EXHIBIT 4.1 The Incremental Contribution from Segmented Price Structure
Tactics for Pricing Differently Across Customer Segments
Discovering in every man that which distinguishes him from others is to know him.
Hermann Hesse1
After developing products or services that create value and making customers aware of it, a marketer must determine how most profitably to capture a share of that value in both volume and margin. The challenge is that individual customers will value the differentiating features of products and services very differently due to differences in their abilities to pay, their subjective preferences, their end-use applications, and their prior experience with the product category. Moreover, the timing of customers’ needs, the speed of their payments, and the level of service and support they require can drive significant differences in the cost to serve them. When a company tries to serve all customers with one price, or even with a standard markup over cost, it is invariably forced to make large trade-offs between volume and margin, with gains in volume requiring either lower prices or higher costs. Fortunately, a well-designed price structure can substantially mitigate that trade-off.
Except for highly competitive commodities, charging the same price per unit is rarely the best way to generate revenues. A far more profitable strategy requires creating a structure of prices that aligns with the differences in economic value and cost to serve across customer segments. The goal is to capture more revenue from sales where value or cost to serve is higher, while accepting lower revenue to earn additional profits from incremental volume to customers for whom value is less or the cost to serve them is low.
To illustrate the huge benefits of a well-defined segmented price structure, suppose that a supplier faced five different segments, all willing to pay a different price to get the benefits they sought from a product (see Exhibit 4-1). Segment A with sales potential of 50,000 units is willing to pay $20 for the firm’s product. Segment B with sales potential of 150,000 units is willing to pay $15, and so on. What price should the firm set? The right answer in principle is whatever price maximizes profit contribution. If you calculate
EXHIBIT 4.1 The Incremental Contribution from Segmented Price Structure
the profit contribution at each of the five prices assuming a variable cost of $5 per unit, the single price that produces the maximum contribution ($2,750) is $10.
However, a single-price strategy clearly leaves excess money on the table for buyers who are willing to pay more: Those willing to pay $20 and $15. At the price of $10, those high-end buyers are enjoying a lot of what economists call “consumer surplus.” The firm would be better off if it could capture some of this surplus by charging them higher prices. The second problem is that the supplier leaves nearly half of the market unsatisfied, even though it could serve those customers profitably at prices above the $5 per unit variable cost.
For industries with high fixed costs, serving those additional customers is often very profitable and, when they constitute large amounts of volume, can be essential for a company’s survival. Railroads could not maintain, let alone expand, their costly infrastructures without a segmented price structure. Railroad tariffs are designed to reflect the differences in the value of the goods hauled. Coal and unprocessed grains are carried at a much lower cost per carload than are manufactured goods, resulting in a much lower contribution margin per carload. Still, the large volumes of coal and grain transported enables that low-priced business to make a substantial contribution to a railroad’s high fixed-cost structure. If railroads were required to charge all shippers the tariff for manufactured goods, they would likely lose shippers whose commodities would no longer be competitive on a delivered-cost basis and so would lose that profit contribution. On the other hand, if railroads had to charge all shippers the tariff currently charged for a carload of unprocessed grain, their systems would reach capacity before they generated enough contribution to cover their fixed costs and become profitable. Freight railroads survive and prosper by leveraging their capacity to serve multiple market segments at value-based prices for each segment.
Companies that have a large market share but refuse to serve the lower-value segments of a market take a risk in doing so. In his book, The Innovator’s Dilemma, Clayton Christensen cites numerous examples of companies that failed to meet demand from a potentially large, but lower-value segment in a market that they otherwise dominated. Invariably, someone eventually addressed that need and used it as a base to partially support the fixed cost investments necessary to compete for business in higher margin segments.2 For example, Xerox owned the high end of the copier market. It lost that dominant position only after companies that had entered at the bottom of the market developed service networks of sufficient size to support sales of large, higher-priced copiers, such as those bought by copy centers that required quick service to minimize downtime.
How many segments with different price points should a supplier serve? To return to our illustration, Exhibit 4-1 shows that if the firm were able to set two price points serving two general price segments—high-end buyers willing to pay $15 or more, and mid-level buyers willing to pay $8 or more—it could increase profit contribution by 40 percent. But if the supplier could charge separate prices to each of the five market segments, it could increase profit contribution by 80 percent relative to the single price strategy! In principle, more segmentation is always better. In practice, the extent of price segmentation is limited by the ability of the seller to manage the complexity of managing across multiple segments and to enforce the segmentation at an acceptable cost.
Segmentation is much more challenging for pricing than for other aspects of marketing because customers to whom you intend to charge a higher price have a strong incentive to undermine it. They will not freely identify themselves as members of a relatively price-insensitive segment simply to help the seller charge them more, but will try to disguise themselves as customers who should qualify for a lower price. Channel intermediaries too can undermine a segmented pricing strategy by buying the product intended for delivery to customers entitled to a lower price but then actually diverting it for resale to customers targeted to receive a higher price. Commonly referred to as gray-market sales, they create a huge challenge for companies serving international markets because distributors in countries where prices are lower cross ship products to ones where prices are higher. A manufacturer then loses higher-priced sales in the high-value country due to gray-market competition from its own products that have been parallel imported from lower-priced countries. And, to add to the insult, sales are lost even in the low-price country due to shortages that develop when products are diverted away from the low-price market.
Gray-market diversions by channel intermediaries can undermine not only different pricing by region but also by application. There are examples where a specific drug can have two different uses with correspondingly two different levels of clinical value delivered. For example, a drug used to treat a high-risk disease like cancer might also be useful for treating eye irritation. The challenge for a pharmaceutical company is to develop a strategy that allows it to charge differently depending on how the drug is being used. One common tactic is to introduce two versions of the drug, each with a unique brand name and dosing guidelines, even if the active ingredient is the same. The challenge, of course, is that some enterprising physicians might purchase the cheaper version of the drug, adjust the dosing to achieve the same result in the higher clinical-value setting, and pocket the difference in cost of the drugs used in the procedure.
In markets where sales are made directly, without a channel intermediary, it is easier to charge different prices to different customers. Recognizing the huge potential for profit improvement from aligning price with value, many companies adopt flexible pricing policies, empowering sales reps and sales management to discount prices for customers whom they perceive to be more price sensitive, while charging higher prices when the customer is unaware of better alternatives or perceives that what differentiates the offer is worth a higher price.
Flexible pricing can work in markets where customers buy a complex product or service very infrequently, such as when they are purchasing funeral services for a recently departed relative or a business hires a law firm to defend it against a novel civil suit. Customers making infrequent purchases, especially of products that are difficult to compare prior to purchase, are often uninformed about the differences in price and features among competitors and about the value that those differences might create for them. They must rely on the supplier for advice about what to buy, which leads them to reveal information to the supplier that enables the supplier to judge their relative price sensitivity with some accuracy.
Staying flexible in negotiating customer-specific prices in this way can improve both revenue and profitability when selling to uninformed buyers. It has proven horribly counterproductive, however, for setting prices for customers with whom a seller has, or hopes to establish, an ongoing commercial relationship. The problem arises because buyers, especially those who are professional purchasing agents, learn over time how to manipulate a seller’s flexible pricing policy and will do so aggressively to gain competitive advantage, or to avoid being put at a disadvantage. Moreover, sales reps learn that it is easier to make a case to their own management for why some customer needs a bigger discount than it is to justify prices to buyers where access to decision-makers is more limited and the real purchasing process less well understood. Soon, a firm’s negotiated prices become aligned with differences among buyers’ ability to negotiate and manipulate the seller’s expectations rather than with differences in value received and cost to serve. Flexible pricing in this case undermines rather than reinforces profitability.
To prevent losing control of pricing to entrepreneurial channel intermediaries or to customers who are the smart negotiators, a company must understand how drivers of value and cost to serve differ across customers and develop price structures that align price levels proactively to reflect those differences. In the next chapter, we will describe how to define price policies proactively for managing price exceptions without undermining the integrity of a price structure. The balance of this chapter is devoted to explaining how to create a segmented price structure that distinguishes between applications or customer types that should be priced differently in order to optimize profitability. There are three mechanisms that one can use, individually, but more often in combination, to form a segmented price structure: Offer configurations, price metrics, and price fences.
