Case Studies Regional Grocery Chain Optimizes Promotion Pricing to Compete More Effectively

Edit This Case Study Record

	Regional Grocery Chain Optimizes Promotion Pricing to Compete More Effectively

Regional Grocery Chain Optimizes Promotion Pricing to Compete More Effectively

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries	E-Commerce Retail
Applicable Functions	Business Operation Sales & Marketing
Use Cases	Demand Planning & Forecasting
Services	Data Science Services System Integration
Challenge	A regional supermarket chain needed to defend its market share against big-box, low-cost retailers and other price-driven providers. The retailer responded by matching the lowest prices in their markets, knowing this was not a viable approach long-term due to the negative impact on margin. For a sustainable advantage, the company needed a more effective and efficient promotion solution to improve its competitive position without 'giving away the store.' Read More
About Customer	The customer is a regional supermarket chain that operates in a highly competitive market dominated by big-box, low-cost retailers like Walmart. The chain has a significant presence in its region and is known for its commitment to providing quality products and services to its customers. However, the increasing competition from price-driven providers has put pressure on the supermarket chain to find innovative ways to maintain its market share and profitability. The company has a large customer base that values both the quality and affordability of its products, making it crucial for the chain to balance competitive pricing with maintaining healthy profit margins. Read More
Solution	The grocer turned to Antuit to improve its retail relevancy through a better understanding of its shoppers’ wants, needs, and behaviors. Antuit worked collaboratively with the retailer to implement a solution that maintained margins and boosted its ability to compete. AD-IN, Antuit’s weekly ad circular optimization tool, was a key component of the solution. Using the retailer’s transaction and loyalty data, Antuit applied predictive analytics within AD-IN to identify key purchasing behaviors, including visit frequency, basket sizes, price elasticity, and promotion responsiveness. Using advanced analytics and proprietary algorithms, Antuit mined all relevant shopper data to define price elasticities and demand curves to better understand shopping behavior, seasonality, and pricing on known value items (KVIs). Antuit’s AD-IN solution also delivered an intuitive visual interface that allowed users to easily connect insights to decisions and accelerate adoption. Planners provided business rules and constraints, such as price min/max, promotion time frames, and inventory thresholds. The solution’s decision engine then determined the optimal price points for the entire product portfolio based on store traffic, sales, and margins. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Application Infrastructure & Middleware - Data Exchange & Integration

Applicable Industries

E-Commerce

Retail

Applicable Functions

Business Operation

Sales & Marketing

Use Cases

Demand Planning & Forecasting

Services

Data Science Services

System Integration

Challenge

A regional supermarket chain needed to defend its market share against big-box, low-cost retailers and other price-driven providers. The retailer responded by matching the lowest prices in their markets, knowing this was not a viable approach long-term due to the negative impact on margin. For a sustainable advantage, the company needed a more effective and efficient promotion solution to improve its competitive position without 'giving away the store.'

About Customer

The customer is a regional supermarket chain that operates in a highly competitive market dominated by big-box, low-cost retailers like Walmart. The chain has a significant presence in its region and is known for its commitment to providing quality products and services to its customers. However, the increasing competition from price-driven providers has put pressure on the supermarket chain to find innovative ways to maintain its market share and profitability. The company has a large customer base that values both the quality and affordability of its products, making it crucial for the chain to balance competitive pricing with maintaining healthy profit margins.

Solution

The grocer turned to Antuit to improve its retail relevancy through a better understanding of its shoppers’ wants, needs, and behaviors. Antuit worked collaboratively with the retailer to implement a solution that maintained margins and boosted its ability to compete. AD-IN, Antuit’s weekly ad circular optimization tool, was a key component of the solution. Using the retailer’s transaction and loyalty data, Antuit applied predictive analytics within AD-IN to identify key purchasing behaviors, including visit frequency, basket sizes, price elasticity, and promotion responsiveness. Using advanced analytics and proprietary algorithms, Antuit mined all relevant shopper data to define price elasticities and demand curves to better understand shopping behavior, seasonality, and pricing on known value items (KVIs). Antuit’s AD-IN solution also delivered an intuitive visual interface that allowed users to easily connect insights to decisions and accelerate adoption. Planners provided business rules and constraints, such as price min/max, promotion time frames, and inventory thresholds. The solution’s decision engine then determined the optimal price points for the entire product portfolio based on store traffic, sales, and margins.

Impact #1	The solution helped planners optimize the performance of their weekly circulars by analyzing hundreds of pricing decisions, and calculating the optimal product mix, price point, and ad placement to maximize financial performance.
Impact #2	Using price elasticity and demand curves, Antuit delivered industry-leading forecast accuracy, with front page offers averaging 82% accuracy and inside pages averaging 92% accuracy.
Impact #3	The solution also uncovered an average margin increase of 8%. In addition to margin improvement, the retailer was able to successfully defend its market position.

Impact #1

The solution helped planners optimize the performance of their weekly circulars by analyzing hundreds of pricing decisions, and calculating the optimal product mix, price point, and ad placement to maximize financial performance.

Impact #2

Using price elasticity and demand curves, Antuit delivered industry-leading forecast accuracy, with front page offers averaging 82% accuracy and inside pages averaging 92% accuracy.

Impact #3

The solution also uncovered an average margin increase of 8%. In addition to margin improvement, the retailer was able to successfully defend its market position.

Benefit #1	Identified an average margin increase of 8%.
Benefit #2	Front page offers achieved 82% forecast accuracy.
Benefit #3	Inside pages achieved 92% forecast accuracy.

Benefit #1

Identified an average margin increase of 8%.

Benefit #2

Front page offers achieved 82% forecast accuracy.

Benefit #3

Inside pages achieved 92% forecast accuracy.

Download PDF Version

Overview

Regional Grocery Chain Optimizes Promotion Pricing to Compete More Effectively

Operational Impact

Quantitative Benefit