In 2005, Zilliant, an Austin, Texas (US)-based provider of data-driven, strategic pricing applications, and the Institute for International Research (IIR) released the results of a survey that showed strategic pricing was gaining in priority among some US businesses. The PriceX Conference poll surveyed nearly seventy businesspeople responsible for making pricing decisions at their respective companies.
Despite this finding, adoption of strategic, science-based pricing and associated technologies is relatively minor in industries other than airlines, hotels, and retailers. These industries practice a form of science-based pricing called yield management. Yield management, also known as revenue management, was invented three decades ago; its goal is to fill as many seats and rooms as possible while charging the highest prices the market can bear. Since then, these industries have adopted sophisticated software programs to predict demand and to set prices, resulting in as many different price points per flight as passengers, or per room as guests.
Armed with a wealth of customer data, programmers then developed formulas that could manipulate prices up or down depending on existing sales, the likelihood of last-minute purchases, and other variables ranging from weather forecasts to competitors' prices. The underlying logic was that airplane seats and hotel rooms are worthless if unused, and selling them even at a loss meant gaining some revenue.
Given that "computer power" is much more affordable these days, user enterprises can harness statistical science to analyze transactions and other customer data to more accurately explore the cause-and-effect relationship between prices and purchase decisions. The idea here is to be able to discern customers' "willingness to pay," and set "take-it-or-leave it" prices where companies will make the maximum revenue.
Using mathematical formulas and massive databases of sales records, companies can forecast their sales plans, and test pricing and demand elasticity under various discount or package scenarios before trying them in the market. Layering in data from other customer interactions can help companies set prices, schedule markdowns, and identify top performing buyers with more sophistication than ever before. Companies can also set prices based on the value consumers derive from specific products, or even plan different discounting and pricing strategies based on anticipated customer behavior.
Again, as indicated earlier on (see Know Thy Market Segment's Price Response), business-to-business (B2B) pricing environments are different in that pricing is opaque and largely discretionary. Now that technologies have been brought to market that address these dynamics, B2B companies are getting on board too.
Nevertheless, according to Zilliant, although pricing is generally accepted as a core business practice, the process most B2B companies go through in determining a price is often archaic and arbitrary. Some businesses simply take the cost of a product and add margin on top of that price, while others simply match or better their competitor's offering. Another common practice is the so-called "out of thin air" (OTA) or "sucking (knowledge) out of my thumb" method; in other words—guessing. According to the above mentioned PriceX survey, 56 percent of companies polled have some sort of pricing strategy in place, while only 44 percent have a dedicated pricing department or an individual with pricing responsibility.
Other key trends uncovered in the survey included that 35 percent of companies consider pricing to be a top priority, yet 61 percent of companies use Excel spreadsheets to determine price (rather than specialized pricing applications from a vendor). Data cleansing was cited as the main obstacle to improving pricing policies, followed by ineffective customer segmentation.
In a somewhat older survey (taken a few years ago) by the Professional Pricing Society of its members, 30 percent of respondents said they priced new products by mirroring their nearest competitors' prices, and another 22 percent set prices for new products based on recovery of costs and to tack on a profit. Only 18 percent revealed that they performed some sort of customer research to determine the value of the product or service to potential customers. And when it comes to the Internet pricing, 40 percent said they simply mimic the pricing of their off-line sales channels, and 28 percent responded that they do not have an Internet strategy at all.
In other words, most businesses lack a detailed understanding of their market segments' responses to prices and deal terms. They rely solely on undifferentiated discount policies and sales team discretion to structure all types of deals, from quotes to orders, agreements to contracts. As a result, some deals go through with overly generous terms, while others are lost due to gross pricing misalignment.
These harmful practices continue to take place despite some pricing pundits "shouting blue murder" (protesting) about the ingrained, casual thinking that pervades the global economy regarding pricing. Both consumers and businesspeople erroneously assume that price has everything to do with cost. Yet, while any company has to know the cost of a product, it is only so that it can understand the profitability implications of the price, not for the purpose of setting the price. The value (benefit per unit price) is in the eye of the customer and depends on the circumstances surrounding the deal. Another faulty practice is the assumption that when a company is in a competitive situation and prices drop, the company must match the price-drop. Also, executives who are devoted to using data and analytics in all kinds of other functional areas still think it is entirely acceptable to set prices based on "history," "experience," or "instinct."
