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Project 3: Digital Marketing Analytics


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Introduction

Discuss Data Analytics

While you are about to continue attending meetings and participating in discussions, Ying sends out the following email to you and the team.

INBOX: 1 New Message

Subject: Digital Marketing Follow-Up for CompanyOne
From:     Ying Bao, Associate Consultant, MCS
To:          You and Team

Hi team,

Great work on the first two topic discussions at last week’s meetings. I can tell we’re heading in the right direction. To keep the momentum going, I’d like you to complete two more group discussions at our meetings scheduled for this week. You can review the discussion topics below. It is required that you respond to both of these topics as well.

As you discuss these topics, be sure you understand the following concepts related to data analytics:

· working with data

· tracking and collecting data

· key elements of web analytics

· segmentation in web analytics

Regards,

Ying


Discussion Topics 1 and

2

Topic 1

There are three key elements to be considered in any web analytics study like the kind MCS is doing for CompanyOne. These elements are (1) behavior, (2) outcomes, and (3) user experience. A powerful technique to gauge user behavior is segmentation. Explain the concept of segmentation in relation to web analytics. Some common ways of segmenting your site visitors are by new users, returning users, paid search traffic, nonpaid search traffic, direct traffic, referral source, landing page, browser, and mobile traffic, among hundreds of possible options. Recommend any five ways of segmentation to CompanyOne, including some that are not listed here, and discuss the relative merits of each.

Topic 2

In Google Analytics (GA), a funnel is a navigation path (series of web pages) that you expect CompanyOne’s online customers to follow in order to achieve the business’s goals for their website. A funnel is made up of a goal page (or pages) and one or more funnel pages (also known as the funnel steps). CompanyOne needs to choose either the Goal Flow Report or the Funnel Visualization Report in Google Analytics. They come to you for advice. What questions will you ask in order to arrive at your recommendation for CompanyOne? Explain your reasoning.

Support your arguments under each topic with at least one source from the course readings, and three reliable non-scholarly sources derived from your own research.

Learning Topic

Data Analytics

Picture the scene: you’ve opened up a new fashion retail outlet in the trendiest shopping center in town. You have spent a small fortune on advertising and branding. You have gone to great lengths to ensure that you’re stocking all of the prestigious brands. Come opening day, your store is inundated with visitors and potential customers.

And yet, you are hardly making any sales. Could it be because you have one cashier for every hundred customers? Or possibly it is the fact that the smell of your freshly painted walls chases customers away before they complete a purchase? While it can be difficult to isolate and track the factors affecting your revenue in this fictional store, if you move it online, you will have a wealth of resources available to assist you with tracking, analyzing, and optimizing your performance.

To a marketer, the internet offers more than just new avenues of creativity. By its very nature, it allows you to track each click to your site and through your site. It takes the guesswork out of pinpointing the successful elements of a campaign, and can show you very quickly what’s not working. It all comes down to knowing where to look, what to look for, and what to do with the information you find.

Key Data Analytics Terms

A/B test

Also known as a split test, it involves testing two versions of the same page or site to see which performs better.

Click path

The journey a user takes through a website.

Conversion

Completing an action or actions that the website wants the user to take. Usually a conversion results in revenue for the brand in some way. Conversions include signing up to a newsletter or purchasing a product.

Conversion funnel

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A defined path that visitors should take to reach the final objective.

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Cookie

A text file sent by a server to a web browser and then sent back unchanged by the browser each time it accesses that server. Cookies are used for authenticating, tracking, and maintaining specific information about users, such as site preferences or the contents of their electronic shopping carts.

Count

Raw figures captured for data analysis.

Event

A step a visitor takes in the conversion process.

Goal

The defined action that visitors should perform on a website, or the purpose of the website.

Heat map

A data visualization tool that shows levels of activity on a web page in different colors.

JavaScript

A popular scripting language. Also used in web analytics for page tagging.

Key performance indicator (KPI)

A metric that shows whether an objective is being achieved.

Log file

A text file created on the server each time a click takes place, capturing all activity on the website.

Metric

A defined unit of measurement.

Multivariate test

Testing combinations of versions of the website to see which combination performs better.

Objective

A desired outcome of a digital marketing campaign.

Page tag

A piece of JavaScript code embedded on a web page and executed by the browser.

Ratio

An interpretation of data captured, usually one metric divided by another.

