Video summary

푸드트렌드 2023 _ 문정훈 서울대학교 푸드비즈랩 교수

Main summary

Key takeaways

Educational

Main ideas & lessons (Food Trends 2023; post-COVID forecast)

  • The presentation summarizes research conducted over the past year by Seoul National University’s Food Biz Lab to forecast how food consumption and related markets will change from pre-COVID → COVID → post-COVID.
  • It reframes “trend prediction” as hypothesis-driven analysis using industry data, not just a single expert’s intuition.
  • Core framing: society is moving from the COVID era to the post-COVID era, and the talk asks:
    • What changes occur?
    • Where are business opportunities?
  • The work is organized into 7 chapters:
    • Ch. 1 overview
    • Ch. 2–5 focus on retail convenience food, proteins, beverages, online, etc.
    • Ch. 6–7 cover Food Tech trends and consumer value

Method & analytical approach (explicitly described)

Time transitions

  • T1 = pre-COVID period (before the Feb 2020 outbreak)
  • T2 = COVID period (roughly through the pandemic’s first two years)
  • T3 = post-COVID period (data available up to summer 2022, due to limited data)

Decision logic

  • Identify items that continued growing during post-COVID (T2 → T3).
  • Items that only grew in COVID but then decline in post-COVID are treated as having fewer sustainable opportunities.

Data treatment

  • Uses purchase/market data for home consumption, explicitly noting excludes dining out in the main grocery/retail analysis.
  • Adjusts for price changes using statistical adjustments (example shown with CPI-style adjustment).
  • Uses visualizations:
    • line slopes indicate growth/decline across periods
    • circle size represents market size

Research framing

  • Avoids “guru-style” prediction.
  • Builds 10+ hypotheses, verifies with data; typically only 1–2 hypotheses yield strong, clear results—requiring substantial effort.

Chapter 1 overview: retail/home consumption changes (main findings)

1) Proteins (meat, seafood, tofu, etc.)

  • During COVID, protein intake rose; the key question is which proteins keep growing in post-COVID.

  • Growth observations (home purchase data):

    • Increased from T1 → T2 (COVID period):
      • pork, chicken, beef, mollusks, tofu, fish
    • Did not increase:
      • soy milk
    • Keep increasing in post-COVID specifically (T2 → T3):
      • pork and chicken

  • Interpretation:

    • Even as dining out returns, home-purchase patterns for pork/chicken remain resilient.
    • Some categories (e.g., fish, yellow croaker, alcohol) show shifting downward as home cooking changes.

2) Carbohydrates (rice, noodles, etc.)

  • Some carbs that grew during COVID declined in post-COVID:
    • most rice, glutinous rice, sweet potatoes
    • ramen also declines
  • Post-COVID stable vs growing:
    • stable: potatoes, bread, rice cakes
    • growing: noodles (excluding ramen)
      • includes thin noodles, cold noodles, spaghetti, buckwheat noodles, etc.
  • Even though noodles are smaller than some carb markets, noodles show strong post-COVID growth.

3) Food products: processed vs fresh; and what keeps rising

  • COVID era:
    • Fresh foods (except fresh fruit) increased for home consumption.
    • Processed foods increased (“for home consumption”).
  • Post-COVID:
    • Fresh foods generally decline
    • Processed meat and processed seafood continue to grow

  • Within processed meat/seafood (notable category shifts):

    • Growth:
      • fermented seafood
      • processed seaweed
    • Stagnation/decline:
      • fish cakes, imitation crab meat, seaweed (stagnating)
      • sausages (moving toward decline)

  • Home-cooking sauces/oils:

    • Home cooking frequency decreases in post-COVID, but some items remain stable or rise:
      • stable: sesame oil, perilla oil, butter, soy sauce, soybean paste, salt
      • increasing (even with inflation): vegetable cooking oils, sugar, vinegar

4) Side dishes, vegetables, fruits, snacks

  • Side dishes: salted seafood is highlighted as a category that keeps growing.
  • Vegetables:
    • perilla leaves and bean sprouts keep growing
    • others tend to stagnate/decline
  • Fruits:
    • apples, strawberries, Korean melon rise
    • many fruit items show slower growth or decline (with more “bottom-right” declines in the table)
  • Snacks:
    • unexpected resilience: jams continue growing post-COVID
    • snacks and ice cream roughly maintain levels
    • declining fast in post-COVID:
      • candy, jelly, chocolate, gum

