ANALYTICSFOR PPCGOOGLE

Integrating AdWords & A/B Testing

D A N I E L W A I S B E R G

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eBook designed by Daniel Bronfen

D A N I E L W A I S B E R G

ANALYTICSFOR PPC

GOOGLE

Integrating AdWords & A/B Testing

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Daniel’s an expert in all things Google Analytics. Listen and learn. I do.

The data you get from Google Analytics is awesome. Google Analytics plus AdWords equals super awesome! Suddenly you are saving money and bringing more targeted visi-tors to your website - all tied to Macro and Micro Conversions. Did you think a humble eBook could do that? This one can. Buy it!

Daniel does a great job in his book helping users understand how to get up and run-ning with Google Analytics. He cuts through a lot of the noise and offers practical advice about how to get started with Google Analytics. With his book you’ll have the basics covered quickly and be on your way to insights fast.

Daniel Waisberg is a definitive authority in the analytics and marketing optimiza-tion space. One thing that makes him a consistent “must read” is his ability to articulate ideas in a way that’s accessible to all levels of marketer, tech-savvy or otherwise. His lat-est eBook on implementation best practices is essential in the library of all web workers responsible for data: from marketing manager to analyst. Useful links, step-by-step in-structions and examples from actual sites make it easy for everyone to follow. As market-ing measurement becomes more important daily you need to be sure you’re making the best possible use of tools and getting clean, integrated data. This eBook will get you on the right path to doing just that.

Danny Sullivan - Editor In Chief, Marketing Land & Search Engine Land

Avinash Kaushik - Author, Web Analytics 2.0 & Web Analytics: an Hour A Day

Justin Cutroni - Analytics Advocate, Google

Adam Singer - Product Marketing Manager, Google Analytics

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Daniel Waisberg is the Founder & Editor of Online Behavior, a respected Market-ing Measurement & Optimization portal. He has worked as a Google Analytics Certified Partner for over 4 years, delivering multiple training programs, account designs, and analytical insights to large and medium businesses (including 888 Holdings, Caesars Entertainment Corporation and Google.)

Daniel holds a MSc degree on Operations Research & Decisions from Tel Aviv Uni-versity where he developed a statistical model using Markov Chains to analyze online behavior. He presents at major conferences such as Google Engage, SMX and eMetrics Summit; he also writes for major portals such as Search Engine Land and Smashing Magazine. A full list of his articles and speaking engagements can be found at danielwaisberg.com

This eBook had a significant contribution by Yehoshua Coren, the Analytics Nin-ja. You can learn more about him at http://onbe.co/SYMmqi

ABOUT THE AUTHOR

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Copyright © 2012 by Daniel Waisberg - By reading this eBook you agree to be solely responsible for the use of any content and hold Daniel Waisberg harmless in any event or claim.

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INTRODUCTION 6

1. IMPLEMENTATION BEST PRACTICES 11

Implementing the right code 13Setting up the Google Analytics interface properly 14Campaign tagging best practices 17Managing implementations effectively 18

2. INTEGRATING WEBMASTER TOOLS 21

Linking Webmaster Tools to Google Analytics 23Webmaster Tools reports available on Google Analytics 25

3. INTEGRATING ADWORDS 31

Step-by-step guide to linking AdWords accounts to Google Analytics 33Analyzing AdWords campaigns using Google Analytics 37Content Experiments: Optimizing PPC campaigns with Google Analytics 53Testing tips and guidelines 57 ADDITIONAL RESOURCES 84

TABLE OF CONTENTS:

05

THE BLIND MEN AND THE ELEPHANT

I.

IT was six men of IndostanTo learning much inclined,Who went to see the Elephant(Though all of them were blind,)That each by observationMight satisfy his mind.

II.

The First approached the Elephant,And happening to fallAgainst his broad and sturdy side,At once began to bawl:“God bless me! – but the ElephantIs very like a wall!”

III.

The Second, feeling of the tusk,Cried:”Ho!—what have we hereSo very round and smooth and sharp?To me ‘t is mighty clearThis wonder of an ElephantIs very like a spear!”

IV.

The Third approached the animal,And happening to takeThe squirming trunk within his hands,Thus boldly up and spake:“I see,” quoth he, “the ElephantIs very like a snake!”

V.

The Fourth reached out his eager hand,And felt about the knee.“What most this wondrous beast is likeIs mighty plain,” quoth he;“’T is clear enough the ElephantIs very like a tree!”

VI.

The Fifth, who chanced to touch the ear,Said: “E’en the blindest manCan tell what this resembles most;Deny the fact who can,This marvel of an ElephantIs very like a fan!”

VII.

The Sixth no sooner had begunAbout the beast to grope,Than, seizing on the swinging tailThat fell within his scope,“I see,” quoth he, “the ElephantIs very like a rope!”

VIII.

And so these men of IndostanDisputed loud and long,Each in his own opinionExceeding stiff and strong,Though each was partly in the right,And all were in the wrong!

MORAL.

So, oft in theologic warsThe disputants, I ween,Rail on in utter ignoranceOf what each other mean,And prate about an ElephantNot one of them has seen!

A HINDOO FABLE - POEM BY JOHN GODFREY SAXE

INTRODUCTION

any marketers are still seeing a single part of their visitors’ interaction with their websites and brands: they can’t see all the factors (and data) that affect their websites. This happens mainly because data is scattered over multiple tracking tools, making it hard for professionals to integrate all sources of information into

one place. In addition, some platforms and networks still protect their data, making it impossible to export data in order to analyze it. As we will see in this chapter, Google is extremely well positioned to create an analytics platform that will centralize critical information for marketers.

As I discuss in the first chapter of this eBook, having a Google Analytics (GA) account properly set is a very good start. But in order to obtain a 360- ‐degree view of a company’s digital presence, it is essential to have as much information imported into Google Analytics as possible. In this chapter I provide a short introduction to Google Analytics and discuss the value, for website owners, marketers, and analysts, of integrating other Google tools into Google Analytics.

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To put it simply: every website on the web! While this might sound like an exag-geration, very few digital marketing professionals would disagree with the claim that Google Analytics is essential. GA is a standard in the Web Analytics industry. In a web analytics vendor research conducted in October 2011 by Cardinal Path (http://onbe.co/LgRD8L), a digital marketing agency, Google Analytics was found in 64% of Top 500 retail websites and 45% of Fortune 500 websites.

Google Analytics is used by large and small businesses alike (over 10 million websites.) However, while large enterprises typically employ analysts and expe-rienced online marketers, small businesses usually have Google Analytics imple-mented by a Jack- of- all- trades. So while this eBook will include technical terms, I try to explain the subject as clear and down- to- earth manner as possible, with screenshots that support the written explanations. Hopefully, both experts and occasional Google Analytics users will be able to implement the integrations pre-sented here. Clearly, if you do not (and will not) use AdWords to promote your website, this eBook is not for you.

One of the important advantages of Google Analytics over other analytics solu-tions is the large number of help articles available on the Web. So why would you need this eBook?

I have been working with Google Analytics since its launch, and I have been a Google Analytics Certified Partner for over four years. This experience has pro-vided me with the opportunity to be in a close relationship with the GA team and follow the product development closely. In addition, I have worked with over one hundred companies, large and small, on both the implementation of GA and the analysis of the data it produces, helping them to understand what can go wrong and how to fix it. Last but not least, during the writing of this eBook I conducted extensive research both on the official Google help centers and industry blogs in order to present the most accurate and comprehensive data to you. In other words, this eBook cen-tralizes everything you need to know about integrating and analyzing AdWords data with Google Analytics.

Please note that while I provide links throughout this book to Google help cent-

WHO NEEDS GOOGLE ANALYTICS AND THIS EBOOK?

WHY THIS EBOOK?

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ers and other critical resources, those links are largely there to meet the needs of readers with specialized needs. Indeed, one of the advantages of using this eBook as a starting place is that it can help you to avoid wading in a morass of details

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Briefly, integration refers to the process of unifying disparate parts to create a whole. In this context, Google Analytics allows AdWords advertisers to import data from it to be viewed and analyzed alongside GA reports. This means that instead of having to analyze data using AdWords, Analytics and other third party analytical tool, it is possible to centralize all information into GA to make data analysis easier and quicker.

While this eBook is specifically about AdWords, I have written eBooks on other in-tegrations as well. Check http://online- behavior.com/ebooks for a list of eBooks on the subject.

WHAT IS AN INTEGRATION AND WHY IS IT SO IMPORTANT?

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PC In this eBook I provide practical advice on integrating Google products into Google

Analytics, with detailed information and screenshots. If you use Google products long enough, you are probably aware that Google is constantly testing new flows and optimizing its products, which means you might not see exactly what I see.

I will update the book constantly, and I will appreciate if you drop me a line at http://onbe.co/Nv2JJJ if you are presented with a screen that is significantly dif-ferent from what is presented in the eBook.

Another important note is that I will provide Direct links to Google Analytics re-ports on this eBook. Whenever you read “Direct link,” it means that the link will send you to the report being discussed. Please note that you need to be signed in to your account in order to see them.

