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What is a pricing strategy?
A pricing strategy is the means by which a firm intends to reach a pricing objective; it is not the price itself. Noble and Gruca (1999)3 give a definition that keeps three things apart: “A pricing strategy is the means by which a pricing objective is to be achieved.” The objective is the result a decision maker seeks to achieve, such as profit maximization. The determinants are “the internal and external conditions that determine managers’ choices of pricing strategies”. That makes three different things: what you want, how you intend to get it, and what about your situation makes that route sensible.
Most strategies imply a relative price before anyone types a number into a price list. In the same paper’s words, “Most pricing strategies imply a relative price level or schedule related to costs, competition, or customers.” High against cost, level with the market, low against the buyer’s alternatives: each of those is a position a team can defend or revise.
The definition becomes useful when a team writes the strategy down in the fields it separates. Figure 1 is that record. Each column answers a question that a price on its own cannot.
Figure 1A pricing strategy record
One row per pricing decision. If a field stays empty, the team has a price, not yet a strategy.
Source: Author's decision worksheet grounded in Noble and Gruca (1999) and Ingenbleek et al. (2003); reader inputs only.
What gets mistaken for a pricing strategy?
Four things: the price, the pricing practice, positioning and pricing architecture. Each confusion leaves a different gap.
The price is the output. A strategy explains why the price sits high or low relative to something, so a price list with no recorded strategy cannot be reviewed when costs, rivals or buyers move.
The pricing practice is the information used to reach the price. Ingenbleek et al. (2003)1 keep the two apart: practices are “the use of information in a pricing process that leads to price decisions”, while strategies “refer to how the firm tries to achieve its pricing objectives in the market place”. They also treat cost, competitor and customer-value information as used “as a matter of degree”, which is why they write cost-informed, competition-informed and value-informed pricing rather than cost-based, competition-based and value-based. Mistaking the practice for the strategy leaves the objective unstated.
Positioning chooses the comparison set the buyer prices you against; mistaken for strategy, it leaves the route unstated. Pricing architecture is how a chosen strategy is carried into value metrics, offers, terms and approval rights; mistaken for strategy, it builds structure for a route nobody chose. Value-based pricing is one way of informing the ceiling, which makes it a practice, the second confusion above. A team that answers the question about its pricing strategy with a number, a method or a positioning line has not written the strategy yet.
What types of pricing strategy are there?
Noble and Gruca (1999)3 organise ten pricing strategies under four pricing situations. “The first level consists of four pricing situations: New Product, Competitive, Product Line, and Cost-based”, and within them sit “a total of ten pricing strategies”. A situation is defined by a condition its strategies share: a new model, a mature market, a firm that also sells related products, or demand that is hard to estimate.
The ten are not every pricing strategy there is. They are Noble and Gruca’s3 selection for industrial capital goods, adapted from Tellis’s framework, which leans toward consumer products: the authors left out strategies used mainly for consumer products, commodities or export markets, left out pricing tactics, and added cost-plus and customer value pricing because industrial studies kept finding them.
