Data quality issues are an ever-growing problem for sales and marketing. Professionals in these sectors are expected to understand, clean and categorize data, though they may not always be data professionals.
Covering how to deal with and fix data disasters, this book is designed to be a complete guide for early-mid career sales and marketing professionals on how to clean and organise their data and create a framework for data governance to future-proof it. It explains how to build a taxonomy to allow for easy segmentation and targeting of customers and how this in turn reduces spend and maximises effectiveness whilst minimising unnecessary costs. As data is now the foundation of every company, making sure your data is clean, complete and correct has never been more important.
With practical examples and how-to guides throughout, Optimizing Sales and Marketing Data is immediately implementable, allowing readers to apply the knowledge to their own data right away. By being able to clean up and organize their data, sales and marketing professionals will be able to reduce their spend, increase their efficiency and profitability and become more confident handling and analyzing their customer data for further insights.
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Produkt-Hinweis
Maße
Höhe: 234 mm
Breite: 156 mm
ISBN-13
978-1-3986-2395-8 (9781398623958)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Susan Walsh is the Founder of The Classification Guru, a company that focuses on helping clients solve dirty data problems to maximise profitability and impact. Based in London, UK, she is an industry thought leader, influencer and global speaker. She has been listed in the DataIQ100 for the last two years, as well as winning DataIQ Data Champion 2022 and 2023 and is a finalist for The Great British Businesswoman Awards in the Technology category.
Chapter - 00: Introduction
Chapter - 01: The Importance of Clean and Classified Sales and Marketing Data
Chapter - 02: What Dirty Sales and Marketing Data Looks Like
Chapter - 03: A Framework for Effective Data Governance
Chapter - 04: Why Data Must Be Clean Data For AI, Machine Learning and Gen AI to Work Properly
Chapter - 05: Cleaning Key Sales and Marketing Data Points Efficiently for Accurate Analytics
Chapter - 06: Normalising Company and Brand Names for More Accurate Analytics
Chapter - 07: Categorisation of Sales and Marketing Data for Better Business Decisions
Chapter - 08: How a Customized Taxonomy Can Leverage Your Analytics and Improve Decision Making
Chapter - 09: How to Maintain Data to Future-Proof it
Chapter - 10: Spot-Checking Data to Avoid Future Errors
Chapter - 11: Data Disasters and How to Fix Them
Chapter - 12: Real-World Examples
Chapter - 13: Summary