IF YOU LIKE THIS EBOOK, PLEASE CONSIDER ADDING A REVIEW ON AMAZON, IT WILL BE GREATLY APPRECIATED: http://onbe.co/T1tHti

A NOTE ON SCREENSHOTS AND DIRECT LINKS

IMPLEMENTATION

BESTPRACTICES

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oogle Analytics data is as good as its implementation. In order to use Google Analytics as a decision-making tool, companies cannot afford to rely on partial, inaccurate or otherwise misaligned data.

Google Analytics must be set up properly to meet the tracking needs and business objectives of a website.

In this chapter I discuss some of the most important steps in order to have data gathered in a clean and accurate way. I first discuss code implementation and then the settings required for Google Analytics and external campaigns. Last, I offer tips on how to keep the implementation under control, especially important for large enterprises.

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1.1. IMPLEMENTING THE RIGHT CODE

Google Analytics provides a wizard to help its users implement the right code. The wizard does a good job of pointing users to the most critical coding decisions when it comes to a basic GA implementation: multiple (sub)domains and mobile implementations.

In order to find the wizard, log into your account and click on “Admin” on the top-right corner of your screen (in the orange bar.)

You will reach the following screen.

Figure 1.1 – Google Analytics admin section

Figure 1.2 – Finding the Google Analytics tracking code

Figure 1.3 – The Google Analytics tracking code wizard

Clicking on “Tracking Code” will lead you to the wizard. The first decision you will need to make is whether you are tracking a website or a mobile application. If you are tracking a mobile application, I recommend you read further about how to proceed at the Google Analytics code website (http://onbe.co/PaIne9). The integrations discussed in this eBook are most relevant to website tracking.

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The second decision you will need to make is whether you are tracking multiple domains or subdomains. It is a common practice on the web to use subdomains and multiple domains to organize the content of an organization, especially when it comes to ecommerce checkout pages. Failing to take into account multiple do-mains when implementing GA can significantly decrease data accuracy.

In the wizard below, you will be able to choose the option that best fits your needs. However, I recommend you read thoroughly the guide at http://onbe.co/PaJvi7 (Google Analytics code website) to understand how tracking multiple domains or subdomains can affect your data. In the link above you will also find additional codes you might need to implement.

Figure 1.4 – Multiple domain tracking wizard

While other issues might appear when it comes to website coding, this eBook is not intended to cover all the required coding implementations. For such informa-tion, visit the Google Analytics code website at http://onbe.co/PaIne9

Below I provide the most relevant tips to create a good level of data accuracy and insight.

This should be a simple task if you follow Google Analytics’ recommendation: “Copy the following code, then paste it onto every page you want to track immedi-ately before the closing </head> tag.” However, commercial sites are more com-plicated than a handful of pages; if you manage a complex website check the Site Audit section in the official Google Analytics App Gallery (http://onbe.co/MVYgRu), it contains numerous solutions for automatic code snippet checks.

Goals are the soul of a Google Analytics account, no analysis will provide valuable insights if you do not measure your goals. Goals can be measured in multiple ways:

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1.2. SETTING UP THE GOOGLE ANALYTICS INTERFACE PROPERLY

MAKE SURE THE SITE IS 100% TRACKED

SET UP GOALS

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an ecommerce transaction, a thank you page for a newsletter subscription, a visit that lasted a certain time, a visit with a certain number of pages viewed, and others. Google provides a  handy guide  for setting up goals at http://onbe.co/KcQOBo .

Wide ranges of people may visit your website; unfortunately, that number includes employees of your own organization and service providers, neither of whom are the visitors you want to understand and optimize for. Therefore, it is important to create filters that exclude the IP range used by your organization and its service providers, such as web development and marketing agencies. Here is a guide on how to do it: http://onbe.co/MVZKv0

One of the interesting insights we can learn from Google Analytics is the naviga-tion patterns between website pages; you can find this information in the Content section of GA standard reports. However, websites can use multiple URL param-eters to refer to the same page (e.g., a session ID,) and Google Analytics consid-ers one page with multiple parameters as multiple distinct pages. Therefore, if your content is not unique for these parameters, you should remove the duplicate pages from your reports.

Google Analytics provides a simple interface to exclude URL parameters from re-ports (screenshot below.) When you add a parameter to the field shown below, GA will ignore the parameter, joining pages that might be considered separate pages. The screenshot below shows where to find this field on the Admin section of your account (to reach this page click on “Admin” on the orange bar upon login.)

FOCUS ON POTENTIAL CUSTOMERS

REMOVE UNIQUE URLS THAT DO NOT POINT TO UNIQUE CONTENT

Figure 1.5 – Excluding URL Query Parameters

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Google Analytics is case sensitive. This means that example.com/HELLO and ex-ample.com/hello would be recognized as two different pages, generating dupli-cated data. However, from a customer perspective, those pages are the same. Therefore, it is important to lowercase all URLs. Below is an example of how to create a filter for such purpose:

An excellent way to understand visitor intent is to study search terms used on the internal website search; they show what potential customers are looking for on the website. A proper  setup of GA’s internal search function will help web-site owners understand which content is being searched for, which searches are yielding irrelevant results and which ones are driving sales (or other goal) on the website. Here is a guide on how to do it: http://onbe.co/Kh9MVQ

Since the same issue can affect other fields, especially campaign data, I recom-mend creating filters to the following fields:

• Campaign Name• Campaign Term• Campaign Medium• Campaign Source

ELIMINATE DUPLICATE PAGES

UNDERSTAND VISITOR INTENT

Figure 1.6 – Filter to lowercase all URLs

1.3. CAMPAIGN TAGGING BEST PRACTICES

Properly implemented, Google Analytics can help you with the important task of tracking marketing campaigns. Google automatically detects when visitors reach a website through an organic search or website referral, but it won’t know a visi-tor came from a newsletter unless you give it a way to detect that. The same hap-pens to AdWords campaigns: unless you link AdWords to Analytics, you won’t see accurate numbers on your GA reports; but this is the subject of an entire chapter, now we will focus on other marketing campaigns.

If you are sending newsletters, advertising on Bing, doing banner campaigns or even offline advertising, it is important to use campaign tags properly. GA will show visitors coming from a billboard or TV ad as (direct) traffic; it will show visitors from newsletters as either (direct,) mail.google.com or other email pro-vider traffic; it will show visitors from banner campaigns as either (direct) or ad.doubleclick.net or the website itself traffic. These behaviors are clearly subop-timal when it comes to measuring campaign effectiveness.

For such cases, Google Analytics has developed a system for marketers to “tell” it if visitors came from a campaign using something called “UTM parameters” (UTM stands for Urchin Tracking Module, a remnant of Urchin, the tool Google acquired in order to build Google Analytics.) Basically, the system allows mar-keters to construct links that convey specific information about how the visitor arrived at the website. You can learn more about the technicalities of how the process works at the GA help center: http://onbe.co/NZrClm

Using the UTM method we can create links that include five variables which, tak-en together, help Google Analytics “see” how visitors have gotten to the website:

A. Source describes the origin of the visitor. Since every visitor must come from some place, this is a required parameter. It is usually the URL of the website where the campaign is running, such as “bing.com,” “cnn.com,” “facebook.com,” “newsletter” or others.B. Medium describes the channel used by the visitor. It is also a required parameter. It could be “cpc,” “banner,” “social,” ”email” or others.C. Name: describes the name of the campaign. It could be a special campaign, such as “Christmas 2012,” an ongoing campaign, such as “Product x,” or a newsletter edition, such as “newsletter-oct2012.”D. Term describes the term clicked on a campaign. It could be a search term on bing.com or a term used in a newsletter. For example, if you are advertising on Bing for the search term “analytics” and “tracking” you would have the source “bing.com,” the medium “cpc,” the name “Analytics Campaign,” and the terms “Analytics” and “tracking” for each ad.

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E. Content describes the version of an advertisement on which a visitor clicked. It is usually used to analyze the effectiveness of banner design or copy in a campaign. For example, if you advertise on CNN and use two different banners, you would use the same parameters for source, medium and name, but would add a unique value for each banner on the content UTM; this would enable you to learn which banner is better.

Google has developed a tool in order to build links using these campaign variables called URL Builder; it can be accessed at http://onbe.co/LRKhf7

If you have existing campaigns tagged with link parameters different from those GA uses (the UTM,) there is a way to translate them into UTMs without physically changing the campaign links; but this would require an addition to the GA track-ing code. For technical implementation details on the codes to be added, check the following section on the GA code website http://onbe.co/NZvHpK

Google Analytics implementations are a continuous process; there are always new features that require changes to the code or to the account settings. In order not to lose the thread, the analyst must be extremely organized. In this chapter, I pro-vide a method to avoid losing data and context on GA reports.

Below I describe four techniques that will help analysts and marketers to improve their data accuracy. If you are not acquainted with the definitions of accounts, web properties and profiles, read http://onbe.co/RaFTK6 in the Google Analytics code website.

