Advanced Digital Analytics Strategies and Tactics - Chris...

ADVANCED DIGITAL ANALYTICSSTRATEGIES AND TACTICS

Chris Sietsema | Digital Marketing & Analytics Consultant, Teach to Fish Digital

MASTERCLASS WORKBOOK

© Conversion Sciences LLC. Used with permission.

TABLE OF CONTENTS

Introduction

Setting a Foundation for Analytics Success

How to Create a Google Analytics Account

Property Level Elements

About Google Analytics Views

Defining Conversion Goals

Exercise: Tying Conversion Goals to the Customer Journey

Secondary Actions

Campaign Tracking

Exercise: Creating a Campaign Tracking Protocol

Filters and Segments

Regular Expression Tutorial/Tips

Integrations

Google Analytics Integrations

Analytics Configuration with Tag Manager

The Container Tag

Tag Manager Hierarchy

Variables, Triggers & Tags

Exercise: Documenting Custom Event Tags

Cross-Domain Tracking

Ecommerce Tracking

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TABLE OF CONTENTS

Reporting

Marketing Reports are Icebergs

The One-to-Three Rule

Aligning Reports to Audiences

Exercise: Objective-Oriented Reporting Layouts

Reports Customization in Google Analytics

Automated vs. Annual Reporting

Google Data Studio

Exercise: Create a Google Data Studio Report from Scratch

Reporting Cadence

Additional Reporting & Automation Tools

Marketing Attribution

Mining for Insights, The Analytics Cycle & Kaizen Method

Uncovering Deep Insights

Exercise: Questions to Inform Your Analysis Process

Analytics Documentation

Kaizen: Planning for Continuous Improvement

Additional Testing, Heat Mapping & Attribution Tools

Helpful Reading & Resources

About Chris Sietsema

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INTRODUCTION

easurement is a critical element for any successful and long-sustaining marketing program. With an endless Msupply of data from an abundant array of sources, the analyst's challenge is no longer how to gather data, but

how best to tame it. When property planned and executed, a strategic analytics process can help us arrive at

smarter business decisions with velocity.

Within the contents of this workbook, you will find both instruction and exercises to help you establish a solid

foundation for measurement success, take advantage of the latest tools and functionality to improve accuracy and

efficiency with your analytics process, and uncover important insights to move your organization forward.

The workbook is divided into four sections:

Section A: Setting a Foundation for Analytics Success

Here we will walk through the proper method of creating a fresh Google Analytics account while establishing

Properties and Views as necessary. This section will also include notes and instruction related to Conversion Goal

definitions, campaign tracking processes, filter and segment creation, and more. We will wrap up this section with a

full analytics audit.

Section B: Analytics Configuration with Tag Manager

Now that we have our Google Analytics account, property and view(s) established, we can continue to customize

our approach to measurement with the help of Google Tag Manager (GTM). This helpful platform not only provides

an efficient means for placing tracking and other marketing-related tags on a website or app quickly, it also improves

the process for custom event tagging, cross-domain tracking, and ecommerce measurement configuration. All of

these processes will be explored and explained in this section.


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INTRODUCTION

Section C: Reporting

While the analyst's time is spent primarily in gathering, transforming and interpreting data, the report gives her the

opportunity to share the fruits of that labor with others. Reporting is not an easy task as it involves a delicate balance

between providing what is truly important and necessary while eliminating the superfluous and distracting. This

section will provide a pros/cons discussion of automated vs. manually constructed reports. In addition, this section

covers Google Data Studio, attribution modeling and several helpful automation and visualization tools.

Section D: Mining for Insights, The Analytics Cycle and Kaizen Method

The analyst's work is truly never done. As data is gathered, manipulated, translated and presented, new data

becomes available concurrently. All the while we must strive to make subtle and noteworthy improvements along

the way to consistently improve business outcomes. This section will include samples and exercises to hone your

insights gathering skills and the cyclical pattern the analyst must follow. To assist you in your process, we will also

cover several analytics documents that are common staples in many data-driven organizations. Finally, this section

wraps up with a review of tools for testing, heat mapping and attribution.


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SETTING A FOUNDATION FOR ANALYTICS SUCCESS

Workshop Phase A

Note: Throughout this workbook, we will make reference to tools found within the Google Marketing Platform. Step-

by-step instruction and exercises are geared toward users of this toolset. However, several measurement concepts

can be applied to other analytics tools as well.

The Google Analytics configuration consists of Accounts, Properties and Views. Think of this structure similar to a

tree. At the base level or trunk, we have our Account. From the Account, we can have one more Properties, which

act as branches. Stemming from each branch, we can have one or more Views – the twigs and leaves of our

configuration.


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HOW TO CREATE A GOOGLE ANALYTICS ACCOUNT

For new users:

1. Create a Google Account if you have not done so previously

2. Visit analytics.google.com

3. Sign up for a new account

4. Identify the account name, website/app name, URL, industry and time zone



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For existing users:

1. Navigate to the admin page of any existing account

2. Select the “+Create Account” button (marked with the below)blue arrow

3. Identify the account name, website/app name, URL, industry and time zone



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At the Account level, users can:

Ÿ Alter general settings including the account name and country of business

Ÿ Define and set account filters to remove and include different types of traffic (more on this functionality later)

Ÿ Define users and set permissions. There are four separate permission levels:



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PROPERTY LEVEL ELEMENTS

The Analytics property is most closely associated with the Universal Analytics (UA) tracking code. Please see below.

Each property has a unique UA code and tracking script that can be placed on a website or app to gather analytics

data and populate reports in Google Analytics.



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In addition to accessing the unique tracking code associated with each Google Analytics Property, users can also

update settings at the Property level including:

Ÿ Referral Exclusions – This is a specific list of website domains that should not be included in website traffic

reports. This functionality is typically used to omit traffic from the company intranet, subdomains and other

internal assets that could compromise data accuracy. Referral exclusions also come into play when setting up

cross-domain tracking.

Ÿ Integrations – Several integrations can be established with Google Analytics. The two most common

integrations involve Google Ads and Google Search Console. The integration between Google Analytics and

these two tools allow for data to populate in specific reports related to paid search and search engine

optimization performance.

Ÿ Audiences – If the Google Analytics tracking code is properly placed on a website or app, it allows the user to

build an audience defined by certain characteristics (e.g. All visitors or visitors to certain pages or visitors from

a unique referral source). These audiences can be used for segments and for advertising purposes via Google

Ads.



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Ÿ Custom Dimensions & Metrics – Standard metrics like pageviews, average visit duration and bounce rate can

be accompanied by custom dimensions and metrics relevant to your organization. While not used by all

account users, Custom Dimensions and Metrics help to paint a clearer picture of visitor behavior and

interaction with a website or app. Here is a sampling of custom dimensions and metrics:



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ABOUT GOOGLE ANALYTICS VIEWS

As noted previously, the View is the last element in the Google Analytics configuration chain. While you may have

access to Properties with several Views or Properties with only a singular View, it is most often recommended that

each Property have three distinct Views:

1. Raw – The raw view provides an unfiltered look at all the data collected in the Property.

2. Filtered – Analytics filters (discussed thoroughly below) can be defined and applied to omit certain traffic

from appearing in a View. The Filtered View is the most often used.

3. Test – The Test view is utilized on certain occasions to check the accuracy of filters and conversion goals

before they are enacted in the Filtered View.

Other operations available within the Google Analytics View element include:

Ÿ Conversion Goals – Define and update important conversion goals at the View level.

Ÿ Apply Filters – While filters are typically defined at the Account level, they can be applied at the View level



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Ÿ Content Groupings – In some cases it is helpful to categorize content into groups (e.g. product pages vs. blog

pages vs. landing pages, etc.). There is a limit on Content Groupings per View (maximum 5), and each

Grouping is assigned an Index number. Please note that the process to define Content Groupings requires

additional code placement. See below.



