Google Analytics Guide. A step by step guide to a best practice implementation of Google Analytics

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Google Analytics

Guide

A step by step guide to a best practice

implementation of Google Analytics

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DBD Media – Search. Social. Analytics.

www.dbdmedia.co.uk

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1. INTRODUCTION: What You Need To Know Before You Start

1.1. What is Google Analytics?

Google Analytics (GA) is a free service offered by Google that generates detailed statistics about the visitors to a website.

GA can track visitors from all referring sources, including search engines, display advertising, email marketing and other digital collateral such as links within PDF documents.

When integrated with Google AdWords, users can their review online campaign performance by tracking landing page quality and conversions (goals). Goals might include sales, booking enquiries, lead generation, viewing a specific page, or downloading a particular file. By using GA, marketers can determine which ads are performing, and which are not, providing vital information to optimise, expand or cull campaigns.

GA’s approach is to show high-level dashboard-type data for the casual user, and more in-depth data further into the report set. Through analysis of GA data, website performance can be understood using techniques such as funnel visualisation, referrer source (where visitors came from), how long they stayed and their geographical location. It also provides more advanced features, including custom visitor segmentation.

If your website sells products or services online, you can use Google Analytics ecommerce reporting to track sales activity and performance. The ecommerce reports show you your website’s transactions, revenue, and many other commerce-related metrics.

1.2. Cookies

GA uses first-party tracking cookies only, which are considered minimally intrusive by the new EU Privacy Directive. To be compliant with the Directive, you need to list these cookies in your privacy policy and request users’ consent to use them.

Cookie Name Purpose Expiration

_utma Visitor identifier 2 years

_utmb Session identifier When the visitor closes the browser or after 30mins of inactivity

_utmc Session identifier When the visitor closes the browser _utmz Stores the campaign tracking values

that are passed via tagged URLs

6 months

_utmv (optional) Custom visitor segmentation 2 years

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1.3. Installing Google Analytics

To implement Google Analytics on your website you first need a Google account. If you do not have one, you can create it here: https://accounts.google.com/NewAccount (you can use any email address, not just Gmail). Once you’ve created your Google account and are logged in, you can access Google Analytics by selecting “Products” on the left-hand navigation menu.

When you set up your Google Analytics account, you will be provided with your Google Analytics Tracking Code (GATC) as per the example below. You’ll need to install this tracking code across all pages of your website. It is customary to place the code in the header, right before the </head> tag to increase the likelihood that the tracking beacon will be sent before the user leaves the page.

Figure 1: GATC example

It is important you carefully select which tracking option suits your website as this will influence the readability of your data.

Figure 2: Advanced GA tracking options

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Figure 3: Account organisation example

1.4. Verifying Implementation

1.4.1. Checking Reports for Data

Once you’ve installed your tracking code on your website, it usually takes about 24 hours for data to appear in your reports.

The best way to verify that you are receiving data is to simply look at your reports. Select the “Home” tab, then “Real-Time”, “Overview” on the left-hand navigation menu. If you browse on your website at the same time your visit should appear in the report.

Figure 4: Real-Time report

After 24 hours have passed, you can also check directly into your Standard Reports, “Content”, “Site Content”, “Pages” and make sure that you see Pageview numbers for each of your pages.

1.4.2. Checking Source Code

You can also view your webpage’s source code to verify that the tracking code is correctly installed. Navigate your browser to any page on your website. Right click within the browser window and select the “View Page Source” or “View Source” option in your browser. This will open a new window that contains the source code for that page. To find out whether Google Analytics Tracking Code is installed, search for “ga.js” (from the source code menu, select “Edit” and click the “Find” option.)

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If you find the Google Analytics Tracking Code on your page, then you can be sure that Google Analytics has been installed on your website. Repeat this process across any page you doubt is being tracked on your website to make sure that your installation is complete.

Figure 5: Page source code

1.4.3. GA Debugger

If you are using Google Chrome, you can install the Google Analytics Debugger (see Figure 6).

