most of us are accustomed to the straightforward pricing models of brick-and-mortar stores. Items are displayed with clear price tags, and discounts are often available through coupons, memberships, or group-specific deals like student or AARP discounts. These discounts are typically well-publicized, allowing equal access to all shoppers.
However, the transition to online shopping has introduced a new pricing paradigm that diverges significantly from traditional models. The notion that the same buying principles apply online is a misconception many consumers hold, but recent revelations have challenged this belief.
It was in 2010 when consumers first became aware of Amazon’s practice of price differentiation. The company was found to be charging different prices for the same DVD to different consumers. Following this, a 2012 Wall Street Journal report unveiled that Staples varied its pricing based on customers’ locations. Orbitz also came under scrutiny for showing pricier hotel options to Mac users compared to PC users.
These instances of price discrimination and steering led to substantial negative press for the companies involved. This lack of transparency raised critical questions: How widespread is the practice of altering prices and search results for individual online shoppers? What extent of consumer data is used for such customization? And what percentage of price variation occurs when online retailers tailor their offerings to each consumer?
Unregulated Pricing and Market Manipulation
In response to these concerns, a project was initiated at Northeastern University, involving a study of ten major online retailers (like Walmart and Home Depot) and six travel booking sites (including Expedia and Orbitz). The objective was to determine the prevalence of price discrimination and steering, and identify the user variables triggering these customizations.
The study involved 300 Mechanical Turk users who conducted product searches on these sites. Their results were compared with those from a computer-generated browser that mimicked their actions but did not store cookies.
The research revealed several instances of customization. Sears, for instance, showed price drifts and varying search result sequences for different users. Price discrimination was evident on sites like Home Depot, Sears, Cheaptickets, Orbitz, Priceline, Expedia, and Travelocity, with product prices fluctuating between users. However, the exact causes of such individualized outcomes remained unclear due to the lack of access to extensive consumer data histories.
Further experiments were conducted using fictitious accounts, differing in browser type, platform, login status, and purchase history. These tests unearthed various personalization tactics. For example, Travelocity offered discounts on hotel rooms for smartphone users, while Cheaptickets and Orbitz provided unadvertised discounts to their paying members.
Expedia and Hotels.com employed A/B testing to segment users and gauge their likelihood to book more expensive rooms. Home Depot showed a stark difference in the product experience between desktop and mobile users, with varying numbers of search results and average item prices.
Despite the backlash faced by Amazon, Staples, and Orbitz in earlier incidents, it was surprising to find that such customization practices were still prevalent. The business logic behind these practices remains largely unclear. Interviews with representatives from Orbitz and Expedia corroborated the findings but offered little explanation regarding the design decisions behind their website layouts. Travelocity, however, acknowledged that offering discounts to mobile users was a strategy to encourage app downloads and site visits.
Strategies for Shoppers Seeking Deals
Diverse Browsing Tools
One fundamental strategy for encountering the best online deals is to use a variety of browsing tools. This means alternating between different devices and browsers. For instance, you might check a price on your desktop using Chrome, then compare it with the price shown on Safari on your iPhone. Retailers often track your device type and might offer different prices based on the perceived spending power of users on different platforms. By comparing across these, you can potentially spot and take advantage of price discrepancies.
Leveraging Incognito Mode
Incognito or private browsing modes are useful for minimizing the amount of tracking data websites can collect about you. Since these modes typically don’t save cookies, your browsing history, or form data, websites have less information to use for personalizing prices. By shopping in incognito mode, you might see different, often lower, prices than what’s presented when you browse regularly. This tactic can be especially effective if you frequently visit a website and notice prices creeping up over time.
Comparing Across Platforms
Prices can vary not just between browsers and devices, but also between a store’s website and its mobile application. Some retailers offer app-only deals or different prices when you visit their site from a mobile device. Regularly checking both the desktop and mobile versions of a site, as well as the store’s official app, can help you spot the best deals. This cross-platform comparison takes advantage of the different pricing strategies businesses use for different types of users.
Using Price Comparison Tools
There are many tools and browser extensions designed to help consumers find the best deals. These tools automatically scan multiple retailers for the best price on a product and can alert you to price drops. Some even provide historical price data, so you can see if the current price is genuinely a good deal. Using these tools in conjunction with your own cross-browser and cross-platform checks can provide a more comprehensive view of the best available prices.
Clearing Cookies and Browsing Data
Regularly clearing your cookies and browsing history can reset the personalized pricing strategies that websites apply based on your browsing habits. If a site sees you as a new visitor each time, you might avoid some of the dynamic pricing increases that can occur after repeated visits to a particular product page. This is particularly useful if you’re researching a big purchase over time and want to prevent incremental price increases.
Creating Multiple Accounts
Some online shoppers create multiple accounts with the same retailers to compare the prices and deals offered to new customers versus returning ones. New users sometimes receive better offers as an incentive to make their first purchase. By comparing the prices and deals offered to different accounts, you can determine if it’s worth it to make a purchase as a ‘new’ customer.
Timing Your Purchases
Understanding when to buy is as crucial as knowing how to buy. Prices for many products follow a predictable cycle or are seasonally discounted. For example, electronics are often cheaper during Black Friday sales, while other items might be discounted at the end of a season. Keeping track of these patterns and timing your purchases accordingly can lead to substantial savings.
The overarching goal of this research is to encourage companies to be more transparent about the data they use for customizing search results and pricing. There’s a growing need for businesses to revert to transparent incentivizing methods like sales and coupons, rather than relying on opaque algorithms to subtly manipulate content.