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Ÿ Channel Groupings – As a default setting, Google Analytics defines certain channels like Direct, Organic

Search, Paid Search, Referral, etc. However, users can alter these definitions to match Channel names and

labels with naming conventions for marketing programs and platforms employed by the organization.

Please see below for a sample.

Ÿ Ecommerce Settings – Within each View, users can turn Ecommerce tracking On or Off. There are additional

steps to take to enable accurate Ecommerce measurement, which will be covered later in this workbook.

Taking the steps necessary to properly configure your Account(s), Properties and Views helps to establish a

trustworthy baseline from which to measure and derive key insights for your organization.



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DEFINING CONVERSION GOALS

Google Analytics enables users to create Conversion Goals, which measure important behaviors and metrics that are

directly tied to business objectives. While the context for each goal likely varies, there are four types of Conversion

Goals available:

The most commonly used Conversion Goal Types are destinations and events. Please see the graphic below to

clearly draw a distinction between these two goal types. Destination goals simply require that a visitor access a

specific page, typically a “thank you” or confirmation page. Event-oriented goals track click behavior, and these

custom events can typically require additional tracking code on buttons, links, embedded videos, etc.



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DEFINING CONVERSION GOALS

Defining Conversion Goals is a crucial step in the analytics process as it helps the analyst tie metrics to quantified

business objectives for the organization. If there is no goal, questions may arise about the purpose of our efforts

both to market and to measure. While we typically associate “Goals” as a final, culminating action in a long pathway

taken by each of our customers, it is also important to consider the key actions our audiences take along the

customer journey.



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EXERCISE: TYING CONVERSION GOALS TO THE CUSTOMER JOURNEY

Complete the Customer Journey table below by defining key actions in your own customer's journey (or your

client's journey) as well as key interactions along the way that may be categorized as Conversion Goals.

For example: Prospective customers passively gathering information about recreational vehicles may choose to subscribe for email updates

and product announcements from a local RV dealer. This subscription action would be tracked as a Destination Conversion Goal when the

prospect reaches the “thank you for subscribing” page.


Journey Phase

CATALYST

Definition Customer Action Goal / Metric Destination or Event

The point at which a potential customer becomes aware of your brand/solution

PASSIVE EXPLORATION

The audience begins to gather information but is not yet actively shopping

ACTIVE EXPLORATION The prospect seeks to answer key questions related to your offering

DECIDING Options are narrowed between your brand and competitors

EXPERIENCING Current customers interact with your product/service and offer feedback


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“Your scientists were so preoccupied with whether they could that they didn't stop to think if they should.”

- Dr. Ian Malcolm (played by Mr. Jeff Golfblum)

Google Analytics allows for up to 20 Conversion Goals (four sets of five conversion goals) in every view. Just

because you can measure that many goals, doesn't necessarily mean you should. Our efforts to measure too many

things limits our ability to measure the most important items very well.

If you are just defining Conversion Goals for the first time, consider limiting the total range to three to five. If you

already have identified more than 12 conversion goals, consider consolidating this quantity to a manageable

amount.

Creating Conversion Goals

The following demonstrates how to create a new Conversion Goal for both a Destination-oriented goal and an Event

goal.




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Destination Goal Walkthrough

1. Within the Goals option under View within the Admin portion of Google Analytics, select +New Goal.

2. Goal Setup: Google Analytics offers several Template options for Conversion Goals, but here we will select

“Custom” and continue.

3. Goal Description: Provide a name for your new Conversion Goal using a consistent naming convention with

your other goals. Choose the “Destination” option under Goal Type and continue.




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4. Goal Details: It is important at this step to identify the “thank you” or confirmation page on which the goal

should be marked, but do not use the full URL. You only need the Page Path. For example:

a. Full URL: www.site1.com/orderconfirmation.html

b. Page Path: orderconfirmation.html

5. Goal Detail Options: Within the Goal Details area, users also

have the option of adding a Goal Value and defining a funnel.

In the example below, we have assigned a value of $25 and

listed the pages preceding the orderconfirmation.html page in

our sample funnel.

Note: The Value option should only be used when there is a consistent value for your

conversion goal. Do not use this for Ecommerce transactions that have varying values

and prices associated with them. Also, the funnel can be helpful, but you might consider avoiding it if there are several potential paths to

your final destination page.




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In addition to Conversion Goals which are the primary actions we want our audience to take and reflect our core

business objectives, it is also necessary to identify other key actions that are indicative of interest and engagement

from our audiences and convey meaning at a lesser scale.

Sample secondary actions for your website or app may include:

Ÿ Asset downloads

Ÿ Video views

Ÿ Email address clicks

Ÿ “Add to cart” buttons

Ÿ Clicks to share on social media

Ÿ Clicks to view directions, etc.

These items are typically measured as custom events, which can be configured with static code or via Google Tag

Manager (to be covered later in this workbook). Events typically have values for Event Category, Event Action and

Event Label. Event reports can be found in the Behavior section of Google Analytics standard reports.


SECONDARY ACTIONS


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Suggest documenting items and actions you would like to track and/or explore. This list

can also come in handy when extracting insights. To give you a head start in this process,

the table below provides a layout you can work with to define secondary actions and

corresponding event values. Two samples are provided in the boxes.highlighted


SECONDARY ACTIONS

Secondary Action

Download Product Info

Product Detail Page Content Download Product Info PDF

Clicks to YouTube Channel

Omnipresent Social Click YouTube

Location Event Category Event Action Event Label


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As discussed previously Google Analytics enables users to define custom Channels or categories of traffic defined by

its original source. Similarly, users can add detail to their marketing campaigns by appending their URLs with tracking

code. These codes are typically referred to as UTM (Urchin Tracking Module) parameters. Separate parameters are

available for source, medium, campaign and other values we will explore below.

Please note that UTM tracking codes should only be used when driving traffic from external sources. It is not

necessary to tag clicks from your own website or app that lead to other areas of your website or app with campaign

tracking code.

There are typically two helpful ways to append your campaign URLs with specific tracking code. The first method

involves Google's Campaign URL Builder found at . This https://ga-dev-tools.appspot.com/campaign-url-builder/

helpful tool allows advertisers to build out tracking code-appended URLs one at a time.


CAMPAIGN TRACKING


https://ga-dev-tools.appspot.com/campaign-url-builder/

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The orange box below marks the inputs including the landing page URL, source, medium and campaign values. The

blue arrow points to the URL that has been updated with UTM parameters and values. While this tool is helpful, it can

be time-consuming for advertisers who have several URLs to update with tracking code.


CAMPAIGN TRACKING


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As noted previously, Google allows for several UTM parameters. A brief explanation of each follows:

1. UTM Source – Source provides a label for the venue utilized to drive traffic.

2. UTM Medium – The Medium parameter/field categorizes referral sources into meaningful segments (cpc,

display, email, social, sponsorship, etc.)

3. UTM Campaign – While Source and Medium values are straightforward and often consistent, the Campaign

parameter allows the advertiser some license to define each marketing program according to the message,

the object of promotion, dates, etc. There is no universally accepted standard for UTM Campaign naming

conventions, but each organization should absolutely define its own convention for UTM Campaign values.

4. UTM Content – The Content parameter is a field typically used to distinguish one ad from another in an ad

set. Advertisers can use the UTM Content parameter to detail advertising specs (300x250 vs. 728x90),

creative (blue vs. green), call to action (Learn More vs. Act Now), and so on. Suggest implementing the UTM

Content parameter only when it is important to measure ad performance in this manner.

5. UTM Term – The Term field is reserved for keywords. This parameter is populated by Google Ads and other

keyword search referral sources.

After Google's Campaign URL Builder tool, the second option for adding tracking code to your URLs is by creating

your own campaign tracking sheet in Google Sheets or Microsoft Excel.


