Tag: Fundamentals

March 30, 2023

The SaaS Sales Method Fundamentals How to Have Customer Conversations (Sales Blueprints)

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Free Download The SaaS Sales Method Fundamentals: How to Have Customer Conversations (Sales Blueprints) By Jacco Van Der Kooij, Dominique Levin, Winning by Design, Fernando Pizarro (editor)
2018 | 124 Pages | ISBN: 1986270203 | EPUB | 6 MB
The SaaS Sales Method Fundamentals: How to Have Customer Conversations distills how the entire organization communicates with customers down to a simple set of interactions. These interactions happen across multiple channels, from email to phone to in person meetings. What is different about how Blueprints approaches communication is that it emphasizes Impact – understanding how everything in the customer relationship affects the customer’s business results. Sales professionals, whether Sales Development Representatives, Account Executives, Customer Success Managers, or Account Managers, will benefit from the important impact-oriented communications frameworks in this book.

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March 30, 2023

Conceptual Landscapes Fundamentals in the Beginning Design Process

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Free Download Simon M. Bussiere, "Conceptual Landscapes: Fundamentals in the Beginning Design Process"
English | ISBN: 036751303X | 2023 | 264 pages | PDF | 174 MB
Conceptual Landscapes explores the dilemma faced in the early moments of design thinking through a gradient of work in landscape and environmental design media by both emerging and well-established designers and educators of landscape architecture. It questions where and, more importantly, how the process of design starts.

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March 29, 2023

Bayesian Inverse Problems Fundamentals and Engineering Applications

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Free Download Bayesian Inverse Problems: Fundamentals and Engineering Applications By Juan Chiachio-Ruano (editor), Manuel Chiachio-Ruano (editor), Shankar Sankararaman (editor)
2021 | 248 Pages | ISBN: 1138035858 | PDF | 12 MB
This book is devoted to a special class of engineering problems called Bayesian inverse problems. These problems comprise not only the probabilistic Bayesian formulation of engineering problems, but also the associated stochastic simulation methods needed to solve them. Through this book, the reader will learn how this class of methods can be useful to rigorously address a range of engineering problems where empirical data and fundamental knowledge come into play. The book is written for a non-expert audience and it is contributed to by many of the most renowned academic experts in this field.

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