Two senior staffers from a commodity board had just landed in our office with a familiar problem: a thick binder of last year’s “definitive” market report, a trade mission in six weeks, and a blunt question from their chair: What’s actually changed in our priority markets since this was published?
Everyone looked at the PDF. Then at each other.
Flights were booked. Budgets were tight. The fieldwork that fed that report had been conducted nine months prior, in two cities, with an overworked local panel. Crude price moves, retailer resets, and new import rules since then? Not in the deck. Meanwhile, the board needed answers—who to target, which claims would land, which pack and price would stick, how to brief buyers with confidence.
That’s the moment synthetic research earns its keep.
What synthetic research is (in plain English) Think of AI‑powered synthetic research as a high‑fidelity flight simulator for markets. Instead of waiting months to ask a small group of people a small set of questions, we build digital twins of the populations you care about—consumers, buyers, importers, chefs, retailers—in any city or country.
These synthetic cohorts are calibrated using official statistics, trade flows, retail and foodservice signals, past studies, and cultural cues. When you ask them questions about claims, pricing, pack sizes, channels, you get answers that,according to deep research conducted by Stanford University, Cambridge University and others, show no statistically significant difference from in‑market samples on key measures.
The difference is speed and access: the panel is always on. You can ask questions 24/7, 365 days a year, and watch the model update as new data hits the world.
Why commodity groups are turning to it now Export markets don’t wait for fieldwork.
Commodity groups and boards are expected to make decisions on tighter timelines with higher stakes. Yet traditional research in many markets is slow, expensive, and—let’s be honest—hard to verify. Panels can be thin. Translation can mangle nuance. By the time the report lands, prices, policies, and competitors have moved on.
Synthetic research doesn’t replace local judgment or relationships, but it does change the tempo. It turns “once-a-year insights” into always-on market intelligence that helps you choose targets, shape messaging, and prep trade teams with current answers instead of last season’s assumptions.
From binder to buyer meeting in a week
Back to that boardroom. The commodity group’s priority was Southeast Asia. In 72 hours, we calibrated three digital cohorts: urban chefs, foodservice procurement managers, and health-conscious diners in two cities. Then we ran focused tests:
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Which claims actually moved chef interest: menu versatility, nutrition density, or sustainability? (Answer: nutrition plus versatility beat standalone sustainability; sustainability still mattered, but only with concrete proof points.)
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Where price resistance kicked in versus local alternatives in horeca and retail.
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Which pack sizes reduced waste in kitchens and fit distributor constraints.
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Which objections buyers were most likely to raise next month—and which evidence would neutralize them.
By day five, the team had a distributor-facing mini deck, a buyer FAQ grounded in data, and two message tracks localized for each city. Week two, they validated with three partner chefs to ensure cultural fit and sharpen recipes. The trade mission didn’t just happen; it landed.
What makes synthetic research credible?
Calibration. We don’t let an LLM “guess” the market. We:
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Ingest and harmonize data you already trust: census and household budgets, FAOSTAT/Comtrade flows, retail scanner data, menu scraping, price and pack audits, and prior studies.
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Build synthetic cohorts that match real-world distributions: demographics, income, channel usage, dietary patterns, willingness to pay, claim preferences.
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Validate against anchors: known benchmarks, recent fieldwork, observed purchase trends. Where data is thin, we say so and set confidence bands.
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Keep humans in the loop: local expert review catches cultural misses, compliance checks keep claims market-safe.
For commodity boards, that means you get speed without hand‑waving. When we say “chefs in London, UK prefer X over Y,” we can show you, the calibration steps, and the tradeoffs.
What you can do with always‑on market intelligence
A few high‑impact use cases we deliver for commodity groups and trade associations:
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Market selection and prioritization: Compare five markets in days, not quarters. Rank by fit, margins, and message resonance.
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Message and claims testing: Nutrition, origin, sustainability, animal welfare, regenerative—see what actually shifts intent, and where it backfires.
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Price and pack architecture: Identify acceptable premiums, waste‑reducing formats, and channel‑specific SKUs.
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Channel strategy: Retail vs. foodservice sequencing, distributor value propositions, e‑commerce viability.
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Trade mission prep: Build live dossiers, buyer FAQs, and objection handling for your delegation in a week.
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Policy and advocacy: Quantify economic contribution and sustainability outcomes with evidence buyers and policymakers can cite.
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Crisis monitoring: Track misinformation or emerging narratives before they snowball.
How it works with 6 Seeds
We keep it simple, using our 3R Wayfinder Method.
Reveal
We map the market: who buys, how they buy, what they pay, and what they believe. We ingest your data and external sources and build the synthetic cohorts.
Reimagine
We pressure-test strategy. Claims, creative, channel sequencing, pack and price—rapidly tested, ranked, and localized.
Realize
We turn insight into action. Trade decks, message toolkits, buyer FAQs, and a standing “ask-the-market” pipeline your team can use anytime.
Where synthetic research excels—and where it doesn’t
Excels at:
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Speed, breadth, and iteration. Test five markets in parallel. Update weekly.
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Comparability. One method across countries, so you can compare apples to apples.
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Cost discipline. More learning for the same budget; save fieldwork for validation.
Use classic fieldwork for:
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Sensory and in‑kitchen trials.
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Deep ethnography and creative development.
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Legal and labeling verification with local counsel.
The point isn’t to replace people on the ground. It’s to send them in sharper, sooner, and with fewer blind spots.
Why 6 Seeds, food and agriculture is our whole map, not a side street. We’ve pioneered synthetic research programs tailored to commodity groups, combining domain‑tuned AI, rigorous calibration, and practical trade experience.
Andreas Duess, our CEO, recently delivered a keynote on this approach at the USAEDC conference in Washington, D.C., and we’ve been invited to brief several commodity boards in the last three months. That matters because this isn’t a lab exercise - it’s already changing how export decisions get made.
Common questions we get from boards
Is this compliant with privacy laws?
Yes. We work with aggregated, permissioned, and public data; no personally identifiable information.
Can synthetic outputs be trusted for board decisions?
On key measures—claim resonance, price bands, channel preferences—well‑calibrated synthetic cohorts have matched in‑market samples within normal confidence intervals in our validations. We document confidence levels and recommend targeted field validation where needed.
How fast can we get started?
Most boards see their first market answers in 4-8 weeks. Trade mission prep sprints can be done in two to three week; always‑on programs stand up in 4–8 weeks.
What does success look like?
Sharper market selection, higher hit rates in buyer meetings, fewer misfires on claims and pack, and a team that stops waiting on PDFs and starts asking the market in real time.
A quick checklist to get moving
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Pick two priority markets and three questions per market.
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Gather your existing research, trade insights, and price/pack lists.
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Decide where you want to validate in-market after we learn synthetically.
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Then let’s fly the simulator before we fly the plane.
Book a 30‑minute scoping call, and we’ll show you exactly how an always‑on, AI‑powered synthetic research program would work for your commodity group.
We can share anonymized examples, set expectations, and outline where to validate locally. And if you need to brief your board, we’ve been doing that a lot lately—happy to tailor a session.