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Transaction History Data Specification


For sales analytics, elasticity modeling, and retail intelligence Check the sample sample_transactions

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1. Objective

Use this dataset for:
  • Sales performance analytics
  • Price elasticity modeling
  • Demand curve estimation
  • Price optimization
  • Promotion impact analysis
  • Store performance benchmarking
You must provide data at transaction line level.

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2. Data granularity requirement

Each row must represent:
One product in one transaction
Correct:
transaction_idproduct_idquantity
TRX_001P0012
TRX_001P0021
Incorrect:
  • Daily aggregated totals
  • Store-level summaries
  • Pivoted exports

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3. Transaction History – Unified Data Specification

Field NameRequiredTypeFormatDescriptionExampleAlternative Names
transaction_id✅ YesstringUniqueUnique identifier of the transaction. Must be stable and not reused.TRX_000123order id, receipt id, invoice id, ticket id
store_id✅ YesstringTextIdentifier of store or sales location.S001location id, branch id, outlet id
product_id✅ YesstringTextProduct identifier. Must match product_id in Product Master file.P001item id, sku id, article id
transaction_timestamp✅ YesdatetimeYYYY-MM-DD HH:MM:SSDate and time of transaction in ISO 8601 format. Preferably UTC.2026-02-18 14:22:05sale timestamp, order datetime, event time
quantity✅ Yesdecimal(12,2) or integerPositive for sales, negative for returnsUnits sold (positive) or returned (negative). Must not be zero.3 / -1units, qty, quantity sold, units sold
selling_price✅ Yesdecimal(12,2)Dot separatorActual price paid per unit in that transaction (after discount).129.99unit price, final price, transaction price
regular_price⬜ Optionaldecimal(12,2)Dot separatorStandard non-discounted product price at time of sale.139.99base price, list price, shelf price
unit_cost⬜ Optionaldecimal(12,2)2 decimalsCost per unit at time of transaction (for margin calculation).80.00cost price, cogs unit, purchase cost
discount_rate⬜ Optionaldecimal(5,4)0–1Discount applied as a rate (0.15 = 15%).0.15discount pct, promo rate
sales_value⬜ Optionaldecimal(12,2)Dot separatorTotal transaction value per row. If provided, must equal quantity × selling_price.389.97revenue, line revenue, gross sales
gross_profit⬜ Optionaldecimal(12,2)Dot separatorGross profit per row. If provided, must equal (selling_price - unit_cost) × quantity.149.97margin value, contribution margin
stock_after_sale⬜ Optionalinteger≥ 0Inventory level after transaction occurred.37stock on_hand, inventory after
currency⬜ Optional*string(3)ISO 4217Currency code used for price fields. Required if multi-currency.EURcurrency code
tax_rate⬜ Optionaldecimal(5,4)0–1VAT/tax rate applied (0.20 = 20%).0.20vat rate, tax percentage
transaction_type⬜ Optionalstringsale / returnType of transaction. If return, quantity must be negative.saleorder type, operation type

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4. Return handling policy (mandatory if returns exist)

Returns must be provided as separate transaction rows.

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4.1 Format for Returns

FieldValue
transaction_typereturn
quantityNegative value
selling_pricePositive
transaction_timestampActual return time
product_idSame as original sale

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4.2 Example

Original Sale
transaction_idproduct_idquantityselling_pricetransaction_type
TRX_1001P0012129.99sale
Return
transaction_idproduct_idquantityselling_pricetransaction_type
TRX_1055P001-1129.99return

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4.3 Important Rules

  • Do NOT delete original sale rows
  • Do NOT aggregate net values before export
  • Do NOT use positive quantity for returns
  • unit_price must remain positive
  • Returns must reflect the actual return date

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5. Data format requirements (strict)

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5.1 Timestamp

Must follow ISO 8601: 
YYYY-MM-DD HH:MM:SS
Example: 
2026-02-18 14:22:05
Timezone:
  • Preferably UTC
  • Or timezone must be clearly specified

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5.2 Numeric Fields

  • Decimal separator: .
  • No thousand separators
  • No currency symbols
  • No localized formats
Correct: 
129.99
Incorrect: 
129,99
1 299.99
$129.99

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5.3 Discount Format

Must be a rate: 
0.15  = 15%
0.00  = no discount
Not: 
15%
-20

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6. File format

Accepted:
  • CSV (UTF-8 encoding) — preferred
  • XLSX
No pivot tables
No formulas
Raw data only

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7. Historical data requirements

Minimum:
  • 6–12 months of history
  • Preferably 24 months
Recommended minimum volume:
  • 10,000+ transaction rows per store

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8. Data validation rules

  • quantity ≠ 0
  • quantity > 0 for sales
  • quantity < 0 for returns
  • unit_price ≥ 0
  • discount_rate between 0 and 1
  • transaction_timestamp not null
  • product_id must exist in product master file

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9. SQL schema example

CREATE TABLE transaction_history (
    transaction_id VARCHAR(64) NOT NULL,
    store_id VARCHAR(32) NOT NULL,
    product_id VARCHAR(64) NOT NULL,
    transaction_timestamp TIMESTAMP NOT NULL,
    quantity INT NOT NULL,
    unit_price DECIMAL(12,2) NOT NULL,
    unit_cost DECIMAL(12,2),
    discount_rate DECIMAL(5,4),
    stock_after_sale INT,
    currency CHAR(3),
    transaction_type VARCHAR(16),
    sales_channel VARCHAR(16)
);

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10. Minimal dataset (if system limitations exist)

If the system cannot provide full structure, minimum required: 
transaction_id
store_id
product_id
transaction_timestamp
quantity
selling_price
Returns must still follow negative quantity logic.