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Customer relationship management: History, Companies & Products

Customer relationship management (CRM) is a strategic process that organizations use to manage, analyze, and improve their interactions with customers. By using data-driven insights, CRM often involves dedicated information systems that help store and analyze customer data, support communication, and coordinate sales, marketing, and service activities.

Language: English [EN]
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Customer relationship management topic overview

The analysis highlights History, Companies and Products as prominent areas in the source structure around Customer relationship management.

Related topics
111
Source areas
10
Connected nodes
121
Extracted relationships
74
Concept neighborhoods
40
Bridge connections
121

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

History · 27 topics
Components · 14 topics
Market trends · 13 topics
Effect on customer satisfaction · 11 topics
Overview · 11 topics
Improving CRM · 9 topics
Types · 9 topics
In practice · 8 topics
Customer profile · 6 topics
Criticism · 3 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

History

Types

Components

Effect on customer satisfaction

Customer profile

Improving CRM

In practice

Market trends

Criticism

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How Customer relationship management connects Entity context

The extracted context around Customer relationship management shows recurring relationship patterns in the source. For example, Customer relationship management → ACT, At, By, CRM, Developed, ERP, Farley, Farley File, FDR, Franklin Roosevelt's, In, James Farley, Kate, Kestenbaum, Mike Muhney, Navision, One, Oracle, Pat Sullivan, Peoplesoft. Use these groups to spot repeated connection types before inspecting the individual relationships.

Customer relationship management

Top relations

related to history · 30
Customer relationship management → ACT, At, By, CRM, Developed, ERP, Farley, Farley File, FDR, Franklin Roosevelt's, In, James Farley, Kate, Kestenbaum, Mike Muhney, Navision, One, Oracle, Pat Sullivan, Peoplesoft

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

crm customer customers systems data sales marketing also companies management relationships information automation relationship service social use help may company

Customer relationship management relationships Subject–Predicate–Object triples

TTTA extracted 74 structured relationships around Customer relationship management. Examples in this analysis include phone → instance of → customers are supported through multiple channels and data mining → instance of → Analytical CRM systems use techniques. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
phoneinstance ofcustomers are supported through multiple channels0.80text
emailinstance ofcustomers are supported through multiple channels0.80text
knowledge basesinstance ofcustomers are supported through multiple channels0.80text
ticketing portalsinstance ofcustomers are supported through multiple channels0.80text
FAQsinstance ofcustomers are supported through multiple channels0.80text
and more.AnalyticalThe role of analytical CRM systems is to analyze customer data collected through multiple sourcesinstance ofcustomers are supported through multiple channels0.80text
present it so that business managers can make more informed decisionsinstance ofcustomers are supported through multiple channels0.80text
data mininginstance ofAnalytical CRM systems use techniques0.80text
correlationinstance ofAnalytical CRM systems use techniques0.80text
and pattern recognition to analyze customer datainstance ofAnalytical CRM systems use techniques0.80text
suppliersinstance ofthe company might think to market to this subset of consumers differently to best communicate how this company's products might benefit this group specifically.CollaborativeThe…0.80text
vendorsinstance ofthe company might think to market to this subset of consumers differently to best communicate how this company's products might benefit this group specifically.CollaborativeThe…0.80text

Related concept clusters Concept neighborhoods

The concept neighborhoods around Customer relationship management bring nearby vocabulary together. In this analysis, examples include Crm, Service and Systems. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • Customer relationship management
    • Crm
    • Service
    • Systems
    • Relationships
    • Marketing
    • Data
    • Relationship
    • Management
    • Businesses
    • Companies
    • Contact
    • Also
  • customer relationship management
    • Relationship
    • Crm
    • Service
    • Systems
    • Relationships
    • Marketing
    • Data
    • Management
    • Businesses
    • Companies
    • Contact
    • Also
  • compile data
    • Information
    • Systems
    • Use
    • Companies
    • Social
    • Many
    • Media
    • Software
    • Marketing
    • May
    • Products
    • Automation
  • retaining customers
    • May
    • Relationship
    • Information
    • Firms
    • Company
    • Social
    • Systems
    • Marketing
    • Used
    • Also
    • Contact
    • Media
  • sales
    • Automation
    • Marketing
    • Analysis
    • Service
    • Contact
    • Systems
    • Businesses
    • Companies
    • Using
    • Software
    • Company
    • Also
  • standalone mainframe systems
    • Marketing
    • Data
    • Use
    • Sales
    • Also
    • Companies
    • Automation
    • Social
    • Media
    • Company
    • Service
    • Business
  • database marketing
    • Automation
    • Systems
    • Sales
    • Service
    • Using
    • Products
    • Social
    • Relationships
    • Analysis
    • Different
    • Services
    • Firm
  • siebel customer relationship management
    • Relationship
    • Crm
    • Service
    • Systems
    • Relationships
    • Marketing
    • Data
    • Management
    • Businesses
    • Companies
    • Contact
    • Also

Connections between topic areas Semantic bridges

For Customer relationship management, one of the stronger structural bridges in this analysis connects Customer relationship management with History. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
Customer relationship management — History · splits 94 ⟂ 28
Customer relationship management — Components · splits 107 ⟂ 15
Customer relationship management — Market trends · splits 108 ⟂ 14
Customer relationship management — Overview · splits 110 ⟂ 12
Customer relationship management — Effect on customer satisfaction · splits 110 ⟂ 12
Customer relationship management — Types · splits 112 ⟂ 10
Customer relationship management — Improving CRM · splits 112 ⟂ 10
Customer relationship management — In practice · splits 113 ⟂ 9
Customer relationship management — Customer profile · splits 115 ⟂ 7
Customer relationship management — Criticism · splits 118 ⟂ 4

Map overview Semantic statistics

Customer relationship management

Nodes122
Edges121
Triples74
Avg. degree1.98
Density0.016393
Components1

Source & methodology

TTTA analyzes the structure around Customer relationship management to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Companies & Products, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Customer relationship management · EN edition · Analysis: TopicsToTalkAbout

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