Pricing Workbench

Module 1 · Evaluate a change

Should these products be sold as a bundle?

The model runs in eight steps for two to four products, each with its own pricing model. Fields with a teal underline are inputs you can change. Each label has a definition behind its i button, and each result is calculated from the fields to its left.

example Prefilled with an enterprise bundle of Stripe Tax and Radar. Every field can be changed, and changes are saved in this browser.
01 / 08

Decision

The question, the success measure, and the period are written down before any number is entered, which keeps the model on the question being asked.

02 / 08

Baseline

The baseline is what one customer pays today for each product bought separately at published prices. Every later result is compared with it.

Customer profile

One illustrative account. All three inputs can be changed.

Annual volumeAnnual volumeThe dollar value of payments a customer settles in a year.Also calledTPV, payment volume$
Average ticketAverage ticketThe average dollar amount of one settled transaction.Watch forA single average hides the spread. Real accounts have a distribution of tickets.Also calledAOV, average order value$
Settle rateSettle rateSettled transactions as a share of screened transactions.ExampleAt 92%, every 100 settled payments took about 109 screens.%
list price

A share of each transaction, up to a maximum fee.

Average ticketAverage ticketThe average dollar amount of one settled transaction.Watch forA single average hides the spread. Real accounts have a distribution of tickets.Also calledAOV, average order value$20.00
Tax list ratePercentage rateThe share of each transaction's amount charged as a fee.Example0.50% of a $20 sale is $0.10.%
Tax list capCapThe most a percentage fee charges on one transaction.Example0.50% capped at $0.50 stops growing at a $100 sale.Watch forAbove the cap the effective rate falls as tickets grow, with no change in price.$
Annual unitsAnnual unitsHow many units of a product one customer uses in a year: settled transactions, screened transactions, or a count you enter such as seats or API calls.25,000,000
Tax at listAnnual feeA year of one product's fees for this customer under one pricing model.$2,500,000
list price

The same fee for every unit.

Radar list fee per unitFee per unitA fixed fee for each unit, whatever the transaction amount.Example$0.07 per screened transaction.$
Annual unitsAnnual unitsHow many units of a product one customer uses in a year: settled transactions, screened transactions, or a count you enter such as seats or API calls.27,173,913
Radar at listAnnual feeA year of one product's fees for this customer under one pricing model.$1,902,174

A-la-carte bill Stripe's published prices as of 2026-09-21

Tax at list$2,500,000
Radar at list$1,902,174
A-la-carte totalA-la-carte totalWhat the customer pays for every product in the bundle bought separately at published prices.Also calledlist total$4,402,174

The bundle can hold 2 to 4 products. Adding or removing a product rebuilds the account segments in step 4.

03 / 08

Drivers

Every usage fee multiplies a count of units. Payments that settle and attempts that are screened both come from the customer profile. Screening counts every attempt, including attempts that fail, so its count is larger.

Annual volumeAnnual volumeThe dollar value of payments a customer settles in a year.Also calledTPV, payment volume$500,000,000
Average ticketAverage ticketThe average dollar amount of one settled transaction.Watch forA single average hides the spread. Real accounts have a distribution of tickets.Also calledAOV, average order value$20.00
Settled transactionsSettled transactionsPayments that complete.FormulaAnnual volume ÷ Average ticket = Settled transactions25,000,000
Settled transactionsSettled transactionsPayments that complete.FormulaAnnual volume ÷ Average ticket = Settled transactions25,000,000
Settle rateSettle rateSettled transactions as a share of screened transactions.ExampleAt 92%, every 100 settled payments took about 109 screens.92.0%
Screened transactionsScreened transactionsPayment attempts that are screened, including ones that are blocked or fail.FormulaSettled transactions ÷ Settle rate = Screened transactionsWatch forThere are always at least as many screens as settled payments.27,173,913
ProductUnitAnnual unitsAnnual unitsHow many units of a product one customer uses in a year: settled transactions, screened transactions, or a count you enter such as seats or API calls.
TaxSettled transactions25,000,000
RadarScreened transactions27,173,913

Annual volume, average ticket, settle rate, and each product's unit are set in step 2.

