A groundbreaking approach to selling in a world demanding change Leaders, sales managers and professionals have found themselves stuck at a crossroads between the past and the future of selling, and they need a roadmap to help them embrace the challenges they face at such a critical juncture. Selling Vision is a step-by-step guide to creating and selling change. By implementing new change management strategies into their unique X→XY→Y selling methodology, the authors: · Propose a new logic for thinking about and executing major sales transformations · Examine these transformations from the customer’s perspective and how their changing buying patterns suggest a particular way of focusing selling activities · Consider the perspective of salespeople and what they can do to sell change to their customers · Look at how sales leaders and managers can change the way their organizations sell products or services · Highlight the pivotal moments that determine the success of major change initiatives Based on their unique X→XY→Y selling methodology, Schachter and Cheatham provide a proven sales strategy to help any sales leader, manager, or professional. For sales leaders, their approach provides a path for transforming the sales organization. For sales managers, it describes how to inspire change in the behavior of salespeople. And for salespeople, it offers a new way of selling that will have a dramatic impact on their performance. For any business executive, Selling Vision provides a faster path to driving change. This book provides immediate actions you can take and experiments you can conduct to find the right direction for future sales efforts at any level of an organization. How you respond to changing sales dynamics will determine your company’s success, that of your customers, and, to a great extent, your own personal career goals and future.

Master the art of prospecting and cold calling with strategic, multi-touch sequences Getting attention while prospecting is harder than ever. The field is crowded, and attention spans are short. How can you make sure that you stand out from the competition? In Fanatical Prospecting Sequences: The Complete Guide to Multi-Touch Prospecting and Cold Calling Cadences that Grab Attention, Get Responses, and Open Sales Conversations, celebrated sales leader and bestselling author Jeb Blount walks you through a comprehensive blueprint for converting leads into customers. Through practical hands-on exercises, you'll learn how to design compelling, multi-touch, multi-channel prospecting campaigns that break through the noise and drive meaningful engagement, consistently filling your sales pipeline with high-quality opportunities. Building on the proven principles covered in his bestselling Fanatical Prospecting, Blount offers new insights and tactics that incorporate the latest trends in business development and top of the funnel sales activity. You'll discover how to: Use the seven steps of effective prospecting sequences to get noticed, jumpstart engagement, and generate better outcomes Develop compelling messages that speak directly to your prospects' needs and get them to respond Target prospects with precision and focus your time and effort where it really counts Use the latest tech and AI prompts to enhance your prospecting effectiveness and efficiency Follow step-by-step communication frameworks for phone, email, video, text messaging, LinkedIn, DMs, voicemail, snail mail, and in-person communication Handle objections and gatekeepers with proven, advanced techniques Build confidence and master prospecting sequences to sell more, win more, and earn more Perfect for new sales professionals and seasoned veterans in the industry, this guide is a must-read prospecting roadmap for account executives, business and sales development representatives, sales leaders, entrepreneurs, and small business owners.

Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

This text on mathematical problem solving provides a comprehensive outline of "problemsolving-ology," concentrating on strategy and tactics. It discusses a number of standard mathematical subjects such as combinatorics and calculus from a problem solver's perspective.

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.

When you borrow a plate from grandma, does she ask you to pay a deposit? Of course not. Likewise, blocking your non-paying ("freemium") customers from the core experience of your product, is like chopping your own leg off while running a marathon. Yet, this is just one of the crucial mistakes that most SaaS companies make right off the bat. Think about it. Do YOU have... Stalled accounts taking up valuable space? Sub-par clients who only expect freebies and don't ever use the full features of your product? Low conversion from free accounts to paid? Then, you might have a shot-yourself-in-the-foot problem. In this book, you'll find the easy, 6-step formula you can apply to your operations today that can change absolutely everything. You'll be able to count your company among giants like Mixpanel, Ubisoft, and Outsystems when you: Captivate clients' attention from the get-go. Make it easier for clients to get good at using your software so they are more likely to use it. Create a fool-proof checklist to make your product go viral. Match services with behaviors, and get users addicted to your product. Win rave reviews by making clients feel like VIPs. Use this strategy at each level in your team to supercharge its effect. Rinse and repeat, and watch your business grow while you sleep. In short, you'll discover why putting your customer first is the ultimate secret to growing your company. And how you can achieve astronomical conversions and customer loyalty without even trying. Check out what others are saying:

Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic desig