I stop listening when a candidate says "cost-plus, value-based, and competition-based pricing" and then never multiplies anything. Naming the three lenses is not the case. The scoring sheet rewards whether you can say, with a contribution margin in hand, how much volume a price rise can lose before profit falls.
That single arithmetic step is what most first-rounds miss. Everything else — floor, rival response, willingness to pay — is there to feed numbers into that calculation, not to decorate a framework slide.
After this piece you should be able to open a pricing prompt with a margin, a proposed hike, a breakeven volume-loss ratio, and three numbered lenses that either support or kill the move.
What the interviewer is actually scoring
In a typical first round of eight, two or three candidates will mention elasticity. One will compute it. The sheet is blunt:
| Signal | What earns the point | What burns it |
|---|---|---|
| Structure | Cost floor, competitor, customer value — each with a figure | Reciting textbook strategies without a number |
| Math | Max volume loss the hike can absorb at stated margin | Price up X%, volume down "a bit," profit "probably up" |
| Insight | Convert meter changes (seat → usage) into comparable $/unit | Treating a repackaging as "alignment with value" |
| Judgment | Recommend with a kill condition (rival match, churn band) | "Raise 10% because value is high" |
Pricing is not a 4Ps tour. If profit fell and you do not know whether list price moved, isolate the driver on a profitability bridge first. When the prompt is "should we raise, cut, or re-meter," stay on pricing and force the volume–margin tradeoff into the open.
Elasticity is a ratio, not a vibe
Own-price elasticity is percent change in quantity divided by percent change in price. Interviewers almost never hand you a clean coefficient. They hand you a promo history, a lost-bid file, or a segment split. You still need a bound, and published estimates are useful as anchors you state with provenance, not as gospel for the case company.
A few durable primary figures:
| Category | Own-price elasticity (approx.) | Provenance |
|---|---|---|
| Soft drinks (U.S. food review) | about −0.79 (mean abs. 0.79) | Andreyeva, Long, Brownell synthesis of U.S. studies (AJPH / PMC) |
| Cigarettes (Europe, panel) | about −0.4 (95% CI roughly −0.67 to −0.24) | Tobschall et al., 2010–2020 European panel (PMC) |
| Gasoline (U.S. short run, 2001–06) | about −0.03 to −0.08 | Hughes, Knittel, Sperling NBER Working Paper 12530 (NBER PDF) |
Food and drink demand is typically inelastic under 1.0 in absolute terms; soft drinks sit toward the more responsive end. Tobacco in high-income Europe clusters near −0.4. Short-run gasoline in the early 2000s looked far less responsive than the 1970s estimates many textbooks still quote. Say the date and the method when you borrow a number. Do not pretend a jacket brand has a published elasticity of −0.79.
In the room, convert the case's crumbs into a range: "Last year a 5% promo lifted units 8% — rough elasticity around −1.6 on the promotional fringe; base demand is stickier. I will stress-test −0.5 to −1.2."
Three lenses, each forced to a number
Cost, competitor, and value are useful only when each produces a constraint you can write down.
Cost (floor). Variable cost per unit, or cash cost in the slow month if fixed costs do not scale. Floor is a constraint, not a destination. Cost-plus 20% on a $12 COGS is $14.40 — usually the wrong answer and always an incomplete one.
Competitor (response). Next-best list price, share you lose at +X%, and whether rivals can match in weeks. A ceiling that ignores a cheaper twin on the same aisle is fiction.
Value (ceiling). What the budget owner pays versus the next-best way to get the job done — not versus "our features." For a consumer SKU that is often private label; for B2B it is the alternative process.
| Lens | Number to put on the page | Fail mode |
|---|---|---|
| Cost | VC $/unit; contribution margin % | Treating margin target as the price |
| Competitor | Rival ASP; estimated share loss if unmatched | Assuming rivals stay put for a year |
| Value | WTP or next-best cost for the buyer | Pricing the feature list, not the job |
The 3Cs tree (company, customer, competitor) maps cleanly here; pricing just insists each branch ends in arithmetic.
The absorbable volume-loss formula
Let contribution margin as a share of price be m = (P − V) / P. Raise price by fraction r (variable cost unchanged). New margin dollars per unit rise by P times r. Profit is flat when volume falls by:
r / (m + r)
That is the maximum volume loss the hike can absorb before contribution dollars decline. If your elasticity (or scenario) implies more volume loss than that ratio, the price rise destroys profit even before fixed costs and competitor retaliation.
Memorize the intuition: at a 40% margin, a 10% price rise can absorb about 0.10 / 0.50 = 20% volume loss. At an 80% software-like margin, the same 10% hike can absorb about 0.10 / 0.90 ≈ 11%. High-margin businesses look "safe" on a slide; they are less tolerant of volume loss for a given percentage hike because each lost unit was carrying a large absolute contribution.
Worked example: GlacierPack soft coolers
Prompt. GlacierPack sells a 24-can soft cooler. Current ASP $120. Variable cost (shell, insulation, zipper, inbound freight) $48. Contribution $72, so (m = 60%). Volume last year: 220,000 units. Marketing proposes an 8% list increase to $129.60 for the next season. A mid-tier rival sits at $109. Private-label coolers at big-box run $70–85. Should GlacierPack take the hike?
Step 1 — absorbable volume loss.
0.08 / (0.60 + 0.08) = 0.08 / 0.68 ≈ 11.8%
If units fall more than about 26,000 (11.8% of 220,000), contribution dollars fall. Write that threshold before debating brand.
| Scenario | Units | ASP | Contribution / unit | Total contribution |
|---|---|---|---|---|
| Base | 220,000 | $120 | $72 | $15.84m |
| +8%, flat volume | 220,000 | $129.60 | $81.60 | $17.95m |
| +8%, −11.8% volume | 194,000 | $129.60 | $81.60 | $15.83m (breakeven) |
| +8%, −18% volume | 180,400 | $129.60 | $81.60 | $14.72m (worse) |
Step 2 — cost lens. Floor is $48. At $129.60 you are nowhere near cash cost. The floor does not block the hike. Winter clearance risk matters if you overproduce: a forced $90 sell-through still clears variable cost but wrecks the planned contribution.
