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Factors Influencing Customer Relationship Management CRM Performance in Agribusiness Firms

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Definitions of CRM. Customer Relationship Management (CRM) is an enterprise approach to ... email, internet, intranet. Information system/database challenges (Q-17) ... – PowerPoint PPT presentation

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Title: Factors Influencing Customer Relationship Management CRM Performance in Agribusiness Firms


1
Factors Influencing Customer Relationship
Management (CRM) Performance in Agribusiness Firms
  • Presented by
  • Dr. Antonio Torres, Jr.
  • Dr. Jay T. Akridge, Committee Co-chair
  • Dr. Allan W. Gray, Committee Co-chair
  • Dr. Michael Boehlje, Committee Member
  • Dr. Rick Widdows, Committee Member

2
Definitions of CRM
  • Customer Relationship Management (CRM) is an
    enterprise approach to understanding and
    influencing customer acquisition, customer
    retention, and customer value-current and
    lifetime-through interactive, relevant
    information exchange (Marketing Science
    Institute).
  • The integrated use of people, process, and
    technology to build and maintain long-term,
    profitable relationships with target customers.

3
Porter and Strategy
  • the essence of strategy is in activities
    -choosing to perform activities differently or to
    perform different activities than rivals.
    Otherwise, a strategy is nothing more than a
    marketing slogan that will not withstand
    competition.
  • Michael Porter
  • Professor, Harvard University HBR,
    1996, p. 64

4
Research Objectives
  • Identify activities/behaviors/outcomes which
    comprise CRM programs
  • Taxonomy of respondents
  • Group (segment) respondents by performance
  • Identify SUPERIOR performers
  • Cluster analysis
  • Identify clusters (segments)
  • Develop profile for each segment based on
    activities/behaviors/outcomes

5
Activities/Behaviors/Outcomes
  • CRM performance
  • CRM objectives
  • Types of customer data collected or accessed
  • Uses of customer Data
  • Approach to market
  • Tactics used to develop and maintain customer
    relationships
  • Information technology infrastructure assessment
  • Information system/database challenges

6
Research Methodology
  • Self-administered mail questionnaire
  • 20 questions
  • Classification variables
  • Activities/behaviors/outcome variables
  • Agribusiness managers
  • Target middle/upper management
  • Pre-tested/revised
  • 2,000 mailed questionnaires
  • Response rate
  • Usable questionnaires
  • 11.65

7
Note 1 significance level, 5
significance level, and 10 significance level
8
Note 1 significance level, 5
significance level, and 10 significance level
9
Customer Data Collected/Accessed
  • Name and address
  • Phone number
  • Email address
  • Contact history
  • Sales data
  • Location/source of purchase for each transaction
  • Product specification data
  • Complaint data
  • Cost of service
  • Customer lifetime value (CLV)

Note 1 significance level, 5
significance level, and 10 significance level
10
Note 1 significance level, 5
significance level, and 10 significance level
11
Note 1 significance level, 5
significance level, and 10 significance level
12
Tactics Used to Develop and Maintain Customer
Relationships
  • Reward/frequent buyer programs
  • Sales force
  • Newsletters
  • Pre-pay/early pay programs
  • Websites
  • Restrict access to websites
  • Direct mail
  • Personalized emails
  • Telemarketing
  • Price discounts based on amount purchased
  • Trips, gifts, etc.
  • Informational meetings
  • Complaint resolution policies/procedures
  • Inventory/stock protection programs
  • Product Bundling

Note 1 significance level, 5
significance level, and 10 significance level
13
Note 1 significance level, 5
significance level, and 10 significance level
14
Note 1 significance level, 5
significance level, and 10 significance level
15
Summary
  • Segment into 3 groups
  • Leaders, Emerging Leaders, Underachievers
  • Those segments which performed better were
  • More ambitious in objectives
  • Collected/accessed more sophisticated customer
    data
  • Used more data
  • Had fewer information system/database challenges
  • Information technology was not a driving force in
    performance
  • People may be distinguishing variables
  • EXECUTION!

