product-analytics

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Product Analytics

Author : Joanne Rodrigues-Craig
ISBN : 0135258529
Genre : Big data
File Size : 40. 7 MB
Format : PDF, ePub, Docs
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Product Analytics is a complete, hands-on guide to generating actionable business insights from customer data. Experienced data scientist and enterprise manager Joanne Rodrigues introduces practical statistical techniques for determining why things happen and how to change what people do at scale. She complements these with powerful social science techniques for creating better theories, designing better metrics, and driving more rapid and sustained behavior change. Writing for entrepreneurs, product managers/marketers, and other business practitioners, Rodrigues teaches through intuitive examples from both web and offline environments. Avoiding math-heavy explanations, she guides you step by step through choosing the right techniques and algorithms for each application, running analyses in R, and getting answers you can trust. Develop core metrics and effective KPIs for user analytics in any web product Truly understand statistical inference, and the differences between correlation and causation Conduct more effective A/B tests Build intuitive predictive models to capture user behavior in products Use modern, quasi-experimental designs and statistical matching to tease out causal effects from observational data Improve response through uplift modeling and other sophisticated targeting methods Project business costs/subgroup population changes via advanced demographic projection Whatever your product or service, this guide can help you create precision-targeted marketing campaigns, improve consumer satisfaction and engagement, and grow revenue and profits.

Deep Data Analytics For New Product Development

Author : Walter R. Paczkowski
ISBN : 9780429663314
Genre : Business & Economics
File Size : 32. 82 MB
Format : PDF, Docs
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This book presents and develops the deep data analytics for providing the information needed for successful new product development. Deep Data Analytics for New Product Development has a simple theme: information about what customers need and want must be extracted from data to effectively guide new product decisions regarding concept development, design, pricing, and marketing. The benefits of reading this book are twofold. The first is an understanding of the stages of a new product development process from ideation through launching and tracking, each supported by information about customers. The second benefit is an understanding of the deep data analytics for extracting that information from data. These analytics, drawn from the statistics, econometrics, market research, and machine learning spaces, are developed in detail and illustrated at each stage of the process with simulated data. The stages of new product development and the supporting deep data analytics at each stage are not presented in isolation of each other, but are presented as a synergistic whole. This book is recommended reading for analysts involved in new product development. Readers with an analytical bent or who want to develop analytical expertise would also greatly benefit from reading this book, as well as students in business programs.

End To End Data Analytics For Product Development

Author : Rosa Arboretti Giancristofaro
ISBN : 9781119483700
Genre : Mathematics
File Size : 22. 53 MB
Format : PDF
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An interactive guide to the statistical tools used to solve problems during product and process innovation End to End Data Analytics for Product Development is an accessible guide designed for practitioners in the industrial field. It offers an introduction to data analytics and the design of experiments (DoE) whilst covering the basic statistical concepts useful to an understanding of DoE. The text supports product innovation and development across a range of consumer goods and pharmaceutical organizations in order to improve the quality and speed of implementation through data analytics, statistical design and data prediction. The book reviews information on feasibility screening, formulation and packaging development, sensory tests, and more. The authors – noted experts in the field – explore relevant techniques for data analytics and present the guidelines for data interpretation. In addition, the book contains information on process development and product validation that can be optimized through data understanding, analysis and validation. The authors present an accessible, hands-on approach that uses MINITAB and JMP software. The book: • Presents a guide to innovation feasibility and formulation and process development • Contains the statistical tools used to solve challenges faced during product innovation and feasibility • Offers information on stability studies which are common especially in chemical or pharmaceutical fields • Includes a companion website which contains videos summarizing main concepts Written for undergraduate students and practitioners in industry, End to End Data Analytics for Product Development offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.