Referrer

The URL that originally generated the request for the current page.

Segmentation

Filtering visitors into distinct groups based on characteristics in order to analyze visits.

Target

A specific numerical benchmark.

Visitor

An individual visiting a website that is not a search engine spider or a script.

Resources

Data Analytics: Goals, Tools, Benefits, and Challenges (/content/scor/uncurated/mba/2218-mba640/learning-resourcelist/data- analytics-goalstoolsbenefitsandchallenges.html?ou=610159)

Licenses and Attributions

Chapter 18: Data Analytics

(https: /www.redandyellow.co.za/content/uploads/woocommerce_uploads/2017/10/ema rketing_textbook_download.pdf) from eMarketing: The Essential Guide to Marketing in a Digital World, 5th Edition by Rob Stokes and the Minds of Quirk is available under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported

(https: /creativecommons.org/licenses/by-nc-sa/3.0/) license. © 2008, 2009, 2010,

2011, 2013 Quirk Education Pty (Ltd). UMGC has modified this work and it is available under the original license.

© 2021 University of Maryland Global Campus

All links to external sites were verified at the time of publication. UMGC is not responsible for the validity or integrity of information located at external sites.

10/20/21, 12:26 PM Data Analytics

https://leocontent.umgc.edu/content/scor/uncurated/mba/2218-mba640/learning-topic-list/data-analytics.html?ou=610159 1/3

Learning Topic

Data Analytics
Picture the scene: you’ve opened up a new fashion retail outlet in the trendiest shopping

center in town. You have spent a small fortune on advertising and branding. You have

gone to great lengths to ensure that you’re stocking all of the prestigious brands. Come

opening day, your store is inundated with visitors and potential customers.

And yet, you are hardly making any sales. Could it be because you have one cashier for

every hundred customers? Or possibly it is the fact that the smell of your freshly painted

walls chases customers away before they complete a purchase? While it can be difficult to

isolate and track the factors affecting your revenue in this fictional store, if you move it

online, you will have a wealth of resources available to assist you with tracking, analyzing,

and optimizing your performance.

To a marketer, the internet offers more than just new avenues of creativity. By its very

nature, it allows you to track each click to your site and through your site. It takes the

guesswork out of pinpointing the successful elements of a campaign, and can show you

very quickly what’s not working. It all comes down to knowing where to look, what to

look for, and what to do with the information you find.

Key Data Analytics Terms

A/B test
Also known as a split test, it involves testing two versions of the same page or site to see
which performs better.

Click path
The journey a user takes through a website.

Conversion
Completing an action or actions that the website wants the user to take. Usually a
conversion results in revenue for the brand in some way. Conversions include signing up
to a newsletter or purchasing a product.

Conversion funnel
A defined path that visitors should take to reach the final objective.

C ki

10/20/21, 12:26 PM Data Analytics

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Cookie
A text file sent by a server to a web browser and then sent back unchanged by the
browser each time it accesses that server. Cookies are used for authenticating, tracking,
and maintaining specific information about users, such as site preferences or the
contents of their electronic shopping carts.

Count
Raw figures captured for data analysis.

Event
A step a visitor takes in the conversion process.

Goal
The defined action that visitors should perform on a website, or the purpose of the
website.

Heat map
A data visualization tool that shows levels of activity on a web page in different colors.

JavaScript
A popular scripting language. Also used in web analytics for page tagging.

Key performance indicator (KPI)
A metric that shows whether an objective is being achieved.

Log file
A text file created on the server each time a click takes place, capturing all activity on
the website.

Metric
A defined unit of measurement.

Multivariate test
Testing combinations of versions of the website to see which combination performs
better.

Objective
A desired outcome of a digital marketing campaign.

Page tag
A piece of JavaScript code embedded on a web page and executed by the browser.

Ratio
An interpretation of data captured, usually one metric divided by another.

Referrer
The URL that originally generated the request for the current page.

Segmentation
Filtering visitors into distinct groups based on characteristics in order to analyze visits.

Target
A specific numerical benchmark.

