Big Data. Big Decisions
InformationWeek
Special Coverage Series


Mac Users See Pricier Rooms At Orbitz

Orbitz says Mac users are willing to pay 30% more for hotel rooms than PC users so it is showing them more expensive options.

Imagine walking into a retail outlet and asking how much a certain item costs and instead of an answer you get a question: How much do you have?

Online merchants however don't have to engage in such an overt shakedown, because they already have a pretty good idea how much you have, thanks to data surrendered to online tracking techniques.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

The latest example of this comes from travel website Orbitz, which has been presenting Mac users with more expensive travel options than Windows users. According to the Wall Street Journal, Orbitz has found that Mac users are willing to pay as much 30% more than Windows users on hotels and has begun presenting them with different and sometimes pricier options through its website.

[ Want another browser option? Read Firefox For Android Reborn. ]

A 2009 study by research firm NPD explains Orbitz's finding that Mac users will pay more. It found that 36% of Apple computer owners reported incomes above $100,000, compared to 21% of consumers in general, and the average Apple household has twice as many consumer electronics devices compared to other households.

Orbitz did not immediately respond to a request for comment but a company tweet endorses a Fortune article that characterizes the company's actions as merely an attempt to please a group that is seeking higher-end lodging than other Orbitz visitors.

Michael Belch, professor of marketing at San Diego State University, said in a phone interview that while dynamic pricing of this sort may not be illegal, he believes it's unethical. He describes a scenario in which a Mac user and a Windows user visit Orbitz to book a room. "We both go to Orbitz to help us find the best price, but they're not doing that," he said.

Orbitz might respond by noting that it still presents the cheapest rates elsewhere on its website, Belch suggests. "They're going to say all you have to do is scroll down," he said. "But that's not full disclosure."

Dynamic pricing, or price discrimination, as economist Paul Krugman has referred to it, is not new. It has been practiced for years in the airline industry and can be seen in movie ticket pricing, in which youths and seniors pay less than adults. But it becomes controversial when the factors used to discriminate are unexpected, undisclosed, or unlawful.

Orbitz is not so much engaged in dynamic pricing as dynamic presentation: It's not pricing the same room differently for different people; rather it's showing different, sometimes higher priced rooms to Mac users on the assumption they're more interested in these options.

Twelve years ago, the Wall Street Journal ran a similar story, "Amazon.com Varies Prices of Identical Items for Test," about how the online retailer offered DVDs to customers at prices that varied by as much as 40%. The ensuing outcry prompted Amazon to offer refunds to almost 7,000 customers.

Ironically, Amazon prompted a related outcry from merchants late last year when it introduced its Price Check app, which allows customers to scan merchandise bar codes on their mobile phones and determine whether items can be purchased for less on Amazon. Merchants like having data about customers, but they're not so keen when customers have data about their operations.

But the absence of data privacy no longer scandalizes in the Facebook era. Companies are awash in customer data and plenty of them are trying to find ways to use it, with only muted grumbling from consumers. Expect to see more efforts to link pricing to customer data.

The Federal Trade Commission did not immediately respond to a query about its views on dynamic pricing, but it has in the past supported the dynamic pricing as practiced by energy utilities.

Nonetheless, a 2001 article from the Virginia Journal of Law and Technology, "Online Dynamic Pricing: Efficiency, Equity and the Future of E-commerce," suggests that the FTC may have to become more active in determining where to draw the line between lawful and unlawful price discrimination.

"The current legal regime seems to permit some previous forms of price discrimination," the article states. "But the question remains whether new information technology has unleashed a new form of price discrimination and, in the process, ushered in a completely new era of online pricing practices. How we deal with this new era--whether we leave it to the information flows of self-regulation and the market forces of competition, or whether we use the more traditional powers of the state--may well determine the future fate of e-commerce."

Given the silence of the state on this issue, it would appear that businesses are free to continue exploring different prices for different customers, at least until something more egregious than pitching rich Mac users on more expensive rooms comes along.

At this year's InformationWeek 500 Conference, C-level execs will gather to discuss how they're rewriting the old IT rulebook and accelerating business execution. At the St. Regis Monarch Beach, Dana Point, Calif., Sept. 9-11.



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.