Masashi Fukada

Market Research Internship: Plant-Based Meat Market

In May of 2023, I started a market research internship and Precision Research Inc. to work on a market research project about the plant-based meat industry.

Key Skills

Qualitative Coding

Thematic Analysis

Data Analysis (R Programming)

Data Visualization

Presentation Design

Problem

The client for the project is company focused on elimination animal consumption for the betterment of the environment and people’s health. They are seeking insights about current plant-based alternatives on the market in order to give direction to developing better plant-based alternatives. An overall reluctance to switch to plant-based meat alternatives among consumers has stood in this company’s way in trying to improve the environment through reduced animal consumption.

Approach

OVERVIEW

5 separate research sessions were conducted, each featuring one of these meat categories:

  • Bacon
  • Chicken nuggets
  • Chicken tenders
  • Hamburgers
  • Hot dogs

~100 participants per session were recruited for this study (~500 total).

RESEARCH METHODOLOGY

Blind Survey

All participants took part in a blind tasting for their respective plant-based meat product. Anywhere from 5-12 plant-based alternatives were chosen per category (hot dog, nuggets, etc.). In addition, the real meat version of that product were included in the lineup.

Participants tasted all products without any information on its brand or whether it was plant-based or real meat. After blind tasting each product, participants completed a survey rating that product’s:

  • Appearance
  • Taste
  • Smell
  • Texture
  • Product specific categories (e.g. “breading” for chicken nuggets)
  • Motivations for switching to a plant-based diet (e.g. environmental)

Focus Group

6-person focus groups were chosen for each product (bacon, chicken nuggets, chicken tenders, hamburgers, and hot dogs) from the pool of blind survey participants to discuss their experience with the products.

The products they had tried were brought out for them to try again and spur discussion. Guided by a moderator, discussion included topics such as:

  • Favorite/least favorite products
  • Why they liked/disliked products
  • Taste, smell, texture, appearance
  • If they’d buy any of the products sampled
    • How much they would pay

My Role

Data Analysis

  • Used R programming to perform statistical analysis on close-ended survey data (Likert and semantic differential scales) for over 500 participants.
  • Identified best products, outliers, consistent poor performers, etc. overall and for specific categories (e.g. “appearance”).

Qualitative Coding

  • The survey contained a number of open-ended questions, such as “What most about the appearance did you like” or “dislike” for each product.
  • A “like” and “dislike” open-ended question was included for each overall section on the survey (taste, smell, texture, appearance)
    • I developed inductive codebooks for each product’s open-ended questions in order to extract and analyze themes from qualitative data.
      • I coded over 9000 open-ended survey responses.
    • After coding, I translated this into usable numbers to include in graphs/charts to quantitatively reflect participants’ open-ended attitudes and opinions.
Example of part of codebook I developed for chicken nuggets

Uncovering Insights

  • I used close-ended and open-ended survey data to uncover insights about people’s preferences, attitudes, and opinions towards each plant-based meat product.
  • Analyzed insights between categories for a specific meat product and across all five products.

Presentation of Data and Insights

  • I created five comprehensive slide decks that housed all relevant quantitative information for each product
  • Each slide deck included:
    • Pictures of all plant-based and real-meat products
    • Summary of methodology
    • Overview of all questions and question types use
    • Summary of overall findings
    • Insights about each category (taste, appearance, smell, etc.)
    • Detailed findings from data, including graphs/charts showcasing performance of each product tested
    • Graphs for open-ended results per product
Slide deck title page (client name removed)
Example of graph

Other responsibilities included occasional transcription and thematic analysis of focus group data, email communication with Precision Research Inc. CEO to revise methodology or slide decks, and Zoom call discussion (internship was remote).

Conclusion

All data analysis, coding, and slide deck creation was done over the course of May 2023 – October 2023.

Due to the nature of my employment, I can’t go all too in-depth on insights/findings found for the client. However, here are some broader, overall takeaways about the plant-based meat market I found from this experience:

  1. Plant-based meat is not necessarily worse
    • Many plant-based meat products performed better than the real meat product in certain categories
  2. Taste is not the only factor
    • Taste, while important, is not always the most important factor for plant-based meat products.
      • Just tasting good overall, rather than tasting exactly like meat, was a big factor for certain products.
  3. A willingness for plant-based meat
    • Most participants showed at least some willingness to incorporate plant-based meat into their diets.
    • However, for many this came with significant obstacles, some of which were not necessarily anticipated going into this study.

Overall, I really enjoyed this internship at Precision Research Inc.! This was my first experience in research outside of academia in the industry; I learned a lot about how things work in the real world. Thank you to Scott from Precision Research for entrusting me with so many responsibilities for the plant-based meat project!