CRO / Pricing
Ecommerce Pricing Strategy and Psychology
// price is the fastest lever on profit, and the scariest to touch
By Fracto Solutions
October 28, 2026
The short answer
Pricing is deciding what to charge and how to present it. Price has more leverage on profit than volume, but only if you hold volume, and retail demand is usually elastic. Set prices from margin and perceived value, and test every change rather than trusting textbook effects.
11.1%
-2.62
19 of 19
Why does pricing strategy matter beyond covering costs?
Because price has more leverage on profit than volume does. The classic measurement is from Marn and Rosiello at McKinsey, writing in Harvard Business Review in 1992: for the average company in a Compustat aggregate of 2,463 firms, a 1% improvement raised operating profit by 11.1% on price against 3.3% on volume.
That figure is real and worth knowing, and it comes with a condition that is almost always dropped when it is quoted: it assumes no volume loss. The same paper notes the symmetry, that a 1% price cut destroys 11.1% of operating profit. It is also 34 years old and based on early-1990s large-cap industrial cost structures, not ecommerce.
Hold that condition in mind, because it cuts against the other thing you will read everywhere. Meta-analyses of retail price elasticity put the mean at -1.76 (Tellis, 1988, 367 estimates) and -2.62 (Bijmolt et al., 2005, 1,851 estimates across 81 studies), and online channels tend to be more elastic than offline. Demand is usually elastic, which means the no-volume-loss case is the exception rather than the rule. The honest version of the pricing-leverage argument is: price is the highest-leverage lever per unit of volume held, so the whole job is finding the increases that do not cost you volume, and measuring rather than assuming.
Pricing also interacts with everything else. It frames perceived value on the product page, shapes average order value, and determines how much room you have for discounts without wrecking margin.
Does price psychology actually work?
Some of it does, some of it is narrower than advertised, and at least one popular rule is not what the underlying research found. We would rather give you the replication status than a tidy list of tactics.
Here is where each of the four big ones actually stands:
Tactic
Evidence
How much to rely on it
Anchoring (explicit reference price)
Many Labs 1: 4 of 4 replicated, d = 1.27 to 2.60, n = 6,344
Solid, but field effects are far smaller
Charm pricing ($X.99)
Real across a leading-digit boundary only; one large 2022 null
Worth testing, not assuming
Good-better-best tiers
+8 to +17 points of share in 1989 lab work; weak on absolute share
Shifts mix, rarely grows demand
Decoy / asymmetric dominance
Null in 27 of 38 studies and in all 19 with realistic products
Do not build on it
Anchoring is the only one of the four on solid replication footing, and only in its classic form where the shopper explicitly considers the reference number.
People do judge prices relative to references rather than in a vacuum, which is the durable insight underneath all of this. What does not hold is the idea that these are reliable levers you can pull for a predictable result. That is exactly why we test rather than assume, and it is the whole argument of charm pricing and anchoring explained.
How should I set my prices?
From value and margin, not cost alone. Start with your required margin and your customer’s perceived value and alternatives, then position within that range. Cost sets the floor; value and competition set the ceiling.
Cost-plus is simple but blind: it prices off your costs instead of the customer’s perception. A better approach brackets the price between a margin floor and a value ceiling, then positions deliberately within it. We should flag that this is our operating framework from client work rather than a research finding, though it follows from the elasticity evidence: if demand responds strongly to price in your category, the cost-plus number is unlikely to be the profit-maximising one by accident. Local and market context matters too if you sell across regions, as covered in international selling.
How do I use anchoring and tiering?
Anchoring is the one tactic here with strong replication behind it, so use it, with genuine references. Tiering shifts which option people pick more than it grows demand, so treat it as mix management rather than a revenue lever.
On anchoring: Many Labs 1 tested four classic anchoring items across 36 sites and 6,344 participants and replicated all four with effect sizes larger than the originals. The important boundary is that this holds for anchors the person explicitly considers. Incidental, background numbers failed in Many Labs 2 at d = 0.04. And the huge lab effects come from numeric estimation tasks; realistic consumer settings produce something closer to d = 0.2, so expect a nudge rather than a transformation.
