Optimizing Sales and Marketing Data
portes grátis
Optimizing Sales and Marketing Data
Strategies for Accuracy and Efficiency
Walsh, Susan
Kogan Page Ltd
03/2026
256
Dura
Inglês
9781398623958
15 a 20 dias
Descrição não disponível.
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 cleaned for AI and GenAI to work properly;
Chapter - 05: Normalizing company and brand names for more accurate analytics;
Chapter - 06: Categorization of sales and marketing data for better business decisions;
Chapter - 07: Cleaning key sales and marketing data points efficiently for accurate analytics;
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 projects;
Chapter - 13: Summary;
Chapter - 02: What dirty sales and marketing data looks like;
Chapter - 03: A framework for effective data governance;
Chapter - 04: Why data must be cleaned for AI and GenAI to work properly;
Chapter - 05: Normalizing company and brand names for more accurate analytics;
Chapter - 06: Categorization of sales and marketing data for better business decisions;
Chapter - 07: Cleaning key sales and marketing data points efficiently for accurate analytics;
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 projects;
Chapter - 13: Summary;
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Optimizing Sales and Marketing Data; Susan Walsh; Kogan Page; data cleaning; data quality basics; data management for beginners; how to clean marketing data; how to clean sales data; beginner data skills; customer segmentation for beginners; simple data governance; data taxonomy guide; sales and marketing data essentials; fix messy data; how to organize customer data; improve marketing targeting; reduce wasted marketing spend; beginner-friendly data guide; data confidence for early-career professionals; marketing data toolkit; sales data toolkit; CRM data cleanup; spreadsheet data cleaning; marketing operations basics; sales operations support; data analyst beginner skills; marketing assistant data tasks; sales coordinator data tasks; early-career marketer skills; early-career sales skills; how to categorize customers; data hygiene checklist; repeatable data cleaning steps; practical data examples; improve campaign accuracy; marketing fundamentals; customer data structure; build a data taxonomy; data governance for small teams; UK marketing data; US sales data; EU customer data rules; entry-level data management; data troubleshooting tips; everyday data problems; marketing segmentation techniques; sales targeting improvement; real-world data examples; practical how-to data guide; data accuracy improvement; clean data for better results
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 cleaned for AI and GenAI to work properly;
Chapter - 05: Normalizing company and brand names for more accurate analytics;
Chapter - 06: Categorization of sales and marketing data for better business decisions;
Chapter - 07: Cleaning key sales and marketing data points efficiently for accurate analytics;
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 projects;
Chapter - 13: Summary;
Chapter - 02: What dirty sales and marketing data looks like;
Chapter - 03: A framework for effective data governance;
Chapter - 04: Why data must be cleaned for AI and GenAI to work properly;
Chapter - 05: Normalizing company and brand names for more accurate analytics;
Chapter - 06: Categorization of sales and marketing data for better business decisions;
Chapter - 07: Cleaning key sales and marketing data points efficiently for accurate analytics;
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 projects;
Chapter - 13: Summary;
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Optimizing Sales and Marketing Data; Susan Walsh; Kogan Page; data cleaning; data quality basics; data management for beginners; how to clean marketing data; how to clean sales data; beginner data skills; customer segmentation for beginners; simple data governance; data taxonomy guide; sales and marketing data essentials; fix messy data; how to organize customer data; improve marketing targeting; reduce wasted marketing spend; beginner-friendly data guide; data confidence for early-career professionals; marketing data toolkit; sales data toolkit; CRM data cleanup; spreadsheet data cleaning; marketing operations basics; sales operations support; data analyst beginner skills; marketing assistant data tasks; sales coordinator data tasks; early-career marketer skills; early-career sales skills; how to categorize customers; data hygiene checklist; repeatable data cleaning steps; practical data examples; improve campaign accuracy; marketing fundamentals; customer data structure; build a data taxonomy; data governance for small teams; UK marketing data; US sales data; EU customer data rules; entry-level data management; data troubleshooting tips; everyday data problems; marketing segmentation techniques; sales targeting improvement; real-world data examples; practical how-to data guide; data accuracy improvement; clean data for better results
