Leveraging Search Technologi Leveraging Search Technologi Google is the world’s premier search engine with more than 60,000 searches made every second, wh

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  Leveraging Search Technologi

Google is the world’s premier search engine with more than 60,000 searches made every second, which equates to between five and six billion searches on any given day. As a result, the company is highly profitable earning around $100 billion in advertising revenue each year.

Research an organization located in the Kingdom Saudi Arabia and discuss the following:

· What type of search engine technology is the company using?

· Discuss the benefits the company is gaining from using that technology?

· What sort of metrics does the company use to measure the success of the utilized search engine technology?

· What other metrics might the company consider using to measure the success of the utilized search engine technology? Why?


1. Chapter 6 in Information Technology for Management: On-Demand Strategies for Performance, Growth, and Sustainability

2. Wei, L., & Na, C. (2020). Personalized recommendation algorithm based on improved trustworthiness. 2020 International Conference on Robots & Intelligent System (ICRIS), 526–528.

3. Drivas, I. C., Sakas, D. P., Giannakopoulos, G. A., & Kyriaki-Manessi, D. (2020). Big Data Analytics for Search Engine Optimization. Big Data and Cognitive Computing, 4(5), 5.


Chapter 6 PowerPoint slides


  • Be 4-5 pages in length
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Search, Semantic, and
Recommendation Technology


Case 6.1 Opening Case: Mint.com Uses Search
Technology to Rank Above Established Competitors

6.1 Using Search Technology for Business

6.2 Organic Search and Search Engine

6.3 Pay-Per-Click and Paid Search Strategies

6.4 A Search for Meaning—Semantic Technology

6.5 Recommendation Engines

Case 6.2 Business Case: Deciding What to Watch—
Video Recommendations at Netflix

Case 6.3 Video Case: Power Searching with Google


6.1 Describe how search engines work and identify ways that
businesses gain competitive advantage by using search
technology effectively.

6.2 Explain how to improve website ranking on search
results pages by optimizing website design and creating
useful content.

6.3 Describe how companies manage paid search advertising
campaigns to increase awareness and drive sales volume.

6.4 Describe how semantic Web technology enhances the accuracy
of search engines results and how businesses can optimize their
websites to take advantage of this emerging technology.

6.5 Describe how recommendation engines are used to enhance
user experience and increase sales on e-commerce websites.

Every day, over 1.5 billion people around the world use what seems to be a simple tool to find
information online—a search engine. We sometimes take for granted that behind a relatively
simple user interface, an increasingly complex set of search engine technologies are at work,

166 C H A P T E R 6 Search, Semantic, and Recommendation Technology

helping us find the information we need to do our jobs, conduct research, locate product
reviews, or find information about the television shows we watch. Because most search engine
services are free, people are not generally aware that “Search” has become a multibillion- dollar-
a-year business. More importantly, the way search engines work and how they rank-order the
links displayed when we conduct a search have huge implications for millions of other busi-
nesses. Because consumers typically don’t look past the first few pages of search results, hav-
ing your business appear at the top of a search results page can make a big difference in how
much traffic your website gets. In this chapter, you will read about how search engines work
and how they determine which websites are listed at the top of search results. You will also read
about the strategies companies use to increase their presence on search results pages includ-
ing search engine optimization (SEO) and pay-per-click (PPC) advertising.

Semantic technologies are increasingly being used by search engines to understand
Web page content. In this chapter you will read about the ways that search engines are using
semantic technology to improve performance, increasing relevant pages and decreasing the
number of irrelevant pages that appear in search results.

Finally, you will read about recommendation engines. These tools attempt to anticipate
online information you might be interested in. Netflix uses recommendation engines to sug-
gest movies you might like to watch and news organizations use them to recommend stories
you might want to read on their websites. Amazon credits its recommendation technology for
increasing sales by suggesting products that customers might want to buy.

Business managers need to understand search and recommendation technologies because
their influence in directing potential consumers to business websites is already significant and
expected to grow substantially in the future.

Case 6.1 Opening Case

Mint.com Uses Search Technology to Rank Above
Established Competitors

Company Overview
Mint is a popular, Web-based personal finance service that makes it
easy for users to keep track of bank, credit card, and other financial
accounts using a computer or mobile device. Customers can also use
the service to create budgets and monitor progress toward financial
goals. Since it began in 2006, the company has grown rapidly despite
competition from more established companies. In 2009, Mint was
acquired by Intuit, the maker of TurboTax and Quicken financial soft-
ware. Today, over 20 million people use Mint’s free financial manage-
ment service (Table 6.1).

