Chapter 6-E-Marketing Research

Module Overview

  • Module Leader: Dr. Soumaya Askri

  • Course Title: E-Marketing

  • Chapter 6: E-Marketing Research

Chapter 6 Objectives

  • Identify key data sources for addressing e-marketing research problems.

  • Discuss the importance of data quality in online research.

  • Explain the relevance of the internet in primary research and its methodologies.

  • Outline techniques for web monitoring to collect information.

  • Differentiate between client-side and server-side data collection; explain real-space approaches.

  • Understand concepts of big data and cloud computing.

  • Describe analysis methods for data in marketing databases.

A. The Purina Story

  • Company: Nestle Purina PetCare

  • Research Goal: Evaluate influence of online presence on offline behavior.

    • Research Questions:

      • Are buyers visiting branded websites?

      • Should investments in online advertising extend beyond branded sites?

      • What is the optimal placement for advertising?

B. Data Driven Strategy

  • Market Research Overview:

    • Organized efforts to gather information on target markets.

    • The U.S. invests $47.1 billion annually; global expenditure is $76.42 billion.

    • E-marketers accumulate significant data through: surveys, web analytics, social media.

    • Marketing insight bridges information and actionable knowledge; data devoid of insight is rendered useless.

C. Big Data Management

  • IBM's Four Dimensions of Big Data:

    • Volume: Amount of data being processed.

    • Velocity: Speed of data processing.

    • Variety: Types of data (social media, customer behaviors, etc.).

    • Veracity: Trustworthiness and reliability of information.

  • Data Volume Benchmarking:

    • 1 Exabyte = 1,000 Petabytes or 1 billion gigabytes.

D. Email Statistics

  • E-mails Sent Per Day Worldwide (2018-2027):

    • Peaks expected at 361.6 billion daily.

    • Average over 4 million emails sent per second, emphasizing the scale of information exchange.

E. Data Sources for Marketing Research

  • 1. Internal Data:

    • Collects data from financial, accounting, and marketing departments.

    • Provides insights on sales, customer behaviors, and web activity.

  • 2. Secondary Data:

    • Benefits: quicker, cost-effective.

    • Limitations: may not meet specific research needs and can be outdated.

    • Key Information Needs:

      • Demographics, competitor analysis, market trends, and economic factors.

  • 3. Primary Data:

    • Collected for specific marketing issues; tailored and current.

    • Considered proprietary and relevant but can be time-consuming and expensive to gather.

      • Methods Include:

        • Focus Groups, Surveys, Web Analytics, Direct Observation.

F. Primary Research Steps

  • 1. Define Research Problem: Clear and specific.

  • 2. Formulate Research Plan: Strategy to address the defined problem.

  • 3. Data Collection: Implement the plan to gather relevant information.

  • 4. Data Analysis: Utilize analytical tools to interpret results.

  • 5. Distribution of Findings: Incorporate findings into broader marketing strategies.

G. Ethics in Online Research

  • Respondents' concerns over unsolicited emails for surveys.

  • Ethical considerations in collecting identifiable user data (e.g., email addresses).

H. Technology-Enabled Approaches

  • Client-side Data Collection:

    • Utilizes cookies on users' PCs to track online behavior.

  • Server-side Data Collection:

    • Analyzes website interaction including visits, purchases, and clickstream data.

I. Marketing Databases and Data Warehouses

  • Integrate data into various databases:

    • Product, Customer, and Transaction Processing databases.

  • Data Warehousing:

    • Designed for decision-making; segmented for ease of access.

J. Data Analysis Techniques

  • Data Mining: For uncovering insights and predicting consumer behaviors.

  • Customer Profiling: Identifies target groups and preferences based on data warehouse insights.

  • RFM Analysis: Assessing customer interactions based on recency, frequency, and monetary value of purchases.

K. Knowledge Management Metrics

  • Evaluating marketing research costs vs. potential insights.

  • Key Metrics: ROL (Return on Logistics) and TCO (Total Cost of Ownership) for effective data management.