5) Beverages & home alcohol

  • Beverage surprise: tea consumption rises rapidly post-COVID.
  • Alcohol (purchase/consumption discussion):
    • whiskey continues growing post-COVID
    • soju, beer, wine, fruit wine maintain
    • makgeolli decreases

Convenience foods & meal kits: the key demographic mechanism

Central concept

  • Convenience food purchasing is strongly affected by whether there are school-aged children in the home.
  • Households are split into:
    • with children receiving school meals
    • without such children (includes 1–2 person households and elderly solo households)

COVID vs post-COVID behavior

  • During COVID:
    • school-aged children stayed home → convenience foods & meal kits grew rapidly
  • Post-COVID:
    • children return to full-time schooling → overall growth stagnates
  • “Two segments behave differently”:
    • School-meal households: fluctuate strongly with social change (fast increases/decreases)
    • Non-school households: demand stays steadier, with gradual accumulation

Item category patterns (detailed segmentation)

The talk describes multiple “product response categories” for the convenience food market:

  1. Increase during school-meal period, then decrease post-COVID
    • examples: fried foods, meatballs, instant foods
    • includes “other foods” like tteokbokki, pizza
  2. Rise then falls sharply for non-school households (no future interest)
    • instant fried foods, dumplings
    • expected to stagnate most overall post-COVID
  3. Increase during school-meal period, but other households lose interest
  4. Continued purchase mainly in school-meal households; non-school households reduce
    • examples: instant soups, instant hot pots, instant juices
  5. Expected strongest growth in 2023
    • instant soups and stews (speaker notes “broth” preference as a cultural driver)
  • “Big important segments”:
    • noodles and salads are described as major areas where interest remains.

Frozen vs refrigerated vs ambient convenience foods (distribution implications)

  • Post-COVID insight: consumers “open their hearts” to frozen convenience foods.
    • frozen preference reaches 38%
  • Distribution channel differs by storage preference:
    • refrigerated preference: more offline + known stores; online via stores they already visit; conservative pattern
    • frozen/ambient focus: stronger preference for Market Kurly
  • Notable item differences by preference:
    • instant rice: frozen-preference consumers buy much more
    • salad: refrigerated-preference consumers buy more frequently
  • Salad distribution nuance:
    • salad buyers may rely more on bakeries (e.g., Paris Baguette) rather than regular retail channels.

Meal kits: global collapse vs Korea’s “surprising” rebound

Main claims

  • Globally (US/EU especially), meal kits are in trouble and customer return rates drop.
  • In Korea:
    • Q1–Q2 2022 was poor (dining out reduced → home dining changes → meal kits decline)
    • after mid-2022, meal kit purchases rise again, with year-on-year sales looking strong
    • Freshigee is cited as rapidly growing and “market leader”-like (a unique case)

Why Korea differs (as explained)

  • Korea’s model prioritizes high processing for convenience, unlike US/EU “basket” prep models.
  • Korea’s meal kit market shifts toward:
    • early morning delivery channels
    • frozen products (speaker estimates 50%+ already shifted to frozen)

Freezing value proposition

  • easier storage + cook “whenever needed”
  • improved assembly through higher processing
  • technical progress to reduce packaging waste

Generational evolution of meal kit formats (timeline)

  1. Generation 1: bundle existing products + attach recipe
  2. Generation 2: subscription-style fresh produce boxes + recipes
  3. Generation 3: higher processing to remove prep steps (Korean style)
  4. Generation 4: frozen preservation optimization
  5. 4.5 generation: reduced packaging types; resolves moisture-exchange issues; further reduces packaging waste
  • Conclusion on direction: meal kits are trending toward “premium convenience foods.”

Meat substitution and protein strategy during COVID → post-COVID (inference from data indices)

Big picture

  • A substitution index compares:
    • dining out vs
    • processed meat vs
    • meat products
  • The speaker notes:
    • dining-out fluctuates strongly during outbreaks (severe drops, rebounds tied to relief funds)
    • substitution effects look stronger for meat products than processed meat

Post-COVID expectation

  • Longer disruption → tighter finances → meat growth may stagnate slightly.
  • When food is unavailable, people lean toward home substitutes (speaker intent appears to be “home substitute products,” not dining-out).

