments side by side in your reports. In contrast, filtered profiles can only be viewed one at a time. It is much easier to create an advanced segment than it is to create a filtered profile. If you want to permanently affect the data that a profile shows, you should use a filtered profile. So if you want a profile that only shows CPC data, you should set up a filtered profile to do this. And if you want to restrict user access to only a subset of data, the best way to do this is to set up a filtered profile and restrict the users' access to only that profile. (See diagram below for more) Advanced Segments • Can be applied to historical data • Available across all accounts and profiles • Maximum of 4 advanced segments • Easier to use than a Filter • Can be see across all reports and applied to historical data too Filters • Can only filter traffic moving forward • Only applies to an individual profile (web property) • Best to show only CPC (Adwords) data 39
  40. 40. • Best for restricting access to a subset of data Once you’ve applied one or more advanced segments, you can see the data for the segments throughout all of your reports. You can also change your date range and see the segments applied to historical data. The segments remain applied until you deselect them or you logoff or view reports on another account or profile. The segment will now appear in the Custom Segments area of the Advanced Segments pulldown. You can only change custom segments Customizations • In this lesson, you will learn: 40
  41. 41. o how to change session timeout value o how to change campaign expiration o how to change campaign precedence o how to add a search engine o how to treat certain keywords as direct o how to treat certain referring sites as direct **In Google Analytics, a visit—or session—is defined by 30 minutes of inactivity, or when a user quits the browser. Changing the Session Timeout Value _setSessionCookieTimeout() You can change the 30 minute default by calling setSessionCookieTimeout as shown in the slide. Simply specify a new timeout value in milliseconds as the argument to _setSessionCookieTimeout() 41
  42. 42. Changing the Campaign Expiration _setCampaignCookieTimeout() By default, a conversion can be attributed to a campaign that is up to 6 months old. But, if your business has a longer or shorter marketing campaign timeframe, you can change this value. Just call _setCampaignCookieTimeout() and specify your new campaign length in milliseconds. For example, let’s say that you want to set a campaign length of 30 days. To figure out the number of milliseconds that is, type “30 days in milliseconds” into Google Search. The search engine will give you the answer which you can plug into _setCampaignCookieTimeout(). Changing campaign Precedence utm_nooverride=1 Google Analytics attributes conversions to the campaign that most recently referred the visitor. For example, let’s say that someone discovers your site by clicking one of your AdWords ads. 42
  43. 43. Then, they come back to your site by clicking a banner ad that you’ve tagged with campaign variables. This time, they convert to one of your goals. *By default, the banner ad will get the credit for the conversion, not the AdWords ad that originally referred them. To change this behavior, you can tag all of your campaign links with utm_nooverride=1. If you do this consistently with all of your campaigns, Google Analytics will attribute conversions to the first referring campaign, instead of the most recent one. *Note that the utm_nooverride setting can be used in conjunction with autotagging. Adding a search Engine _addOrganic() Google Analytics automatically tracks referrals from over 30 search engines. But, if you want to add a search engine, you can do it by calling _addOrganic() in your Google Analytics Tracking Code. First, perform a search in the search engine and look at the URL of the search results page. In the URL, look for the keyword you searched -- it should be preceded by a letter and an equal sign. This letter is the query variable for the search engine. In the example, the query variable is “p”. 43
  44. 44. Add a call to _addOrganic in your Google Analytics Tracking Code. The first argument is the name of the search engine. The second argument is the query variable. Treating Certain Keywords as Direct _addIgnoredOrganic() You may wish to treat traffic that results from certain search keywords as Direct. For example, if someone searches for the exact name of your site, you might want to treat that visit as a Direct visit instead of a search. To do this, simply add a call to _addIgnoredOrganic() in your Google Analytics Tracking Code. Specify the keyword as the argument. Treating Certain Referring Sites as Direct _addIgnoredRef() You can also treat referrals from certain sites as Direct traffic instead of as referrals. For each site that you want to exclude as a referral and treat as Direct, add a call to _addIgnoredRef() in your Google Analytics Tracking Code. Specify the name of the site as the argument. 44