04 / 08

Assumptions

These inputs describe how accounts respond, and none of them can be looked up. Each one shows its source. The account counts and rates below are placeholders until real account data replaces them.

Who takes the bundle, by Account segmentAccount segmentA group of accounts that responds to the bundle in the same way, defined by which products they already use.

estimate

A segment is a group of accounts that buy the same products at list today. Tick the products a segment already buys. An account that takes the bundle ends up on every product.

InputsResults
SegmentAlready buysAccountsTake-up rateTake-up rateThe share of a segment's accounts that move to the bundle.EffectPer accountPer year
On every product
%Give-up($771,739)($15,434,783)
Payments + Radar, adds Tax
%Attach gain$1,728,261$20,739,130
Payments + Tax, adds Radar
%Attach gain$1,130,435$13,565,217
New deals quotedNothing yet%Win rate changeWin rate changeThe change in the share of quoted deals won because the bundle is on offer.$3,630,435$9,076,087

Every account in a segment uses the customer profile from step 2. Real segments have a spread of volumes and tickets, which is the first data to pull before relying on the totals.

Cost to serveCost to serveWhat it costs to deliver the product to one customer for one period, or one unit.Watch forIt is usually fixed in dollars, so raising price widens the margin percentage. Costs that scale with price, like processing fees, are entered separately. for a newly attached product

estimate
Tax cost per settled transaction$
Radar cost per screened transaction$

These are the weakest inputs in the model, so step 6 solves for the cost at which an attach stops adding contribution and compares your entry with it.

05 / 08

Calculations

The bundle bill is built the same way as the baseline. It then has to pass two tests: the discount has to be recoverable, and the bundle can never cost less than a smaller set of its products at list. The price floors for the second test are solved first, so they can guide the bundle prices as they are set.

Price floors from rule 2Bundle floor (rule 2)The bundle must never cost less than a smaller set of its products at list price.ExampleIn the example at a $100 ticket, the bundle is $2,326,087 and Tax alone is $2,500,000, so the rule fails.Watch forIt has to hold at every ticket size. A check at a few sample tickets can miss a failing range.Also calledtwo-product floor

Each bundle price has a floor: the lowest value at which the bundle still costs at least as much as any smaller set of its products at list, at every ticket in the range. The floors come from the list prices, the customer profile, and the other bundle prices as they stand, so moving one slider moves the other floors.

Lowest average ticket$
Highest average ticket$
Tax bundle rate
0.40% now, 0.50% at list
0.00%floor 0.44%list 0.50%
Below its floor of 0.44%.
Tax bundle cap
$0.44 now, $0.50 at list
$0.00list $0.50
No value up to list keeps the rule. Another price has to move first.
Radar bundle fee per unit
$0.0600 now, $0.0700 at list
$0.0000list $0.0700
No value up to list keeps the rule. Another price has to move first.

Green is the range that keeps rule 2 across average tickets from $5 to $500. A floor is found by testing prices between zero and list until the lowest passing one is isolated, then confirming it at every cent of the ticket range. Tier prices and included units are not given floors.

Bundle bill

Each product keeps its pricing model in the bundle. Only its prices change.