CAMPAIGN TRACKING


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Open up a web browser and navigate to Google Sheets ( . Copy the format https://docs.google.com/spreadsheets/)

detailed below by placing (Landing Page, Source, Medium, Campaign, and Final URL) in Row 1, Columns static values

A-E.


EXERCISE: CREATING A CAMPAIGN TRACKING PROTOCOL

A B C D E

Landing Page Source Medium Campaign Final URL1

2

3

4

Next, place sample values for Landing Page, Source, Medium and Campaign in the cells below the static values. Align

your landing pages with their Source/Medium/Campaign values in each row.

A B C D E

Landing Page Source Medium Campaign Final URL

www.site1.com/abc.html google cpc abc

www.site1.com/def.html mailchimp email def

www.site1.com/ghi.html outbrain display ghi

1

2

3

4


https://docs.google.com/spreadsheets/

http://www.site1.com/abc.html

http://www.site1.com/def.html

http://www.site1.com/ghi.html

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Once you have a sample values in place on a few rows, follow the steps below to create a tracking code-appended

URL for each.

1. Navigate to Cell E2 in your Google Sheet – . marked on previous page

2. Place the following formula in Cell E2 and hit Enter.

=CONCATENATE(A2,“?utm_source=”,B2,“&utm_medium=”,C2,“&utm_campaign=”,D2)

3. At this point, you should have an appended URL in Cell E2. Click on this cell and drag the lower right

corner of the cell down to populate Column E for all of the landing pages and Source/Medium/Campaign

combinations on your sheet.

This process is preferred to using the Google Campaign URL Builder because:

A. It allows for quick preparation of multiple campaign tracking codes, avoiding a one-at-a-time approach to

UTM parameter configuration.

B. The Google Sheet can be shared amongst and utilized by multiple members of the team.

C. The landing page and UTM parameters can act as a historical record of campaign tracking activity.

D. Extra cells can easily be added for UTM Content, UTM Term, notes, descriptions, authors, etc.




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In addition to creating a Campaign Tracking Sheet for your organization or each of your clients, recommend also

preparing a protocol for all those who plan to utilize the Sheet to follow. This resource document should provide

explicit instructions and sample definitions (in Glossary format if

possible like the sample on the right) to avoid any confusion when

creating tracking codes for marketing and advertising campaigns. The

more that your team can remain consistent in preparation of these

values, the easier it will be to maintain clean and clear data in Google

Analytics campaign reports.

This process and documentation should be considered a constantly

evolving entity that improves over time. However, strict adherence to

source and medium definitions is paramount and necessary to avoid

muddy data.




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Our ability to extract meaning from data often requires that data be limited to only the pertinent details. Both filters

and segments are helpful features in this regard. While Filters completely remove certain results from our data set,

Segments can be employed to take a closer look at our results through a specific lens. To explain this more clearly,

take a look at the images below.

This figure on the left represents all the data at our disposal in Google Analytics.

This figure represents the same data set with a Filter applied. All of the yellow bits have been

removed.

When filters are applied, they clear away data from our view, leaving only the information we want

to see. For example, filters can be applied to remove visitor traffic arriving from within our office or

headquarters.

Finally, this figure represents the same data set with a Segment applied.

Segments act like lenses and allow us to focus on specifically defined data more clearly (e.g. show

me only visitors accessing our website/app from Nashville).


PREPARING FILTERS & SEGMENTS


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With respect to how Google treats both Filters and Segments, please read below.

Filters

Ÿ Defined at the Account level within the Google Analytics Admin, Filters can also be applied at the View Level.

They are specific to the Account and View and are applied for all users of the Account.

Ÿ Sample Filters:

o Exclude Traffic from IP

o Exclude Specific Site Traffic

o Hostname in URL (Hostname Prepend)

o Lowercase Filters: Hostname / Search Term / UTM Values

o Exclude Query String

Ÿ Example: Exclude Traffic from an IP address to avoid

counting traffic from our organization amongst

audience behavior.




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Segments

Ÿ Unlike Filters, Segments are defined and applied at the user level. If you create a Segment, it will not

automatically be available for your colleagues to use as well.

Ÿ Segments can, however, by copied and shared. When sharing a segment, Google Analytics will provide you

with a URL that, when opened, will load the segment you created into the account of whoever opens the link.

o Please note the “Build Audience” option here as well, which will enable users to group website/app

visitors into audiences for remarketing purposes via Google Ads.




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Ÿ Sample Segments:

o Hostname Equals or Contains

o Page Equals or Contains

o Landing Page Equals or Contains

o Segment by Source / Channel / Campaign

o Sequences

o Event Equals or Contains

o Timing (e.g. Session Duration > 60 Seconds)

Ÿ Example: Segment traffic to those that accessed the “Request Info” page and completed the form to reach the

resulting “Thank You” page. With this segment in place, users can see how visitors who completed this action

accessed the website, what other pages they visited, what other actions/behaviors they demonstrated, etc.




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As several Filters and countless Segments can be constructed to maintain data hygiene and answer important

questions more clearly, a standard naming convention for these features is highly recommended. A mix of Filters and

Segments with a mish-mash of labels can create hurdles in the analysis process.

When defining Filters and Segments, users have a variety of operators from which to choose. Sample operators

include “equals,” “contains,” “begins with,” “ends with,” etc. In addition to these operators users can employ Regular

Expressions to define Filters and Segments. Regular Expressions are often utilized in Google Tag Manager as well.

The following table provides definitions and examples of popular regular expressions.


REGULAR EXPRESSION TUTORIAL/TIPS


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Google Analytics can also be integrated with other tools to include meaningful data in reports relevant to Google

Ads and search engine optimization performance among others.

The process to sync data between Google Analytics and Google Ads follows.

1. First ensure that access has been granted to your Google account (Gmail address or

other) for both the Google Ads account and Google Analytics.

2. Navigate to the Google Ads Linking section within the admin panel at the Property

level. See right.

3. Finally, select the Google Ads account you would like to integrate with Google

Analytics, and choose the View(s) that should receive data.


GOOGLE ANALYTICS INTEGRATIONS


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Google Search Console can also be integrated with Google Analytics within minutes.

1. Be sure to gain proper access to both the Google Analytics and Search Console accounts to be synced.

2. Navigate to the “All Products” option within the admin panel at the Property level. Select “Link Search

Console.”

3. Choose the “Add” option on the following screen. Then select the site in Google Search Console you would

like to integrate.

Several other venues in the Google family can be integrated with Google Analytics including Google AdSense,

Google Ad Exchange, BigQuery and more. There is also a Postback option that allows Google Analytics users to send

important conversion information back to advertising networks other than Google Ads.


GOOGLE ANALYTICS INTEGRATIONS


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To wrap up Section A, please see the table below for a Google Analytics audit template and checklist you can use to

assess your current configuration.


ANALYTICS AUDIT CHECKLIST

Audit Component Status Notes

Account / Property / View ConfigurationTracking Code Placement(Rely on )Google Tag Assistant

Conversion Goals Configuration

Filters – Available in Account

Session Settings Status(Admin » Property » Tracking Info » Session Settings)

Cross-Domain Tracking Status

Referral Exclusion Status

Account Integrations


https://get.google.com/tagassistant/

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Audit Component Status Notes

Audience Definitions Utilization

Custom Dimensions Utilization (if applicable)

Bot Filtering

Query Parameter Exclusion (if applicable)

Site Search Tracking Status

Content Grouping Utilization

Channel Grouping Definitions

Ecommerce Settings & Configuration (if applicable)


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Features Usage:

Campaign Tracking Naming Conventions

Custom Event Tracking

Custom Reports

Saved Reports

Advanced Segments

Custom Alerts


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ANALYTICS CONFIGURATION WITH TAG MANAGER

Workshop Phase B

Google Tag Manager (GTM) is a free utility that enables analysts and marketers to create, manage and govern the

various tags (or code snippets) placed on their website and apps. These tags are usually placed to aid in the process

of analytics (i.e. the Google Analytics pageview tag) or advertising (the Google Ads remarketing tag).