  45. 45. Pageviews, Visits, and Visitors VISIT = SESSION In Google Analytics, a pageview is counted every time a page on your website loads. So, for example, if someone comes to your site and views page A, then page B, then Page A again, and then leaves your site -- the total pageviews for the visit is 3. A visit -- or session -- is a period of interaction between a web browser and a website. Closing the browser or staying inactive for more than 30 minutes ends the visit. For example, let’s say that a visitor is browsing the Google Store, a site that uses Google Analytics. He gets to the second page, and then gets a phone call. He talks on the phone for 31 minutes, during which he does not click anywhere else on the site. After his call, he continues where he left off. Google Analytics will count this as a second visit, or a new session. Note that throughout these modules, the words “visit” and “session” may be used interchangeably. A visitor is uniquely identified by a Google Analytics visitor cookie which assigns a random visitor ID to the user, and combines it with the timestamp of the visitor’s first visit. Unique ID: The combination of the random visitor ID and the timestamp establish a Unique ID for that visitor. 45
  46. 46. Generally, the Visitors metric will be smaller than the Visits metric which in turn will be smaller than the Pageviews metric. (See Diagram Below) For example, 1 visitor could visit a site 2 times and generate a total of 5 pageviews. Unique Pageview: A unique pageview represents the number of visits during which that page was viewed--whether one or more times. In other words, if a visitor views page A three times during one visit, Google Analytics will count this as three pageviews and one unique pageview. Absolute Unique Visitor / New vs. Returning Visits Absolute Unique Visitor The “Absolute Unique Visitors” report counts each visitor during your selected date range only once. So, if visitor A comes to your site 5 times during the selected date range and visitor B 46
  47. 47. comes to your site just once, you will have 2 Absolute Unique Visitors. Remember, a visitor is uniquely identified by a Google Analytics visitor cookie. New vs. Returning Visits The “New vs. Returning” report classifies each visit as coming from either a new visitor or a returning visitor. So when someone visits your site for the first time, the visit is categorized as “Visit from a new visitor.” If the person has browsed your website before, the visit is categorized as “Visit from a returning visitor.” A high number of new visits suggest that you are successful at driving traffic to your site while a high number of return visits suggests that the site content is engaging enough for visitors to come back. Recency Report: You can look at the Recency report to see how recently visitors have visited. Loyalty Report: You can look at the Loyalty report to see how frequently they return. Both the Recency and Loyalty reports are under Visitor Loyalty in the Visitors section. Pageviews, Visits , Visitors in Reports The Pageviews metric can be found in the Visitors Overview and in the Content section reports. Most of the other reports show Pages Viewed per Visit instead of Pageviews. Unique Pageviews is only found in the Content section. Almost all of the reports show Visits. 47
  48. 48. The Visitors metric -- in other words the number of visitors who came to your site -- is found in the Visitors section. (see diagram below) 48
  49. 49. • Campaign Tracking and AdWords Integration (13:47 minutes) In this lesson, you will learn: o how to track campaigns using tagged links o how to track AdWords campaigns o when to use autotagging and how it works o how to enable autotagging o where to find AdWords data in your reports o the expected kinds of data discrepancies between AdWords and Analytics data o when and how to manually tag URLs o how to use the URL Builder o best practices for tagging links • you can only link one Analytics account to one AdWords account • create a new Analytics account for each associated AdWords account. • the time zone in Google Analytics will automatically take that of the AdWords Account (if they are different). Within AdWords, select Google Analytics under the Reporting tab to link your accounts. The AdWords login that you’re using will need administrator privileges in Analytics in order to link the accounts. There are two ways to track ad campaigns (AdWords). 1) Keyword Autotagging (AdWords) 2) Manual Tagging 1) Keyword Autotagging (AdWords): For AdWords campaigns, you should enable keyword autotagging. This allows Google Analytics to automatically populate your reports with detailed AdWords campaign information. In order to enable autotagging, you’ll need to link your AdWords and Google Analytics accounts; we’ll look at this in more detail in the next slide. If autotagging is not enabled, your Analytics reports will show that the clicks from the sponsored listings and the organic listings are both coming from the same source: google organic. When linking accounts you should enable Destination Autotagging (will show organic from paid): **When you link your accounts, you should enable "Destination URL Autotagging”. This option allows you to differentiate your paid ads from organic search listings and referrals and allows 49