When differences in the value of an offer across segments is caused by differences in the features and services that customers need or value, a seller can segment the market by configuring different offers consisting of different bundles of features and services for different segments. Using offer configurations to implement segmented pricing requires minimal enforcement of price differences because customers will self-select the offers that determine their prices. An airline’s segmented price structure (see Exhibit 4-2) enables passengers to choose freely whether they want to pay only the most discounted price, want to pay a little more for the ability to check a bag or board early enough to get overhead space, or need the ability to cancel or change flights. The price structure also includes separate à la carte charges for priority seats that are closer to the front of the plane (enabling faster exit) and have more leg room. Additional categories (Refundable and Business/First) afford travelers more services such as flexibility and privileged bag delivery.
To create an effective bundled offer structure, one must first determine which features and services the firm should include in bundles, rather than pricing each element à la carte and leaving customers to customize their own offers. There are multiple arguments against pricing all individual features and services separately. A single price for a bundle of features and services reduces transactions costs for both customers and sellers. The costs to make and deliver most products and services increase with the number of variations allowed, although technology is reducing the cost of mass customization. Lastly, research shows convincingly that people are less sensitive to the cost of value-added features and services when bundled as a single expenditure.3 Still, something that is particularly high-cost or difficult to provide in greater quantities (e.g., the best seat locations) should be charged separately from any bundled price to ensure that customers who most value that feature can be confident that it will be available to them at some price while simultaneously maximizing the seller’s income from that feature.
EXHIBIT 4-2 Segmented Price Structure in Airlines
Creating bundles is simple when customers targeted for higher prices value some feature, like the ability to make changes in an airline ticket, which other customers do not. By including that feature only in the higher-priced bundle, high-value customers (e.g., business travelers with schedules subject to change) choose to pay the higher fare. Sometimes value-adds can be used, to attract the lower-value customer. When they have capacity, airlines make seats available to tour operators at prices lower than their lowest published fares with the proviso that the airline seat is sold only as part of a bundle including other items such as tickets to tourist attractions and nights in tourist hotels. That bundle insures that those tickets will not end up being sold to non-tourists who otherwise could have been sold a seat at a higher fare.
Cable TV operators create different bundles focused on families, sports enthusiasts, and movie buffs that simply include types of programming that they value most. The challenge occurs when different customers value the same features and services enough to make sales to both profitable, but they value them differently. Segmenting by bundled offer configurations can still be more profitable than pricing elements separately if different segments of customers simply rank the importance of features differently that they would like to have in a bundled offering. The following example illustrates this principle.
Sports channels create an ideal opportunity for bundling to maximize profitability. Some sports enthusiasts highly value “fight sports” like boxing and mixed martial arts. They may also value access to “team sports” like baseball and soccer, but to a lesser extent than team sport enthusiasts do. Team sport enthusiasts have exactly the opposite ranking. They will subscribe to a channel or a sports package of channels primarily for the team sports, but would also value the occasional “fight sport”—but would not value a subscription as much as “fight sport” enthusiasts do. The challenge is to maximize income from these two segments combined, since, with most costs fixed, there is a large return from maximizing total revenue by getting them both to watch both types of sporting events.
Now let’s make the pricing challenge a bit more complicated. Let’s say that there are many more team-sport broadcasts than fight-sport broadcasts, so that it is possible to charge more to both segments for team-sport access. Based upon past research and experimentation, assume that those pricing cable TV options believe that the subscription prices in Exhibit 4-3 represent roughly the acceptable prices that would optimize revenue from each segment for access to each type of event. Now, how could a pricing manager maximize revenue? (To simplify the illustration, we assume that the payment to the teams for broadcast rights is a percentage of revenue rather than a variable cost per subscriber so that everyone is aligned with revenue maximization as the goal.)
The maximum viable price per event would be $18/month for a fight-sport package and $33/month for a team-sport package. That strategy would, however, exclude a lot of potential viewers and their revenue. An alternative that would not restrict the market would be to charge $6/month for a fight sports subscription and $25/month for a team sports subscription—for a total of $31/month. That option would slightly increase total revenue and overall customer satisfaction. But there is a still better strategy. Can you see it?
Instead of offering a price structure with a separate price for fight sports and team sports, observe what happens if the seller offers a combined all-sports bundle? They could then charge $39/month and still get both segments of sports enthusiasts to subscribe earning $8/month more revenue per subscriber than if they set prices for the individual elements low enough to generate the same volume of subscriptions. So, should cable companies force customers to buy such bundles. Some do, but the lack of choice annoys their customers. A better option is to offer the all-sports bundle at $39/month and the option to buy fight sports for $18/month and team sports for $33/month. Not only does that open the market for what may be some customers who only value one or the other, but it establishes in the customer’s mind a reference value for the package elements separately. Even if few people buy the separate options, the company can advertise that buyers of the all-sport package can get both streams of shows that would individually sell for $51/month for the low discount price of only $39!
EXHIBIT 4-3 Revenue Optimizing Subscription Pricing by Segment
In practice, there are often more than two segments, segments of very different sizes, and more than two types of products to bundle. Maximizing profit contribution requires building a spreadsheet or employing a complex optimization model to evaluate bundling alternatives.4 The principle, however, is the same for bundling features in auto packages, items to include in the four-course dinner special, items in a vacation package, or spots for advertising at different times embedded in different shows on a television network. The key is to bundle elements that are valued differently by different segments, so long as the incremental revenue earned from inducing more customers to buy an element of the bundle exceeds the incremental cost to supply it. In principle, one could maximize revenue from three segments with one bundle containing three different elements, each valued most highly by one of the segments.
Bundling can also facilitate segmented pricing, thus increasing profitability, when different customer segments have different price sensitivity for a core product or service (for example, lodging at a popular vacation spot). When it is possible to find features or services that one segment values highly and another does not (for example, access to a pro-quality golf course or a kids’ club where children can be left safely and entertained), it is easy to design segment-specific pricing by bundling. The golfer evaluates the sum of the room cost plus the golf cost in figuring the cost of the vacation. If the golfer values lodging at this location by $100 per night more than the family, he will pay up to $100 more per day for greens fees than he would at an equal quality course in a less desirable location. (Assuming, of course, that no cheaper but equal quality course is available near this location.) Since the family did not come to play golf, they are unaffected by high greens fees.
As rewarding, but often overlooked, is the potential for bundling value-added features and services to attract customer segments that require a lower price to win their patronage. Although they pay a lower price, their purchase volume may, nevertheless, be profitable, especially during off-peak periods or economic downturns when excess capacity would otherwise remain unused. Simply cutting prices to win their business would, however, make it difficult to continue charging other customer segments a higher price and could cheapen the image of the brand. Bundling a “free” or low-cost service or feature specifically preferred by this segment, however, can improve the value proposition for that segment without having to cut the offer price explicitly.
For example, the resort hotel could charge a higher price for the room but bundle the kids’ club free for one child with each paying adult, admit children free at the breakfast buffet, or provide a shuttle and discount tickets to nearby family-friendly entertainment. Since the golfers would find none of this worthwhile, the attraction to the buyer and the added cost to the seller are limited to the targeted segment. Similar bundles exist in business-to-business markets. Companies that cannot discount prices to small businesses without facing demands for lower prices from larger customers may offer their price-sensitive small business customers low-cost financing, free software for better inventory management, or anything else that they would value but that large company customers would not want.
There is an alternative to adding a feature that raises the value of the discounted offer to only the low-price segment. That is to add a feature to the lower cost offer that kills value for the higher-priced segment without affecting the value to the discount segment. Dick Harmer, a former colleague of ours, gave this practice the memorable name “selective uglification.” Chemical companies often do not have separate lines for making “food grade” and cheaper “industrial grade” chemicals. They simply add something to the industrial grade that makes it no longer acceptable for food manufacturers and consumers. A Saturday night stay requirement for a discount airline ticket is another example, since it has no effect on the pleasure traveler who wants the trip to include the weekend anyway, but precludes most business travelers.
While bundling can be a profit-enhancing strategy for segmentation, it often has the opposite effect when variable cost services are bundled simply to differentiate an offering. For example, a business-to-business equipment company might try to convince customers to pay more for its machines by bundling the promise of faster warranty repair service and free delivery anywhere, and an airline might hope to charge more for its tickets because they include free baggage handling and agent assistance with reservations. Such price-offer structures often undermine rather than enhance profits and can be fatal to companies that cling to them in competitive markets for two reasons.
