Should Your Business Bet on Great¹⁰⁰⁰ Grandma's Taste Using Genetic Data?

Picture your great¹⁰⁰⁰ grandma crouched by a fire pit 25,000 years ago, deciding whether to eat unfamiliar berries or face starvation. She braves the bitterness, survives, and passes her taste-sensing genes through generations, eventually reaching you. Fast forward to today: you’re ordering an extra-dark roast at Starbucks while your friend frowns over your “bitter” choice. Little do they know, your ancient ancestor might still be calling the shots.

Now here’s the twist: major genetic testing companies have collected DNA from 30+ million people, including data that reveals the ancestors’ taste legacy in unprecedented detail. Companies can potentially benefit from this genetic treasure. But should they? When does betting on ancient taste make business sense? How can marketers decipher these ancient ties and utilize them in their decision making?

In a recent Journal of Marketing Research study, authors Remi Daviet and Gideon Nave analyzed genetic and survey data from 182,212 UK adults, examining 1.5 million genetic variations across seven taste dimensions (bitter, fatty, salty, savory, sour, spicy, and sweet). Their study provides the first large-scale empirical assessment of how genetic information performs against traditional demographic, behavioral, and consumption data in real-world marketing applications.

The results from Daviet and Nave’s study are remarkably promising: genetic data can predict 10.9% to 12.5% of taste preferences, which is meaningful for business decisions. Genetic data shines brightest for uncommon tastes that don’t appear in consumption data, delivering 97% to 233% improvements over traditional methods for flavors like spicy, sour, and bitter. Even familiar tastes saw gains ranging from 28% to 68%.

Genetic data boosts the prediction accuracy of what customers will crave before they know it themselves, giving companies a first-mover advantage in untapped preferences.

Implications in Different Contexts

Food/Beverage Companies: Target customers before they discover niche tastes, especially for products with uncommon flavor profiles.
Healthcare/Pharma: Develop better-tasting formulations for genetically bitter-averse patients to improve medication adherence.
Meal Kit Services: Use genetic screening to curate boxes that match individual taste predispositions, reducing returns and waste.
Government Agencies: Design nutrition programs that align with genetic predispositions rather than fighting against them.

To explore the real-world implications of this research, we interviewed both authors about the practical questions their findings raise. Our conversation moved from research motivations and surprising discoveries to business cases and implementation strategies, before examining broader industry opportunities and future evolution.

Q: Was there any specific moment, observation, or personal experience that made you think, “we need to research this?” Was doing a genetic test the inspiration?

Dr. Nave: It was just the right time for this. There is a lot of genetic data that was never available before, and research from twin studies shows many behaviors are heritable and genetics should be informative of them. Although there were a few commercial applications, it’s unclear when managers should use this data. We wanted to look for the most basic input to this process, which is how predictive genetic data is relative to other variables. Lastly, as academic researchers, we chose nutrition and diet as our focus because this research can potentially improve people’s lives and contribute to social benefit.

Dr. Daviet: I did genetic testing because I was curious. I actually did it in Europe because they have better consumer protection for genetic data. We examined food taste because it’s one of the characteristics that is heavily heritable and relevant. We know that taste preferences are a very strong predictor of consumption. That was a good case study, demonstrating that genetics has an effect and is relevant to predicting consumption.

Q: Were there any surprising or unexpected findings in your study that challenged your initial assumptions? How did the research evolve from the surprising findings?

Dr. Daviet: We know from past research that genetics is predictive of most behavior to some extent. We were unsure whether genetics would offer predictive value beyond other factors, such as sociodemographic background or consumption patterns. My prediction was that it would add some predictive power to a bit of everything, but that was not the case. There are others where it adds a lot of predictive power, such as tastes like bitter, spicy, or sour, which are not often consumed in the local British diet.

Dr. Nave: For many tastes, we know that there are genetically programmed sensitivities because of known genes. For example, there is a receptor in the tongue that senses spiciness. To our surprise, genes that are known to be related to sensitivity to these tastes do not have a strong effect on preferences. Most of the genetic variants that are predictive cannot be directly linked to a known biological mechanism.