| Situation | Strategy | What the firm does | Conditions under which surveyed managers chose it |
|---|---|---|---|
| New product (a new model) | Price skimming | Sets the initial price high and reduces it over time | High differentiation in the market; cost disadvantage of scale (p < 0.10) |
| New product | Penetration pricing | Sets the initial price low to accelerate adoption | Cost advantage of scale; elastic market demand; inelastic brand demand (against the authors’ own normative case, which lists elastic brand demand) |
| New product | Experience curve pricing | Sets the price low to build volume and cut cost through experience | High differentiation (p < 0.10, contrary to expectation); not a major product change; low capacity utilization (p < 0.10) |
| Competitive (a mature market) | Leader pricing | Initiates a price change and expects others to follow | None at p < 0.10 |
| Competitive | Parity pricing | Matches the market or the price leader | High costs; low share; low differentiation; elastic market demand (p < 0.10, contrary to expectation); elastic brand demand (expected in the authors’ Table 2, although their text calls it contrary); high capacity utilization (listed by the authors, but p = 0.57 in their estimate table) |
| Competitive | Low-price supplier | Always strives to have the low price | Low costs; scale advantages (p < 0.10); low utilization (p < 0.10); elastic brand demand (p < 0.10); no learning advantage (listed by the authors, but p = 0.49 in their estimate table) |
| Product line (related products) | Complementary product pricing | Prices the core product low when parts, supplies or services carry a premium | High profit on supplementary sales |
| Product line | Price bundling | Sells the product in a bundle at a saving on the separate prices | Per-sale or contract pricing; elastic brand demand |
| Product line | Customer value pricing | Prices a version with fewer features at a very competitive level | Price changes hard to detect; narrow market appeal; high market growth (p < 0.10, contrary to expectation) |
| Cost-based (demand hard to estimate) | Cost-plus pricing | Sets the price at a specified margin over cost | Demand difficult to estimate (p < 0.10; also the situation’s defining condition) |
Figure 2Four pricing situations, ten strategies
The strategies are routes, not prices. The conditions record what went with managers' choices in one survey, not what justifies a choice, and the authors caution that the same conditions might suit other strategies.
Source: Noble and Gruca (1999), Tables 1 and 6 to 9, condensed; industrial capital goods, US sample surveyed in 1994, associations only.
The table hides the point that matters most in practice: one decision can sit in several situations at once. Noble and Gruca3 use a Harvard case in which Deere prices a new bulldozer model, which is a new product decision, in a mature market where Caterpillar offers comparable models, which is a competitive one, while spare parts earn a significant income over the product’s life, which is a product line one. As they put it, “a manager may be in more than one pricing situation simultaneously.”
What did industrial pricing managers choose in practice?
More than half of the US industrial pricing managers that Noble and Gruca (1999)3 surveyed in 1994 used more than one strategy, and cost-plus was the one cited most. The questionnaire was mailed in May and June 1994 and asked about the most recent pricing decision for a high-value industrial product sold in the United States. It has 270 usable responses, a 27% response rate, and cost-plus was cited by 56% of respondents. When cost-plus was used, it was the dominant strategy 71% of the time, and over 35% of managers combined it with one of the nine market-based strategies: looking inward at cost and outward at the market in the same decision.
Overall, Noble and Gruca (1999)3 report that the choices “are consistent with normative pricing research”. Skimming appeared where differentiation was high and the firm was at a cost disadvantage of scale. Penetration appeared where the firm had a scale advantage and overall demand was elastic while brand demand was not. Parity pricing appeared among firms with high costs, low share and little differentiation. The study explains which strategy managers chose; it does not measure what the choice earned.
The match is not complete, and the authors say how far the associations go. “Since these conditions are not unique to a given strategy, they should be viewed with some caution if used to predict which strategy a firm might use.” Three associations ran against what the normative literature expected: experience curve pricing in highly differentiated markets, parity pricing where market demand was elastic, and customer value pricing in fast-growing markets. For the first, they suggest some firms may be cutting prices to build volume ahead of a price-led phase of competition that might not come. A fourth sits against their own normative case without a flag: penetration went with inelastic brand demand, although the paper lists elastic brand demand among the conditions that make penetration acceptable; the authors read the result as penetration being used early, when competition comes mainly from substitutes. Their significance threshold is p < 0.10.
Two further limits matter for anyone applying this outside the sample. The data cover industrial capital goods, sold to US customers, by firms selling in US markets, in 1994. And the framework, in the authors’ own words, “does not suggest how these strategies are or should be combined to determine the ultimate pricing schedule.” It shows which routes are plausible; it does not weigh them into one price.
Is cost-plus pricing a strategy or a fallback?
It is a strategy: one of the ten in Noble and Gruca’s3 framework, and in their sample the most common. Whether it should stand alone or beside a market-based strategy is not something these studies tested, although over a third of their managers combined the two. Most of the normative literature cautions against cost-based methods, and practice in their sample used cost-plus most. Noble and Gruca (1999) state its weakness plainly: it “ignores consumer and competitive information”. They also find it chosen more often where demand is very difficult to estimate, a weak association (p < 0.10), and there, they write, “cost-based pricing makes a great deal of sense.”