Once installed and enabled, open your website in a new window, right-click and select “Inspect element”. Go to the “Console” tab: if your GATC is properly implemented, you should see “Tracking beacon sent!” at the top.

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2. SETUP: What To Do Before Your Data Comes In

2.1. Profiles & Filters

Google Analytics gives account administrators multiple ways to segment their data according to different desired dimensions. Using filtered profiles is the most accurate way of segmenting data and allows accounts to have access to all reporting features including goal/funnel visualisation. Profiles can also be used to allow a more limited view of your data to a user, for example non-specialist management within your organisation.

Filters require a lot of care when applied to profiles. Filters are applied before extracting data from your website and in the order in which they are listed, therefore fundamentally changing the way in which data is collected. Once applied, filters cannot influence historical data and the information excluded cannot be retrieved. Filtered profiles can be created to:

 Separate traffic data from different subdomains e.g. store.mysite.com and info.mysite.com  Separate traffic data from different domains

e.g. www.mysite.co.uk and www.mysite.fr  Isolate a certain part of your website

e.g. www.mysite.com/blog  Focus on specific traffic channels

e.g. paid vs. organic traffic

Google Analytics provides three commonly used predefined filters. You will see them by selecting the “Filters” tab on the Admin page.

1. Traffic from the domains – Excludes all or includes only traffic from the domain you specify in the domain field directly below the Filter Type dropdown.

e.g. isolate traffic coming from your sister company’s website

2. Traffic from the IP addresses – Excludes all or includes only traffic from an IP address or range of IP addresses entered into the IP address field.

e.g. exclude your internal company traffic

3. Traffic from the subdirectories – Excludes all or includes only traffic to a specified directory on your website.

e.g. track www.mysite.com/blog/ separately As a best practice we recommend you always:

 Maintain an unfiltered profile to backup your historical data.  Keep a test profile for trying out new filters.

 Exclude your company’s internal traffic as well as traffic from any development/media/PR agency you are using which might skew your data.

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2.2. Traffic Channel Tracking

2.2.1. Paid Traffic: Google AdWords Integration

By linking Google Analytics to your Google AdWords account, you can get advanced reporting that measures campaign ROI and on-site performance for paid traffic generation (e.g. bounce rate, time on site, pages/visit...) In order to link both accounts, you first need to add your AdWords username (if different) as an Admin on your GA account. Then, log into AdWords and select “Tool and Analysis” in the main navigation, then “Google Analytics” in the drop-down menu. You will be taken to a GA dashboard. Click on the “Admin” tab on the right-hand side and select the GA account you wish to link. Go to “Data Sources”, select the profiles you want to transfer AdWords data to and click on “link”.

When you link your accounts, enable "Destination URL Autotagging” (AdWords main navigation, “My Account”) to differentiate your paid ads from organic search listings and referrals and see detailed campaign information in the AdWords section of your Traffic Sources reports.

Be aware that you can only link one Analytics account to one AdWords account. For administration purposes, you will want to create a new Analytics account for each associated Google AdWords account.

Figure 7: Post-click data on AdWords campaigns Importing Cost Data from AdWords

Your cost data (clicks and keyword spending information) will be applied once you link your accounts. 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.

Make sure both your AdWords and Analytics accounts are set to the same currency so that ROI data is accurately calculated.

Note that Google Analytics is only able to import cost data from AdWords, and not from other PPC networks such as Bing, Yahoo...

Data Discrepancies between AdWords and Google Analytics

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 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.

 Google AdWords automatically filters out invalid clicks (clicks on ads that Google considers to be illegitimate, such as unintentional clicks or clicks resulting from malicious software) from its reports while Google Analytics will still report the visits.

 AdWords data is only uploaded once a day to Analytics so the results for each may be temporarily out of sync.

 If the landing pages don’t contain the Google Analytics Tracking Code, campaign information will not be passed to Analytics, but clicks will register in AdWords.

 Make sure that you have autotagging enabled – otherwise visits will be marked as Google Organic instead of Google PPC.

