Quantitative Research: Feedback Mechanisms

Quantitative Research

  • Definition: Quantitative research involves collecting and analyzing numerical data to understand patterns, measure variables, and generalize findings. In the context of feedback, it refers to obtaining feedback that is expressed in numbers or quantifiable metrics, rather than detailed textual explanations.
  • Characteristics:
    • Focuses on "how many" or "how much."
    • Provides numerical summaries.
    • Does not typically offer deep insights into why individuals feel a certain way.
  • Examples of Quantitative Feedback Mechanisms:
    • Facebook "Likes" (Thumbs Up):
      • When a user gives a post a "thumbs up" on Facebook, they are providing quantitative feedback.
      • This feedback indicates the number of people who liked the post (e.g., "120120 people liked it").
      • It does not provide deeper qualitative information about why they liked it, only the numerical count of approval.
    • Event Attendance Figures:
      • The number of people who attend an event (e.g., a "full squad" for tonight) serves as quantitative feedback.
      • It indicates the popularity or interest level in the event based on attendance figures.
      • Again, it's a numerical measure without delving into individual motivations for attending or not attending.
    • In-Store Service Feedback Buttons:
      • Many physical shops provide feedback stations (e.g., at the exit) where customers can press buttons to rate their service.
      • Options often include "Good," "Average," or "Bad."
      • The aggregated results (e.g., "50%50\% thought the service was good today") provide quantitative data on overall customer satisfaction.
      • While useful for tracking performance, these numbers don't explain the specific reasons behind individual ratings.
    • Star Ratings (e.g., Product Reviews, App Stores):
      • Star ratings, such as those found on e-commerce sites or app stores, are a common form of quantitative feedback.
      • A product might have "five stars" based on a large number of individual ratings (e.g., "975975 people really like this").
      • This aggregated numerical rating helps consumers make quick purchase decisions ("Bing will be alright. Go buy it.") by indicating general approval without providing detailed qualitative reviews.