Fuel-retail demand-response dataset assembled inside the pricing engine

Name: Fuel-retail demand-response dataset assembled inside the pricing engine: historical POS transaction history and consumer behaviour patterns per station, the model's optimal-price recommendations with real-time market alignment, competitor price movements, and the joined external factor set the model actually consumes (weather, local events, time of day, global incidents) — plus the learned elasticity patterns from each price decision and its observed demand outcome
Creator: A2isystems

A2ISYSTEMSManage supplier listing

Fuel-retail demand-response dataset assembled inside the pricing engine: historical POS transaction history and consumer behaviour patterns per station, the model's optimal-price recommendations with real-time market alignment, competitor price movements, and the joined external factor set the model actually consumes (weather, local events, time of day, global incidents) — plus the learned elasticity patterns from each price decision and its observed demand outcome

Open buyer room →

Sample

Brickroad customers

Sample this dataset before you buy it.

Your sourcing agent asks A2isystems and files the sample in your catalog — private to you.

Start 7-day trialNothing is charged until the trial ends.

Coverage

Universe, instruments and categories.

Industry: Oil & Gas Refining and MarketingFinancial Exchanges & Data
Instruments: commoditiesequitiesderivatives

Dataset card

Type: not stated
Format: Tabular transaction and pricing time series (station, grade, timestamp, litres, price, demand) joined to structured external-factor records (weather, event, calendar/time-of-day features), delivered inside a hosted pricing platform with configurable model outputs
Volume: Order 10^7-10^9 transaction records over the archive (est.: hundreds to a few thousand stations × thousands of fuel transactions per station per day × multi-year POS history retained for model training)
Users: Order low hundreds to low thousands of retail fuel/c-store sites across a small European customer base, with a correspondingly small set of pricing-manager seats (inferred from an 11-person company with a ~US$1.2M revenue band and a configured-per-customer delivery model)
History: 15 years
Update frequency: not stated
Growth: Active (current site content with 2025-dated imagery and an AI-principles/governance positioning being actively marketed, plus a published explainer series on turning fuel pricing into a learning machine — an evolving product rather than a legacy maintenance line)
Launched: ~2010-2015 for A2i's fuel pricing platform (an established European fuel-pricing vendor with a mature product page; PriceCast is marketed as a current-generation AI iteration of that base)
Delivery: not stated
Entity mapping: not stated
Sample: not stated
Point-in-time: not stated
Licence: not stated

supplier index read from their site