 If your website uses redirects, campaign data can be lost: Analytics won’t show the visits as coming from AdWords, but your AdWords report will still report the clicks.

2.2.2. Paid Traffic: Non-AdWords Campaign Tracking (UTM Parameters)

Google Analytics automatically tracks all search queries and referring sources that send traffic to your website. However, if you are running paid advertising campaigns, you should add tags to the destination URLs of your ads in order to identify them as paid traffic channels rather than referring websites, so that you are able to fully understand their performance on-site.

UTM tags override the default traffic source (referral) so it is important you only use them on links external to your website to avoid self-referrals. To identify clicks on internal links, see 2.5.2 Event Tracking.

There are five variables you can use when tagging URLs. To tag a URL, add a question mark to the end of the URL followed by your tag or use the Google Analytics URL Builder.

Source – identify the referrer: search engine, newsletter name, or other source Medium – identify the marketing medium such as email, cpc, display...

Campaign – identify a specific product promotion or strategic campaign Term (optional) – identify the paid keywords

Content (optional) – used for A/B testing and content-targeted ads to differentiate ads or links that point to the same URL

Example 1 Example 2 Example 3

Analytics Guide email newsletter2 n/a n/a Analytics Guide cpc yahoo analytics setup

using word ‘Free’

Analytics Guide

social

twitter

n/a

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Example URL tags

1.

http://www.dbdmedia.co.uk/assets/google-analytics-guide.pdf?utm_source=newsletter2&utm_medium=email&utm_campaign=Analytics%2BGuide

2.

http://www.dbdmedia.co.uk/assets/google-analytics-guide.pdf?utm_source=yahoo&utm_medium=cpc&utm_term=analytics%2Bsetup&utm_content=with

%2BFree&utm_campaign=Analytics%2BGuide

3.

http://www.dbdmedia.co.uk/assets/google-analytics-guide.pdf?utm_source=twitter&utm_medium=social&utm_campaign=Analytics%2BGuide

It is important to adopt a naming convention that is consistent across all your campaigns, and also with GA’s naming conventions, in order not to skew traffic reports.

For instance, GA uses by default google/cpc (source/medium) for Google AdWords traffic. When tagging URLs for Yahoo PPC ads, use yahoo/cpc (rather than Yahoo/PPC for instance) in order to group all Yahoo related data under “yahoo” and all PPC related data under “cpc”.

Figure 8: Source drill-down Figure 9: Medium drill-down

Figure 10: Traffic Sources / Sources / All Traffic

2.2.3. Organic Traffic: Google Webmaster Tools Integration

Organic search reports are found in the “Traffic Sources” section under “Sources”, “Search”, “Organic”. This allows you to see which keywords delivered organic traffic to your website and how relevant your landing pages were to the user (e.g. bounce rate). The Search Engine Optimisation (SEO) reports in Google Analytics will show Google search queries which have returned impressions (see 3.1 Definitions) and the proportion of those impressions which resulted in a click to your website (CTR).

By identifying the search queries that drive traffic to your website, you can also learn which paid keywords make the most sense for your business objectives. In addition, you can identify how to optimise your website for both content and search quality.

To integrate Webmaster Tools, you need to enable Webmaster Tools by editing the Property Settings on the Admin page, and following the instructions (see Figure 9).

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Figure 11: Enabling Google Webmaster Tools

2.3. Ecommerce Tracking

If your website sells products or services online, you should use GA ecommerce reporting to track sales activity and performance. The ecommerce reports show you your website’s transactions, revenue, and many other commerce-related metrics.

Figure 12: Conversions / Ecommerce / Overview

Some examples of the kind of information you can get from the ecommerce reports include:  The products that were purchased from your online store

 Your sales revenue

 Your ecommerce conversion rate

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2.3.1. Setting up ecommerce

1. Enable ecommerce reporting within your Analytics profile by selecting “Yes, an ecommerce website” in the drop-down menu

2. Ensure the Google Analytics Tracking Code is tagged on your confirmation page or “transaction complete” page

3. Add ecommerce tracking code to your confirmation page so that you can capture the details of each transaction – you will need the help of a developer and the Google Developers tutorial.

