The Data Behind Concept Studio: Opensurvey's Food Diary

When we introduce Concept Studio, one question comes up again and again: "How is this different from other synthetic panel services?"

On the surface, the features can look alike. You enter an idea, a synthetic panel evaluates it, and you get a purchase-intent read along with the reasons behind it. But before you put a tool like this to real work, the first thing to check isn't what's on the screen. It's the data the synthetic panel was built from.

For Concept Studio, that answer lives in Opensurvey Food Diary. Concept Studio is built on Opensurvey Food Diary, a dataset we design, collect, and refine ourselves, and on years of food and beverage insight we've accumulated by analyzing it continuously.

The difference in Concept Studio isn't how much data went into it. It's the purpose behind why that data was collected, and how we've learned to read it.

The difference starts with the data behind it

A synthetic panel is built from virtual consumers. But that doesn't mean the basis for its judgments should be virtual too. Assigning an age and a gender and having a model produce a plausible-sounding reason is not enough to tell whether an idea has real potential in the market.

So the data underneath matters, and it has to be checked. Who designed it and why, who was asked and what they were asked, and on what basis the responses were organized: you need to know all of this to read what the data actually means. When the people who created the data and the people who built the service are different, it becomes hard to fully carry the collection context, the definition of each variable, and the quirks of how things were recorded into the product.

Opensurvey Food Diary is original data that Opensurvey plans and builds directly to understand how Koreans eat. From the survey questions to the recording method, from the menu classification system to the refinement rules, Opensurvey designs and manages all of it. That's why we can tell, by a single consistent standard, the circumstances under which each record was collected and what each entry means.

Concept Studio carries the collection purpose, the definitions, and the recording characteristics of Opensurvey Food Diary into the very way the synthetic panel is composed. Designing the product from a position of understanding why each piece of data is used, and to what end, is the first difference.

A sample that mirrors the Korean market

Not all data collected in Korea actually represents the Korean consumer. If it leans toward a handful of heavy users or one particular group, it can't describe the market as a whole. Whose records to include, and in what proportion, has to be part of the design before the data means anything as consumer data.

Opensurvey Food Diary samples men and women aged 20 to 59 across the country, built to reflect the population proportions of that age range (the core of Korea's consumer market). Every month, 350 to 400 consumers take part, spanning a wide range of life stages. It's a design meant to hold the makeup of Korea's 20-to-59 consumers evenly, rather than amplify any single group's voice.

The consumer base Concept Studio draws on begins from exactly this kind of sample: one built with population composition and life stage in mind. So the synthetic panel's judgments, too, rest on the living conditions of the many different consumers who make up the Korean food and beverage market.

Recording a full week of eating, every month

Ask a consumer "what do you usually like?" and they'll give you a tidy summary of their taste. But in real life, people don't always choose the way that summary suggests. Someone who cares about health can still reach for a ready meal on a busy weekday evening; someone who loves trying new flavors can still pick the familiar dish when eating with family.

To see that gap, Opensurvey Food Diary records not a single opinion but a full week of daily life. It captures not only what people ate and drank, but the meal and the time, the place and the occasion, who they ate with, the intent behind the choice, how it was prepared, the purchase channel, and their satisfaction. This adds up to roughly 7,000 meal records and 20,000 individual menu entries every month.

Records of daily life don't become analyzable data just by being collected. From the moment a menu name is entered, Opensurvey guides respondents to make the main ingredient and cooking method clear, and structures each record by menu, ingredient, preparation method, and eating situation. "Black-bean rice," a common Korean home dish, is classified as multigrain rice and as a Korean rice dish; "made 100% at home" is classified as eating in.

Opensurvey has been accumulating these organized records every month since July 2016. That long span lets us see what a single point-in-time survey can't: seasonality and cyclicality, and the shifts in eating habits that steadily grow or fade over time. What Concept Studio draws on isn't a few recent fads, but the actual path along which Korean eating habits have changed.

Years of reading the data show what to look at first

Opensurvey Food Diary holds an enormous amount of information: menu, time, place, dining companions, the intent behind a choice, how it was prepared, and more. So would looking at all of it turn up a good idea? Not necessarily. Depending on the category and character of an idea, the consumer behaviors and metrics you should check first are different.

How often a menu appears in the records and how broad the range of people who eat it are two different things. Whether consumption concentrates at a particular time or in a particular situation, and how something tends to be prepared, have to be examined separately. And because recording characteristics differ by category, the same number can call for a different basis of interpretation.

By analyzing Opensurvey Food Diary continuously, Opensurvey has built up food and beverage insight about which analytical axis a given question needs, and which of many metrics deserves priority. That insight is reflected in the classification system and metric structure of Opensurvey Food Diary, in the interpretation criteria for each category, and in the direction Concept Studio takes when it validates.

Concept Studio holds not only Opensurvey Food Diary data, but the insight into how that data should be read.

Judgments grounded in data you can trust

Concept Studio composes its synthetic panel from the profiles of Opensurvey Food Diary participants, their attitudes toward food, and their actual eating records. A statistical model isolates the attributes that matter for evaluating an idea, and an LLM produces responses that fit each consumer's context. The observed experience of real Korean consumers becomes the starting point for judging an idea.

This lets you evaluate many ideas under the same conditions and examine reactions by gender and age, along with the reasons behind preference and rejection. You narrow down promising candidates before running formal consumer research, and at the same time prepare, in concrete terms, the questions and hypotheses to confirm in the next stage.

Opensurvey Food Diary is not an answer key that tells you the actual purchase outcome of a new product. What Concept Studio offers isn't a prophecy that settles the future, but a reasoned basis, grounded in consumers' real lives, for deciding which idea to validate next. That is precisely the role it's meant to play at the idea-screening stage.

Evaluating ideas on top of data you've built yourself, and a standard for reading that data: this is why Opensurvey Concept Studio is different.