The first problem is that the cost to provide bundled service can be widely different across customers. Customers who have a high need for the bundled services gravitate to the companies that offer them for free. As companies gain share among these high cost-to-serve users, the average cost to deliver the bundle increases. If they try to add the increasing average service cost to the price, they begin losing sales to customers who are not high-service users. If they avoid raising the price of the bundle to reflect the increasing cost of the service, the increasing cost erodes their margins. The second problem is that customers often fail to recognize the value of differentiating services unless they have a price attached to them.5 Even when included in a bundle, the price assigned to the unbundled services draws attention to their value, making the bundled price appear to be a better deal relative to the sum of the component parts.
Unless the cost to deliver a service is trivial relative to the overall value of the offer, bundling optional services for free will undermine profitability. Unbundling them as many airlines have done for baggage handling or for using an agent to make reservations, is in fact strategically essential when facing intense competition. This can be accomplished either by charging per-use fees for the services and/or by including them only in higher-priced bundles of services, as airlines commonly due if one pays for a full-fare airline ticket rather than a discounted one. Companies can unbundle the price structure without upsetting customers who have come to expect a costly service as part of the package by including it in the price but offering rebates for forgoing its use. For example, one company whose customers had become accustomed to placing orders on short notice for free raised its prices but, at the same time, offered a discount of more than the price increase for orders that could be shipped with a delay of up to seven days. That enabled it to avoid disrupting relationships with customers who valued its ability to receive delivery quickly by more than the price premium, while enabling it to match competitive prices when necessary with a slower, lower-cost service option.
Not all differences in value across segments reflect differences in the features or services desired. Value received is sometimes not even related to differences in the quantity of the product consumed necessitating a price structure that involves earning revenues unrelated to the quantity of the product or service provided. For example, in the field of health care, both government and private payers are resisting paying for health care on a fee-for-service basis since delivery of more days in the hospital or more tests is often indicative of poor treatment choices, not better patient care. Both payers and health care providers, like Kaiser Permanente6 and Mayo Clinic,7 that have a proven ability to deliver care more cost-effectively than their peers, have benefited from adopting more value-based price metrics: Either a “capitation price” that covers all services required by a patient during a year, or a price per illness or procedure that covers all services required to treat a condition to a satisfactory outcome. By adopting such metrics, health care providers that can provide better care in less time or with less resources expended can avoid the difficult problem of having to convince payers to pay more per service to reflect the value of better treatment. It is much easier to make the case that they can get patients “back on their feet” for no more than the cost per patient of less effective providers.
The example just described involved changing from a feature-based to a benefit-based price metric. Price metrics are the units to which the price is applied. They define the terms of exchange—what exactly the buyer will receive per unit of price paid. There are often a range of possible options. For example, a health club could charge per hour of use, per visit, per an annual membership for unlimited access, or per some measure of benefit (inches lost at the waist or gained at the chest). The club might also vary those prices by time of day (low for a midday membership, higher for peak-time membership) or by season of the year to reflect differences in the opportunity cost of capacity. Finally, it might have a multi-part metric: An annual membership with an additional hourly charge for use of the tennis courts. These reflect the common categories of price metrics: Per unit, per use, per time spent consuming, per person who consumes, per amount of benefit received.
The problem with most price metrics is that they are adopted by default or tradition. For example, initially, software companies charged a price per copy installed on one server machine. In most cases, that led to a poor alignment with value. A few creative vendors recognized that when more users accessed the software, the buyer was getting more value. Consequently, they changed the price metric from a price “per server” to a price “per seat,” resulting in customers paying more when they had more users accessing the software. When this per-seat metric proved much more profitable for the computer-aided design and financial analysis companies that adopted it, other software companies copied it. For many of their applications, however, the number of users still aligned poorly with value, leaving many customers underpriced while pricing others out of the market. The most thoughtful among them created still better price metrics. Leaders in manufacturing software replaced “price per seat” with “price per production unit.” Storage management software suppliers replaced “price per server” with a “price per gigabit of data moved.” Each time a company discovers a better metric than its competitors, it gains margin from existing customers, incremental revenue from customers formerly priced out of its markets, or both.
EXHIBIT 4-4 Criteria for Evaluating Pricing Metrics
There are five criteria for determining the most profitable price metrics for an offering (Exhibit 4-4). The first criterion for a good price metric is that it tracks with differences in value across segments. While offer design facilitates pricing differently based upon what people chose to buy, a price metric not based upon units of purchase can facilitate different pricing for the same offer. For example, it often makes more sense to price drug per day of therapy rather than per milligram of the drug—as Eli Lilly did when it launched the antidepressant Prozac. Someone who requires only a 10-milligram dose gets no less value than someone who requires a 30-milligram dose to control the disease. Consequently, the company charged the same amount per pill regardless of the quantity of active ingredient it contained. Second, a good metric tracks with differences in cost to serve across customer segments. When customers’ behavior influences the incremental cost to serve them and those costs are significant, a profit-maximizing price metric needs to reflect that as well. The cost to deliver a service is significant if it exceeds the cost of measuring, monitoring, and charging for differences in its usage. Marketers are often reluctant to charge for services, even when costs are significant, because they fear that they will become uncompetitive relative to others who do not charge for them. In fact, the opposite is the case.
Giving services for free attracts customers who are relatively higher users of them. Customers who want to minimize their inventories will gravitate to suppliers who offer free rush orders. Customers with a lot of employee turnover resulting in poor equipment maintenance, will gravitate to equipment suppliers who offer unlimited and quick on-site service. Customers who require only minimal amounts of service will, in similar fashion, gravitate to competitors offering little or no service but lower prices. As a result, marketers often find that they have differentiated their companies into lower profitability by improving their service offerings because they lack an appropriate metric to capture the value and discourage excessive use of services.
By adding charges for services, at least for those customers who are excessively costly to serve, companies are able to keep their core product prices competitive and avoid attracting a mix of customers who are costly to serve. As their markets have become more competitive, software suppliers added charges for formerly free online telephone support. Banks have added charges for small account holders to use a teller, or to access a teller machine more than some authorized amount. United Parcel Service has a $3.80 charge for delivery to a residential address and a $13.40 charge for shipments with a missing UPS account number or that require an address correction. These charges reflect the added cost of service for such packages, and the tendency for customers to cause those costs when they don’t have to pay for them. Suppliers with separate service charges can price more competitively for the core business (the software, the checking account, the package delivery) to win the customers who are lower cost to serve, while still attracting higher cost customers if they are willing to pay for the higher service levels that they demand. In fact, companies with unbundled service can offer better service because they have a financial incentive to do so.
A third criterion for a good metric is that it is easy to implement without any ambiguity about what charge the customer has incurred. Profit-sharing or performance-based pricing are theoretically ideal ways to achieve the first two criteria for a good metric—tracking with value and cost. But in practice, these methods often end in rancorous debate about how profit or performance should be measured. At minimum, it is important to have absolute clarity in advance about what the metric is and who will measure it. That generally means that the metric must be objectively measured or verified.
We once helped to create a value-based metric at a company whose lubricant enabled manufacturers to cut through difficult materials more quickly with less wear on their tools. The company’s product was an easy sell at launch when potential customers were operating at maximum capacity. Cutting materials faster increased capacity at this stage in the production process enabling many customers to increase revenues without additional capital cost. But when a recession hit, the value associated with increased capacity fell to zero. The value created by the company’s product was reduced to the savings in labor costs and machine wear.
In theory, the price could be adjusted to reflect the customer’s capacity utilization. However, whenever price depends upon the customer voluntarily reporting information that will lead to a higher price, the potential for conflicts and misinformation is almost always too high. Fortunately we found a published industrial sales index that seemed to track well with the customers’ capacity utilization. The company continued to charge a price per pound for its product, but in return for lower pricing during the recession, the customers accepted automatic price adjustments monthly based upon changes in the level of an industry sales index.
The fourth criterion for evaluating a price metric is how the metric makes your pricing appear in comparison with competitors’ pricing and the impact of that on the perceived attractiveness of your offer. A new, hosted voice-recognition software that enabled a call center to process more callers without as much need for human intervention promised to create huge differential economic value for purchasers. Unfortunately, the traditional metric for pricing and evaluating hosted call center software was a price per minute of use. Since voice-recognition software processes callers faster, minutes using traditional call center software were not comparable to minutes using the voice-recognition software. A value-based price using that per-minute metric would need to be at least 72 percent higher than the price per minute for traditional software—which was inviting resistance from potential purchasers.