The Business Challenge
In the months leading up to the 2006 launch of Mint.com, a personal
finance service, the leadership team faced a formidable challenge: How

to establish name awareness and brand equity in a market filled with
established competitors, without spending a lot of money? Mint knew
it would be competing in a market space already populated by familiar
brands like Quicken Online and Microsoft Money Online. Since online
platforms and communication channels tend to favor existing compa-
nies with established audiences and reputations, the team knew they
had to come up with a powerful strategy for overcoming the estab-
lished brands.

Mint’s Content Marketing Strategy
As a Web-based service, it was critical for Mint.com to rank high on
search engine results pages (SERPs) when consumers used sites like
Google or Bing to find information about personal finance services and
related topics. Consumers are more likely to visit websites that appear
at the top of SERPs. While the service was still in the beta (trial) stage
of development, workers at Mint developed an aggressive strategy to
optimize the brand’s ranking on popular search engines. Their strat-
egy involved building the company’s Web presence on criteria used by




























Introduction 167

TA B L E 6 . 1 Opening Case Overview

Company Mint

History Mint was launched in 2006 as a free, Web-based personal finance app by founder Aaron Patzer. In 2009,
the company was acquired by the financial software company Intuit.

Growth Within two years of launch, Mint claimed over 1.5 million users. By 2012, the company claimed
10 million users and by 2016, the number of users rose to over 20 million.

Product lines Mint’s original service allowed users to track balances and transactions on credit card, investment, and
bank accounts as well as to create budgets and establish financial goals. In addition, Mint now offers
users a bill pay service and credit score monitoring.

Social technology Prior to the release of its flagship personal finance app, Mint created a large following of prospective
users with MintLife, a blog that offered valuable advice targeted to young professionals.

Search technology Mint utilized an aggressive SEO strategy to rank highly on search results pages. Specific actions
included the following:
• Creation of useful personal finance content on its blog, MintLife
• Use of targeted keywords in website content
• Established audiences on popular social media sites such as Facebook and Twitter
• Used various strategies, including sponsorship of third-party blogs, to generate links (or “backlinks”)

to Mint.com from other websites

Website Mint.com

search engines to determine SERP ranking. The strategy focused on
the following:

• Increasing the number of other websites that linked back to
Mint’s website (called “backlinks”)

• Creating interesting and useful content about personal finance
topics that prospective customers would find helpful

• Identifying keywords and phrases used by prospective customers
when searching for personal financial services, and creatively
inserting these words and phrases into website content

• Regularly updating and adding to their collection of personal
finance content

• Establishing a presence on popular social media sites, expanding
their audience on those sites, and encouraging the audience to
share links to Mint’s website content

Months prior to the launch of its personal finance service, Mint
rolled out a personal finance blog called MintLife and quickly devel-
oped a reputation for providing helpful financial advice targeted to
young professionals. Blog posts on MintLife were creatively seeded
with keywords and phrases the team had identified as likely to be
used by prospective customers when conducting Internet searches
for financial services. Mint also created landing pages on their web-
site containing content optimized for keywords and phrases related
to financial services. As search engines tracked this content, Mint
began to lay a foundation for eventually being viewed by search
engines as a credible authority for personal finance topics. New
posts were regularly added to the blog, which further enhanced
Mint’s ranking since search engines favor websites with lots of
content (content depth) and regular updates. To further establish
its position as a useful and authoritative site, Mint sponsored sev-
eral third-party blogs and cultivated relationships with authors of
established finance and money management blogs. Mint’s founder,
Aaron Patzer, gave hundreds of interviews, resulting in print media
and online articles about the start-up company. These and other
actions resulted in more third-party websites posting links back to

Mint.com. These “backlinks” were tracked by search engines and
resulted in additional increases to the site’s ranking on SERPs. Popu-
lar search engines also track a company’s presence on social media
and the extent to which users share information about the company
and its products. Mint’s blog featured content in a variety of inter-
esting formats: videos, podcasts, infographics, and so on. Users on
social news sites like Reddit.com frequently shared and “upvoted”
interesting infographics from Mint’s blog. Links to other types of blog
content were shared by users on Facebook, Twitter, and other social
media platforms. As a result, Mint’s expanding audiences on Face-
book, Twitter, and other social media platforms further enhanced
the new company’s SERP ranking.