16
Contributions to Literature
  • Moved beyond rhetoric in CRM
  • Segment agribusinesses w.r.t. performance and
    developed profile on activities/behaviors
  • Benchmarking

17
(No Transcript)
18
Winers World
  • Create a Database a database of customer
    activity.
  • Analysis Analyze the database.
  • Customer Selection given the analyses,
    decisions about which customers to target.
  • Customer Targeting tools for targeting
    customers.
  • Relationship Marketing how to build
    relationships with the targeted customer.
  • Privacy (and Security) Issues - relating to the
    extent to which customer data is used or
    distributed.
  • Metrics for measuring the success of CRM
    programs.

19
Limitations/Future Research
  • Sample size
  • Low frequency counts in analysis
  • Self-reported performance
  • Objective measure of success?
  • Include other performance metrics
  • Website metrics
  • Brand equity measures
  • Identify attributes
  • Marketing mix metrics
  • Awareness, attitude, relative price, time to
    service, sales per store, etc.
  • Include respondents from lower mgmt. levels
  • Other explanatory variables
  • Market dynamics
  • Competitive intensity
  • Security issues/problems
  • Customer concentration (typo)

20
Implications For Agribusiness Managers
  • Leaders
  • Keep doing well
  • Improve Information technology infrastructure
  • Emerging Leaders
  • Keep Improving especially profitability
  • Reduce impact of challenges
  • Underachievers
  • Must Improve
  • Begin with successes
  • Top Mgmt Support
  • Profitability
  • Information technology Infrastructure

21
88.4 of original grouped cases correctly
classified. 81.5 of cross-validated grouped
cases correctly classified.
22
Univariate Analysis Highlights (Ch. 5 -
Continued)
  • CRM performance (Q-19)
  • Maintain long-term customer relationships
  • Fairness
  • Provide value
  • CRM Objectives (Q-10)
  • Maintain long-term customer relationships
  • Providing value for customers
  • Retain current customers
  • Customer Data (Q-12)
  • Name, address, phone number
  • Uses for Customer Data(Q-13)
  • Analyze marketing strategies
  • Distaste for consumer response to promotions

23
Univariate Analysis Highlights (Ch. 5 -
Continued)
  • Approach to Market (Q-9)
  • Service and quality
  • No focus on low price
  • Tactics to develop and maintain customer
    relationships (Q-11)
  • Sales force
  • Price discounts
  • Personalized e-mails
  • Restrict access to web sties
  • Informational meetings
  • Information technology Infrastructure(Q-14)
  • email, internet, intranet
  • Information system/database challenges (Q-17)
  • How to use and collect data

24
CRM Framework
25
Research Objectives
  • Identify activities/behaviors/outcomes which
    comprise CRM programs
  • Analyze by
  • Firm size
  • Resources (money, people, technology)
  • Industry segments
  • Structural differences
  • Primary position in distribution channel
  • Direct/Indirect customer contact

26
Bivariate Analyses Highlights (Ch. 5)
  • ANOVA and Cross Tabulations
  • Firm size (medium large firms)
  • Tend to perform better
  • Collect more customer data
  • Use more costly tactics
  • Industry segments (crops livestock)
  • Performed very well w.r.t. Up-selling
  • Performed poorly w.r.t. understanding customer
    purchasing behavior
  • Tend to collect/access more customer e-mail
    addresses
  • Position in distribution channel (direct)
  • Anticipate customers emerging needs
  • Use data to customize product/service offerings
  • Focus on superior service when approaching market

27
Multivariate Methods (Ch.6)
  • Data cleaning
  • Correlation matrix
  • Principle components (a form of factor analysis)
  • Cluster analysis
  • Basis variables CRM performance variables
  • ANOVA/Cross tabulations
  • Develop profile
  • Discriminant analysis
  • Hit rate on CRM performance - 88
  • Cross-validation on CRM performance - 81
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