What Ingenbleek et al. (2003)1 measured is cost information, not cost-plus as such: how much cost information went into a launch price, by degree. In their words, “Cost-informed pricing helps to understand the lower-boundary of the price discretion.” Across 77 new industrial products, heavier use of cost information went with better new product performance as competitive intensity rose. It is a weak interaction (p < 0.1, one-tailed), which the authors read as “best practice” under intense competition and “bad practice” under weak competition. Their sample came from electronics and engineering, industries with high fixed and low variable costs, and they warn that the results may differ elsewhere.
They draw the link to cost-plus themselves. Of the 56% cost-plus share in Noble and Gruca’s3 sample, they write that “this high percentage doesn’t seem worrisome after all.” Our reading, which neither study tested: cost belongs in the record as the floor, and a price set from cost alone needs a stated reason.
Does value-based pricing beat cost-based and competition-based pricing?
In both studies cited here, heavier use of customer-value information went with better reported performance; in one, the benefit disappeared where competition was most intense. Neither shows an effect on profit.
Liozu and Hinterhuber (2013)2 surveyed 1,812 professionals involved in pricing and sorted pricing approaches into cost-, competition- and customer value-based. The 1,812 come from three surveys run between March and July 2011 among pricing professionals, chief executives and business owners, and account managers, with response rates of 6% to 12%, and the orientation scales were adapted from Ingenbleek et al. (2003)1. Both studies therefore measure how much each kind of information was taken into account, which this article calls practice. They find value-based pricing positively linked to firm performance. Their negative result for competition-based pricing is a direct path in a model that also contains pricing capabilities and value-based pricing; the simple correlation between competition-based pricing and relative performance in their data is positive (0.17). Their own limitations section sets how far the findings go: “The performance measures used in this research are perceptual”, which they defend as accepted practice in strategy research, and “Like all studies using cross-sectional data, causality is a concern.” It is an association with managers’ assessments of relative performance, not a measured profit effect.
Ingenbleek et al. (2003)1 look at new product performance against the product’s stated objectives and find that “the success of pricing practices is contingent upon relative product advantage and competitive intensity.” Competition information helps locate the ceiling only when a product is close to what competitors offer; when relative advantage is high, the authors call it bad practice, and on its own it showed no significant effect. Customer-value information went with better performance at low, average and high relative advantage, most strongly at high, and was never negative; where competitive intensity was high, its effect fell to about zero.
| Information used | What it tells the firm | Stronger when | Weaker or negative when |
|---|---|---|---|
| Cost information | Where the floor of the price range sits | Competitive intensity was higher (a weak interaction, p < 0.1, one-tailed) | Competitive intensity was lower; the authors call it “bad practice” there |
| Competition information | Where the ceiling sits, for a product close to rivals | Relative product advantage was lower | Relative product advantage was higher; the authors call it “bad practice” there |
| Customer-value information | Where the ceiling sits, most of all for a product hard to compare | Positive at low, average and high relative advantage, strongest at high | Never negative; no detectable effect when competitive intensity was high |
Figure 3How the payoff from price information shifted
No kind of information was best everywhere. The cost and competition rows report interaction terms as the authors read them, not effects measured at each level.
Source: Ingenbleek et al. (2003), pp. 299-301; 77 new industrial products, Belgian sampling frame, single informants.
The two studies are compatible rather than contradictory. Both find customer-value information going with better performance. On competition information, Liozu and Hinterhuber’s2 negative path comes from a model that also contains pricing capabilities and value-based pricing, and Ingenbleek et al.1 found a dependence on relative advantage that the later study did not test. They also measure different outcomes: managers’ assessments of relative firm performance in one, new product performance in the other. The fair reading is narrower than either headline. Customer-value information was not associated with worse performance in either sample, but no single orientation came out right in every situation, and neither design measures what changing strategy would do to profit.
