Retail and Consumer Goods

Re-Imagine Customer Analytics

We hope you enjoy this collection of resources for Retail and Consumer Goods. Keep an eye on the BlueGranite Blog for updates on utilizing Microsoft Data & AI for customer analytics.

DIGITAL TRANSFORMATION IN RETAIL

MagGlass

Shopper Insights

Analytics

Build new loyalty and win the category at each store! We use new data sources and types to manage retail categories at store level, with real-time price optimization, and individual space and assortment optimization. BlueGranite drives faster innovation by mining web, social, sales, and customer service to better engage consumers.
TransformIdea

Personalized Marketing

Personalization

Drive top line revenue growth and margin improvement! We leverage a behavioral view of the consumer to drive more relevant, contextual offers and recommendations, and implement personalized marketing and personalized pricing and promotions to give shoppers the best possible experience.
ProjectionChart

Omnichannel & Supply Chain

Optimization

Optimize the path to purchase! We employ digital, mobile, and physical channel measurement to capture and convert customers. Marketing mix analytics, ad spent optimization, and multi-touch attribution models are reviewed. Additionally, we use demand forecasting to solve for inefficiencies in retail supply chains, and increase operational effectiveness.

RETAIL AND CPG BLOG POSTS

Explore insightful blog posts from the BlueGranite team covering Retail Analytics, Microsoft Azure, artificial intelligence, and more.

Featured Case Study

RETAIL MARKETER MOVES TO THE CLOUD FOR INNOVATIVE REPORTING

Moving top-brand consumer goods products off store shelves is the chief priority for a North American sales and marketing giant. More than 30,000 employees across 100-plus offices work directly inside retailers and behind the scenes to keep products selling.

On the front lines, close to 16,000 staff members keep stock visible, organized, and accurately priced across North American retail stores. Backstage, nearly 600 analysts focus on metric-based measurements to gauge product success.

Learn More

 

TECHNICAL OVERVIEW:

  • Instituted new advanced analytics and machine learning capabilities in a single unified platform, allowing for more complex modeling than previously possible.

  • Improved capabilities to investigate retail at greater scale will improve product sales.

  • Designed a platform that makes use of the marketer’s existing skill sets.

  • Uncovered opportunities, including a way to look for additional prospects or strategic influencers within a client’s data, and integration with a management application.

  • Created a solid platform for future machine learning and AI capabilities. 

SOLUTION BRIEFS

Retailer Predicts Inventory Demand with Azure Databricks

Retail victory requires expertly juggling supply and demand. When this retailer began grappling with too many products at some locations and not enough at others, the corporation set out to gain a deeper understanding of its customers’ evolving needs and reduce disruption in sales. To better predict adequate future supply, the company enlisted BlueGranite to help it uncover underlying factors influencing sales.

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Billion-dollar Retailer Forecasts Future by Adding Modern Reporting to ERP

It’s been decades since a billion-dollar American clothing retailer began in a single location. Despite its now far-reaching brick-and-mortar and online presence, the merchant is committed to continuing the quality and service that made it a success. Part of that process includes a major, multiyear deployment of a company-wide SAP enterprise resource planning (ERP) system.The new technology touches, and is expected to improve, every facet of the business.

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First Data Warehouse Eases Specialty Food Distributor’s Growing Pains

Less than a decade ago, a U.S. direct-to-store marketer and distributor of international foods had just one warehouse and five employees. The booming business now employs more than 100 people who supply products to over 7,000 stores. This supplier faced some data challenges as it grew. Using a best of breed approach for choosing business information systems obtained the best individual IT applications but left the data created in silos.

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WANT TO LEARN MORE

About How We Can Help You Gain a Competitive Advantage Using Customer Churn Prediction Models?

CHECK OUT OUR CUSTOMER CHURN WEBINAR
 

FEATURED DEMO

Power BI Showcase: Online Retail Reviews

A common data source among retailers are online reviews from ecommerce sites - what buyers have been saying about their products after a purchase. This example scenario includes users who make a purchase from ABC Apparel are asked whether they recommend the product, how they would rate the product on a scale of 1 to 5, and to review the product in a free text form.

This Power BI example report was made to analyze this information. It contains a summary of reviews, ratings, and recommendations sliced by the most important categories for ABC Apparel. In addition, we can also see ratings distributions for the most important categories, and we can drill down to see the individual reviews. ABC might be having a problem with repeat customers, so they are turning to reviews to see if it exposes any product issues. Or they might just be doing a brand health check and want to be sure that there are mostly positive reviews left on their website.

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DEMO SHOWCASE OVERVIEW:

  • Power BI example showcasing online customer product reviews: recommendation, ratings, and free-form text
  • Ratings distributions for the most important categories, and we can drill down to see the individual reviews
  • Native interactivity of Power BI reports facilitates quick and easy exploration of trends and relationships in the data
  • Users can then drill through to a detail page to see whether the sizing issue is commonly mentioned in comments

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or any questions you may have. I am happy to help!