To overcome that, the company adopted a new metric: “Cost per call completed.” That metric naturally required conversion of the competitors’ cost-per-minute metric into a cost-per-call metric. While the new software was still more expensive, its percent price premium was much smaller (5 percent) when framed in terms of cost per call than in terms of a cost per minute (see Exhibit 4-5). Moreover, the differentiation value of the avoided operator intervention was much more dramatic when framed in terms of cost-per-call rather than cost-per-minute basis. The total cost per call completed was 11 percent less with the new software, despite being higher on a per-minute basis. While the favorable economics of the new software was exactly the same using either metric, the per-call basis of comparison made the sales effort a lot easier.
EXHIBIT 4-5 Hosted Call Center Software
The fifth criterion for evaluating a price metric is how the metric aligns with how buyers experience the value in use of the product or service. The better the alignment—how a price metric fits the timing and magnitude of the customers’ expenditure—the more attractive the offer. At a time when Blockbuster video stores dominated the market for movie rentals and Netflix was a struggling competitor, Netflix changed the metric in a way that made it much more competitive. Before most people had the capability to stream films online, movie renters liked the ability to get a movie on DVD immediately from Blockbuster rather than having to wait to get it by mail from Netflix. But movie renters disliked the Blockbuster price metric, a daily charge commonly around $3.95, since the value was related to watching the movie once, not to how many days the DVD disk sat around before it was returned. When Netflix changed its metric to a monthly membership fee based on the number of films out at a time ($8.99 per month for one DVD at a time, $13.99 per month for two, and so forth), Netflix eliminated the inconvenience of having to acquire the movie shortly before watching it and return it shortly thereafter, or to pay what felt like a fine for extra days unrelated to the value sought from the purchase. Netflix’s new metric was more compelling than the video store metric for a large share of the video rental market, while it also had the effect of discounting to the heavy users who watch many films per month. Consequently, Netflix’s market share and profitability boomed.
In some cases it is not possible to achieve all of these criteria with one metric, but they can be achieved with a multi-part metric. Mobile telephone service providers charge a fixed monthly fee, capturing the value of simply having access to a phone when needed, plus charges for the amount of different services consumed (calls, text messages, internet time). Amusement parks sometimes have an entry fee plus a ticket charge for each ride. Banks may charge a monthly fee for an account, plus additional charges for transactions. Each of these structures is designed to strike a balance between service cost recovery, winning customers with pricing that is seen as aligned with value, and capturing more profit from those customers who are getting more value without losing those who are still profitable despite the need for lower pricing to retain them.
It should also be noted that, depending on the context, the criteria outlined above may need to be modified or added to. For example, in highly regulated markets such as utilities, health care, or insurance, any potential new price metric also needs to pass muster with regulators and legal requirements. In other markets, there may be well-established norms around fairness that may limit the application of new metrics. For example, while it is seen as fair for airlines and hotels to adjust prices relative to demand (with a tactic called yield management), raising the price of a taxi ride when it is raining outside is generally not viewed as fair, although several ride-sharing services at the time of writing have successfully challenged that norm.
An ideal price metric would tie what the customer pays for a product or service directly to the economic value received and the incremental cost to serve. In a few cases, called performance-based pricing, price structures can actually work that way.8 Attorneys often litigate civil cases for which they are paid their out-of-pocket expenses plus a share of the award if they win, rather than for hours worked. Internet ads are usually priced based on the number of click-throughs rather than the traditional metric for advertising: Cost “per thousand” exposure. Systems that control the lights, heating, and cooling within office buildings are sometimes installed in return for contracts that share the energy cost savings, rather than charges for the equipment installed. In each case, the price metric naturally charges customers differently for the same product or service based on differences in the value they receive.
Most importantly, performance-based pricing has the effect of shifting the performance risk from the buyer to the seller. General Electric (GE) used bundling to reduce risk when it launched a new series of highly efficient aircraft engines, its GE90 series. These engines promised greater fuel efficiency and power that could make them much more profitable to operate. The catch was a high degree of uncertainty about the cost of maintenance. Some airlines feared that these high-powered engines might need to be overhauled more frequently, thus easily wiping out the financial benefits from operating them. This undermined GE’s ability to win buyers at the price premium that power and fuel efficiency would otherwise justify.
Rather than accept a lower price to account for a buyer’s perceived risk, GE responded by changing the price metric. Instead of selling or leasing an engine alone, GE effectively rented aircraft engines for a fee per hour flown that included all costs of scheduled and unscheduled maintenance. Without the uncertainty of maintenance cost, GE90 engines quickly became popular, despite a price premium.
In many cases, however, performance-based pricing is simply impractical. It requires too much information and too much trust that the buyer will actually report the information accurately. It also leaves the buyer uncertain regarding the cost of a purchase until after it is used. In practice, therefore, marketers must design profit-driven price structures by finding measures that at least roughly predict the value a customer will receive and the costs to serve, even if the resulting price metric does not allow for a perfect correlation between price and value. Often the difference between a good and a great pricing strategy lies in finding, or creating, such measures.
Evolution of the Price Metric for Mobile Video Games
As video gaming grew from being the passion of hard-core fanatics with dedicated equipment to a widely practiced pastime on practically any device with an internet connection, the challenges for pricing multiplied. How could a game developer optimize revenues from games with which some hard-core users engaged intensely while millions of others simply dabbled? And in a market with a huge and growing number of substitutes, how could a developer induce lots of players to try a game without giving away the value if it turned out to be highly engaging? Fortunately for game developers and the gaming category, game marketers have been particularly adept at adapting their price and revenue models to rapid changes in their market.
For several decades, video games were largely published for three mediums: Personal computers, TV-based gaming consoles, and portable gaming consoles.9 The established consumer price metric for the industry was price per video game title, which resulted in the acquisition of a physical DVD or a cartridge containing the software. Customers were then free to play the video game as much or as little as they wished. Most games were designed to be played either in narrative form by a single individual (as is the case with first-person shooter games) or in a multi-player format with several players in the vicinity of the same game console (as is the case in sports and combat titles).
Although the price-per-title metric served to recover development costs, it was far from optimal. Yes, price per title was easy to measure and consistent with how retailers liked to acquire products for resale, but it didn’t really allow for differences in value across different segments of players. It didn’t align with how a user might experience value when playing the game, and it didn’t really track with cost to serve. It also did not lend itself to discounting to induce product trial. Unfortunately, given the developers’ loss of control once the game was sold to a retailer, it was difficult to imagine how game publishers might overcome these limitations—although retailers tried alternative pricing schemes such as membership fees to borrow games and buy-back options to induce heavy users to try new games.
The success of the Apple and Android smartphones beginning in the mid-2000s created a relatively huge new market for games—there are an estimated 2.9 billion smartphone users worldwide,10 compared to an estimated 529 million game consoles sold from 2008 to 201611 —and new opportunities to engage more directly with game players on an ongoing basis. In the United States, for example, close to 80 percent of consumers with mobile phones were using smartphone models at the end of 2015.12 Prior to smartphones, mobile devices lacked the high-performance computing and graphics-processing capability required for really engaging games. With a much larger potential market suddenly opening up, the traditional price elasticities of video games changed. The relatively huge installed base on this new platform created at least the possibility to sell many more units and to earn much more revenue at a lower price per sale than game publishers were earning selling games to people with dedicated game consoles. Still, the volume gain would have to be huge. Consider that while the average price of a game for the Nintendo 3DS console was $40, a similar game title on the Apple Store ® was priced at around $2.13
The fundamental problem that the price metric didn’t track well with how buyers experienced value remained. A game that people loved and kept them engaged for a long time could earn no more revenue than one that a gamer found interesting initially but tired of quickly. Fortunately, two other evolutions in technology opened opportunities for improvement. Access to cheap, high-speed internet ultimately became ubiquitous in most developed markets, allowing for online multi-player gameplay and the digital delivery of IP versus physical delivery through a retail store.14 Even more important, platforms developed to enable in-app purchases that some creative game developers recognized could be used to make revenues track more closely with a gamer’s engagement.
Publishers of popular, technically sophisticated, but previously expensive game titles soon realized that it was possible to compete with less sophisticated free titles by transforming the price structure of games to a “freemium” model, in which it is free for the end-user to download a game, and then pay for value delivered within the game. The next questions that each game developer needed to answer were: How do users experience value? and, What are the primary drivers of the differences in value experienced? The answers would drive decisions, unique to each game, about how best to design product options and price metrics that would effectively drive revenues based upon value received.