In 2007, Mint launched its new financial services website into a market
where it already enjoyed considerable name recognition and aware-
ness. Within 2 years, the service acquired 1.5 million users and was
purchased by Intuit for $170 million. The company continued its suc-
cessful content marketing strategy, climbing to 10 million users in 2012
and over 20 million users today.

1. Why did Mint invest the time and effort to publish a financial

services blog almost two years before the launch of its service?

2. How did Mint use social media sites to increase its ranking on the
search results pages of popular search engines?

3. Why did Mint use keywords and phrases associated with personal
finance when creating content for its blog?

4. Why did Mint put so much emphasis on improving the rank of its
website on SERPs?

5. Why did Mint use infographics, videos, and other types of rich
media in its financial services blog?

Sources: Compiled from Sukhraj (2015), Bulygo (2013a), Obi-Azubuike (2016),
Prince (2016), Greene (2016).

168 C H A P T E R 6 Search, Semantic, and Recommendation Technology

6.1 Using Search Technology
for Business Success
Search engines like Google, Bing, Yahoo, and others have traditionally been regarded as a
consumer technology. But search technology has become an important business tool with
many different uses and applications. In this section, you will learn how search engines work
and the role they play in generating revenue and consumer awareness for organizations. You
will also discover how businesses use enterprise search technology to unlock hidden content
with their organizations. Finally, you will read about how search and Internet technology is
evolving to provide more accurate and useful results.

How Search Engines Work
People use the word search engine to refer to many different kinds of information retrieval (IR)
services that find content on the World Wide Web. These services vary in significant ways.
Understanding how these services differ can improve the quality of results obtained when con-
ducting a search for online information. Listed below is a brief description of different IR ser-
vices for finding Web content:

• Crawler search engines rely on sophisticated computer programs called spiders, crawlers,
or bots that surf the Internet, locating Web pages, links, and other content that are then
stored in the search engine’s page repository. The most popular commercial search engines,
Google and Bing, are based on crawler technology.

• Web directories list Web pages organized into hierarchical categories. Originally, Web direc-
tories were created and maintained by human editors who decided how a website would
be categorized. Today, many Web directories use technology to automate new website list-
ings. Web directories are typically classified as “general” directories that cover a wide-range
topical categories, or “niche” directories that focus on a narrow range of topics. Examples
of popular general directories include Best of the Web, JoeAnt, and LookSmart. Wikipedia
maintains a list of general and niche Web directories.

• Hybrid search engines combine the results of a directory created by humans and results
from a crawler search engine, with the goal of providing both accuracy and broad coverage
of the Internet.

• Meta-search engines compile results from other search engines. For instance, Dogpile
generates listings by combining results from Google and Yahoo.

• Semantic search engines are designed to locate information based on the nature and
meaning of Web content, not simple keyword matches. The goal of these search engines
is to dramatically increase the accuracy and usefulness of search results. Semantic search
engines are described in more detail in Section 6.4.

Web Directories
Before crawler search engines became the dominant method for finding Web content, people
relied on directories created by human editors to help them find information. Web directories are
typically organized by categories (for instance, see the categories listed on Best of the Web). Web
page content is usually reviewed by directory editors prior to its listing in a category to make sure
it is appropriate. This reduces the number of irrelevant links generated in a search. The review
process, however, is very slow compared to the automated process used by crawlers (described
in the following section). As a result, the listings in a Web directory represent a relatively small
portion of the Web. Directories are particularly useful when conducting searches on a narrow
topic, such as identifying suppliers of a specific type of product or service. Companies who need

Search engine an application
for locating Web pages or other
content (e.g., documents, media
files) on a computer network.
Popular Web-based search
engines include Google, Bing,
and Yahoo.

Spiders also known as
crawlers, Web bots, or simply
“bots,” spiders are small computer
programs designed to perform
automated, repetitive tasks over
the Internet. They are used by
search engines for scanning Web
pages and returning information
to be stored in a page repository.

Using Search Technology for Business Success 169

to identify vendors or suppliers may consult a niche Web directory created for just this purpose.
For example, see the Web directory at business.com.

How Crawler Search Engines Work
The two most popular commercial search engines on the Web, Google and Bing, are based
on crawler technology. Behind the relatively simple interfaces of these two powerful search
engines, a great deal of complex technology is at work (Figure  6.1). Because modern search
engines use proprietary technology in the race to stay ahead of competitors, it is not possible
to tell exactly how they decide what websites will appear in a SERP. While they each produce
different results, it is possible to describe the basic process shared by most crawler search
engines. The following description is based on publications by Grehan (2002) and Oak (2008).