Here’s an example of what the ecommerce tracking code on your confirmation page might look like:

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2.3.2. 3rd party shopping basket

For many ecommerce websites, the checkout process occurs on a separate domain or subdomain. For example, if you send customers from www.mystore.com to basket.mystore.com, you’re sending them to a subdomain, and if the checkout process sends them from www.mystore.com to www.mysecurecheckout.com, you are sending them to a different domain.

If either of these scenarios applies to your website, you’ll need to add some code to some of your pages so that you can track activity across domains and subdomains. The specific methods you’ll use are listed on the Google Developers tutorial.

2.4. On-Site Search Tracking

Google Analytics provides internal Site Search reports that allow you to see how people search once they’ve arrived at your website.

By analysing your Site Search reports, you can find out which products or items visitors are looking for, where visitors started their search and where they ended up after searching and whether searches resulted in conversions.

Remember: Google Analytics reports use “search term” when referring to internal Site Searches and “keyword”, when referring to search engine queries.

2.4.1. Setting Up Site Search

In order to set up Site Search tracking for your website, you’ll need to configure your Profile Settings. 1. Select the profile on which you want to set up internal search

2. Once the Profile Settings page appears, select the Profile Settings tab

3. In the Site Search Settings section, select the ‘Do Track Site Search’ radio button.

4. In the ‘Query Parameter’ field, enter the letter, word or words that designate an internal query parameter (see 2.4.2. Query Parameter)

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2.4.2. Query Parameter

To find out what the query parameter is, perform a search on your website. The query can be found in the search result URL.

For example, if you search on “analytics training” on our website, you will see your search query preceded by “?s=”. Therefore, our query parameter is “s”

In the example above, the query parameter is “s”, and the query is “analytics training”.

If you have a particularly large website, some sections of your website may use different query parameters. You may provide up to five parameters, separating each parameter by a comma.

2.5. On-Page Interaction Tracking

Google Analytics tracks interactions via pageviews. However, some types of interactions don’t generate additional pageviews, such as video players, Flash games, file downloads or clicks outbound clicks.

There are two ways to track such on-page activities: virtual pageviews and event tracking (discussed below).

2.5.1. Virtual Pageviews

You can create a virtual pageview through the _trackPageview() function to represent practically any kind of activity or interaction you want. It’s “virtual” because you’re telling Google Analytics to register a pageview even though no new page has actually been loaded.

You can use virtual pageviews to track whitepaper downloads on your website, Flash events, pop-ups, iframes etc.

To create a virtual pageview provide any name you want as the argument to the _trackPageview() method as per the example below (e.g. /whitepaper/analytics-guide.pdf). Then insert the snippet in the code of the call-to-action you want to generate a pageview when clicked.

_trackPageview’,’/whitepaper/analytics-guide.pdf’

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 organise all of your virtual pageviews under a specific subdirectory (e.g. here /whitepaper/).

2.5.2. Event Tracking

The second way of tracking actions that don’t generate pageviews is through event tracking. This method is particularly useful to record interactions with video players and calls-to-action (“add to basket”, “download PDF”, etc.) as well as identify clicks on ads and internal links to understand what calls to action grabbed your visitors’ attention.

One advantage of using Event Tracking is that you can easily organise your events into categories, actions, and provide labels and even values for each event you track. Also, event tracking won’t inflate your pageview count. All of your events show up in the Events reports within the Content section.

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_trackEvent(category, action, opt_label, opt_value, opt_noninteraction)

Category – a name that you supply as a means to group objects (usually user interface elements that you want to track)

Action – name you want to give to the type of interaction you’re tracking

Label (optional) – allows you to provide additional information for the event you are tracking Value (optional) – use it to assign a numeric value to a tracked page object

Non interaction (optional) – generates a bounce on a page a user landed on and exited from even if their visit generated an event (yes/no argument)

Naming Convention

It is important to use a clear and consistent naming convention when creating events so that the reports are readable and provide actual insights.