The most sophisticated game publishers now either give away access to the game or charge a very low price to download it. They earn revenues reflecting the amount and intensity of players’ engagement with the game as revealed by their purchases within three broad categories of virtual products offered within a game:
Rather than initiate a credit card transaction for each purchase, games generally involve the purchase with real money of a digital currency used for making smaller purchases quickly. Some mobile video game publishers have taken game monetization and value capture a step further by paying gamers in digital currency to view online ads. When they do so, their ad network partners pay real money to the game publisher based upon views.15
By all accounts, this evolution of price metrics has been an extremely successful strategy for mobile game publishers. According to Distimo, a market research firm, in-game purchase revenue accounted for 79 percent of iOS mobile app revenue (and up to 94 percent in Asian markets) with only 21 percent coming from the traditional model of paying for the title upfront at the start of 2014.16 More importantly, popular games that collect revenue from in-game purchases rather than from upfront purchases earn up to three times more revenue per game.17
Prepared by Junaid Qureshi, who is both an accomplished gamer and consultant at Deloitte Consulting LLP.
A very common challenge for a company that sells capital goods is that the value of owning them can vary widely across segments based upon how intensely they are used. For example, a company that makes a uniquely efficient canning machine might like to sell it both to salmon packers in Alaska, who will use it intensely for only a couple months each year, as well as to fruit and vegetable packers in California, who will use it to can crops all year round. One option would be to put a meter on the machine to record every time that machine went through one cycle. That, in fact, is how Xerox priced its copiers at launch, by leasing them at a price based upon machine usage and refusing to sell them outright.
For the canning machine manufacturer, a usage-based lease was not practical because it did not have service people at the client site on a regular basis to monitor usage. Instead, a more practical metric was a tie-in sale that contractually required purchasers of the canning machine to use it only with cans sold by the seller at a premium price. Thus, the true cost of the machine was not just its low explicit price but also the net present value of the price premiums paid for the tied-in cans. Since buyers who used the machine more intensely must buy more of the tied-in product to use it, they effectively paid more for the asset.
Tie-in sales like those that tied purchase of cans contractually to purchase of the machine were quite common until 1949, when the federal courts decided that such contracts were not enforceable under U.S. antitrust law because of their impact on the otherwise freely competitive market for the tied commodity.18 Although contractual tie-ins are no longer enforceable, companies still frequently use technological design to tie a unique consumable to an asset— often referred to as the proverbial razor-and-razor blades strategy. For example, some manufacturers of document printers will often price the printer—the asset—low to drive adoption of the product. The corresponding replacement ink cartridges—the consumables—are often designed with proprietary technology to fit uniquely with the asset and carry high wholesale margins. The key to the success of this business model is that the pricing allows the seller to build a significant installed base of users, and earn significant profits from users who use—and benefit from—the printers the most.
In service-based companies, tie-in contracts are frequently used to reduce the cost for new buyers to try their services. Wireless phone providers offer a digital telephone for a nominal fee, and sometimes free, if the buyer agrees to purchase a long-term service contract to use the company’s wireless network for 12 or 24 months. Satellite entertainment companies offer households a satellite dish and receiver unit for a greatly reduced price when buyers agree to subscribe to a higher-priced entertainment package of channels for a minimum of 12 or 24 months. These packages can be particularly effective for low-knowledge buyers who perceive significant risk in investing in a new and little-known technology—and then developing them into loyal buyers who become accustomed to the firm’s technology and programming.
Value-Based Pricing Finances Hamlet's Castle
The seeds of value-based pricing were planted centuries ago with the first documented use of value-based pricing metrics to improve profitability. The use occurred in the 15th century when Erik of Pomerania, King of the United Kingdom of Scandinavia, summoned to Copenhagen a group of merchants from the powerful German Hanseatic League, which at the time dominated nearly all trade in northern Europe. He informed them that henceforth, he intended to levy a new toll: Every ship wishing to sail past Elsinore, whether on its way out of or into the Baltic, would have to dip its flag, strike its topsails, and cast anchor so that the captain might go ashore to pay the customs officer in the town a toll of “one English noble.”
Nobody challenged the right of the King of all Scandinavia to impose a toll of this kind. After all, mere barons who owned castles on the banks of the Rhine, the Danube, and other major European waterways had for centuries forced all passing ships to pay a similar toll. However, its relative heaviness, combined with the obligation to cast anchor at Elsinore in order to hand over the money, made it highly unpopular. Erik foresaw that if he also established a proper town at Elsinore, sea captains, after paying their toll and then waiting for a favorable wind, would welcome an opportunity to replenish stocks of water, wine, meat, vegetables, and whatever else they needed. In other words, even if they had to pay a toll, calling in at Elsinore could have its attractions—all he had to do was provide them.
Elsinore’s fortunes changed in 1559 with the accession to the throne of Frederik II, aged 25. He was young, ambitious, and entertained imperialistic ideas about reconquering Sweden and restoring the Nordic Union. Consequently, he declared war, and it dragged on for seven years. Like all wars, it was a severe drain on Denmark’s finances. By 1566, the situation was so serious that Frederik II and his councillors decided as a last resort to enlist the help of a man with special talents named Peder Oxe. Oxe was acknowledged to be a financial wizard, which was just what Frederik needed.
Erik of Pomerania’s toll of one English noble per ship had long been regarded by skippers and ship owners as grossly unfair. After all, ships were of so many different sizes, carried so many different cargoes, and according to nationality, had various interests and affiliations. The system had also been proving increasingly disadvantageous from the Danish king’s point of view. The first four or five kings after Erik of Pomerania had therefore continually tried to introduce amendments of one kind or another, and these in turn made it necessary to introduce various special concessions. Some nationalities were exempted completely and others enjoyed preferential treatment in certain respects.
By this time, the basic toll had been raised from one to three nobles per ship, but it was still far from being a satisfactory system. Peder Oxe realized that the only answer lay in a radical reform of the whole basis upon which the tolls were calculated. Henceforth, instead of a simple toll per ship, payment must be made, he suggested, on the basis of the cargo carried. To start with, two Rixdollars per last (a “last” being approximately two tons of cargo). Soon this was changed to an even subtler and more flexible system: A percentage of the value of each last of cargo.
The King held the right of pre-emption, that is to say an option to buy, if he so chose, all cargoes declared. This royal prerogative encouraged the captain of a ship to make a correct declaration. Naturally, if he thought the King might be interested in buying his cargo, he was tempted to put a high value on it. However, in doing so, he ran the risk that His Majesty might be totally disinterested, in which case he would have to pay a duty calculated on this high valuation. Conversely, if he played safe and declared a low value in the hope of getting away with paying a low duty, the King might decide to buy the whole consignment which could leave the captain seriously out of pocket. Summoning Peder Oxe to reorganize the levying of the Sound Dues proved to be a masterful stroke. Within a few years, the King’s income from this source practically tripled. At the age of 38, Frederik II married his 15-year-old cousin, Sophie of Mecklenburg, and in 1574 embarked on what was to become the major architectural project of his life, the building of a new castle at Elsinore.
Abridged from Hamlet’s Castle and Shakespeare’s Elsinore by David Hohnen (Copenhagen: Christian Ejlers, 2000).
Sometimes value differs between customer segments even when all the features and measurable benefits are the same. Value can differ between customer segments and uses simply because they involve different formulas for converting features and benefits into economic values. The difference may be tied to differences in income, in alternatives available, or in psychological benefits that are difficult to measure objectively. Unless there is a good proxy metric that just happens to correlate with the resulting differences in value, the seller needs to find a price fence: A means to charge different customers different price levels for the same products and services using the same metrics.
Price fences are fixed criteria that customers must meet to qualify for a lower price. At theaters, museums, and similar venues, price fences are usually based on age (with discounts for children under 12 years of age and for seniors) but are sometimes also based on educational status (full-time students get discounts), or possession of a coupon from a local paper (benefiting locals who know more alternatives). All three types of customers have the same needs and cost to serve them, but perceive a different value from the purchase. Price fences are the least complicated way to charge different prices to reflect different levels of value. Unfortunately, while simple to administer, the obvious price fences sometimes create resentment and are often too easy for customers to get over whenever there is an economic incentive to do so. Thus, finding a fence that will work in your market usually requires some creativity.