Prior to the tag management platforms, analysts, marketers and information technology professionals would have to

work together to place tags manually. This was usually an arduous and error-prone process that was extremely time

consuming. Individual tags were placed, tested and often fixed after the fact. Tag management solutions like Google

Tag Manager now allow us to place one singular tag, called a “container” tag. Then from the Google Tag Manager

interface, we can define how all our tags are triggered throughout the website or app.

Then: Multiple TagsPlaced Individually

Now: Container TagHandles Firing Process for All Tags


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The advantages to utilizing a tag management solution include:

1. Massive time-savings as IT/technical staff is no longer relied upon after the container tag is placed.

2. Efficiency as multiple tags are housed in the container and triggered based explicit instructions defined

within Google Tag Manager.

3. Cleanliness and governance. All tags can be controlled, monitored and policed within a single GTM

account.


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The container tag, which must be placed on all pages throughout a website or app, is actually made up of two code

snippets. One snippet is placed in the <head> of the page, and the other should be placed after the opening <body>

within page script.

Once you create a new account in Google Tag Manager, you can find your container tag by clicking on the

hyperlinked GTM ID. See the below.orange arrow

THE CONTAINER TAG


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Sample instructions are provided in the graphic below, but Wordpress users can also place GTM container script

easily with plugins such as:

Ÿ DuracellTomis Google Tag Manager for Wordpress

Ÿ Metronet Tag Manager

Ÿ Header Footer Code Manager

Ÿ Simple Google Tag Manager Plugin

THE CONTAINER TAG


https://wordpress.org/plugins/duracelltomi-google-tag-manager/

https://wordpress.org/plugins/metronet-tag-manager/

https://wordpress.org/plugins/header-footer-code-manager/

https://wordpress.org/plugins/simple-google-tag-manager/

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Much like Google Analytics' Account/Property/View configuration, Google Tag Manager has its own systematic

hierarchy.

Ÿ Account – Each organization or client should have its own GTM account. Users can house multiple containers

within a single account.

Ÿ Container – The container equates to a single website or app. Multiple tags can be placed within a container.

Ÿ Tag – Tags or individual script elements for tracking and advertising purposes are placed within each

container. There is no limit to the number of tags that can be placed within a single container.

TAG MANAGER HIERARCHY


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The Google Tag Manager container is comprised of three primary elements: variables, triggers and tags. To explain

these three unique elements consider the musical metaphor below.

Ÿ Variables are like musical notes. Just as dozens of notes can be found in a single melody, an equal amount of

variables come in to play when monitoring audience behavior in a single session.

Ÿ Triggers are our sheet music. They provide a set of instructions for when certain notes are used in a song or

hymn. In GTM, triggers provide instruction on what tags to fire based on a combination of variables that come

into play.

Ÿ Tags are like the keys on the piano or the strings on the guitar. They are pressed or plucked to play musical

notes according to the instructions provided in the sheet music. Similarly, tags are only fired based on

predefined triggers.

VARIABLES, TRIGGERS & TAGS


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Here is a sample tag with elements marked by color: , , .Variable Trigger Tag

Fire the with .Google Ads conversion tag when the visitor views the page confirmation.aspx in the URL

Translation:

This is a Google Ads Conversion Tag

It uses a trigger typePage View

The tag will fire when is a value contained in the confirmation.aspx Page URL

About GTM Variables

Variables are populated with values as the audience accesses pages and interacts with content on your website or

app. Variables can be split into two categories, Page View variables and visitor behavior variables. Page View

variables are populated as soon as the page loads. Visitor Behavior variables are assigned values following specific

user actions.



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For example, in the sample page below, the following variables are populated on Page View.

Ÿ Page URL: https://kansascity.digitalsummit.com/

Ÿ Page Path: /

Ÿ Page Hostname: kansascity.digitalsummit.com

When the “View Agenda” button is clicked, the following Visitor Behavior variables are populated:

Ÿ Click Text: View Agenda

Ÿ Click Class: btn-primary

Ÿ Click URL: https://kansascity.digitalsummit.com/2019/agenda/



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As a default, only a few variables are available to GTM users straight away. To enable new variables, access the

Variables section in GTM and click the “Configure” button. New or custom variables can also be created in the “User-

Defined Variables” area. Sample User-Defined Variables that should be considered include Google Analytics Settings,

Google Analytics Tracking ID (UA-XXXXXX), Page Title, Page H1, etc.

Triggers in Google Tag Manager

As noted previously, triggers provide instructions for tags to fire based on specified criteria. There are six categories

of triggers in GTM:



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1. Page View Triggers: Three separate triggers are available to fire at unique stages of the page load process.

2. Click Triggers: These include link clicks and clicks on any element.

3. User Engagement: These triggers include form submissions, scroll depth and video interactions.

4. Custom Events: Used to attach tags to events that fire as part of website functionality (e.g. a common

custom event is a transaction event on ecommerce websites).

5. History Change: Similar to page view triggers, history change triggers are helpful for single page websites

and apps in which a Page URL does not change.

6. Timer Triggers: Fire tags based on visit duration in increments (i.e. 30 seconds, 60 seconds, 90 seconds,

etc.).

A sample trigger configuration for the “View Agenda” button example provided earlier would look like so:



50


Tag Types & Configuration

Nearly 100 different tag types are currently available in Google Tag Manager, but the most common tags revolve

around Google Analytics, Google Ads and Custom HTML/Image Tags.

The following provides a sample of a Page View tag that will fire the Google Analytics tracking code on every page of

the website or app.



51


The following depicts the configuration of a Google Analytics custom event tag. This particular configuration is

designed to fire a custom event and feed Event Category, Event Action, and Event Label values when a PDF

document is clicked/downloaded. Please note the use of the {{Click URL}} variable in the Event Label, which allows

the analyst to determine what specific PDF document was clicked to download.



52


The accompanying trigger for this tag would look like so:

Several advertisers who rely on Google Ads must place conversion tracking on confirmation pages. A sample

configuration for a Google Ads Conversion Tracking tag follows:



53


The trigger for the tag above would be configured like so:

For Google Ads Remarketing there are two ways to place tags. One option includes relying on the Google Ads

Remarketing tag type, which allows users to identify a conversion ID and label.

The second option allows users to copy and paste the tag script from Google Ads and place it with the Custom

HTML tag type. Both options are captured below.



54


In addition to several options for Google Analytics and Google Ads tag

types, GTM allows for the placement of dozens of other tags from

advertising, testing and measurement platforms and venues. The following

example shows a tag for the popular heat mapping software HotJar. Note

that the only element required to configure this tag is the HotJar account

ID marked with an arrow.



55


Preview, Test & Publish

Prior to submitting new Tags and Triggers, suggest utilizing the GTM Preview function that allows users to verify that

their tag configurations are firing as designed.

Selecting the “Preview” button will display a preview pane at the bottom of any open window of a site with the GTM

container tag placed and published.

The “Submit” button can be selected once updates to tags have been tested and finalized. Recommend adding

descriptions for each newly published version. This will help identify what changes went live at what time in case

changes need to be reversed or modified in the future.


In addition to tag configuration, testing and publishing, it is strongly recommended that all tags be documented

separately. As the process and collective configuration of tags becomes more intricate with each tag that is

implemented, documentation is a vital step in the GTM process.