The best approach is to determine in advance all of the kinds of events that you’ll want to track, so as to create a hierarchy of Categories, Actions, and Labels that will grow with your needs. Work with everyone who uses GA reports to make sure that the hierarchy makes sense.

For example, instead of just seeing how many times a video clip was played on your website, you can analyse how people use your video player, and see how different events correlate with website usage and ecommerce metrics.

Examples

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2.6. Goal Tracking

Every website has an objective, usually in the form of a specific action that it pushes the user to complete: buy a product, fill in a form, read a page, view an ad... These actions are the main conversion points which need to be tracked in order to measure your website’s performance against your objectives.

There are also multitudes of other measurable interactions which help direct the visitor towards the main conversion point. Tracking them can help you understand how you can help your visitors to convert more easily as well as how the different parts of your website are being used. Here is a non-exhaustive list of micro-conversion points:

 Newsletter subscriptions

 Content sharing via social media  Video plays

 Use of interactive tools (calculators, quizzes...)  Product customisation

 Add to basket

You can track all of these conversion points in Google Analytics by setting up goal tracking.

To set up a goal, first go the Admin page, select the profile for which you want to configure a goal and select the “Goals” tab. You can create up to 4 sets of 5 goals each.

Figure 17: Setting goal tracking

2.6.1. Goal Types

URL Destination – triggers a conversion when a visitor views the page you’ve specified. For an account sign-up, this might be the “Thank You for signing up” page. For a purchase, this might be the confirmation page. To define a URL Destination Goal, you don’t need to enter the complete URL, simply the request URI (Uniform Resource Identifier, which is what comes after the domain or hostname, including the “/”).

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Visit Duration – triggers a conversion when a visitor spends more (or less) time on your website than the threshold you specify.

Pages/Visit – triggers a conversion when a visitor views more (or fewer) pages than the threshold you’ve set. Event – triggers a conversion when a visitor performs an event you are tracking on your website (e.g. play a video, download a file...)

2.6.2. URL Match Types

If you set goals by URL Destination, you will need to select the type of match for the entered request URI. Head Match – indicates that the URL of the page visited must match what you enter for the Goal URL, but if there is any additional data at the end of the URL then the goal will still be counted. For example, some websites append a product ID or a visitor ID or some other parameter to the end of the URL. Head Match will ignore these.

Exact Match – means that the URL of the page visited must exactly match what you enter for the Goal URL. In contrast to Head Match, which can be used to match every page in a subdirectory, Exact Match can only be used to match one single page.

Regular Expression Match – gives you the most flexibility. For example if you want to count any sign-up page as a goal when sign-up pages exist in various subdirectories. You can create a regular expression that will match any sign-up page in any subdirectory (see 2.8 Regular Expressions (RegEx)).

2.6.3. Case sensitive Setting

Check the “Case Sensitive” box if you want the URLs you entered into your goal and funnel to exactly match the capitalisation of visited URLs.

2.6.4. Goal Value

For non-ecommerce websites, goal value allows you to assign a monetary value to goals. For example: you are tracking visitors who complete and send the contact form on your website. You know that one in 10 leads becomes a customer and your average order value is £200. So you can attribute a goal value of £20 for that goal.



The use of goal value is not restricted to non-ecommerce websites though, as you might want to assign a value to actions which are not ecommerce transactions, such as clicks on a partner’s advertisement.

By setting a goal value, you make it possible for Google Analytics to calculate metrics like average per-visit-value, page value and ROI. These metrics are calculated based on a combination of goal value and transaction value (revenue), so you need to be careful to only assign goal value to actions which aren’t already recorded by ecommerce tracking.

2.7. Goal Funnel Visualisation

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 go through on their way to complete the conversion.

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So, the goal page signals the end of the activity – such as a “thank you” or “confirmation” page – and the funnel steps are the pages that visitors encounter on their way to the goal.

Knowing the stage at which would-be customers abandon the process allows you to eliminate bottlenecks and create a more efficient conversion path. For example, if you notice that many of your visitors never go further than the “Enter delivery information” page, you might focus on redesigning that page so that it’s simpler for them to use.