Average ticketAverage ticketThe average dollar amount of one settled transaction.Watch forA single average hides the spread. Real accounts have a distribution of tickets.Also calledAOV, average order value$20.00
Tax bundle ratePercentage rateThe share of each transaction's amount charged as a fee.Example0.50% of a $20 sale is $0.10.%
Tax bundle capCapThe most a percentage fee charges on one transaction.Example0.50% capped at $0.50 stops growing at a $100 sale.Watch forAbove the cap the effective rate falls as tickets grow, with no change in price.$
Annual unitsAnnual unitsHow many units of a product one customer uses in a year: settled transactions, screened transactions, or a count you enter such as seats or API calls.25,000,000
Tax in the bundleAnnual feeA year of one product's fees for this customer under one pricing model.$2,000,000
Radar bundle fee per unitFee per unitA fixed fee for each unit, whatever the transaction amount.Example$0.07 per screened transaction.$
Annual unitsAnnual unitsHow many units of a product one customer uses in a year: settled transactions, screened transactions, or a count you enter such as seats or API calls.27,173,913
Radar in the bundleAnnual feeA year of one product's fees for this customer under one pricing model.$1,630,435
Tax in the bundle$2,000,000
Radar in the bundle$1,630,435
Bundle totalBundle totalWhat the customer pays for every product together at bundle prices.$3,630,435
Bundle totalBundle totalWhat the customer pays for every product together at bundle prices.$3,630,435
A-la-carte totalA-la-carte totalWhat the customer pays for every product in the bundle bought separately at published prices.Also calledlist total$4,402,174
Bundle discountBundle discountHow much less the bundle costs than the same products bought separately.Formula1 − Bundle total ÷ A-la-carte total = Bundle discountExample1 − $3,630,435 ÷ $4,402,174 = 17.5%.17.5%
Bundle discountBundle discountHow much less the bundle costs than the same products bought separately.Formula1 − Bundle total ÷ A-la-carte total = Bundle discountExample1 − $3,630,435 ÷ $4,402,174 = 17.5%.17.5%
Bundle discountBundle discountHow much less the bundle costs than the same products bought separately.Formula1 − Bundle total ÷ A-la-carte total = Bundle discountExample1 − $3,630,435 ÷ $4,402,174 = 17.5%.17.5%
Breakeven volume gainBreakeven volume gainThe extra volume a price cut or discount must win to keep revenue flat.FormulaPrice cut ÷ ( 1 − Price cut ) = Breakeven volume gainExampleA 20% cut needs 25% more volume. A 17.5% bundle discount needs 21.3%.Watch forThe gain needed is always larger than the cut. It is a revenue test. When each unit has a cost to serve, keeping contribution flat needs a larger gain.21.3%

The last line reads: a discount of 17.5% needs 21.3% more revenue per account to break even. Step 6 shows where the extra revenue has to come from.

Bundle floor (rule 2)Bundle floor (rule 2)The bundle must never cost less than a smaller set of its products at list price.ExampleIn the example at a $100 ticket, the bundle is $2,326,087 and Tax alone is $2,500,000, so the rule fails.Watch forIt has to hold at every ticket size. A check at a few sample tickets can miss a failing range.Also calledtwo-product floor

PASS
At this customer's $20.00 ticket: the bundle is $3,630,435. Radar alone is $1,902,174 at list. Tax alone is $2,500,000 at list.
FAIL
Across every ticket from $5 to $500: the rule fails for average tickets from $65.22 to $108.69. The worst point is a $100.00 ticket, where a customer on this volume pays $173,913 less for the bundle than for the same products without Radar at list. In that range Radar is priced below zero.
Price per settled transaction, by ticket size
Rule 2 holds where the bundle line is on or above every other line. Each of those lines is the list price of the bundle's products with one left out.
Why a bundle can fail in a range and what fixes it

A bundle discounts every product at once. When one product's discount grows with the ticket and another product's bundle price is a fixed amount, there can be a range where the growing discount is larger than the fixed amount. In that range the whole bundle costs less than the first product alone. A check at a few sample ticket sizes can pass while a range between them fails, so the sweep tests 49,501 ticket sizes, one cent apart.

In the example, Tax at list is 0.50% of the ticket and Tax in the bundle is 0.40%, while Radar in the bundle adds a fixed $0.0652 per settled transaction. A check at $5, $20, and $500 passes because all three sit outside the failing range. The variant preset raises the bundle rate to 0.44% and keeps the $0.44 cap. It passes at every ticket, and the discount at a $20 ticket falls from 17.5% to 13.0%.

06 / 08

Outputs

A customer discount is a different number on the seller's side, and the sign depends on which accounts take the bundle. Accounts already on every product give up revenue. Accounts adding a product bring new revenue. This section is the forecast.

