Business Research Proposal: Laundry Dispenser Usage and Detergent Application

1. Information Collection: Gathering the necessary raw data from the market and directly from consumers.
2. Information Analysis: Transforming that raw data into strategic insights and actionable recommendations.

Recommended Framework: Jobs-to-be-Done (JTBD) & The KANO Model

Framework Explanation:

• Jobs-to-be-Done (JTBD): This framework focuses on understanding the fundamental "job" a consumer is trying to accomplish when they use a product. Instead of focusing on the product itself or the customer's demographics, we seek to understand the underlying goal or progress they are trying to make. For laundry, the job isn't just "to clean clothes"; it might be "to preserve the newness of my expensive garments," "to quickly and efficiently get through a mountain of family laundry," or "to ensure my baby's clothes are free from irritants."
• The KANO Model: This model is used to categorize customer preferences and product attributes into three key types:
  1. Must-be Attributes: These are basic expectations. If they are not met, the customer will be dissatisfied, but their fulfillment doesn't cause satisfaction (e.g., the washing machine turns on).
  2. Performance Attributes: With these, more is better. Higher performance leads to higher satisfaction (e.g., a faster wash cycle).
  3. Attractive Attributes (Delighters): These are unexpected features that, when present, create significant satisfaction and delight. Their absence, however, does not cause dissatisfaction (e.g., a machine that automatically orders more detergent when you're low).

Applicability to Your Problem:

• JTBD will allow you to move beyond surface-level feedback ("I don't like this dispenser") to uncover the deep, functional, and emotional drivers behind user behavior ("I am frustrated because the sticky dispenser makes me feel like my 'clean' laundry process is starting with a mess").
• The KANO Model will then help you take the insights from the JTBD analysis and prioritize them for product development. It will clarify which pain points are "Must-be" fixes, which features are worth investing in for a competitive edge ("Performance"), and where the true opportunities for game-changing innovation lie ("Delighters").

Part 1: Information Collection

A. Web Search Plan

• Web Search Content & Purpose:
  • Market Landscape:
    • Queries: "laundry machine market share by brand 2025", "consumer reports best washing machines 2025 dispenser reviews"
    • Purpose: To understand the competitive landscape, identify dominant dispenser designs, and see what features are currently being marketed. This provides context for what consumers are used to and what is considered "standard."
  • Detergent Format Trends:
    • Queries: "growth trends in laundry detergent formats (pods vs liquid vs sheets)", "laundry sheets vs pods vs liquid"
    • Purpose: To evaluate market opportunities for new detergent formats. Understanding the rise of formats like sheets and pods, which are often driven by convenience and eco-consciousness, helps frame the "job" consumers are hiring detergent for.
  • Technical Architecture & Common Problems:
    • Queries: "patents for automatic laundry detergent dispensing systems", "common problems with HE washer dispensers forum", "user complaints about washing machine drawers reddit"
    • Purpose: To gather a preliminary list of known pain points and understand the technical constraints of current systems. Forums and patent searches can reveal long-standing issues (e.g., mold, clogging) and innovative solutions being explored.

