Data-Driven Personalization: How to Use Consumer Insights to Generate Customer Loyalty
Your customers expect highly personalized experiences. Discover exactly how to deliver by collecting the right data and crafting messages that tap into behavioral psychology.
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Buch |
Sprache: | English |
Veröffentlicht: |
London
Kogan Page, Limited
2024
|
Ausgabe: | 1st ed. |
Schlagworte: | |
Zusammenfassung: | Your customers expect highly personalized experiences. Discover exactly how to deliver by collecting the right data and crafting messages that tap into behavioral psychology. Cover -- Contents -- List of Figures -- About the Author -- Introduction -- 01 The Case for Data-Driven Personalization -- Why Now is the Time to Improve How Your Marketing Team Uses Data -- Why Personalization Matters -- Customer Expectations Around Personalization -- Our Opportunity and the Impact of Personalization -- Resources Related to this Chapter -- Chapter 1 Summary -- PART ONE Understanding Your Customers -- 02 Starting With the Right Audiences -- Recognizing the Right Customers -- Keeping the Right Customers -- Going From Segmentation to Personalization -- Resources Related to this Chapter -- Chapter 2 Summary -- 03 Researching and Segmenting Your Audiences -- Building a Robust Picture of Your Customers -- Customer Segments That Inform Our Data Collection -- Resources Related to this Chapter -- Chapter 3 Summary -- 04 Gaining Insights When Your Resources Are Limited -- Leveraging Third-Party Research -- Capitalizing on AI and Large Language Models -- Testing With Live Customers -- Resources Related to this Chapter -- Chapter 4 Summary -- PART TWO Building the Toolkit for Personalization -- 05 Preparing for Personalization: The Strategy Behind the Data -- Working With Limited Cognitive Bandwidth -- Crafting Persuasive Messages Like Aristotle -- Aligning Audience Needs With Data Collection -- Resources Related to this Chapter -- Chapter 5 Summary -- 06 Setting Up Data Systems for Today and Tomorrow -- Start With Your Foundation: Unify Your Data -- Invest in Data Quality -- Leverage AI and Machine Learning -- Identify and Interface With New Behaviors -- Resources Related to this Chapter -- Chapter 6 Summary -- 07 Mapping Multi-Faceted Customer Journeys -- What a Customer Journey Map Is-and Isn't -- Rightsizing Your Customer Journey Maps -- Adding Dimension to Your Customer Journey Maps -- Resources Related to this Chapter. |
Beschreibung: | Description based on publisher supplied metadata and other sources |
Beschreibung: | 259 Seiten |
ISBN: | 9781398614604 9781398614628 |
Internformat
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500 | |a Description based on publisher supplied metadata and other sources | ||
520 | 3 | |a Your customers expect highly personalized experiences. Discover exactly how to deliver by collecting the right data and crafting messages that tap into behavioral psychology. | |
520 | 3 | |a Cover -- Contents -- List of Figures -- About the Author -- Introduction -- 01 The Case for Data-Driven Personalization -- Why Now is the Time to Improve How Your Marketing Team Uses Data -- Why Personalization Matters -- Customer Expectations Around Personalization -- Our Opportunity and the Impact of Personalization -- Resources Related to this Chapter -- Chapter 1 Summary -- PART ONE Understanding Your Customers -- 02 Starting With the Right Audiences -- Recognizing the Right Customers -- Keeping the Right Customers -- Going From Segmentation to Personalization -- Resources Related to this Chapter -- Chapter 2 Summary -- 03 Researching and Segmenting Your Audiences -- Building a Robust Picture of Your Customers -- Customer Segments That Inform Our Data Collection -- Resources Related to this Chapter -- Chapter 3 Summary -- 04 Gaining Insights When Your Resources Are Limited -- Leveraging Third-Party Research -- Capitalizing on AI and Large Language Models -- Testing With Live Customers -- Resources Related to this Chapter -- Chapter 4 Summary -- PART TWO Building the Toolkit for Personalization -- 05 Preparing for Personalization: The Strategy Behind the Data -- Working With Limited Cognitive Bandwidth -- Crafting Persuasive Messages Like Aristotle -- Aligning Audience Needs With Data Collection -- Resources Related to this Chapter -- Chapter 5 Summary -- 06 Setting Up Data Systems for Today and Tomorrow -- Start With Your Foundation: Unify Your Data -- Invest in Data Quality -- Leverage AI and Machine Learning -- Identify and Interface With New Behaviors -- Resources Related to this Chapter -- Chapter 6 Summary -- 07 Mapping Multi-Faceted Customer Journeys -- What a Customer Journey Map Is-and Isn't -- Rightsizing Your Customer Journey Maps -- Adding Dimension to Your Customer Journey Maps -- Resources Related to this Chapter. | |
650 | 0 | 7 | |a Kundenbindung |0 (DE-588)4384508-3 |2 gnd |9 rswk-swf |
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Datensatz im Suchindex
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adam_text | |
any_adam_object | |
author | Hou, Zontee |
author_facet | Hou, Zontee |
author_role | aut |
author_sort | Hou, Zontee |
author_variant | z h zh |
building | Verbundindex |