Per account, no counts needed

Give-upGive-upRevenue lost when an account already paying list price for every product moves to the bundle.FormulaA-la-carte total − Bundle total = Give-upExample$4,402,174 − $3,630,435 = $771,739 a year.Watch forIt assumes the account pays list today. A large account with a negotiated discount gives up less.Also calledcannibalization, dilution
$771,739
An account on every product moving to the bundle
Processing-rate equivalentProcessing-rate equivalentThe cut in the processing rate that would cost the same as the bundle discount, in basis points.FormulaGive-up ÷ Annual volume × 10,000 = Processing-rate equivalentExample$771,739 ÷ $500,000,000 = 15.4 bps.Watch forOne basis point is 0.01% of payment volume. Net revenue after network costs is a small share of volume, so the same dollars are a much larger share of net revenue.
15.4 bps
The same concession expressed as a rate on payment volume
Contribution given upContribution given upThe share of an account's contribution that the bundle discount removes, for an account already paying list for every product.FormulaGive-up ÷ ( A-la-carte total − Cost to serve ) = Contribution given upExample$771,739 ÷ ($4,402,174 − $1,043,478) = 23.0%, against a 17.5% discount.Watch forThe cost to serve does not fall with the price, so the share of contribution is always larger than the discount. It is only as good as the cost estimates.
23.0%
Against a 17.5% discount on the bill
A-la-carte totalA-la-carte totalWhat the customer pays for every product in the bundle bought separately at published prices.Also calledlist total$4,402,174
Bundle totalBundle totalWhat the customer pays for every product together at bundle prices.$3,630,435
Give-upGive-upRevenue lost when an account already paying list price for every product moves to the bundle.FormulaA-la-carte total − Bundle total = Give-upExample$4,402,174 − $3,630,435 = $771,739 a year.Watch forIt assumes the account pays list today. A large account with a negotiated discount gives up less.Also calledcannibalization, dilution$771,739
Give-upGive-upRevenue lost when an account already paying list price for every product moves to the bundle.FormulaA-la-carte total − Bundle total = Give-upExample$4,402,174 − $3,630,435 = $771,739 a year.Watch forIt assumes the account pays list today. A large account with a negotiated discount gives up less.Also calledcannibalization, dilution$771,739
Annual volumeAnnual volumeThe dollar value of payments a customer settles in a year.Also calledTPV, payment volume$500,000,000
Processing-rate equivalentProcessing-rate equivalentThe cut in the processing rate that would cost the same as the bundle discount, in basis points.FormulaGive-up ÷ Annual volume × 10,000 = Processing-rate equivalentExample$771,739 ÷ $500,000,000 = 15.4 bps.Watch forOne basis point is 0.01% of payment volume. Net revenue after network costs is a small share of volume, so the same dollars are a much larger share of net revenue.15.4 bps
Give-upGive-upRevenue lost when an account already paying list price for every product moves to the bundle.FormulaA-la-carte total − Bundle total = Give-upExample$4,402,174 − $3,630,435 = $771,739 a year.Watch forIt assumes the account pays list today. A large account with a negotiated discount gives up less.Also calledcannibalization, dilution$771,739
A-la-carte totalA-la-carte totalWhat the customer pays for every product in the bundle bought separately at published prices.Also calledlist total$4,402,174
Cost to serve every productCost to serveWhat it costs to deliver the product to one customer for one period, or one unit.Watch forIt is usually fixed in dollars, so raising price widens the margin percentage. Costs that scale with price, like processing fees, are entered separately.$1,043,478
Contribution given upContribution given upThe share of an account's contribution that the bundle discount removes, for an account already paying list for every product.FormulaGive-up ÷ ( A-la-carte total − Cost to serve ) = Contribution given upExample$771,739 ÷ ($4,402,174 − $1,043,478) = 23.0%, against a 17.5% discount.Watch forThe cost to serve does not fall with the price, so the share of contribution is always larger than the discount. It is only as good as the cost estimates.23.0%

The discount takes 17.5% off the bill and 23.0% off the contribution this account brought in, because the cost to serve does not fall with the price. The cost is the step 4 estimate for every product in the bundle, so the share moves with it.

Adding one product through the bundle

Each row is an account that already buys the other products at list and adds this one by taking the bundle. The cost columns compare the cost entered in step 4 with the cost at which the attach adds zero contribution.