Step 3 — competitor lens. Rival at $109. After the hike the gap widens from $11 to about $21. If 15% of volume is price-shoppers who switch when the gap exceeds $15 (Ned's case assumption — label it as such), you lose 33,000 units — already past the 11.8% breakeven. Match risk: if the rival holds price and spends the differential on retail media, GlacierPack eats the volume; if the rival follows up 5%, industry ASP rises and the volume hit shrinks.
Step 4 — value lens. Buyers who camp monthly may see $130 as still below a hard cooler plus ice runs. Occasional tailgaters compare to the $75 private label. Segment: keep the hike on the flagship SKU sold through specialty outdoor; hold or lightly promote the entry SKU at big-box so you do not teach the whole base a new reference price in one week.
Recommendation. Take +8% on specialty channels where the next-best is another branded soft cooler near $115–125, and watch sell-through for six weeks against the 11.8% volume tripwire. Do not blanket-raise big-box placements until you see whether the rival matches. Kill condition: if specialty units drop more than 12% with no rival match, roll back 4 points rather than "invest through" a profit-negative experiment.
Ned's rule. Before you defend a price rise, compute r / (m + r). If you cannot say that number in one breath, you are not ready to recommend.
What public filings actually disclose
Firms do not publish case-ready elasticities. They publish price/mix versus volume bridges — useful as real-world gravity for your story.
Procter & Gamble's FY 2023 earnings release reported organic sales up 7%, with pricing +9% and mix +1%, partially offset by shipment volume −3%. That is a disclosed price-up, volume-down outcome: pricing still carried organic growth. FY 2024 organic sales grew 4% entirely from pricing, with volume and mix unchanged — a different chapter once inflation cooled.
Coca-Cola's full-year 2024 results showed organic revenue +12%, driven by price/mix +11% and concentrate sales +2%, with unit case volume +1%. Their 10-K risk language is explicit that higher prices can cut volume and push buyers to lower-priced alternatives — the same tradeoff you are modeling, without a single elasticity coefficient on the page.
Use these as pattern evidence ("large CPG brands have recently grown through price while absorbing flat-to-down volume"), not as GlacierPack's elasticity.
Practice this today
Take any product you own (coffee subscription, gym membership, software seat). Write ASP, rough variable cost, and a hypothetical 10% hike. Compute r / (m + r). Then invent one rival price and one next-best alternative. That is a complete pricing mini-case in fifteen minutes.
For timed reps with a live debrief, run a full case on CoachNed: five-minute typed start works without an account; the voice interview is ~18 minutes with a seven-score debrief. Everything is open for seven days, no card; then $120 for a recruiting season or $49 a month. Pricing prompts also sit in the case library and math drills.
Frequently asked questions
What is a pricing strategy case interview?
A pricing case asks where to set list price, whether to raise or cut, or how to change the meter (seat, usage, bundle). You are scored on a cost floor, competitor response, and customer value — each with numbers — and on whether a price change improves contribution after volume moves.
How do you calculate how much volume a price increase can lose?
With contribution margin share m and price increase fraction r, maximum absorbable volume loss is r / (m + r), assuming variable cost per unit stays constant. If expected volume loss exceeds that ratio, contribution dollars fall.
What are the three pricing lenses in a case interview?
Cost (cash floor and margin), competitor (rival price and likely match), and value (buyer willingness versus next-best alternative). Saying the names without figures does not score; each lens should produce a constraint or a scenario input for the elasticity arithmetic.
Do I need a published elasticity number in the interview?
No. Use published estimates only as anchors with sources and dates. In the case, bound elasticity from the exhibits you are given (promos, bid losses, segment splits) and stress-test the recommendation across a range.
When is pricing the wrong first framework?
I stop listening when a candidate says "cost-plus, value-based, and competition-based pricing" and then never multiplies anything. Naming the three lenses is not the case. The scoring sheet rewards whether you can say, with a contribution margin in hand, how much volume a price rise can lose before profit falls.
When you do not know whether price moved and profit is the mystery — start with a profitability bridge. When the product does not exist yet, willingness and attach come before fine-tuning the meter.?
Own-price elasticity is percent change in quantity divided by percent change in price. Interviewers almost never hand you a clean coefficient. They hand you a promo history, a lost-bid file, or a segment split.
Sources
- Andreyeva, Long, Brownell — food price elasticity review (PMC) — U.S. mean own-price elasticities by food category (soft drinks ~0.79 absolute). Checked 2026-09-24.
- Tobschall et al. — cigarette price elasticity in Europe (PMC) — panel estimate near −0.4 for European cigarette demand, 2010–2020. Checked 2026-09-24.
- Hughes, Knittel, Sperling — gasoline demand elasticity (NBER WP 12530) — short-run U.S. gasoline elasticities roughly −0.03 to −0.08 for 2001–06. Checked 2026-09-24.
- P&G FY 2023 Q4 / full-year earnings exhibit (SEC) — organic sales +7% with pricing +9%, mix +1%, volume −3%. Checked 2026-09-24.
- P&G FY 2024 Q4 / full-year earnings exhibit (SEC) — organic sales +4% from pricing; volume and mix flat. Checked 2026-09-24.
- Coca-Cola reports Q4 and full year 2024 results — organic revenue +12%, price/mix +11%, unit case volume +1%. Checked 2026-09-24.
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