C5i Case Studies Product Assortment and Upsell Optimization for a Leading Global Footwear Firm

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	Product Assortment and Upsell Optimization for a Leading Global Footwear Firm C5i

Product Assortment and Upsell Optimization for a Leading Global Footwear Firm

C5i

Technology Category	Analytics & Modeling - Big Data Analytics Analytics & Modeling - Predictive Analytics
Applicable Industries	Apparel
Applicable Functions	Business Operation Sales & Marketing
Use Cases	Inventory Management Predictive Replenishment
Services	Data Science Services
Challenge	The client, a leading global footwear firm, was facing challenges in optimizing product offerings and upsells on their ecommerce site. The situation was further complicated by marketplaces that were out-pricing the brand store. The client wanted to leverage both competitive and internal data to address these issues. The client also wanted to identify promotion opportunities for not-so-popular products and recommend ideal upsells that would help promote high-margin, low-cost accessories. Read More
About Customer	The customer is a leading global footwear firm. They operate in the apparel industry and have a significant online presence through their ecommerce site. The firm is faced with the challenge of optimizing their product offerings and upsells in the face of stiff competition from marketplaces that are out-pricing them. They are keen on leveraging data to make informed decisions and improve their market position. Read More
Solution	The solution involved two phases. In the first phase, Minerva was deployed to evaluate the most popular shoe sizes and colors based on the volume of sales and stock available in the marketplace over a period of time. Automated bots were built to capture data sets for product attributes, pricing, promotions, and reviews for different size and color combinations for the same product range offered by competitor sellers. The bots also captured upsells being offered by marketplaces and other retailers. In the second phase, a combination of descriptive and prescriptive analytics was run to determine the optimized inventory on the basis of shoe type, color, and size. Optimal upsells were recommended on the basis of statistical models. Reviews were analyzed to comprehend the credibility of other sellers and investigate other aspects, such as whether a pair of shoes might be old stock. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Analytics & Modeling - Predictive Analytics

Applicable Industries

Apparel

Applicable Functions

Business Operation

Sales & Marketing

Use Cases

Inventory Management

Predictive Replenishment

Services

Data Science Services

Challenge

The client, a leading global footwear firm, was facing challenges in optimizing product offerings and upsells on their ecommerce site. The situation was further complicated by marketplaces that were out-pricing the brand store. The client wanted to leverage both competitive and internal data to address these issues. The client also wanted to identify promotion opportunities for not-so-popular products and recommend ideal upsells that would help promote high-margin, low-cost accessories.

About Customer

The customer is a leading global footwear firm. They operate in the apparel industry and have a significant online presence through their ecommerce site. The firm is faced with the challenge of optimizing their product offerings and upsells in the face of stiff competition from marketplaces that are out-pricing them. They are keen on leveraging data to make informed decisions and improve their market position.

Solution

The solution involved two phases. In the first phase, Minerva was deployed to evaluate the most popular shoe sizes and colors based on the volume of sales and stock available in the marketplace over a period of time. Automated bots were built to capture data sets for product attributes, pricing, promotions, and reviews for different size and color combinations for the same product range offered by competitor sellers. The bots also captured upsells being offered by marketplaces and other retailers. In the second phase, a combination of descriptive and prescriptive analytics was run to determine the optimized inventory on the basis of shoe type, color, and size. Optimal upsells were recommended on the basis of statistical models. Reviews were analyzed to comprehend the credibility of other sellers and investigate other aspects, such as whether a pair of shoes might be old stock.

Impact #1	The client was able to optimize their inventory and focus on products that needed promotions.
Impact #2	Optimal upsells were put up on the website balancing competition and internal goals.
Impact #3	Ongoing monitoring helped the firm to continually adjust to market demands.

Impact #1

The client was able to optimize their inventory and focus on products that needed promotions.

Impact #2

Optimal upsells were put up on the website balancing competition and internal goals.

Impact #3

Ongoing monitoring helped the firm to continually adjust to market demands.

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Overview

Product Assortment and Upsell Optimization for a Leading Global Footwear Firm

Operational Impact