1.4. MANAGING IMPLEMENTATIONS EFFECTIVELY

Suppose you decide to create a filter to lowercase URLs (as proposed above,) but you are uncertain about how it will affect your data. The best way to proceed would be to have two profiles with the exact same settings (the real profile, and the test profile) and apply the new filter to the test profile only. Once it is applied, you can check the data and compare the numbers to learn if anything went wrong (tip: wait for one full day of data.) Here is an article from the Google Analytics Help Center on how to add profiles: http://onbe.co/RaSUDj

If you have worked in web analytics long enough, you have probably seen data loss as a consequence of bad implementations. Code changes should be undertaken with care. However, since code changes affect all profiles, it is not effective to cre-ate a new profile in this case.

CREATING AN ANALYTICS STAGING PROFILE

CREATING AN ANALYTICS STAGING ACCOUNT

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Since most websites have a staging site where changes are tested before going live, I suggest having a different tracking code (i.e. a new Google Analytics account) used for those environments to test code changes on the Google Analytics script.

Changes are constantly made to Google Analytics profiles by users as they refine their website goals, improve filters, take advantage of new features, and so forth. Every change may impact data in several ways, sometimes in unexpected ways. For this reason, it is essential to have a system in place to keep track of code and profile changes, especially in large organizations where more than one person is involved with Google Analytics. Even when only one person is involved, this is important, as employees may go on leave, get promoted, or leave the company.

In order to facilitate/centralize the collection and sharing of the changes made to a Google Analytics account, I propose using a Google Docs form. The form should be created so that all interested parties can be aware of all changes. These will then be aggregated for historical knowledge that can be used by the whole team (and future teams members.)

Below is an example of such a form with fields that you might want to create (learn how to build a Google Docs form at http://onbe.co/RaUHIJ).

KEEPING TRACK OF INTERNAL CHANGES

Figure 1.7 – Tracking Google Analytics using Google Docs

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Back in 2010, the GA team announced a very important feature: Google Analytics Annotations. This feature allows website managers to provide context directly from inside the graphs on the interface, allowing for richer analyses. Here are some important occasions when you should use this feature:

• Offline marketing campaigns (e.g. radio, TV, billboards.)• Major changes to the website (e.g. design, structure, content.)• Changes to tracking (e.g. changing the tracking code, adding events.)• Changes to goals or filters.

While annotations can (and should) be used for technical changes to the website, it is important to keep them at a high level. You shouldn’t add detailed informa-tion about your changes or annotate relatively minor changes; otherwise the an-notations will become too dense to convey meaningful information to readers.

The use of both methods described above (form and annotations) should create an optimal mix. Watch this video to learn how to use the Annotations feature: http://onbe.co/RaWQ7h

In this chapter we went over best practices for Google Analytics implementations and provided recommendations on how to best set the tool so that it collects clean and accurate data.

We also discussed ways to avoid bad implementations by putting into place a pro-cess that requires users to report on changes made to their Google Analytics ac-counts. This not only helps avoiding mistakes, but also helps finding the source of problems, and solutions for fixing them quickly.

In the next chapters you will learn how to integrate Google tools into Google Analytics in order to enhance your data and create a powerful, data-driven, deci-sion making tool.

KEEPING TRACK OF EXTERNAL & OVERALL CHANGES WITH ANNOTATIONS

SUMMARY

INTEGRATING

WEBMASTER TOOLS

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earch Engine Optimization (SEO) is the process of optimizing a website in order to improve its visibility on search engines. In order to provide indexing information to webmasters so that they can optimize their

website visibility on search results, Google created Webmaster Tools. These tools provide a wealth of information, including (but not limited to): crawl errors, broken links, organic search traffic data, and sitemaps details.

This chapter provides a detailed step-by-step guide on how to integrate Webmaster Tools into Google Analytics as well as a walkthrough to the reports available once the integration is complete. While not all data can be imported into Google Analytics, having the tools integrated will bring additional reports into GA.

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The first step to link a Webmaster Tools account to a Google Analytics account is having the right accesses. The integration cannot be accomplished if you are not an administrator on Google Analytics and an owner on Webmaster Tools. Below are links to the Google help center for information on how to grant the right ac-cess to the person doing the integration:

• Google Analytics administrator: http://onbe.co/JL6Lul • Webmaster Tools owner: http://onbe.co/MTirBG

It is also important to note that the accounts are linked on the web property level; and a site can be associated with only one web property and vice versa. Creat-ing a new association removes the previously existing association. If you are not acquainted with the Google Analytics hierarchy, there are three levels used to manage report access and data collection. Below is a summary of the meaning of each level; you can read more at http://onbe.co/RaFTK6 :

2.1. LINKING WEBMASTER TOOLS TO GOOGLE ANALYTICSIN

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A. Account: an account is the mother of all web properties and profiles, and has a unique account ID that can be used to track multiple websites.B. Web Property: the web property has a unique ID, which is a combination of the account ID and additional digits. Since different web properties have different IDs, their data cannot be merged, but they will be found under the same account.C. Profile: the gateway to the website reports. It determines which data from your website appears in the reports. Filters can be applied to profiles in order to segment the data; for example, it is possible to create a profile only with visitors from USA, only with new visitors, etc. Since profiles use the same account and web property IDs, data for multiple profiles can also be seen in aggregate.

The GA-Webmaster Tools integration is at the web property level, and since it allows for just one-to-one integrations, it might be affected by the way Google Analytics has been implemented.

For example, when tracking websites that span multiple top-level domains (e.g., daniel.com, daniel.fr, waisberg.com), a common solution for implementing Goog-le Analytics is to have all top-level domains under the same web property (oth-erwise data cannot be aggregated.) Since Webmaster Tools accept only one top-level domain per account, webmasters would be obliged to open one Webmaster Tools account for each top-level domain. It would be problematic to have such accounts linked properly as we would have multiple Webmaster Tools accounts linked to one Google Analytics web property.

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Once the technicalities above are out of the way, the linking should be straightfor-ward. First, log into Google Analytics (as an Admin) and click on the Admin link on the top-right of your screen (in the orange bar); this link will appear only when you are viewing reports.

You will reach your administrator dashboard and you should click on the Property Settings tab. If this Google Analytics property is not linked to any Webmaster Tools account, here is what you should see:

In order to continue you must be a Webmaster Tools owner, otherwise you will see the following message: “Oops! Only site owners can access this feature.” Hav-ing the proper access, click on “Edit” to reach the following page (in the Webmas-ter Tools website):

In this screen, you should choose the Webmaster Tools account you would like to link to your Google Analytics and click on “Save.” This will lead you to a confirma-tion page alerting you that by saving this association you are removing all previous associations. Click on “OK.”

Figure 2.1 – Finding Webmaster Tools settings in GA

Figure 2.2 – Enabling Webmaster Tools data in GA

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You will be sent back to your Google Analytics Property settings where you will now see the new Webmaster Tools account. Note that by default all profiles will show this data; if you wish to limit the data to a number of profiles click on the box dropdown box “Enabled profiles,”choose the profiles that should have this data enabled, and click on “Apply.”

Your Google Analytics account is now associated with your Webmaster Tools ac-count. In the next section we will go over the reports that will now be available to you through Google Analytics.

In order to find the reports, log into your Google Analytics account and look for the Traffic Sources tab (left sidebar) on the Reports interface. You should find a set of reports called “Search Engine Optimization.” There you will find three reports available: Queries, Landing Pages, and Geographical Summary. Below is a summary of each report in this section.

Figure 2.3 – Enabling Webmaster Tools data in GA profiles

Figure 2.4 – Finding SEO reports in Google Analytics

2.2. WEBMASTER TOOLS REPORTS AVAILABLE ON GOOGLE ANALYTICS

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This report displays the top 1,000 daily queries with the following metrics: im-pressions, clicks, average position (ranking,) and click through rate (CTR.) Direct link to report: http://onbe.co/M6Seys

This and the other reports resulting from the integration are “hard coded,” i.e., it is not possible to analyze the data using any of Google Analytics analysis features such as Advanced Segments or Secondary Dimensions. However this report al-lows for an interesting view that can provide actionable insights.

The view below shows, in a glance, the click percentage for each keyword as compared to the average click percentage. You will be able to see the keywords with highest number of impressions and their clicks as compared to the average of clicked queries. This will show which queries are receiving high amounts of impressions on search results but are not succeeding in turning searchers into website visitors.

A good practice would be to check these queries and try to optimize the “search snippet,” the words that appear on the results page when someone performs a search, to improve click-through rate. The search snippet is the user’s first inter-action with your website, and ultimately it will determine the click-through rate of visitors coming from search engines. The snippet is what you promise to your user; are you delivering it in the landing page?

In order to reach this view, follow the steps below:A. Find the Query report (above is a direct link to report.)B. Change the graph type to comparison by clicking on the 4th icon to the right of the filter box above the main table.C. Change the right-most drop-down to “Clicks.”

QUERIES REPORT

Figure 2.5 – Queries report in Google Analytics

As we can see above, this report shows the queries searched that yielded a re-sult in your website (“hard work,” “success,” “big data”), it shows the number of impressions for each (in how many results they appeared), and the comparison between the different rates of clicks of each query.