When you use Regular Expression Match (as set up under 2.6.2 URL Match Types), the value you enter as the goal URL as well as each of the funnel steps will be read as a Regular Expression. Remember that regardless of which option you choose, Google Analytics is only matching request URIs. In other words, the domain name is ignored.

Figure 18: Conversions / Goals / Funnel Visualisation

While ecommerce tracking reports on shopping basket abandonment rate, it is not possible to visualise conversion drop-outs at a page level. That is why we recommend setting purchases as a goal with a funnel, particularly for multipage checkout processes.

How visitors move through the funnel

How visitors exit the funnel How visitors enter

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2.8. Regular Expressions (RegEx)

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.

To exclude a range of IP addresses, you can use GA’s RegEx generator.

RegEx can be tricky so be sure to test them on a separate profile before applying them to your data.

Metacharacter Purpose Example Match Does not match

. Match any single character Act. Act1,Act2,Act9 Act10, Act21 \ Use special characters as literal

characters

U\.S\.

Holiday U.S. Holiday UfSd Holiday - Signal a range of characters [a-z] Any lowercase letter,

once A, aa, B, ab...

[ ] Match any single character

contained within the brackets [abc] a, b or c d, e, f… ? Match the preceding pattern

element zero or one times colou?r color, colour + Match the preceding pattern

element one or more times ab+c abc,abbc, abbbc,... ac * Match the preceding pattern

element zero or more times ab*c ac, abc,abbc, abbbc ( ) Group a string of characters (G|g)oogle Google or google

| Separate alternatives gray|grey gray or grey

^ Signal the beginning of an

expression ^US Holiday US Holiday 2012 2012 US Holiday $ Signals the end of an expression US Holiday$ 2012 US Holiday US Holiday 2012

2.9. Social Media Integration

Social Media reports allow you to understand social activities happening both on and off your website as well as identify the real revenue value of your social presence.

All of your Social data show up in the Traffic Sources reports within the Social section. Traffic data, on-site activity and conversions from referring social networks are automatically recorded.

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To track on-site social interactions via social plugins however, you will need to use the _trackSocial() function. Google+ is automatically integrated.

_gaq.push([‘_trackSocial’, network, socialAction, opt_target, opt_pagePath]);

Network – social network being tracked (Facebook, Twitter, LinkedIn...) Social Action – social action being tracked (like, share, tweet...)

Target (optional) – URL or resource which receives the action (if undefined, page on which the action took place)

Page Path (optional) – page from which the action occurred (generally the source of the social action – only really necessary if you are using virtual pageviews)

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3. EVERYDAY ANALYTICS : How To Read Your Data

3.1. Definitions

Dimension – A dimension is a descriptive attribute or characteristic of an object that can be given different values. Dimensions appear in all of your reports, though you might see different ones depending on the specific report. Use them to help organise, segment, and analyse your data. In some reports, you can add and remove dimensions to see different aspects of your data.

Metrics – Metrics are individual elements of a dimension that can be measured as a sum or a ratio.

Although dimensions and metrics can stand alone, they usually are used in conjunction with one another. The values of dimensions and metrics and the relationships between those values is what gives meaning to your data. For the greatest insights, dimensions are often associated with one or more metric.

3.1.1. Dimensions

Action – action for the event being tracked (e.g. “Play”, “Pause” or “Stop” for video interactions) Ad Content – 1st line (headline) of your PPC ad

Ad Group – ad groups that you or your campaign manager have identified for your online ad campaigns Browser Type – name of the browser used by visitors to your website (e.g. Internet Explorer or Firefox) Browser Version – version of the browsers used by visitors to your website (e.g. 2.0.0.14)

Campaign – names of the online campaigns that you or your campaign manager use for your website Category – category pertaining to the event being tracked (e.g. “Videos” for video interactions) City – visitors’ city based on IP address

Connection Speed – network connection speed of visitors to the website (e.g. DSL, Cable, Dialup...) Continent – visitors’ continent based on IP address