Occasionally pricing goods and services at different levels across segments is easy because customers have obvious characteristics that sellers can use to identify them. Barbers charge different prices for short and long hair because long hair takes more time to cut. But, during non-peak hours, barbers also cut children’s hair at a substantial discount, despite the fact that children can be more challenging and time-consuming. The rationale in this case is entirely to drive business with a discount for a more price-sensitive segment. Many parents view home haircuts as acceptable alternatives to costly barber cuts for their children, even though they would never bear the risk of letting their spouses cut their own hair. For barbers, simple observation of the customer segment, children, is the key to segmented pricing.
Issuers of credit cards resort to far more sophisticated, proprietary models to anticipate the price sensitivities and costs to serve for different types of consumers. Some are more sensitive to the annual fee, some to the interest rate, and others to the frequent flyer miles or other benefits they can earn. On the cost side, some consumers are more likely to default or to use their card only infrequently, thus generating fewer fees from retailers for processing charges. Finally, the companies can see from consumers’ credit reports what competitive cards they hold and can estimate their annual fee and interest rates, thus determining the reference value of the next best competitive alternative (NBCA). Based upon these analyses, credit card companies very finely segment their potential customer base and send out different offers that optimize the expected profitability of each segment. The metrics are the same, but the levels vary depending on which metric the issuer can use most cost-effectively to capture the most value. Rarely is identification of customers in different segments straightforward. Yet, management can sometimes structure price discounts that induce the most price-sensitive buyers to volunteer the information necessary to identify them. Many service providers, from hotels and rental car companies to theaters and restaurants, offer senior discounts to those who will show an American Association of Retired Persons (AARP) card, Medicare card, or some other ID that confirms their eligibility. College students qualify for discounts on various types of entertainment because their low incomes and alternative sources of campus entertainment make them, as a group, price-sensitive shoppers. Seniors and students readily volunteer their identification cards to prove that they are members of the price-sensitive segment. Members of the less price-sensitive segment identify themselves by not producing such identification.
Even schools and colleges charge variable tuitions for the same education based on their estimates of their students’ price sensitivities. Although the official school catalogs list just one tuition, it is not the one most students pay at private colleges. Many receive substantial discounts disguised as “tuition remission scholarships” obtained by revealing personal information on financialaid applications. By evaluating family income and assets, colleges can set tuition for each student that makes attendance attractive while still maximizing the school’s income.
Deal proneness is another form of self-induced buyer identification— especially through the use of coupons and sales promotions, a frequent tool of consumer marketers. Coupons provided by the seller give deal-prone shoppers a way to identify themselves.19 Supermarkets and drug stores put coupons in advertising circulars because people who read those ads are part of the segment that compares prices before deciding where to shop. Packaged-goods and small appliance manufacturers print coupons and rebate instructions directly on the packages, expecting that only price-sensitive shoppers will make the effort to clip them out and use them for future purchases.20
Often a buyer’s relative price sensitivity does not depend on anything immediately observable or on factors a customer freely reveals. It depends instead on how well informed about alternatives a customer is and on the personal values the customer places on the differentiating attributes of the seller’s offer. In such cases, the classification of buyers by segment usually requires an expert salesperson trained in soliciting and evaluating the information necessary for segmented pricing.
When customers who perceive different values buy at different locations, they can be segmented by purchase location. This is common practice for a wide range of products. Dentists, opticians, and other professionals sometimes have multiple offices in different parts of a city, each with a different price schedule reflecting differences in the target clients’ price sensitivity. Many grocery chains classify their stores by intensity of competition and apply lower markups in those localities where competition is most intense. Colorado ski resorts use purchase location to segment sales of lift tickets. Tickets purchased slope side are priced the highest and are bought by the most affluent skiers who stay in the slope-side hotels and condos. Tickets are cheaper (approximately 10 percent less) at hotels in the nearby town of Dillon, where less affluent skiers stay in cheaper, off-slope accommodations. In Denver, tickets can be bought at grocery stores and self-serve gas stations for larger discounts (approximately 20 percent less). These discounts attract locals, who know the market well and who are generally more price sensitive because the ticket price represents a much higher share of the total cost for them to ski.
A clever segmented pricing tactic common for pricing bulky industrial products such as steel and coal is freight absorption. Freight absorption is the agreement by the seller to bear part of the shipping costs of the product, the amount of which depends upon the buyer’s location. The purpose is to segment buyers according to the attractiveness of their alternatives. A steel mill in Pittsburgh, for example, might agree to charge buyers the cost of shipping from either Pittsburgh or from Gary, Indiana, where its major competitor is located. The seller in Pittsburgh receives only the price the buyer pays, less the absorbed portion of any excess cost to ship from Pittsburgh. This enables the Pittsburgh supplier to cut price to customers nearer the competitor without having to cut price to customers for whom his Chicago competitors have no location advantage. The Chicago competitor probably uses the same tactic to become more competitive for buyers nearer Pittsburgh.
Trade barriers between countries once made segmentation by location viable even for products that were inexpensive to ship. As trade barriers have declined around the world, and especially within the European Union, the tactic has become less effective. For example, automobiles used to be sold throughout Europe at prices that varied widely across borders. German luxury cars sold in Britain were at least 20 percent more expensive than when sold just across the channel in Belgium. But after Britain joined the EU, brokers in Britain began to survey the continent for cars, which people could fly to pick up and drive home—or even have the broker bring it back for them. To fight back, some makers of German luxury brands, which are cheaper in Germany than in some other countries where they carry a more premium image, have used their warranties to enforce location fences. A car bought in Germany and imported to Britain cannot get warranty service in the United Kingdom without paying an additional charge for warranty transfer to a British dealership.
When customers in different market segments purchase at different times, one can segment them for pricing by time of purchase. Theaters segment their markets by offering midday matinees at substantially reduced prices, attracting price-sensitive viewers who are not employed during the day at times when the theater has ample excess capacity. Less price-sensitive evening patrons cannot so easily arrange dates or work schedules to take advantage of the cheaper midday ticket prices. Restaurants usually charge more to their evening patrons, even when their peak demand is at lunch, because demand (in the United States, but not in Europe) is more price sensitive for the midday meal. Why? There are more numerous inexpensive substitutes for lunches than there are for dinners. A fast food meal or a brown bag, acceptable for lunch, is often viewed as a poor substitute for a formal dinner as part of an evening’s entertainment.
Priority pricing is one example of segmenting by time of purchase. Innovative new retail products are offered at full price, or even at a premium. Over time, as product appeal fades in comparison to still newer competitive alternatives, buyers discount the product’s value until they are willing to pay only a fraction of its original price for leftover models. This is common in the retail fashion and automobile industries, where customers with high incomes and low price sensitivity pay premium prices for the latest styles and models. Over time, as inventories age and novelty declines, prices are reduced in successive rounds of promotions to appeal to more price-sensitive buyers who are willing to wait for the opportunity to buy high-quality, but less trendy, inventory.
Priority pricing also applies in business-to-business purchases. A strategy of Intel has long been to introduce a leading-edge semiconductor at a premium price that reflects the higher performance level, and then adjust prices on its existing product lines to make them viable upgrades for less demanding applications, as well as to reduce the inventory of the now older semiconductors. Leading-edge original equipment manufacturer (OEM) computer manufacturers that produce and sell the fastest and latest computers to innovative professional buyers with low price sensitivity pay the price premium for the latest chip technology. More price-sensitive buyers who do not require the highest levels of performance are able to choose from a tiered selection of Intel semiconductors that vary in price and performance levels.
Predictable, periodic sales offering the same merchandise at discounted prices can also segment markets. This tactic is most successful in markets with a combination of occasional buyers who are relatively unfamiliar with the market, and with more regular buyers who know when the sales are and plan their purchases accordingly. Furniture manufacturers employ this tactic with sales every February and August, months when most people usually would not think about buying furniture. However, people who regularly buy home furnishings, and who are more price sensitive because of the reference-price and total-expenditure effects, know to plan their purchases to coincide with these sales.
Time is also a useful fence when demand varies significantly with the time of purchase but the product or service is not storable. This problem plagues airlines, hotels and restaurants, electric utilities, theaters, computer time-sharing companies, beauty salons, toll roads, and parking garages. Unable to move supplies of their products from one time to another, their only option is to manage demand to match supply by charging high prices when supply would otherwise exceed demand and lower prices when it is highly unlikely that the seller will face demand that exceeds capacity.