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This report shows the top daily organic search landing pages for your site, up to a maximum of 1,000 unique URLs. The URLs are ranked by impressions (the number of times a search result included a snippet leading to the specific landing page) on Google Search result pages. You see the number of impressions and clicks for your top 1,000 pages, as well as the average position (where this page appeared on search results.)

With this report, you can see which pages drive the most organic search traffic to your site and which pages might need content improvements in order to deliver a better click-through rate. Direct link to report: http://onbe.co/MpwLxE

When discussing paid search campaigns, it is very natural to talk about landing page optimization; however, optimizing organic search landing pages is not so common. But the importance is the same; both should be highly efficient in con-verting incoming traffic. Unfortunately, Google Analytics does not provide any success metric in this report. This means that we can only learn which page brings the highest number of organic impressions and clicks, as well as their average position on search appearances (screenshot below.)

We can tell from this screenshot that the page with the highest number of impres-sions is /cartoons/success, and it has an average CTR. The page with the highest number of clicks and the highest CTR is /analytics/chart-types.

However, using Google Analytics standard reports we can analyze landing pages from search engines and discover how well they are performing. We will not be able to see this analysis side by side with the Webmaster Tools metrics (impres-sions, clicks, average position and CTR,) but knowing organic landing page con-version rates (i.e. the number of visits to a certain page divided by the number of visits that ended up in a purchase) will provide an excellent measure of SEO success.

In order to perform this analysis, log in to your Google Analytics account and click on this direct link: http://onbe.co/LkGaKG , which will lead you to the report below. The report shows all landing pages from organic traffic and their perfor-

LANDING PAGES

Figure 2.6 – Landing page report in Google Analytics

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mance when it comes to bounce rates or any other goal you have configured in your account. Here is a quick explanation of what you see:

A. Non-Paid Search Traffic advanced segment. This segment assures that only non-paid search traffic information will appear in this report. If you want to learn more about Advanced Segments check out this video http://onbe.co/LkJmGa B. Explorer. In this tab you will be able to choose which metrics will appear on the table below. As you can see, you will be able to see landing page performance by any Goal, Ecommerce or AdSense revenue.C. Visualization Type. As explained above, the comparison visualization is very effective when analyzing data. It shows how each row compares to the average of the website for a specific metric (middle grey line.) Note that for bounce rates (the rate at which visitors leave a site without interacting with it,) lower is better. Thus, below the average is represented in green and above the average is represented in red. For conversion metrics (the rate at which searchers visitors complete a website goal,) the colors would be inverse.D. Metrics drop-down: This drop-down can be used to choose which metric will be shown in the visualization. Metrics that can be used are % new visits, bounce rate, pages / visit, average visit duration, and other goal conversion metrics.

Figure 2.7 – Analyzing organic landing pages in Google Analytics

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The SEO Geographical Summary table provides a breakdown of impressions, clicks and CTR with Country as the default primary dimension. You can also select Google Property as a primary or secondary dimension to get a breakdown of the metrics by one of the following search types: Web, Image, Mobile, Mobile Smart-phone, or Video. Direct link to report: http://onbe.co/LUqN8H

The default view in this report, which shows countries where your site has been exposed on search queries, is interesting in order to understand in which coun-tries you appear the most on search results. This view can be used to understand CTR from different countries, which might be used to decide which countries need their own localized version using the country language.

The second view provides information about searcher behavior based on Google search properties (e.g., Image, Web, Mobile, Video, etc.) Direct link to report: http://onbe.co/PW3LmI . This information can be used to understand how your site is optimized for different properties. For instance, based on the information shown in the screenshot below, you might decide to create an image sitemap, which may draw more visitors through Google “Image” searches.

GEOGRAPHICAL SUMMARY

Figure 2.8 – Google properties report in Google Analytics

In this chapter we discussed the integration between Google Analytics and Web-master Tools. As we saw, while this integration is not complete, as it does not al-low deep use of Analytics features for Webmaster Tools data, it is certainly helpful and can be used to extract important insights.

If you are new to Analytics or SEO, I recommend reading “Analytics Tribulations of an SEO” (http://onbe.co/PW53hz), an article that focuses on how to analyze SEO traffic. Another interesting discussion of SEO metrics is http://onbe.co/LkReHR , where Jackson Lo describes 5 metrics that SEOs should be tracking:

A. Growth in brand vs. non-brand vs. (not provided) traffic and conversions

SUMMARY

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B. Conversions and engagement by keyword categoriesC. Conversions assisted by organic searchD. Last interaction conversions from organicE. # Landing pages > 1 visit

SEO is a very important practice, and analytics is extremely important in support-ing it. In the past, SEO success was measured by rankings of targeted keywords; then the focus moved to traffic; today we look to the bottom line: organic traffic must be measured by its impact on revenue.

A few takeaways:

• Check query performance (using impressions and click data) and try to optimize the search snippet to improve Click Through Rate.• Analyze landing pages from organic search engine traffic and discover how well are they performing.• Optimize your website for different Google search properties.

INTEGRATING

ADWORDS

3

inking Google Analytics to AdWords is essential to online marketers using both tools. It allows Pay Per Click (PPC) optimizers, professionals who manage AdWords accounts, to go beyond success and failure, i.e., to understand not only which campaigns are failing, but also what happens to visitors

who do not purchase (or complete any other goal) during their visits. This information can help efforts to improve campaign performance by shedding light on which campaigns are failing as a result of suboptimal targeting, poorly designed landing pages, or poor ads. In addition, by importing AdWords data into GA, marketers can compare campaign traffic to other sources of traffic, understanding how each can be optimized for its strength.

In this chapter, I also provide a bonus section on how to use Google Analytics Content Experiments, a tool to create A/B Tests. While this is not specific to AdWords and technically not an integration, testing campaigns can significantly increase Return On Investment (ROI) by creating a better experience to website visitors.

L

This chapter was co-written with Yehoshua Coren (learn about him at http://onbe.co/N5hVgb)

Below, I describe the process of linking and unlinking Analytics and AdWords ac-counts and then discuss some of the most common issues that might be encoun-tered in the process.

3.1. STEP-BY-STEP GUIDE TO LINKING ADWORDS ACCOUNTS TO GOOGLE ANALYTICS

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The first step to linking an AdWords account to Google Analytics is having the right accesses. The integration cannot be accomplished if you are not an Adminis-trator on both services. Below are links to the Google help center for information on how to grant the right access to the person performing the integration:

• Google Analytics admin: http://onbe.co/JL6Lul • AdWords admin: http://onbe.co/NuZpOC

Note: If you have multiple AdWords accounts linking to one Analytics account or multiple Analytics accounts linking to one AdWords account, you will need to repeat the process I am about to describe for each account.

This integration is performed from inside AdWords; the first step is to sign in to your AdWords account at adwords.google.com . Once you are logged in (as an administrator), click the “Tools and Analysis” tab, then click “Google Analytics.” On the top-right of this page, just below the green bar, click the “Admin” tab. If you have access to multiple Analytics accounts, you will need to choose to which you want to link the AdWords account. Now click the “Data Sources” tab, and you should see the following screen:

LINKING ADWORDS AND ANALYTICS

Figure 3.1 – Data Sources screen on Google Analytics

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When you click on “Link Accounts” you will receive the following pop-up:

In answering the first question, “How would you like to track AdWords clicks?” I highly recommend you choose to use Auto-tag, which means AdWords will ap-pend a unique ID to destination URLs that allows Analytics to report the details of clicks. Please note that if you choose to manually tag your links you will get less detailed information about your clicks; refer to this table to understand the implications of not using auto-tagging: http://onbe.co/MgJcNc (The question of whether or not to use auto-tags is extremely important, and we will discuss it more in-depth in the section about discrepancies between Analytics and Ad-Words.)

The second question is very straightforward: “Which Analytics profiles should this AdWords Account be linked to?” This choice is important if some of the Analyt-ics users are not supposed to have access to AdWords data. When you choose a profile, cost data will automatically be applied to it; that is, you will be able to see actual costs of clicks and campaigns in those profiles. It is always recommended to have a profile in your account with the same settings as your main profile, but without PPC data, this way you will have a backup in case you need to share infor-mation with a third party that shouldn’t have access to PPC data.

Click “Continue.” Your accounts should now be linked. If you opted to keep auto-tagging turned on, Analytics will automatically tag your AdWords links, and you can track the behavior of visitors coming from your AdWords ads. If you want to link another AdWords account to your Analytics account, repeat the procedure above using the additional AdWords account.

Figure 3.2 – Linking AdWords to Google Analytics

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Now that the accounts are linked, you might want to go the other way around and import Analytics goals and transactions to AdWords conversion tracking; here is a detailed step-by-step guide: http://onbe.co/OQHIrC

My Client Center (MCC) is a tool provided by Google to manage multiple Ad-Words accounts, an “umbrella” account with several AdWords accounts (called “managed” or “child” accounts) linked to it. It is heavily used by agencies that manage multiple AdWords accounts, but large advertisers also use it (e.g., compa-nies that have one AdWords account per GEO location or per brand.)