Ibm Watson Content Analytics Discovering Actionable Insight From Your Content

Author : Wei-Dong (Jackie) Zhu
ISBN : 9780738439426
Genre : Computers
File Size : 77. 50 MB
Format : PDF, ePub
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IBM® WatsonTM Content Analytics (Content Analytics) Version 3.0 (formerly known as IBM Content Analytics with Enterprise Search (ICAwES)) helps you to unlock the value of unstructured content to gain new actionable business insight and provides the enterprise search capability all in one product. Content Analytics comes with a set of tools and a robust user interface to empower you to better identify new revenue opportunities, improve customer satisfaction, detect problems early, and improve products, services, and offerings. To help you gain the most benefits from your unstructured content, this IBM Redbooks® publication provides in-depth information about the features and capabilities of Content Analytics, how the content analytics works, and how to perform effective and efficient content analytics on your content to discover actionable business insights. This book covers key concepts in content analytics, such as facets, frequency, deviation, correlation, trend, and sentimental analysis. It describes the content analytics miner, and guides you on performing content analytics using views, dictionary lookup, and customization. The book also covers using IBM Content Analytics Studio for domain-specific content analytics, integrating with IBM Content Classification to get categories and new metadata, and interfacing with IBM Cognos® Business Intelligence (BI) to add values in BI reporting and analysis, and customizing the content analytics miner with APIs. In addition, the book describes how to use the enterprise search capability for the discovery and retrieval of documents using various query and visual navigation techniques, and customization of crawling, parsing, indexing, and runtime search to improve search results. The target audience of this book is decision makers, business users, and IT architects and specialists who want to understand and analyze their enterprise content to improve and enhance their business operations. It is also intended as a technical how-to guide for use with the online IBM Knowledge Center for configuring and performing content analytics and enterprise search with Content Analytics.

Look Smarter Than You Are With Essbase 11 An Administrator S Guide

Author : Edward Roske
ISBN : 9780557063512
Genre : Business
File Size : 53. 35 MB
Format : PDF, ePub, Mobi
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Learn how to be an Essbase Administrator:'¢ Use the basics of the Smart View Add-in to retrieve and analyze data.'¢ Build aggregate storage option and block storage option databases.'¢ Tune and optimize aggregate storage option and block storage option databases.'¢ Administer Essbase databases. '¢ Take advantage of all the new Essbase 9x and 11x features.This book focuses on Essbase development and administration. For a complete end user guide, please see Look Smarter Than You Are with Smart View and Essbase 11.

End To End Data Analytics For Product Development

Author : Rosa Arboretti Giancristofaro
ISBN : 9781119483694
Genre : Mathematics
File Size : 89. 49 MB
Format : PDF, ePub
Download : 297
Read : 663

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An interactive guide to the statistical tools used to solve problems during product and process innovation End to End Data Analytics for Product Development is an accessible guide designed for practitioners in the industrial field. It offers an introduction to data analytics and the design of experiments (DoE) whilst covering the basic statistical concepts useful to an understanding of DoE. The text supports product innovation and development across a range of consumer goods and pharmaceutical organizations in order to improve the quality and speed of implementation through data analytics, statistical design and data prediction. The book reviews information on feasibility screening, formulation and packaging development, sensory tests, and more. The authors – noted experts in the field – explore relevant techniques for data analytics and present the guidelines for data interpretation. In addition, the book contains information on process development and product validation that can be optimized through data understanding, analysis and validation. The authors present an accessible, hands-on approach that uses MINITAB and JMP software. The book: • Presents a guide to innovation feasibility and formulation and process development • Contains the statistical tools used to solve challenges faced during product innovation and feasibility • Offers information on stability studies which are common especially in chemical or pharmaceutical fields • Includes a companion website which contains videos summarizing main concepts Written for undergraduate students and practitioners in industry, End to End Data Analytics for Product Development offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.