Dr. Daviet: There is a specific gene that can predict how people are sensitive to sourness, whether they can detect sourness in a sample. We were expecting that this would predict well if people like sour or not, but actually not. Instead, the liking is a lot of tiny effects across the genome that accumulate to create the overall taste preference, which is very complex.

Q: Suppose you were advising a Fortune 500 CEO who’s skeptical about investing in genetic marketing. What would be your elevator pitch to convince them this isn’t just academic curiosity but a real business opportunity?

Dr. Daviet: They don’t have to invest in marketing, and they can just let the competitor do it and gain a competitive advantage if they prefer. One of the strong advantages of genetics is its ability to identify patterns not revealed in past purchase data. This can help you identify new markets where there is no data, as they are unexplored and lack existing products. It can help you personalize based on different segments, something that traditional data might miss because either there is no data about it or it’s at an aggregate level.

Dr. Nave: Imagine you know what a consumer will need or will love before they even buy it—before they realize it themselves. One example is male balding patterns. This tendency is genetic so that you can predict it from birth. Knowing this allows you to build your brand image among potential customers before they become actual customers. Often, we only reveal certain traits after a while, and having first access is a significant competitive advantage.

Q: What are the most realistic applications of your findings? For example, if I’m launching a new energy drink, can you walk us through a simple, nontechnical roadmap? What’s the step-by-step genetic marketing playbook?

Dr. Nave: Imagine your energy drink has several flavors: bitter coffee, sweet strawberry, and sour lemon. These tastes are determined by people’s genetic profile, not just demographics. You could partner with a company like Ancestry.com to market to people with a certain flavor preference, without needing to collect the genetic data yourself. The key factor is that the data is very sensitive, and people may react very negatively to its use without their consent. The playbook will be used as carefully as possible, serving as a tool for segmentation and targeting.

Dr. Daviet: Let’s say you want to do a personalized drink, and you can identify key genetic traits such as caffeine metabolism, taste preference, health consciousness, and lifestyle without even having access to the data. You can see how these traits correlate in the genetic data and then tailor your product offering to different profiles and ask genetic companies to do personalized recommendations.

Dr. Nave: Some conditions, like having allergies to certain things or not being able to metabolize certain things, do have a strong genetic signal. Specific products, like lactose-free or alcohol-free versions, sometimes address these needs. There could be small segments that reveal these needs through genetic data.

Q: Beyond taste preferences, what other consumer behaviors have strong genetic components that non-food/health industries should pay attention to? Which industry do you think is missing the biggest genetic marketing opportunity right now?

Dr. Daviet: Behavioral genetics predicts everything to some extent. We can consider experiential services, as well as cultural services such as travel and entertainment. If you know someone’s ancestry background, you can tailor your marketing efforts to explore their cultural heritage. Based on genetics, someone might discover they have Latin American ancestry they didn’t know of and start exploring that. You can extend to pretty much anything—lifestyle, work.

Dr. Nave: Basically, everything is heritable except for the language you speak and the religion you practice. Even aspects such as your likelihood of divorce can be genetically influenced to some extent, as they correlate with specific genetic traits. There could be helpful signals everywhere. The question is when it’s stronger, when it’s not predictable from other data. That’s where genetics comes into play. Beauty and educational attainment have potential, but they’re not limited to these.

Q: Please paint us a picture: How do you see genetic marketing evolving over the next 10 years?

Dr. Daviet: Epigenetics might be easier. Epigenetics looks at how molecules attach to DNA and change gene expression, which evolves throughout life and provides a lot of additional information. Without the need for sampling one million people, and because it evolves over life, it’s more accurate. Currently, some companies are working in that field, and what’s trendy is biological age. Maybe you’re 25, but biologically, are you closer to 30 or 20? I could see an opportunity there because it’s more accessible, informative, and growing. Since it’s less complicated to gain insight from, it might be more sustainable on the business side, too.

Our conversation revealed that genetics work best for “hidden” preferences not shown in purchase data, and surprisingly, the authors noted that “basically everything is heritable except language and religion,” which opens up endless possibilities.

However, this raises critical questions: If genetic data can have such promising predictive power, where do we draw the ethical lines? For a comprehensive framework on the promise and perils of genetic marketing, read Dr. Daviet, Dr. Nave, and Dr. Wind’s essential guide, “Genetic Data: Potential Uses and Misuses in Marketing.”