Despite this finding, adoption of strategic, science-based pricing and associated technologies is relatively minor in industries other than airlines, hotels, and retailers. These industries practice a form of science-based pricing called yield management. Yield management, also known as revenue management, was invented three decades ago; its goal is to fill as many seats and rooms as possible while charging the highest prices the market can bear. Since then, these industries have adopted sophisticated software programs to predict demand and to set prices, resulting in as many different price points per flight as passengers, or per room as guests.
Armed with a wealth of customer data, programmers then developed formulas that could manipulate prices up or down depending on existing sales, the likelihood of last-minute purchases, and other variables ranging from weather forecasts to competitors' prices. The underlying logic was that airplane seats and hotel rooms are worthless if unused, and selling them even at a loss meant gaining some revenue.
Given that "computer power" is much more affordable these days, user enterprises can harness statistical science to analyze transactions and other customer data to more accurately explore the cause-and-effect relationship between prices and purchase decisions. The idea here is to be able to discern customers' "willingness to pay," and set "take-it-or-leave it" prices where companies will make the maximum revenue.
Using mathematical formulas and massive databases of sales records, companies can forecast their sales plans, and test pricing and demand elasticity under various discount or package scenarios before trying them in the market. Layering in data from other customer interactions can help companies set prices, schedule markdowns, and identify top performing buyers with more sophistication than ever before. Companies can also set prices based on the value consumers derive from specific products, or even plan different discounting and pricing strategies based on anticipated customer behavior.
Again, as indicated earlier on (see Know Thy Market Segment's Price Response), business-to-business (B2B) pricing environments are different in that pricing is opaque and largely discretionary. Now that technologies have been brought to market that address these dynamics, B2B companies are getting on board too.
Nevertheless, according to Zilliant, although pricing is generally accepted as a core business practice, the process most B2B companies go through in determining a price is often archaic and arbitrary. Some businesses simply take the cost of a product and add margin on top of that price, while others simply match or better their competitor's offering. Another common practice is the so-called "out of thin air" (OTA) or "sucking (knowledge) out of my thumb" method; in other words—guessing. According to the above mentioned PriceX survey, 56 percent of companies polled have some sort of pricing strategy in place, while only 44 percent have a dedicated pricing department or an individual with pricing responsibility.
Other key trends uncovered in the survey included that 35 percent of companies consider pricing to be a top priority, yet 61 percent of companies use Excel spreadsheets to determine price (rather than specialized pricing applications from a vendor). Data cleansing was cited as the main obstacle to improving pricing policies, followed by ineffective customer segmentation.
In a somewhat older survey (taken a few years ago) by the Professional Pricing Society of its members, 30 percent of respondents said they priced new products by mirroring their nearest competitors' prices, and another 22 percent set prices for new products based on recovery of costs and to tack on a profit. Only 18 percent revealed that they performed some sort of customer research to determine the value of the product or service to potential customers. And when it comes to the Internet pricing, 40 percent said they simply mimic the pricing of their off-line sales channels, and 28 percent responded that they do not have an Internet strategy at all.
In other words, most businesses lack a detailed understanding of their market segments' responses to prices and deal terms. They rely solely on undifferentiated discount policies and sales team discretion to structure all types of deals, from quotes to orders, agreements to contracts. As a result, some deals go through with overly generous terms, while others are lost due to gross pricing misalignment.
These harmful practices continue to take place despite some pricing pundits "shouting blue murder" (protesting) about the ingrained, casual thinking that pervades the global economy regarding pricing. Both consumers and businesspeople erroneously assume that price has everything to do with cost. Yet, while any company has to know the cost of a product, it is only so that it can understand the profitability implications of the price, not for the purpose of setting the price. The value (benefit per unit price) is in the eye of the customer and depends on the circumstances surrounding the deal. Another faulty practice is the assumption that when a company is in a competitive situation and prices drop, the company must match the price-drop. Also, executives who are devoted to using data and analytics in all kinds of other functional areas still think it is entirely acceptable to set prices based on "history," "experience," or "instinct."
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