10/20/21, 12:26 PM Data Analytics

https://leocontent.umgc.edu/content/scor/uncurated/mba/2218-mba640/learning-topic-list/data-analytics.html?ou=610159 3/3

Resources

Data Analytics: Goals, Tools, Benefits, and Challenges

(/content/scor/uncurated/mba/2218-mba640/learning-resourcelist/data-

analytics-goalstoolsbenefitsandchallenges.html?ou=610159)

Licenses and Attributions

Chapter 18: Data Analytics

(https://www.redandyellow.co.za/content/uploads/woocommerce_uploads/2017/10/ema

rketing_textbook_download.pdf) from eMarketing: The Essential Guide to Marketing in

a Digital World, 5th Edition by Rob Stokes and the Minds of Quirk is available under a

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported

(https://creativecommons.org/licenses/by-nc-sa/3.0/) license. © 2008, 2009, 2010,

2011, 2013 Quirk Education Pty (Ltd). UMGC has modified this work and it is available

under the original license.

© 2021 University of Maryland Global Campus

All links to external sites were verified at the time of publication. UMGC is not responsible for the validity or integrity

of information located at external sites.

Visitor
An individual visiting a website that is not a search engine spider or a script.

10/20/21, 12:26 PM Segmentation in Web Analytics

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Learning Topic

Segmentation in Web Analytics
Every visitor to a website is different, but there are some ways in which we can

characterize groups of users and analyze metrics for each group. This is called

segmentation.

Default Segments in Google Analytics

Examples of segments include the following:

referral source—Users who arrive at your site via search engines, those who type in

the URL directly, and those who come from a link in an online news article are all

likely to behave differently. In addition to conversion rates, click path and exit pages

are important metrics to consider. Consider the page that these visitors enter your

website from—can anything be done to improve their experience?

landing pages—Users who enter your website through different pages can behave

very differently. What can you do to affect the page on which they are landing, or

what elements of the landing page can be changed to influence outcomes?

connection speed, operating system, browser—Consider the effects of technology

on the behavior of your users. A high bounce rate for low-bandwidth users, for

example, could indicate that your site is taking too long to load. Visitors who use

open-source technology may expect different things from your website than other

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visitors. Different browsers may show your website differently—how does this affect

these visitors?

geographical location—Do users from different countries, provinces or towns

behave differently on your website? How can you optimize the experience for these

different groups?

first-time visitors—How is the click path of a first-time visitor different from that of

a returning visitor? What parts of the website are more important to first-time

visitors?

Licenses and Attributions

Chapter 18: Data Analytics

(https://www.redandyellow.co.za/content/uploads/woocommerce_uploads/2017/10/ema

rketing_textbook_download.pdf) from eMarketing: The Essential Guide to Marketing in

a Digital World, 5th Edition by Rob Stokes and the Minds of Quirk is available under

a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported

(https://creativecommons.org/licenses/by-nc-sa/3.0/) license. © 2008, 2009, 2010,

2011, 2013 Quirk Education Pty (Ltd). UMGC has modified this work and it is available

under the original license.

© 2021 University of Maryland Global Campus

All links to external sites were verified at the time of publication. UMGC is not responsible for the validity or integrity

of information located at external sites.

10/20/21, 12:26 PM Key Elements of Web Analytics

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Key Elements of Web Analytics

In order to test the success of your website, you need to remember the TAO of

conversion optimization: track, analyze, optimize.

A number is just a number until you can interpret it. Typically, it is not the raw figures that

you will be looking at, but what they tell you about how your users are interacting with

your website. Because your web analytics package will never be able to provide you with

completely accurate results, you need to analyze trends and changes over time to

understand your brand’s performance.

Avinash Kaushik, author of Web Analytics: An Hour a Day, recommends a three-pronged

approach to web analytics (2007):

1. Analyzing data about behavior infers the intent of a website’s visitors. Why are

people visiting the website?

2. Analyzing outcomes metrics shows how many visitors performed the goal actions on

a website. Are visitors completing the goals we want them to?

3. A wide range of data tells us about the user experience. What are the patterns of

user behavior? How can we influence them so that we achieve our objectives?

Behavior

Web users’ behavior can indicate a lot about their intent. Looking at referral URLs and

search terms used to find the website can tell you a great deal about what problems

visitors are expecting your site to solve.