Data Analytics In Marketing Entrepreneurship And Innovation

Author : Mounir Kehal
ISBN : 9780429591686
Genre : Computers
File Size : 89. 19 MB
Format : PDF, Mobi
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Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences. Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics. It features case studies that provide realistic examples of applications. This multifaceted examination of data analytics looks at: Business analytics Applying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analytics Developing new products Technopreneurship Disruptive versus incremental innovation The book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing. Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery. Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques. Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.

The Complete Guide To Business Analytics Collection

Author : Thomas H. Davenport
ISBN : 9780133091250
Genre : Business & Economics
File Size : 84. 90 MB
Format : PDF, ePub
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A brand new collection of business analytics insights and actionable techniques… 3 authoritative books, now in a convenient e-format, at a great price! 3 authoritative eBooks deliver comprehensive analytics knowledge and tools for optimizing every critical business decision! Use business analytics to drive maximum value from all your business data! This unique 3 eBook package will help you harness your information, discover hidden patterns, and successfully act on what you learn. In Enterprise Analytics, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) bring together the latest techniques, best practices, and research on large-scale analytics strategy, technology, implementation, and management. Using real-world examples, they cover everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. You'll find specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions; plus chapter-length case studies from healthcare, retail, and financial services. Next, in the up-to-the-minute Analysis Without Paralysis, Second Edition, Babette E. Bensoussan and Craig S. Fleisher help you succeed with analysis without getting mired in advanced math or arcane theory. They walk you through the entire business analysis process, and guide you through using 12 core tools for making better decisions about strategy and operations -- including three powerful tools covered for the first time in this new Second Edition. Then, in Business and Competitive Analysis, Fleisher and Bensoussan help you apply 24 leading business analysis models to gain deep clarity about your business environment, answer tough questions, and make tough choices. They first walk you through defining problems, avoiding pitfalls, choosing tools, and communicating results. Next, they systematically address both “classic” techniques and the most promising new approaches from economics, finance, sociology, anthropology, and the intelligence and futurist communities. For the first time, one book covers Nine Forces, Competitive Positioning, Business Model, Supply Chain Analyses, Benchmarking, McKinsey 7S, Shadowing, Product Line, Win/Loss, Strategic Relationships, Corporate Reputation, Critical Success Factors, Driving Forces, Country Risk, Technology Forecasting, War Gaming, Event/Timeline, Indications, Warning Analyses, Competitor Cash Flow, ACH, Linchpin Analyses, and more. Whether you're an executive, strategist, analyst, marketer, or operations professional, this eBook collection will help you make more effective, data-driven, profitable decisions! From world-renowned analytics and competitive/business intelligence experts Thomas H. Davenport, Babette E. Bensoussan, and Craig S. Fleisher

Predictive Analytics And Data Mining

Author : Vijay Kotu
ISBN : 9780128016503
Genre : Computers
File Size : 20. 1 MB
Format : PDF, Mobi
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Put Predictive Analytics into Action Learn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining. You’ll be able to: 1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process. 2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases. 3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open source GUI based data mining tool Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveAnalytics.com Demystifies data mining concepts with easy to understand language Shows how to get up and running fast with 20 commonly used powerful techniques for predictive analysis Explains the process of using open source RapidMiner tools Discusses a simple 5 step process for implementing algorithms that can be used for performing predictive analytics Includes practical use cases and examples

Data Analytics With Hadoop

Author : Benjamin Bengfort
ISBN : 9781491913758
Genre : Computers
File Size : 23. 26 MB
Format : PDF, ePub, Mobi
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Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib

Product Analytics Complete Self Assessment Guide

Author : Gerardus Blokdyk
ISBN : 1489144889
Genre :
File Size : 30. 59 MB
Format : PDF, Kindle
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Whats the best design framework for Product Analytics organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant? Have the types of risks that may impact Product Analytics been identified and analyzed? How do we accomplish our long range Product Analytics goals? Is a fully trained team formed, supported, and committed to work on the Product Analytics improvements? Do we cover the five essential competencies-Communication, Collaboration, Innovation, Adaptability, and Leadership that improve an organization's ability to leverage the new Product Analytics in a volatile global economy? This amazing Product Analytics self-assessment will make you the accepted Product Analytics domain auditor by revealing just what you need to know to be fluent and ready for any Product Analytics challenge. How do I reduce the effort in the Product Analytics work to be done to get problems solved? How can I ensure that plans of action include every Product Analytics task and that every Product Analytics outcome is in place? How will I save time investigating strategic and tactical options and ensuring Product Analytics opportunity costs are low? How can I deliver tailored Product Analytics advise instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Product Analytics essentials are covered, from every angle: the Product Analytics self-assessment shows succinctly and clearly that what needs to be clarified to organize the business/project activities and processes so that Product Analytics outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Product Analytics practitioners. Their mastery, combined with the uncommon elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Product Analytics are maximized with professional results. Your purchase includes access details to the Product Analytics self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.

Product Analytics

Author : Joanne Rodrigues-Craig
ISBN : OCLC:1151009370
Genre :
File Size : 87. 94 MB
Format : PDF, ePub, Docs
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Product Analytics bridges the divide between high-value business insights and today's best statistics and machine learning techniques, offering practical qualitative and quantitative techniques to generate actionable insight into customer behavior. Experienced data scientist and enterprise manager Joanne Rodrigues-Craig presents statistical techniques to determine why things happen, and how to change what people do at scale. She complements these with the social sciences' most useful qualitative techniques for creating better theories, designing better metrics, and driving more rapid and sustained behavior change. You'll learn through intuitive examples from both web products and "real life," including numeric examples illuminating hypothesis testing, regression, and other statistical techniques. Discover how to: Think like a social scientist to contextualize individual behavior in social environments, explore how human behavior develops, and establish the conditions for change Develop core metrics and effective KPIs for user analytics in any web product Understand statistical inference, the differences between correlation and causation and when to apply each technique Conduct more effective A/B tests Build intuitive predictive models to capture user behavior in product Using the latest quasi-experimental design techniques and statistical matching tease out causal effects from observational data Implement sophisticated targeting methods like uplift modeling for marketing campaigns Project business costs/subgroup population changes by using advanced demographic projection methods Do all this in R (sample code available in a separate code manual).

Customer Analytics For Dummies

Author : Jeff Sauro
ISBN : 9781118937594
Genre : Business & Economics
File Size : 82. 32 MB
Format : PDF, ePub
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The easy way to grasp customer analytics Ensuring your customers are having positive experiences with your company at all levels, including initial brand awareness and loyalty, is crucial to the success of your business. Customer Analytics For Dummies shows you how to measure each stage of the customer journey and use the right analytics to understand customer behavior and make key business decisions. Customer Analytics For Dummies gets you up to speed on what you should be testing. You'll also find current information on how to leverage A/B testing, social media's role in the post-purchasing analytics, usability metrics, prediction and statistics, and much more to effectively manage the customer experience. Written by a highly visible expert in the area of customer analytics, this guide will have you up and running on putting customer analytics into practice at your own business in no time. Shows you what to measure, how to measure, and ways to interpret the data Provides real-world customer analytics examples from companies such as Wikipedia, PayPal, and Walmart Explains how to use customer analytics to make smarter business decisions that generate more loyal customers Offers easy-to-digest information on understanding each stage of the customer journey Whether you're part of a Customer Engagement team or a product, marketing, or design professional looking to get a leg up, Customer Analytics For Dummies has you covered.