  50. 50. you to see detailed campaign information in the AdWords section of your Traffic Sources reports. Cost Data: Your cost data -- the information about clicks and keyword spending -- will be applied once you link your accounts. When linking your AdWords account to your Analytics account, your cost data will be applied to all of your profiles. Don’t want Cost data imported to a Profile: If you don't want cost data imported into a particular profile, you can edit the profile settings and de-select the cost data option -- after you've completed the linking process. You can find Cost data here: Analytics Settings > Profile Settings > Edit Profile Information Google Analytics allows you to track and analyze all of your marketing campaigns -- including paid search campaigns, banner ads, emails and other programs. How Autotagging Works Autotagging works by adding a unique id, or g-c-l-i-d, to the end of your destination URLs. This unique id allows Analytics to track and display click details in your reports It is important to note that 3rd party redirects and encoded URLs can prevent autotagging from working properly. You should test these cases by adding a unique parameter to the end of your URL --- for example you could add ?test=test. Test to make sure that the parameter is carried through to your destination page and that the link doesn’t break. (See Diagram Below) 50
  51. 51. 51
  52. 52. Here’s an example of a gclid appended to the end of a URL. To enable autotagging, in ADWORDS!!!!! select “Account Preferences” under “My Account”. 52
  53. 53. Make sure that the Tracking option reads “yes”. If it says “no”, click the edit link, check the box for “Destination URL Autotagging”, and click “Save Changes”. When linking your AdWords account to Analytics for the first time, you’ll be prompted to automatically select “Destination URL Autotagging” and “Cost Data Import”. If you want to change your autotagging settings later, you can do so by editing your AdWords account preferences. 2) Manual Tagging: The second way to track campaigns is to manually tag links. So, for example, you could tag the links in an email message with campaign-identifying information. You may also choose to manually tag AdWords links if you do not wish to enable autotagging. Paid Advertising campaigns: if you are running paid advertising campaigns, you should add tags to the destination URLs of your ads. Adding a tag allows you to attach information about the campaign that will show up in your Analytics reports. If you manually tag your AdWords ads, the AdWords reports will only show you information by Campaign and Keyword. If you enable auto-tagging, you’ll be able to see much more detail. The AdWords reports will show you results by ad group, matched search query, placement domain and many other AdWords attributes. The tags are campaign variables that you append to the end of your URLs. 5 variables to use when manually tagging URLS There are five variables you can use when tagging URLs. To tag a URL, you add a question mark to the end of the URL, followed by your tag, as shown in the slide. The variables and values are listed as pairs separated by an equals sign. Each variable-value pair is separated by an ampersand. Let’s look at each variable. utm_source You should use utm_source to identify the specific website or publication that is sending the traffic. utm_medium Use utm_medium to identify the kind of advertising medium -- for example, cpc for cost per click, or email for an email newsletter. utm_campaign Use utm_campaign to identify the name of the campaign -- for example, this could be the product name or it might be a slogan. You should always use these three variables when tagging a link. You can use them in any order you want. 53
  54. 54. utm_term If you're tagging paid CPC campaigns, you should also use utm_term to specify the keyword. utm_content And, you can differentiate versions of a link -- for example, if you have two call-to-action links within the same email message, you can use utm_content to differentiate them so that you can tell which version is most effective. (see diagram below) 54