B. User Interview Plan

• Interview Subjects: A diverse mix of users is crucial. I recommend recruiting for 3-4 distinct segments:
  1. Families with Young Children: High-frequency users, often dealing with heavy soil and a wide variety of stains. Their "job" is often about effectiveness and efficiency.
  2. Young Urban Professionals/Renters: May have smaller, shared, or combo washer-dryer units. Convenience, space, and avoiding mess are often key drivers.
  3. Users of High-End, Feature-Rich Machines: Those who have already invested in premium appliances. What "jobs" led them to pay more? Are they using the advanced features?
  4. Users of Older, Basic Machines: Their habits are not influenced by modern features. Their core "jobs" and workarounds can be very revealing.
• Interview Purpose:
  • To uncover the functional, social, and emotional "Jobs-to-be-Done" related to the entire laundry process, from sorting clothes to putting them away.
  • To identify specific "struggling moments," pain points, and desired outcomes associated with using dispensers and adding detergents.
  • To gather qualitative data that will be categorized using the KANO model (e.g., what do they expect, what would delight them?).
• Core Interview Questions (Open-Ended):
  1. "Walk me through the last time you did a load of laundry, from start to finish. What were you thinking and feeling at each step?"
     • Analysis Purpose: This creates a journey map and uncovers the entire context, not just the moment of adding detergent. It helps identify hidden pain points and workarounds.
  2. "Tell me about the detergents you use. Why did you choose those specific formats (liquid, pod, powder, etc.)?"
     • Analysis Purpose: This reveals the "job" the detergent is hired for—is it convenience, stain-fighting power, scent, eco-friendliness?
  3. (Observational) "Could you show me how you add detergent to your machine for a typical load?"
     • Analysis Purpose: To compare what people say they do with what they actually do. Do they measure carefully? Do they spill? Do they use the dispenser correctly? This is crucial for interaction analysis.
  4. "What, if anything, is frustrating or annoying about your laundry dispenser drawer? Have you ever had to clean it?"
     • Analysis Purpose: Directly targets pain points (gunk build-up, confusing compartments, messiness) which are candidates for "Must-be" attributes in the KANO model.
  5. "If you could wave a magic wand and change anything about the process of getting detergent into the wash, what would you change?"
     • Analysis Purpose: This question encourages creative thinking and helps uncover unmet needs and potential "Attractive/Delighter" features.

Part 2: Information Analysis

1. Define the Core "Jobs-to-be-Done":
   • How to do it: Transcribe the user interviews. Go through each transcript and highlight any mention of a goal, a struggle, or a desired outcome. Rephrase these as "Job Stories" using the format: "When ____ [the situation], I want to ____ [the motivation], so I can ____ [the expected outcome]."
   • Example Job Story (Hypothetical): "When I'm rushing to do laundry before leaving for work, I want to add the detergent quickly and without spills, so I can feel confident the process is clean and I haven't wasted any expensive detergent."
   • Goal: To create a master list of 10-15 key "jobs" that consumers are trying to get done.
2. Map Pain Points and Opportunities with the KANO Model:
   • How to do it: Take the list of dispenser/detergent issues and desired features from your interviews and web search (e.g., "dispenser gets moldy," "auto-dosing," "easy to clean," "clear compartments").
   • Categorize each item:
     • Must-be: A non-moldy, non-clogging dispenser.
     • Performance: A dispenser that requires less frequent cleaning than competitors.
     • Attractive/Delighter: A dispenser that automatically senses the load size and dispenses the perfect amount of detergent.
   • Goal: To create a prioritized grid that clearly shows which problems are critical to solve (Must-bes) and where the most valuable innovation opportunities are (Delighters).
3. Develop User Personas and a Customer Journey Map:
   • How to do it: Based on the interview segments, create 2-3 user personas (e.g., "Brenda, the Busy Mom," "Alex, the Apartment Dweller"). Give them names, goals, and frustrations based on your research.
   • Then, create a visual Customer Journey Map for the "laundry job." Plot the key steps (e.g., Sort Clothes -> Pretreat Stains -> Load Machine -> Add Detergent -> Select Cycle -> Unload). For each step, map out the persona's actions, thoughts, feelings, and pain points.
   • Goal: To build empathy and provide a powerful visual tool for your product and design teams to rally around. It makes the data tangible and user-centric.
4. Synthesize Findings into Actionable Recommendations:
   • How to do it: Combine all the previous steps to directly address the initial business objectives.
     • Pain Points & Preferences: Use the KANO analysis to present a ranked list of pain points and a clear picture of which design attributes are most valued.
     • Usage Patterns: The Journey Map and JTBD analysis will provide a rich narrative of how and why people use their machines and detergents in specific ways.
     • Future Product Development: The "Attractive/Delighter" features from the KANO analysis and the most important "unmet jobs" from the JTBD analysis become your primary candidates for innovation.
     • Market Opportunities: Cross-reference the user needs with the market trend data. For example, if a key "job" is "reducing plastic waste" and you see a market trend of detergent sheets growing, this points to a clear opportunity.
   • Goal: To deliver a final report that doesn't just present data, but tells a compelling story about the user and offers clear, evidence-based strategic direction for the business.