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Author: Kai Yang Publisher: McGraw Hill Professional ISBN: 0071593411 Category : Technology & Engineering Languages : en Pages : 430
Book Description
Discover All the Advantages of Using Design for Six Sigma to Develop and Build Customer Value-Based Products Voice of the Customer Capture and Analysis equips Six Sigma you with the skills needed to create and deploy surveys, capture real customers need with ethnographic methods, immediately analyze the results, and coordinate and drive responsive actions. Quality expert Kai Yang explains how to utilize the statistical methods of Design for Six Sigma to identify key customer needs and assess the cost of poor quality. He then shows how to design robust products to meet those needs, optimize product life cycles, and accurately validate their findings. Voice of the Customer Capture and Analysis features a wealth of information on Six Sigma and value creation...customer survey design, administration, and analysis...ethnographic research...process management and Lean Product Development...the deployment of customer value into products-DFSS...and value engineering. This product design tool enables you to: Minimize sources of response and measurement error Discern customer preferences Design VOC research to minimize mistranslation Respond to analytical implications of VOC data Optimize design to decrease sensitivity of CTQs to process parameters With the help of Voice of the Customer Capture and Analysis, you can now acquire the skills needed to truly understand a customer's wants and needs, in order to develop and build optimal products. Most Design for Six Sigma product development teams fall short of truly understanding their customers' want and needs until it is too late. Market research studies and reports simply do not provide sufficient guidance. Today's Six Sigma practitioners need a comprehensive approach to designing and building customer value-based products. Voice of the Customer Capture and Analysis now gives you the ability to create and deploy surveys, capture real voice of the customer in the field, immediately analyze the results, and coordinate and drive responsive actions. This powerful product-development tool demonstrates how to utilize the statistical methods of Design for Six Sigma to identify key customer needs ...assess the cost of poor quality...design robust products to meet those needs...optimize product life cycles...and accurately validate their findings. By using the expert methods, strategies, and guidelines presented in Voice of the Customer Capture and Analysis, you can: Harness VOC data to create value-based products Employ Design for Six Sigma to optimize value creation Become proactive in gathering VOC information Improve customer survey design, administration, and analysis Accurately process VOC data Deploy customer value into products-DFSS Perform effective quality function deployment (QFD) Get the most out of value engineering Capitalize on creative design methods Utilize process management and Lean Product Development Apply statistical techniques and Six Sigma metrics This wide-ranging resource will give you the ability to minimize sources of response and measurement error ...clearly discern customer preferences...design VOC research to minimize the perils of mistranslation...respond to analytical implications of VOC data ...and optimize design to decrease sensitivity of CTQs to process parameters. Comprehensive and authoritative, Voice of the Customer Capture and Analysis provides you with all the tools you need to fully understand customer needs and wants_and then develop and build outstanding products that meet, or exceed, customer expectations.
Author: Kai Yang Publisher: McGraw Hill Professional ISBN: 0071593411 Category : Technology & Engineering Languages : en Pages : 430
Book Description
Discover All the Advantages of Using Design for Six Sigma to Develop and Build Customer Value-Based Products Voice of the Customer Capture and Analysis equips Six Sigma you with the skills needed to create and deploy surveys, capture real customers need with ethnographic methods, immediately analyze the results, and coordinate and drive responsive actions. Quality expert Kai Yang explains how to utilize the statistical methods of Design for Six Sigma to identify key customer needs and assess the cost of poor quality. He then shows how to design robust products to meet those needs, optimize product life cycles, and accurately validate their findings. Voice of the Customer Capture and Analysis features a wealth of information on Six Sigma and value creation...customer survey design, administration, and analysis...ethnographic research...process management and Lean Product Development...the deployment of customer value into products-DFSS...and value engineering. This product design tool enables you to: Minimize sources of response and measurement error Discern customer preferences Design VOC research to minimize mistranslation Respond to analytical implications of VOC data Optimize design to decrease sensitivity of CTQs to process parameters With the help of Voice of the Customer Capture and Analysis, you can now acquire the skills needed to truly understand a customer's wants and needs, in order to develop and build optimal products. Most Design for Six Sigma product development teams fall short of truly understanding their customers' want and needs until it is too late. Market research studies and reports simply do not provide sufficient guidance. Today's Six Sigma practitioners need a comprehensive approach to designing and building customer value-based products. Voice of the Customer Capture and Analysis now gives you the ability to create and deploy surveys, capture real voice of the customer in the field, immediately analyze the results, and coordinate and drive responsive actions. This powerful product-development tool demonstrates how to utilize the statistical methods of Design for Six Sigma to identify key customer needs ...assess the cost of poor quality...design robust products to meet those needs...optimize product life cycles...and accurately validate their findings. By using the expert methods, strategies, and guidelines presented in Voice of the Customer Capture and Analysis, you can: Harness VOC data to create value-based products Employ Design for Six Sigma to optimize value creation Become proactive in gathering VOC information Improve customer survey design, administration, and analysis Accurately process VOC data Deploy customer value into products-DFSS Perform effective quality function deployment (QFD) Get the most out of value engineering Capitalize on creative design methods Utilize process management and Lean Product Development Apply statistical techniques and Six Sigma metrics This wide-ranging resource will give you the ability to minimize sources of response and measurement error ...clearly discern customer preferences...design VOC research to minimize the perils of mistranslation...respond to analytical implications of VOC data ...and optimize design to decrease sensitivity of CTQs to process parameters. Comprehensive and authoritative, Voice of the Customer Capture and Analysis provides you with all the tools you need to fully understand customer needs and wants_and then develop and build outstanding products that meet, or exceed, customer expectations.
