Iris Case Studies Pricing Analytics Transformation for a Global Beauty Retailer

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	Pricing Analytics Transformation for a Global Beauty Retailer Iris

Pricing Analytics Transformation for a Global Beauty Retailer

Iris

Technology Category	Sensors - Level Sensors
Applicable Industries	Consumer Goods Retail
Applicable Functions	Sales & Marketing
Use Cases	Retail Store Automation Theft Detection
Challenge	The client, a multinational retailer of personal care and beauty products, was seeking to optimize their retail pricing for approximately $5B in retail sales annually. The challenge was to maximize revenue and margin while minimizing traffic loss. The client needed a data-driven approach to guide strategic price and promotion adjustments, adhering to industry MSRP and MAP restrictions. They also required weekly competitive intelligence on portfolio-wide pricing, promotions, and inventory levels for major competitors like Ulta Beauty, Macy’s, and Amazon. Read More
About Customer	The customer is a multinational retailer of personal care and beauty products. They have a significant market presence with approximately $5B in retail sales annually. The customer operates in a highly competitive market, with major competitors like Ulta Beauty, Macy’s, and Amazon. They have a vast network of over 1,100 locations across the US market. The customer was seeking to optimize their retail pricing to maximize revenue and margin while minimizing traffic loss. They required a data-driven approach to guide strategic price and promotion adjustments, adhering to industry MSRP and MAP restrictions. Read More
Solution	The solution involved leveraging extensive analytics expertise to model product level elasticities, identify price sensitivities, and simulate revenue impact. This data-driven product segmentation was designed to guide pricing decisions. The consultants provided weekly competitive intelligence on portfolio-wide pricing, promotions, and inventory levels for major competitors. They also enabled the client to adjust prices and promotions more dynamically by having access to a web tool which feeds competitor price changes at a weekly level. This tool could track any change in price, promotion, or out of stock status directly from Ulta Beauty, Macy’s, and Amazon. Additionally, they delivered store tiering and stratified price guidance for over 1,100 locations across the US market, factoring in tourist demand, sales performance, product mix, and competition into store classifications. Read More Log in to view content
Contents

Technology Category

Sensors - Level Sensors

Applicable Industries

Consumer Goods

Retail

Applicable Functions

Sales & Marketing

Use Cases

Retail Store Automation

Theft Detection

Challenge

The client, a multinational retailer of personal care and beauty products, was seeking to optimize their retail pricing for approximately $5B in retail sales annually. The challenge was to maximize revenue and margin while minimizing traffic loss. The client needed a data-driven approach to guide strategic price and promotion adjustments, adhering to industry MSRP and MAP restrictions. They also required weekly competitive intelligence on portfolio-wide pricing, promotions, and inventory levels for major competitors like Ulta Beauty, Macy’s, and Amazon.

About Customer

The customer is a multinational retailer of personal care and beauty products. They have a significant market presence with approximately $5B in retail sales annually. The customer operates in a highly competitive market, with major competitors like Ulta Beauty, Macy’s, and Amazon. They have a vast network of over 1,100 locations across the US market. The customer was seeking to optimize their retail pricing to maximize revenue and margin while minimizing traffic loss. They required a data-driven approach to guide strategic price and promotion adjustments, adhering to industry MSRP and MAP restrictions.

Solution

The solution involved leveraging extensive analytics expertise to model product level elasticities, identify price sensitivities, and simulate revenue impact. This data-driven product segmentation was designed to guide pricing decisions. The consultants provided weekly competitive intelligence on portfolio-wide pricing, promotions, and inventory levels for major competitors. They also enabled the client to adjust prices and promotions more dynamically by having access to a web tool which feeds competitor price changes at a weekly level. This tool could track any change in price, promotion, or out of stock status directly from Ulta Beauty, Macy’s, and Amazon. Additionally, they delivered store tiering and stratified price guidance for over 1,100 locations across the US market, factoring in tourist demand, sales performance, product mix, and competition into store classifications.

Impact #1	The implementation of the data-driven pricing strategy and the use of analytics tools transformed the client's pricing approach. The client was able to identify price sensitivities and simulate revenue impact, which guided strategic price and promotion adjustments. The weekly competitive intelligence provided valuable insights into the pricing, promotions, and inventory levels of major competitors. The web tool enabled the client to adjust prices and promotions more dynamically, responding swiftly to competitor price changes. The store tiering and stratified price guidance for over 1,100 locations across the US market allowed the client to factor in tourist demand, sales performance, product mix, and competition into store classifications, optimizing their pricing strategy across different locations.

Impact #1

The implementation of the data-driven pricing strategy and the use of analytics tools transformed the client's pricing approach. The client was able to identify price sensitivities and simulate revenue impact, which guided strategic price and promotion adjustments. The weekly competitive intelligence provided valuable insights into the pricing, promotions, and inventory levels of major competitors. The web tool enabled the client to adjust prices and promotions more dynamically, responding swiftly to competitor price changes. The store tiering and stratified price guidance for over 1,100 locations across the US market allowed the client to factor in tourist demand, sales performance, product mix, and competition into store classifications, optimizing their pricing strategy across different locations.

Benefit #1	Identified $50 Million in pricing opportunity through data-driven scenario planning on key product segments (to be captured in the first 12 months of implementation)
Benefit #2	Enabled dynamic price adjustments through a web tool which feeds competitor price changes at a weekly level
Benefit #3	Delivered store tiering and stratified price guidance for over 1,100 locations across the US market

Benefit #1

Identified $50 Million in pricing opportunity through data-driven scenario planning on key product segments (to be captured in the first 12 months of implementation)

Benefit #2

Enabled dynamic price adjustments through a web tool which feeds competitor price changes at a weekly level

Benefit #3

Delivered store tiering and stratified price guidance for over 1,100 locations across the US market

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Overview

Pricing Analytics Transformation for a Global Beauty Retailer

Operational Impact

Quantitative Benefit