Some methods to gauge the intent of your visitors include the following:

click density analysis—Looking at a heatmap to see where people are clicking on the

site and if there are any noteworthy clumps of clicks (such as many people clicking

on a page element that is not actually a button or link).

segmentation—Selecting a smaller group of visitors to analyze based on a shared

characteristic (for example, only new visitors, only visitors from France, or only

visitors who arrived on the site by clicking on a display advert). This lets you see if

particular types of visitors behave differently.

behavior and content metrics—Analyzing data around user behaviors (e.g., time

spent on site, number of pages viewed) can give a lot of insight into how engaging

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and valuable your website is. Looking at content metrics will show you which pages

are the most popular, which pages users leave from most often and more. This data

provides excellent insight for your content marketing strategy and helps uncover

what your audience is really interested in.

A crucial, often-overlooked part of this analysis is internal search. Internal search refers to

the searches of the website’s content that users perform on the website. While a great

deal of time is spent analyzing and optimizing external search—using search engines to

reach the website in question—analyzing internal search goes a long way to exposing

weaknesses in site navigation, determining how effectively a website is delivering

solutions to visitors, and finding gaps in inventory on which a website can capitalize.

For example, consider the keywords a user may use when searching for a hotel website,

and keywords they may use when on the website. Keywords to search for a hotel website

may be Cape Town hotel or bed and breakfast Cape Town. Once on the website, the user

may use the site search function to find out more. Keywords they may use include Table

Mountain, pets, or babysitting service. Analytics tools can show what keywords users

search for, what pages they visit after searching, and, of course, whether they search

again or convert.

Outcomes

At the end of the day, you want people who visit your website to perform an action that

increases your revenue. Analyzing goals and key performance indicators (KPIs)

demonstrates where there is room for improvement. Look at user intent to establish if

your website meets the users’ goals and if these match with the website goals. Look at

user experience to determine how outcomes can be influenced.

Website Performance

Reviewing conversion paths can give you insight into

improving your website.

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In the figure above, after performing a search, one hundred visitors land on the homepage

of a website. From there, 80 visitors visit the first page toward the goal. This event has an

80 percent conversion rate. Twenty visitors take the next step. This event has a 25

percent conversion rate. Ten visitors convert into paying customers. This event has a 50

percent conversion rate. The conversion rate of all visitors who performed the search is

10 percent, but breaking this up into events lets us analyze and improve the conversion

rate of each event.

User experience

In order to determine the factors that influence user experience, you must test and

determine the patterns of user behavior. Understanding why users behave in a certain

way on your website will show you how that behavior can be influenced to improve your

outcomes.

References

Kaushik, A. (2007). Web analytics: An hour a day. San Francisco, CA: Sybex.

Licenses and Attributions

Chapter 18: Data Analytics

(https://www.redandyellow.co.za/content/uploads/woocommerce_uploads/2017/10/ema

rketing_textbook_download.pdf) from eMarketing: The Essential Guide to Marketing in

a Digital World, 5th Edition by Rob Stokes and the Minds of Quirk is available under

a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported

(https://creativecommons.org/licenses/by-nc-sa/3.0/) license. © 2008, 2009, 2010,

2011, 2013 Quirk Education Pty (Ltd). UMGC has modified this work and it is available

under the original license.

© 2021 University of Maryland Global Campus

All links to external sites were verified at the time of publication. UMGC is not responsible for the validity or integrity

of information located at external sites.

Learning Topic

Tracking and Collecting Data

Currently, there are two main approaches for collecting web analytics data: cookie-based tracking and server-based tracking. A third option, called universal analytics, is set to dramatically change how data is gathered and analyzed. Universal analytics is one of the most exciting examples of non-cookie-based server tracking.

How Information Is Captured

Cookie-Based Tracking

The most common method of capturing web analytics is to use cookie-based tracking. Here’s how it works:

1. The analyst adds a page tag (a piece of JavaScript code) to every page of the website.

2. A user accesses the page using their browser.

3. When the browser loads the page, it runs the page tag code.

4. This tag sends an array of information to a third-party server (like Google Analytics), a service that stores and collates the data.

5. The analyst accesses this data by logging in to the third-party server.

The data gathered this way can capture a wide array of factors about each visitor, from their device, operating system, and screen resolution, to their long-term behavior on your website. This is currently the most common option for most website tracking.

Server-Based Tracking

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Web servers are the computers that websites are stored on so that they can be accessed online. Server-based tracking involves looking at log files—documents that are automatically created by servers and that record all clicks that take place on the server. A

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new line is written in a log file every time a new request is made—for example, clicking on a link or submitting a form.