Pricing for travel through the Eurotunnel between England and France is an interesting application of segmented pricing for a product with fixed capacity. The channel tunnel allows transport of an automobile and its occupants between England and France for a flat price. Prices that allow travel at whatever time of day you choose are twice as high as during the off-peak evening and night periods. This reflects the opportunity cost of limited capacity. More interesting is the fact that rates increase with the time elapsed between the outbound and the return trips. Roundtrip use of the tunnel for a two-day, one-night visit from the United Kingdom to France costs from £53 per auto, while roundtrip use for a three- to seven-day visit costs from £79 at the same times of day. Clearly, this has nothing to do with cost or available capacity, so what drives it? The answer is that the value of having your own car with you on the trip versus having to rent one after traveling by plane or train increases with the length of the stay.21
When customers in different segments buy different quantities, one can sometimes segment them for pricing with quantity discounts. There are four types of quantity discount tactics: Volume discounts, order discounts, step discounts, and two-part prices. All are common when dealing with differences in price sensitivity, costs, and competition.22 Customers who buy in large volume are usually more price sensitive. They have a larger financial incentive to learn about all alternatives and to negotiate the best possible deal. Moreover, the attractiveness of selling to them generally increases competition for their business. Large buyers are often less costly to serve. Costs of selling and servicing an account generally do not increase proportionately with the volume of purchases. In such cases, volume discounting is a useful tactic for segmented pricing.
Volume discounts are most common when selling products to business customers. Steel manufacturers grant auto companies substantially lower prices than they offer other industrial buyers. They do so because auto manufacturers use such large volumes they could easily operate their own mills or send negotiators around the world to secure better prices. Volume discounts are based on the customer’s total purchases over a month or year rather than on the amount purchased at any one time. At some companies, the discount is calculated on the volume of all purchases; at others, it is calculated by product or product class. Many companies give discounts for multiple purchases of a single model but, in addition, give discounts based on a buyer’s total expenditure on all products from the company.
Although less common, some consumer products are volume discounted as well. Larger packages of most food, health, and cleaning products usually cost less per ounce, and canned beverages cost less in 12-packs than in six-packs. These differences reflect both cost economies for suppliers and the greater price sensitivity for these products by large families. Warehouse food stores, such as Costco, Sam’s Club, and BJ’s Wholesale Club often require consumers to buy in large-quantity packages to qualify for discounted prices.
Often sellers vary prices by the size of an order rather than by the size of a customer’s total purchase volume. Order discounts are the most common of all quantity discounts. Almost all office supplies are sold with order discounts. Copier paper, for example, can be purchased for about $20 per case of ten reams, but purchased individually it costs several dollars per ream. The logic for this is that many of the costs of processing an order are unrelated to the size of it. Consequently, the per-unit cost of processing and shipping declines with the quantity ordered. For this reason, sellers generally prefer that buyers place large, infrequent orders, rather than small frequent ones. To encourage them to do so, sellers give discounts based on the order quantity. Order discounts may be offered in addition to volume discounts for total purchases in a year, because volume discounts and order discounts serve separate purposes. The volume discount is given to retain the business of large customers. The order discount is given to encourage customers to place large orders.
Step discounts differ from volume or order discounts in that they do not apply to the total quantity purchased, but only to the purchase beyond a specified amount. The rationale is to encourage individual buyers to purchase more of a product without having to cut the price on smaller quantities for which they would pay a higher price. Thus, in contrast to other segmentation tactics, step discounting may segment not only different customers, but also different purchases by the same customers. Such pricing is common for public utilities, from which customers buy water and electricity for multiple uses and place a different value on it for each use.
Consider, for example, the dilemma that local electric companies face when pricing their product. Most people place a very high value on having some electricity for general use, such as lighting and running appliances. The substitutes (gaslights, oil lamps, and hand-cranked appliances) are not very acceptable. For heating, however, most people use alternative fuels (gas, oil, coal, and kerosene) because of their lower cost. Utilities would like to sell more power for heating and could do so at a price above the cost of generating it. They do not want to cut the price of electricity across the board, however, since that would involve unnecessary discounts on power for higher-valued uses. One solution to this dilemma is a step-price schedule. Assume that the electric company could charge a typical consumer $0.06 per kilowatt-hour (KWH) for general electricity usage but that it must cut its price to $0.04 per KWH to make electricity competitive for heating. If the company charged the lower price to encourage electricity usage for heating, it would forgo a third of the revenue it could earn from supplying power for other uses. By replacing a single price with a block-price schedule, $0.06 per KWH for the first block of 100 KWH and $0.04 for usage thereafter, the company could encourage people to install electric heating without forgoing the higher income it can earn on power for other purposes. To encourage people to use electricity for still more uses, such as charging their car batteries during off-peak hours, utilities often add another step discount for quantities in excess of those for general use and heating. Exhibit 4-6 illustrates a step-price schedule for an electric utility.
EXHIBIT 4-6 Step-Price Schedule for Electricity
Two-part pricing is another way to structure volume discounts and is used most commonly in situations where there is an incremental cost to take on a new customer but a lower cost to sell an existing customer additional volume. For example, a company that supplies fuel oil or LPG to homes and businesses must send a truck to each customer location to top-off the tank on a regular basis. Customers who require only a small amount at each visit would need to be charged a high price per gallon or cubic foot simply to cover the delivery cost, while those who require much larger quantities could be served profitably at a lower price per unit and would therefore have a lot of competition for their business. The typical solution is a two-part price, which in this case would be a price to make the delivery plus a price for the amount of product actually delivered.
Given the clear increase in profit from offering step discounts, effectively moving along an individual customer’s demand curve, why do most companies still offer each individual customer volume at only one price? The answer is that segmenting different purchases by each customer is possible only under limited conditions. It is profitable only when the volume demanded by individual buyers is significantly price sensitive.
In industries where the product or service is not storable, a seller’s current capacity imposes a limit on the amount of demand that can be satisfied at any point in time, while any capacity that is not sold when available is lost forever. This is a common problem for airlines, hotels, taxi fleets, and amusement parks. It is also a common problem for services from government such as the capacity of roads and central city streets that become congested and impassable at peak times. The easiest solution to this problem involves simply raising price reactively, or peak pricing, whenever supply is inadequate to meet the quantity demanded. Uber, for example, adjusts its prices upward when demand exceeds supply, ensuring that at some price it is almost always possible to get an Uber car while rewarding drivers for joining the pool of cars when demand is greatest. Even some governments have come to recognize how peak pricing can both improve the quality of life for its citizens while earning revenues disproportionately from people who are willing to pay a premium at peak times. Cities from London to Singapore have begun to charge drivers a “congestion charge” for the right to drive on inner-city streets when traffic would otherwise exceed capacity, while highways throughout the U.S. have additional priority lanes where traffic is kept flowing by setting an access charge high enough to keep the number of cars using the lanes within the available capacity.
The most challenging pricing problems occur when a seller attempts to manage both the peak demand problem and pricing across different segments simultaneously. In the distant past, most sellers would attempt to manage one and simply accept management of the other as a lost opportunity. As the cost of computing power and data management declined over recent decades, companies with the most to gain began developing a process called Yield Management to optimally manage these two pricing problems simultaneously. A few firms in the airline industry and petroleum refining have led the way in developing sophisticated yield management techniques. The ability to do so proved to be a huge competitive advantage substantially increasing the return on capital invested relative to those firms that simply adjust price reactively.
There are three tasks required for effective yield management. The first is to use one of the pricing tactics described above to enable segmented pricing based upon value to the purchaser. Second, because one must generally set the price level by segment before potential customers reveal their demand, yield management requires a means to forecast changes in demand by segment over time. Initially, airlines used past variation over days of the week and over weeks of the year to forecast demand by segment in the future. Over time, the best yield management practitioners have added more variables to their forecasting models to anticipate demand even more accurately. Third, yield management involves estimating demand price elasticity by segment to determine which prices should be adjusted to optimize the balance between margin and capacity utilization.