1. The crawler control module assigns Web page URLs to programs called spiders or bots. The
spider downloads these Web pages into a page repository and scans them for links. The
links are transferred to the crawler control module and used to determine where the spi-
ders will be sent in the future. (Most search engines also allow Web masters to submit
URLs, requesting that their websites be scanned so they will appear in search results.
These requests are added to the crawler control queue.)

2. The indexer module creates look-up tables by extracting words from the Web pages and
recording the URL where they were found. The indexer module also creates an inverted
index that helps search engines efficiently locate relevant pages containing keywords
used in a search. (See Figure 6.2 for examples of an inverted index.)

3. The collection analysis module creates utility indexes that aid in providing search results.
The utility indexes contain information about things such as how many pages are in a web-
site, the geographic location of the website, number of pictures on a Web page, Web page
length, or other site-specific information the search engine may use to determine the rel-
evance of a page.

4. The retrieval/ranking module determines the order in which pages are listed in a SERP.
The methods by which search engines determine website listing order varies and the spe-
cific algorithms they use are often carefully guarded trade secrets. In some cases, a search
engine may use hundreds of different criteria to determine which pages appear at the top
of a SERP. Google, for instance, claims to use over 200 “clues” to determine how it ranks
pages (Google.com, 2014).

Page repository a data
structure that stores and manages
information from a large number
of Web pages, providing a fast and
efficient means for accessing and
analyzing the information at a
later time.

Crawler control module
a software program that controls
a number of “spiders” responsible
for scanning or crawling through
information on the Web.

Page Repository


Text Utility



Analysis Module

Surfer–Client QueriesSpiders/

Crawler Control


1. URL
2. URL
3. URL





FIGURE 6.1 Components of crawler search engine (Adapted from Grehan, 2002).

170 C H A P T E R 6 Search, Semantic, and Recommendation Technology

5. Web pages retrieved by the spiders, along with the indexes and ranking information, are
stored on large servers (see IT at Work 6.1).

6. The query interface is where users enter words that describe the kind of information they
are looking for. The search engine then applies various algorithms to match the query string
with information stored in the indexes to determine what pages to display in the SERP.

Each search engine utilizes variations and refinements of the aforementioned steps in
an attempt to achieve superior results. The Web search industry is highly competitive and
the proprietary advances in search technology used by each company are closely guarded
secrets. For instance, even the first step in the process, crawling the Web for content, can vary
greatly depending on the strategic goals of the search engine. Some search engines limit the
number of pages scanned at each website, seeking instead to use limited computing power
and resources to cover as many websites as possible. Other search engines program their spi-
ders to scan deep into each website, seeking more complete coverage of each site’s content.
Still other search engines direct their spiders to seek out websites that contain certain types
of content, such as government sites or shopping (e-commerce) sites. Another decision that
search engines make regarding spiders is the amount of resources directed at searching
new websites versus devoting resources to exploring previously indexed pages for updates
or changes.

One of the many challenges faced by large commercial search engines is storage. In the
simplest sense, the crawler approach to search requires a company to store a copy of the Web
in large data centers. In addition to the petabytes of storage required to maintain this copy of
the Web, the search engine must also store the results of its indexing process and the list of
links for future crawls.

Petabyte a unit of measurement
for digital data storage. A petabyte
is equal to one million gigabytes.

Document ID

To the heart, real love
always endures.

Though passion may
cool, love remains true.
True love kindles the
passion in my heart.



Content URL

Search Query:

Page Index

Inverted Index

ID Term Document: Position

1 1:3, 3:7


1:5, 2:5, 3:2



2:7, 3:2


2:2, 3:5































True love

Results Ranking (based on position)

True love kindles the passion in my heart.

Though passion may cool, love remains true.

Documents with
both terms: 2 and 3

FIGURE 6.2 Search engines use inverted indexes to efficiently locate Web content based on search query terms.

Using Search Technology for Business Success 171

IT at Work 6.1

Google Data Centers
Not only does Google maintain a copy of the Internet for its search
engine services, it is also constantly updating a map of the entire
planet for users of its popular Google Earth application. In addition,
the company is making a full-text, searchable copy of over 129,864,880
known books, equal to 4 billion pages or 2 trillion words. And then
there are applications like Gmail, serving roughly 425 million people
and YouTube, where 300 hours of video are uploaded every minute!
Add all this up, and Google is facing perhaps the biggest data storage
challenge ever. So where does Google store all of these data?