56


Use the table below to identify and document several Google Analytics custom event tags that you will likely place

via Google Tag Manager. A similar structure can be replicated in Google Sheets for ongoing documentation and

records keeping. The row below has been provided as a sample.highlighted

EXERCISE: DOCUMENTING CUSTOM EVENT TAGS

Tag Name Description Tag Type Trigger TypeEvent Category/Action/Label

GA Event – PDF Download

All download actions by site visitors

Universal Analytics – Event

PDF / Download / Asset Download {{Click URL}}

Link Click Click URL (contains) .pdf

Testing

Trigger Detail Tag Status


57


In many cases, visitors to your website or app may need to visit other properties you own (subdomains, microsites,

shopping carts, member portals, etc.). When a visitor moves from one website to another, data is captured for both

website as two different visits. The process to view a single visitor's experience as one continuous session across

websites is referred to as cross-domain tracking.

Historically, cross-domain tracking with Google Analytics has involved placement of two or more separate tracking

codes – one tracking code for the primary site and another tracking code for each additional site. An historical

configuration for three separate sites that needed to be measured together follows:

Primary Website Tracking Code

ga('create', 'UA-0000000-1', 'auto', {'allowLinker': true});

ga('require', 'linker');

ga('linker:autoLink', [' , ']);site2.com site3.com

Secondary Website Tracking Code




Tertiary Website Tracking Code




CROSS-DOMAIN TRACKING


58


Such a configuration would pull data into one Google Analytics Property for all three sites, but given the complexity

of the code and the potential to make mistakes when placing the code, this particular process is not always

recommended.

Thanks to Google Tag Manager, configuration of cross-domain tracking is much less perilous and comparably easy.

The following shows steps necessary to configure cross-domain tracking in GTM. For this step-by-step walkthrough,

we will assume that three separate sites need to be tracked in a singular Google Analytics property.

1. Place the GTM container tag on all three websites (site1.com, site2.com and site3.com)

2. Create a user-defined variable called “Cross-Domain Tracking” with the following configuration:

a. Constant variable type

b. Value: site1.com, site2.com, site3.com



59


3. Create a Google Analytics Settings variable called “Google Analytics Settings” with the following

configuration:

a. Variable Type: Google Analytics Settings

b. Place your tracking ID (UA)

c. Cookie Domain: auto

d. Within the “More Settings” area:

i.Fields to Set » Field Name: allowLinker / Field Value: true

ii. Cross-Domain Tracking » Select your {{Cross-Domain Tracking}} variable



60


4. Create a Universal Analytics tag called “GA – Page View” with the following configuration:

a. Tag Type: Google Analytics – Universal Analytics

b. Track Type: Page View

c. Google Analytics Settings: Select your {{Google Analytics Settings}} variable

d. Trigger: All Pages



61


5. The final step involves updating your Google Analytics Property settings.

a. Within the admin panel, navigate to the Tracking Info item under the Property settings.

b. Select Referral Exclusion List

c. Add all three website domains as separate referral exclusions.



62


Soon after completing this process (24 hours), you should no longer see any of the sites in Source/Medium and

Referrals reports. Meanwhile, your site behavior reports should be populated with activity from all three sites. A few

other considerations for this process:

Ÿ Verify the GTM container tag has been placed on all of the domains you wish to bring together in analytics

reports.

Ÿ The same process applies for subdomains. Subdomains are viewed by Google Analytics as distinct and

separate websites.

Ÿ Consider implementing a “Hostname Prepend” filter that will prepend each page path in Site Content reports

(e.g. /aboutus.html, /services.html, /contactus.html, etc.) with its hostname (e.g. site1.com/aboutus.html,

site2.com/services.html, site3.com/contactus.html). A sample Hostname Include filter is depicted below.



63


Similar to cross-domain tracking, Google Tag Manager provides a much more efficient method for enabling

Ecommerce tracking in Google Analytics. The three primary requirements for Ecommerce measurement are detailed

below. Each requirement involves a different entity: Google Analytics settings, website/shopping cart settings and

Google Tag Manager configuration.

1. Enable Ecommerce in Google Analytics

a. Navigate to Ecommerce Settings within the Google Analytics admin panel at the View level.

b. Switch the “Enable Ecommerce” setting to “ON.”

ECOMMERCE TRACKING


64


2. Verify Contents of the dataLayer. The dataLayer is an object on a page that contains information relevant to

the Ecommerce transaction. This information is extracted from the order confirmation page and delivered

to Google Analytics to populate Ecommerce reports. Please note that the dataLayer is most often

completed with necessary values when using an off-the-shelf shopping cart tool (e.g. Shopify,

WooCommerce, Bigcommerce, 3Dcart, etc.), but you may need to work with a developer to ensure that all

the required transaction data and product data values listed below are present on the confirmation page

that is presented to the audience when an order is successfully placed. The information that should be

found in the dataLayer is and below.referenced here

a. Transaction Data

i. Transaction ID

ii. Transaction Total

iii. Optional: Shipping, Tax, Store Affiliation

b. Product Data

i. Product Name

ii. Product SKU

iii. Price

iv. Quantity

v. Optional: Product Category

ECOMMERCE TRACKING


https://support.google.com/tagmanager/answer/6107169?hl=en

65


3. Configure a tag called “GA – Transaction” in Google Tag Manager with the following settings.

a. Tag Type: Google Analytics – Universal Analytics

b. Track Type: Transaction

c. Google Analytics Settings: Select your {{Google Analytics Settings}} variable

d. Trigger Type: Page View

i. Fire on Page View » Order complete or confirmation page

e. Alternative Trigger Type: Custom Event

i. Alternatively: Fire on Custom Event » Transaction event

ECOMMERCE TRACKING


66


The trigger for this example transaction tag would be configured like so:

ECOMMERCE TRACKING


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REPORTING

Workshop Phase C

Many of us operate under the assumption that the larger the report, the more value it provides. At one point in your

career, you have likely come into contact with (or perhaps even built and delivered) a massive report that included

every possible data point, consisted of multiple pages, provided ridiculous quantities of charts/graphs/wayward

visuals, and hopefully passed some supposed weight test.

The truth is good things come in small packages, especially if you are the executive, chief marketing officer or other

head-honcho type who is tasked with reading marketing dashboards and digesting all that marvelous data.

Every marketing metrics report you create must answer three critical

questions:

1. What happened?

2. Why did it happen?

3. What are we going to do next?

That is all. Keep the target set on the ultimate goal(s) while avoiding toiling

in minutiae.


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REPORTING

If you can pull it off, try to keep your reports to a single page – just enough to convey meaning without wasting your

audience's precious time. This “single page” reporting format enables the analyst to analyze as opposed to

aggregating, manipulating and formatting data sets. It also results in meetings and discussions about performance

results that are more productive. As less time and effort are required to cover every detail of an involved and

convoluted reporting presentation, more time can be dedicated to determining meaningful action items based on

your insights.

If the “single page” mantra sounds like a dream, consider this: just because your reports may only consist of a

solitary, albeit riveting, page, does not mean they require any less effort to prepare.


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REPORTING

Take a moment to visualize a massive hunk of ice floating in the

ocean. That enormous frozen block represents the all data we have

available to us. Unfortunately, presenting an overabundance data

often results in very little understanding.

Only the top-level stuff should be visible to your reporting audience.

Yes, there is a colossal heap of information below the surface, and as

an analyst, you will come to rely upon it when gathering provocative

insights. However, strive to maintain discipline by limiting the charts

and graphs to the most crucial, goal-oriented metrics and campaign-

related performance results. The written portion of your report is

where you can dive deep to explore the intricacies of your marketing

program. This most crucial written section typically delivers in three areas:

1. Interpret the data without repeating what the charts and graphs clearly convey.

2. Demonstrate why particular findings are relevant to the organization. Indicate importance and

consequence. Tell your audience why they should care about certain metrics and specific results.

3. Illustrate a plan of action. While it is not mandatory that your insights clearly dictate next steps for the

organization, they should spark a constructive dialogue amongst you and your reporting audience (i.e. your

client, your team/colleagues, your organization's decision makers).