Server-based tracking is very useful for tracking mobile visitors (since many phones cannot execute the cookie-based JavaScript tags) and is also essential for universal analytics, discussed below.

Comparing the Options

Cookie-Based Tracking vs. Server-Based Tracking

Cookie-Based

Tracking Server-Based Tracking

Web Servers Page tagging requires changes to the website and can be used by companies that do not run their

own web servers.

Log files are produced by web servers, so the raw data is readily available, but the company must have access to the server.

Accuracy Cookie-based tracking can be less accurate than server- based tracking. If a user’s browser does not support

JavaScript, for example, no information will be captured.

Log files are very accurate— they record every click. Log files also record visits from search engine spiders, which is useful useful for search engine optimisation.

Cookie-Based

Tracking Server-Based Tracking

Historical Data Page tags are proprietary to each vendor, so switching can mean losing

historical data.

Log files are in a standard format, so it is possible to switch vendors and still be able to analyze historical data.

Page Requests Page tagging shows only successful page

requests.

Log files record failed page requests.

Capturing Information JavaScript makes it easier to capture

more information (e.g. products purchased,

or the version of a

user’s browser).

Server-based tracking can capture some detailed information, but this involves modifying the URLs.

Events Reporting JavaScript tracking can report on events such as interactions

with a Flash movie.

Server-based tracking cannot report on events.

Log File Analysis Third-party page tagging service providers usually offer a good level of

support.

Log file analysis software is often managed in-house.

Because these two options use different methods of collecting data, the raw figures produced will differ. For example, caching occurs when a browser stores some of the information for a web page, so that it can retrieve it more quickly when you return.

Opening this cached page will not send a request to the server. This means that the visit won’t show up in the log files, but would be captured by page tags.

Website analytics packages can be used to measure most, if not all, digital marketing campaigns. Website analysis should always account for the various campaigns being run. For example, generating high traffic volumes by employing various digital marketing tactics such as SEO, PPC (pay per click), and email marketing can prove to be a pointless

and costly exercise if visitors are leaving your site without achieving one (or more) of your website’s goals. Conversion optimization aims to convert as many of a website’s visitors as possible into active customers.

Universal Analytics

Google recently announced a new feature in its analytics suite called universal analytics. The biggest problem web analysts have faced up until now is that they can’t actually track individual people—only individual browsers (or devices), since this is done through

cookies. So, if Joe visits the website from Chrome on his home computer, and Safari on his work laptop, the website will think he’s two different people. And if Susan visits the site from the home computer, also using Chrome, the website will think she’s the same user as Joe.

An additional concern is that cookies are on the decline. Most modern browsers allow users to block them, and many mobile devices simply can’t access or execute them. With growing consumer privacy concerns, and new laws like the EU Privacy Directive (which requires all European websites to disclose their cookie usage), cookies are falling out of favor.

Universal analytics allows you to track visitors (that means real people) rather than sessions. By creating a unique identifier for each customer, universal analytics means you can track the user’s full journey with the brand, regardless of the device or browser they use. So, that means you can track Joe on his home computer, work laptop, mobile phone during his lunch break, and even when he swipes his loyalty card at the point of sale.

Crucially, however, tracking Joe across devices requires both universal analytics and authentication on the site across devices. In other words, Joe has to be logged in to your website or online tool on his desktop, work laptop, and mobile phone in order to be tracked this way. If he doesn’t log in, we won’t know it’s the same person.

With universal analytics, you can glean a lot of information:

How visitors behave depending on the device they use (e.g., browsing for quick

ideas on their smartphone, but checking out through the eCommerce portal on their desktop)

How visitor behavior changes the longer they are a fan of the brand. Do they come back more often, for longer, or less often but with a clearer purpose?

How often they’re really interacting with your brand.

Their lifetime value and engagement.

Another useful feature of universal analytics is that it allows you to import data from other sources into Google Analytics—for example, customer relationship management (CRM) information or data from a point-of-sale cash register. This gives a much broader view of the customers and lets you see a more direct link between your online efforts and real-world behavior.

The Type of Information Captured

KPIs are the metrics that help you understand how well you are meeting your objectives. A metric is a defined unit of measurement. Definitions can vary among web analytics vendors depending on their approach to gathering data, but the standard definitions are provided here.