  55. 55. The first link in the slide does not have a tag. Traffic from this link will show up in your reports as a referral from There won’t be any campaign information. The second link has a tag. Traffic from this link will show up with a source of yoursite, and it will show as a banner, instead of a referral. Also, you’ll see this traffic reflected under summerpromo in your Campaigns report while the untagged will be set to “not set” 55
  56. 56. Paid Keywords tagging examples Let’s look at a destination URL from an AdWords ad. In the first example, no tag has been provided and autotagging is disabled. In this case, you won’t see this traffic in your AdWords reports. The second example shows how to manually tag an AdWords link. This traffic will show up in your AdWords reports, but information will be limited to campaign and keyword. You must specify cpc as your medium and google as your source in order to see this traffic in your AdWords reports. You should also specify cpc as your medium when tagging paid search campaigns from other search engines. The third example shows what an AdWords autotagged URL might look like once AdWords has appended the g-c-l-i-d variable to the end of the URL. 56
  57. 57. This traffic will show up in your AdWords reports and you’ll see complete AdWords information. (see diagram below) Let’s look at where information from each of the tags shows up in your reports. Source You can see all the sources in the All Traffic Sources report. This report will include not only all the sources you tagged, but also sources like “direct” and website names. 57
  58. 58. Medium You can see also see traffic by medium in the All Traffic Sources report. In addition to all the mediums you tagged, you’ll also see mediums such as “referral” and “organic”. Campaign Campaigns will appear in the Campaigns report. Term Terms that you’ve used will show up in the Keywords report. Content Your content tags will show up in the Ad Versions report. You can also segment on any of these variables. For example, to see all of the sources in California from which you received traffic, you could go to the Map Overlay report, drill down to California, and segment by Source. Manually Tagging with URL Builder: URL Builder in the Google Analytics Help Center to construct your URLs. Always Use: Source Medium Campaign More than one Link then use a spreadsheet… If you have a large number of URLs to tag, you can use spreadsheets to automate the process. Generate a sample URL in the URL Builder and create a simple spreadsheet formula. Spreadsheets can make it much easier to generate thousands of tagged URLs. Best Practices for tagging your Advertising campaigns: 58
  59. 59. Data Discrepancies Between AdWords and Analytics AdWords tracks clicks, while Analytics tracks visits. You may notice differences between the data in your Google Analytics and AdWords reports. There are several reasons for these differences. First, AdWords tracks clicks, while Analytics tracks visits. Second, some visitors who click on your AdWords ads may have JavaScript, cookies, or images turned off. *As a result, Analytics won't report these visits, but AdWords will report the click. You’ll also see differences between Analytics and AdWords if the Google Analytics Tracking Code on your landing page doesn’t execute. In this case, AdWords will report the click but Analytics will not record the visit. 59
  60. 60. Invalid clicks may also cause reporting differences because while Google AdWords automatically filters invalid clicks from your reports, Google Analytics will still report the visits. Finally, keep in mind that AdWords data is uploaded once a day to Analytics so the results for each may be temporarily out of sync. Installing the Google Analytics Tracking code 60
  61. 61. • In this lesson, you will learn: o how to create a new account o where to place the Google Analytics Tracking Code o about website setups that require customization o how to verify installation • Link Adwords to Analytics to Report on Cost and Click data • Select Google Analytics Under Reporting tab using Google Adwords • Put GA code into </HEAD> right before end tag at top of page • 24 hours to see data GA JavaScript and first party cookies to gather anonymous data about users OLD: Traditional ga.js is old and still used on some sites…. CHECK STATUS -> BEST: Asynchronous version of the Google Analytics Tracking Code. The asynchronous version of the tracking code allows your site to run at its fastest, so we recommend that you always use this version. It is customary to place JavaScript code in the <head> section Goals in Google Analytics • In this lesson, you will learn: o the purpose of using goals, goal values, and funnels o when to use each Goal URL Match Type o how to assign meaningful values to goals o how goal conversions differ from transactions o how filters can affect goals o where to find goal and funnel information in reports • best way to access how site is meeting business objectives What is a Goal? • A goal represents an activity or a level of interaction with your website that’s important to the success of your business. • an account signup • request for a Sales call • visitor spends certain amount of time on site • Maximum of 4 sets of 5 goals each • Assign a monetary value to a goal (Download of PDF) • Only provide values for non-eCommerce type goals • If you define a funnel for a goal, Google Analytics populates the Funnel Visualization report 61
