Case Studies Insight into Big Data Boosts Sales by $3.1 Million

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	Insight into Big Data Boosts Sales by $3.1 Million

Insight into Big Data Boosts Sales by $3.1 Million

Technology Category	Analytics & Modeling - Data Mining Analytics & Modeling - Predictive Analytics Functional Applications - Inventory Management Systems
Applicable Industries	E-Commerce Retail
Applicable Functions	Business Operation Sales & Marketing
Services	Data Science Services System Integration
Challenge	Independent office products dealers were struggling to maintain their competitive edge due to a lack of insight into customer buying patterns. This resulted in lost profit opportunities, primarily because of the proliferation of product-related data across multiple sales channels and the inability to convert customer-buying patterns into cross-selling opportunities. The dealers needed a way to identify and analyze real-time buying patterns across multiple channels to boost sales and regain their competitive advantage. Read More
About Customer	Founded in 1848, S.P. Richards, a leading business products wholesaler and a Genuine Parts Company (GPC), distributes over 50,000 business products from 45 distribution centers across the U.S. and Canada. They serve thousands of office product resellers, including independent dealers, large contract stationers, national office supply superstores, mail order distributors, internet resellers, and college bookstores. S.P. Richards also offers a comprehensive range of value-added sales and marketing programs, advanced logistics technology, and sophisticated margin management and data analytics programs. Read More
Solution	S.P. Richards chose Emcien’s pattern detection platform to automatically detect customer-buying patterns for cross-selling and substitution opportunities. Emcien’s software analyzes multiple data streams, including product data and POS transactions, to identify these patterns and push recommendations across multiple channels. The platform’s ability to keep up with market dynamics and automatically detect buying patterns without human intervention was crucial. For example, if a customer buys a mop online, the software suggests related items like a bucket, floor cleaning solutions, and mop head refills. This automated approach also helps in organizing products in catalogs and promotional materials based on actual buying patterns. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Data Mining

Analytics & Modeling - Predictive Analytics

Functional Applications - Inventory Management Systems

Applicable Industries

E-Commerce

Retail

Applicable Functions

Business Operation

Sales & Marketing

Services

Data Science Services

System Integration

Challenge

Independent office products dealers were struggling to maintain their competitive edge due to a lack of insight into customer buying patterns. This resulted in lost profit opportunities, primarily because of the proliferation of product-related data across multiple sales channels and the inability to convert customer-buying patterns into cross-selling opportunities. The dealers needed a way to identify and analyze real-time buying patterns across multiple channels to boost sales and regain their competitive advantage.

About Customer

Founded in 1848, S.P. Richards, a leading business products wholesaler and a Genuine Parts Company (GPC), distributes over 50,000 business products from 45 distribution centers across the U.S. and Canada. They serve thousands of office product resellers, including independent dealers, large contract stationers, national office supply superstores, mail order distributors, internet resellers, and college bookstores. S.P. Richards also offers a comprehensive range of value-added sales and marketing programs, advanced logistics technology, and sophisticated margin management and data analytics programs.

Solution

S.P. Richards chose Emcien’s pattern detection platform to automatically detect customer-buying patterns for cross-selling and substitution opportunities. Emcien’s software analyzes multiple data streams, including product data and POS transactions, to identify these patterns and push recommendations across multiple channels. The platform’s ability to keep up with market dynamics and automatically detect buying patterns without human intervention was crucial. For example, if a customer buys a mop online, the software suggests related items like a bucket, floor cleaning solutions, and mop head refills. This automated approach also helps in organizing products in catalogs and promotional materials based on actual buying patterns.

Impact #1	Automated cross-selling opportunities across 50,000 office products and multiple sales channels.
Impact #2	Enhanced customer satisfaction and ease-of-use.
Impact #3	Improved marketing efforts by organizing products in catalogs and promotional materials based on buying patterns.

Impact #1

Automated cross-selling opportunities across 50,000 office products and multiple sales channels.

Impact #2

Enhanced customer satisfaction and ease-of-use.

Impact #3

Improved marketing efforts by organizing products in catalogs and promotional materials based on buying patterns.

Benefit #1	Realized a 9% boost in sales.
Benefit #2	Generated almost $800,000 additional revenue per quarter.
Benefit #3	Achieved an additional $3.1 million in revenue per year.

Benefit #1

Realized a 9% boost in sales.

Benefit #2

Generated almost $800,000 additional revenue per quarter.

Benefit #3

Achieved an additional $3.1 million in revenue per year.

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Overview

Insight into Big Data Boosts Sales by $3.1 Million

Operational Impact

Quantitative Benefit