Inside the Future of Food Innovation: A Conversation with a Leading Beverage Market Strategist
Introduction: Meeting the Strategist Shaping Tomorrow's Beverage Aisle
Dr. Priya Venkataraman has spent nearly two decades at the intersection of consumer science and food and beverage innovation. As a former Global Consumer Insights Director at a major multinational FMCG company and now an independent strategic advisor to emerging food and beverage brands, she has led research programs spanning functional beverages, plant-based dairy alternatives, and premium spirits across markets in North America, Europe, and Asia-Pacific. We sat down with Dr. Venkataraman to discuss how market research is — and isn't — keeping pace with one of the most dynamic sectors in global commerce.
Setting the Scene: The State of Food and Beverage Market Research
The food and beverage industry is often described as both mature and intensely innovative. How do you reconcile those two characterizations from a research perspective?
It's a genuinely fascinating tension to work within. The global food and beverage market is enormous — valued at roughly $8.9 trillion in 2023 — and much of it is dominated by products and categories that have been stable for generations. Coca-Cola, Heinz ketchup, Kraft cheese — these are not products in urgent need of market rediscovery. The research serving those businesses is about optimization: pricing architecture, pack size elasticity, channel-specific promotion response. Important work, but not groundbreaking.
Where I find the real intellectual excitement — and the most consequential research challenges — is in the disruptive edge of the market. Plant-based beverages growing at a CAGR of 12.4% through 2028. Functional drinks with adaptogens and nootropics moving from health food stores to mainstream retail. RTD (ready-to-drink) cocktails reshaping the entire off-premise alcohol category. These are segments where consumer behavior is genuinely novel, where our existing research frameworks were built for a different world, and where getting the insights wrong can mean a brand burns through $50 million in launch investment chasing a consumer that doesn't exist the way we imagined them.
Can you give us a concrete example of research frameworks breaking down in this new environment?
Absolutely. The plant-based meat and dairy category is the most instructive case study I can point to. Around 2019 and 2020, almost every major CPG company and investor was receiving consumer research showing extraordinary levels of trial intent for plant-based products. Survey after survey indicated that large proportions of meat-eating consumers were willing to substitute plant-based proteins regularly.
What actually happened? Trial rates were reasonable, but repeat purchase rates collapsed. The research had captured a moment of aspirational self-identity — people telling us who they wanted to be — rather than an accurate prediction of habitual behavior. Standard purchase intent scales, even when corrected with conventional normative adjustments, were not calibrated for a category where the gap between environmental aspiration and taste-driven daily decision-making is this wide.
"The lesson for every researcher working in food and beverage innovation is that your job is not to measure what consumers say they'll do — it's to understand the psychological distance between their stated intentions and the moment they're standing in front of a refrigerated shelf at 6:30pm on a Tuesday."
On Research Methodology: What Works in Food and Beverage?
What methodological approaches do you trust most when researching genuinely new food and beverage concepts?
In-home usage tests — IHUTs — remain the gold standard for behavioral validation, and I don't think that's going to change. There is simply no substitute for getting your product into the hands of real consumers in their real consumption contexts, with all the competing options in their pantry and refrigerator present, and tracking actual usage behavior over a sustained period. Platforms like Curion and FMCG research specialists have sophisticated IHUT capabilities that generate far more reliable predictive data than any in-facility or online concept test.
That said, I've become a genuine believer in implicit association testing as a complement to explicit attitudinal research in this category. Food choice is deeply emotional, habitual, and identity-laden in ways that people cannot — and often will not — articulate accurately in a survey. When I'm trying to understand what a brand like an oat milk company really means to a consumer emotionally, implicit measures give me a window that explicit brand equity trackers simply don't open.
I'm also paying close attention to passive behavioral data integration. Loyalty card data, recipe app engagement, food delivery platform ordering patterns — these behavioral streams, when analyzed alongside primary research, create a much more textured and reliable picture of the consumer than either data type alone.
How has AI changed your research toolkit in food and beverages specifically?
The most transformative application I've seen is in unstructured data analysis — specifically, qualitative synthesis at scale. We used to face a real constraint: rich qualitative insight from focus groups and ethnographic interviews was expensive to generate and slow to analyze, while large-scale quantitative data was fast but shallow. AI-powered analysis tools are beginning to close that gap meaningfully.
I recently worked on a flavor trend forecasting project where we used NLP models trained on food media content, recipe platform data, restaurant menu databases, and social media to identify emerging flavor and ingredient signals twelve to eighteen months ahead of mainstream adoption. The model flagged yuzu, black sesame, and calamansi as high-momentum flavors in the Western premium beverage market well before they appeared in any of the conventional trend reports. That kind of early signal detection has real commercial value for brands trying to innovate ahead of the curve.
Looking Forward: The Research Priorities That Will Define the Next Five Years
What research priorities should food and beverage companies be investing in right now?
Three things, in my view. First, sustainability preference research that's actually predictive — not attitudinal surveys about environmental concern, but rigorously designed choice experiments and behavioral studies that tell you at what price premium and what packaging trade-off the sustainability message actually moves purchase behavior for your specific consumer segment.
Second, cross-cultural adaptation research for global innovation pipelines. The assumption that a successful beverage concept in Western markets can be translated globally with minor modification has been disproven so many times that I'm genuinely puzzled it persists. Flavor profile adaptation, occasion-based consumption mapping, and packaging semiotics all require dedicated local research, not assumptions.
Third, longitudinal consumption tracking. The food and beverage industry runs too much of its consumer research on cross-sectional designs. Our understanding of how dietary and beverage preferences evolve across life stages, health events, economic cycles, and cultural moments is remarkably thin. Companies that invest in genuine panel-based longitudinal research will develop durable competitive advantages in innovation targeting.
The food and beverage industry feeds the world, in the most literal sense. The research that helps brands understand what consumers truly need — nutritionally, emotionally, culturally — is not just commercially important. It matters in a deeper way than most market research does. That's what keeps me in this work.