  62. 62. • Reverse Path Goal Report: Report found in Goal section…. great report for identifying funnels that you hadn’t considered • • You can see this data even if you haven’t defined a funnel. It lists the navigation paths that visitors took to arrive at a goal page and shows you the number of conversions that resulted from each path. There are three types of goals in Google Analytics URL Destination goal is a page that visitors see once they have completed an activity. For an account sign-up, this might be the “Thank You for signing up” page. For a purchase, this might be the receipt page. A URL Destination goal triggers a conversion when a visitor views the page you've specified. Funnel: For each URL Destination goal that you define, you can also define a funnel. A funnel is the set of steps, or pages, that you expect visitors to visit on their way to complete the conversion. Example: sales Checkout Process Funnel Steps: pages where visitors go on their way to a goal *Defining a Funnel helps Determine where a visitor enter and exits the conversion process Funnel Example: page where visitor enter CC information Goal: thank you page Goal URL Destination Match Types: Head Match – for a folder and anything inside it: Every page in a subdirectory counted as a goal. Exact Match – For an exact pagname Regular Expression Match – most flexible Time on Site goal is a time threshold that you define. When a visitor spends more or less time on your site than the threshold you specify, a conversion is triggered. For measuring site engagement Pages per Visit goal allows you to define a pages viewed threshold. When a visitor views more pages --or fewer pages --than the threshold you've set, a conversion is triggered. 62
  63. 63. Goals VS Ecommerce Transactions • A goal conversion can happen only once during a visit Visitor download pdf 5 times during visit – counted a 1 conversion • An ECommerce transaction can occur multiple times during a visit Every download will be tracked as a conversion E-commerce Tracking • In this lesson, you will learn: o where to find ecommerce metrics in reports o how to enable and track ecommerce 63
  64. 64. If your site sells products or services online, you can use Google Analytics e-commerce reporting to track sales activity and performance. The Ecommerce reports (and on Ecomerce tabs in some reports) shows you your site’s transactions, revenue, and many other commerce- related metrics. Ecommerce Reports: Examples of information you can get: • the products that were purchased from your online store • your sales revenue • your e-commerce conversion rate • the number of times people visited your site before purchasing Ecommerce tab of the AdWords Campaigns report, you can see how much revenue is associated with your AdWords campaigns. Ecommerce tab of the Referring Sites report, you can see how many transactions are associated with site referrals. Ecommerce tab of the All Traffic Sources report, you can see the per visit value across all traffic sources How to Track eCommerce 1. Enable e-commerce reporting within your Analytics website profile. 2. Add the Google Analytics Tracking Code to your receipt page or “Transaction Complete” page. 3. Add some additional e-commerce tracking code to your receipt page so that you can capture the details of each transaction. _addTrans() method ; _addItem() ; trackTrans() Below is an example of what the ecommerce tracking code on your receipt page might look like. Remember, you’ll be sandwiching this code into the basic Google Analytics Tracking Code. _addTrans() n the first part of the code, there is a call to the _addTrans() method. The call to _addTrans() tells Google Analytics that a transaction has occurred. The _addTrans() method establishes a transaction and takes the arguments .Your code will need to dynamically retrieve the values from your merchant software to populate these fields.You can type single-quote single-quote to leave an optional field blank, but note that Order ID and Total are required.The arguments to _addTrans() provide details about the transaction -- for example an Order ID, the total order amount, and the amount of tax charged. _addItem() After the call to _addTrans(), there must be at least one call to the _addItem() method. This call provides Google Analytics with details about the specific item purchased. For each item that a visitor purchases, call _addItem(). If more than one item is purchased, you’ll call _addItem() multiple times. As with _addTrans(), you can leave some of the fields blank, but 64