Product addedAttach gainAttach gainNew revenue when an account that buys the other products adds one more through the bundle.FormulaBundle total − List total of the other products = Attach gainExampleIn the example, a Payments + Tax account adding Radar: $3,630,435 − $2,500,000 = $1,130,435.Watch forIt nets off the discount the account now gets on the products it already had.Attaches per give-upAttach breakeven ratioNew attaches needed for each cannibalized account to keep revenue flat.FormulaGive-up ÷ Attach gain = Attach breakeven ratioExample$771,739 ÷ $1,130,435 = 0.68 Radar attaches per three-product account.Watch forIt needs no account counts. It is a revenue test, and contribution also depends on cost to serve.Breakeven costBreakeven cost to serveThe cost per unit above which attaching a product through the bundle loses money.FormulaAttach gain ÷ Annual units = Breakeven cost to serveExample$1,130,435 ÷ 27,173,913 screens = $0.0416 per screen.Watch forIt is the zero-contribution line. A required margin sets a lower ceiling.Cost enteredResult
Tax$1,728,2610.45$0.0691$0.0200Adds contribution
Radar$1,130,4350.68$0.0416$0.0200Adds contribution
Bundle totalBundle totalWhat the customer pays for every product together at bundle prices.$3,630,435
Tax alone at listList total of the other productsWhat the customer pays at published prices for every product in the bundle except one.ExampleIn the example, the bundle without Radar is Tax alone: $2,500,000.$2,500,000
Attach gain, adds RadarAttach gainNew revenue when an account that buys the other products adds one more through the bundle.FormulaBundle total − List total of the other products = Attach gainExampleIn the example, a Payments + Tax account adding Radar: $3,630,435 − $2,500,000 = $1,130,435.Watch forIt nets off the discount the account now gets on the products it already had.$1,130,435
Give-upGive-upRevenue lost when an account already paying list price for every product moves to the bundle.FormulaA-la-carte total − Bundle total = Give-upExample$4,402,174 − $3,630,435 = $771,739 a year.Watch forIt assumes the account pays list today. A large account with a negotiated discount gives up less.Also calledcannibalization, dilution$771,739
Attach gain, adds RadarAttach gainNew revenue when an account that buys the other products adds one more through the bundle.FormulaBundle total − List total of the other products = Attach gainExampleIn the example, a Payments + Tax account adding Radar: $3,630,435 − $2,500,000 = $1,130,435.Watch forIt nets off the discount the account now gets on the products it already had.$1,130,435
Attach breakeven ratioAttach breakeven ratioNew attaches needed for each cannibalized account to keep revenue flat.FormulaGive-up ÷ Attach gain = Attach breakeven ratioExample$771,739 ÷ $1,130,435 = 0.68 Radar attaches per three-product account.Watch forIt needs no account counts. It is a revenue test, and contribution also depends on cost to serve.0.68
Attach gain, adds RadarAttach gainNew revenue when an account that buys the other products adds one more through the bundle.FormulaBundle total − List total of the other products = Attach gainExampleIn the example, a Payments + Tax account adding Radar: $3,630,435 − $2,500,000 = $1,130,435.Watch forIt nets off the discount the account now gets on the products it already had.$1,130,435
Radar units per yearAnnual unitsHow many units of a product one customer uses in a year: settled transactions, screened transactions, or a count you enter such as seats or API calls.27,173,913
Breakeven Radar cost per screened transactionBreakeven cost to serveThe cost per unit above which attaching a product through the bundle loses money.FormulaAttach gain ÷ Annual units = Breakeven cost to serveExample$1,130,435 ÷ 27,173,913 screens = $0.0416 per screen.Watch forIt is the zero-contribution line. A required margin sets a lower ceiling.$0.0416

Radar cost per screened transaction entered: $0.0200. That is $0.0216 under breakeven, so each attach adds contribution.

Across segments: full-year run rate once adoption is complete

estimate
CannibalizationCannibalizationExisting full-price revenue that a new offer replaces with discounted revenue. The give-up, summed across accounts.
($15,434,783)
Attach gains
$34,304,348
Net revenue impactNet revenue impactAttach gains and new deals, less the give-up, across all segments for a year.
$27,945,652
Net contribution impactNet contribution impactNet revenue impact less the cost to serve the newly attached products.
$12,815,217
Year one by quarter: net revenue impact as the Adoption curveAdoption curveThe share of eventual take-up reached by each quarter.Watch forExisting accounts can move at once while new attaches build slowly, so the early quarters look worst. builds
Year one comes to $11,677,989, against a run rate of $27,945,652, because accounts already on every product move at once while attaches and new deals reach 25%, 50%, 75%, 100% of their yearly run rate by quarter. The difference is timing, and both figures use the same assumptions.
Q1 ($1,147,418)Q2 $1,563,859Q3 $4,275,136Q4 $6,986,413Year one $11,677,989
07 / 08

Sensitivity

Each assumption moves across a range while the others stay fixed. The table ranks them by how far net contribution moves, which shows where a wrong input would change the answer.