bvnumber | BV049757999 |
classification_rvk | QP 611 |
ctrlnum | (OCoLC)1454762945 (DE-599)BVBBV049757999 |
dewey-full | 658.8343 |
dewey-hundreds | 600 - Technology (Applied sciences) |
dewey-ones | 658 - General management |
dewey-raw | 658.8343 |
dewey-search | 658.8343 |
dewey-sort | 3658.8343 |
dewey-tens | 650 - Management and auxiliary services |
discipline | Wirtschaftswissenschaften |
edition | 1st ed. |
format | Book |
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id | DE-604.BV049757999 |
illustrated | Not Illustrated |
indexdate | 2024-09-10T00:32:40Z |
institution | BVB |
isbn | 9781398614604 9781398614628 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035099497 |
oclc_num | 1454762945 |
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owner | DE-739 |
owner_facet | DE-739 |
physical | 259 Seiten |
publishDate | 2024 |
publishDateSearch | 2024 |
publishDateSort | 2024 |
publisher | Kogan Page, Limited |
record_format | marc |
spelling | Hou, Zontee Verfasser aut Data-Driven Personalization How to Use Consumer Insights to Generate Customer Loyalty Zontee Hou London Kogan Page, Limited 2024 259 Seiten txt rdacontent n rdamedia nc rdacarrier Description based on publisher supplied metadata and other sources Your customers expect highly personalized experiences. Discover exactly how to deliver by collecting the right data and crafting messages that tap into behavioral psychology. Cover -- Contents -- List of Figures -- About the Author -- Introduction -- 01 The Case for Data-Driven Personalization -- Why Now is the Time to Improve How Your Marketing Team Uses Data -- Why Personalization Matters -- Customer Expectations Around Personalization -- Our Opportunity and the Impact of Personalization -- Resources Related to this Chapter -- Chapter 1 Summary -- PART ONE Understanding Your Customers -- 02 Starting With the Right Audiences -- Recognizing the Right Customers -- Keeping the Right Customers -- Going From Segmentation to Personalization -- Resources Related to this Chapter -- Chapter 2 Summary -- 03 Researching and Segmenting Your Audiences -- Building a Robust Picture of Your Customers -- Customer Segments That Inform Our Data Collection -- Resources Related to this Chapter -- Chapter 3 Summary -- 04 Gaining Insights When Your Resources Are Limited -- Leveraging Third-Party Research -- Capitalizing on AI and Large Language Models -- Testing With Live Customers -- Resources Related to this Chapter -- Chapter 4 Summary -- PART TWO Building the Toolkit for Personalization -- 05 Preparing for Personalization: The Strategy Behind the Data -- Working With Limited Cognitive Bandwidth -- Crafting Persuasive Messages Like Aristotle -- Aligning Audience Needs With Data Collection -- Resources Related to this Chapter -- Chapter 5 Summary -- 06 Setting Up Data Systems for Today and Tomorrow -- Start With Your Foundation: Unify Your Data -- Invest in Data Quality -- Leverage AI and Machine Learning -- Identify and Interface With New Behaviors -- Resources Related to this Chapter -- Chapter 6 Summary -- 07 Mapping Multi-Faceted Customer Journeys -- What a Customer Journey Map Is-and Isn't -- Rightsizing Your Customer Journey Maps -- Adding Dimension to Your Customer Journey Maps -- Resources Related to this Chapter. Kundenbindung (DE-588)4384508-3 gnd rswk-swf Personalisierung (DE-588)4384600-2 gnd rswk-swf Kundendaten (DE-588)4425089-7 gnd rswk-swf Kundenmanagement (DE-588)4236865-0 gnd rswk-swf Kundendaten (DE-588)4425089-7 s Personalisierung (DE-588)4384600-2 s Kundenmanagement (DE-588)4236865-0 s Kundenbindung (DE-588)4384508-3 s DE-604 Erscheint auch als Online-Ausgabe 978-1-3986-1461-1 |
spellingShingle | Hou, Zontee Data-Driven Personalization How to Use Consumer Insights to Generate Customer Loyalty Kundenbindung (DE-588)4384508-3 gnd Personalisierung (DE-588)4384600-2 gnd Kundendaten (DE-588)4425089-7 gnd Kundenmanagement (DE-588)4236865-0 gnd |
subject_GND | (DE-588)4384508-3 (DE-588)4384600-2 (DE-588)4425089-7 (DE-588)4236865-0 |
title | Data-Driven Personalization How to Use Consumer Insights to Generate Customer Loyalty |
title_auth | Data-Driven Personalization How to Use Consumer Insights to Generate Customer Loyalty |
title_exact_search | Data-Driven Personalization How to Use Consumer Insights to Generate Customer Loyalty |
title_full | Data-Driven Personalization How to Use Consumer Insights to Generate Customer Loyalty Zontee Hou |
title_fullStr | Data-Driven Personalization How to Use Consumer Insights to Generate Customer Loyalty Zontee Hou |
title_full_unstemmed | Data-Driven Personalization How to Use Consumer Insights to Generate Customer Loyalty Zontee Hou |
title_short | Data-Driven Personalization |
title_sort | data driven personalization how to use consumer insights to generate customer loyalty |
title_sub | How to Use Consumer Insights to Generate Customer Loyalty |
topic | Kundenbindung (DE-588)4384508-3 gnd Personalisierung (DE-588)4384600-2 gnd Kundendaten (DE-588)4425089-7 gnd Kundenmanagement (DE-588)4236865-0 gnd |
topic_facet | Kundenbindung Personalisierung Kundendaten Kundenmanagement |
work_keys_str_mv | AT houzontee datadrivenpersonalizationhowtouseconsumerinsightstogeneratecustomerloyalty |