The 2020 International Conference On Machine Learning And Big Data Analytics For Iot Security And Privacy

Author : John MacIntyre
ISBN : 9783030627461
Genre : Big data
File Size : 32. 77 MB
Format : PDF
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This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field

Heuristics In Analytics

Author : Carlos Andre Reis Pinheiro
ISBN : 9781118416747
Genre : Business & Economics
File Size : 77. 16 MB
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Employ heuristic adjustments for truly accurate analysis Heuristics in Analytics presents an approach to analysisthat accounts for the randomness of business and the competitivemarketplace, creating a model that more accurately reflects thescenario at hand. With an emphasis on the importance of properanalytical tools, the book describes the analytical process fromexploratory analysis through model developments, to deployments andpossible outcomes. Beginning with an introduction to heuristicconcepts, readers will find heuristics applied to statistics andprobability, mathematics, stochastic, and artificial intelligencemodels, ending with the knowledge applications that solve businessproblems. Case studies illustrate the everyday application andimplication of the techniques presented, while the heuristicapproach is integrated into analytical modeling, graph analysis,text analytics, and more. Robust analytics has become crucial in the corporateenvironment, and randomness plays an enormous role in business andthe competitive marketplace. Failing to account for randomness cansteer a model in an entirely wrong direction, negatively affectingthe final outcome and potentially devastating the bottom line.Heuristics in Analytics describes how the heuristiccharacteristics of analysis can be overcome with problem design,math and statistics, helping readers to: Realize just how random the world is, and how unplanned eventscan affect analysis Integrate heuristic and analytical approaches to modeling andproblem solving Discover how graph analysis is applied in real-world scenariosaround the globe Apply analytical knowledge to customer behavior, insolvencyprevention, fraud detection, and more Understand how text analytics can be applied to increase thebusiness knowledge Every single factor, no matter how large or how small, must betaken into account when modeling a scenario or event—even theunknowns. The presence or absence of even a single detail candramatically alter eventual outcomes. From raw data to finalreport, Heuristics in Analytics contains the informationanalysts need to improve accuracy, and ultimately, predictive, anddescriptive power.

Pricing Analytics

Author : Walter R. Paczkowski
ISBN : 9781351713092
Genre : Business & Economics
File Size : 40. 38 MB
Format : PDF
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The theme of this book is simple. The price – the number someone puts on a product to help consumers decide to buy that product – comes from data. Specifically, itcomes from statistically modeling the data. This book gives the reader the statistical modeling tools needed to get the number to put on a product. But statistical modeling is not done in a vacuum. Economic and statistical principles and theory conjointly provide the background and framework for the models. Therefore, this book emphasizes two interlocking components of modeling: economic theory and statistical principles. The economic theory component is sufficient to provide understanding of the basic principles for pricing, especially about elasticities, which measure the effects of pricing on key business metrics. Elasticity estimation is the goal of statistical modeling, so attention is paid to the concept and implications of elasticities. The statistical modeling component is advanced and detailed covering choice (conjoint, discrete choice, MaxDiff) and sales data modeling. Experimental design principles, model estimation approaches, and analysis methods are discussed and developed for choice models. Regression fundamentals have been developed for sales model specification and estimation and expanded for latent class analysis.

Product Analytics Complete Self Assessment Guide

Author : Gerardus Blokdyk
ISBN : 1546690395
Genre :
File Size : 72. 4 MB
Format : PDF, Kindle
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What vendors make products that address the Product Analytics needs? What tools do you use once you have decided on a Product Analytics strategy and more importantly how do you choose? How do we keep improving Product Analytics? What other organizational variables, such as reward systems or communication systems, affect the performance of this Product Analytics process? How is the value delivered by Product Analytics being measured? Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role... In EVERY company, organization and department. Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' For more than twenty years, The Art of Service's Self-Assessments empower people who can do just that - whether their title is marketer, entrepreneur, manager, salesperson, consultant, business process manager, executive assistant, IT Manager, CxO etc... - they are the people who rule the future. They are people who watch the process as it happens, and ask the right questions to make the process work better. This book is for managers, advisors, consultants, specialists, professionals and anyone interested in Product Analytics assessment. Featuring 599 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Product Analytics improvements can be made. In using the questions you will be better able to: - diagnose Product Analytics projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Product Analytics and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Product Analytics Scorecard, you will develop a clear picture of which Product Analytics areas need attention. Included with your purchase of the book is the Product Analytics Self-Assessment downloadable resource, containing all 599 questions and Self-Assessment areas of this book. This enables ease of (re-)use and enables you to import the questions in your preferred Management or Survey Tool. Access instructions can be found in the book. You are free to use the Self-Assessment contents in your presentations and materials for customers without asking us - we are here to help. This Self-Assessment has been approved by The Art of Service as part of a lifelong learning and Self-Assessment program and as a component of maintenance of certification. Optional other Self-Assessments are available. For more information, visit http://theartofservice.com