How do you write a pricing strategy down?
Use the record in Figure 1, one row per pricing decision, filled in this order.
- Objective. Name the result the price should help achieve. Profit, volume, adoption and share pull in different directions, and a strategy cannot serve an objective nobody wrote down.
- Situation. Mark every situation that applies: new product, competitive, product line, cost-based. Check whether more than one applies; in the Deere case three did.
- Strategy and its conditions. Name the strategy and the conditions you observe for it, and keep them apart from the general case for the strategy: survey associations show what went with managers’ choices, not what justifies a choice. If no condition can be named, the team has a habit, not a strategy.
- Floor and ceiling inputs. Record the cost information that sets the floor and the competitor and customer-value information that sets the ceiling, and roughly how much each one weighed.
- Reopen when. Name the change that sends the strategy back for review: a new entrant, a shift in capacity, a new related product, a change in how hard demand is to estimate.
The fourth field is where the practice is easiest to mistake for the strategy. A team that says “we are value-based” has described an input. It still has to say what the price is for and why this route fits this situation.
How does the record handle one decision in three situations?
It keeps the three situations, and the routes each one suggests, in separate fields until someone weighs them. Take a hypothetical maker of industrial pumps that launches a new model. The objective is to recover the model’s development cost over its life without weakening service revenue. The decision sits in three situations at once: it is a new product; the market is mature, with two comparable rivals who compete hard on price; and the installed base buys spare parts and service contracts that carry high margins. The example is illustrative; it carries no company data.
The normative case for penetration that Noble and Gruca3 summarise rests on conditions such as a scale advantage and demand that responds to price, so the record should say whether the firm has the scale advantage and how demand responds. Their survey also found penetration where brand demand was inelastic, against that case, so the association is a prompt to check, not a gate. Skimming needs high differentiation in the market, in the normative case and in the survey, and a mature market of comparable models is unlikely to show it. The high margins on parts and service make complementary product pricing a live option. And because the rivals compete hard, the cost floor deserves more attention than usual, on Ingenbleek et al.’s reading. Noble and Gruca (1999) do not say how to weigh those routes into one price, so the record has to say who weighed them and on what grounds.
The last field almost writes itself: a third competitor, a change in parts margins, or a capacity constraint that removes the scale advantage.
Where does the evidence on pricing strategy stop?
None of the studies cited here measures profit objectively, or as the effect of a change in strategy. Noble and Gruca (1999)3 model the strategy managers chose. Liozu and Hinterhuber (2013)2 and Ingenbleek et al. (2003) measure how much each kind of information was used and relate it to self-rated performance scales that include profit items among others: perceived relative performance in a cross-sectional survey in one, new product performance on 77 launches with single informants in the other.
Noble and Gruca3 and Ingenbleek et al.1 sampled industrial firms: US capital goods in 1994, and Belgian electronics and engineering firms with a 13% response. Liozu and Hinterhuber2 sampled members of three professional organisations across manufacturing, service and retail, without reporting a business-to-business share. Applying the framework to software or consumer goods is reasonable as a structure for thinking, and it is an assumption, not a finding. How several strategies combine into one price remains open in this literature.
The neighbouring questions each have their own page: the comparison set under positioning, the ceiling under value-based pricing, the implementation under pricing architecture, and the cross-market case in A global price is not one price.
References
- Ingenbleek, P., Debruyne, M., Frambach, R. T., & Verhallen, T. M. M. (2003). Successful new product pricing practices: A contingency approach. Marketing Letters, 14(4), 289-305. https://doi.org/10.1023/B:MARK.0000012473.92160.3d
- Liozu, S. M., & Hinterhuber, A. (2013). Pricing orientation, pricing capabilities, and firm performance. Management Decision, 51(3), 594-614. https://doi.org/10.1108/00251741311309670
- Noble, P. M., & Gruca, T. S. (1999). Industrial pricing: Theory and managerial practice. Marketing Science, 18(3), 435-454. https://doi.org/10.1287/mksc.18.3.435