Detailed meat category notes (pork vs beef vs grilling)

  • Pork substitution is described as stronger:
    • pork shows stronger “resolve at home via purchase” behavior
  • Beef vs pork in post-COVID:
    • people reduce beef consumption when dining out returns
    • but do not reduce pork significantly
  • Beef/grilling vs raw/soup pattern:
    • grilled beef at home is affected more by dining-out changes
    • non-grilled categories (e.g., soups/stews) grow
  • Pork categories:
    • both grilled and non-grilled pork rise in 2022
    • pork belly and pork neck highlighted as growing
  • Processed meats:
    • seasoned processed meat (e.g., jerky, bulgogi-like products) grows more than unseasoned forms
  • Demand interpretation:
    • as the economy worsens and fresh meat is harder/less affordable, relatively affordable processed meat options sell well
    • examples include dried meat products; the speaker highlights Market Kurly’s “Sharkeytree” as growing post-COVID and becoming part of daily life

Beverage market: what is growing and who buys

Market shifts after COVID (per Mintel/Open Survey claims)

  • Beverage segments with increased share:
    • coffee, carbonated drinks, tea
  • Coffee:
    • whole bean grows
    • instant coffee decreases
    • brewing with machines rises (including delivery/cafe-like behavior)
    • rising trend toward decaffeinated options (not mainstream yet, but increasing)
  • Tea:
    • growth in infusion teas via imports
  • Carbonated drinks:
    • zero-calorie market growing rapidly

Target customer focus (explicit)

  • Overall beverage consumer order described:
    • coffee → carbonated drinks → milk → fruit juices → tea
  • Women are crucial consumers, especially women in 40s and 50s (Generation X entering their 50s)

Alcohol (brief summary due to time)

  • Wine and whiskey markets continue to grow
  • Whiskey growth mainly via highballs (home and dining out)
  • Traditional liquor/soju also mentioned as growing

Chapters list (as stated, high level)

  • Chapter 1: overview; pre-COVID, COVID, and early post-COVID comparison (5 research quests including convenience, school meals, drinking alone, etc.)
  • Chapters 2–5: convenience foods, proteins (meat), beverages/tea and alcohol, online market dynamics, and meal kit/convenience-related topics (some details expanded in the talk)
  • Chapters 6–7: Food Tech
    • includes global report/paper analysis across Korea, Japan, China, US, and Europe
    • focuses on hot issues and technologies
    • discussion structured around consumer value

Data sources & collaborators (speakers’ sources)

  • Data providers specifically thanked:
    • ATFIS
    • Market Kurly
    • Credit Data Korea
    • Open Survey
    • Mintel Korea
  • Also referenced:
    • Statistics Korea (for alcohol/other market stats)
    • Rural Development Administration (for purchase data cited in convenience/online sections)
    • SSG, Coupang, Market Kurly (top early-morning delivery players; Market Kurly repeatedly referenced)
    • SK News (mentioned as producing an index for beef/grilling analysis)
  • Mentions of export/import and market data (e.g., “64% of the world’s RTD decaffeinated coffee produced in Korea” is stated as a fact from the speaker’s data)

Speakers / sources featured (as requested)

Speakers

  • Professor Moon Jeong-hoon (문정훈) — main presenter (indicates “I” and closes with thank you/applause)

Named researchers (Seoul National University Food Biz Lab) credited for doing the research

  • Professor Lee Dong-min (이동민)
  • Um Ha-ram (엄하람)
  • Kim Na-young (김나영)
  • Lee Hyun-jung (이현정)
  • Jung Hoe-jin (정회진)
  • Kim Joo-young (김주영)
  • Lee Eun-jin (이은진)
  • Cho Sung-hwan (조성환)
  • Kim Kyung-hee (김경희)
  • Kim Hyung-jun (김형준)
  • Kim Dong-hee (김동희)
  • Kim Sa-hoe (김사호)
  • Kim Se-young (김세영)
  • Han Yu-chan (한유찬)

Other named sources / organizations mentioned in the talk

  • Seoul National University Food Biz Lab
  • ATFIS
  • Market Kurly
  • Credit Data Korea
  • Open Survey
  • Mintel Korea
  • Statistics Korea
  • Rural Development Administration
  • SSG
  • Coupang
  • SK News

Original video