Author: MicroStrategy Product Manuals Publisher: MicroStrategy, Inc. ISBN: 1938244540 Category : Computers Languages : en Pages : 216
Book Description
A reference for the MicroStrategy Customer Analysis Module (CAM), part of the MicroStrategy Analytics Modules that come with MicroStrategy Architect. This guide provides a description, usage scenarios, and screenshots for all the packaged reports for CAM.
Author: David A. Aaker Publisher: John Wiley & Sons ISBN: 0470689757 Category : Business & Economics Languages : en Pages : 369
Book Description
Suitable for all business students studying strategy and marketing courses in the UK and in Europe, this text also looks at important issues such as the financial aspects of marketing.
Author: MicroStrategy Product Manuals Publisher: MicroStrategy, Inc. ISBN: 1938244869 Category : Computers Languages : en Pages : 216
Book Description
A reference for the MicroStrategy Customer Analysis Module (CAM), part of the MicroStrategy Analytics Modules that come with MicroStrategy Architect. This guide provides a description, usage scenarios, and screen shots for all the packaged reports for CAM.
Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 326
Book Description
The project "Credit Card Churning Customer Analysis and Prediction Using Machine Learning and Deep Learning with Python" involved a comprehensive analysis and prediction task focused on understanding customer attrition in a credit card churning scenario. The objective was to explore a dataset, visualize the distribution of features, and predict the attrition flag using both machine learning and artificial neural network (ANN) techniques. The project began by loading the dataset containing information about credit card customers, including various features such as customer demographics, transaction details, and account attributes. The dataset was then explored to gain a better understanding of its structure and contents. This included checking the number of records, identifying the available features, and inspecting the data types. To gain insights into the data, exploratory data analysis (EDA) techniques were employed. This involved examining the distribution of different features, identifying any missing values, and understanding the relationships between variables. Visualizations were created to represent the distribution of features. These visualizations helped identify any patterns, outliers, or potential correlations in the data. The target variable for prediction was the attrition flag, which indicated whether a customer had churned or not. The dataset was split into input features (X) and the target variable (y) accordingly. Machine learning algorithms were then applied to predict the attrition flag. Various classifiers such as Logistic Regression, Decision Trees, Random Forests, Support Vector Machines (SVM), K-Nearest Neighbors (NN), Gradient Boosting, Extreme Gradient Boosting, Light Gradient Boosting, were utilized. These models were trained using the training dataset and evaluated using appropriate performance metrics. Model evaluation involved measuring the accuracy, precision, recall, and F1-score of each classifier. These metrics provided insights into how well the models performed in predicting customer attrition. Additionally, a confusion matrix was created to analyze the true positive, true negative, false positive, and false negative predictions. This matrix allowed for a deeper understanding of the classifier's performance and potential areas for improvement. Next, a deep learning approach using an artificial neural network (ANN) was employed for attrition flag prediction. The dataset was preprocessed, including features normalization, one-hot encoding of categorical variables, and splitting into training and testing sets. The ANN model architecture was defined, consisting of an input layer, one or more hidden layers, and an output layer. The number of nodes and activation functions for each layer were determined based on experimentation and best practices. The ANN model was compiled by specifying the loss function, optimizer, and evaluation metrics. Common choices for binary classification problems include binary cross-entropy loss and the Adam optimizer. The model was then trained using the training dataset. The training process involved feeding the input features and target variable through the network, updating the weights and biases using backpropagation, and repeating this process for multiple epochs. During training, the model's performance on both the training and validation sets was monitored. This allowed for the detection of overfitting or underfitting and the adjustment of hyperparameters, such as the learning rate or the number of hidden layers, if necessary. The accuracy and loss values were plotted over the epochs to visualize the training and validation performance of the ANN. These plots provided insights into the model's convergence and potential areas for improvement. After training, the model was used to make predictions on the test dataset. A threshold of 0.5 was applied to the predicted probabilities to classify the predictions as either churned or not churned customers. The accuracy score was calculated by comparing the predicted labels with the true labels from the test dataset. Additionally, a classification report