The inside scoop on boosting sales through spot-on analytics Retailers collect a huge amount of data, but don't know what to do with it. Retail Analytics not only provides a broad understanding of retail, but also shows how to put accumulated data to optimal use. Each chapter covers a different focus of the retail environment, from retail basics and organization structures to common retail database designs. Packed with case studies and examples, this book insightfully reveals how you can begin using your business data as a strategic advantage. Helps retailers and analysts to use analytics to sell more merchandise Provides fact-based analytic strategies that can be replicated with the same success the author achieved on a global level Reveals how retailers can begin using their data as a strategic advantage Includes examples from many retail departments illustrating successful use of data and analytics Analytics is the wave of the future. Put your data to strategic use with the proven guidance found in Retail Analytics.

A non-technical guide to leveraging retail analytics for personal and competitive advantage Style & Statistics is a real-world guide to analytics in retail. Written specifically for the non-IT crowd, this book explains analytics in an approachable, understandable way, and provides examples of direct application to retail merchandise management, marketing, and operations. The discussion covers current industry trends and emerging-standard processes, and illustrates how analytics is providing new solutions to perennial retail problems. You'll learn how to leverage the benefits of analytics to boost your personal career, and how to interpret data in a way that's useful to the average end business user or shopper. Key concepts are detailed in easy-to-understand language, and numerous examples highlight the growing importance of understanding analytics in the retail environment. The power of analytics has become apparent across industries, but it's left an especially indelible mark on retail. It's a complex topic, but you don't need to be a data scientist to take advantage of the opportunities it brings. This book shows you what you need to know, and how to put analytics to work with retail-specific applications. Learn how analytics can help you be better at your job Dig deeper into the customer's needs, wants, and dreams Streamline merchandise management, pricing, marketing, and more Find solutions for inefficiencies and inaccuracies As the retail customer evolves, so must the retail industry. The retail landscape not only includes in-store but also website, mobile site, mobile apps, and social media. With more and more competition emerging on all sides, retailers need to use every tool at their disposal to create value and gain a competitive advantage. Analytics offers a number of ways to make your company stand out, whether it's through improved operations, customer experience, or any of the other myriad factors that build a great place to shop. Style & Statistics provides an analytics primer with a practical bent, specifically for the retail industry.

This book addresses the challenging task of demand forecasting and inventory management in retailing. It analyzes how information from point-of-sale scanner systems can be used to improve inventory decisions, and develops a data-driven approach that integrates demand forecasting and inventory management for perishable products, while taking unobservable lost sales and substitution into account in out-of-stock situations. Using linear programming, a new inventory function that reflects the causal relationship between demand and external factors such as price and weather is proposed. The book subsequently demonstrates the benefits of this new approach in numerical studies that utilize real data collected at a large European retail chain. Furthermore, the book derives an optimal inventory policy for a multi-product setting in which the decision-maker faces an aggregated service level target, and analyzes whether the decision-maker is subject to behavioral biases based on real data for bakery products.

From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture. This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.

The inside scoop on boosting sales through spot-on analytics Retailers collect a huge amount of data, but don't know what to do with it. Retail Analytics not only provides a broad understanding of retail, but also shows how to put accumulated data to optimal use. Each chapter covers a different focus of the retail environment, from retail basics and organization structures to common retail database designs. Packed with case studies and examples, this book insightfully reveals how you can begin using your business data as a strategic advantage. Helps retailers and analysts to use analytics to sell more merchandise Provides fact-based analytic strategies that can be replicated with the same success the author achieved on a global level Reveals how retailers can begin using their data as a strategic advantage Includes examples from many retail departments illustrating successful use of data and analytics Analytics is the wave of the future. Put your data to strategic use with the proven guidance found in Retail Analytics.

Retailers today are drowning in data but lacking in insight. They have so much information at their disposal that they struggle with both how to sort through it, and how to add science to their decision-making process without blunting the art that they correctly believe is a key ingredient of their success. This book reveals how retailers can use data to manage everything from strategic assortment planning, inventory management, and markdowns to improve store-level execution. This data-driven approach to the retail supply chain leads to far greater and faster inventory turns, far fewer and lower discounted goods and services, and better profit margins. The authors also tease out the personnel issues and the organizational implications of this approach.

Essentials of Modeling and Analytics illustrates how and why analytics can be used effectively by loss prevention staff. The book offers an in-depth overview of analytics, first illustrating how analytics are used to solve business problems, then exploring the tools and training that staff will need in order to engage solutions. The text also covers big data analytical tools and discusses if and when they are right for retail loss prevention professionals, and illustrates how to use analytics to test the effectiveness of loss prevention initiatives. Ideal for loss prevention personnel on all levels, this book can also be used for loss prevention analytics courses. Essentials of Modeling and Analytics was named one of the best Analytics books of all time by BookAuthority, one of the world's leading independent sites for nonfiction book recommendations.