Web analytics metrics are divided into two categories:

counts—raw figures that will be used for analysis

ratios—interpretations of the data that is counted

Metrics can be applied to three different groupings:

aggregate—all traffic to the website for a defined period of time

segmented—a subset of all traffic according to a specific filter, such as by campaign

(PPC) or visitor type (new visitor vs. returning visitor)

individual—the activity of a single visitor for a defined period of time The key metrics used in website analytics are covered in the sections below. Building-Block Terms

Building-block terms are the most basic web metrics. They tell you how much traffic your website is receiving. For example, looking at returning visitors can tell you how well your website creates loyalty. A website needs to grow the number of visitors who come back. An exception may be a support website, as repeat visitors could indicate that the website has not been successful in solving the visitor’s problem. Each website needs to be analyzed based on its purpose. Building-block terms include the following:

hit—one page load (Note that hit is an outdated term that we recommend you avoid using).

page—unit of content (downloads and Flash files can be defined as pages).

page views—the number of times a page was successfully requested.

visit or session—an interaction by an individual with a website consisting of one or more page views within a specified period of time.

unique visitors—the number of individual people visiting the website one or more times within a set period of time. Each individual is counted only once.

new visitor—a unique visitor who visits the website for the first time ever in

the period of time being analyzed.

returning visitor—a unique visitor who makes two or more visits (on the same device and browser) within the time period being analyzed.

New and Returning Visitors in

Google Analytics

Visit Characteristics

These are some of the metrics that tell you how visitors reach your website and how they move through the website. The way that a visitor navigates a website is called a click

path. Looking at the referrers, both external and internal, allows you to gauge the click

path that visitors take. These metrics include the following:

entry page—the first page of a visit

landing page—the page intended to identify the beginning of the user experience resulting from a defined marketing effort

exit page—the last page of a visit

visit duration—the length of time in a session

referrer—the URL that originally generated the request for the current page

internal referrer—a URL that is part of the same website

external referrer—a URL that is outside of the website

search referrer—a URL that is generated by a search function

visit referrer—a URL that originated from a particular visit

original referrer—a URL that sent a new visitor to the website

clickthrough—the number of times a link was clicked by a visitor

clickthrough rate—the number of times a link was clicked divided by the number of times it was seen (impressions)

page views per visit—the number of page views in a reporting period divided by the number of visits in that same period to get an average of how many pages are being viewed per visit

Visitor Behavior in Google Analytics

Content Characteristics

When a visitor views a page, they have two options: leave the website, or view another page on the website. These metrics tell you how visitors react to your content. Bounce rate can be one of the most important metrics that you measure. There are a few exceptions, but a high bounce rate usually means high dissatisfaction with a web page.

page exit ratio—number of exits from a page divided by total number of page views

of that page

single page visits—visits that consist of one page, even if that page was viewed a number of times

bounces (or single page view visits)—visits consisting of a single page view

bounce rate—single page view visits divided by entry pages

Conversion Metrics

These metrics give insight into whether you are achieving your analytics goals (and through those, your overall website objectives):

event—a recorded action that has a specific time assigned to it by the browser or the server.

conversion—a visitor completing a target action.

Goal Conversions in Google Analytics

Mobile Metrics

When it comes to mobile data, there are no special, new or different metrics to use. However, you will probably be focusing your attention on some key aspects that are particularly relevant here—namely technologies and the user experience. Mobile metrics include the following:

device category—whether the visit came from a desktop, mobile device, or tablet

mobile device info—the specific brand and make of the mobile device

mobile input selector—the main input method for the device (e.g., touchscreen, clickwheel, stylus)

operating system—the OS that the device runs (some popular operating systems include iOS, Android, and BlackBerry)

Mobile Device Categories in Google Analytics

Now that you know what tracking is, you can use your objectives and KPIs to define what metrics you’ll be tracking. You’ll then need to analyze these results and take appropriate actions. Then the testing begins again!

Licenses and Attributions

Chapter 18: Data Analytics

(https: /www.redandyellow.co.za/content/uploads/woocommerce_uploads/2017/10/ema rketing_textbook_download.pdf) from eMarketing: The Essential Guide to Marketing in a Digital World, 5th Edition by Rob Stokes and the Minds of Quirk is available under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported

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2011, 2013 Quirk Education Pty (Ltd). UMGC has modified this work and it is available under the original license.

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