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India Knowledge@Wharton | Getting the price right the first time
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When Apple Inc. dropped the price of its iPhone by a third after only two months on the market, even its most loyal buyers complained bitterly, forcing chief executive Steve Jobs to apologize and offer a partial rebate.
According to Wharton faculty and analysts, the iPhone episode reveals the perils of pricing in a marketplace where constant innovation, fierce competition and globalization are changing the rules of the game. “The product life cycle is short and the market is moving quickly," says Wharton marketing professor John Zhang. “You don’t have a lot of time to learn from your mistakes. You have to price the product right the first time."
There is new interest in pricing as management looks for ways to increase revenues after years of focusing on downsizing and cost-cutting. Firms are just beginning to apply to pricing some of the data collection and management tools they have been using in supply chain management and other parts of their businesses. “Pricing is the last bastion of gut feel," says Greg Cudahy, managing partner of Accenture’s pricing and profit optimization practice.
According to Cudahy, companies that take a strategic approach to pricing throughout their business and monitor their success with hard numbers can raise revenue by 1-8%. New York drugstore chain Duane Reade, Inc., for example, used pricing software to examine sales data, which showed that parents of newborns are not as price-sensitive as parents of toddlers. In response, the firm cut prices on toddler diapers to remain competitive with other stores and raised prices on infant diapers, increasing baby product revenues by 27%.
Apple’s price cut is an example of a strategy known as “temporal price discrimination", says Wharton marketing professor Jagmohan Raju. Companies using this strategy charge people different prices depending on the buyer’s desire or ability to pay. As a result, companies reap wide profit margins from those willing to pay a premium price. In addition, they benefit from high volume, even at a lower per unit price, by building a wider customer base for the product, later.
Consumers have come to accept this form of pricing in the airline industry, Raju notes. Technology marketers, however, often must set pricing below profitable levels to build an installed user base that will lead to profitable levels of sales volume later. “If I’m the only one with a video phone, whom am I going to call?" Raju asks.
Is ?urban development driving rural growth in?India?
It is widely believed that economic growth in India has not only been skewed towards urban areas but has also been gained at the expense of the countryside. Often overlooked, however, is the fact that the rural economy is no longer limited to agriculture. During the past two decades, rural India has diversified significantly into non-farm activities—and this has brought India’s cities much closer to their hinterlands than people might imagine.
According to Roopa Purushothaman, chief economist for Future Capital Research—a division of fast-growing Indian retailer Future Group—despite the “near devotional status" of the rural-urban divide, fundamental misconceptions exist about how these two economies in India interact with one another. Purushothaman presented research on the topic at the recent Global Supply Chain Summit 2007, organized by the Indian School of Business in Hyderabad.
“If we look at the data, the story in rural India is a lot more dynamic than it gets credit for," she said. “A 10% increase in urban expenditure is associated with a 4.8% increase in rural non-farm employment…. As supply chains strengthen across the country, growing urban demand could provide a significant boost to the rural economy." The categories of expenditure the researchers studied include food, housing, health, transport, education, clothing and footwear, consumer durables, automobiles, entertainment, household appliances, toiletries and cosmetics.
Using an econometric approach spanning the past 26 years, the study shows that a Rs100 increase in urban consumption expenditure leads to an increase of Rs39 in rural household incomes. The channel through which this takes place is increased employment in the rural non-farm sector.
The impact of online ‘recommenders’
Online retailers may be shooting themselves in the tail—the long tail, that is, according to Kartik Hosanagar, Wharton professor of operations and information management, and Dan Fleder, a Wharton doctoral candidate, in new research on the “recommenders" that many of these retailers use on their websites. Recommenders— perhaps the best known is Amazon.com Inc.’s—tend to drive consumers to concentrate their purchases among popular items rather than allow them to explore and buy whatever piques their curiosity, the two scholars suggest in a working paper.
The term “long tail", taken from the graphical depiction of a statistical distribution, alludes to the fact that online shoppers have shown themselves to be far more willing to purchase niche products—like documentary movies and old-time acoustic blues recordings—than marketers ever imagined.
Outfits like Amazon and Apple’s iTunes figured this out because, with dramatically lower inventory costs than their bricks-and-mortar competitors, they could afford to carry huge lists of titles. Individually, many of those books or recordings didn’t sell often, but as a group, they outsold the hits on which media businesses had previously depended.
Online retailers, like their old economy counterparts, seek out ways to prompt consumers to buy more, and that’s where the recommenders that Hosanagar and Fleder studied come in. Amazon, for example, suggests additional books or CDs based on the ones that customers put in their shopping cart—the online equivalent of the record store clerk who tells someone buying an album that he also might like one by a similar musician. “Automated recommendations can be even more influential than human ones," Hosanagar says.
But they are not without shortcomings, the two scholars point out. “Because common recommenders recommend products based on sales and (consumer) ratings, they cannot recommend products with limited historical data, even if they would be rated favourably," they write. “This can create rich-get-richer effects for popular products and vice versa for unpopular ones, which results in less diversity."
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