I spend a lot of time in marketing-oriented discussion lists. If you do, you probably also sense the incredible frustration of people who keep asking about using their customer data to retain customers and increase profits. Everybody knows they should be doing it, but can't find out how to do it. Consultants and agencies make this process sound like some kind of "black magic", something you can't possibly do yourself. I disagree. I think the average business owner can do a perfectly decent job creating profiles and using them to retain customers and drive profits. Thus the book. The examples provided are Internet specific, but the methods can be used in any business where customer data is available. This book is about the down-and-dirty, nitty-gritty art of taking chunks of data generated by your customers and making sense of it, getting it to speak to you, creating insight into what types of marketing or general business actions you can take to make your business more profitable. We'll be talking about "action-oriented" ideas you can generate on your own to drive sales and profits, ideas that will reveal themselves by analyzing your own customer data, using only a spreadsheet. We have all heard how important it is to collect customer data, to "know" your customer. What I don't hear much about is what exactly you DO with all that data once you have collected it. How is it used? What exactly is Drilling Down into the data supposed to tell me, and what am I looking for when I get there? For that matter, what data should I be collecting and how will I use it when I have it? And how much is this process going to cost me? The following list outlines what you will learn and be able to do after reading the Drilling Down book: --What data is important to collect about a customer and what data is not --How to create action-oriented customer profiles with an Excel spreadsheet --How to use these profiles to plan marketing promotions --How to use these profiles to define the future value of your customers --How to use these profiles to measure the general health of your business --How to use these profiles to encourage customers to do what you want them to --How to predict when a customer is about to defect and leave you --How to increase your profits while decreasing your marketing costs --How to design high ROI (Return on Investment) marketing promotions How to blow away investors with predictions of the future profitability of your business Table of Contents Chapter 1: What's a Customer Profile? Chapter 2: Data-Driven Marketing - Customer Retention Basics Chapter 3: The Language of Data, The Science of Profit Chapter 4: Interactivity Changes the Rules of the Game Chapter 5: How to Build a Customer Profiling Spreadsheet Chapter 6: How to Profile (Score) Your Customers Chapter 7: Marketing Using Customer Scores - Basic Approach Chapter 8: Using Customer Characteristics and Multiple Scores Chapter 9: Watching Scores over Time - Customer LifeCycles Chapter 10: Customer Scoring Grids - Profiling on Steroids Chapter 11: Calculating and Using LifeTime Value in Promotions Chapter 12: Turning Profiles into Profits - the Staging Area Chapter 13: Turning Profiles into Profits - the Financial Model Chapter 14: Turning Profiles into Profits - Financial Tweaks Chapter 15: Measuring Success in Best Customer Promotions Chapter 16: Some Final Thoughts Seasonal Adjustments to Marketing Promotions Don't Fight Customer Behavior CRM Software and Customer Scoring Data-Driven Marketing Program Descriptions There's more! Automate the basic customer scoring process on large groups of customers. Use the software included free with this edition! Windows OS and MS Access and Excel required to run the software.

How to track customers using simple value metrics, set up early warning reports to alert you to positive or negative changes, and launch a marketing action with customers flagged by the reports.

Transforming data into revenue generating strategies and actions Organizations are swamped with data—collected from web traffic, point of sale systems, enterprise resource planning systems, and more, but what to do with it? Monetizing your Data provides a framework and path for business managers to convert ever-increasing volumes of data into revenue generating actions through three disciplines: decision architecture, data science, and guided analytics. There are large gaps between understanding a business problem and knowing which data is relevant to the problem and how to leverage that data to drive significant financial performance. Using a proven methodology developed in the field through delivering meaningful solutions to Fortune 500 companies, this book gives you the analytical tools, methods, and techniques to transform data you already have into information into insights that drive winning decisions. Beginning with an explanation of the analytical cycle, this book guides you through the process of developing value generating strategies that can translate into big returns. The companion website, www.monetizingyourdata.com, provides templates, checklists, and examples to help you apply the methodology in your environment, and the expert author team provides authoritative guidance every step of the way. This book shows you how to use your data to: Monetize your data to drive revenue and cut costs Connect your data to decisions that drive action and deliver value Develop analytic tools to guide managers up and down the ladder to better decisions Turning data into action is key; data can be a valuable competitive advantage, but only if you understand how to organize it, structure it, and uncover the actionable information hidden within it through decision architecture and guided analytics. From multinational corporations to single-owner small businesses, companies of every size and structure stand to benefit from these tools, methods, and techniques; Monetizing your Data walks you through the translation and transformation to help you leverage your data into value creating strategies.