MARKETING REPORTS ARE ICEBERGS


70

REPORTING

For every hour you spend gathering and manipulating data for reporting presentations, spend three hours

analyzing it.

Marketing analytics reporting is not merely an exercise of encountering and regurgitating the news. You must also

spend the time to examine and diagnose problems. You must seek out crucial communications mistakes and

recommend a means for correcting them. You must uncover the unsightly, lagging metrics and suggest methods to

improve them.

Like the high school custodian in “The Breakfast Club,” you must be the eyes and ears of this institution. To do that

job right requires time. Some of the effort you expend may be worthy of including in your report insights. Other

findings may not make the cut. No matter what, respect the process.

THE ONE-TO-THREE RULE


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REPORTING

No two reporting audiences are alike, and a critical element to reporting success is the ability to gauge how much

(or how little) data to present to an audience. There seems to be an inverse relationship between one's position in

the organization hierarchy and her available bandwidth to read and interpret data.

For this reason, it is imperative to cater your reporting layouts and details to the audience. A one-size-fits-all

approach is likely reckless. The following table outlines they types of reports you can plan to prepare based on your

audience. Please note that anomalies are present in every group. Some at the C-level may not be able to control

their ravenous appetite for the finer points of your marketing analytics data set.

ALIGNING REPORTS TO AUDIENCES


72

REPORTING

Creating an objective-oriented reporting layout for senior leadership requires some simple steps but also takes

practice. In this exercise, we will walk through the process of crafting a high-level report that reflects our most

critical business goals.

Step 1: Take a blank sheet of paper.

Step 2: Divide the paper into three or four sections – one section for each of

your organization's primary business goals.

Step 3: On one side of each section of paper, jot down a quantified business

goal.

Step 4: Flip each section of paper over and identify a metric for the

corresponding business objective on the opposite side. This metric should be

utilized to indicate success or failure for the objective.

Step 5: Place each section, metric-side up on a table or other flat surface.

Slide them around so that the highest priority metric/objective section is

positioned at the top. The metric/objective combination with the next highest

priority should be positioned just below and so on.

The result should look like a rudimentary outline for a high-level report you can construct for an executive audience.

EXERCISE: OBJECTIVE-ORIENTED REPORTING LAYOUTS


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REPORTING

Within the Google Analytics interface, users have the ability to customize reports to answer commonly asked

questions and provide reporting audiences with information requested on a regular basis. There are four types of

customization options within Google Analytics.

1. Dashboards – This functionality enables the analyst to prepare charts,

graphs, tables and geographic data illustrations to review and share with her

team. Dashboards have been replaced somewhat with the emergence of

Google Data Studio (to be covered later in this workbook).

2. Custom Reports – The analyst creates these reports from scratch to provide

data not readily available in any standard report in Google Analytics.

a. Custom reports are unique to the user, but can be copied and shared.

It is also possible to create a Custom Report in one View and have it available for viewing in a

separate Account/Property/View.

b. The following Custom Report configuration shows activity by hour of the day. Please make note of

the usage of Dimensions (the element that is measured) and Metrics (the unit of measurement).

c. Filters can also be applied to Custom Reports to only include traffic and behaviors from a subset of

the audience or referral sources.

REPORTS CUSTOMIZATION IN GOOGLE ANALYTICS


74

REPORTING



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REPORTING

3. Saved Reports – Think of Saved Reports as your Google Analytics bookmarks. If there is a specific standard

report that you or your reporting audience reviews regularly that also requires some manipulation, consider

creating a Saved Report

a. These are standard reports that can be modified with Advanced Segments, secondary dimensions,

report-specific filters and date ranges to customize how the data is presented.

b. Similar to Custom Reports, Saved Reports are specific to the user. However, they cannot be shared.

c. The following sample saved report is marked with a number of color-coded features that can be

manipulated to configure your report prior to saving.

i. Saved Report Name

ii. Advanced Segment

iii. Secondary Dimension

iv. Report-Specific Filter

v. The “Save” button to mark this

configuration as a Saved Report



76

REPORTING

4. Custom Alerts – These act as automated messages from Google Analytics that deliver updates to the

analyst or anyone on our team. Thresholds can be defined to deliver alerts when positive or negative results are

witnessed. These alerts save the analyst time from constantly checking on the status of Google Analytics to ensure

all is well and/or the status quo is in tact. Sample custom alerts that you can develop include:

a. Daily Traffic is below X

b. Weekly Transactions are above Y

c. Daily Bounce Rate has eclipsed Z%



77

REPORTING

With respect to the analytics reports that exist outside of the Google Analytics platform, analysts typically develop

their own reports that fall within one of two categories: automated reports and manual reports.

A. Automated Reports are configured one time and automatically populate reporting elements (charts, graphs,

tables, etc.) from a source like Google Analytics.

B. Manual Reports are defined by layouts that are manually constructed by the analyst at a regular reporting

cadence using a tool like Microsoft Excel or Numbers for Mac.

The unique Pros and Cons to automated vs. manual approaches to report construction are detailed below.

AUTOMATED VS. MANUAL REPORTING


78

REPORTING

One of the automated reporting tools that is growing in popularity among analysts and their audiences alike thanks

to the recent updates and support it has received from Google is Data Studio. Similar to other automated reporting

software, Google Data Studio operates with the help of data connectors that extract and load data to be constructed

and manipulated by the user. While there are limits to Data Studio's capabilities with respect to chart types, data

sources and interactive elements, it provides a sound solution to automated reporting, which will likely improve over

time.

Reports and Data Sources

Each Data Studio account is primarily comprised of Reports and Data Sources. You can add new reports and data

sources by selecting the blue “+” symbol in the lower right of the Data Studio main page.

GOOGLE DATA STUDIO


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REPORTING

There are three primary methods to creating a new Report in Data Studio:

1. Start from scratch with a blank reporting page.

2. Kick start your process by altering an existing layout in Data Studio's templates or reporting gallery.

3. Modify an existing report previously created by you or shared by a colleague.

Data Sources (also known as Connectors) are split into two groups.

1. Google Data Sources: Including Google Analytics, Google Ads, Search Console, YouTube Analytics and other

sources operated by Google.

GOOGLE DATA STUDIO


https://datastudio.google.com/gallery

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REPORTING

2. Third-Party Connectors: Sources created and managed by Data Studio partners that can bring in data from

sources like Bing Ads, Adroll, Amazon, CallRail, email marketing service providers, display advertising

networks, etc. In many cases there is a fee associated with connecting data from a third-party source that is

determined by the number of dimensions and metrics utilized and the frequency with which the data is

called, refreshed and populated in your reports. Each data source is managed by a Data Studio partner.

Popular partner organizations headquartered domestically and internationally include , SuperMetrics

Power My Analytics Report Dash Funnel.io , , and more.

GOOGLE DATA STUDIO


https://supermetrics.com/

https://www.powermyanalytics.com/

https://www.powermyanalytics.com/

https://www.reportdash.com/

https://funnel.io/marketing-reporting-google-data-studio

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REPORTING

Dimensions & Metrics

Prior to constructing your own Data Studio dashboard, it is important to understand the distinction between

Dimensions and Metrics, two elements that are used quite commonly in the report construction process.