On tiering: Simonson’s 1989 work found options gained on average 17.5 percentage points of share when placed in the middle, which is a real effect. But a 2023 meta-analysis of 23 papers and 29,538 observations found the compromise effect moves relative choice share while only weakly affecting absolute choice share. In plain terms, three tiers change which thing people buy, not reliably whether they buy. That is still useful if the middle tier is your best-margin product. It is not a conversion tactic, and we would not describe good-better-best as one of the most reliable structures available, because the decoy logic usually offered alongside it is null in every published study that used realistic products.
The one hard rule: the anchor must be genuine. A fabricated “was” price is not just a trust problem, it is regulated, and the rules differ by market. See the mistakes section below.
How do I raise prices without losing customers?
Raise deliberately and with communication: increase in steps, tie it to value, forewarn or grandfather loyal customers, and test the impact on total gross profit rather than units. Note that advance notice is legally required in several places, not merely courteous.
Price increases are often less damaging than founders fear, but given mean elasticities around -1.8 to -2.6 you should treat that as a hypothesis about your category rather than a general rule. For subscriptions, California’s amended Automatic Renewal Law (AB 2863, effective 1 July 2025) requires clear and conspicuous notice between 7 and 30 days before a changed fee takes effect, with cancellation instructions, and Arkansas, New York, Colorado and Massachusetts have their own versions. The full approach is in how to raise prices without losing customers.
What are the common pricing mistakes?
Pricing purely on cost, never revisiting prices, over-relying on discounts, treating lab effects as reliable levers, and using reference prices that will not stand up. The last one has moved from an ethics question to a compliance question.
On reference pricing, the rules differ sharply by market and all three matter if you sell internationally. In the US, FTC 16 CFR Part 233 requires a former price to be “the actual, bona fide price at which the article was offered to the public on a regular basis for a reasonably substantial period of time”, and California adds a three-month prevailing-market-price test with real class-action exposure. In the EU, Price Indication Directive Article 6a, applicable since 28 May 2022, requires any announcement of a price reduction to state the lowest price you applied in at least the previous 30 days, and the CJEU confirmed in Aldi Sued (C-330/23, September 2024) that a percentage reduction must be calculated on that figure. In the UK the DMCC Act applies from 6 April 2025 with direct CMA fines up to 10% of global turnover, and the High Court in CMA v Emma Sleep (July 2026) replaced the CMA’s proposed fixed volume ratio with a contextual test, so keep contemporaneous evidence for any reference price you use. General information, not legal advice.
The other mistake is treating price as fixed. Markets, costs and competitors move. Price with intent, review regularly, and lean less on discounts, which train customers to wait and quietly erode margin.
Can I just A/B test prices?
Usually yes, with two real constraints most guides never mention. A randomized holdout on traffic is generally fine; using personal data to set the price is regulated in both New York and the EU.
New York’s Algorithmic Pricing Disclosure Act took effect on 10 November 2025 and requires the disclosure “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA” wherever a price is set algorithmically using personal data such as location, income or shopping history, at $1,000 per violation. A First Amendment challenge by the National Retail Federation failed. In the EU, the Omnibus Directive has required traders to tell consumers when a price has been personalised through automated decision-making since 28 May 2022, with penalties up to 4% of turnover.
Two smaller practical points: the Robinson-Patman Act is about selling commodities to competing resellers, not retail pricing to consumers, so it is not the constraint people fear; and if you run Google Shopping, your landing-page price has to match your feed, which price tests routinely break. Within those limits, testing price is ordinary testing discipline.
How often should I review my prices?
On a cadence plus whenever something material changes: costs, competitors, demand or positioning. Quarterly is a reasonable default for many stores, with event-driven checks in between.
Set a rhythm so pricing does not drift into neglect, and pair the review with evidence: margin by product, sell-through, and how your prices sit against alternatives. Then adjust the outliers and test the changes. This cadence is our recommendation from client work rather than a researched optimum, but the alternative, setting a price once and forgetting it, is the thing the elasticity and leverage evidence both argue against. It is the same measure-and-improve discipline behind our growth-strategy pillar.
We treat price as a tested lever, not a markup you set once.
We look at your margins, perceived value, and competitive context, frame prices with tiering and genuine anchoring, and test changes rather than guessing, because a small, well-judged price move often beats a big push for more traffic.
It’s the same measurement-first discipline behind our conversion optimization and analytics work, where we rebuild the buying path and measure the result .