was generated, including metrics such as precision, recall, and F1-score for both churned and not churned customers. To further evaluate the model's performance, a confusion matrix was created. This matrix visualized the true positive, true negative, false positive, and false negative predictions, allowing for a more detailed analysis of the model's predictive capabilities. Finally, a custom function was utilized to create a plot comparing the predicted values to the true values for the attrition flag. This plot visualized the accuracy of the model and provided a clear understanding of how well the predictions aligned with the actual values. Through this comprehensive analysis and prediction process, valuable insights were gained regarding customer attrition in credit card churning scenarios. The machine learning and ANN models provided predictions and performance metrics that can be used for decision-making and developing strategies to mitigate attrition. Overall, this project demonstrated the power of machine learning and deep learning techniques in understanding and predicting customer behavior. By leveraging the available data, it was possible to uncover patterns, make accurate predictions, and guide business decisions aimed at retaining customers and reducing attrition in credit card churning scenarios.
Author: Étienne Garbugli Publisher: Étienne Garbugli ISBN: 1778074006 Category : Business & Economics Languages : en Pages : 225
Book Description
Get from Idea to Product/Market Fit in B2B. The world has changed. Nowadays, there are more companies building B2B products than there’s ever been. Products are entering organizations top-down, middle-out, and bottom-up. Teams and managers control their budgets. Buyers have become savvier and more impatient. The case for the value of new innovations no longer needs to be made. Technology products get hired, and fired faster than ever before. The challenges have moved from building and validating products to gaining adoption in increasingly crowded and fragmented markets. This, requires a new playbook. The second edition of Lean B2B is the result of years of research into B2B entrepreneurship. It builds off the unique Lean B2B Methodology, which has already helped thousands of entrepreneurs and innovators around the world build successful businesses. In this new edition, you’ll learn: - Why companies seek out new products, and why they agree to buy from unproven vendors like startups - How to find early adopters, establish your credibility, and convince business stakeholders to work with you - What type of opportunities can increase the likelihood of building a product that finds adoption in businesses - How to learn from stakeholders, identify a great opportunity, and create a compelling value proposition - How to get initial validation, create a minimum viable product, and iterate until you're able to find product/market fit This second edition of Lean B2B will show you how to build the products that businesses need, want, buy, and adopt.
Author: Edwin J. Nijssen Publisher: Springer Science & Business Media ISBN: 9780792372721 Category : Business & Economics Languages : en Pages : 158
Book Description
Creating and delivering superior customer value is essential for organizations operating in today's competitive environment. This applies to virtually any kind of organization. It requires a profound understanding of the value creation opportunities in the marketplace, choosing what unique value to create for which customers, and to deliver that value in an effective and efficient way. Strategic marketing management helps to execute this process successfully and to achieving sustainable competitive advantage in the market place. Creating Customer Value Through Strategic Marketing Planning discusses an approach that is both hands-on and embedded in marketing and strategy theory. This book is different from most other marketing strategy books because it combines brief discussions of the underlying theory with the presentation of a selection of useful strategic marketing tools. The structure of the book guides the reader through the process of writing a strategic marketing plan. Suggestions for using the tools help to apply them successfully. This book helps students of marketing strategy to understand strategic marketing planning at work and how to use specific tools. Furthermore, it provides managers with a practical framework and guidelines for making the necessary choices to create and sustain competitive advantage for their organizations.
Author: Peter Fader Publisher: University of Pennsylvania Press ISBN: 1613631413 Category : Business & Economics Languages : en Pages : 136
Book Description
A 2019 Axiom Business Award winner. In The Customer Centricity Playbook , Wharton School professor Peter Fader and Wharton Interactive's executive director Sarah Toms help you see your customers as individuals rather than a monolith, so you can stop wasting resources by chasing down product sales to each and every consumer.
Author: Kai Yang
Author: Kai Yang
Author: MicroStrategy Product Manuals
Author: David A. Aaker
Author: MicroStrategy Product Manuals
Author: MicroStrategy Product Manuals
Author: MicroStrategy Product Manuals
Author: Vivian Siahaan
Author: Étienne Garbugli
Author: Edwin J. Nijssen
Author: Peter Fader