Google recommends that each My Client Center (MCC) managed account have its own Google Analytics account, although that might not be relevant if, for ex-ample, a large enterprise uses different AdWords accounts for different GEO loca-tions. You cannot link client-manager MCC accounts to an Analytics account, as these top-level MCC accounts contain no AdWords campaign information.

In order to link an MCC child account to its Analytics account, log in to AdWords with the MCC client-manager account and navigate to the child account you want to link to an Analytics account. Within the child account, click the Reporting and Tools tab, and then repeat the process described in the previous section.

Unlinking Analytics and AdWords accounts from the GA interface is simple, and the process is the same if you want to manage which profile has access to this data.

First, log in to Google Analytics and click on “Admin” on the top-right corner of your screen (in the orange bar.) Then, click on your account name, as seen in the image below:

LINKING ANALYTICS ACCOUNTS TO MY CLIENT CENTER -MCC- ACCOUNTS

UNLINKING AND MANAGING ANALYTICS ACCOUNTS AND ADWORDS

Figure 3.3 – Unlinking and managing Analytics Accounts and AdWords

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Click on the “Data Sources” tab and you will reach the following page. In this page you can both unlink accounts and manage which profiles have access to this in-formation. This might be important for companies where not all employees have access to AdWords information or where a company works with multiple Search Marketing agencies. Usually cost data is confidential and not shared with all Google Analytics users.

If you followed the steps above, your data should be accurate: Happy analyzing! But, if you find numbers that do not match between the tools, it is probably the result of one of the issues below. While other problems might appear, the Top 10 list below covers the vast majority of discrepancies between Analytics and AdWords data.

1. The date range being compared includes a period during which the accounts were not linked.2. There are multiple AdWords accounts linked to the same Analytics profile, which means data from multiple AdWords accounts is needed in order to match the numbers.3. The Google Analytics tracking code is not placed on the ad’s landing page: this causes the campaign information to be lost. Alternatively, the landing page may redirect to a different page, which keeps the Google Analytics code from launching and properly identifying the visit as having come from a paid search campaign.

Once you unlink this account, all AdWords cost data will be removed from Google Analytics. Cost data from AdWords (i.e: clicks, impressions, cpc, etc.) will no longer be visible in Google Analytics reports. Visit data up until the time you unlink the account will still be available. Any new visits that result from clicks in this AdWords account after you have unlinked will appear in Analytics reports as “(not set).” If you only wish to remove AdWords data from a single profile: Edit the profiles settings to deselect the AdWords account under AdWords Cost Source Settings.

“

“If you proceed to unlink the accounts you will receive the following reminder before completing the process:

DATA DISCREPANCIES BETWEEN ANALYTICS AND ADWORDS

Figure 3.4 – Unlinking AdWords from Analytics

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4. There are filters applied to Google Analytics (such as excluding internal IPs, discussed in the first chapter of this eBook); these filters do not apply to AdWords reports.5. Google Analytics and AdWords do not synchronize at the same time, so if the report is very recent (such as same day reports,) the data may not match.6. Google AdWords tracks clicks, while Google Analytics tracks visits. If a user clicks on an ad twice within thirty minutes without closing his or her browser, this is registered by Analytics as one visit while it is registered as two clicks on AdWords. 7. AdWords automatically filters invalid clicks (e.g. clicks generated by robots or multiple clicks from the same user at the same time), while GA reports on all the resulting visits to a website. 8. Auto-tagging is turned off or the “cost data” option is not applied. This can lead to a series of undesirable situations. Learn more about this at http://onbe.co/MgJcNc9. Cookie expiration dates are different in AdWords and Analytics: AdWords cookies expire 30 days after a customer’s click, while Analytics uses a cookie that expires in two years. That means if a customer completed a conversion 31 days after clicking on an AdWords ad, the conversion wouldn’t be recorded in AdWords but would be in Analytics.10. If a visitor comes to your site from an ad, and then leaves the landing page before the tracking code executes, then the gclid parameter (which is added automatically by AdWords’ auto-tagging to track campaign data) is never passed to the Google servers and that click is not associated with the visit.

Below, I describe the process of linking and unlinking Analytics and AdWords ac-counts and then discuss some of the most common issues that might be encoun-tered in the process.

3.2. OPTIMIZING ADWORDS CAMPAIGNS USING GOOGLE ANALYTICS

In order to understand how the different reports in Google Analytics work, we first need to introduce the concepts of “dimensions” and “metrics.” I will then discuss the dimensions and metrics that are specific to AdWords, and how they are used in both standard and custom reports.

Dimensions: describe dataDimensions are what make up the rows in GA reports. Google defines a dimension as “a descriptive attribute or characteristic of an object that can be given different values.” In other words, dimensions describe the visit, visitor, page, or event. For

DIMENSIONS & METRICS

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example, both Source and Medium are considered dimensions. For a visit from an AdWords ad, the Source/Medium combination will be “google / cpc.” One can then drill down into that dimension to see more granular data (additional dimen-sions) about the visit, such as: the ad campaign, the ad keyword, geographic loca-tion, browser type and version, device used, and more).

Metrics: measure dataMetrics make up the columns in GA reports; they are the numbers themselves, the actual data. Google defines metrics as the “individual elements of a dimension that can be measured as a sum or a ratio.” The most common metric in Goog-le Analytics is “visits,” which is simply the number of visits within a certain date range. Other common metrics include bounce rate, pageviews, conversion rate, and revenue. Metrics offered in the form of a “ratio” are almost always calculated by dividing the sum of a particular metric by the number of visits.  For example, the conversion rate for a particular goal is the percentage of visits when the goal was completed (# of goal completions divided by # of visits).

The picture below describes the hierarchy of an AdWords account. Note that we describe the different elements of the account vis- à-vis dimensions. The image below will serve as a good starting point for understanding AdWords account structure in general and AdWords specific dimensions in GA.

Campaigns are at the highest level of an AdWords account. Campaigns are com-prised of ad groups, which in turn contain the keywords and ads triggered during a search (or which placements on the display network that are determined by site URL). Campaigns are particularly important because the majority of targeting

ADWORDS ACCOUNT STRUCTURE

Campaigns

Figure 3.5 – Google AdWords account structure

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and budget settings are controlled at the campaign level.

The following is a list of the most important AdWords Campaign settings. For a more in depth introduction to campaign settings and ad targeting, please see this help page from Google: http://onbe.co/QWLXFa

A. Network. Determines which networks will display ads in the campaign. This can be limited to search ads on Google.com itself, ads on Google and its search partners, or the Google display network, the world’s largest display advertising network comprised of over 2 million websites (learn more about the Google display network at http://onbe.co/OrMhQ4).B. Devices. Determines if ads will appear on computers, smartphones, tablets or a combination of the three.C. Location. Determines the specific geographic location where ads will appear (for example, United States). Location can be limited to very granular areas (such as a particular zip code).D. Language. Limits ad presentation to users who have browsers set to the language(s) indicated.E. Budget. Specifies the daily budget cap for a campaign.F. Ad Scheduling. Establishes days of the week and hours of the day during which ads will display.G. Ad Rotation. Determines how often one ad is chosen to display in relation to other ads within an Ad Group.

While there are other campaign settings in AdWords, the above list contains the settings most relevant to optimizing AdWords performance. Because Google An-alytics has dimensions that correspond to network, devices, location, language, and ad scheduling, insights gleaned from GA data can directly impact how adver-tisers configure their campaign settings.  

Rather than using the default campaign names (e.g. Campaign #1), or naming the campaign by date of creation (New Campaign Fall 2012), you should give your campaigns descriptive names that make it easy to determine the focus of the key-words and ads therein. If the campaign is focused on a particular product brand or product type, name it as such. For example, an online food retailer might have one campaign named Sports Drinks and another named Energy Bars. This naming strategy allows the retailer to quickly determine how much money is being spent on each category. It is also a best practice to have separate campaigns for Search and for Display advertising.

An ad group is a set of keywords, ads, and bids; each campaign is made up of Ad groups

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one or more ad groups. When a search is performed on Google.com or a search partner site, the keyword triggered will display one of the ads in the ad group. Ad groups that make up these campaigns should be comprised of tightly knit group-ings of keywords that relate very closely to the copy of the ad. Keyword types will be discussed in the next subsection.

Ads in the display network can be triggered by a number of different signals, in-cluding keywords, placements, and audiences (including retargeting). When key-words are used in the Google display network, the AdWords algorithm contextu-ally places ads within its network. These are known as “automatic placements.”

Specific websites can also be added to the ad group and/or bids adjusted for web-sites discovered through automatic placements. These are known as “managed placements.” For example, if I reach the conclusion that the quality of the traffic I get from The New York Times is particularly relevant, I can bid higher on that particular site to increase the number of times my ad is displayed there.

Lastly, ads can be targeted to different “audiences,” either groups of websites that are categorically similar or groups of people who have visited your site that have an AdWords remarketing cookie set in their browser.

KeywordsIn the search network, keywords are what trigger an ad to display in response to a query. For organic search, a keyword is defined as the exact query that a user en-tered into the search engine. For Pay-per-Click (PPC) campaigns, keywords have four different match types.