AssumptionTested rangeNet contribution, low to highSwingSensitivityHow much the result moves when one assumption moves and the rest stay put.Watch forMoving one input at a time hides cases where two inputs move together.
Take-up: On every product25.0% to 75.0%$20,532,609 to $5,097,826
$15,434,783
Take-up: Payments + Radar, adds Tax10.0% to 30.0%$5,445,652 to $20,184,783
$14,739,130
Radar cost per screened transaction$0.0100 to $0.0300$16,755,435 to $8,875,000
$7,880,435
Tax cost per settled transaction$0.0100 to $0.0300$16,440,217 to $9,190,217
$7,250,000
Take-up: Payments + Tax, adds Radar10.0% to 30.0%$9,293,478 to $16,336,957
$7,043,478
Win rate change2.5% to 7.5%$9,581,522 to $16,048,913
$6,467,391
Settle rate87.0% to 97.0%$13,221,264 to $12,451,031
$770,233
Average ticket$10.00 to $30.00$12,630,435 to $12,876,812
$246,377

Breakeven assumption valueBreakeven assumption valueThe value of an assumption at which the change exactly matches the baseline.ExampleAt $7 the cohort is worth the same as today if monthly churn reaches 6.9%.Watch forIt measures the room for error. It does not say how likely that value is.: net contribution is zero when 2.6% of the segment "Payments + Radar, adds Tax" takes the bundle. You entered 20.0%.

Two assumptions at once: net contribution by take-up and ticket size

Rows are the take-up rate among accounts already on every product, which is the give-up. Columns are the average ticket. Every other input stays as entered. The outlined cell is the current scenario.

Take-up \ Ticket$5$10$20$50$100$200$500
0%$44.0M$33.5M$28.2M$25.1M$24.1M$14.7M$5.9M
25%$28.1M$23.1M$20.5M$19.0M$18.5M$12.9M$5.2M
50%$12.3M$12.6M$12.8M$12.9M$13.0M$11.1M$4.5M
75%($3.6M)$2.2M$5.1M$6.8M$7.4M$9.4M$3.7M
100%($19.5M)($8.2M)($2.6M)$752K$1.9M$7.6M$3.0M
Adds contribution Loses contribution, shown in parenthesesDeeper color is a larger amount.
08 / 08

Validation

The checks to run before committing to the price, the comparisons to make after launch, and the questions this model leaves open.

Before committing

  • Pull the ticket distribution of real accounts. Rule 2 and attach gain both change with ticket size, and this model gives every account one average.
  • Count accounts in each segment, and the discounts that accounts on every product already have. A negotiated discount shrinks the give-up.
  • Get the cost to serve each product from finance and compare it with the breakeven costs in step 6.
  • Quote a sample of live deals both ways and record which offer the customer picks.

After launch

  • Compare each quarter with this forecast, split into volume, mix, and price.
  • Track realized price against the bundle's published price to catch discounting on top of the bundle.
  • Watch take-up among accounts already on every product first. It arrives earliest and every dollar of it is give-up.

What this model cannot prove

  • How accounts will respond. The take-up and win rates are estimates with no data behind them yet. A pricing test or real account data is needed to confirm them.
  • Net revenue after the base product's costs. The base product's price is held constant, so a bundle discount traded against it does not show up.
  • Ramp within a deal. Volumes are a full year at steady state.

Send this forecast to Explain a miss

Module 2 takes one quarter of this forecast as its plan and compares it with what happened. The table shows what will be sent.

Line, quarter 1Settled transactionsRevenue per transactionRevenue
Tax and Radar at list125,000,000$0.1761$22,010,870
Radar at list356,250,000$0.0761$27,105,978
Tax at list356,250,000$0.1000$35,625,000
Bundle166,406,250$0.1452$24,165,082
Forecast revenue, with a net impact of ($1,147,418) against no bundle$108,906,929