GOOGLE DATA STUDIO


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REPORTING

Construct your own Data Studio report replicating the layout below. Add a Google Analytics data source. Include the

following elements in your Data Studio report:

Ÿ Add a logo (Image or Text)

Ÿ Add a date range widget

Ÿ Add Charts

o Line : Traffic Over Time

§ Dimension: Date

§ Metric: Sessions

o Bar : Channel Performance

§ Dimension: Default Channel Grouping

§ Metric: Sessions

o Table : Content Performance

§ Dimension: Page

§ Metrics: Pageviews & Unique Pageviews

EXERCISE: CREATE A GOOGLE DATA STUDIO REPORT FROM SCRATCH


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REPORTING

Ÿ o Donut : Device Preference

§ Dimension: Device Category

§ Metric: Sessions

o Column : New vs. Returning Traffic

§ Dimension: User Type

§ Metric: Sessions

Ÿ Add Greek text for Insights (placeholder)



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REPORTING

Once you have created your report in “Edit” mode, switch to “View.” You will notice several controls in the top right

of the “View” layout. Please see below.

These controls from left to right are as follows:

Ÿ (Down Arrow) : Download the report as a PDF

Ÿ (Clock) : Schedule the report for delivery to your audience (or yourself) at regular intervals

Ÿ (Link Icon) : Get a report link for distribution purposes

Ÿ (Hyphenated Box) : View your report layout in full screen

Ÿ (Circular Arrow) : Refresh the report data

Ÿ (Pages Overlay) : Copy this report

Ÿ (+Person Icon) : Share this report with others – list their email addresses and send from Google Data Studio

Ÿ (Question Mark) : Review “help” options



85

REPORTING

Any marketer or analyst has likely been asked the question, “how often should we prepare reports?” There is no

standard frequency. Some reports should be prepared and discussed weekly. Other reports deserve a monthly or

quarterly review.

The frequency with which you prepare and deliver reports, whether automated or manual, and accompanying

insights should never be based on an arbitrary time limit. Plan to create new reports with refreshed data at an

interval in which you and your team have the ability to make decisions and fulfill strategic directives.

Q: How often should reports be prepared?

A: As often as insights can be acted upon and data-driven recommendations can be implemented.

REPORTING CADENCE


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REPORTING

Google Data Studio provides a free and reliable option for reporting and automation. Several other options are

available for analysts as well. Consider the following for your marketing analytics stack. Nearly all of the tools listed

below have an associated fee for usage.

Reminder: None of the tools below will replace the effort required to analyze data and provide meaningful and

relevant insights or associated action items.

Ÿ Aggregation & Visualization: These tools collect data and allow users to present it in meaningful ways to their reporting

audiences.

o Tableau

o PowerBI

o Datorama

o Domo

o Looker

o Qlik

Ÿ ETL (Extract, Transform, Load): An ETL is commonly used by organizations and agencies that require data from multiple

sources. An ETL gathers data and aligns it according to a schema defined by the analyst before pushing it to a

visualization platform.

o Sisense

o Funnel.io

o Alight Analytics

o Rivery

o Improvado

ADDITIONAL REPORTING & AUTOMATION TOOLS


https://www.tableau.com/

https://powerbi.microsoft.com/en-us/

https://datorama.com/

https://www.domo.com/

https://looker.com/

https://www.qlik.com/us/products/qlikview

https://www.sisense.com/

https://funnel.io/

https://alightanalytics.com/

https://rivery.io/

https://improvado.io/

87

REPORTING

An emerging topic discussed by analysts and decision makers within data-driven organizations revolves around the

concept of attribution. Simply stated, attribution is the systematic process of quantifying contribution.

The audiences for your marketing programs will likely receive your message, interact with your content and

experience your brand in many different ways throughout the customer journey. When a prospect transitions to

customer status, how can we determine what channel, advertising program, content marketing asset or other

element played the key role in conversion? The employment and usage of attribution models seek to answer that

question.

To explain the conundrum marketing attribution poses, consider the following metaphor.

MARKETING ATTRIBUTION


88

REPORTING

Late in the 2018 baseball season, the Los Angeles Dodgers

played the Milwaukee Brewers in a playoff game. The winner

would advance to the World Series. The Dodgers won the

game thanks to the efforts of several pitchers on their team

to keep the Brewers from advancing on the base paths and

scoring runs. The following depicts the sequence in which

various Dodgers pitchers took the mound. The number in

parentheses represents innings pitched (e.g. 4.2 equates to

four and two-thirds innings).



89

REPORTING

Given this sequence, which pitcher deserves the most credit for the Dodgers' win?

Ÿ Should it be Walker Buehler who pitched the most innings and started the game? (First-Click Attribution)

Ÿ Should we credit the win to Clayton Kershaw who successfully recorded the final out to close the game?

(Last-Click Attribution)

Ÿ Or should we give each pitcher equal credit for recording outs and helping their team win? (Linear Attribution)

Similar questions are pondered by analysts who must create models to assign ample credit to referral sources that

deliver messages and encourage customer response during paths to purchase like the one pictured below:

This is the analyst's quandary. Given the number of possible paths to a conversion that our prospective customers

can take, attribution modeling is both an inexact and difficult science to master.



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REPORTING

The following provides a brief overview of popular attribution models that marketers, media buyers and analysts

utilize to assign due credit.

Ÿ First Click: The first customer interaction gets the credit.

o Translation: “From a little spark may burst a flame.”

o Issue: Difficult to prove

o Issue: Relies on the assumption that remarketing efforts are inconsequential

o Issue: Sales cycles can be too long

Ÿ Last Click: The last customer interaction in a sequence gets the credit.

o Translation: “Standing on the shoulders of giants.”

o Issue: Relies on assumption that awareness and attraction efforts are

inconsequential

o Issue: Favors bottom-funnel tactics and channels

Ÿ Linear: Assigning equal credit to all channels and referral sources.

o Translation: “Everybody gets a trophy.”

o Issue: Gives equal credit where certain stages of the customer journey are likely

more important than others.



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REPORTING

Ÿ Time Decay: Giving incremental amounts of credit to channels and sources positioned at

the end of the customer journey.

o Translation: “Short-term memory illustrated.”

o Issue: Similar to Last-Click, this model does not give proper credit to tactics that

play an introductory role

Ÿ “U” or Position-Based: Assign most of the credit to channels and sources that either

introduce the brand to the prospect or finalize the transaction.

o Translation: “Ice breakers and deal closers.”

o Issue: Gives heavy credit to first and last-click tactics, and discredits everything in

between



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REPORTING

For Every Organization, A Unique Model

No two organizations or analytics programs are exactly alike. Each situation requires a unique approach to

measurement and quantifying contribution.

The initial task of the analyst when it comes to attribution modeling does not involve experimentation with different

models, results analysis for each model, or fine-tuning of attribution settings to produce a reliable and tenable

solution. Rather, the first step is to truly understand the customer journey. Every attribution model should be a

reflection of the path your prospects take, and added weight should be assigned to critical stages in that journey.

When it comes to the tools at our disposal, Google Analytics does provide some attribution modeling features.

However, the data collected is primarily based on pageview activity and not user activity. A handful of sophisticated

tools utilize a process referred to as “user stitching” which involves maintaining records for individual users and tying

those records back to original visits and behaviors subsequently after a key conversion goal is tracked. As the graphic

below illustrates, Google Analytics currently offers a more shallow view of marketing attribution. Other tools like

Google Analytics 360, MixPanel and Heap play at the

deeper end of the data pool. They can provide a more

realistic and accurate view of user actions, content

engagement/events and the referral sources that play

an active role throughout the customer journey.



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MINING FOR INSIGHTS, THE ANALYTICS CYCLE & KAIZEN METHOD

Workshop Phase D

The most difficult and time-consuming task for any analyst revolves around the process of insights extraction. Often

times the practice can feel less like studying and scrutinizing a data table and more like reading tea leaves. Well-

constructed analytics recommendations do not mystically materialize in the written portion of any report; they are

meticulously cultivated.

The ability to uncover key findings that move data-driven organizations forward does not necessarily stem from

knowing what buttons to push, when to apply an advanced segment or how to explain the difference between

bounce and exit rates. In this phase of the analyst's role, art can outrank mathematics. Feel is prioritized over

precision. The juiciest discoveries come from understanding various facets of the business well enough to sense the

elements most ripe for growth and improvement.