A. Exact Match. Keyword triggered by the exact query the user searched at Google.B. Phrase Match. The query must contain the words in the keyword phrase in the exact order used.C. Broad Match. Keyword can also be triggered by conceptually related terms or synonyms; word order does not matterD. Modified Broad Match. Like broad match, but synonyms will not trigger the keyword.

Examples of different matching options can be found at http://onbe.co/QWMqqV

Below is a list of all AdWords-specific dimensions available on Google Analytics following the integration and a short description of the dimension.

A. Campaign. As noted above, the campaign is the highest structural level in an account where many important targeting settings are set.

LIST OF ADWORDS DIMENSIONS ON GOOGLE ANALYTICS

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B. Ad Content. The headline of an AdWords ad, a useful identifier of an ad that is natively set by AdWords in GA.C. Ad Distribution Network. Google, search partners, content (display.)D. Ad Group. As noted above, ad groups make up campaigns and are comprised of keywords, placements, or audiences.E. Ad Slot. The position of the ad clicked in the search result page. Either top or right hand side (RHS).F. Ad Slot Position. The position of the clicked ad within the ad slot: 1-3 for top 1-9 for RHS.G. Campaign Code. A new feature that allows advertisers to automatically set Source/Medium and Campaign name information based upon their own codes.H. Social Annotation Type. The type of Google Plus +1 annotation made to an ad: none, basic, or personal. Social annotations can display on ads in the Google display network.I. Placement Domain. The website where a display ad was shown.J. Placement Type. Automatic (contextually targeted) or “managed placements” (manually targeted or bid enhanced.)K. Placement URL. The full exact URL where a Display Ad was shown, similar to placement domain, but more granular data.L. Destination URL. The full, exact URL entered into the AdWords system that defines the landing page for one’s ads.

Below is a list of all AdWords specific metrics available on Google Analytics follow-ing the integration and a short description of the metric.

A. CPC. Cost per click.B. CPM. Cost per 1,000 ad impressions.C. CTR. Click through rate, the ratio of clicks to impressions.D. Clicks. The number of clicks received.E. Cost. The total cost incurred for clicks and impressions (impressions cost money when doing CPM bidding in the display network.)F. Impressions. The number of times an ad was displayed (or keyword triggered.)G. Margin. (ecommerce revenue + total goal value - cost) divided by revenue. Represented as a percentage.H. ROI. Return on Investment, (ecommerce revenue + total goal value - cost) divided by cost.  Represented as a percent.I. RPC. Return per click, total configured value in GA (ecommerce revenue + total goal value) divided by clicks.

LIST OF ADWORDS METRICS ON GOOGLE ANALYTICS

Underneath the Advertising section of the left navigation in GA, you’ll find links ADWORDS STANDARD REPORTS OVERVIEW

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Figure 3.6 – Google AdWords reports on GA

The main benefit of this report is that it allows you to quickly identify which campaigns, ad groups, and keywords are performing best and worst.  The cam-paigns report allows you to drill down into the different campaigns based upon the hierarchical structure described above. At each level of drilldown, you may toggle between preset primary dimensions, as well as choose secondary dimen-sions from the list of AdWords dimensions listed above and other standard dimen-

CAMPAIGNS REPORT

Figure 3.7 – Campaign report overview

to the seven standard reports that GA offers for AdWords. At this time, Google Analytics does not import cost data or other performance in-formation from any other advertising platform (such as Microsoft AdCenter, Facebook Ads, or any of the Comparison Shopping Engines). The following is a brief introduction to each of these reports. Methods for using these reports and custom reports to optimize PPC accounts are shared in the next section.

Quick links to advanced segments by device type.

Tab between different sets of metrics

Toggle between campaign and ad group.

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The drilldown nature of the report allows you to easily see the overall account performance, while at the same time offering a granularity that can help you gain insights to make pinpoint level changes.

As with all AdWords standard reports, all of the AdWords-specific metrics are pre-sent in the “Clicks” tab (with the exception of CPM).

Figure 3.8 – Keywords report with example of a secondary dimension by match type

This report is similar to the campaigns report described above, but the primary di-mensions are keyword or ad content, irrespective of campaign and ad group. The main benefit of this report is the ability to analyze all keywords in an account in one place, which makes it easy to identify poorly performing keywords. It is im-portant to remember that the keywords shown in this report are not identifiable by match type unless match type is chosen as a secondary dimension.

In PPC campaigns, one bids on keywords that are of a particular match type. As such, it is critical to know how a keyword is performing at the match type level. In the example below, we see a significant difference in performance metrics be-tween the same keyword in phrase match vs. exact match. If one were to look at the keyword report without applying a secondary dimension of match type, one might think that this particular keyword was performing quite well. In reality, the same keyword in phrase match is losing money whereas the exact match is quite profitable.

The Matched Search Queries report is extremely useful for both keyword research and for finding opportunities to add negative keywords to one’s AdWords campaigns. The

KEYWORDS REPORT

MATCHED SEARCH QUERIES REPORT

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Figure 3.9 – Graph showing visits per hour

report defaults to two primary dimensions: matched search query and match type.

From a keyword research perspective, having the full list of queries that brought people to your site can help identify well performing search terms that you might not be currently bidding on. On the flip side, there are times when broad and phrase match keywords may be bringing non-relevant traffic to one’s site. Using this report, one can quickly browse through the actual search queries to add to negative keyword lists. A step-by-step guide to using matched search queries for adding negative keywords follows the optimization section of this chapter.

Currently, the match search queries dimension is not mapped to AdWords cost data metrics. In order to view information such as total spend or cost per click for these queries, use the keyword details report underneath the Keywords tab in the AdWords interface.

Also note that you will probably find a “(not set)” entry on the matched search queries report. In most cases, this is traffic from the Google display network where there indeed was no query performed. Other reasons “(not set)” can occur include mobile browsers not passing referrer information to Google Analytics or searches being conducted on Google encrypted search, where this information is held back completely (different than “not provided” organic keywords, where only the keyword is absent.)

The Day Parts report is for exploring hour-of-day and day-of-week dimensions. This report is useful for gaining insights into optimizing ad scheduling in campaign settings within AdWords.

In the figure above, we see that this advertiser sees its traffic peak between 5 and-8 p.m. When adding a secondary dimension of per visit value, however, we see that the per visit value of visitors is highest during the morning hours of 6-9a.m.

DAY PARTS

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Figure 3.10 – Graph showing visits per hour and per visit value

The practical next step this advertiser would take would be to adjust the ad scheduling settings in its campaigns to drive more traffic to the site during those morning hours, as that traffic is more valuable. Here is how to do it:

A. Navigate to a specific campaign in the AdWords interface.B. Choose the Campaign Settings tab.C. Under Advanced Settings, click the plus (+) box next to Schedule: Start Date, End Date, Ad Scheduling.D. Next to Ad Scheduling, choose Edit.E. Change mode from Basic to Bid Adjustment.F. Under Time Period (next to day of week), click to reveal an overlay.G. Adjust the bid settings (by a percent multiplier to increase or decrease bids). There is a button to copy to other days to speed up making these changes.H. Click OK and then save.

The Destination URLs report is designed to explore the destination URL, ad distri-bution network, and keyword dimensions.  At the time of this writing, the landing page dimension is not available in any of the standard AdWords reports, so one must rely on destination URL report (or use custom reports). Destination URLs cannot be re-written with filters in GA. As a result, any bid management software or other tracking parameters will populate the Destination URL dimension.

On the flip side, when bid management software is not being used, the destina-tion URL is an excellent way to add tracking parameters that distinguish between ads. The ad content dimension in GA AdWords Reports, while useful, will only provide the headline for ads. When two different ads share the same headline but split testing is being done on the rest of the ad copy, there is no default way for GA to report which ad sent the visit one’s site. Adding a tracking parameter to the destination URL in AdWords is a great way to gain visibility into ad split testing. This tracking parameter can be removed from all other reports via GA profile set-tings, but will remain in the Destination URL of AdWords reports.

The Placements report provides quick access to the placement type, placement

DESTINATION URLS

PLACEMENTS

Per visit value peak between 6-9 am Visit peak between 5-8 am

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Figure 3.11 – Keyword positions report

domain, and placement URL dimensions. Like the Matched Query and Day Parts reports, the Placements reports (and its dimensions) are not linked to AdWords specific metrics. The default screen of the Placements report shows placement type (either automatic or managed), from where you can drill down into the spe-cific domain that sent traffic.

The Keyword Positions report is the default report that utilizes the ad slot and ad slot position dimensions. The report currently does not integrate AdWords cost data, although the AdWords specific metrics are indeed available for the ad slot and ad slot position dimensions. The report allows you to select a single keyword and then provides a visualization for that keyword at different positions.

This section is a guide to optimizing PPC accounts based on Google Analytics data. While I try to be comprehensive in my presentation, PPC management and optimization is an industry in and of itself and there are many different approach-es practitioners take to this process. The goal of this chapter is to provide those with beginner, intermediate and hopefully advanced PPC skillsets with insights into how to access the valuable data store that Google Analytics has to offer to PPC optimizers and analysts.