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Frequently asked questions
Why is pricing such a powerful lever?
Marn and Rosiello found a 1% improvement on price raises operating profit by 11.1% for the average company, against 3.3% for volume. The condition usually dropped from that quote is that it assumes no volume loss, and meta-analyses put mean retail price elasticity between -1.76 and -2.62, so demand is usually elastic. The leverage is real; the no-volume-loss case is what you have to find.
Does charm pricing (ending in .99) actually work?
Sometimes, and more narrowly than the popular version. Thomas and Morwitz found the left-digit effect occurs only when the leading digit changes, so $2.99 against $3.00 works and $3.59 against $3.60 does not. A large 2022 experiment with 4,788 incentivized decisions failed to reproduce it at all. Worth testing on your own prices rather than assuming.
Should premium brands use round numbers?
The rule ’round equals premium’ is not what the research found. Wadhwa and Zhang showed a fit effect: round prices suit emotionally-driven purchases, precise prices suit reason-driven ones, and a round price on a utilitarian purchase can hurt. Separately, Thomas, Simon and Kadiyali found precise prices are judged lower in magnitude and anchored buyers higher.
Is good-better-best pricing effective?
It shifts mix rather than growing demand. Simonson found middle options gained about 17.5 percentage points of share, but a 2023 meta-analysis found the compromise effect only weakly affects absolute choice share. The related decoy tactic is null in 27 of 38 studies and in all 19 that used realistic products, so do not build on that part.
Is it legal to show a 'was' price?
Only if it is genuine, and the test differs by market. US FTC guidance requires a bona fide former price offered on a regular basis for a reasonably substantial period. The EU requires the lowest price applied in at least the previous 30 days, confirmed by the CJEU in 2024. The UK applies a contextual test with CMA fines up to 10% of global turnover.
Sources
Pricing leverage on profit: Marn and Rosiello, “Managing Price, Gaining Profit”, Harvard Business Review 70(5), September to October 1992, both authors then at McKinsey. For the average company in a Compustat aggregate of 2,463 companies, a 1% improvement raises operating profit by 11.1% on price, 7.8% on variable cost, 3.3% on volume and 2.3% on fixed cost. Two conditions we keep attached: the 11.1% figure explicitly assumes no volume loss, and the analysis is 34 years old and based on early-1990s large-cap US industrial cost structures. Read alongside the elasticity evidence above, the no-volume-loss assumption is the thing to test rather than assume. https://pages.charlotte.edu/wp-content/uploads/sites/868/2014/12/ManagingPrice.pdf
Price elasticity: Tellis, “The Price Elasticity of Selective Demand”, Journal of Marketing Research 25(4), 1988: mean price elasticity -1.76 across 367 estimates covering more than 220 brands and markets. Bijmolt, van Heerde and Pieters, “New Empirical Generalizations on the Determinants of Price Elasticity”, Journal of Marketing Research 42(2), 2005: mean -2.62 across 1,851 elasticities in 81 studies, and elasticities have grown more negative over four decades. Online channels tend to be more elastic than offline. So retail demand is typically elastic, which is the opposite of the common claim that shoppers are less price-sensitive than founders fear. https://doi.org/10.1509/jmkr.42.2.141.62296
Anchoring: Tversky and Kahneman, “Judgment under Uncertainty”, Science 185(4157), 1974. Replication status matters here and it splits. Classic, explicitly-considered anchoring replicated strongly in Many Labs 1 (Klein et al., Social Psychology 45(3), 2014): four anchoring items across 36 sites and 6,344 participants, all four replicating with effect sizes larger than the originals, d from 1.27 to 2.60. Incidental or background anchoring failed in Many Labs 2 (Klein et al., 2018, 15,305 participants): d = 0.04, 95% CI from -0.01 to 0.09. Note also that the large Many Labs 1 effects come from numeric estimation tasks, not purchase decisions; field estimates in consumer settings are around d = 0.2. https://doi.org/10.1027/1864-9335/a000178
