Gas Price Simulator - Transformation of manual into a seamless & automated product.
Web Design
UX
Dashboard
Gas Price Simulator - Costco
Transformation of manual, system-dependent process which running the model manually, exporting results into Excel, and sharing the final target price with business users each day - into a seamless, user-friendly product that automates model execution, streamlines data delivery, and enhances decision-making efficiency.
Overview
🌏 Setting the scene
Every day, Costco’s pricing analysts are responsible for determining accurate fuel prices across hundreds of gas stations. But the process behind those numbers is far from simple. Analysts must run a prescriptive model inside an internal system, export the output to Excel, and manually share the recommended prices with business teams.
As multiple teams depend on this data for timely decisions, even small delays or inconsistencies can slow operations and create confusion. With more analytical models planned for the future, Costco asked a critical question - how might we transform this manual model workflow into a scalable, self-serve experience for their internal users?
🧩 The Problem
Our discovery revealed a growing operational strain. Analysts and business users were spending unnecessary time on managing files, validating outputs, and coordinating daily delivery.
time spent by
Analysts, Exporting, and Distribution
support requests due to
Missing files, or Unclear outputs
1-2
hrs/day
before receiving daily target prices
Operational Delay & Frozen state
🎯
The goal was clear
Transform a complex pricing model
that empowers teams
to confidently review and publish gas prices
into a simple, transparent tool
that empowers teams
to confidently review and publish gas prices
Setting out to solve
🔬 The Secondary Research
To build an experience that truly supports Costco’s pricing teams, first i needed to understand the broader ecosystem surrounding fuel pricing. My secondary research focused on three key areas:
Industry Context
Since i’m new to this field
Pricing Determinants
to find how it works
Internal User Groups
who interact with the model.
Glimpse of Research
🏭 Industry Context
To design a tool that accurately reflects how fuel pricing decisions are made at Costco, we first needed to understand the broader business model and market forces shaping Costco’s gas operations. Our secondary research uncovered several key insights about Costco’s pricing strategy, customer value proposition, and competitive positioning.
To purchase their gas, you have to be a member, and membership sales make up about 75 percent of the chain’s profit.
Costco typically sells gas at 20 cents below the market average, CNN reported.
Costco purchases gas several weeks in advance, so when prices go up, we can still offer a lower price.
Costco purchases gas several weeks in advance, so when prices go up, we can still offer a lower price.
Costco is known for offering high-quality gasoline at competitive prices to its members.
High-volume, low-profit model
💰 Pricing Determinants
Understanding how Costco arrives at its final gas price was essential for shaping the design of our tool. Fuel pricing is
influenced by a combination of primary cost factors—such as crude oil, refining, distribution, and taxes—along with secondary, location-specific variables that fluctuate daily. While the primary components remain relatively consistent, the secondary factors are dynamically calculated by Costco’s prescriptive AI model.
By mapping these inputs end-to-end, from government-regulated buying price to the final selling price at each station, we gained clarity on which data points needed to be surfaced, how transparency could be improved, and where the tool could support users in making informed pricing decisions.
The Solution
Solution
Introduce Transparent, Efficient & Interactive Gas Price Simulator
A Simulator that brings the prescriptive AI model directly into the hands of pricing analysts and business users. This solution centralizes all pricing factors, both constant and location specific - into one intuitive interface, allowing users to review, understand, adjust, and publish daily gas prices with confidence.
✅ What we can Achieve
By addressing the gaps in the current workflow, there is an clear opportunities to reduce operational effort, improve transparency, and accelerate daily pricing decisions. The following metrics highlight the areas where the redesigned experience can create the most impact by REDUCING:
time spent for
Analysts, Exporting, and Distribution
support requests raised for the
Missing files, or Unclear outputs
1-1.5
hrs/day
the time of
Operational Delay & Frozen state
The Redesign
Here’s how we transformed the experience:
🩻 Wireframe
In wireframe we have done in total of 4 iterations to achieve the output that expected.
🗂️ Design Guide
We researched Costco's design guidelines and implemented the almost matching guideline to ensure alignment with their standards and easy adaptability.
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🎖️ Top Features
Visualization
Visual representation of pricing trends, parameter impacts, and comparison of scenarios.
Simulation and Comparison
Users can change and compare pricing scenarios to explore different outcomes and strategies.
Real-time Data Integration
Incorporates real-time market data, transportation costs, and other relevant factors.
🖼️ The Design - Dashboard
Provides an overview of key metrics and insights for gas pricing. It helps users quickly understand current price predictions, user-adjusted prices, and the impact of various factors on gas pricing.
Recommended Price
AI-generated gas price based on all major cost components. It gives starting point by summarising the model suggestion for that day’s average retail price.
Review Recommended Price
user can confirm or modify the suggested price. This step adds a layer of human oversight, allowing analysts to validate the model’s logic, and decide whether they want to accept, adjust, or override the recommendation before publishing.
Factors influencing gas price
Breaks down all the components that influence the gas price. users gain full transparency into how a price was generated and what contributed to the final value also each factor differentiated using color for better scanning.
Retail Price Breakdown
station-wise breakdown of all pricing components, giving users a detailed view of how costs vary across locations. If the user changes any value in the pricing model, they can select specific stations and publish the updated price directly from this section. Enabling precise, controlled updates.
If satisfied with AI recommendation, one click for Publishing the price
Select a U.S. state to publish gas prices for all stations within that region.
Option to select different types of fuel and specific date
Hover Breakdown
While hovering each level of the graph, the price of specific level will be displayed for quick analysis.
Flexible time analysis
Allows users to switch between weekly, monthly, yearly, or custom views to analyze gas price behavior across different time ranges.
Price composition clarity
Breaks down the average retail price into individual components such as crude oil, refining, taxes, profit margin, and local costs, improving transparency and trust.
Location-based insight
Displays gas stations on a map, enabling users to understand regional variations and location-specific pricing.
Price of specific Station
while hovering the station, the price of hovered station will be displayed with the option where user can switch to different types of gas.
Price trend visualization
Visualizes gas price trends over time, helping users quickly understand how prices have changed and identify patterns or anomalies.
Crafting Experience that feel Effortless to be in
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Ramakrishnan Santhanam