食品・飲料技術市場調査

Digital Tech は、食品および飲料技術市場調査を通じて、新たな顧客ロイヤルティと収益性の機会を提示します。

Apps, tools, mobile payments and smartphones are revolutionizing how consumers eat.  When examining the impact of technology on the food industry, there is the business perspective as well as the consumer view.

Food Beverage Technology Market Research Food Tech: How Category Leaders Build Advantage

Food tech investment has shifted from speculative bets to disciplined category plays. The winners are running sharper research.

Capital that once chased plant-based protein launches and cold-pressed startups now flows toward platforms with defensible unit economics: precision fermentation, AI-driven flavor optimization, automated micro-fulfillment for grocery, and shelf-life extension chemistry. The shift has raised the stakes for Food Beverage Technology Market Research Food Tech programs. Decisions on indication prioritization, channel sequencing, and ingredient sourcing now demand evidence that holds up in front of an investment committee.

The leaders separating themselves are not buying more data. They are designing research that connects sensory science, retailer economics, and operator workflows into a single decision instrument.

Why Food Tech Demands a Different Research Architecture

Most consumer categories can be sized through syndicated panel data and concept testing. Food tech cannot. A precision-fermented dairy protein launches into a market governed by GRAS regulatory pathways, dairy-aisle planogram politics, foodservice operator specs, and a consumer who reads the back panel before the front. Each gate has its own decision-maker and its own evidence standard.

The conventional approach treats these as sequential studies. The better approach runs them as a connected program. SIS International Research has found that food tech ventures clearing the eighteen-month commercialization window almost always combine descriptive analysis panel calibration with retailer category management interviews in the same engagement, rather than testing product and channel separately. Sensory parity scores read differently when overlaid on a retailer’s private label taste parity benchmark and shelf space allocation logic.

This is the architecture question VPs of Innovation and Chief Growth Officers should be asking. Not “what does the consumer think,” but “which evidence chain unlocks which gate.”

The Sensory-to-Shelf Evidence Chain

Food tech products live or die on the gap between technological achievement and consumer hedonic acceptance. A cell-cultured chicken analog can match poultry on protein structure and miss on JAR (just-about-right) scales for juiciness by enough to kill repeat purchase. A functional beverage can win on ingredient story and lose on temporal dominance of sensations when the adaptogen note lingers past swallow.

Category leaders close this gap with a layered protocol:

• Triangle test discrimination against the incumbent benchmark to confirm whether the consumer can detect a difference at all
• QDA (quantitative descriptive analysis) with a calibrated panel to map the specific attribute deltas
• CATA (check-all-that-apply) and penalty analysis with target consumers to weight which deltas drive rejection
• Accelerated shelf-life testing (ASLT) layered with sensory drift tracking, because food tech ingredients often degrade on different curves than legacy formulations

Companies including Perfect Day, Eat Just, and Motif FoodWorks have publicly described iteration cycles built on this kind of layered sensory work. The discipline shows up in their retailer pitches as concrete attribute parity claims rather than narrative.

Foodservice and Retail Operator Intelligence

The fastest path to scale for most food tech platforms runs through foodservice operators and retail category buyers, not direct-to-consumer. These buyers ask different questions: throughput in a 28-day kitchen cycle, case fill rates, slotting fees against velocity projections, and whether the SKU cannibalizes a higher-margin incumbent.

B2B expert interviews with category managers at chains such as Kroger, Sysco, Compass Group, and US Foods produce intelligence that consumer panels cannot. In structured expert interviews SIS has conducted with category buyers and foodservice procurement leads across North America and Western Europe, the most consistent rejection driver for food tech entrants is not price or taste but operational fit: case configuration, prep time, and back-of-house training load. Pricing comes fourth or fifth.

This finding inverts the assumption underlying most food tech go-to-market plans. The pitch deck optimizes for cost-down narrative. The buyer is solving for operational simplicity.

Where Technology Market Research Meets Food Science

Food tech is, structurally, a vertical SaaS problem dressed as a CPG problem. The platforms that scale (Hazel Technologies in produce shelf life, Apeel Sciences in coatings, Afresh in grocery inventory AI, NotCo in formulation AI) sell into food companies and retailers as enterprise technology. Their research needs blend product-led growth metrics, net revenue retention, and customer acquisition cost payback with sensory and regulatory evidence.

This dual nature is where most market research falls short. Pure tech research firms miss the sensory and regulatory layers. Pure food and beverage firms miss the SaaS economics. The work has to span both.

Source: SIS International Research

The Private Label and Sober-Curious Inflection

Two structural shifts are reshaping where food tech investment pays off. Private label has moved from value tier to innovation tier at chains including Aldi, Trader Joe’s, Whole Foods 365, and Costco Kirkland. These programs now license food tech ingredients directly, compressing the branded incumbent’s window. Food tech platforms that built around branded partnerships are pivoting toward private label co-development, and the research signal they need is different: clean label consumer perception studies, retailer-specific sensory benchmarking, and concept-product fit testing against private label rather than national brand reference points.

The sober-curious shift has opened a parallel category in functional beverages, adaptogenic mocktails, and non-alcoholic spirits. SIS International’s proprietary research in beverage innovation indicates that the strongest predictor of repeat purchase in non-alcoholic spirits is not flavor matching to the alcoholic counterpart but ritual completeness: glassware, garnish, and serving occasion fidelity. Brands building research programs around taste alone are missing the variable that drives the category.

The SIS Food Tech Research Stack

SIS International applies a layered methodology specifically designed for food tech: descriptive analysis panel calibration, central location tests with hedonic and JAR scales, ethnographic kitchen observation in foodservice settings, B2B expert interviews with category buyers and procurement leads, and competitive intelligence on regulatory pathways including GRAS, novel food authorization in the EU, and FSSAI clearances in India. The stack is built to answer one question across every gate: where does this platform actually win.

For a VP weighing a food tech investment or launch, the question is not whether to commission research. It is whether the research program connects sensory, retailer, operator, and platform economics into a single evidence chain. Food Beverage Technology Market Research Food Tech done as separate studies produces decks. Done as a connected program, it produces decisions that hold up in front of a board.

SISインターナショナルについて

SISインターナショナル 定量的、定性的、戦略的な調査を提供します。意思決定のためのデータ、ツール、戦略、レポート、洞察を提供します。また、インタビュー、アンケート、フォーカス グループ、その他の市場調査方法やアプローチも実施します。 お問い合わせ 次の市場調査プロジェクトにご利用ください。