Country/Territory – visitors’ country or territory based on IP address

Days to Purchase – number of days between users’ purchases and their first visit to your website Depth of Visit – number of pages visited by users to your website in a session (visit)

Entrance Page – request URI where the resultant page is the entrance or landing page for your visitors Exit Page – request URI where the resultant page is the last or "exit" page for your visitors

Flash Versions – versions of Flash supported by visitors’ browsers, including minor versions Hostname – hostnames visitors used to reach your website

Java Support– browser capabilities for visitors

Keyword – keywords (both paid and organic) used by users to reach your website

Label – optional label you can apply to a particular event you are tracking (e.g. “[movie name]” for video interactions)

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Landing Page – see Entrance Page

Language – user’s browser language returned in a 2 or 4 character code (e.g. “en-br” for British English)

Medium – This field identifies the type of referral to your website. Thus, while a referring source (URL) to your website might be a search engine, there are two possible mediums that can be used from a search engine referral: organic (from a search result) and cpc (from an online ad).

Operating System – operating system used by your visitors (e.g. Windows, Linux, Macintosh)

Operating System Version – version of the operating system of your visitors (e.g. “‘XP” for Windows or “OSX” for Macintosh)

Page – see Request URI

Page Title – <title></title> field of the HTML header area for your pages

Position – position of the advertisement as it appears on the hosting page (e.g. “side” or “top”) Product – product name

Product Category – product category as defined in your website’s ecommerce structure (e.g. “lighting”, “furniture” or “flooring”)

Product SKU – product code as defined in your ecommerce structure (e.g. “#1234325”) Provider Domain – fully-qualified domain of the service provider of visitors to your website Provider Name – name of the service provider of visitors to your website

Referral Path – referral URI (path and page, generally) of the referring site Region – visitors’ region based on IP address

Request URI – page or a set of pages on your website by path and/or query parameters (e.g. the request URI for the URL “www.mysite.com/about-us/” is “/about-us/”)

Screen Colours – screen colour depth of visitors’ monitors, as reported by the browser HTTP Request Header Screen Resolution – screen resolution depth of visitors’ monitors, as reported by the browser HTTP Request Header

Search Category – categories used for the internal search (e.g. “lighting” “furniture” or “flooring”)

Search Refinement – subsequent keyword search terms or strings entered by users after a given initial string search using the internal site search function

Search Terms – keywords used via your website’s internal search function

Source – used in reporting traffic sources to your site, identifies the domain of the referring source (e.g. “google” or “bing”)

Sub-continent – visitors’ sub-continent based on IP address Sub-region – visitors’ sub-region based on IP address Time On Site – visitor session duration for the day

Transaction ID – transaction ID for the shopping basket purchase as defined in your ecommerce structure (e.g. booking number, order number...)

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Visits – number of visits to your website, calculated by determining the number of visitor sessions (e.g. if a visitor comes to your site, exits their browser, and returns 5 minutes later via the same browser, that is calculated as 2 visits)

Visits to a Transaction – number of visits made to your website before a user makes a purchase

3.1.2. Metrics

% Exit – percentage of site exits that occurred from a page or set of pages % New Visits – percentage of visits from new visitors

Average Value – average value of an ecommerce transaction Avg. Visit Duration – average time spent per visit on your website

Bounce Rate – percentage of single-page visits (i.e. visits in which the person left your website from the entrance page/landing page)

Bounces – number of single-page visits to your site over the selected dimension (e.g. if you apply this metric to the Campaign dimension, it’ll display the number of single-page visits to your site by users that reached your site via a particular campaign)

Clicks – number of clicks that your ads received Cost – campaign cost

CPC or cost per click –average price you paid for each click on your search ads CPM or cost per mille – cost per thousand ad impressions

CTR or click through rate – clicks to impressions ratio Entrances – number of entrances to your website or page Exits – number of exits from your site or page

Goal Conversion Rate – the percentage of sessions on a website that include a conversion goal being reached Goal Conversions – number of overall goals completed by visitors