To be a great analyst, you don't have to have all the right answers.

The best analysts simply ask the right questions.


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Unless you are painting by number, it can be difficult to apply a systematic approach to a work product with artistic

qualities. Regardless, we will attempt to do so anyway.

For the sake of the following exercise, let's operate under the assumption that there are three types of desired

outcomes for any business or organization. Whether your focus is on lead generation, ecommerce, not-for-profit

endeavors or driving foot traffic to a brick-and-mortar store, chances are your objectives can be segmented into

three areas:

A. Increase Volume

B. Increase Yield

C. Eliminate Waste

Under each of these three categories of preferred results, questions emerge. For instance…

Increase Volume

Ÿ What channels/sources are driving the most awareness now? Can I gear my marketing program to make them even

more productive?

Ÿ What channels/sources are producing the most conversions? Should I reallocate budget to give them greater support?

Ÿ Are there certain types of content that have more gravity among search and website/app users? Where does my

audience naturally go? Can I build out more content similar to what is most effective?

UNCOVERING DEEP INSIGHTS


95


Increase Yield

Ÿ What elements of the conversion process can be modified to increase conversion rate?

Ÿ Are there certain content assets or features that naturally correlate to conversion behavior? Do they deserve a more

prominent call to action? Can they “sell harder?”

Ÿ Do certain behaviors or content engagements consistently precede conversion actions? Should I purposefully

introduce or involve them to aid the conversion process for my audience?

Eliminate Waste

Ÿ Which content productions fail to deliver? How can they be improved or revamped?

Ÿ Are there certain points in the conversion process that are susceptible to abandonment? What modifications can be

made to hold the audience's interest?

Ÿ Do visitors from one device category behave differently than another? What adjustments can be made so the

experience is appealing to customers on any screen size or device?

UNCOVERING DEEP INSIGHTS


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Pose at least five questions specific to your organization's audience. Each question you identify should align with in

one of the nine question types above.

Examples:

How does video play a role in the conversion process?

How does conversion rate differ between mobile and desktop users?

Which of the top 50 most popular blog posts demonstrate the highest bounce rates?

1. ________________________________________________________________________________________

2. ________________________________________________________________________________________

3. ________________________________________________________________________________________

4. ________________________________________________________________________________________

5. ________________________________________________________________________________________

EXERCISE: QUESTIONS TO INFORM YOUR ANALYSIS PROCESS


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A critical component to a successful analytics program is the ability to document implementation plans,

configurations and processes. Thorough documentation helps the analyst and the analytics team to stay on task and

organized. The following table provides a list of documents you may consider for your program. Suggest preparing

these documents in a shared format like Google Docs or Sheets.

ANALYTICS DOCUMENTATION


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Kaizen is the Japanese word for “improvement.” Many organizations throughout the world have adopted Kaizen

principles in which all members of the company contribute to the continuous improvement of every facet of

operations from how board meetings are run, to assembly line maneuvers, and even how the coffee is made.

Kaizen is achieved with tiny little upgrades and enhancements from one day to the next. This concept is portrayed

brilliantly in the 1993 film Groundhog Day, starring Bill Murray. The plot of Groundhog Day and the lessons it teaches

has actually been included in the syllabus of several philosophy classes taught at the university level.

As the story goes, a disgruntled weatherman is assigned to a story in Punxsutawney, Pennsylvania, home to the

famous groundhog that is celebrated every February 2nd. After falling asleep that night, he wakes up to find himself

in the same day. Confused and bewildered, the main character struggles through the repeat day only to wake up

again on February 2nd. As he finds himself in repetitive limbo, the story goes from hysterical to comical to dark to

poignant.

At one point during the course of the movie, the main

character starts to make small observations. The next

day he acts on those observations and picks up new

information about his surroundings along the way.

After continuing to make minor improvements on a

daily basis, the story culminates in what could only be

described as the best day possible.

KAIZEN: PLANNING FOR CONTINUOUS IMPROVEMENT

© Sony Pictures Home Entertainment


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Similarly, the analyst's job is to make small observations and steward the organization with course corrections little-

by-little. With time, effort and stream of continuous improvement, we too can hope to achieve what can only be

described as the best business outcome possible.

To strive toward this kind of result incorporate the following into your measurement process:

Ÿ Improvements Little-by-Little – With every report or request for results metrics, the analyst should strive to deliver

something valuable and new that will move the organization forward (even inches at a time).

Ÿ Planned Approach to Improvement – In addition to the list of documentation outputs discussed previously, suggest

developing a written plan that lists items that you aim to emphasize with your measurement program in the near

future. This could include fine-tuning campaign tracking, rolling out an A/B split test, experimenting with attribution

models, etc.

Ÿ Structured Elimination of Points of Failure – An undeniable element to achieving success is enduring mistakes and

mishaps. To fail is simply to eliminate an ineffective route on your quest to triumph. Each fruitless attempt narrows

your options and increases your chances of progress. As you attempt to solve problems as an analyst, work to

identify all the potential methods to achieve an improved result and systematically attempt them one-by-one until

you find a solution.

Ÿ Working Backwards – When attempting to improve the results of a marketing program, many attempt to mimic the

actions of a prospective customer from start to finish. It is actually more efficient and effective to trace the

audience's steps in reverse order to identify potential issues at the point of conversion and work backwards to a

prospect's initial interactions with your marketing message.



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The Analytics Cycle & Kaizen

The spirit of Kaizen is also present in the analytics process. No matter what reporting cadence you adopt, be sure to

rely on a cyclical pattern of analytics operations. Each step in the process illustrated on the right feeds the next.

Over time, the natural repetition of the Analytics Cycle improves business results and sharpens skills. Seek out

methods to develop each of the four stages of the cycle as your program matures and achieves a state of continuous

improvement.

Ÿ Gather / Aggregate

Ÿ Analyze

Ÿ Insight

Ÿ Enact



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The Google Marketing Platform provides some extremely helpful utilities. As your program matures, recommend

utilizing additional tools to answer important questions and strive toward continuous improvement.

Ÿ Testing

o Optimizely

o (VWO)Visual Website Optimizer

o AB Tasty

Ÿ Heat Mapping

o HotJar

o CrazyEgg

Ÿ Attribution Tools

o Bizible

o Rockerbox

o Wizaly

ADDITIONAL TESTING, HEAT MAPPING AND ATTRIBUTION TOOLS


https://www.optimizely.com/

https://vwo.com/

https://www.abtasty.com/

https://www.hotjar.com/

https://www.crazyegg.com/

https://www.bizible.com/

https://www.rockerbox.com/

https://www.wizaly.com/

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Ÿ Occams Razor by Avinash Kaushik

Ÿ - Google Tag Manager blog and tutorialsSimo Ahava

Ÿ - GTM eBooks and coursesAnalytics Mania

Ÿ - Data storytelling blogLea Pica

Ÿ - Intentional reporting and data visualizationStephanie Evergreen

Ÿ - Analytics tutorial YouTube ChannelMeasureSchool

HELPFUL READING & RESOURCES


https://www.kaushik.net/avinash/

https://www.simoahava.com/

https://www.analyticsmania.com/

http://leapica.com/blog/

http://stephanieevergreen.com/blog/

https://www.youtube.com/channel/UClgihdkPzNDtuoQy4xDw5mA

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ABOUT CHRIS SIETSEMA

Chris Sietsema has nearly 20 years of experience in the interactive marketing

space. Chris excels at educating his clients and colleagues about online marketing

disciplines and how best to employ them. He runs Teach to Fish Digital, a

consultancy committed to helping its clients make sense of marketing data. He’s

held leadership positions at two great agencies in Phoenix and a Fortune 500

company.

Questions & Follow Up

[email protected]

480.570.1636


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