In the figure above, we see that the selected keyword (blurred in row 2) sent the majority of its visits to the site from top 2 positions. Other metrics, such as bounce rates or conversion rates, can be seen across positions as well.

However, there is a fundamental flaw with this report: it is not possible to distin-guish between match type and ad distribution network (via advanced segment or otherwise.) As such, there is little actionable insight when it comes to optimizing keyword bids since bidding is done on the keyword + match type level. The return on ad spend (ROAS) can be very different for a keyword based on match type.

KEYWORD POSITIONS

OPTIMIZING PPC CAMPAIGNS

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It is a best practice to create separate profiles for PPC traffic, organic traffic, and overall search traffic. Doing so allows one to compare the performance of cam-paigns and keywords to each other, and not just to the site average. Since web-sites usually have revenue streams from direct traffic, email marketing, or organic search (return visitors with a high propensity to buy), it is not always relevant to compare PPC traffic with the website average, which might target different seg-ments of visitors and customers.

Therefore, by creating a separate profile just for PPC traffic we are able to see a much cleaner view of how PPC campaigns perform as compared to other cam-paigns. (The numbers of visits are not exactly the same due to slightly different filters on the profiles, but the main point is still expressed).

To create profiles you must have administrative access. Below are the steps need-ed to create a profile:

A. Go into the Admin section of Google AnalyticsB. On your main profile, click the Profile Settings tab.C. Click on “Copy Profile” in the bottom right cornerD. Name the Profile (Paid Search or similar) and click the Copy Profile ButtonE. In newly created profile, click the Filters tab.F. Choose Filter Type: Custom FilterG. Selected Radio Button “Include”H. Filter Field = Campaign MediumI. Filter Pattern = cpc|ppc. To create a profile for ALL search, paid and organic, the filter patter would be cpc|ppc|organic   -- the pipe bar means “or” in regular expressions.K. Case Sensitive = noL. Click the Save button

While most advertisers spend the majority of their time and money with Google AdWords due to Google’s market share in search, Bing ads (formerly adCenter) can be an important traffic channel. It is common for advertisers import their AdWords campaigns directly into Bing. In order for Google Analytics to properly track visits from this traffic source, however, the destination URLs for Bing Ads need to be manually tagged (as explained in the first chapter of this eBook: Imple-mentation Best Practices.) The following is an effective way of tagging Bing Ads:

A. Source = Bing AdsB. Medium = cpc

CREATING UNIQUE PROFILES FOR SEARCH ENGINE TRAFFIC

TAGGING BING ADS

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C. Campaign = [campaign name]D. Term = {keyword}E. Ad Content ={QueryString}F. matchtype (optional) = {MatchType}

When campaigns are mirrored between AdWords and Bing ads, you will be able to compare how each campaign performs from each traffic source. The campaign name needs to be set manually in the destination URL. Term will dynamically in-sert the keyword in the keyword dimension, whereas we use the ad content di-mension to capture the “matched search query.” Since there is no search query report available in GA for non-AdWords platforms by default, we effectively lever-age the ad content dimension to turn GA into a search query reporting engine for Bing ads. Match type was noted as being optional because it requires capturing the match type and then using a profile filter to pass that information into the User Defined Value dimension.

The resulting URL looks something like this (%20 represents a space):

http://www.example.com?utm_source=Bing%20Ads&utm_medium=cpc&utm_campaign=exact%20campaign%20name&utm_term={keyword}&utm_content={QueryString}&matchtype={MatchType}

To create tags, use the GA URL Builder at http://onbe.co/S3Cm4a, this Google Analytics App http://onbe.co/S3CznT, or Excel to concatenate fields.

To add the MatchType to the User Defined Value field, use the following Ad-vanced Filter:

A. Custom FilterB. AdvancedC. Field A: Request URID. Extract A: (.*)&matchtype=([^&]*)E. Output To: User DefinedF. Constructor: $A2

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Also, make sure to remove the match type from URLs in the content report using the following Advanced Filter:

A. Custom FilterB. AdvancedC. Field A : Request URID. Extract A : (.*)&matchtype=([^&]*)E. Output To: Request URIF. Constructor : $A1

Figure 3.12 – Inserting match type as a user defined variables

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Figure 3.13 – Removing match type from content reports

When thinking about measuring the performance of inbound traffic in GA, Avi-nash Kaushik provides a highly insightful framework: Acquisition, Behavior, and Outcomes (or the “ABCs” - Acquisition, Behavior, and Conversions.) Avinash’s blog is a fountain of insight, but this post is a particularly good starting point: http://onbe.co/S3EzfX .  

The ABCs are a way to group different metrics. Acquisition metrics measure the number of people coming to the website, the percentage of new visitors, the cost to acquire them, etc. Behavior metrics measure the interaction of users with the website apart from goals: bounce rate, pages per visit, time on site, etc. Conver-sion metrics measure the desired actions that users take on the site, such as con-version rates, per visit value, ROI, etc.

While the out-of-the-box reports described above are extremely useful, ultimate-ly using custom reports will provide more flexibility in the analysis and allow you to put most of the key performance indicators (KPIs) on the same screen without the need to flip between tabs. For example, bounce rate and per visit value can be

IDENTIFYING WINNERS AND LOSERS - THE ABCS

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in the same tab, instead of bounce rate under site usage and per visit value under ecommerce.

Below is a sample custom report, followed by an explanation of how it would be used to optimize campaigns. The example is for an ecommerce store, you can create this custom report by logging into your account and opening the following link http://onbe.co/SgdX60 .

Following the creation of this report, we will be able to sort, filter, and segment the data to determine which campaigns (or ad groups or keywords) can be paused, which bids can be adjusted, or which campaign settings can be changed.

A good starting point for identifying winners and losers is the bounce rate. While bounce rate definitely needs to be analyzed contextually, in most circumstances

Figure 3.14 – Sample custom report

Acquisition

A

A

B

C

A

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Behavior

Conversions

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advertisers bring visitors to their websites hoping that the visitor has some level of interaction with the website (such as browsing multiple products, download-ing a white paper, or filling out a contact form). For most PPC accounts, a high bounce rate is problematic. Consult this article for a more detailed analysis of how to interpret bounce rates http://onbe.co/UDTbP4 .

However, simply sorting the list of campaigns by bounce rate from high to low yields a number of campaigns that are irrelevant due to very low traffic. Instead, you should apply weighted sort to the bounce rate metrics and GA will automati-cally sort the list of campaigns by weighted importance. All of the campaigns that “float to the top” deserve drilling down into the ad groups and keywords to analyze if any of them is leading to wasted spend.

Another way to quickly identify winning and losing campaigns is to sort by ROI (if you have ecommerce tracking and/or goal values configured.) At this time, weighted sort for ROI is not available, so we will use an advanced filter to make sure that we are displaying the most relevant campaigns (based on volume.) In the example below, we include only campaigns that hit a certain spend threshold.

Figure 3.15 – Using weighted sort helps increasing analysis relevance

Figure 3.16 – Using weighted sort helps increasing analysis relevance

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The figure below has a sample custom report that can be used to identify oppor-tunities for adding negative keywords to ad groups or campaigns. You can create

FINDING NEGATIVE KEYWORDS

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this custom report by logging into your account and opening the following link http://onbe.co/VTRqQh .

The first level of drill down is the match type. Since the objective is to find search queries that may not be relevant to the website, we will drill down into either broad or phrase match.

Drilling down from the keyword into the matched search query dimension re-veals the culprits of the high bounce rate. If, for example, a particular advertiser sells the Hickory brand of cabinet hardware, yet matches on queries specifically for “tools handles” or “axe handles,” adding them as negative keywords can save money and improve profitability.

Figure 3.17 – Custom report to assist finding negative keywords

Content Experiments is a tool provided by Google Analytics to create A/B testing. It allows marketers to test their campaign landing pages (and other parts of the website) in order to improve customer experience and increase revenues.

3.3. CONTENT EXPERIMENTS: OPTIMIZING PPC CAMPAIGNS WITH GOOGLE ANALYTICS

 Figure 3.18 – Creating a new experiment

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While Content Experiments is not technically an integration, its history and func-tionality make it a good candidate for inclusion in this discussion. It started as a feature inside AdWords, to provide advertisers with a tool to improve campaign performance. In April 2008 it became a stand-alone product, growing in impor-tance. In June 2012 the product was integrated into Google Analytics as one of its features, an important development because it allows website owners to use existing Analytics codes and goals for their tests.

As of the writing of this eBook, only A/B Testing is available (no Multivariate Test-ing.) This type of test is the most common, especially for landing page optimiza-tion. It consists of creating alternative versions of a specific page and showing each version to a certain percentage of visitors. For example, if you create four different variations of a landing page, 20% of visitors will see each version (four variations plus the original.) Cookies are used to maintain a consistent user ex-perience—a visitor who sees one version of the landing page will see it again and again when visiting the website as long as the cookies are not deleted.