Challenges: Energy, Performance, and Security
Information collected by Google is housed on over 1 million servers
spread across 12 different facilities worldwide. The facilities are
large, factory-like installations containing row upon row of racked
and stacked servers. Cooling systems, required to keep servers from
overheating, are a significant component of any large data center
(Figure  6.3). Google pioneered the software systems that connect
the company’s servers and make it possible for various applications
to access data stored on the machines. Unlike other companies that
purchase servers from outside suppliers, Google builds its own.
Based on its experience creating the hardware, software, and facil-
ities necessary to power the company on a global scale, Google is
recognized as a leader in data center operations.

The company’s data centers, including the servers, are built
with energy efficiency, reliability, and performance in mind. As
Google is a leading provider of Internet services, its data infrastruc-
ture must keep up with growing consumer demand for speedy
performance and reliability. A typical Google search delivers millions
of pages of results in less than half a second. Consumer expectations
for performance have grown so high that waiting more than a few
seconds for an e-mail to load or a search to run can cause frustration.

More recently, Google has had to contend with revela-
tions that the U.S. National Security Agency (NSA) breached
its server network security. This follows cyberattacks in 2010
and 2011 by hackers suspected of being associated with the
Chinese government. Protecting company data from criminals
is a significant challenge in itself, but Google is understandably

frustrated by the fact that it must now fight off cyber-attacks from
two world superpowers, one of which is its own government.

Environmental Impact
Industrywide, data centers used 70 billion kilowatt-hours of
electricity in 2014, representing a 4% increase from the amount
used in 2012. Industrywide, data center energy use and the related
environmental impact have become an issue of growing concern.
Google is widely recognized as operating some of the most efficient
data centers in the world, but many critics are disturbed by the
industry’s overall level of energy consumption. According to some
estimates, data centers account for about 2% of the world’s energy
use and the fast rate of growth is cause for concern (see Figure 6.4).
Google has taken an active approach to reducing its environmental
footprint. Beginning in 2017, Google will source 100% of its energy
needs for offices and data centers from renewable sources. See
Google’s data center Web page https://www.google.com/about/
datacenters for additional information.

Google Data Center Statistics
• Number of servers worldwide Over 1 million
• Number of data centers Nine in North America, one in

South America, two in Asia, and four in Europe

• 2016 Capital investment in data centers Approximately
$11 billion

• Data processing volume Over 100 petabytes a day
• Average energy efficiency PUE* = 1.12
• Energy use Continual use of about 260 megawatts of

electricity, approximately 0.01% of global energy consumption

• Energy use comparisons Owns about 3% of servers world-
wide, but only uses about 1% of data center industry energy

• Renewable energy Claims that 100% percent of its energy
use comes from renewable sources

*PUE stands for Power Usage Effectiveness. A PUE of 2.0 means that for
every watt of power devoted to computing, an additional watt is spent
on cooling, power distribution, and overhead. The Data Center Industry
average PUE falls between 1.8 and 1.89.

Sources: Jacobson (2010), Grifantini (2011), Newman (2011), Schneider
(2011), Glanz (2011, 2012), Gallagher (2012), Venkatraman (2012), Anthony
(2013), Miller (2013), Sverdlik (2016).







FIGURE 6.3 Pipes pass through the chiller plant at the
Google, Inc., data center in Changhua, Taiwan. Google doubled
its spending plan for its new data center in Taiwan to $600
million amid surging demand from Asia for its Gmail and
YouTube services.







FIGURE 6.4 New, large-scale data centers being constructed
for companies like Google, Microsoft, and Facebook house
thousands of servers and are creating concern among
environmentalists over increases in energy consumption.

172 C H A P T E R 6 Search, Semantic, and Recommendation Technology

Why Search Is Important for Business
Search engines have become a part of our everyday life. They are free, easy to use, and become
more powerful and effective every day. Most of us take them for granted and are generally
unaware of the complex technologies that power these tools. For the average Web user,
it may not be vitally important to understand how search technology is evolving. But for
business managers, understanding the potential power of search technology is crucial and
becoming more important every day. It has long been recognized that access to information
is a competitive advantage. Search technology impacts business in each of the following ways:

• Enterprise search—finding information within your organization
• Recommendation engines—presenting information to users without requiring them to

conduct an active search
• Search engine marketing (SEM)—getting found by consumers on the Web
• Web search—finding crucial business information online

Each of these important search technology applications are described in what follows.

Enterprise Search Enterprise search tools are used by

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