  65. 65. note that Order ID, SKU or Code, Price and Quantity are required arguments. Use the same Order ID that you used in the call to addTrans(). _trackTrans() Finally, after the calls to _addTrans() and _addItem(), you’ll need to call _trackTrans() to send the transaction information to Google Analytics. Remember that all of the e-commerce code must appear after the Google Analytics Tracking Code calls _trackPageview(). The standard Google Analytics Tracking Code automatically detects when an https protocol is being used. So you won’t need to add any special tracking code for secure pages. Time Metrics 65
  66. 66. • In this lesson, you will learn: o how Time on Page and Time on Site are calculated o how Avg. Time on Page and Avg. Time on Site are calculated o about the Length of Visit report • Analytics compares the timestamps of the visited pages. Now, suppose the visitor continued on to a third page before exiting. The second page now has a Time on Page of 1 minute 10 seconds.The Time on Site is now calculated as 2 minutes and 25 seconds. For Average Time on Page, bounces are excluded from the calculation. In other words, any Time on Page of 0 is excluded from the calculation. For Average Time on Site, bounces remain a part of the calculation. 66
  67. 67. To calculate Average Time on Site, Google Analytics divides the total time for all visits by the number of visits. Total time on Page / (PageViews – Exits) Flash Websites have high bounce rates and low average times on site. Often, these kinds of sites don’t load new pages frequently and all the user interaction takes place on a single page. The Length of Visit report can be found under Visitor Loyalty in the Visitors section. Cookies and Google Analytics • In this lesson, you will learn: o how Google Analytics uses cookies o the differences between persistent and temporary cookies o the differences between first party and third party cookies o the names of the Google Analytics cookies and the information they track There are two types of cookies. First-party cookies are set by the domain being visited. Only the web site that created a first-party cookie can read it. This is the kind of cookie used for Google Analytics tracking. Third-party cookies are set by third party sites -- basically sites other than the site being visited. Cookies can be set with or without an expiration date. This detail is important in order to understand how Google Analytics tracks visits and unique visitors. *Cookies must be enabled for: login to many online shopping carts and to use web mail. Persistent cookies All GA are persistent except for _utmc Cookie. Persistent cookies have an expiration date, and remain on your computer even when you close your browser or shut down. On return visits, persistent cookies can be read by the web site that created them. **The __utmv cookie is optional, and will only be set if the _setVar() method is called. You will learn about _setVar() in the module on Custom Visitor Segmentation Temporary cookies do not have an expiration date, as they are only stored for the duration of your current browser session. As soon as you quit your browser, temporary cookies are destroyed. 5 Types - Cookie Expiration dates below… 67
  68. 68. Unique Visitor Identification: The random unique ID combined with the first timestamp make up the visitor ID that Google Analytics uses to identify unique visitors to the site. These details allow Google Analytics to calculate the number of unique visitors and number of visits. (see diagram below) 68
  69. 69. Session: The __utmb and __utmc cookies together identify a session. When the visitor loads a page, the JavaScript in the Google Analytics Tracking Code checks for both the __utmb and __utmc cookies. If either one is missing, it notes this as a new session, and creates whichever cookie-- __utmb, __utmc, or both-- was missing. 69
  70. 70. __utmb cookie is destroyed if a visitor stay on a site longer that 30 minutes. Page refreshed and another session begins __utmc Cookie • Stores information about the campaign, medium, source • Has value for 6 months or overwritten by another value • Shows up in All Traffic Sources The __utmz cookie stores the campaign tracking values that are passed via tagged campaign URLs. So, for example, if a visitor comes to your site on a link tagged with campaign variables utm_source, utm_medium, and utm_campaign, the values for these variables will be stored in the __utmz cookie. 70
  71. 71. What a _utmz cookie looks like; __utmv cookie is for custom visitor segmentation Persistent Cookie – expires after 2 years Member login – members Only The __utmv cookie is for custom visitor segmentation. You’ll only see this cookie if the site calls the _setVar() method. This cookie contains the domain hash, and one other value: the value you assign using _setVar().The __utmv is a persistent cookie that expires after 2 years END! 71