Below is a step-by-step guide on how to use Content Experiments to create A/B tests.CREATING A/B TESTS USING GOOGLE ANALYTICS

Create A New ExperimentIn order to create a new experiment, navigate to the “Content reports” tab on Google Analytics and click on the “Experiments” link on the sidebar (direct link: http://onbe.co/MvKKFB.) You will see a page that shows all your existing experiments. Above this table you will find the “Create experiment” button. Once you click on it, you will reach the following page:

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In this page you can add the URLs of the original page and its variations. You will see thumbnails of each variant page, which helps you make sure the URLs are correct.

Click “Next.”

Set Experiment Options

In the page above you will be offered a drop-down menu of all your profile goals, which can be used as a goal for your tests. If there is not an existing goal for the con-version you want to measure in this specific test, you will have to create a new goal to use in the test.

In addition to that, you can set a percentage to limit the number of visits included in the test. If you are testing radical alternatives to an important page, it is recommend-ed you don’t try them on 100% of your traffic because a highly unsuccessful variant can damage your conversions. You can also add notes to your experiment.

Click “Next.”

Add and Check Experiment Code

Figure 3.19 – Setting the experiment options

Figure 3.20 – Adding and checking the experiment code

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You will need to implement one code in order to use this tool. In the page above you can choose either to get the code to implement immediately or to send it to your webmaster.

Click “Next,” and your pages will be verified. If the GA code is not found in all pages and the redirection code is not found in the original page, you will see the following error message:

Figure 3.21 – Validating the experiment code

Figure 3.22 – Reviewing the experiment before it starts

Note that you will be able to skip validation if you want; just click on “skip validation and continue.” However, it is recommended that you check the code to understand why you are seeing an error and then try validating again.

Review Experiment

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Figure 3.23 – Navigating through a running test

This page is a review of your article, showing all the decisions you took along the pro-cess. You can either “Save and run later” or “Run experiment now.”

Experiment Results

The screenshot above shows how you can navigate through a running test. You have the following capabilities:

• Advanced Segments is an extremely valuable feature that enables you to understand better how each variation performs for each segment of visitors on your website.• Conversions / Page Metrics changes the metrics on the test results table • Stop Experiment• Re-validate• Disable Variation• Explorer gives you the option to check the test results using alternative metrics such as site usage (metrics like Bounce Rate, Time Page and others,) and all goal tabs active on the profile

Reviewing All Experiments

Any time you want to review your experiments, just visit http://onbe.co/IXznAO

If testing is not part of your company’s process already, it might be worth starting with the guidelines below. I provide a few tips on how to choose the best page to be tested and what should be tested in the first place.

3.4. TESTING TIPS AND GUIDELINES

With hundreds, or even thousands, of pages, how should a marketer decide where to start? The most obvious place to start is the landing page or pages. However, once

HOW DO YOU CHOOSE A PAGE TO TEST?

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the landing pages are optimized, what comes next? Which other pages, if tested, will bring the biggest increase in revenues? The following three metrics are highly useful when choosing pages to test:

A. Page Value. This metric (also called $ index) tells you the contribution of each page to the overall revenue of the website. It is calculated using the ecommerce and goal values of the website based on the following formula: Page Value = (Transaction Revenue + Total Goal Value) / Unique Pageviews for the page. You will find this metric on the All Pages report (direct link: http://onbe.co/OTP1o4), in the last column of the table.B. Exit rate. This is the percentage of visitors abandoning the website from a specific page. A high exit rate shows that a page is not engaging enough and can be driving your customers away—unless the page is the “thank you” page, where it is not a bad sign to have a high exit rate. (If the objective is to test landing pages, the more appropriate metric is the bounce rate, the percentage of visitors leaving the website without interacting with it. A high bounce rate shows that a landing page is performing poorly and should be optimized.)C. Average time on page. This metric can be an indication that visitors are having difficulty completing a task. For example, if you notice a very high time on page for one of the steps of a registration process, it might be a hint that users are having difficulties understanding what they are supposed to do. (This might not be a concern for content websites, where you want your visitors to spend more time reading content.)

These are common measures of success and failure of a page for most websites. It is important to consider all three metrics (and others that might be specific to your website) and prioritize pages to test. Once you know which pages are the most im-portant, check which ones can be tested quickly; once you start testing and optimiz-ing the website it is easier to implement additional tests.

When choosing a page to test, it is also important to take into consideration what elements affect the time it will take in order to receive significant results (significance is automatically calculated by Google). Basically, the variables that will affect the dura-tion of your test are:

• Number of combinations tested: As the number of combinations increases, the duration of the test increases.• Volume of traffic on the page: As the traffic of the tested page increases, the duration of the test decreases.• Conversion rate of page: The higher the conversion rates of the page, the quicker the test.

HOW LONG WILL THE TESTS LAST?

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• Expected improvement (% by which you expect to improve the website): As the difference between the pages tested increases, the duration of the test decreases.

The elements that should be tested depend on the type of website, on the targeted public, on the budget available, and on the page being tested. Here are three things to test that can bring high benefits with low costs.

A. Calls to action are often hidden, for instance appearing below the fold, or badly designed (too small, faint color, or ambiguous, e.g., having a button that does not look like a button.) Simply improving the call to action and making it prominent on the page can sometimes boost conversion rates drastically. B. Look and feel. Pages must be visually comfortable;, i.e., people should feel at home in your website. One way to do this is to test different images. Sometimes using a baby picture works, sometimes a couple at the beach, sometimes even using something creepy, like an insect—depends what people are looking for on your website and what you are selling.C. Copywriting. For visitors to consider buying a product or signing up for a newsletter, there must be a good unique selling proposition. And people should see it as they land on the website. Make your unique selling proposition simple and prominent. Depending on the page you are testing, you should adapt the length of your text: for landing pages, short text usually works better; for product pages, longer, telling visitors all the reasons why your product is the best in the market.

In addition, a great way to get ideas is to learn what your competitors do. This can be done using DoubleClick Ad Planner (http://onbe.co/MlGtRb), a place to get ideas that will be tailored to the audience segments you are trying to target. Since traffic is always limited, it is important to run tests that have a high chance of making a dif-ference.

The tool can be used to understand your audience tastes and which kind of websites they like. The DoubleClick Ad Planner provides important insights into how to design your website. Here is an article showing how to do it http://onbe.co/OYl8zB

WHAT SHOULD BE TESTED?

As we have seen in this chapter, integrating AdWords takes a few steps, but Google has streamlined the process for its advertisers. In addition, the unlinking and management of linked accounts is very easy, which is an important security feature. We also discussed discrepancies when it comes to Analytics and AdWords information and provided a Top 10 list of issues that might cause it.

SUMMARY

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As we have seen in this chapter, integrating AdWords takes a few steps, but Google has streamlined the process for its advertisers. In addition, the unlinking and management of linked accounts is very easy, which is an important security feature. We also discussed discrepancies when it comes to Analytics and AdWords information and provided a Top 10 list of issues that might cause it. Once the integration is completed, PPC optimizers and analysts will have a pow-erful tool to optimize AdWords campaigns. Basically, the advantage of GA over other tools when it comes to analyzing campaign performance is that it enables us to link AdWords data to overall website usage in a synergetic way. Below are some tips from this chapter:

A. Adjust the ad scheduling settings in your AdWords campaigns to drive more traffic during hours where traffic is more valuable. B. Create unique profiles on GA for PPC campaigns; this will be helpful when comparing campaigns between themselves, with not other traffic sources.C. If you advertise on Bing, be sure to tag the links properly so that you can compare its performance to AdWords.D. Use custom reports wisely in order to understand in a more effective way how campaigns perform.E. Use Google Analytics to find negative keywords that should be removed from AdWords campaigns.F. Always be testing!

Avinash Kaushik, Digital Marketing Evangelist at Google, wrote an in-depth post about using Google Analytics custom reports for paid search campaigns analysis. Check the post for more tips http://onbe.co/SprkEP .

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ADDITIONAL RESOURCES

In this section I provide additional resources for those readers who are looking to learn more about Google Analytics. I have used these resources for years to learn about the tool and I warmly recommend you bookmark or buy them too.

OFFICIAL HELP WEBSITES

• Google Analytics help center http://onbe.co/SfNgTq - is without a shadow of doubt, the most helpful resource when it comes to understanding what each report means.• Google Analytics code website http://onbe.co/SfNR7M - provides a detailed and encompassing description of all the coding necessary to track website behavior. • Google Analytics Youtube channel http://onbe.co/TxqXcP - offers interesting videos, short and long.

BOOKS

• Online Behavior eBooks - http://onbe.co/P209MG • Web Analytics 2.0 by Avinash Kaushik - http://onbe.co/Sbp0Cu • Google Analytics by Justin Cutroni - http://onbe.co/P6Q1kJ • Advanced Web Metrics with Google Analytics by Brian Clifton http://onbe.co/P6PFe5 • Performance Marketing with Google Analytics by Justin Cutroni, Caleb Whitmore and Sebastian Tonkin - http://onbe.co/TxrLya • Regular Expression for Google Analytics by Robbin Steif http://onbe.co/TxssHP (link to PDF)