Goal1-20 Completions – total number of visitors who have completed all elements defined for a particular goal Goal1-20 Start – total number of visitors who have completed the first goal step for a particular goal

Goal1-20 Value – total cumulative value for a particular goal Impressions – number of times your ads were displayed

New Visits – numberof visits by people who have never been to the website before

Page Value – average value for a page a user visited before converting (Revenue + Goal Value, divided by Unique Pageviews for a page viewed before the conversion occurred) – formerly known as “$ Index”

Pages/Visit – number of pages viewed by users per visit

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Quantity – total number of items sold for the product (or group of products) Revenue –total revenue

RPC – revenue per click

Search Depth – average number of pages visitors viewed after performing a search Search Exits – number of searches a visitor made immediately before leaving the website

Search Refinements – number of times a visitor searched again immediately after performing a search Shipping – cost of delivery for a transaction

Tax – amount of tax included in the transaction price (e.g. VAT)

Time after Search – starting from the first use of internal search, time spent on website until either the session ended or until another search happened

Time on Page – time a visitor spent on a particular page or set of pages. It is calculated by subtracting the initial view time for a particular page from the initial view time for a subsequent page. Thus, this metric does not apply to exit pages for your site

Time on Site – time a visitor spends on your website

Total Unique Searches – total number of times your Site Search was used, excluding multiple searches on the same keyword during the same visit

Transactions – total number of transactions

Unique Pageviews – number of visits during which the specified page(s) was/were viewed at least once Unique Purchases – total number of times a product was included in a transaction

Unique Visitors – number of users that visits your website

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3.2. Dashboards

Dashboards are a great way to get an overview of the key performance indicators (KPIs) for your website. At DBD Media, we provide PPC, SEO, Social Media and CRO (Conversion Rate Optimisation) services, so we like to have one dashboard for each of these services to quickly showcase their performance.

3.2.1. Search Engine Optimisation

To install this dashboard on your Google Analytics account, log into GA and go to this link: http://tinyurl.com/SEO-dashboard and select the profile you wish to implement the dashboard on.

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3.2.2. PPC Advertising

To install this dashboard on your Google Analytics account, log into GA and go to this link: http://tinyurl.com/PPC-dashboard and select the profile you wish to implement the dashboard on.

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3.2.3. Social Media

To install this dashboard on your Google Analytics account, log into GA and go to this link: http://tinyurl.com/SMedia-dashboard and select the profile you wish to implement the dashboard on.

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3.2.4. Conversion Rate Optimisation

To install this dashboard on your Google Analytics account, log into GA and go to this link: http://tinyurl.com/CRO-dashboard and select the profile you wish to implement the dashboard on.

You might need to edit the widget settings to fit your website, such as replacing transactions with goal completions, revenue with goal value and ecommerce conversion rate with goal conversion rate for non-ecommerce websites.

3.3. Advanced Segments

Advanced Segments allow you to isolate and analyse specific kinds of traffic. For example, you might create a segment that only includes visits from users who have made a purchase. You can then browse through your Analytics reports, viewing data only for this segment or even comparing it side by side with data from other segments or data from all visits.

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Figure 21: Example of applied advanced segments Advanced Segments vs. Filtered Profiles

While filtered profiles may also be used to isolate and analyse subgroups of traffic, there are some key differences between using filters and advanced segments:

 You can examine historical (e.g. last month’s) data for an advanced segment, even if you only created the segment today. In contrast, a filtered profile will only contain data starting from the date you created it.

 You can see and compare multiple advanced segments side by side in reports. In contrast, you can only view data for one filtered profile at a time.

A filtered profile is usually the best choice if you want to always exclude a certain kind of traffic from your analysis. For example, while you can create an advanced segment that only includes external traffic, it would be better to create a profile that excludes internal traffic instead. That way, you won’t have to remember to apply the segment each time you look at reports. Also, you can always apply other advanced segments to the filtered profile data.

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Google Analytics Guide. A step by step guide to a best practice implementation of Google Analytics