Reflects the latest applied research and features state-of-the-art software for building and solving spreadsheet optimization models Thoroughly updated to reflect the latest topical and technical advances in the field, Optimization Modeling with Spreadsheets, Second Edition continues to focus on solving real-world optimization problems through the creation of mathematical models and the use of spreadsheets to represent and analyze those models. Developed and extensively classroom-tested by the author, the book features a systematic approach that equips readers with the skills to apply optimization tools effectively without the need to rely on specialized algorithms. This new edition uses the powerful software package Risk Solver Platform (RSP) for optimization, including its Evolutionary Solver, which employs many recently developed ideas for heuristic programming. The author provides expanded coverage of integer programming and discusses linear and nonlinear programming using a systematic approach that emphasizes the use of spreadsheet-based optimization tools. The Second Edition also features: Classifications for the various problem types, providing the reader with a broad framework for building and recognizing optimization models Network models that allow for a more general form of mass balance A systematic introduction to Data Envelopment Analysis (DEA) The identification of qualitative patterns in order to meaningfully interpret linear programming solutions An introduction to stochastic programming and the use of RSP to solve problems of this type Additional examples, exercises, and cases have been included throughout, allowing readers to test their comprehension of the material. In addition, a related website features Microsoft Office® Excel files to accompany the figures and data sets in the book. With its accessible and comprehensive presentation, Optimization Modeling with Spreadsheets, Second Edition is an excellent book for courses on deterministic models, optimization, and spreadsheet modeling at the upper-undergraduate and graduate levels. The book can also serve as a reference for researchers, practitioners, and consultants working in business, engineering, operations research, and management science.

This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are focused on understanding the techniques and their proper application, and are supplemented by a wealth of in-chapter and end-of-chapter exercises. In addition to the general statistical methods, the book also includes Monte Carlo simulation and optimization. The second edition has been thoroughly revised: new topics, exercises and examples have been added, and the readability has been further improved. The book is primarily intended for students in business, economics and government, as well as professionals, who need a more rigorous introduction to business and data analytics – yet also need to learn the topic quickly and without overly academic explanations.

The Profit Impact of Business Intelligence presents an A-to-Z approach for getting the most business intelligence (BI) from a company's data assets or data warehouse. BI is not just a technology or methodology, it is a powerful new management approach that – when done right – can deliver knowledge, efficiency, better decisions, and profit to almost any organization that uses it. When BI first came on the scene, it promised a lot but often failed to deliver. The missing element was the business-centric focus explained in this book. It shows how you can achieve the promise of BI by connecting it to your organization's strategic goals, culture, and strengths while correcting your BI weaknesses. It provides a practical, process-oriented guide to achieve the full promise of BI; shows how world-class companies used BI to become leaders in their industries; helps senior business and IT executives understand the strategic impact of BI and how they can ensure a strong payoff from their BI investments; and identifies the most common mistakes organizations make in implementing BI. The book also includes a helpful glossary of BI terms; a BI readiness assessment for your organization; and Web links and extensive references for more information. - A practical, process-oriented book that will help organizations realize the promise of BI - Written by Nancy and Steve Williams, veteran consultants and instructors with hands-on, "in the trenches" experience in government and corporate business intelligence applications - Will help senior business and IT executives understand the strategic impact of BI and how they can help ensure a strong payoff on BI investments