With those three bits of information—a segmented price structure, demand forecasts and elasticities by segment—yield managers can optimize prices to maximize revenue and profit. The ultimate goal is to target price changes to induce the more price-sensitive customers to adapt their purchase behavior while maintaining pricing for the less price-sensitive segments, where inducing changes in demand would be more costly to the seller and painful for the buyer. To illustrate how they do this, consider the recent pricing on the route from Boston to Chicago. The fully refundable, changeable fare, purchased almost exclusively by relatively price-insensitive business travelers, is $302 for all flights during the work week. At that price, the airline makes a lot on each seat sold and so would like to ensure that seats are always available at that price point on every flight, even if purchased near the flight time. On the other hand, since the costs of a flight are mostly independent of the number of customers actually on the plane, the airline would also like to fill as many seats as possible, since an empty seat is a wasted revenue opportunity.
To achieve these conflicting goals in a way that maximizes the revenue, or yield, on each flight, the airline focuses its price management on the customers who are most price sensitive. On Monday morning, usually a time of peak demand, the price for a non-refundable, non-changeable ticket at the most popular flight times is $232. A price that high is sufficient to discourage some discretionary travelers from traveling at that time, leaving seats available to sell more profitably and refundable tickets to business travelers. On Wednesdays, however, demand from business travelers is much less than on Mondays, so there are potentially many empty seats. The solution, however, is not to discount the refundable fare, since few if any additional business travelers would take a trip on Wednesday simply because fares were lower.
Instead, the airline holds the refundable fare at the same $302 level, despite the lower demand for it, because that demand is not particularly price sensitive. To fill the additional seats that cannot be sold at full price, the yield manager will lower the price for a non-refundable, non-changeable ticket on Wednesday morning. But an airline cannot wait until it sees how many people will buy a refundable ticket before deciding whether and how much to discount non-refundable tickets, since the buyers of refundable tickets often wait to book until close to the time of the flight. Consequently, the airline must estimate how many seats it can sell in advance at a discount without foreclosing the ability to sell those seats at a higher price later. To do that, a yield manager must first forecast how many higher-priced, refundable tickets the airline will be able to sell closer to flight time.
Apparently, the yield manager in this case expected demand for Wednesday morning flights to fall substantially relative to Monday flights, leaving a lot of empty seats. Consequently, the airline reduced its lowest, non-refundable fare for Wednesday morning to only $127. Since that is 37 percent below its price for the same time on Mondays, the airline apparently estimated from past experience that it could sell, and would have the capacity to serve, greater than 37 percent more seats on Wednesday morning than it could have sold by retaining the same price it offered on Monday.
Obviously, the better an airline’s ability to forecast demand, and the better the ability to estimate the impact of price on seats demanded, the more successful the yield management will be in loading capacity with the most profitable passengers available for each date and flight time. The key to transforming simple peak pricing into sophisticated yield management in any industry is the forecasting of demand and adjustment of price based upon how current sales are tracking against forecasted sales. While software to do this was initially built in house, software companies have since developed sophisticated software packages to make and display these estimates automatically, drawing upon analysis of past demand patterns for similar days of the week and times of the year. Those yield management packages are now widely used to set prices for hotel rooms, rental cars, and advertising space as well as for airline seats. Less sophisticated versions are sometimes used to price seats at concerts and other popular performance venues.
Designing an optimal price structure that effectively segments your market and maximizes your profitable sales opportunities is clearly among the most difficult, but potentially rewarding, aspects of pricing strategy. For companies that are launching an offering with differentiated benefits or employing a business model with a different cost structure, creating a new price structure that aligns with those differences is usually necessary to capture the profit potential associated with them. Even without such a change, a company that can incrementally improve the price structure can gain profitable incremental volume. The principles of price structure discussed in this chapter, and the examples cited to illustrate them, can serve as a guide to a better basis for collecting revenues across segments. There is no simple formula. Each case requires creativity to find the best means to implement those principles within your market. It is, however, one of the most important activities that a marketer can do to improve profitability, since the investment required is small relative to other marketing investments, and the payoff is often very large.
1. Herman Hesse, Narcissus and Goldmund, trans. Ursule Molinaro (New York: Picador, 1968), p. 41.
2. Clayton M. Christensen, The Innovator’s Dilemma (Cambridge, MA: Harvard Business School Press, 1997), pp. 44–46.
3. Daniel Kahneman, Jack L. Knetsch, and Richard H. Thaler, “The Endowment Effect, Loss Aversion, and Status Quo Bias,” Journal of Economic Perspectives, 5(1) (Winter 1991), pp. 193–206.
4. Gary D. Eppen, Ward A. Hanson, and R. Kipp Martin, “Bundling— New Products, New Markets, Low Risk,” Sloan Management Review, 32(4) (Summer 1991), pp. 7–14, describes a model for optimizing very complex bundles.
5. Marco Bertini and Luc Wathieu, “How to Stop Customers from Fixating on Price,” Harvard Business Review (May 2010). Accessed at https://hbr.org/2010/05/how-to-stop-customers-from-fixating-on-price.
6. “Kaiser Permanente—California: A Model for Integrated Care for the Ill and Injured,” Brookings Institution, May 4, 2015. See also: Reed Abelson, “The Face of Future Health Care,” The New York Times, March 20, 2013. Accessed at www.nytimes.com/2013/03/21/business/kaiser-permanente-is-seen-as-face-of-future-health-care.html.
7. Atul Gawande, “The Cost Conundrum: What a Texas Town Can Teach Us About Health Care,” The New Yorker, June 1, 2009. Accessed at www.newyorker.com/magazine/2009/06/01/the-cost-conundrum.
8. For a complete treatment of performance-based pricing, see Benson P. Shapiro, “Performance-Based Pricing Is More Than Pricing,” Harvard Business School Note 9-999-007, February 25, 2002.
9. “The Global Games Market Reaches $99.6 Billion in 2016, Mobile Generating 37%,” Newzoo.com, April 21, 2016. Accessed at https://newzoo.com/insights/articles/global-games-market-reaches-99-6-billion-2016-mobile-generating-37.
10. Statista, “Number of Smartphone Users Worldwide from 2014 to 2020.” Accessed at www.statista.com/statistics/330695/number-of-smartphone-users-worldwide.
11. Statista, “Global Unit Sales of Current Generation Video Game Consoles from 2008 to 2016.” Accessed at www.statista.com/statistics/276768/global-unit-sales-of-video-game-consoles.
12. “Smartphone Penetration Nears 80% of the US Mobile Market,” MarketingCharts.com, February 8, 2016, cites statistics from comScore. Accessed at www.marketingcharts.com/online/smartphone-penetration-nears-80-of-the-us-mobile-market-65214/.
13. Ali Shah, “Nintendo 3DS vs Smart-phone Gaming: Which Wins?” Gigaom, March 31, 2011. Accessed at https://gigaom.com/2011/03/31/nintendo-3ds-vs-smartphone-gaming-which-wins.
14. Andrew Burger, “LRG: U.S. Broadband Penetration Rises to 79% of Households, Smartphone Role Increasing,” Telecompetitor.com, October 24, 2014. Accessed at www.telecompetitor.com/lrg-u-s-broadband-penetration-rises-to-79-of-households-smartphone-role-increasing.
15. Brian Rifkin, “How to Win With In-Game Advertising,” Adweek, September 28, 2015. Accessed at www.adweek.com/socialtimes/how-to-win-with-in-game-advertising/627399.
16. Shane Schick, “Distimo: In-app Purchases Accounted for 79% of iOS Revenue in January,” FierceWireless.com, March 24, 2014. Accessed at www.fiercewireless.com/developer/distimo-app-purchases-accounted-for-79-ios-revenue-january.
17. Sourcebits, “Paid vs. Free Apps in the App Store vs. Google Play,” July 16, 2014. Accessed at http://sourcebits.com/app-developmentdesign-blog/paid-vs-free-appsapp-store-vs-google-play.
18. United States v. American Can Company (Northern District court of California, 1949).
19. See Narasimhan Chakravarthi, “Coupons as Price Discrimination Devices—A Theoretical Perspective and Empirical Analysis,” Marketing Science, 3 (Spring 1984), pp. 128–147; Naufel J. Vilcassim and Dick R. Wittink, “Supporting a Higher Shelf Price Through Coupon Distributions,” Journal of Consumer Marketing, 4(2) (Spring 1987), pp. 29–39.
20. See the discussion in Chapter 5 of the framing effect to understand why rebates may influence purchases by customers who do not ultimately redeem them.
21. Source: Fare finder function at www.eurotunnel.com.
22. For an in-depth discussion of the motivations for quantity discounting, see Robert J. Dolan, “Pricing Structures with Quantity Discounts: Managerial Issues and Research Opportunities,” Harvard Business School working paper, 1985.