Charm pricing and the left-digit effect: Thomas and Morwitz, “Penny Wise and Pound Foolish: The Left-Digit Effect in Price Cognition”, Journal of Consumer Research 32(1), 2005, five lab experiments on student samples. The effect occurs only when the leftmost digit changes: $2.99 against $3.00 produces it, $3.59 against $3.60 does not. Field evidence: Anderson and Simester, “Effects of $9 Price Endings on Retail Sales”, Quantitative Marketing and Economics 1(1), 2003, three randomized mail-order catalog experiments. In the clothing test, a $39 dress outsold the same dress at $34, with 66 units at 9-ending prices against 43 at $5 less and 48 at $5 more; those unit counts are small, it is one apparel category, and the data is from 1990s catalogs. The effect was stronger for new products than established ones and weaker when a “Sale” cue was already shown. https://doi.org/10.1086/429600
The failed replication: Fenneman, Sickmann, Fullbrunn, Goldbach and Pitz, “Psychological price perception may exert a weaker effect on purchasing decisions than previously suggested”, PLOS ONE 17(8), 2022, e0270850. 266 participants, 4,788 incentivized purchasing decisions with systematically varied prices. It found no support for either the left-digit effect or the perceptual-fluency effect behind round pricing. A 2020 Journal of Marketing Research extension of the left-digit bias was independently replicated with the key interaction only marginally significant. We report the effect as real but boundary-conditional and contested, which is what the literature supports. https://doi.org/10.1371/journal.pone.0270850
Round versus precise prices: Wadhwa and Zhang, “This Number Just Feels Right”, Journal of Consumer Research 41(5), 2015, five experiments. The finding is a fit effect, not a premium effect: rounded prices encourage reliance on feelings and non-rounded prices on cognition, and products are evaluated more favorably when the format matches the purchase motivation. A round price on a utilitarian purchase can hurt. Pointing the other way, Thomas, Simon and Kadiyali, “The Price Precision Effect”, Marketing Science 29(1), 2010, found precise prices are judged lower in magnitude than round ones, and in residential real-estate market data buyers paid higher prices when list prices were more precise. The blanket rule “round equals premium” is not supported. https://doi.org/10.1086/678484 and https://doi.org/10.1287/mksc.1090.0512
Good-better-best and the compromise effect: Simonson, “Choice Based on Reasons”, Journal of Consumer Research 16(2), 1989: 372 business students across three universities; options gained on average 17.5 percentage points of share when positioned as the middle option, ranging from +8 for televisions to +16 for apartments. Its sibling, the decoy or attraction effect, largely does not survive: Frederick, Lee and Baskin, “The Limits of Attraction”, Journal of Marketing Research 51(4), 2014, ran 38 studies and found no significant attraction effect in 27 of them, including all 19 that used realistic stimuli, with repulsion effects in several. A 2023 meta-analysis of 23 papers and 29,538 observations found the compromise effect moves relative choice share but only weakly affects absolute choice share, which is the number a merchant cares about. https://doi.org/10.1509/jmr.12.0061
Reference and “was” prices: in the US, the FTC Guides Against Deceptive Pricing, 16 CFR Part 233. §233.1 requires a former price to be “the actual, bona fide price at which the article was offered to the public on a regular basis for a reasonably substantial period of time”, and condemns an “artificial, inflated price established for the purpose of enabling the subsequent offer of a large reduction”. These are guides enforced through FTC Act §5 and state law; California Business and Professions Code §17501 adds a three-month prevailing market price test with class-action exposure. In the EU, Price Indication Directive 98/6/EC Article 6a, inserted by the Omnibus Directive and applicable from 28 May 2022, requires any announcement of a price reduction to state the lowest price applied in at least the previous 30 days, with penalties of at least 4% of turnover; the CJEU confirmed in Case C-330/23 (Aldi Sued, 26 September 2024) that a percentage reduction must be calculated on that 30-day lowest price. In the UK the DMCC Act 2024 applies from 6 April 2025 with direct CMA fines up to 10% of global turnover, and the High Court in CMA v Emma Sleep (30 July 2026) rejected a fixed volume ratio in favour of a contextual test. https://eur-lex.europa.eu/eli/dir/1998/6/2022-05-28/eng
Stated as Fracto’s position, not research: that most stores under-work pricing and set it once by cost-plus, that a quarterly review plus event-driven checks is a sensible cadence, and that price should be bracketed between a margin floor and a value ceiling. These reflect client work rather than published research. Where we cite an effect above, we also give its replication status, because several famous pricing-psychology results do not hold up as well as their popularity suggests.