Software Business

Author : Andrey Maglyas
ISBN : 9783319405155
Genre : Business & Economics
File Size : 21. 48 MB
Format : PDF, Mobi
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This book contains the refereed proceedings of the 7th International Conference on Software Business, ICSOB 2016, held in Ljubljana, Slovenia, in June 2016. Software business refers to commercial activities in and around the software industry aimed at generating income from the delivery of software products and services. The theme of the event was "Software as a New Way of Providing Cutting-edge Solutions". The 10 full and 5 short papers for ICSOB were selected from 38 submissions. The papers span a wide range of issues related to contemporary software business, ranging from strategic aspects to operational challenges. The strong presence of software ecosystem papers confirms the importance of this topic and influence on software business. In addition, a short abstract of the key note by Peter Lick and Hans-Bernd Kittlaus is also included.

Advances In Business Operations And Product Analytics

Author : Matthew J. Drake
ISBN : 0133963705
Genre : Computers
File Size : 52. 84 MB
Format : PDF, ePub
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If you're seeking to master business analytics, case studies offer invaluable help: they expose you to the entire decision-making process, helping you practice an active role in both performing analysis and using its output to recommend optimal decisions. Now, drawing on his extensive teaching and consulting experience, Prof. Matthew Drake has created the ideal new casebook for all analytics students and practitioners. Drake, author of the widely-praised Applied Business Analytics Casebook, now presents a collection of up-to-date cases that are longer and more detailed than those typically presented in undergraduate texts, but concise and focused enough to be taught in a single classroom session. Organized by analytical technique, Advances in Business, Operations, and Product Analytics covers: Descriptive analytics: descriptive statistics, sampling/inferential statistics, statistical quality control, and probability Predictive analytics: forecasting, demand managing, data and text mining Prescriptive analytics: optimization-based modeling, simulation-based modeling, decision analysis, and multi-criteria decision making Industry-specific analytics: HR and managerial analytics, financial analytics, and healthcare/life sciences In addition to practitioners, this casebook will be especially valuable to students and faculty in undergraduate and masters' courses that cover topics in business analytics, and courses applying analytics to specific industries such as healthcare, or specific business functions such as marketing.

Deep Data Analytics For New Product Development

Author : Walter R. Paczkowski
ISBN : 9780429666032
Genre : Business & Economics
File Size : 42. 61 MB
Format : PDF, ePub
Download : 536
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This book presents and develops the deep data analytics for providing the information needed for successful new product development. Deep Data Analytics for New Product Development has a simple theme: information about what customers need and want must be extracted from data to effectively guide new product decisions regarding concept development, design, pricing, and marketing. The benefits of reading this book are twofold. The first is an understanding of the stages of a new product development process from ideation through launching and tracking, each supported by information about customers. The second benefit is an understanding of the deep data analytics for extracting that information from data. These analytics, drawn from the statistics, econometrics, market research, and machine learning spaces, are developed in detail and illustrated at each stage of the process with simulated data. The stages of new product development and the supporting deep data analytics at each stage are not presented in isolation of each other, but are presented as a synergistic whole. This book is recommended reading for analysts involved in new product development. Readers with an analytical bent or who want to develop analytical expertise would also greatly benefit from reading this book, as well as students in business programs.

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